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Seismic Vulnerability and Capacity Assessment at Ward Level

A Case Study of Ward No. 20, Lalitpur Sub - Metropolitan City, Nepal

Ganesh Kumar Jimee March, 2006

Seismic Vulnerability and Capacity Assessment at Ward Level

A Case Study of Ward No. 20, Lalitpur Sub - Metropolitan City, Nepal

By

Ganesh Kumar Jimee Thesis submitted to the International Institute for Geo-information Science and Earth Observation in partial fulfilment of the requirements for the degree of Master of Science in Geo-information Science and Earth Observation, Specialisation: Natural Hazard Studies Supervisors: Dr. C. J van Westen (First Supervisor) Dr. M.K. Mc Call (Second Supervisor) Thesis Assessment Board Prof. Dr. F.D. van der Meer (Chair) Prof. Dr. V. Jetten (External) Dr. C. J van Westen (First Supervisor) Ms. Veronica Botero (Member) Observer: Dr. P.M. van Dijk (Programme Director)

INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION ENSCHEDE, THE NETHERLANDS

Disclaimer This document describes work undertaken as part of a programme of study at the International Institute for Geo-information Science and Earth Observation. All views and opinions expressed therein remain the sole responsibility of the author, and do not necessarily represent those of the institute. Data used in the thesis will not be used for publishing without written permission of the thesis supervisor.

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Abstract

This study is an effort to develop a method which can be adopted by municipal authorities in order to assess the vulnerability and level of capacity of local people. It included estimating the building collapse probability and casualties for certain earthquake scenarios, and measuring the capacity of local people to cope with earthquake risk in ward 20 of Lalitpur Sub-Metropolitan City, Nepal.

The socio-economic information was collected through a household survey for a sample of 5% of the total 3,329 building floors. Population density was calculated for the sampled building floors according to space uses for different time periods of the day, and based on these sample calculations the population for each building and of the entire ward was estimated. Individual buildings were separated in the footprint map by visual observation and relevant attributes were recorded for the all buildings in the ward.

Building damage and collapse probability were estimated for individual buildings considering their conditions in addition to building height, construction types and earthquake intensity using an existing damage matrix prepared by JICA and NSET. The estimations were made for different possible earthquake scenarios defined by previous researches. In the worst case scenario, due to an intensity IX earthquake, 26% of the total of 988 buildings were estimated with high probability (>0.5) of collapse. In intensity VIII and VII earthquakes most of the buildings were estimated with medium (0.2-0.5) and low (<0.2) probability of collapse.

An empirical relation between collapse probability of buildings and population distribution, established by HAZUS, was used to estimate the casualties. Estimations were made for different severity levels for individual buildings due to different earthquake scenarios occurring in different periods of the day i.e. morning, day, evening and night. The study estimated 1,602 and 401 casualties respectively for severity 1 (minor injury) and 4(dead) in ward 20 due to an intensity IX earthquake occurring at daytime, and 1607 and 402 for the night time. Proportionally more casualties were estimated in non-residential buildings during daytime and in residential at night. Moreover, proportionally very high casualty rates were estimated in school class rooms during daytime and school hostels at night.

The level of public awareness, preparedness and capacity were analyzed from the information received by interviewing local people. The responses were analyzed and grouped in three levels i.e. high, medium and low. From the analysis it was concluded that the respondents have a medium level of awareness but a very low level of capacity. The low level of capacity was because of the low level of preparedness, and the low level of preparedness due to the ineffectiveness of awareness. That is why raising awareness directed to concrete preparedness measures would be the crucial very first step for the earthquake risk reduction process. Therefore this study has recommended to increase the efforts in raising effective awareness addressing each sector of the local communities i.e. students, teachers, housewives, masons, engineers, clubs etc. to improve public preparedness and ultimately the capacity to cope with earthquake risk.

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Acknowledgements

First of all I express my deep gratitude to my first supervisor Dr. Cees van Westen for the thought provoking suggestions and constant support as well as encouragement, all of which has contributed significantly to this work. I also express gratitude to my second supervisor Dr. MK Mc Call for the encouragement and invaluable suggestions.

Similarly I would like to express my gratitude to Mr. Shiva Bahadur Pradhanang, President, Mr. Amod Mani Dixit, General Secretary and Mr. Varun Prasad Shrestha, Chief Technical Advisor of NSET for their encouragement and guidance. I am very grateful to S. N. Shrestha jee and Basyal Jee for their help and suggestions throughout the study. Likewise I also would like to thank other friends from NSET for their support in different aspect.

Also, I would like to express my gratitude to Dr. P. M. van Dijk, for his contributions and support on many research from the very beginning of my study at ITC.

Similarly I would like to thank to Drs. Nannete Kingma for being always positive and suggestive during the study at ITC. And also, my respectful gratitude goes to Dr. Luc Boerboom and Dr. Erik De Man for encouragement and suggestion.

The endless suggestions and comments of Ms. Veronica Botero (PhD student) lead me easily through many obstacles, I am really thankful to her.

Friends from LSMC, Suman, Niyam, Ram and Chhatra are highly appreciated for their help. And I would like to thank students, Shovendra et. al. from Pulchowk Engineering Institute and Ramesh Thapaliya from UPLA, ITC for their sincere help and cooperation during the field work.

All my class fellows - especially Zul, Manuel, Sheila, Kung, Lee, Edgar, Hendro, Tomy, Nata and Samuel, who were always helpful and friendly throughout the course and made my stay memorable at ITC; and the first six during the field study in Italy, will never escape from my mind.

My sincere thanks also go to all ITC staff members for their help in one way or the other.

And most importantly, I would like to express my deepest gratitude to my parents and relatives, for their endless support and love.

Lastly but not the least, I wish especially thank to my wife Alungma-Bimala, for being so patient and encouraging life partner; she never let me to feel lonely though we were almost at the two poles of the globe.

Ganesh Kumar Jimee

ITC, Enschede

The Netherlands

March 2006

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Table of contents

1 INTRODUCTION.......................................................................................................................1

1.1. BACKGROUND .............................................................................................................................1 1.2. RESEARCH PROBLEM...................................................................................................................1 1.3. CONCEPTUAL FRAME WORK .........................................................................................................2 1.4. RESEARCH OBJECTIVES...............................................................................................................3 1.5. RESEARCH QUESTIONS................................................................................................................3 1.6. RESEARCH SEQUENCE AND COMPONENTS ....................................................................................3

1.6.1. Pre-fieldwork .............................................................................................................4 1.6.2. Fieldwork...................................................................................................................4 1.6.3. Post fieldwork............................................................................................................6

1.7. STUDY AREA ...............................................................................................................................7 1.7.1. Location ....................................................................................................................7 1.7.2. History and culture....................................................................................................8 1.7.3. Population .................................................................................................................8 1.7.4. Urbanization..............................................................................................................8

1.8. LIMITATIONS OF THE STUDY .........................................................................................................9 1.9. THESIS OUTLINE ..........................................................................................................................9

2 EARTHQUAKE VULNERABILITY AND RISK REDUCTION IN NEPAL: A LITERATURE REVIEW 10

2.1. EARTHQUAKES IN NEPAL ...........................................................................................................10 2.2. EARTHQUAKE LOSS ESTIMATION IN KATHMANDU VALLEY .............................................................11 2.3. DISASTER MANAGEMENT SITUATION IN NEPAL.............................................................................13 2.4. COMMUNITY BASED DISASTER MANAGEMENT IN KATHMANDU VALLEY ..........................................14

2.4.1. Involvement of organizations for awareness raising activities in Ward 20 Lalitpur.18 2.5. PREVIOUS WORKS WITHIN THE SLARIM PROJECT ......................................................................19

3 CHARACTERIZATION OF WARD 20 ....................................................................................21

3.1. INTRODUCTION ..........................................................................................................................21 3.2. PHYSICAL DATABASE .................................................................................................................21

3.2.1. Digital data sources ................................................................................................21 3.2.2. Building footprints ...................................................................................................22 3.2.3. Building inventory....................................................................................................22

3.2.3.1. Space uses............................................................................................................... 23 3.2.3.2. Age and structure of buildings .................................................................................. 24 3.2.3.3. Building heights ........................................................................................................ 25 3.2.3.4. Building geometry..................................................................................................... 25 3.2.3.5. Building construction materials................................................................................. 25 3.2.3.6. Building classification ............................................................................................... 26 3.2.3.7. Building condition ..................................................................................................... 27 3.2.3.8. Attached buildings and height coincidence .............................................................. 27

3.2.4. Road infrastructure and utilities ..............................................................................28 3.3. POPULATION DATA.....................................................................................................................28

3.3.1. Spatiotemporal distribution of population................................................................29 3.3.1.1. Spatial distribution of population............................................................................... 29 3.3.1.2. Temporal distribution of population .......................................................................... 30

3.3.2. Socio-economic characteristics ..............................................................................32 3.3.2.1. Age and gender composition.................................................................................... 32

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3.3.2.2. Ethnic groups and language..................................................................................... 32 3.3.2.3. Religion..................................................................................................................... 33 3.3.2.4. Education.................................................................................................................. 34 3.3.2.5. Economy................................................................................................................... 34 3.3.2.6. Travel between wards .............................................................................................. 35

3.4. SUMMARY .................................................................................................................................36

4 BUILDING VULNERABILITY ASSESSMENT .......................................................................37

4.1. INTRODUCTION ..........................................................................................................................37 4.2. BUILDING DAMAGE MATRIX .........................................................................................................37 4.3. MULTI-CRITERIA ANALYSIS OF OTHER BUILDING PARAMETERS......................................................38 4.4. BUILDING VULNERABILITY...........................................................................................................40 4.5. EARTHQUAKE SCENARIOS ..........................................................................................................40

4.5.1. Building loss estimation ..........................................................................................41 4.5.2. Building damage by types.......................................................................................44

4.6. CONCLUSION.............................................................................................................................44

5 CASUALTY ESTIMATION......................................................................................................46

5.1. INTRODUCTION ..........................................................................................................................46 5.2. HUMAN CASUALTIES DUE TO EARTHQUAKE..................................................................................46 5.3. CASUALTY ESTIMATION..............................................................................................................46 5.4. CASUALTIES DUE TO DIFFERENT EARTHQUAKE SCENARIOS..........................................................47 5.5. CASUALTIES BY BUILDING TYPES ................................................................................................51 5.6. CASUALTIES BY THE USE OF BUILDINGS ......................................................................................52 5.7. SOCIO-ECONOMIC FACTORS OF POPULATION VULNERABILITY.......................................................54

5.7.1. Age and gender ......................................................................................................54 5.7.2. Economy and activities ...........................................................................................54 5.7.3. Ethnicity and religion...............................................................................................54 5.7.4. Education and awareness ......................................................................................55 5.7.5. Provision of infrastructures .....................................................................................55

5.8. CONCLUSIONS...........................................................................................................................55

6 MEASURING PUBLIC AWARENESS, PREPAREDNESS AND CAPACITY ........................56

6.1. INTRODUCTION ..........................................................................................................................56 6.2. EXISTING SITUATION ..................................................................................................................56

6.2.1. Public awareness....................................................................................................56 6.2.1.1. Public knowledge...................................................................................................... 56 6.2.1.2. Information about critical facilities............................................................................. 57

6.2.2. Response how to act during an earthquake ...........................................................58 6.2.3. Risk perception .......................................................................................................59 6.2.4. Earthquake preparedness ......................................................................................61

6.3. DEVELOPMENT OF INDICIES FOR AWARENESS, PREPAREDNESS AND CAPACITY.............................61 6.3.1. Measuring awareness.............................................................................................63 6.3.2. Measuring preparedness ........................................................................................64 6.3.3. Measuring capacity .................................................................................................65

6.4. EXAMPLES FROM THE HOUSEHOLD SURVEY ................................................................................66 6.4.1. Example 1: A respondent from a residential apartment..........................................66 6.4.2. Example 2: A respondent from a school.................................................................67

6.5. CORRELATING THE CAPACITY LEVEL WITH VULNERABILITY ...........................................................69 6.6. CONCLUSION.............................................................................................................................71

7 CONCLUSIONS AND RECOMMENDATIONS ......................................................................72

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7.1. CONCLUSIONS...........................................................................................................................72 7.2. RECOMMENDATIONS..................................................................................................................73

REFERENCES .......................................................................................................................................77

ANNEXES...............................................................................................................................................80

ANNEX I..............................................................................................................................................80 ANNEX II.............................................................................................................................................86 ANNEX III............................................................................................................................................87 ANNEX IV ...........................................................................................................................................90 ANNEX V ............................................................................................................................................92 ANNEX VI ...........................................................................................................................................97

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List of figures

Figure 1-1Conceptual framework of the research...................................................................................2 Figure 1-2 Research sequence and components......................................................................................3 Figure 1-3: Sampled buildings for socioeconomic survey ......................................................................5 Figure 1-4: Location of the study area ....................................................................................................7 Figure 1-5: A view of Durbar Square, Lalitpur.......................................................................................8 Figure 1-6: Population growth and urbanization in Kathmandu Valley ................................................9 Figure 2-1: Shake-table demonstration for public awareness ..............................................................17 Figure 3-1: Building footprints..............................................................................................................22 Figure 3-2: Buildings by space uses ......................................................................................................24 Figure 3-3: Building age and structural types ......................................................................................24 Figure 3-4: Number of floors with the buildings ...................................................................................25 Figure 3-5: Building classification ........................................................................................................26 Figure 3-6: Building conditions.............................................................................................................27 Figure 3-7: Provision of utilities in surveyed households .....................................................................28 Figure 3-8: Temporal distribution of population in residential and non-residential buildings ...........30 Figure 3-9: Overall temporal distribution of population ......................................................................31 Figure 3-10: Age and gender composition of population......................................................................32 Figure 3-11: Population by ethnic groups.............................................................................................33 Figure 3-12: Population by mother tongue ...........................................................................................33 Figure 3-13: Population by religious group..........................................................................................34 Figure 3-14: Population by education level ..........................................................................................34 Figure 3-15: Occupational structure of population ..............................................................................35 Figure 3-16: Database generated during the current study ..................................................................36 Figure 4-1: Building vulnerability considering building condition ......................................................40 Figure 4-2: Building collapse/damage probability for each earthquake scenarios..............................42 Figure 4-3: Building collapse/damage probabilities in intensity IX earthquake ..................................42 Figure 4-4: Building collapse/ damage probability for Mid Nepal earthquake scenario (intensity VIII)................................................................................................................................................................43 Figure 4-5: Building collapse/damage probability for North Bagmati earthquake scenario (intensity VII) .........................................................................................................................................................43 Figure 4-6: Probability of building collapse/damage by their types.....................................................44 Figure 4-7: Building collapse probability according to building characteristics ................................45 Figure 5-1: Casualties due to different earthquake intensities .............................................................48 Figure 5-2: Casualties of severity level 1and 4 due to intensity IX earthquake (assumed) ..................49 Figure 5-3: Casualties of severity level 1 and 4 due to Mid Nepal earthquake scenario (MMI VIII) ..50 Figure 5-4: Casualties of severity level 1 and 4 due to North Bagmati earthquake scenario (MMI VII)................................................................................................................................................................51 Figure 5-5: Probability of casualties by building types ........................................................................52 Figure 5-6: Casualties by the use of buildings due to intensity IX earthquake.....................................53 Figure 6-1 Knowledge about earthquake related matters .....................................................................57 Figure 6-2: Information about the critical facilities .............................................................................58 Figure 6-3: Public knowledge to act during an earthquake on the upper floor of a building ..............58

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Figure 6-4: Means for making light during an earthquake ...................................................................59 Figure 6-5 Argument about the outdoor safe place during an earthquake ...........................................59 Figure 6-6: Public perception about earthquake risk ...........................................................................60 Figure 6-7: Responsibility for the loss due to an earthquake................................................................60 Figure 6-8: Preparedness for the possible earthquake .........................................................................61 Figure 6-9: Some examples from the sampled buildings comparing vulnerability and capacity .........68 Figure 6-10: Casualties due to intensity IX earthquake and level of capacity in sampled building floors ......................................................................................................................................................70 Figure 7-1: Proposed strategy for awareness leading towards preparedness......................................75

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List of tables

Table 1-1: Sampled building floors .........................................................................................................5 Table 2-1: Major earthquakes in Nepalese history ...............................................................................11 Table 3-1: Projection parameters..........................................................................................................21 Table 3-2: Building floors classified by space use.................................................................................23 Table 3-3: Buildings by space uses........................................................................................................23 Table 3-4: Distribution of population by main building uses................................................................30 Table 4-1: Damage probability matrix for different types of building ..................................................38 Table 4-2: Comparison of building parameters ....................................................................................39 Table 4-3: Building collapse/damage probability due to different earthquake scenarios ....................41 Table 5-1: Injury severity levels description .........................................................................................47 Table 5-2: Casualties due to different earthquake intensities ...............................................................48 Table 6-1: Weights for the components of awareness ...........................................................................63 Table 6-2: Summary of awareness index for residential and non-residential respondents ..................64 Table 6-3: Weights for the components of preparedness.......................................................................64 Table 6-4: Summary of preparedness index for residential and non-residential respondents..............65 Table 6-5: Summary of capacity index for residential and non-residential respondents......................65

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List of abbreviation and acronyms

ADPC Asian Disaster Preparedness Centre ADRC Asian Disaster Preparedness Centre ATC Applied Technology Council CARE Cooperation for American Relief Everywhere CBS Central Bureau of Statistics DMG Department of Mines and Geology EPC Emergency Preparedness Canada FEMA Federal Emergency Management Authority GIS Geographic Information System HAZUS Hazards US ICIMOD International Center for Integrated Mountain Development IRCS International Red Cross Society JICA Japan International Cooperation Agency KERMIT Kathmandu Earthquake Risk Mitigation Tool KVERMP Kathmandu Valley Earthquake Risk Management Project LSMC Lalitpur Sub-Metropolitan City LWS Lutheran World Service MMI Modified Mercalli Intensity NHEMATIS Natural Hazards Electronic Map and Assessment Tools NIBS National Institute for Building Science NRCS Nepal Red Cross Society NSET National Society for Earthquake Technology-Nepal PGA Peak Ground Acceleration RADIUS Risk Assessment Tools for Diagnosis of Urban Areas Against Seismic Disasters SLARIM Strengthening Local Authorities for Risk Management TU Tribhuvan University UMN United Mission to Nepal UNDP United Nations Development Program USAID United States Agency for International Development VDC Village Development Committee

SEISMIC VULNERABILITY AND CAPACITY ASSESSMENT AT WARD LEVEL: A CASE STUDY OF WARD 20,

LALITPUR SUB- METROPOLITAN CITY, NEPAL

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1 Introduction

1.1. Background

Nepal, a small Himalayan kingdom, is located on the southern hill-slopes of the Himalayas in-between India in the south, east, west, and China in the north. The surface area of the country is 147,181 Sq. Km. Two- third of the territory, which is mountainous, lies in the northern side and one-third, the plain area, lies in the southern part. Within its 150 km width, Nepal has varied climatic conditions. It has annual snow cover, mountain glaciers and glacial lakes in the north, heavy rainfall, hailstorm and dry spells in the summer in midland and prolonged dry spells with dust wind, hailstorm in the summer and heavy rainfall in the months of June to September in the flat Terai. According to the 2001 census total population of the country is more than 23 million with a growth rate of 2.24% per year. More than 14 percent of the total population lives in urban areas. The country is known as one of the most seismic prone countries of the world. Large-scale earthquakes have repeatedly hit the country. The country's high seismicity is related to the presence of active faults between tectonic plates along the Himalayas, such as the Main Boundary Fault (MBF) and Main Central Thrust (MCT). Among the main reasons for Nepal's high vulnerability to earthquake is the poor construction of public buildings and houses especially in densely populated cities like Kathmandu and Lalitpur. Since the return period of a large-scale earthquake is about 100 years in this region, it is foreseeable that the next large- scale earthquake might occur anytime in the future.

1.2. Research problem

Nepal, as a whole, lies in a high seismically prone zone. Lalitpur Sub-Metropolitan City (LSMC), one of the historical and highly populated cities of the country, located in Kathmandu Valley, geologically on lacustrine sediments, which may amplify seismic acceleration considerably. According to previous studies the probability of human casualties, death and damage of buildings and urban infrastructures during the large earthquakes seems to be very high (JICA, 2002).

Although mainly non-government agencies have invested a lot of efforts on earthquake risk reduction in Nepal the earthquake risk in the country and in LSMC have continued to grow, due to population growth, high rate of unplanned urbanization, use of inappropriate technology in the construction of buildings, lack of basic infrastructure, inappropriate organization system, and lack of awareness.

Lalitpur Sub-Metropolitan City has recognized the need for enhancing the activities in earthquake risk reduction, but they lack the expertise and resources required. The municipality does not have the required spatial information to investigate the existing trend of urbanization, population growth rate, and the resulting level of building and population vulnerability. They would need this to carry out the most useful types of earthquake vulnerability reduction measures, namely a building permit system that includes seismic safety and public awareness campaign. Population vulnerability mainly depends on their characteristics and the vulnerability of the buildings they live-in. Therefore to



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analyze the characteristics of population is a prerequisite for vulnerability analysis and also for the risk reduction process.

The disaster mitigation work in Lalitpur is not well organized. Although there are some initiatives with community groups in the local level and a municipal level, a section on Earthquake Safety was established within the urban development division, there is still a lack of good cooperation and co-ordination. Therefore to reduce the risk in the municipality as a whole, there is need of possible cooperative works between communities and the municipality.

1.3. Conceptual frame work

The current research is conceptualized mainly aiming to develop a method that could be adopted by municipal authorities in order to assess the vulnerability and level of capacity of local people to cope with earthquake risk. It estimates the casualties due to possible earthquakes in relation of building collapse or damage probability and population distribution, and combines with the capacity level of local people received from the household surveys. Based on the analysis of capacity components (awareness and preparedness) and casualties, it identifies the gaps and needs, and proposes the possible strategies. Figure 1.1 provides overview of the research.

Figure 1-1Conceptual framework of the research

Short definition of terms in the context of present study: Earthquake hazard- an earthquake that has the potential to cause harm or loss Vulnerability- degree of loss of a building or people due to a certain intensity earthquake. Risk- the probability of meeting danger or suffering harm or loss. Building inventory- details of buildings in the study area Casualty- a person injured or killed due to an certain intensity earthquake Intensity-measure of the felt effect of an earthquake Awareness- knowing that something exists, or having knowledge or being conscious of an earthquake risk Preparedness-to make or get (something or someone) ready for possible earthquake in the future Capacity-positive conditions which increase the ability of people to cope with an earthquake risk.



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1.4. Research objectives

The main objective of this research is to develop a method which can be adopted by municipal authorities in order to assess the vulnerability and level of capacity of local people.

Specific objectives along with sub objectives of the research are:

1. To design data collection methods and databases for the estimation of vulnerability and capacity. Also involving local people and local expertise from universities in the data collection.

2. To estimate the building damage under different probable earthquake scenarios, and the resulting expected human casualties.

3. To develop a method for the quantification of capacity of local people to cope with earthquake risk.

4. To combine the information on vulnerability and capacity, identify gaps, and propose possible strategies to improve the capacity of local people.

1.5. Research questions

The research questions pertaining to each of the objectives have been enlisted hereafter:

1. How to collect the information from local people on their earthquake vulnerability and level of awareness?

2. What will be the scenarios of building damage and casualties if there is an earthquake of a certain magnitude?

3. What is the situation of public capacity to cope with earthquake risk and how can it be quantified?

4. What could be best strategy to improve the capacity level of local people?

1.6. Research sequence and components

The research work for this study is mainly divided in three sections as shown in the figure 1.2.

Figure 1-2 Research sequence and components



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1.6.1. Pre-fieldwork

The study started with a review of previous research carried out in the Kathmandu Valley and on earthquake loss estimation worldwide. The main findings were incorporated in the research proposal and in formulating the major objectives to address the existing research problem.

After discussion with local authorities in Lalitpur it was decided to select ward 20 of Lalitpur Sub-Metropolitan City (LSMC) as the case study area. An IKONOS panchromatic image with 1meter resolution was used as the main base image to delineate the building units in the map. Before fieldwork it was used together with existing building footprints prepared by previous ITC students under the SLARIM project (Guragain, 2004; Islam, 2004). The ward boundary and other relevant thematic maps were overlaid, and new buildings were interpreted from the image. Since the boundary of ward 20 demarked by previous studies did not match with the one officially used by LSMC, it was corrected after discussion with municipal engineers.

It was experienced from the previous studies that the use of building blocks and homogenous units give a number of disadvantages as compared to the use of individual buildings, and due to the large heterogeneity of such aggregation units there may be large uncertainties in the estimation of building and population vulnerability. To avoid this problem all individual buildings were marked in the building footprint map. Since the map used by previous students, had building blocks rather than individual building units, it was decided to separate the individual building polygons in the original building footprint map as far as possible. The study area was divided into six different sections and the resulting map was printed in large scale overlaying the building footprint map on the IKONOS image.

Four type of questionnaire/survey forms were developed for the field data collection. A building survey form was developed to collect information on building age, structure, materials, floor/height, space use, geometry, building condition, etc. (See Annex 1-1). Two different questionnaires were developed for socio-economic and cultural information: one for residential buildings (See Annex 1-2) and one for non-residential buildings (See Annex 1-3). Both of them included questions the respondents' knowledge, preparedness and attitude towards earthquakes but the questions related to family structures and household information were not included in the non-residential questionnaires.

1.6.2. Fieldwork

A field study of one-month was conducted from 4 September to 4 October 2005 during which 4 architecture students from the Institute of Engineering, Pulchowk, Lalitpur were involved.

All individual buildings were visually observed and traced in the field map, and the interpreted building foot print map was checked and updated. The drawing of new buildings and the separation of large building polygons into separate building units was done manually without using precise measuring because of the limited time available. A building inventory survey was carried out for all 988 buildings of the study area. Each building received a unique code consisting of the ward number, section number, and household id. Roads, foot tracks and other important features like temples, pounds, nurseries, etc. were also traced on the map.

After the completing the building inventory a household survey was conducted. A preliminary analysis of collected building data was carried out to decide and locate the buildings that would be sampled for the household survey. Since the building uses in the study area are heterogeneous, the



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stratified random sampling method was adopted (See figure 1-2). Most of the buildings in the study area have mixed uses and very few of them have a specific use. Though many types of space uses were found and recorded during the building inventory, they were grouped in seven major groups for the household survey.

Figure 1-3: Sampled buildings for socioeconomic survey

Since most of the buildings were found with multiple uses, it was realised that to conduct household survey by floors is wiser then by buildings. Thus the five percent of the total building floors (168 floors out of 3,329), proportionally representing from all space uses, were selected and located in the footprint map in order to perform the survey.

Table 1-1: Sampled building floors

Each of the sampled building floors was visited and the adult persons present were interviewed. In the case of respondents' negligence for answering, they were not forced and another alternative floor was visited. As shown in the table 1-1, 131 residential and 37 non-residential floors were interviewed.

The Central Bureau of Statistics (CBS) was visited for overall population and building information for Lalitpur. The population data for the ward was also received but it doesn’t record the

Total Floors Sampled Floors Space use

No. % No. %

% from each space uses

Residential Residential 2,633 79 131 78 5 Industrial 59 2 3 2 5 Institutional 91 3 7 4 8 Commercial Pvt. office 77 2 3 2 4 Commercial shop 389 12 19 11 5 Public facility 63 2 2 1 3

Non -residential

Hotel/restaurant 17 1 3 2 18 Total 3,329 100 168 100 5



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number of people living in rented buildings and it also doesn't record the population within the buildings dividing different time periods of the day. For the current study the population data received from CBS was only used for comparison, since casualty calculation requires time distributed population and also the renting population.

The municipal and ward offices of LSMC were frequently visited for other relevant information. The Earthquake Safety Section (ESS) is responsible for earthquake related activities for LSMC and handles the information on municipal programs for earthquake risk reduction. Different social groups like Samudayik Bikash Sakha and Local clubs/Tolesudhar Samitiee etc. were visited to enquire about relevant information. The Central Library of Tribhuvan University has a good collection of researches and text books, newspapers and other historical records, and experts from Department of Mines and Geology (DMG) were consulted regarding geological and seismic condition of the valley. Experts from National Society for Earthquake Technology-Nepal (NSET), a local non-governmental organization working in this field provided important input in the various discussions which were held. NSET's publications in the field of earthquake risk assessment, community based awareness raising were collected and reviewed.

1.6.3. Post fieldwork

The new boundary of ward 20 was digitized and all the data was adjusted to that boundary as the spatial limitation of the study area.

The field maps with the drawings generated during the fieldwork were scanned and imported into ILWIS format. After geo-referencing the scanned maps the new building footprints were digitized. A point map was made with building IDs assigned during the building inventory survey, and the building footprints were polygonized. Likewise, transportation networks were also digitized.

In order to calculate the population vulnerability to earthquake there is need to estimate the total population living in individual buildings in a particular time. The population for the study area was calculated for different time periods for specific space uses by the population density factors calculated from the samples of the household survey.

Socio economic information collected during the household surveys was tabulated in Excel and household information, family structure, socioeconomic conditions were stored. The information on public awareness, response, perception and preparedness were recorded for both, residential and non-residential surveys. Several charts were generated from the calculated results for better representation.

Vulnerability functions describing the relation between seismic intensity and the damage rate of the building types are necessary for building damage estimation. An intensity-damage matrix, considering existing Nepalese building types, prepared by NSET and JICA during the national building code project and modified after the 1988 earthquake was used for the current study. In addition to building type and height, the current study considered other building parameters like geometry, condition, age, structural bands, the existence of soft storeys and upper partial floors (See Chapter 5 for more detail). The characteristics of different earthquake scenarios used for this study were taken from earlier research carried out by JICA (2002).

Once the building damage was estimated, human casualties were estimated in relation of population distribution and probability of building damage and collapse. Casualty ratios related to building damage used for this study were those defined by HAZUS-MH (2003).



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Level of public awareness, preparedness and capacity were analyzed from the information received interviewing with local people. Received information were grouped in awareness and preparedness, and then summed with available infrastructure and facilities with the household to get the overall capacity. All fields within the components were assigned the weights and final score were categorized in three levels i.e. high, medium and low. Finally the level of awareness, preparedness and capacity were correlated with vulnerability.

1.7. Study area

The present study selected Lalitpur Sub-Metropolitan City (LSMC) of Nepal as the study area considering its increasing vulnerability to earthquake due to unplanned urbanization, improper construction, poor infrastructures and lack of public awareness. Within LSMC, ward 20 was selected as the case study for the current research.

1.7.1. Location

Lalitpur Sub-Metropolitan City (LSMC) is located in the Kathmandu Valley, neighbouring the capital of the Kingdom of Nepal, Kathmandu, almost at the central hilly part of the country. Relatively, the main urban area of the municipality is on flat terrain with an elevation of about 1,280 m to 1,330 m occupying a total area of 15.4 Km2 (LSMC, 2004b).

The sub-metropolitan city area is divided into 22 administrative units called Wards. In Nepal, ward is the lowest formal administrative unit. Usually the boundary of the ward is defined using natural boundaries like rivers, roads or foot trails, but the population size and the area generally define the ward extent. The ward is chaired by a ward chairman elected by local people with other members representing their respective area. The current study area, ward 20, lies almost at the center part of LSMC (See Figure 1-3).

Figure 1-4: Location of the study area

Lalitpur



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1.7.2. History and culture

In 1918 the "Patan Sawal" (A legal document of Lalitpur) was issued and "Cheemdol" (Sanitation management office) was established to maintain sanitation and other aspects of city management in this historical city. The same office, Cheemdol, became Lalitpur Municipality in 1953 and Lalitpur Sub-Metropolitan City in 1996 (LSMC, 2004b). It is one of the oldest historical cities in Nepal, famous for its arts around the world. Patan Durbar Square (Figure 1-4), the ancient royal palace, is the most important monumental centre of this city, which has been recognized by UNESCO as a World Heritage Site (LSMC, 2004c).

Figure 1-5: A view of Durbar Square, Lalitpur

1.7.3. Population

LMSC has a total population of 162,991, with 34,996 households, according to the 2001 census (CBS, 2004). The main ethnic groups are Newar, Brahmin, Chhetri, Tamang, Rai, Limbu and they are tied different religious groups like Hinduism, Buddhism, Muslim, Christianity, Kirant, etc. The study area, ward 20 covers 1.17 percent (0.18 Km2) of the total area of the municipality. According to CBS the total population of this ward is 6,519 with 1,447 households. Chapter 3 will treat population characteristics of the study area in more detail.

1.7.4. Urbanization

Kathmandu Valley as a whole has a long history of settlement. The post 1950 Kathmandu Valley experienced a rapid functional expansion, with the opening of highways and air services and increased development activities. Migration from outside of the valley grew as the major infrastructural, institutional facilities and trading opportunities developed. Moreover, the tourism growth of the 1960's and industrial development, particularly carpet and garment manufacture, during late 1970's and 1980's, added to the urban expansion (MOPE, 1999).

Figure 1-5 provides the urbanization pattern of Kathmandu Valley, including Lalitpur from 1952 to 2011. During this period the urbanization increased in all three cities of the valley. In the case of Lalitpur only the present core area, Patan Durbar Square, appeared as urbanized area in 1969 and



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during 1971 the study area seemed to be urbanized and as time passes urbanization is expanding towards the periphery from the core. The current study area is now almost occupied by buildings. No more open space is left except for some courtyards, small ponds, play grounds and nurseries, but still in the remaining small open spaces the construction of new buildings has not stopped.

Figure 1-6: Population growth and urbanization in Kathmandu Valley

1.8. Limitations of the study

The current study has a limited scope due to the limited time and resources. This research has estimated the casualties related to buildings damage and collapse probability for different earthquake scenarios at different time periods of the day (morning, day, evening and night). Existing public capacity to cope with earthquake risk are measured on the basis of information received by interviewing local people during the field surveys. The spatial accuracy and georeferencing of the building footprint was not assessed during this study, since the data used was previously prepared during other MSc researches.

1.9. Thesis outline

The current thesis is mainly organised into four major parts. The first part consists of two chapters dealing with a general introduction of the research, a description of the study area, and a review of previous works and methodologies. The second part, the main body of the research, consists of three chapters, mainly focusing on the characteristics of the ward and the assessment of the vulnerability of buildings and population in different aspects considering different magnitude of earthquakes. The third part of the research deals with an analysis and measurement of the existing awareness preparedness and capacity to cope with earthquake risk. The conclusive findings and recommendations are presented in the last part of the research. Relevant tables, charts and maps generated during the analysis but not included in the main body of the research, are presented in Annexes.



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2 Earthquake Vulnerability and Risk Reduction in Nepal: a Literature Review

This chapter deals with a brief review of the theoretical background and the past efforts in the field of earthquake loss estimation and risk reduction. Previous MSc researches at ITC have made overview on the general aspects related to earthquakes, seismicity in Nepal and earthquake vulnerability assessment (Destegul, 2004; Guragain, 2004; Islam, 2004; Khanal, 2005; Piya, 2004; Tung, 2004). Therefore the literature review will be limited in this thesis.

2.1. Earthquakes in Nepal

Earthquakes are often considered as being an act of God. Actually earthquakes are the most destructive, endogenous, rapid, natural phenomena that cannot be avoided and can occur at any time without any signals and can destroy buildings instantaneously, killing or injuring the inhabitants. It is a sudden ground motion, or series of motions, originating in a limited region inside the earth and spreading from this point in all directions (Davis and Gupta, 1990; Gupta and Singh, 1980).

Though from early years some predictions are made which sometimes coincided with the events, so far no one has succeeded to attest scientifically that his/her prediction was able to predict the earthquake regarding its occurrence time, scale and location. Hence still it is a challenge to scientists to predict earthquakes in order to save human lives and property.

Nepal is among the countries with the highest seismicity in the world, related to the presence of active faults between tectonic plates along the Himalayas, mainly in the Main Boundary Fault (MBF) and Main Central Thrust (MCT). Earthquakes of even moderate intensities can have devastating consequences in the country since traditional houses are in many cases too weak to resist their effects of earthquake. Most modern houses are also vulnerable, particularly in densely populated urban areas where the risk of collapse in the event of earthquake is very high (Russell et al., 1991). The major earthquakes in terms of magnitude and loss of life and building damage are listed in table 2-1. According to historical records the earthquakes in 1255, 1408 (M 7.7), 1681(M 7.0), 1913 (M 7.3), 1916 (M 7.7), 1934 (M 8.4), 1980 (M 6.5), 1988 (M 6.6) and in 1991 (M 6.1) were the major ones. In 1934 earthquake, about 19,000 buildings were heavily damaged, about 3,800 people were killed and about 11,000 people were seriously injured only in Kathmandu Valley (JICA, 2002). The deadliest earthquake in recent history was centred across the border in the Indian state of Bihar. It caused mainly heavy damage in parts of eastern Nepal, including Kathmandu Valley. Since the western region of Nepal has had very few large earthquakes as compared to neighbouring areas, recent studies indicate the presence of dangerous seismic gap in this zone.

Within the last 33 years (1971-2003), Nepal experienced 22 earthquakes with magnitudes ranging from 4.5 to 6.5 on the Richter scale. In this time span about 34,000 buildings were destroyed and 56,000 were damaged. More than 126 million dollars were lost because of earthquakes during this time span. The major part of losses in this period were due to 1988 earthquake (NSET, 2004).



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Table 2-1: Major earthquakes in Nepalese history

Human Buildings Year Date

Earthquakes epicentre Deaths Injured Collapsed Damaged

1993 Jajarkot NA NA 40% of the buildings are estimated to be affected

1988 21 Aug Udaypur 721 6453 22328 49045 1980 04 Aug Bajhang 46 236 12817 13298 1934 15 Jan Bihar/Nepal 8519 NA 80893 126355 1837 17 Jan NA NA NA NA NA 1834 Sept-Oct NA NA NA NA NA 26 Sept NA NA NA NA NA 13 July NA NA NA NA NA 11 July NA NA NA NA NA 1833 26 Aug NA NA NA 18000 in total 25 Sept NA NA NA NA NA 1823 NA NA NA NA NA NA 1810 May NA Moderate Heavy 1767 Jun NA NA NA NA NA 1681 NA NA NA NA NA NA 1408 NA NA Heavy Heavy 1260 NA NA NA NA NA NA 1255 07 Jun NA One third of the total population

including king Abhya Malla, killed Many buildings and temple collapsed

Note: ‘NA’ indicates ‘description not available’. Source: National Society for Earthquake Technology-Nepal (NSET), 2000

Rajbhandari (2002) mentioned that the medium earthquakes occur in Nepal in every 50 years

and major earthquakes occurs in an interval of 100 years. It is highly expected that another major earthquake is due in near future. But he has not mentioned the definition of medium and major earthquakes in his study. However according to experts from Department of Mines and Geology (DMG) earthquakes less than 5 magnitude are considered as "small", 5-7 magnitude "medium" and greater than 7 are considered as "large". Geoscientists from His Majesty’s Government of Nepal and a team of geophysicists from France have monitored microseismicity in Nepal for more then 10 years. Out of the 4,000 local events recorded between 1985 and 1992, 1200 occurred within Kathmandu network (Thakur et al., 2001). Kathmandu Valley has grown rapidly in an unplanned way in the past few decades. Although the Draft National Building Code of Nepal (NBC) was already prepared in 1994 following the 1988 earthquake, it is not yet being enforced (JICA, 2002).

2.2. Earthquake loss estimation in Kathmandu Valley

Although the detail studies on the current study area are not made yet, many initiatives have been taken by the experts from national and international organizations for the assessment of earthquake vulnerability in Kathmandu Valley including Lalitpur. The spatial distribution of the earthquake losses is a very important basis for a proper earthquake vulnerability reduction and emergency planning at municipal level. Municipality would need to have databases at individual



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building level, in order to be able to carry out proper control over building construction (Westen et al., 2005).

A study carried out by the National Society for Earthquake Technology-Nepal (NSET) under The Kathmandu Valley Earthquake Risk Management Project (KVERMP) concluded that if an earthquake with the same shaking pattern and characteristics as the one in 1934 struck, approximately 40,000 deaths and 95,000 injuries in the Kathmandu Valley (Dixit et al., 1999). KVERMP used limited information to come up with a scenario of potential damage to buildings in the valley, and demonstrated the need to undertake a systematic inventory of existing buildings to arrive at conclusions on the vulnerability of the existing buildings to strong earthquakes.

The Japan International Cooperation Agency (JICA, 2002) carried out a detailed study on Earthquake Disaster Mitigation in the Kathmandu Valley in 2001. During this study for earthquake risk assessment in Kathmandu Valley, the area was divided into grids with meshes of 500 by 500 m and buildings were mapped from aerial photos and refined during field survey. It made an intensive effort to develop a model to estimate earthquake damage for the valley that includes human casualties, and prepared a series of vulnerability maps for buildings and infrastructures as well considering different earthquake scenarios. The model is simple and easy to use but it is too coarse (lacks detail). It does not consider the temporal distribution of population and talks about the groups of buildings rather then individual.

Most of the previous studies on earthquake loss estimation in Kathmandu Valley have concentrated on estimation of physical vulnerability. However, vulnerability is a reflection of the state of the individual and collective physical, social, economic and environmental conditions at hand that are shaped continually by attitudinal, behavioural, cultural, socio-economic and political influences at the individuals, families, communities, and countries (ISDR, 2002).

Broadly, vulnerability can be understood from three aspects i.e. physical vulnerability, social vulnerability and economic vulnerability.

Physical vulnerability considers the expected damage of constructions such as buildings, infrastructure and essential facilities. Social vulnerability is linked to the level of well being of individuals, communities and society (ISDR, 2002). It includes aspects related to levels of literacy and education, the existence of peace and security, access to basic human rights, systems of good governance, social equity, positive traditional values, knowledge structures, customs and ideological beliefs, and overall collective organizational systems. Since a large percentage of population is still illiterate and living with deep-rooted socio-cultural conservatives, the social aspect of vulnerability is more essential to address in the developing countries like Nepal.

Economic vulnerability measures the risk of hazards causing losses to economic assets and processes. It focuses on evaluating the direct loss potential (i.e. damage or destruction of physical and social infrastructure and its repair or replacement cost, as well as crop damage and losses to the means of production); indirect loss potential (i.e. the impact on lost production, employment, vital services and income-earning activities); and secondary effects (epidemics, inflation, income disparities and isolation of outlying areas) (UNDRO cited in (Carter, 1991).

Capacity assessments is an indispensable complement to vulnerability assessment (ISDR, 2002). Capacity is the capability of an element at risk to reduce the impact during an earthquake, for instance building code implementation, changing the public attitude before, during and after an earthquake, improving infrastructures etc. Thus the vulnerability of an element at risk to a particular



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hazard may differ before and after adding the capacity. Most of the developing countries, like Nepal, are more vulnerable to earthquakes because they have low capacity to reduce the vulnerability. It shows the poor are, in general, far more vulnerable than economically better off sectors of society (NSET et al., 2002). This relates both to the proportional possibility of higher losses when a disaster strikes, and to the capacity to recover from disasters. For example, the damage and deaths may be more in Kathmandu then in Tokyo from the earthquakes of same magnitude.

The word “risk” has so many different meanings, which often causing problems in communication. Regardless of the definition, however, the probabilities and consequences of adverse events, and hence the “risks,” are typically assumed to be objectively quantified by risk assessment (Slovic and Weber, 2002). It refers to the nature of hazard and the potential impacts of the hazard if the hazard takes place. The potential impacts (damage) may be in the form of loss of life and injuries and/or loss of land and property. So the risk assessment/analysis is a process to determine the nature and extent of risk by analyzing potential hazards and evaluating existing conditions of vulnerability/ capacity that could pose a potential threat or harm to people, property, livelihoods and the environment on which they depend. Conventionally risk is expressed by the equation Risk = Hazards * Vulnerability / Capacity (ISDR, 2002).

2.3. Disaster management situation in Nepal

The full implementation of the seismic risk reduction strategy directly depends on economic resources of the country and policy in understanding of the existing problem (Balassanian, 2002). Nepal, being a developing, has a very low pace for disaster risk reduction activities.

The legal provision for disaster management actions in Nepal are reflected by the Natural Disaster Relief Act 1982. There is a provision to constitute Disaster Management Committees in different levels under this Act. The Central Disaster Relief Committee (CDRC) and the District Disaster Relief Committee (DDRC) are constituted in central and district level respectively. However most of the works are focused only on relief actions after the disaster occurs. Moreover, the disaster management committees i.e. Regional Disaster Relief Committee (RDRC) and Local Disaster Relief Committee (LDRC) are not actively performing their activities. CDRC and DDRC themselves usually work in central and local level respectively. The Ministry of Home Affairs (MOHA) is designated as the lead agency responsible for implementation of the Natural Calamity (Relief) Act, 1982, which has provision for adequate legal backups to implement HMG/Ns policies and strategies addressing to overall disaster management and risk reduction (MOHA, 2005). The collection and dissemination of disaster data in the kingdom is authentically under its control. In case of emergency in the kingdom it mobilizes Royal Nepalese Army (RNA) and Nepal Police for rescue and relief programs.

As United Nation declared the decade of 1990-2000 as the International Decade of Natural Disaster Reduction (IDNDR), responding the global call of prevention, Nepal constituted IDNDR National Committee and effectively worked during the years. Several new initiatives including implementation of the National Building Code Development Project were made and preparation of an Action Plan for Disaster Management was carried out. The first version of the National Action Plan (NAP), presented to the Yokohama Conference, was subsequently modified, and endorsed by the Government in 1996. However the lack of a well-articulated implementation strategy and mechanism made this document just as a shopping list, with no responsibility assigned to any institution for monitoring the activity or updating the Action Plan (NSET, 2004). Consequently, NAP has never been revisited since 1996 although there has been a overwhelming burst of initiatives in disaster risk



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management in Nepal since then, mainly propelled by the UN system, bilateral agencies, national and international NGOs, communities, and the municipalities. However efforts are made in the country to address the issues of earthquake awareness with a multi-front approach through a number of programs. Incorporating awareness component in activities of hazard identification and risk assessment, planning and mitigation measures is a major aspect of the awareness campaigning besides visible awareness programs by means of rally, public gatherings posters, pamphlet etc. The target groups of the awareness activities are all who are not aware of the risk, who think that the mitigation is not viable solution and government officers who are responsible for planning and execution of development project and operation of infrastructures (Pandey et al., 2002).

2.4. Community based disaster management in Kathmandu Valley

The precise occurrence of earthquakes can not be predicted reliably; therefore, prevention mitigation and preparedness are the principal strategies to protect people and property (Hays, 2004). In so doing, raising awareness in the local communities should be one of the first priorities. It concerns people from every sector of the community, all members of which are to realize how to prepare of a possible earthquake, how to behave if an earthquake strikes and what to do afterwards.

Earthquake risk reduction can not be achieved unless earthquake safety becomes a part of the society’s culture. Vulnerability to earthquakes is often greatest for the poorest members of society and in developing nations (Hays, 2004). A community based approach to disaster preparedness and management is vital especially in the context of developing countries like in Nepal, where local bodies do not have sufficient technical know-how as well as resources to take up the mapping exercises and entire burden of losses due to big disasters like earthquakes.

A community is a group of individuals and households living in the same location and having the same hazard exposure, who can share the same objectives and goals in disaster risk reduction (Bishwokarma, 2002). The community members may have varying perception of disaster risk depending on social class, education, age, gender, etc., and the community risk assessment and disaster risk reduction planning processes helps to unite the community in understanding of the risks and in preparedness, mitigation and prevention actions. Since low-income households and communities are often more vulnerable to natural hazards than the population at large, their active involvement in risk reduction, based on local knowledge and measures tailored to local conditions, offers to complement national disaster management initiatives (EPC, 2005).

Rather than seeing disaster-affected individuals as victims or passive recipients of outside assistance, good disaster management recognizes local people and their community-based organizations—village committees, agricultural cooperatives, tribal councils, women’s associations, youth groups, etc.—as valuable assets. When a disaster strikes, local people, working through their community structures and organizations, are the first to respond. They know which members of the community are hardest hit, and they know what assistance is appropriate. What these local organizations may lack, however, are financial resources, organizational capacity, advanced equipment, and training in disaster prevention, preparation and planning (EFC and COF, 2001).

In this context, it is convincing that the disaster preparedness will not be effective without the participation of the vulnerable communities. The prime component of disaster preparedness is to involve the vulnerable community in the disaster mitigation process. Building their capacities in coping mechanisms and their involvement creates confidence among them and paves the way for self-



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reliant (Newport and Jawahar, 2003). So the current challenge facing development circles is search for “human centered” development strategies which emphasize active participation of the people at the grass roots level. To be successful, the target-oriented approach requires a process of empowerment, consciousness-raising, and leadership development in the community. Development of relevant skills, knowledge, and attitudes among the members of the community is equally important. It is essential for this process to be initiated by the community it self. Integration and sustainability are central to the community-based approach. Community development approach based on the assumption that development starts at the grassroots level and the initiative, creativity, and energies of the people can be utilized to improve their own lives using democratic processes and voluntary efforts (Gajanayake and Gajanayake, 1993). In case of earthquake, the involvement of communities can be made to develop a disaster management plan. For instance in order to prepare the hazard zonation and resource mapping no one can be a reliable source then the local people, who have live experiences of hazard situation in that area.

To reduce earthquake risk in community level, UNEP has suggested mainly establishing an extensive public awareness program that disseminates information about earthquakes and related hazards and institutes disaster mitigation and preparedness measures along with other initiatives. It has proposed also demonstrating the techniques; train local residents and raise awareness of the fact that to retrofit an existing house or build a new house with earthquake proof structures adds only 5-20 percent to total building cost (UNEP, 2004).

For the current study, awareness can be defined as the consciousness of people to reduce risk from possible earthquakes. In other terms it is a part of the capacity to cope with the possible impact of an earthquake. Changing public attitude/behaviour via media or formal/informal education programs, distributing flyers/posters, conducting earthquake drills, organizing meeting/workshops may be the effective strategies for earthquake awareness raising in the community level. Lack of awareness contributes to seismic risk considerably. In the case of earthquake awareness, effective awareness doesn’t mean only to know that what is right or wrong to act before, during and after an earthquake but it’s a kind of effort that is already implicated or initiated for the risk reduction process. It concerns people from every sector of the community, all members of which are to realize how to prepare for possible disasters, how to behave if an earthquake strikes and what to do after.

Lalitpur, a historical city, is full of religious and cultural values. The daily activities and local physical and social environment are directly influenced by such cultural values. In the core area, traditionally designed old buildings, temples and other structures can be found. Indigenous knowledge used for the construction of still standing historical temples and buildings, passing through many devastating earthquakes, are the examples of hidden wisdom with the then local people. Local old people are the live sources of information for the last two big earthquakes in 1934 and 1988.

However to say “so far the local people of Lalitpur are not aware enough in order to act properly to avoid the maximum devastating affect by future the earthquakes” would not be an underestimating statement. They are still living with earthquake risk keeping traditional beliefs for example, the 1934 earthquake was interpreted as the consequence of the actions of Naga the snake God who is supposed to hold the earth, had to shift it from one shoulder to the other, due to its weight caused by unbearable sins on earth. Others interpreted the earthquake as the consequences of the sinful act committed by Europeans flying above the Himalaya (Mount Everest) which is supposed to be a sacred place for Lord Shiva (Rana, 1936).



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Strategy to change public understanding and attitude before, during and after earthquake considering the local experiences and knowledge is the prerequisite for earthquake risk reduction. An effective disaster management must be rooted in the community. From prevention and preparedness through response and rehabilitation, it is essential that not only the planning but also the implementation of the entire process, including how resources are used, must be controlled by the community. As the communities have more motivation and power then any other groups in their territory, the strategy of any disaster management plan would be effective with their direct involvement.

NSET, since its establishment, is working especially in Kathmandu Valley to raise public awareness against earthquake risk at community level. Earthquake awareness was a major component of, Kathmandu Valley Earthquake Risk Management Program (KVERMP), one of the successful programs of NSET. After the project phase out, NSET continued the awareness program through other projects such as School Earthquake Safety Program (SESP), Municipal Earthquake Risk Management Project (MERMP), critical facilities and lifeline vulnerability assessment, Community Based Disaster Management (CBDM) program, training and orientation program and Earthquake Safety Day (ESD) etc. (Pandey et al., 2002).

NSET is working on public awareness raising very closely with LSMC through its different programs. SESP is implemented in some schools of Lalitpur District. Conducting a survey of public schools with the help of respective headmasters, the schools were analyzed considering the size of buildings, density of students, age of constructions and construction technology etc., potential structural intervention for seismic strengthening is identified. Thus, some of the school buildings were reconstructed and some of them were recommended for retrofitting. During the process of retrofitting and reconstruction, several training programs for local masons and orientation programs for the public were conducted. The local masons were involved in the work under the supervision of a trained mason and engineers from NSET. This program has been very effective to motivate the local people to construct their buildings using simple earthquake safety measures. Thus the masonry training program involving local masons has shown positive effect in the newly constructed buildings, especially in Bhaktapur and Lalitpur, and also in some other places from where the masons were involved in the training.

A hand book prepared by NSET (Basnet et al., 2004) describing possible earthquake scenarios for the Kathmandu Valley in a simple way, is very convincing and easily understandable for the public. It describes possible human casualties, building damage, infrastructural paralysis and disturbances in socio-economic life, if there is an earthquake shaking similar to that in 1934.

NSET frequently organizes interactive activities, including discussions on radio and television. A public awareness program of NSET via radio program is highly appreciated. Technical seminars for professionals of the building industry and training programs for masons have increased the technical knowledge in the communities. Essays, poems, quizzes and painting competitions related to the earthquake theme for school children and street performance depicting what to do in case of an earthquake have helped the diffusion of knowledge at different level in the communities. A popular and convincing demonstration is a simulation of how different building types, both with and without seismic reinforcement, would react to a high-intensity earthquake like that of 1934, using a simple shaking table and one-tenth scale models of typical Nepalese buildings (See Figure 2-1).



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Figure 2-1: Shake-table demonstration for public awareness

As the government designated January 15 as the Earthquake Safety Day (ESD), in recognition

of the occurrence of the last major earthquake tragedy to strike the valley on January 15, 1934, every year the local authorities are encouraged to organize earthquake awareness programs such as rallies, exhibitions, seminars, and workshops (Dixit, 2003). In so doing, LSMC also in cooperation of NSET organizes awareness raising programs involving local communities and institutions. Publication and distribution of flyers and booklets with relevant information have been effective tools in transmitting earthquake knowledge. One of the programs, building code implementation is the milestone for reducing building vulnerability, and finally for earthquake risk reduction in the city. The components of building code implementation directly and/or indirectly have made people aware of possible mistakes during building construction. According to building code, the construction of new buildings in the city should meet the criteria indicated by the building code. For the effective implementation of the building code, the municipality has initiated a public interaction program once a week at the municipality office in cooperation with NSET (ESS, 2004).

Since the Royal Nepalese Army (RNA) is under the control of Ministry of Home Affairs (MOHA), it can mobilize the RNA in case there is a disaster in the country. The RNA also takes part in each ESD exhibiting its technology and know-how about the measures to be followed during and after disasters like earthquakes.

Despite all these activities which have been carried out for the community-based disaster management and awareness raising in Kathmandu Valley, the involvement of local authorities and municipalities is still at low level. This thesis intends to develop some simple tools how the municipalities in Kathmandu Valley could collect information to assess vulnerability and awareness, and use it in planning vulnerability reduction measures, tailored to the local communities.



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2.4.1. Involvement of organizations for awareness raising activities in Ward 20 Lalitpur

Since the present study area is only a small part of LSMC, only few organizations are particularly focussing on this area. Informal small local community groups are traditionally formed that are working to conduct common activities like festivals and socio-cultural activities. During the field study, more then 80 percent of the population were found Newars, who have a traditional group called "Guthi" that has own system to perform community works involving its members.

Some of the NGO and INGOs directly or indirectly involved for the earthquake risk reduction process in cooperation with LSMC are: National Society for Earthquake Technology-Nepal (NSET), Nepal Red Cross Society (NRCS), Nepal Scout and other many NGOs and international agencies such as: Japan International Cooperation Agency (JICA), Asian Disaster Reduction Centre (ADRC), Asian Disaster Preparedness Centre (ADPC), United Nations Development Programme (UNDP), International Centre for Integrated Mountain Development (ICIMOD), International Red Cross Society (IRCS), United States Agency for International Development Mission to Nepal (USAID), United Mission to Nepal (UMN), Cooperation for American Relief Everywhere (CARE), World Food Program (WFP), Save the Children Fund (SCF), Technical Cooperation of the Federal Republic of Germany (GTZ), Lutheran World Service (LWS) etc.

As mentioned in above section NSET is working in close cooperation with LSMC from about a decade before. Though so far it has not launched any programs focusing particularly in the current study area, its activities in the Kathmandu Valley and LSMC are significantly important for the risk reduction process in the area.

Nepal Red Cross Society (NRCS) has focused mainly its activities providing relief after earthquakes in Nepal. The trained volunteers of NRCS have been contributing their skills after earthquakes and other disasters. In 2003, as awareness raising program it conducted an earthquake drill program involving students and local club members in Lalitpur in cooperation of NSET. Through the local clubs it has been supporting the community people providing first aid trainings and also participates each ESD exhibiting its emergency rescue operating systems.

The Community Development Section (CDS), established in LSMC in 1993, with the main objectives to promote the low income women and children deprived of education in the community has made different groups for women and children in the local communities and providing education skill development trainings (LSMC, 2004a). Further it organizes some time the first aid trainings in cooperation of other supporting NGO's and INGOs. One of the programs for making women literate in the community is effectively implemented in ward 20 with financial support from LSMC. Though till the date, it has not conducted any awareness raising programs focusing on earthquake, during the ESD 2005 it actively mobilized its members for the participation in the rally and other programs (Interview with Member, Ms. Sarita Maharjan, 23 September 2005).

The Padmavati Saving and Credit Co-operative Society Ltd., one of the active local organizations in the study area, was established in 1993 with main objectives to encourage the local people of ward 20 for regular saving and serve the community through various programs. Now it holds about 1000 members of different age groups from ward 20 of LSMC (PCSC, 2004). It has established different funds for different groups; i.e. children, youth, women and old. The community health programs, first aid training programs, tuition programs for its members, have increased self dependence and cooperation among the community peoples. It has made a provision of life insurance



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for the member, a kind of security for uncertain future. It has planned to extend its works more towards making people aware of disasters in the community. A certain amount of its funds can be used in emergency like earthquake disasters (Interview with the Chairman, Nembir Shakya, 25 September 2005).

2.5. Previous works within the SLARIM project

In order to contribute to urban risk assessment in developing countries the International Institute for Geoinformation Science and Earth Observation (ITC) launched a research project, Strengthening Local Authorities in Risk Management (SLARIM), with the main objective to develop generic methodologies for GIS-based risk assessment and decision support systems that can be beneficial for local authorities in medium-sized cities in developing countries (Westen, 2005). As part of SLARIM research project several studies have been carried out in Lalitpur.

Piya (2004) investigated the subsurface geological conditions of Kathmandu Valley based on a large number of boreholes. He concluded Kathmandu Valley is underlain by thick lacustrine sediments mainly composed of clay, locally called Kalimati (black clay). It is a deposit of the so-called “Paleo-Kathmandu Lake” which was formed between 2 to 2.5 Ma B.P. The lacustrine materials are on top of coarse sand and gravel beds, which were formed by the so-called “Proto-Bagmati River system” of the valley. The valley could be susceptible to liquefaction during a strong earthquake, due to its liquefiable soils (sand and silts), high groundwater level and potential strong earthquake motions in the region.

Khanal (2005) also has carried out an MSc. research under SLARIM project dealing with the spatial variation in seismic responses in Kathmandu Valley. He has used the strong ground motion data of the 1999 Chamoli earthquake of Uttaranchal, India together with the borehole information used by Piya (2004) for the calculation of the spatial variation in seismic responses. The quantity of ground motion amplification he has described in terms of PGA, MMI, response spectra, and amplification ratios. According to his calculation the current study area falls within the zone of MMI VI. For the seismic response analysis 134 soil profiles were used. The spatial distribution of the spectral acceleration map at 10 Hz and 5 Hz frequencies have shown the lowest acceleration values in the range of 0.05-0.3 g. Most of the highly populated and core cities of the valley have spectral acceleration values less than 0.15 g. for the particular earthquake scenario which was used. Therefore, he has concluded, based on the acceleration effects low rise buildings (one – two storeys) are comparatively safe in terms earthquake shaking.

Guragain (2004) in his MSc. research performed a building damage estimation using three different earthquake scenarios and building information on construction methods, materials used, configuration, age, number of storeys and size as the factors contributing to building vulnerability. The building losses in Lalitpur for different probable earthquake scenarios was calculated using an existing intensity damage matrix of the area prepared during the preparation of the building code and modified by JICA and NSET. He calculated two types of building damage i.e. partial damage and the complete collapse. Partial damage refers to the damage, which can be repaired, and complete collapse means the damage that is not cost effectively repairable. For each damage cases the study resulted to a maximum and a minimum number of buildings.

Islam (2004) carried out a study on population vulnerability of LSMC on the basis of building loss estimation by Guragain (2004). Population distribution for different periods of the day within



20

different occupancy classes, the building loss estimations and vulnerability and casualty ratios with respect to building damage are used in his calculation of casualties. These casualty ratios were derived from the HAZUS methodology, which uses the widely accepted ATC-13 vulnerability curves.

However during the studies for building damage and human casualty estimation under SLARIM, the building footprint map they used did not make a separation between individual buildings, but rather displayed entire complexes of buildings as a single polygon. To calculate the number of buildings the building footprint area of these polygons was divided by the average plinth area of a building, which was defined as 45 m2 based on samples. With this method they estimated a total number of 26,873 buildings in Lalitpur for the year 2001 (Westen et al., 2005).

Similarly an assessment of earthquake vulnerability of roads and bridges in Lalitpur, under this project, made an inventory of the existing conditions of roads and bridges and classified them in terms of their characteristics and geographical locations (Tung, 2004). Since roads play a significant role in the evacuation in post earthquake emergency, the information on road vulnerability is very important in the community awareness raising.

Singh (2005), in her MSc thesis, studied and evaluated the population vulnerability of a part of Derhadun city of India and tried to calculate the expected losses due to an earthquake. Her study mainly focused on: (a) Determining the building and population loss (in the event of an earthquake striking the study area); by way of inventory of individual building stock on physical, land use and occupancy characteristics; and; studying the population activity patterns both within buildings as well as outside, and (b) How a community based approach using local knowledge (such as risk and resource mapping) as well as data can re-enforce GIS based population vulnerability assessment. She generated the database for the population and buildings as well as roads in the study area and estimated the building and population loss for a part of Dehradun city. She tried to use the community based approach for identifying risky buildings. She has found from her research that, in a predominantly residential area, population distribution varies considerably diurnally and census sources for exercises such as vulnerability assessments are inadequate.

Palmiano-Reganit (2005) an ITC student under SLARIM project has carried out her research on the coping mechanisms regarding the flood problem in Naga city, the Philippines. A descriptive and exploratory approach is designed to figure out and understand how the community reacts and response with the floods and the possible measures by the Local Government Unit (LGU) to strengthen and help the community reducing flood damages. She has adopted a simple random sampling for household survey including mainly the questions to extract information on how the local community is dealing with floods. She found that the local people living in the place for the proximity to the source of economic livelihood and education of children for the sake of that they have applied more than 6 coping mechanisms. The coping mechanisms employed by the community are mainly at three flood stages –before, during, after. Income, access to assistance, and geographical location show significant relationships with the community’s coping mechanisms. She has argued that the information received from the field survey regarding the community responses, perceptions and coping mechanisms on disasters would be very useful for the disaster management plans by LGU.

This study has taken all previous works, mentioned above, as the background efforts and methodologies. These are treated as the suggestive and guidance materials. The studies in the related fields conducted out of the country are good to buy in the ideas. Loss estimations of building by Guragain (2004) and casualties by Islam (2004) were in homogenous unit (group of buildings) level, are précised in individual building level during this study.



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3 Characterization of Ward 20

3.1. Introduction

This chapter is an attempt to present the overall information on the study area, ward 20 of Lalitpur Sub-Metropolitan City. Information presented in this chapter is based on the field observation and household surveys conducted during September-October 2005. Adopted methodologies for data collection are discussed in chapter 1.

3.2. Physical database

GIS offers tools to handle information that can lead to vulnerability reduction. An effective presentation of the information in the form of map and databases is a convincing tool for policy makers, planners as well as to increase public awareness. It is obvious that the geo-referenced spatial information is a requirement for risk analysis. Complete and accurate information will give effective analysis and ultimately the proper solution.

In the developing world, the cultural environment like haphazard building construction, unplanned infrastructures (narrow roads, unplanned electricity circuit, poor water supply system, etc.) increase the vulnerability of the community. To have an earthquake safe community, people from all sectors should be aware of the hazard, their vulnerability and ultimately their risk.

3.2.1. Digital data sources

It has been just a couple of years that Lalitpur Sub-Metropolitan City (LSMC) maintaining information in GIS format in some aspects including road, electricity, communication network, etc.

The building footprints used in the current study were originally received from previous studies carried out under the SLARIM project, which were initially prepared by the Kathmandu Urban Development Project (KUDP) in Auto Cad dxf format, based on aerial photos of 1981 and 1992 and was updated in 1998 (Guragain, 2004). All the buildings constructed after this year, observed in the IKONOS image from 2001, were digitized on screen to create the building dataset. Also a CORONA image from 1967 was available. This image was used to delete those buildings that were not yet present in 1967, and generate a building footprint map for that year (Westen et al., 2005). The coordinate systems used for the current study are as given in table 3-1.

Table 3-1: Projection parameters

Parameters Value/Reference

Projection UTM, Zone- 45, Northern Hemisphere

Ellipsoid WGS 1984

Datum WGS 1984

Central Meridian 870

Scale Factor at Central Meridian 0.99960000



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3.2.2. Building footprints

The building footprint map prepared by previous studies was in the form of blocks and not at the level of individual buildings so during the fieldwork they were separated at the level of individual buildings by visual observation (no measuring tape was used). Some buildings which did not exist in the field but were indicated in the map, (probably because of wrong interpretation of images or have been demolished) were deleted. Newly constructed buildings, which were absent in the previous map were traced out during the fieldwork.

Figure 3-1: Building footprints

Figure 3-1 presents the total 988 building footprints drawn during the field observation. The

transportation network traced during the field observation is also presented in the building footprint map. For the reference coordinates are added so that the particular building could be located referring the coordinates on the map and in the real field. However, the coordinates and details of transportation networks are not added hereafter in all maps to present the greater extend of the relevant themes. So that figure 3-1 is recommended to refer for the coordinates of the maps presented hereafter.

3.2.3. Building inventory

Since the current study is focused on casualty calculation due to earthquakes, it is prerequisite to have information about the buildings where the people live. Hence an inventory for buildings in the study area was conducted during the fieldwork. All individual buildings were closely observed and traced on the field map as explained in the previous section and the building details, i.e. use of the building, floor-height, shape, attachment, age, materials used (floor, wall, roof), structural bands, building conditions (wall cracks, floor cracks/settlements, wall/floor dampness), existence of soft storey and upper partial floors, etc. were recorded in a designed format (See Annex 1-1).



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3.2.3.1. Space uses

Since all individual buildings were mapped, all the relevant characteristics that could be recorded by visual observation were filled in the inventory form. In the study area, there are 988 total buildings containing 3,329 separate levels (floors). About 75 percent of all floors are used for residential purposes and 12 percent are used for commercial purposes, with the remaining 13 percent for other different purposes (See Table: 3-2).

Table 3-2: Building floors classified by space use

Where,

RH= Residential, Ins= Institutional, Ind= Industrial, EDUrh= Schools residential hostels, EDUsc= School class room, CS= commercial shop, CHR= Hotel/restaurant, PF= Public facility.

Most of the upper floors are used for residential purpose and more than 96 percent of the commercial establishments are found on the first and second floors. Buildings used for educational purposes are not more then 4 floors but some residential boarding schools were found up to 6 floors. There are no large industries in the study area. During the field survey, small workshops and handicraft industries were observed in the lower floors but some small handicraft industries run by single families were also observed on the upper floors.

Finally all buildings were classified according to predominant space uses of the respective building floors. Thus out of 988 total buildings, 758 buildings were predominantly used for residential purposes, 88 for commercial, 60 for educational (hostels and class rooms) and the rest for other purposes (See Table 3-3 and Figure 3-2).

Table 3-3: Buildings by space uses

Space use Buildings %Residential 758 77Institutional 88 9Industrial 33 3Commercial shops 28 3Educational (residential hostels) 28 3Educational (class rooms) 27 3Hotel/restaurant) 20 2Public facility 6 1Total 988 100

No % No % No % No % No % No % No % No % No %1st 596 24 21 26 27 46 28 21 32 37 250 64 6 35 28 44 988 29.72nd 592 24 35 43 8 14 43 32 26 30 126 32 6 35 21 33 857 25.73rd 620 25 18 22 8 14 33 24 19 22 13 3 4 24 10 16 725 21.84th 440 18 7 9 7 12 17 13 9 10 0 0 1 6 3 5 484 14.55th 204 8 0 0 5 8 10 7 1 1 0 0 0 0 1 2 221 6.66th 44 2 0 0 2 3 4 3 0 0 0 0 0 0 0 0 50 1.57th 2 0 0 0 2 3 0 0 0 0 0 0 0 0 0 0 4 0.1Total 2498 100 81 100 59 100 135 100 87 100 389 100 17 100 63 100 3329 100% 75 2 2 4 3 12 1 2 100

Total floorsFloors EDUsc CS CHR PFRH Ins Ind EDUrh



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Figure 3-2: Buildings by space uses

3.2.3.2. Age and structure of buildings

Different dynasties like Kirant, Lichhavi, Malla and Rana who ruled Kathmandu in the past, have left their typical cultural values and structural designs which can still be recognized in the old buildings and used to identify roughly when they were built. The present study has tried to separate the buildings according to age. Likewise other buildings also were divided in different periods considering different stages. For example, buildings aged less than 10 years are assumed as constructed after the building code implementation in 1994 and those aged between 10-30 years have mostly used brick and most of them are load bearing walls (LBW). In the field about 75 percent of new buildings (0-10 years) were found to be reinforced cement concrete buildings (RCC). Likewise, almost all buildings from Shah-Rana period (about 50-150 years old) were found to be LBW structures (See Figure 3-3). It seems the trend of constructing RCC buildings is started during 30-50 years before from today.

0

100

200

300

400

500

600

700

Nu

mb

er o

f b

uild

ing

s

<10 Years 10-30 Years 30-50 Years Shah-Rana OlderAge

LBW Mixed RCC Temporary

Figure 3-3: Building age and structural types



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3.2.3.3. Building heights

Buildings experience acceleration, velocity and displacement with varying frequencies during an earthquake shaking. Each of these modes has a period. Among these periods, the longest is called the structural natural period of vibration and the frequency associated to it is called the natural frequency. Mainly the natural frequency of the building depends on its height and stiffness.

The building heights in this study are taken as the number of floors. It was observed in the field that many of the upper floors were only partial and not covering the entire building. These partial floors, when counting building height they were taken as complete floors. Although some official and commercial buildings have individual floor heights up to floor heights up to 3.7 meter, most of the modern brick with cement mortar (BC) and reinforced cement concrete (RCC) buildings in residential areas have an average floor height of 2.7 meters (Guragain, 2004). Most of the buildings in the study area are 3 and 4 storey buildings (24 and 27 percent respectively). Very rarely buildings with seven storeys are found (See Figure 3-4).

0

50

100

150

200

250

300

Num

ber

of b

uild

ings

1 2 3 4 5 >5Number of floors

Figure 3-4: Number of floors with the buildings

3.2.3.4. Building geometry

The damage of a building by an earthquake also depends on its geometry. Buildings having a large length to width ratio, large height to width ratio and large offset in plan and in elevation behave poorly and suffer greater damage than the regular ones (Guragain, 2004). National Building Code, in the Nepalese context, has indicated that to get a less damaging effect the building should be regular in plan and in elevation and the length and width ratio of the building must kept lesser than three (NBC, 1994).

In the study area more than 95 percent buildings were observed as regular with a length width ratio <=1:3, one percent with ratio >1:3 and 4 percent of the buildings had irregular shapes based on the field survey (See Annex 3-1).

3.2.3.5. Building construction materials

The construction materials used in the different components of buildings may have an important influence on the damage rate during an earthquake. Mainly the wall materials and mortar



26

type control the strength of the buildings. Likewise poor roof and floor materials increase the building's vulnerability during an earthquake.

In the study area, more than 94 percent of the buildings have industrial local mud bricks as wall materials, about 4 percent used industrial Chinese bricks but the buildings with hollow concrete walls were rarely found, only in two buildings (See Annex 3-2). About 62 percent of the buildings have RCC flat roofs, 32 percent have tin roofs and about 6 percent have tile roofs (See Annex 1-3). Most of the buildings were observed using cement and mud as floor materials (See Annex 3-4).

3.2.3.6. Building classification

The development of more detailed vulnerability function for the particular building types within the study area is beyond the scope of this study. So it was only possible to apply the existing general vulnerability curve to estimate the building and population vulnerability in the study area. There are many vulnerability functions used in the different parts of the world but in order to make them more reliable they should be developed considering the local type of buildings. One of the most popular ones is derived from HAZUS method, and was developed for typical buildings in US (HAZUS-MH, 2003). These building types don't fit in the context of Nepal, so to use this methodology for the study area doesn't make any sense. Vulnerability function used by JICA and NSET for Kathmandu Valley can be used for the current study though they are quite general. They consider just the building height and the structural types. But the effort tried in this study was to consider also other building parameters then floor height and structural types; like age, geometry, building conditions, structural bands, soft storey, upper partial floors etc. Thus, first to adjust the building classes with the JICA/NSET study, whole buildings of the study area were classified in five classes i.e. Adobe (AD), Brick in Cement (BC), Brick in Mud (BM), RCC less or equal to 3 storey (RCC3) and RCC greater or equal to 4 storey (RCC4) (See Figure 3-5).

Figure 3-5: Building classification



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3.2.3.7. Building condition

Buildings with poor conditions are more vulnerable to earthquake damage. For example buildings that already show visible cracks in the walls probably don't need a large ground shacking to collapse. Likewise the presence of floor cracks differential settlements, dampness on walls are also contributing factor to make a building more vulnerable. Therefore this study has tried to identify the buildings with such conditions during the fieldwork as far as possible by visual observation. It was found, about 8 percent buildings (82) of the total were observed with wall cracks, 6 percent (54 buildings) with floor cracks and differential settlements and 14 percent (139) with wall/floor dampness (See Figure 3-6).

82

54

139

0

20

40

60

80

100

120

140

Num

ber

of b

uild

ings

Wall cracks Floorcracks/settlements

Wall/floor dampness

Building conditions

Figure 3-6: Building conditions

3.2.3.8. Attached buildings and height coincidence

As mentioned in the previous section, every building has its own natural frequency and swings accordingly during an earthquake. So the building attachment and the floor height coincide will have significant role for damage of buildings during an earthquake. If two buildings have not enough space between them, then they can not swing freely and create pounding effect, which cause local crushing of the structures and failure of structural and non-structural elements located in the zone of impact. As a thumb rule, given in FEMA 310, the minimum separation distance between two buildings must be 4% of the height the buildings (FEMA 310, 1998 cited in (Guragain, 2004). This is based on the assumption that most structures will not drift more than 2% when responding the earthquake motion. During the field survey, individual buildings were observed and found that about 60 percent buildings were found attached with the neighbouring one or other buildings and about 40 percent buildings were attached with neighbouring buildings in both sides. About 19 percent buildings were found floor height coinciding either side neighbouring building or 3 percent coinciding with both neighbouring buildings.



28

3.2.4. Road infrastructure and utilities

Although the infrastructures such as road, electricity, telephone, water supply, etc. are very important analysing the earthquake risk and for the risk reduction planning, the current study didn't pay much attention to them because of time limitation. LSMC as a whole has good connection of transportation with other neighbouring cities. It has a total road length of 383 kilometres.

The typical nature of roads in LSMC is that more than 45 percent are brick paved (LSMC, 2005). Since the buildings are not constructed in a planned manner the road and foot trails were observed to often be very narrow and in poor condition. During the field survey, the roads were categorized in three classes: wide, narrow and foot trails. The road widths were approximately observed as in Kathmandu Street Atlas: wide roads with width over 14 meters, narrow roads with widths between 3-14 meters (locally called "sadak") and foot trails (non-motorable called "gallis") with width less than 3 meters (KMC, 2003).

The responsible authority, Nepal Water Supply Corporation (in Jawalakhel) is not able to supply enough drinking water to Lalitpur. It has a total capacity of 32 mld (million litre per day) in the wet season and 23 mld. in the dry season whereas the demand is more than 38 mld (LSMC, 2005). Hence to resolve the deficit people are dependent on traditional sources of water like stone spouts dug wells, and tube wells. During the field survey it was found that still more than 20 percent of the interviewed people using other sources than piped water and only 89 percent households were having water supply facility. Likewise, 95 percent households had reported sewerage facility, 97 percent had electricity and 92 percent had telephone facility (See Figure: 3-7).

0%

20%

40%

60%

80%

100%

Per

cent

age

of

hou

seh

old

s

Water Sew age Electricity Telephone Television RadioUtilities

Yes No Figure 3-7: Provision of utilities in surveyed households

3.3. Population data

A further requirement for disaster management planning is to know the demographic details of the areas at risk. Census data, if up to date and accurate, can provide such information and may also reveal vital additional details on such matters as population age profiles, the mobility of communities over time and occupational patterns. Such data can be invaluable tools as a basis for risk assessment and ultimately for the disaster management planning (Davis and Bickmore, 1993). Naturally old



29

people and small children are more vulnerable to earthquakes then young people and adults, women are more vulnerable then man and poor people more then riches people (NSET et al., 2002).

Therefore this study made an attempt to collect the information on population characteristics such as distribution, ethnicity, religion, language, age, gender, occupation, activity, literacy, etc.

3.3.1. Spatiotemporal distribution of population

The Central Bureau of Statistics (CBS) is an authorised department collecting and managing demographic data of the nation. It conducts a census every 10 years. The latest census in Nepal was conducted five years before (2001); already there may be lot of changes. Moreover the census counts only the population permanently belonging to a particular building of the respective area. So a large part of the population that actually lives in an area is missing from the census data. People living in rented apartments and in other buildings such as offices/institutions are only counted in the city or village where they are originally from. In practice this give a lot of confusion and makes the actual population figures from CBS very unreliable. To come up with population vulnerability to earthquake it is required to know the actual population living in the study area at the time of an event. Therefore we need to know the spatial and temporal distribution of population of the desired area.

3.3.1.1. Spatial distribution of population

A household survey for the sampled buildings was conducted to estimate the population for the study area. As stated in the chapter 1 the population was estimated considering the space use of all building floors.

During the building inventory a total of 3,329 floors were counted with different space uses. Out of the total floors, 5 percent (168) was taken for the sample survey representing samples from all 7 different major space uses. Population density was calculated for the sampled building floors according to space uses for different time periods of the day, and based on these sample calculations the population for each building of entire ward was estimated. Actually it is difficult to indicate the actual population present in an area because it depends on the time, both of the day and for the year. But roughly speaking the average population calculated for ward number 20 was 16,380 with a population density of 910 persons per hectare. In average 5 persons live in a household.

The population distribution in different types of space uses is presented in the table 3-4. About 55 percent (8,971) of the population is living in the ward predominantly in the residential floors. This population can be matched with the total population calculated by CBS as it counts only the residential population. However this figure is still higher than the figure presented by CBS (6,519). It is because, even from residential buildings CBS counts only the people actually belonging to the respective building, whereas present study has calculated all people living in the residential building (also rented). Further this figure of CBS was according to 2001 census but present study calculated the population based on the field survey conducted on September 2005. The average population in educational institutes including hostels and class rooms is estimated 6, 816. This figure seems to be high but it is possible because of incoming number of students in colleges and higher secondary schools located in the ward. Further the use of the floors within a single building was found different and the distribution of population accordingly (See Annex 3- 8).

As mentioned in the methodology, the half floors often present at the top of the buildings were considered by half the population as compared to a complete floor of the same building. About half of the total residential population were estimated to live in the lower three floors.



30

Table 3-4: Distribution of population by main building uses

Space Use Population Percentage Residential (RH) 8971 54.8 Institutional (Ins) 348 2.1 Industrial (Ind) 120 0.7 Commercial shops (CS) 632 3.9 Hotel/restaurant (CHR) 140 0.9 Public facilities (PF) 353 2.2 Education class rooms (EDUsc) 3450 21.1 Education residential hostels (EDUrh) 2366 14.4 Total 16,380 100

3.3.1.2. Temporal distribution of population

Earthquake may occur at any time and the number of people present in the building may vary considerably. Since building collapse is the main cause for casualties, information on the number of people inside the buildings when the earthquake occurs is necessary for casualty estimation. The current study has estimated the population for the study area for different time periods of the day i.e. morning (6:00 am to 9:00 am), day (9:00 am to 5:00 pm), evening (5:00 pm to 8:00 pm) and night (8:00 pm to 6:00 am).

The population living in a particular building in different time period obviously depends on the type of use of that building. Figure 3-8 presents the population for the 4 time periods dividing the urban land use in two broad categories i.e. residential and non-residential. In the residential class single houses, apartments and school hostels were included and all other land use classes were considered as non-residential buildings (See Annex 1-5). The figure has clearly shows that residential buildings contain more population in the morning than evening, night and day respectively, where non-residential buildings contain more in day and less in other times. The total population present in the ward was highest (17,826) in the time of morning and lowest (14,225) at the night time. The overall temporal distribution of the population in the study ward is presented in the figure 3-9.

0

2000

4000

6000

8000

10000

12000

14000

Num

ber of

pop

ulat

ion

Morning Day Evening Night

Time periodsResidential Non-residential

Figure 3-8: Temporal distribution of population in residential and non-residential buildings



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Figure 3-9: Overall temporal distribution of population

Going more in detail, it was found that the population living in single houses was lower then in apartment buildings. The educational buildings, especially the class rooms were found with lower population in the morning, evening and almost empty at night but if they are hostels, it was the other way around, with a large number of people at night.

School buildings (Class room)



32

In case of the other types of non-residential buildings i.e. commercial, public facilities, office/institutions, they are occupied by a large population during day time but very little at night. Generally education and office buildings are closed on Saturday and obviously there will be a very low population in those buildings on that day. The same happens on the government holidays i.e. in festivals when only the security personnel will stay in those buildings (See Annex 3-6).

3.3.2. Socio-economic characteristics

Based on the household surveys for the sampled buildings, the study managed to capture some socio economic information for the entire study area. The following sections present the socio economic characteristics of the study area.

3.3.2.1. Age and gender composition

Population vulnerability to an earthquake may also be controlled by the age and gender composition of the population. So, to estimate the population vulnerability, there is need of information on age and gender composition of an area. This study has tried to get information also in these aspects. Mainly five age groups were made considering their activities and knowledge level i.e. <5 years (children, totally dependent), 6-13(secondary school level, can be used for knowledge transformation in household level), 14-18 (higher secondary level, can be used as volunteers) 19-59 (active age and supposed to be stronger to cope with an earthquake than other age groups) and >60 (old age, might need physically support from others).

As mentioned in chapter 1, 131 households were surveyed during the field survey. Out of 660 persons in the sampled households, 55 percent were male and 45 percent were female. More than 67 percent were in 19-59 age group. Population in the age group less then 5 years and more then 60 years were 4 percent and 6 percent respectively (See Figure 3-10).

0

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400

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Num

ber

of p

opul

atio

n

<5 years 6 to 13 14 to 18 19 to 59 >60Age group

Male Female Figure 3-10: Age and gender composition of population

3.3.2.2. Ethnic groups and language

The population of LSMC is composed of many ethnic groups such as Newar, Brahmin, Chhetri, Gurung, Rai, Limbu, etc. However, Newar is the major ethnic group occupying 50 percent of the total population of LSMC (CBS, 2004). Since the study area is a part of the very old Newar settlement,



33

about 84 percent of the total surveyed population were found Newars followed by Chhetri/Brahman with 12 percent. The rest of the ethnic groups in the study area are Gurung, Magar, Rai, Limbu and others (See Figure 3-11).

Newar84%

Brahman/Chhetri9%

Gurung/M agar2%

Rai/Limbu2%

Other1%

No response2%

Figure 3-11: Population by ethnic groups

Although the official language in the whole kingdom is Nepali, there are different languages

spoken by several ethnic groups in different parts of the country. In the study area about 78 percent of the total population speaks Newari as the mother tongue followed by Nepali and the rest of the population use other languages i.e. Gurung, Magar, Rai, Limbu, etc. During the survey about 5 percent of the sampled households didn't respond about the language (See Figure 3-12).

Nepali15%

New ari78%

Other2%

No response5%

Figure 3-12: Population by mother tongue

3.3.2.3. Religion

According to the CBS census about 68 percent of the total population are Hindu and 27 percent Buddhist (CBS, 2004).. Almost the same figure was found in the study area, i.e. about 69 percent of total sampled house holds reported as Hindu and 27 percent as Buddhist during the field survey. About 4 percent of the households didn't respond on religious aspect (See Figure 3-13).



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No response4%

Buddhism27%

Hinduism69%

Figure 3-13: Population by religious group

3.3.2.4. Education

LSMC has a literacy rate of 81 percent, which is higher then the national urban literacy rate, 71.55 percent and far higher than the national literacy rate of 54.1 percent (LSMC, 2005).

The educational attainment or the maximum schooling passed of the literate population in the study area is presented in figure 3-14. Out of a total people from the sampled households, about 54 percent have secondary and higher secondary education, more than 28 percent have higher education i.e. graduate and above, 16 percent have below secondary and 2 percent of population have vocational education (See Figure 3-14). In all levels of education, female representation was found a bit lower in comparison to males.

Below Sec.16%

Sec/Higher Sec.54%

Higher education

28%

Technical vocational

2%

Figure 3-14: Population by education level

3.3.2.5. Economy

The most important source of income in LSMC is business. More than half (50.5 %) of the total income is generated from business, followed by services (24.2%). Other categories include remuneration from transitional employment, which is also a major source of income, contributing 12.6 % of the total. Agriculture contributes only about 7 percent, while industry contributes the least with 5.8 % (LSMC, 2005).



35

Lalitpur, being one of the historical cities of Nepal, has been a favourite destination for tourist visiting Nepal. Known for its art and craftsmanship, the business related to traditional handicraft has seen a boom with huge orders received from several foreign countries. The city has become a trade centre for these traditional products. Having a location at core area and dense settlement the study area also enjoys very good trade activities. But the trade in this area are not very large; most of them are small scale running at ground floor of residential houses.

Public_govt12% Manifacturing

4%

Service23%

Trade47%

Agroforest0%

Construction4%

Others10%

Figure 3-15: Occupational structure of population

As shown in figure 3-15, out of total respondents more than 46 % were engaged in trade

followed by services (23.5 %). Since it is almost core and commercial area, no people were found to be engaged in agriculture. Likewise, out of 213 job holders from the sampled households, 39 % were found having fixed income type of job and the rest have variable income type of job. Male representation in job holding is higher then female.

Since the present study aims to estimate human casualties due to earthquakes and to seek methods for community based risk reduction, activities of population in the community is need to be taken in to account. The activities of the population in the study area by age and gender are presented in Annex 3-7.

3.3.2.6. Travel between wards

The number of people present in the ward may be very different from day to night also because of commuting people from other wards. Since LSMC is well connected to other municipalities of the valley, the mobility of the population is significantly high. The current study ward is small in area and has no important offices/institutions, large commercial activities and enough agriculture fields. Hence its residents usually work in other wards or in neighbouring municipalities and Village Development Committees (VDC). For the current study, mainly the work and study places were divided into four categories considering the spatial distance. It was done considering their presence at the distance from the ward during an earthquake. During the field survey it was found that work/study place was closely related to age group. Almost all from age group of below 5 and above 60 are present mostly in the same ward, while from the other age groups, the majority is working or studying outside the ward. From the 19-59 age group more than half the population works or studies outside the ward, were out



36

side the valley and some of them even out of the country. While as the age goes towards middle, the number of population outgoing from the ward increases (See Annex 3-9).

3.4. Summary

This chapter was an attempt to give an overview of the study area and the data prepared during the study. The building footprints were based on field observation, however without detail measurements and also the inventories were made through visual observation and limited interviews. The socio-economic and information about public awareness information was collected through household surveys in a 5 percent of the total building floors. The building footprints and building inventories were used for estimating the number of damaged or collapsed buildings. The result from the household survey was used for the estimation of population casualties and for the measurement of public awareness, preparedness and capacity. An overview of the collected themes is presented in figure 3-16.

Figure 3-16: Database generated during the current study



37

4 Building Vulnerability Assessment

4.1. Introduction

One of the major objectives of this research is to estimate the building damage/collapse probability due to earthquake in the study area, ward 20 of LSMC. Building vulnerability to earthquake highly depends on the building characteristics, such as age, construction materials, height, structural elements and existing condition in addition of earthquake intensity and the geology of the site. Therefore the current study has incorporated these building characteristics for the estimation of building damage in addition to the use of existing building damage matrix, which considered only building type, building height and earthquake intensity, prepared for Kathmandu Valley by NSET and JICA (2002). The details of the building parameters are presented in chapter 3.

4.2. Building damage matrix

Depending on the earthquake intensity and the building strength, a building may suffer damage during an earthquake ranging from fine cracks in plaster to the completely collapse of the building. When the earthquake intensity is considered constant, the damage grade is then directly related to the strength of a building, which again is related to the material and construction type (JICA, 2002). The building inventory report by NSET divided the buildings of the Kathmandu Valley in seven major classes considering their seismic vulnerability. However the current study has divided the buildings of study area in only five classes. It was because the buildings in the class "Stone" of NSET's building inventory were not found in the current study area and further the classes "Brick with Mud Mortar, Poorly Built" and "Brick with Mud Mortar, Well Built" were not separated (they are included in other parameters of the buildings for the current study). Thus the buildings were classified in five classes as presented in chapter 3 (See also Annex 1-5).

Table 5-2 shows the maximum and minimum probability that an individual building will be damaged or will collapse for different earthquake intensities (in MMI) and for different building types in the study area (See Annex 2-1 for MMI scales). This relation has been derived from NSET and JICA considering the fragility curves prepared during the earlier building code project with some modifications based on the damage pattern observed in the 1988 earthquake in Nepal. As JICA (2002) mentioned, the building damages grades partial damage and total collapse indicate reparability and un-reparability respectively. The original building damage matrix addressed only the building height, types and earthquake intensity, and indicates a range of values which indicate the percentage of buildings within the given class that might be damaged/collapsed (See Annex 4-1). These values may differ considerably, as there may be different quality buildings within the same class. In this study these percentage values are used to indicate the probability of damage and/or collapse of individual buildings, in order to be able to later combine it with population data and come to reliable population loss estimation. In order to be able to do that the damage matrix was interpreted as showing the maximum, minimum and average probability of damage or collapse of individual building in different intensity of earthquakes (Table 4-1). For an individual building this probability might be closer to the minimum or the maximum value, depending on the characteristics of the individual building such as geometry, age, building condition, etc. This will be further explained in the next section.



38

Table 4-1: Damage probability matrix for different types of building

Note: Modified from existing damage matrix prepared by NSET and JICA (Modified for the

individual buildings considering other building parameters in addition to building height and types)

4.3. Multi-criteria analysis of other building parameters

The most important effect of an earthquake is ground vibration affecting buildings. A study which reviewed 26 of the most important earthquakes of the 20th century, occurred in 24 countries from most parts of the world, concluded that many of the higher casualty counts were caused by the collapse of buildings made of heavy, weak materials such as un-reinforced masonry or earth (Dowrick et al., 2003). Therefore, before estimating the human casualties, it is important to know their characteristics. For the current study the building damage estimation is carried out in individual building level so that it is possible to indicate the probability of suffering damage or collapse of an individual building in the study area. This is different from the previous study by Guragain (2004). The present study also considered other building characteristics in order to define if the particular probability for damage or collapse of a single building is closer to the minimum or the maximum of the group of buildings to which it belongs. In order to do this, weights were assigned to the building characteristics according to their contribution for vulnerability (See Annex 4-2 for the weight assigned), and also weights were assigned to the major components using a pair-wise method. For example, within a component of a building "geometry", three classes i.e. Regular <=1:3, Regular > 1:3 and irregular were assigned the weights 0 (no vulnerable), 0.5 (medium vulnerable) and 1(high vulnerable) respectively. And the geometry itself was assigned the weight comparing with other parameters of the building.

For the comparison between parameters no engineering analysis was carried out. It was just an educative judgement based on researcher's knowledge and experience in the local situation. So the comparative weight values between parameters may be different by other researches. As shown in the table 4-2 all the parameters were compared each others. In the table, value "1" means a parameter has less importance in comparison of other, "2" more importance and "0" denotes the same or no comparison. Finally the individual scores were summed and final weights for each parameter were received. This weight ranges from 0 to 1 i.e. wall cracks (0.121), floor cracks (0.115), lintel band



39

(0.103), age (0.061), soft storey (0.073), upper partial floors (0.067), etc., higher the weight shows more important for the vulnerability (See Table 4-2).

Table 4-2: Comparison of building parameters

Building Parameters

Age

Wal

l cra

cks

Floo

r cra

cks

Dam

pnes

s

Plin

th b

and

Lin

tel b

and

Roo

f ban

d

Gab

le b

and

Geo

met

ry

Soft

sto

rey

Part

ial f

loor

Tot

al w

eigh

t

Fina

l wei

ghts

Age 0 1 1 1 1 1 1 1 1 1 1 10 0.061 Wall cracks 2 0 2 2 2 2 2 2 2 2 2 20 0.121 Floor cracks 2 1 0 2 2 2 2 2 2 2 2 19 0.115 Dampness 2 1 1 0 2 2 2 2 2 2 2 18 0.109 Plinth band 2 1 1 1 0 1 2 2 2 2 2 16 0.097 Lintel band 2 1 1 1 2 0 2 2 2 2 2 17 0.103 Roof band 2 1 1 1 1 1 0 2 2 2 2 15 0.091 Gable band 2 1 1 1 1 1 1 0 2 2 2 14 0.085 Geometry 2 1 1 1 1 1 1 1 0 2 2 13 0.079 Soft storey 2 1 1 1 1 1 1 1 1 0 2 12 0.073 Partial floor 2 1 1 1 1 1 1 1 1 1 0 11 0.067 Total weight 165 1.000

Later, the individual parameters of the buildings were multiplied by the respective weights and summed. In this regard the buildings with the vulnerability of less than 20 percent were considered as low vulnerable, those with a vulnerability between 20 to 50 as medium and those with a vulnerability of more than 50 were considered as highly vulnerable, considering that the conditions of the buildings in the study area are poor and if they have a vulnerability of more than 50 percent they are more vulnerable to an earthquake. And finally this range of vulnerability (received from other building parameters) was used to define the probability of damage or collapse of an individual building in reference of building damage probability matrix (Table 4-1). It will be treated in detail in the next section.

Considering only these parameters of the buildings (excluding building floor height and type, which are to be considered in the building damage matrix), the old closely spaced buildings mainly in the northeast part of the study area, found most vulnerable to earthquake. Relatively newly constructed buildings in the western part of the area are not highly vulnerable. However this result has not considered any particular earthquake intensity (See Figure 4-1).



40

Figure 4-1: Building vulnerability considering building condition

4.4. Building vulnerability

For the building loss estimation in the current study area, previous studies under the SLARIM project by Guragain (2004), Khanal (2005), Piya, (2004) and Destegul (2004), were reviewed as well as a series of studies by NSET and JICA in Kathmandu Valley and other relevant researches. Guragain (2004) has made the estimation of building collapse/damage for the homogenous units of LSMC considering different potential earthquakes scenarios. He used the earthquake scenarios in the Lalitpur area from the earlier research carried out by JICA (2002). Except some river flood plains, the whole LSMC including the current study area falls in the moderate susceptibility class according to the liquefaction susceptibility map produced by Piya (2004). Since liquefaction doesn't seem to have a clear role in the various earthquake loss estimation methods which were reviewed, it was excluded from the current study area, and only the earthquake intensities were considered.

4.5. Earthquake scenarios

Guragain (2004) has used three possible earthquake scenarios for building damage estimation in LSMC. Since the current study area is one of the 22 wards of LSMC, the same scenario earthquakes are assumed in this study. The scenarios used by Guragain were derived from JICA, who did the study on earthquake loss estimation for the entire Kathmandu Valley. Based on these works the study area falls in intensity zone VIII considering the Mid Nepal and Kathmandu Valley Local Earthquake scenario. Since the Mid Nepal earthquake scenario is considered to be a huge earthquake similar to the 1934 earthquake occurring in the seismic gap, the middle of Nepal, it was chosen instead of the Kathmandu Valley Local Earthquake scenario. It was chosen also because many experts have made remarks that the active fault taken as the source for Kathmandu Valley Local Earthquake has no clear evidences that it is able to generate significant earthquakes and has no neotectonic evidences (Experts from DMG). According to one of the other earthquake scenarios taken by JICA, which is the more



41

frequently occurring middle level North Bagmati Earthquake, the study area falls in intensity zone VII (JICA, 2002). The calculated Modified Mercalli Intensity (MMI) for the study area considering a scenario similar to the 1999 Chamoli Earthquake is VI (Khanal, 2005). However the current study decided to estimate building damages losses in the study area considering three possible earthquakes then others i.e. North Bagmati (MMI VII), Mid Nepal (MMI VIII), and assumed (MMI IX).

4.5.1. Building loss estimation

The probability of building damage and collapse is calculated in several steps. First, individual buildings are identified in three different vulnerability levels (high, medium and low) considering only the building characteristics, and existing conditions (before calculating the damage and collapse using damage matrix prepared by NSET). Then these levels of vulnerability are considered in the building damage probability matrix (modified from previous damage matrix prepared by NSET and JICA) to differentiate the range of damage and collapse probability for individual buildings (See Table 4-2). The damage matrix prepared by NSET addresses the percentage of the building damage/collapse from a group of buildings of an area. However, in the current study these percentages of building damage/collapse are assumed to be the probability of being damaged/collapsed of the same type of building in the case of individual buildings. The probabilities of building damage/collapse were calculated taking into account the vulnerability levels calculated from other building characteristics and conditions. Thus if the vulnerability level of a building was high then the upper range from the damage matrix was picked up, if it was medium then middle value of the range and if it was low vulnerable then lower value of the range was taken as the probability of damage/collapse of that particular building.

Table 4-3: Building collapse/damage probability due to different earthquake scenarios

Earthquake scenarios Assumed (MMI_IX) Mid Nepal (MMI_VIII)

North Bagmati (MMI_VII)

Collapse Damage Collapse Damage Collapse Damage Probability of damage/collapse

Building type Number of buildings

AD 0 0 0 0 2 2 BM 0 0 0 0 143 143 BC 61 0 234 0 234 220 RCC3 179 0 212 179 212 212 RCC4 188 0 272 188 272 272

<0.2

Total 428 0 718 367 863 849 AD 0 18 17 18 16 16 BM 10 252 252 252 109 109 BC 173 61 0 234 0 14 RCC3 33 212 0 33 0 0 RCC4 84 188 0 84 0 0

0.2-0.5

Total 300 731 269 621 125 139 AD 18 0 1 0 0 0 BM 242 0 0 0 0 0 BC 0 173 0 0 0 0 RCC3 0 0 0 0 0 0 RCC4 0 84 0 0 0 0

>0.5

Total 260 257 1 0 0 0

The probabilities of building damage/collapse are estimated in two levels i.e. collapse and damage (See table 4-5 and Table 4-2). Where, damage refers to the probability of being partially



42

damaged of a particular building (reparable) and collapse refers to the probability of being complete damaged (non-reparable). The rate of damage is caused mainly by the weakness of building types such as earthen-mud, stone and adobe in the study area.

0

20

40

60

80

100P

erce

ntag

e of

bui

ldin

gs

Earthquake intensities

Low 43 0 73 37 87 86

Medium 30 74 27 63 13 14

High 26 26 0 0 0 0

Collapse Damage Collapse Damage Collapse Damage

Assumed (MMI_IX) Mid Nepal (MMI_VIII) North Bagmati (MMI_VII)

Figure 4-2: Building collapse/damage probability for each earthquake scenarios

As shown in table 4-5 and figure 4-2, if the study area experiences an earthquake with intensity IX, 26 percent (260 out of 988) have the high chance (>0.5 probability) of collapsing and more than 26 percent (257) buildings have high probability of being damaged. No buildings are found with low probability of being damaged in the area. Most of the buildings with high probability of collapse are from northeast part of the study area (See Figure: 4-3). Buildings in this area are found relatively higher, old and have poor existing conditions (building with visible wall cracks and no structural bands etc.).

Figure 4-3: Building collapse/damage probabilities in intensity IX earthquake

Buildings with high

probability of collapse



43

If the area experiences an intensity VIII produced by the Mid Nepal earthquake, more buildings (73 %) have a low probability (<0.2) of collapsed (See Figure 4-4). Only one building was found with a high probability of collapse in this earthquake scenario and no buildings with high probability of getting only damage. It means that most of the buildings have low and medium probability of getting damage and only one building that completely collapses.

Figure 4-4: Building collapse/ damage probability for Mid Nepal earthquake scenario (intensity VIII)

The third building damage scenario, with an intensity VII (North Bagmati Earthquake) is

expected to produce a damage and collapse scenario quite different from the above two earthquakes. In this earthquake scenario most of the buildings have low and medium probability of getting damaged and collapse (See Figure 4-2 and 4-5). No buildings have high probability of collapse and damage. More than 85 percent of the buildings have a probability of less than 0.2 to be damaged and collapse. Some buildings from the north east part of the ward have a 0.2-0.5 probability of collapse and damage (See Figure 4-5).

Figure 4-5: Building collapse/damage probability for North Bagmati earthquake scenario (intensity VII)

Building with high

probability of collapse



44

4.5.2. Building damage by types

The building damage/collapse probability highly differs according to the building types in the study area (See Figure: 4-6). The adobe (AD) buildings have high probability of being collapse compared to other building types followed by brick in mud (MB) and brick in cement (BC) buildings. The reinforced concrete frame with masonry (RCC) buildings are stronger than other types of buildings but three or less then three storey buildings (RCC3) have less probability of getting damaged or collapsing than those of four or more than four storeys (RCC4). The building type "brick in cement" has more probability of getting damaged than adobe and brick in mud. But simultaneously the adobe and brick in mud buildings have much higher probability of collapse.

Figure 4-6: Probability of building collapse/damage by their types

4.6. Conclusion

This chapter was an effort to estimate the probability of suffering damage and collapse of individual buildings. Although it used the existing damage matrix prepared by NSET and JICA, which was made for groups of buildings, an additional effort was made to consider other building characteristics to make a differentiation within the range of values indicated in the matrix. Unlike the existing damage matrix, the collapse or damage rate of a building highly depends on its condition and other building components in addition to floor height and types. It is important to state here that the approach which was followed is only an assumption, and has clear drawbacks. The behaviour of individual buildings under an earthquake is a highly complicated matter, which is the domain of earthquake engineers. In fact a series of detailed vulnerability curves should be made for many more different typical buildings, based on finite element modelling. Each of the individual building then should be classified in one of the tested building classes. However, this approach is very time consuming and requires technical expertise which is out of the scope of this study.

Taking into account the other building characteristics in addition to the building height and standard types the building damage estimation for the study area was made assuming different possible earthquake intensities defined by previous research/studies. These results show that most of the buildings have a high probability of damage and even collapse by a strong earthquake with an intensity of VIII and IX in the study area. Mainly the buildings in the north east part of the study area were found to be most vulnerable even for relatively small intensity earthquakes. As shown in figure 4-7, this area presents the worst combination of building characteristics (relatively old adobe and brick in mud buildings, buildings with relatively more floor-heights, and already in poor conditions).



45

Figure 4-7: Building collapse probability according to building characteristics



46

5 Casualty Estimation

5.1. Introduction

Loss of human lives and injuries are the most important consequences of earthquakes, and hence the effort of vulnerability reduction has the priority to keep the number of casualties to a minimum (NSET et al., 2002). As one of the major objectives, this study has estimated the casualties for the study area considering the building vulnerability due to different earthquake intensities.

This chapter mainly deals with the estimation of casualties due to different earthquakes in different severity levels for different time periods of the day. The casualties are estimated using an empirical relationship, developed by HAZUS, between population distribution and building damage or collapse probability due to different earthquake intensities, which will be discussed in the next section.

5.2. Human casualties due to earthquake

As mentioned earlier, the current study only estimates the casualties that occur indoors as a result of building collapse or damage. Thus the casualty estimation depends on the building vulnerability. In the previous chapter the probability of damage and collapse for individual buildings was estimated, whereas in this chapter the casualties are estimated for individual buildings and for four different time periods of the day. For the estimation of casualties the building vulnerability obtained from the previous chapter, temporal distribution of population and casualty ratio with respect to building damage/collapse are used. The casualty ratio was derived from the previous study by Islam (2004) which had basically been developed by HAZUS-MH (2003). It is based on the assumption that there is a strong correlation between building damage (both structural and non-structural) and the number and severity of casualties. In smaller earthquakes, non-structural damage will most likely control the casualty estimates. In severe earthquakes where there will be a large number of collapses and partial collapses, there will be a proportionately larger number of fatalities (HAZUS-MH, 2003). Obviously the situation of the current study area is different from the situation in the United Stats of America. So, there should be some modification in the calculation, even in the ratios used. Before going to the details of calculation, some aspects should be clarified including the term casualty itself (Islam, 2004). For the current study, the term casualty refers to human injuries, from slight injury to highest fatality that is instant death. There are indicated in four severity classes (See Table 5-1).

5.3. Casualty estimation

The type of building construction is a major factor controlling the number and severity of injuries due to earthquakes. Statistics for the period 1950-1990 show that the greatest proportion of victims dies in the collapse of masonry buildings (Coburn, 1992 cited in (NSET et al., 2002). It is because generally these buildings have heavy roofs and walls. However there are many factors that may increase or decrease the casualties due to earthquake i.e. individual attitude, preparedness, awareness, age, sex, economy and even the socio-cultural back ground etc.

Since the present study area falls within the area studied by Islam (2004), the percentages of severity and injury levels have been directly adopted from his study for the calculation of casualties.



47

The following table provides a straight casualty rates that have been used by Islam, which were basically developed by HAZUS-MH (2003).

Table 5-1: Injury severity levels description

Building Damage Level Injury Level (in %)

Injury Level (in %) Severity 1 Severity 2 Severity 3 Severity 4

Partial Damage 1 0.1 0.001 0.001

Complete Damage 40 20 5 10

Source: Islam, 2004 Where, Severity level 1: Minor injuries requiring basic medical aid. Severity level 2: Injuries requiring a greater degree of medical care and use of medical technology

such as x-rays or surgery, but not expected to progress to a life threatening status. Severity level 3: Injuries that pose an immediate life threatening condition. Severity level 4: Instantaneously killed or mortally injured.

Building damage and collapse probabilities estimated in chapter 4 and the temporal distribution of population estimated from the field survey (Please refer chapter 3) were used for the casualty estimation. For each case (building damage and collapse) casualties were estimated for four different severity levels and for different time periods of the day (morning, day, evening and night). Thus, the casualties due to different earthquake intensities depend on the damage/collapse probability of the building and the number of persons present in that building following the injury ratios given in table 5-1. The casualty calculation can be expressed in the following formula:

C=PBd*Pop*Irt

Where,

C= Casualties (in each building)

PBd= Probability of building damage or collapse in a given earthquake intensity

Pop= Population present in the building at a given time (morning, day, evening or night)

Irt= Injury ratios in different severity levels

The overall casualty estimation for any given earthquake scenario at any given time period would be the sum of the casualties of all the buildings in the ward.

5.4. Casualties due to different earthquake scenarios

The current study has made an effort to estimate the casualties for different severity levels and different times of the day assuming different possible earthquakes in the study area (See Table: 5-2). Two cases of building vulnerability were taken i.e. building collapse and damage. Calculated casualties were more in case of building collapse then in building damage. The logic behind this is, there is less chance to escape from the building in case of the complete collapse of the building where the victim living in, then in case of damage.

In general the casualties of all severity levels by all scenario earthquakes were smaller during the day than in the morning, evening and night respectively (See Table: 5-2 and Figure 5-1). It was due to different number of people present in different time according to the use of buildings. The majority of the buildings were found of residential types in the study area which were found highly occupied in the morning, evening and night then at day time. Moreover there are more people in the



48

morning and evening (time periods of 6:00-9:00 am and 5:00 pm-8:00 pm respectively) because more people are work/studying outside of the ward in the day time. The reason for a lower population at night than in the morning and evening would be the people from other wards working in the commercial shops, who would go to their place after closing the shops i.e. in late evening and open early morning.

Table 5-2: Casualties due to different earthquake intensities

0

200

400

600

800

1000

1200

1400

1600

1800

2000

Num

ber

of c

asua

lties

Sev

erity

1

Sev

erity

2

Sev

erity

3

Sev

erity

4

Sev

erity

1

Sev

erity

2

Sev

erity

3

Sev

erity

4

Sev

erity

1

Sev

erity

2

Sev

erity

3

Sev

erity

4

MMI IX MMI VIII MMI VII

Earthquake intensities

Morning Day Evening Night

Figure 5-1: Casualties due to different earthquake intensities

Table 5-2 and figure 5-1 have provided the calculated casualties assuming different possible

earthquakes in the study area in different time periods of the day. As the buildings are occupied by more people in the morning the highest numbers of casualties, 1870 (about 11 percent of total population of the ward) of severity level 1 i.e. minor injuries were calculated in the morning due to intensity IX earthquake. But if the same earthquake occurs at day time 1602 casualties of same level were calculated. About 470 and 401 casualties of severity level 4 (instantaneously killed or mortally



49

injured) were calculated for morning and day time respectively. Likewise the number of casualties from minor injuries to serious injuries and dead are calculated decreasing rapidly for lower earthquake intensities. No casualties of high severity were calculated by the building damage in any of the scenarios. Spatial representations of casualties of severity level 1 and 4 due to possible earthquakes assuming at day and night, are provided in figure 5-2, 5-3 and 5-4.

Maps of estimated casualties of severity level 1 (minor injuries) and 4 (mortally injuries i.e. dead) in ward 20 of LSMC assuming a possible earthquake with intensity IX during daytime and night-time are presented in figure 5-2. It was found that a high number of casualties in day time were from the school/college buildings, where the day-classes are running (some of them are marked with red circles in the figure). Some of the school buildings have possibilities to have about 50 casualties of severity one and 10 to 20 of severity 4 alone. The other non-residential buildings also suffer much higher casualties during day than in night-time. At night most of the residential buildings including residential school/hostels were found to have more casualties. Some of the other buildings that have a low probability of collapse and are occupied by less or no people have no casualties.

Figure 5-2: Casualties of severity level 1and 4 due to intensity IX earthquake (assumed)

The casualty number for one of the other possible earthquakes, Mid Nepal Earthquake with intensity VIII in the study area are in the figure 5-3. As the casualties are calculated on the basis of

Schools (class rooms)

Severity Level 1 -Day Severity Level 1 -Night




50

building collapse probability and number of people presence in that building at the time of an earthquake, the number of casualties has decreased as the scenario earthquake is comparatively with a lower intensity than the previous one (intensity IX). But still some of the school buildings (class rooms) hold more than 20 casualties of severity level one during daytime and by the residential school-hostels at night (See Figure 5-3). However many more buildings with less than 5 casualties are calculated in this earthquake. Most of the residential buildings have less than 5 casualties at day and night. However as in previous earthquake the casualties are fewer in day than night.

Figure 5-3: Casualties of severity level 1 and 4 due to Mid Nepal earthquake scenario (MMI VIII)

The North Bagmati earthquake scenario is relatively small in intensity (VII) and as the building collapse probability is not so high, thus casualties due to this earthquake are not high. Only some school buildings, which are clearly seen in the map, have 6- 10 casualties and most of the other buildings have less than 5 casualties in daytime (See Figure 5-4). At night too the same scenario


Severity Level 4-Day Severity Level 4-Night

Severity Level 1-Day Severity Level 1-Night



51

appears except for one school-hostel building with 11-20 casualties. Moreover, the casualties of severity level 4 are less than due to other earthquake scenarios. Most of the buildings have no casualties of severity level 4. Even the casualties of severity level 1 are found less then 5 in many buildings. Some of the school buildings in the daytime, and some school-hostels buildings and rare of other buildings at night time have 1 to 5 casualties of severity level 4.

Figure 5-4: Casualties of severity level 1 and 4 due to North Bagmati earthquake scenario (MMI VII)

5.5. Casualties by building types

As the widely realized saying in the field of earthquake, "Earthquakes do not kill people-unsafe buildings do", the people living in the vulnerable buildings have more probability to suffer injuries of high severity. Again the building vulnerability is highly dependent on their types along with other factors. In the case of current study area, the building vulnerability, in general, can be estimated by






52

considering building types. During the current study an effort was made to correlate the human casualties with the type of buildings. Though the recent trend is to construct RCC buildings, still there are many buildings made of adobe and brick with mud mortar (please refer chapter 3 for detail). Most of the adobe and brick in mud buildings are used for residential purposes. However some of them were found to be used also as non-residential i.e. schools.

In the case of an earthquake with intensity IX, almost 95 % buildings of adobe were found with high probability of collapse. The brick with cement mortar and RCC buildings were safer in comparison with adobe and brick in mud; most of them were found with medium and low probability but within RCC, the buildings with four or more storeys were found more vulnerable than 3 or less storey buildings. Only 18 adobe buildings holding 211 people in day were found in the study area. It was calculated that about 23 and 6 percent of the total population living in adobe buildings suffer injuries of severity level 1 and 4 respectively if there is an earthquake with intensity IX in a daytime. In the case of other types of buildings, 22 percent population of the brick in mud buildings, 8 percent of the brick in cement buildings, 8 percent of the RCC four or more than four storey buildings and 6 percent of the RCC less or equal to 3 storey buildings were found to be injured of severity level 1 (See Annex 5-1). The estimation: 6 percent of the total population living in adobe buildings getting injured of severity level 4 i.e. mortally injured, gives the message that though there are few people living in adobe and brick in mud buildings, the probability of getting injured of the people living in those buildings is much higher then the people living in other buildings (See Figure 5-5).

0.00

0.05

0.10

0.15

0.20

0.25

AD BM BC RCC3 RCC4

Building types

Pro

babi

lity

of c

asua

lties

Severity 1 Severity 4

Figure 5-5: Probability of casualties by building types

5.6. Casualties by the use of buildings

The use of the buildings is the determinant factor for the number of people present. However the time always comes together with the use of building for the presence of people. As mentioned in the previous sections the number of people present in a particular building depends on the use of that building and time. The same building sometime may be full of people and sometime totally empty. For instance if it is a school-class room building then it would be full at day time but empty at night.



53

But if the same building is a residential school-hostel then the presence of people would be other way around. Hence an earthquake with same intensity occurring in different times i.e. at day and night may have heavy casualties in one time and zero in another according to the use of the buildings.

0

200

400

600

800

1,000

1,200

Num

ber

of c

asual

ties

Severity levels

Residential 715 1175 179 294

Institutional 74 26 18 7

Industrial 36 9 9 2

Commersial shops 70 81 18 20

Educational/class 497 0 124 0

Education/ hostel 142 298 35 74

Public facility 55 11 14 3

Hotel/resturant 13 8 3 2

Day Night Day Night

Severity 1 Severity 4

Figure 5-6: Casualties by the use of buildings due to intensity IX earthquake

During the study it was remarkably noted that the use of building was the most important factor for the casualty estimation. Therefore only the number of the buildings and earthquake intensity would not be the best way for the estimation of casualties. A clear picture of casualties by the use of buildings in different severity levels in different times due to an earthquake with intensity IX is presented in figure 5-6. Though there were only 3 percent buildings (33 out of 988) used as school class rooms, they hold more than 30 percent of total casualties if an earthquake occurred at the time of day (please refer chapter 3 for details on use of the buildings); but in case of same earthquake at night, no casualties were calculated in those buildings as they have zero population at night. Obviously as the residential buildings are more in number, the total casualties were found to be more for them in both time i.e. day and night. However, within them the casualties at night time were found nearly double in comparison of the daytime. Likewise it was interesting to calculate that only 2 percent of total buildings used as school hostels were found holding 19 percent of total casualties at night (See Annex 5-2).



54

5.7. Socio-economic factors of population vulnerability

The fact is that earthquakes affect the full range of social classes-from royalties to the homeless and apparently, it treats everyone equally. However some are more equal then others! Actually, the poor and socially disadvantaged groups of the society are the most vulnerable to, and affected by, earthquakes, reflecting their social, cultural, economic and political environment. At the household level, poverty is the single most important factor determining vulnerability to earthquakes (NSET et al., 2002).

However the current study could not manage its time for taking into account all socio-economic and demographic factors for the estimation of casualties due to earthquakes rather than building damage probability and temporal distribution of population, though it made an effort to collect detail information on those fields (please refer chapter 3 for detail information).

Assumption would not be failed that the lower the IDH (Indicator of Human Development), the lower will be the mean wealth, the literacy and average health state of the population, which ultimately increase the vulnerability to earthquake.

5.7.1. Age and gender

In the context of developing countries like Nepal, women, in general, have less access to resources and generally have less representation in decision making at all levels. Hence the gender composition of the study area may increase or decrease the estimated casualties. In the case of current study area, about 45 percent of the total population were female. Likewise the age could be another factor. Generally old and children are more vulnerable to earthquake. In the Great Hanshin Earthquake that affected the city of Kobe and its surroundings was very heavily concentrated in older age groups. 53% of the casualties were aged 60 years or older (Wisner, 1998 cited in NSET et al.(2002). During the field survey more than 10 percent population were of age group less than 5 and more than 60 years.

5.7.2. Economy and activities

Poverty is one of the major vulnerability criteria for developing countries which also have an effect on housing that constitute a usually high damage percentage in case of earthquake. However not always, all members in any one income group suffer equally from disaster, nor do they encounter similar handicaps during recovery. "Being poor" is not synonym for "being vulnerable", and "being rich" is not "being non-vulnerable". A well informed and prepared "poor family" may be less vulnerable to earthquake than a "richer family" that is not well informed and well-prepared (NSET et al., 2002). Though in depth exploration of economic condition was not made, only less than 40 percent people were found having fixed income type of job and more than half percent population were dependent on local business. From the age group of 19-59 more than half population were working or studying out of the ward. About 90 percent women were found to be engaged in household activities, they could be considered more vulnerable during an earthquake in residential buildings.

5.7.3. Ethnicity and religion

Minority racial or cultural groups are often marginalized in ways that increase their vulnerability. However the problem of ethnicity alone as a pre-condition of increased vulnerability to earthquake may not be as conspicuous- this aspect needs to be considered together with other components such as class, gender, age, and other factors. The major ethnic group in the study area is



55

"Newar" holding more than 80 percent of the total population, who have their own language, religion, cultural values and traditional beliefs those are also important to consider for the population vulnerability.

5.7.4. Education and awareness

One of the major indicating factors of vulnerability reduction is education and awareness. In the context of risk=hazard*vulnerability/capacity, education and awareness play the major role for capacity development and ultimately would be the major factor to reduce the risk. Regarding the education level of study area, only 19 percent of total population were found holding higher education and rest were secondary, higher secondary, just literate and illiterate. Talking about awareness, more details are given in chapter 6. However the level of awareness in general was found low in the study area.

5.7.5. Provision of infrastructures

Provision of facilities and infrastructure will increase the capacity of people to prepare better for the effects of an earthquake. Provision of media i.e. TV, radio, telephone, news papers etc. will help the people to be informed and updated. Likewise, electricity, water supply, transportation etc. will make easy and confirmed evacuation and rescue during emergency. The provision of high technology i.e. early warning system for earthquakes is still a dream for the developing countries like Nepal. The study area, being a part of Lalitpur city, holds the basic infrastructures like transportation, telephone and electricity, though the quality may not be maintained (please refer chapter 3 for more details).

It is possible to make a population vulnerability index considering the above mentioned population characteristics i.e. age, sex, ethnic group and education, etc. (as the calculation of capacity index in chapter 6) but due to the lack of time and detailed information it was not included in the current study.

5.8. Conclusions

It is important to note that the estimation of casualties was made only on the basis of building vulnerability and temporal distribution of population using empirical relation established by HAZUS. The study has provided the casualty estimates of different severity levels in individual buildings in four different times of the day due to different possible earthquakes. It was found that casualties were highly depending on the time and the use of the buildings. Proportionally more casualties were estimated in school buildings. In residential buildings more casualties were estimated at night then in day but in non-residential buildings, except school class rooms, the case was the other way around.



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6 Measuring Public Awareness, Preparedness and Capacity

6.1. Introduction

Earthquakes can strike without warning and may cause a large amount of losses in a very short period. Since an earthquake disaster is beyond human control, the only way to reduce the risk is increasing the capacity of potential victims to cope with its impact. In general term the capacity is the capability of individuals or communities to reduce the impact during an earthquake, which comes through awareness and preparedness. An aware and informed public is most valuable for preparedness, and both of them are essential for the capacity (Carter, 1991).

6.2. Existing situation

To know the existing situation of public awareness, preparedness and capacity a household survey was conducted by taking stratified samples from 168 building floors (5 percent of the total 3,329 floors) representing both residential and non-residential (school, shop, institution, hotel/restaurant, etc.) floors. Since most of the buildings were found with multiple uses, it was realised that to perform the survey by floors is wiser then by buildings. A total of 131 respondents were interviewed from residential floors and 37 from non-residential floors. Within non-residential floors respondents were selected for interviewing representing from different urban land use types i.e. schools, commercial shops, industries, hotel/restaurants, institutions, etc. (please refer to chapter 1 for details). Questionnaires were designed to receive the information from respondents about their knowledge, attitude and preparedness towards an earthquake and its impact (See Annex 1-2 and 1-3). The received information is presented in the following sections.

6.2.1. Public awareness

For the current study, awareness is defined as the knowledge and consciousness of people to reduce risk from possible earthquakes. In other terms it is a part of the capacity that prepares potential victim to cope with the possible impact of an earthquake. The level of public awareness can be reflected as public knowledge, perception and response. When community people are fully informed about possible impact of an earthquake, and when they have been educated about risk and crisis management plans, they are more aware of the situation and ultimately the impacts of disasters can be substantially reduced.

6.2.1.1. Public knowledge

During the field survey, questions were asked to extract the public knowledge about related to earthquakes. It was experienced that the answers of each question highly depended on the education level and occupation of the respondent.

Most questions were asked to know whether the respondents know the aspects of earthquakes that are very important for risk reduction. About 93 percent of the total 131 respondents from the residential floors and 78 percent out of 37 respondents from non-residential floors knew about aftershocks (See Figure 6-1). But it doesn't mean that they were able to explain and analyse their



57

impacts and so on. It represents all respondents including those who knew what an aftershock is. Likewise, for the earthquake risk reduction, building code implementation is one of the major works of LSMC but only about half of total respondents (50 %) knew about it. Similarly Earthquake Safety Day as a tool for earthquake awareness raising, which LSMC and NSET organize every year, is known by only 47 and 43 percent of the total respondents respectively from residential and non-residential floors. Only about 14 percent of the total respondents from both type floors knew about the aid organizations and rest of the respondents don't know the names of concerning organizations for getting help in case of earthquake.

0

10

20

30

40

50

60

70

80

90

100

Per

cent

of r

espo

nden

ts

Helping organization Earthquake SafetyDay

Building code inLSMC

After shocks

Fields

Residential Non-residential

Figure 6-1 Knowledge about earthquake related matters

Thus as shown in figure 6-1 it was clear that the level of knowledge about earthquake related

matters was not much different between the respondents from residential and non-residential floors. However the respondents from residential floors had slightly higher level of knowledge than from non-residential floors.

6.2.1.2. Information about critical facilities

Regarding the question whether people knew about the location of critical facilities after an earthquake, 96 and 97 percent respondents of the total residential and non-residential floors respectively could indicate the nearest hospital (See Figure 6-2). Likewise, about 95-98 percent knew the location of the nearest police station and 62-65 percent knew about the location of open spaces that could be used during an earthquake. Only 1-11 percent knew the location of a shelter house. The main reason for this is that there was no provision of shelter houses to be used specially during disasters. The respondents, who knew about it, considered the public halls, schools and temples could be used as the shelter houses.



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0

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30

40

50

60

70

80

90

100

Per

cent

age

of r

espo

nden

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Hospital Openspace Shelter house Police station

Fields


Figure 6-2: Information about the critical facilities

6.2.2. Response how to act during an earthquake

In order to know about the level of public awareness in the community, the respondents of the household survey were asked questions to evaluate the knowledge how to react during an earthquake in different situations.

During the survey it was found that more than half of the respondents from both residential and non-residential floors preferred to search for a safe place if they were on the upper floor of a building during an earthquake where about 27-44 percent argued to use the stairs and 2-5 percent argued that it would be wise to jump through the window. About 3 percent of the total respondents from the non-residential floors and no one from the residential floors argued to use elevator. About 3-11 percent didn't want to respond this question or had no idea (See Figure 6-3).

0

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Per

cent

age

of r

espo

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ts

Use elevator Jump throughwindow

Use stairs Look for a safeplace

No response

Responses

Response on upper floor


Figure 6-3: Public knowledge to act during an earthquake on the upper floor of a building



59

In order to evaluate the awareness of possible secondary effects of an earthquake such as fire a question was asked to know their attitude for making light if it is dark after an earthquake. For example if they would use a gas lighter to make light and the gas is already leaking then it may cause a serious fire. In this regard, 54-65 percent would use a flash light, and the rest would use electricity, gas lighter and kerosene lamp (See Figure 6-4).

0

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100P

erce

nta

ge

of

resp

on

den

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Kerosene lamp Gas lighter Electricity Flash light No response

Means of light


Figure 6-4: Means for making light during an earthquake

For the question to know public perception about possible safe places out side the building

during an earthquake, about 94 percent of the total respondents from residential floors and all of the respondents from non-residential floors mentioned open spaces. Some of the respondents from residential floors also argued such as "under a bridge" and "near an electric pole". About 5 percent of them didn’t answer the question or had no idea (See Figure 6-5).

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Per

cent

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Open spaceUnder a tree Under abridge

By anelectricity

pole

Near a tallbuilding

Other Noresponse

Options for safe places


Figure 6-5 Argument about the outdoor safe place during an earthquake

6.2.3. Risk perception

The risk perception may influence the attitude/response of people during an emergency caused by a disaster like an earthquake; and for the long-term it leads the level and pace of preparedness. It



60

may be influenced by many interrelated factors such as past experience, attitude, values as well as social and cultural perspectives (NSET et al., 2002). If people don't perceive that they are living at risk, they don't think there is a need to be prepared.

During the survey one of the questions to evaluate the public perception was whether they think that they were living at risk. It was found that about 80 percent of the total respondent from residential floors and 73 percent from non-residential floors realized that they were living at risk (See Figure 6-6). Likewise, 22-25 percent thought that old buildings also could be made earthquake resistant (retrofitting) and 16-18 percent thought that the municipality was prepared for possible disasters. In other words more than 80 percent of the total respondents thought that the municipality was not prepared for disasters.

0

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perc

enta

ge o

f res

pond

ents

Municipality is preparedfor a disaster

Old buildings could bemade earthquake safe

We are lliving in risk

Perception


Figure 6-6: Public perception about earthquake risk

0

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25

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35

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45

50

Per

cent

age

of r

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God GovernmentMunicipality Myself Mason Engineer Nobody NoresponseResponsibility


Figure 6-7: Responsibility for the loss due to an earthquake

For the question of responsibility for the loss due to an earthquake, about 37 and 27 percent of

the total respondents respectively from residential and non-residential floors argued that nobody was responsible for the loss of property due to earthquakes and 32 percent respondents from the both type of floors blamed the gods. About 15 and 22 percent of the total respondents respectively from



61

residential and non-residential floors realized themselves might be to blame and the rest argued that it was the responsibility of the municipality; masons and the government (See Figure 6-7).

6.2.4. Earthquake preparedness

Community preparedness is vital for reducing the earthquake risk. The preparedness of individuals is highly controlled by their knowledge, perception and resources. Likewise the preparedness of the community depends on the socio-economic structure, political system and some times even on the physical setting of the area. For example in the society in a developing country like Nepal, because of the low level of education, people don't know the potential impact of earthquakes in their community due to vulnerable structures. So they don't pay much attention to future planning but concentrate on fulfilling the urgent needs at present. Further it is difficult and sometimes almost impossible to make high-tech structures and apply other mitigation measures because of low economy and diverse physical features.

During the survey it was tried to study how the local people are prepared for an earthquake and what kind of preparedness measures they have used. About 56 percent of the total respondents from the residential floors and 30 percent from the non-residential floors mentioned that they have identified a safe place inside their building, 38-47 percent used to discuss about possible earthquake disasters; 30-35 percent have prepared an emergency kit; and 16-25 percent have properly fixed the non-structural elements i.e. TV, computer, fan, cupboard, etc. Only 11 percent of the residential and 19 percent of non-residential respondents mentioned that they have used earthquake safety measures in the construction of their buildings (See Figure 6-8).

0

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Per

cent

age

of r

espo

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Safetymeasures inthe building

Discussed infamily

Identifiicationof safe placeinside house

Properly fixednon-structural

elements

Preparation ofemergency kit

Plannedtemporallodging

Fields


Figure 6-8: Preparedness for the possible earthquake

6.3. Development of indicies for awareness, preparedness and capacity

From the sampled residential and non-residential floors again those samples with at least with four persons were selected for the measurement of awareness, preparedness and capacity. It was because; after all the study aimed to compare the awareness, preparedness and capacity levels with casualties. The floors with few persons have very few casualties and some time with zero, which makes the comparison less useful. Thus in total 101 floors from residential and 17 from non-residential floors were selected.



62

Received information from the selected residential and non-residential respondents were grouped in main components i.e. awareness and preparedness, and then summed to get the overall capacity. Weights were assigned to all fields within the components, and the sub-components using a range from 0 to 1, according to their importance in the context of earthquake awareness, preparedness and capacity. In order to assign the weights, the comparison of components and fields was done just by researcher's judgement; no scientific analysis was carried out. The weights assigned for the components, sub-components and fields are treated in the respective sections (See Tables 6-1, 6-3 and 6-5).

For the calculation of a Capacity Index (CI), as the first step all the scores of the sub-component were calculated summing the obtained scores of fields multiplied with weights, and dividing by the sum of possible maximum scores multiplied with respective maximum weights.

��=

))(*)'((

)*'('

WfMaxscoreOfMax

WfscoreOfscoreS ………………….(i)

Where,

S'score- Score of the sub-component

Of'score- Obtained score of the field

Max(Of'score)- Maximum possible score of the field

Wf- Weight assigned

Max(Wf)- Maximum possible weight

After the calculation of scores for the sub-components, the index for main component of capacity i.e. awareness and preparedness were calculated summing the total scores of the sub-components multiplied with weights, and dividing by the sum of maximum score multiplied with weights.

Thus applying the equation (i) an Awareness Index (AI) and Preparedness Index (PI) were calculated. Then finally the Capacity Index was calculated from the awareness index and preparedness index applying the following equation:

)]*()*[()]*()*[(WpMaxPIWaMaxAI

WpPIWaAICI

++= …………….(ii)

Where,

CI- Capacity Index

AI – Awareness index

PI- Preparedness index

MaxAI- Maximum possible score for awareness

MaxPI- Maximum possible score for preparedness

Wa- Weight for awareness

Wp- Weight for preparedness



63

The calculated indices and followed procedures for the individual components are treated in the next sections.

6.3.1. Measuring awareness

For the preparation of an overall index for public awareness, several steps were carried out (See Table 6-1). First of all the answers for the individual questions received from the respondents were given the scores 0 (wrong) and 1 (correct) considering from an earthquake risk reduction point of view. For example, for the question "what would you do if you are in the upper floor of a building during an earthquake?" the answer "looking for safe place" was considered as correct answer and given the score 1 comparing to other answers such as "jumping through the window", "using elevator" etc. Likewise, "using flash light" for making light; choosing "open spaces" as an outdoor safe place during an earthquake were taken as the correct answers and given score 1. All the other wrong answers were given "0" score. Then the all questions (fields) were again assigned the weights ranging from 0-1 (less to highly important).

As shown in table 6-1 the fields within the sub-components of awareness were assigned the weights according to their importance. For example, the knowledge about an "aftershock" was given comparatively more importance than the others (earthquake safety day, building code and helping organizations), perception of "risk" than the perception of "retrofitting the building", and keeping information about "hospital" than others (open space, shelter house, police station from an earthquake point of view (See Table 6-1).

After assigning the weights for fields, the sub-components of awareness (response, knowledge, perception and level of information) were assigned ranging from 0 to 1. In this regard, considering risk perception as the crucial for earthquake risk reduction, it was assigned comparatively higher weight than knowledge and information for the calculation of overall level of awareness.

Table 6-1: Weights for the components of awareness Sub-Component Weight Field Weight

Look for a safe place in case of on upper floor of a building 0.8 Use flashlight for making a light during an earthquake 1 Response 1

Open spaces as the outdoor safe place 0.9 Helping organizations 0.9 Earthquake Safety Day 0.7 Building code in LSMC 0.8

Knowledge 0.9

Aftershock 1 Retrofit is possible 0.7 Perception 1 Living in risk 1 Open space 0.6 Shelter house 0.7 Hospital 1

Aw

aren

ess

Information 0.8

Police station 1

After assigning the weights for all fields and sub-components, the final scores for sub-components were calculated applying equation (i). The final score of awareness and its components then categorized in three levels i.e. high, medium and low. By doing so, 100 percent score was considered as "high", if less than 50 percent then "low" otherwise "medium". Two separate indices for residential and non-residential households were



64

calculated (See Annex 6-2). A summary of calculated awareness index is presented in table 6-9. Thus the calculated awareness index based on 118 households (101 residential and 17 non-residential) shows the medium level of awareness (ranging from 0.54 to 0.74) in the study area. The individual fields within the components are treated in the previous sections.

Table 6-2: Summary of awareness index for residential and non-residential respondents Components Residential Non-residential Response 0.74 Medium 0.70 Medium Knowledge 0.54 Medium 0.58 Medium Perception 0.56 Medium 0.65 Medium Information 0.71 Medium 0.74 Medium

Awareness

Overall awareness 0.64 Medium 0.67 Medium

6.3.2. Measuring preparedness

In this study the existing level of earthquake preparedness is measured on the basis of preparation at the household level, provision of insurance, representation in the related organizations and the received trainings in the related fields (first aid, evacuation, rescue, etc.). As in previous section for awareness index, the preparedness index also was calculated in different steps. The fields within the sub-components of preparedness were assigned the weights ranging from 0 to 1. And again the weights were assigned for the sub-components. For example, within the component "insurance", life insurance was assigned the highest weight (1) comparing to other insurances i.e. house insurance, health etc. and the insurance itself was assigned 0.9 weight comparing to other sub-components of the preparedness i.e. preparation at house, training and membership (See Table 6-3).

Table 6-3: Weights for the components of preparedness Sub-component Weight Field Weight

Earthquake safety measures in building 0.9 Earthquake discussion in family 1 Identified safe place at home 1 Fixed non-structures 0.9 Emergency kit 0.9

Preparation 1

Temporal lodging 0.8 House 0.8 House assets 0.7 Life 1

Insurance 0.9

Health 0.9 Social 0.9 Health 0.9 Emergency rescue 1 Disaster prevention 1

Membership 0.7

Women 0.8 Disaster prevention 0.9 Emergency preparedness 1 First aid 1 Evacuations 0.9

Pre

pare

dnes

s

Training 0.9

Rescue 0.9 The scores for the sub-components of preparedness were calculated applying the

equation (i). Then the preparedness index was calculated from the components applying



65

equation (iii). The final scores were then categorized as for awareness index i.e. scores 100 percent as "high", below 50 percent "low" otherwise "medium".

For the calculation of preparedness index due to the lack of detail information some assumptions were made. In the case of training and membership people aged below 5 years were excluded from the calculation assuming that they could not have any training and get involvement in any organizations. And in the case of schools 10 percent of the total population was considered as maximum number of people that received training or were involved in emergency response organizations. It was based on the assumption that significant number of people in the schools is low aged (below 13) and one trained person can assist 10 school children in an emergency.

As shown in table 6-4, the overall level of earthquake preparedness was found very low (0.11). Especially the level of training, membership or involvement with the related organization was found very low with both types of respondents. Some of them responded that they made some general preparation i.e. discussion with family, preparation of emergency kit, identifying the safe place inside the building etc. (See Figure 6-8). The level of insurance was found very low with the residential respondents but no information from non-residential respondents was received so this field was not included in preparedness index for non-residential respondents.

Table 6-4: Summary of preparedness index for residential and non-residential respondents Subcomponent Residential Non-residential Preparation 0.35 Low 0.28 Low Insurance 0.01 Low Membership 0.01 Low 0.01 Low Training 0.01 Low 0.01 Low

Preparedness

Overall preparedness 0.11 Low 0.11 Low

6.3.3. Measuring capacity

The level of awareness and preparedness calculated in the above sections were used for the calculation of overall capacity to cope with earthquake risk. For the calculation of capacity these two components i.e. awareness and preparedness were assigned different weights. As preparedness reflects that something is already initiated or implemented for an earthquake risk reduction, it was considered as more important component of capacity comparing to awareness. Thus for the calculation of overall capacity the weights 1 and 0.9 were assigned for the preparedness and awareness respectively.

As shown in the equation (ii), the final scores of respondents for awareness and preparedness were summed multiplying with the respective weights assigned and divided by summation of maximum possible score multiplied with weights to get the overall capacity. The detailed capacity indices for residential and non-residential respondents are presented in Annex 6-1 and 6-2.

Table 6-5: Summary of capacity index for residential and non-residential respondents

Components Residential Non-residential Awareness 0.64 Medium 0.67 Medium Preparedness 0.11 Low 0.11 Low

Capacity

Overall capacity 0.36 Low 0.38 Low



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The table 6-5 gives the summary of the calculated capacity level of respondents. It appears that awareness in both, residential and non-residential respondents is medium level but the preparedness level is very low. Mainly as shown in table 6-4 it was because of very low level of training, membership and insurance. As the preparedness is very important component for the capacity it was assigned high weight therefore the low score of the preparedness finally reduced the capacity as a whole.

6.4. Examples from the household survey

The information described above was collected during the household surveys carried out in 168 sampled households (131 residential and 37 non-residential). In order to provide a better idea about building and population vulnerability in relation of individual knowledge, response, attitude and preparedness, two examples are presented in detail and some others are included in figure 6-9.

6.4.1. Example 1: A respondent from a residential apartment

One of the respondents 41 years of age, a Newar, lives in an apartment with 3 more persons in his family, his wife, son and daughter. He and his wife are engaged in trade and both his son and daughter, aged 14-18 are studying in a secondary school in the same ward.

The building, he is living-in, is a 10 years old 5 storied RCC building with walls made of local industrial mud bricks with cement mortar including a plinth and roof band.

Till the date he has not acquired any kind of insurances for his family and house. Nobody from his family is involved in any kind of social groups nor has received any kind of trainings. He has never participated in awareness raising programs like ESD and doesn't know about any NGO related to earthquake risk reduction nor of the building code implemented by LSMC. He doesn't think that the municipality is prepared for an earthquake and doesn't believe the old buildings can be made earthquake safe. He doesn't know the location of open spaces and shelter buildings which could be used during an emergency but can locate the police station and hospital. In his building, no earthquake safety measures have been implemented. He has never discussed about earthquakes with his family nor made any plan for temporal lodging. However, he said, he has fixed non-structural elements and identified the safest place in his house in case of earthquake. He argued better to use gas lighter for making a light after an earthquake.

The total population in the whole building was estimated to be 63 during the day and 113 during the night time for the day and night time respectively. Considering the building conditions and other components in addition to building height and type of the building, the building was estimated to have a collapse probability between 0.19 and 0.38 in an intensity IX earthquake. And on the basis of building collapsed probability and number of people present in that building, there was a probability of 9 casualties of severity 1 (minor injury) in the building in case of the earthquake occurs at night and 5 persons in case it occurs during the day or evening. Injuries of severity levels 2 and 3 were estimated to be 4 and 1 respectively for night and day. In the same earthquake, if it occurs at night, there is a probability that 2 people might be killed (severity 4) (See Figure 6- 9).



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6.4.2. Example 2: A respondent from a school

Above examples were presented to reflect the real situation in the field representing two respondents from residential and non-residential sampled building floors. The information received from such observations and respondents was used to analyze the building vulnerability, human casualties and level of capacity for the whole study area.

The casualties estimated for the study are based only on the probability of building damage/collapse, earthquake intensity and temporal distribution of population. There are more controlling factors for casualties, such as age, sex, activity, individual perception, attitude, preparedness and capacity that may increase (if they are negative) or decrease (if they are positive) the existing vulnerability of population. In the case of above example buildings, concluding the received level of awareness and preparedness most of the indicators are of low level and some of them are medium, which reflect the low resilience (capacity that they may posses to withstand or recovery from emergencies and which can stand as a counterbalance to vulnerabilities), it might increase the chance of casualties.

One of the respondents out of the 37 sampled non-residential buildings is from a secondary school (class room). According to the respondent, the current building floor contained 10 persons in the morning, 40 during the day, and 5 in the evening but nobody at night.

It is a five storied RCC building made of brick with cement that seems to have been constructed not earlier than 10 years ago. Though it was considered as a residential building from the out side, all five floors are used as school class rooms. The building has plinth and roof bands but no lintel bands. No wall/ floor cracks and dampness were observed with the building.

According to the respondent nobody from the school is a member of any kind of social or disaster-related groups nor has received any kind of emergency training. The respondent personally didn't know about aid organizations, building code in LSMC and has never participated in the awareness programs like ESD. He argues that the old buildings could be made safer by retrofitting. He doesn't believe that the municipality is prepared for an earthquake. However he realizes that he is living at risk.

He knows the location of the police station, hospital and open-spaces which could be used for evacuation during an earthquake but doesn't know about any shelter buildings. As far as he knows, the building has implemented some earthquake safety measures and sometimes they have had discussions on earthquakes and prepared emergency kits but no plan has been made for temporal lodging.

The total population of the building was estimated to be 190 for the daytime and empty at night. Considering the building conditions, the calculated collapse probability was between 0.19 and 0.38 for an intensity IX earthquake. Thus, on the basis of the building collapse probability and the presence of population in the building, there is a probability of 15 persons getting minor injuries (severity level 1) in at daytime and nobody at night. Casualties of severity level 2 and 3 would be 7 and 2 for the daytime. Likewise, if the earthquake occurs at day time, 4 persons at would be killed (See Figure 6-9).



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Figure 6-9: Some examples from the sampled buildings comparing vulnerability and capacity

Figure 6-9 presents some of the sampled buildings including above mentioned examples. The

awareness, preparedness, capacity and vulnerability are presented in three colour approach. All the fields of "low" levels are presented by green colours and "high" by red colours. However the colours for vulnerability and awareness/preparedness/capacity are apposite. For example, red vulnerability is not good and; whereas red awareness is good.

20055

200730

200387

200128 20002

20061

2008220072



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6.5. Correlating the capacity level with vulnerability

In this section an effort was made to know whether there is correlation between expected casualties due to earthquakes and capacity level in the study area. The aim was to know how the public awareness, preparedness and capacity reduce the impact of earthquake i.e. human casualties.

In general, a hypothesis could be made that as the capacity increases, the number of casualties due to an earthquake decreases. But in the case of present study the estimations of casualties were made on the basis of an empirical relationship between building collapse probability and population distribution, no capacity indicators were considered.

However the hypothesis was tested using the most widely used bivariate test, Pearson correlation (See Annex 6-3 and 6-4). The capacity components and casualties of severity level 1 at night and day respectively for residential and non-residential sampled buildings due to an earthquake of intensity IX were taken for the test. The time, severity level and earthquake scenario were chosen because the casualties in residential buildings at daytime due to other earthquakes with other severity levels were calculated as very few and most of the cases "zero", which makes the calculation less useful and the same problem was for the non-residential buildings at night time.

The correlation coefficient may range from –1 to 1, where –1 or 1 indicates a “perfect” relationship. The further the coefficient is from 0, regardless of whether it is positive or negative, the stronger the relationship between the two variables. The calculated Pearson coefficient for the relationship between capacity components and casualties was very low significant. For example the calculated coefficient for the relationship between awareness and night time casualties of severity 1 in residential floors was -0.1, which tells that, the respondents with high awareness have low number of casualties. It means there is negative correlation between awareness and casualties, but very weak. Likewise the relation between other variables was found very low- negative and some times positive (See Annex 6-3 and 6-4).

However in the case of present study the relation (positive or negative) between two variables is just by coincidence. The low casualties are not due to high capacity because none of the components of capacity were considered for the estimation of casualties. Thus it doesn't have any effect on the number of casualties whether the capacity is high or low. Moreover the awareness information were received by one person of a floor of that building that can not represent the whole building in the reality. That is why it is indeed better to compare than to correlate.

Therefore this study has made an effort to show the combination of casualties due to an intensity IX earthquake with the calculated level of capacity. As the highest casualties for residential buildings were estimated during night time and for the non-residential buildings at daytime, respectively night and day casualties were taken for the comparison. Since the capacity (calculated from awareness and preparedness) level was calculated from the household survey and those better represent the sampled floors than the whole building, the casualties were also calculated for the floors from where the samples were taken. Then the numbers of casualties were grouped in three levels i.e. "high", "medium" and "low". The calculated casualty numbers less than 1 and 0 were considered as low casualties, 1-2 as medium and 3 or more than 3 casualties as "high". Then the combination was made crossing the class maps of casualties and capacity levels. Casualties of severity level 1 and 4 for both, residential and non residential floors were combined separately with awareness, preparedness and capacity. Combination of casualties and capacity level of residential and non-residential floors are



70

presented in figure 6-10 (a) and (b). The combination of casualties of severity level 1 and with awareness and preparedness are presented in annex 6-6 and 6-7.

(a) Residential building floors

(b) Non-residential building floors

Figure 6-10: Casualties due to intensity IX earthquake and level of capacity in sampled building floors

As shown in figure 6-10 (a) and (b) the combination was made such as "high casualties + low

capacity" (worst combination) to "low casualties + high capacity" (best combination). In the case of residential building floors, 2 percent of the total sampled building floors were found with the

Legend: Casualty + Capacity



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combination of high number of casualties of severity 1 and medium level of capacity (marked buildings with circle in figure 6-10a). About 14 percent were found with medium number of casualties of severity 1 and low level of capacity. Likewise 2 percent were found with the combination of medium casualties of severity 4 and low level of capacity. The rest of the building floors were found with the combination of "low +low". In the case of non-residential floors, 3 (18%) building floors (school buildings) were found with high casualties of severity level 1 and low level of capacity. Likewise 2 building floors (12%) were found with the combination of high casualties of severity 4 and low capacity (See the marked buildings with red circles in figure 6-10b) The combination of medium casualties of severity 1 and low capacity was found in 10 buildings.

None of the sampled buildings were found with the best combination i.e. low number of casualties and high level of capacity (See Annex 6-5 for details). Thus each sampled building in the study area can be identify with the combination of casualty and capacity level, which could be a tool for disaster management plan that where capacity should be increased.

6.6. Conclusion

After analyzing the information received by interviewing the sampled households the level of overall capacity of the local people to cope with earthquake risk was found to be very low. Though in some aspects the levels of awareness and preparedness were found high, the overall levels were found respectively medium and low. The medium level of awareness but very low preparedness reflects the lack of effectiveness of the awareness programs that have been carried out thus far. It means people who responded as they were aware are not actually applying their knowledge and awareness in practice reducing the earthquake risk which has resulted the low level of preparedness and ultimately low level of capacity.

The correlation between casualties and capacity components was not significantly negative or positive. In other words there was no correlation between casualties and capacity components. Therefore it is much useful to compare then correlate between the. By doing so, it was found that the population in most of the sampled buildings have low awareness, preparedness and capacity whereas medium and low numbers of casualties are estimated. Some of the residential and school buildings were found with the worst combination i.e. high number of casualties and low level of awareness, preparedness and capacity, and none of the buildings were found with the best combination i.e. low number of casualties and high level of capacity components. Thus each sampled building could be identified with the combination of casualty and awareness, preparedness and capacity level which could be use as a tool to indicate that which component of capacity should be prioritized and where.



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7 Conclusions and Recommendations

7.1. Conclusions

The study was carried out with the main objective to develop a method which can be adopted by municipal authorities in order to assess the vulnerability and level of capacity of local people. In order to fulfil the main objective it generated a database for the estimation of building damage and human casualties in case of a particular earthquake scenario; and evaluated the existing level of public awareness, preparedness and capacity to cope with an earthquake risk in the context of ward 20 of Lalitpur Sub-Metropolitan City, Nepal.

The socio-economic information and temporal distribution of population were received performing household surveys for a sample of 5 % building floors. Population density was calculated for the sampled building floors according to space uses for different time periods of the day, and based on these sample calculations the population for each building, and of the entire ward was estimated. Use of the building was found as an important determinant for population distribution which varies strongly between day and night-time. Individual buildings were separated in the footprint map by visual observation and attributes for the individual buildings were assigned.

The estimation of building damage and collapse probability were made in individual building level. Thus it is possible to indicate the probability of general damage/ collapse of a particular building in the study area. For the estimation, some modifications were made to existing building damage matrices prepared by JICA and NSET to consider the building conditions and other components in addition to the height and types of the buildings, and earthquake intensity. The estimations were made due to different possible earthquake intensities defined by previous studies. Thus in the worst case scenario, due to an intensity IX earthquake, 26% of the total 988 buildings were estimated with high probability (>0.5) of damage and collapse. In intensity VIII and VII earthquakes most of the buildings were estimated with medium (0.2-0.5) and low (<0.2) probability but none of them had high probability of damage or collapse. Even by the same intensity earthquake the probability of building damage and collapse were found different according to building type and age. Mainly the buildings in the north east part of the study area, within the old settlement area, were found to be affected even by small intensity earthquakes as they showed a combination of most of the worst buildings characteristics i.e. relatively old adobe and brick in mud buildings, relatively tall and already in poor conditions.

The casualties were estimated on the basis of building damage/collapse probability and the distribution of population using an empirical relationship established by HAZUS that was used by previous studies in the same field. Casualties in different severity levels were estimated for individual buildings due to possible earthquakes in different time periods of the day i.e. morning, day, evening and night. Thus assuming an intensity IX earthquake at daytime 1602 and 401casualties were respectively estimated of severity 1 (minor injury) and 4(dead), and 1607 and 402 for night-time. The number of casualties decreased with a decrease in building damage/collapse probability depending on earthquake intensity. Dividing the buildings in two broad categories, proportionally more casualties were found in non-residential buildings during the daytime scenario and in residential at night. Moreover it was noted that 3 % of the total buildings used as school buildings (class rooms) hold



73

more than 30% of total casualties in case of an earthquake in a daytime. Likewise 2 % buildings used as school hostels hold 19 % of total casualties in case of night-time.

The level of public awareness, preparedness and capacity were analyzed from the information received by interviewing with local people. Received information were grouped in awareness and preparedness, and summed to get the overall capacity. Weights are assigned to all fields within the components and final scores were categorized as high, medium and low. The respondent with a 100 percent score was considered as "high", if less than 50% then "low" and otherwise "medium". From the analysis it was concluded that both residential and non-residential respondents have a medium level of awareness but a very low level of preparedness and capacity. Combining capacity level with the estimated casualties, it was clear that some of the residential buildings and schools combine a high number of casualties with a low level of awareness, preparedness and capacity. The level of overall awareness was found to be at medium level but it seems it is not made effective that is why the preparedness is still very low.

7.2. Recommendations

The estimation of population is based on a sample of 5% of all building floors. The information about the number of households in the sampled floors was not collected, so one household was considered as representative of one floor for the calculation of total population. Therefore the estimated population may not exactly match in the case of individual buildings. So it is recommended to consider the number of households within one floor which provides a better estimation of population.

Since individual building footprints were drawn just by visual observation on the basis of block level footprint maps, prepared in previous studies, they may not provide sufficient accuracy in terms of area which may create error for the estimation of population and ultimately for the casualties. Therefore for increasing the accuracy, a more detailed instrumental survey should be carried out for building footprint mapping. Further, due to lack of time and resources building attributes and conditions were registered by visual observation only, whereas more interviews with the owners and detailed observation would be required for improving the information.

Regarding the building damage estimation, there is no doubt that when more relevant parameters are taken a better estimation will be obtained. That is why this study considered other building parameters in addition to building type and heights used in the existing damage matrix. However, the contribution of these parameters and conditions for the building vulnerability to earthquake were just decided by local experience and educative guess, not implementing any scientific analysis. So there is need for a scientific analysis of those components for the better analysis of building vulnerability to earthquake, involving structural engineers. Moreover the study has not considered the building practices in the study area, which makes much difference in the building damage and collapses probability.

There is no detailed geological and seismic analysis of the study area (large scale), therefore the whole study area falls in one zone in terms of earthquake intensity and geology, which means the hazard for the entire study area is the same. That is why more detailed seismic and geological analyses are needed in the study area.

Casualties were estimated using an empirical casualty rate used by Islam (2004), which was taken from HAZUS, considering the same rate of casualties for a day and night-time scenario. But



74

obviously casualties in number and nature differ with the time. Likewise other population characteristics i.e. age; gender, education, economic situation etc. and casualties by secondary hazards are not considered due to the lack of time and detailed information, which would be more important for further studies. There is possible to make population vulnerability index considering population characteristics i.e. age, sex, education, etc., which was not included in this study due to lack of time, also would more interesting for the further research.

Public awareness, preparedness and the capacity to cope with earthquake risk presented in this study are based on interviews using a limited number of questions with the respondent from sampled building floors that may not represent the actual situation. An intensive household survey with enough relevant questions addressing different land uses should be performed to know the actual situation of awareness, preparedness and capacity level in the study area. Further the weights given to the levels of capacity components was done subjectively using the researcher's knowledge and experience, which may differ with the views from other experts.

After analyzing the information received from the respondents, the study concludes that there is a low level of capacity of the local people to cope with earthquake risk and it was because of low level of preparedness, due to ineffectiveness of awareness campaigns. That is why an effective awareness (leading towards preparedness) would be the crucial very first step for the earthquake risk reduction process. Unless the potential victims are aware, the risk will remain the same even after the implementation of several risk mitigation programs. Hence, this study recommends for raising effective awareness addressing each sector of the local communities (students, teachers, housewives, masons, engineers, clubs etc.).

School buildings might have a high number of casualties and low level of preparedness and capacity, this study strongly recommends paying much attention to the schools where a large number of casualties are possible in the case of an earthquake.

Especially in developing countries like Nepal, the communities are highly governed by the socio-cultural situation, and by indigenous knowledge and traditional (mis)beliefs. Sometime these may increase and/or reduce the risk, therefore they should be addressed by the awareness raising programs. People should be made aware whether their beliefs and doings are right.

In this connection there is an urgent need of effective earthquake awareness raising programs in different aspects (more leading towards preparedness), focussing on different groups in the local communities. In this program the government, municipality, local communities and NGO/INGOs should work in close cooperation. The central government should formulate the national policies emphasizing the awareness raising activities and the district should be responsible to the central government. The municipality, the local body of the government, can work in close cooperation with local communities and central government. In this regard, the national and international non governmental organizations, such as NSET can play a vital role in different levels in the context of the present study area. They can work in close cooperation with all levels of government as well as with local communities.

Finally the awareness raising programs should be focused on the local communities. Any awareness program should spell out its specific role taking into consideration the community’s needs and their level of understanding. Figure 7-1 shows the possible ways which may be effective to make people aware from different sectors in the context of the present study area and also for similar communities in other wards and municipalities.



75

As shown in the figure, orientation lectures to the students, teachers and other professionals would be an effective strategy for transferring knowledge. A single trained teacher can potentially influence a class of 40 students and each student can transfer the knowledge at least to 5 family members which make a large group of aware people. Likewise, other major strategies (as shown in the Figure 7-1) that could be more effective for awareness raising and leading towards preparedness in the community level are listed below:

Focussed on awareness

1. Informal education (providing off time education for different groups who can not join the formal education i.e. old people and house wives).

2. Orientation lectures for teachers, students, other professionals and volunteers

3. Organization of rally and exhibitions to convince the public at a large scale

4. Conduction of fate and festivals containing seminars, talk programs, art, poem, essay competitions and other programs for mass communication.

5. Estimation of losses due to possible earthquakes and public presentation.

6. Distribution of posters, flyers and pamphlets and local newspapers.

7. Broadcasting the news; interviews with experts and live sources.

Leading towards preparedness

8. Trainings for students, teachers and other professionals (first aid, rescue, evacuation etc.), and for masons, contractors and engineers in the community.

9. Earthquake mobile clinic (it is an on-site consultation for the house owners).

10. .Organization of vulnerability tours involving local people with experts to make them aware of vulnerable situation in their community.

Figure 7-1: Proposed strategy for awareness leading towards preparedness



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Above listed first seven programs (informal education, orientation lectures and radio/TV programs etc.) are mainly for raising awareness of the people from different sectors, and the next 3 programs are making people aware more directed to concrete preparedness measures i.e. providing training, to the students, volunteers, professionals (first aid, evacuation, rescue etc.), masons, contractors, engineers (earthquake safety constructions, building code implementation etc.), and earthquake mobile clinic etc (See Figure 7-1).

Besides, there could be many other strategies for public awareness initiating by the central government at the national level, including an earthquake awareness courses in academic curriculum, policy development, formulation of a national action plan, requesting for international assistance, etc. It is not possible to conduct these all works by a single NGO or by the municipality that is why they should work in close cooperation.

In this context, it makes worth to recall the situation in Pakistan during an earthquake on 8 October 2005, which showed the burning examples of lack of awareness and preparedness in the local people that made the victims more vulnerable and even made difficult to manage the post disaster situation.



77

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ANNEXES

ANNEX I

Annex 1-1: Building inventory form

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81

Annex 1-2: Household survey form (only for residential floors)

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0 � ��

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; �+ �� ) � �?�� ,

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/ ��

& �� ( ��

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82

Annex 1-3: Household survey form for residential and non residential buildings

0 ��

� " � ��" � � � �

! � ��

) �� +��

/� �� " � 4 �+ �� 4 � �� 8� �� " ��

= � ��

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� � �� ! ��

3 � �� + �� )'�� ?�� C�� '� � � C�� + �� C�4 ��,D

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3 � �� '�: �� " ��9 < C�� # � �� C�� + � � ��C�'��+ �� D

3 � �� " B � �� '�� + �� # � � � �� D

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� � � ��. ��

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; � � ��

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9 � �� " �� " ��)' �� " � �� " �,

3 � �� " B � �� 4 �� + � D

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�� 4 �� F �� " �� " B � �� # � �� D



83

Annex 1-4: Building classification according to use ExcelCode SpaceUseCode Space_Use Sub_use Specific_Use

1 Agr Agriculture21 CB Commercial Bank22 CD Commercial Disco23 CH Commercial Hotel24 CM Commercial Mall25 CMk Commercial Market square26 CP Commercial Private Offices27 CR Commercial Restaurant / Café / Bar28 CLS Commercial Shop (large scale)29 CSS Commercial Shop (small scale)31 InCh Industrial Chemical32 InB Industrial Construction Site

331 InCM Industrial Craftshop Metal332 InCT Industrial Craftshop Textiles (carpets, clothes)333 InCW Industrial Craftshop Wood carving

33 InC Industrial Craftshop34 InF Industrial Food35 InMM Industrial Metal-mechanical

361 InSD Industrial Storage Dangerous Materials362 InSE Industrial Storage Emergency supply363 InSN Industrial Storage Normal Goods

36 InS Industrial Storage411 IES Institutional Educational Elementary School412 ISS Institutional Educational Secondary School413 IT Institutional Educational Technological414 Itc Institutional Educational Training center415 IU Institutional Educational University / College

41 IE Institutional Educational421 IGC Institutional Governmental Consulate422 IGE Institutional Governmental Embassy425 IGO Institutional Governmental General Public Offices423 IGM Institutional Governmental Municipality424 IGN Institutional Governmental Notary426 IGP Institutional Governmental Post Office

42 IG Institutional Governmental43 NGO Institutional NGO/INGO

441 ISF Institutional Security Fire brigade442 ISM Institutional Security Military Areas443 ISP Institutional Security Police station

44 IS Institutional Security6 Min Mining

71 NS No apparent use Square72 NV No apparent use Vacant land73 NW No apparent use Water body

812 PCCi Public Facility Cultural Cinema811 PCC Public Facility Cultural Convention hall813 PCD Public Facility Cultural Dharmashala814 PCG Public Facility Cultural Gallery815 PCL Public Facility Cultural Library816 PCM Public Facility Cultural Museum817 PCP Public Facility Cultural Old palace818 PCR Public Facility Cultural Rest houses819 PCT Public Facility Cultural Theater

81 PC Public Facility Cultural822 PHD Public Facility Health Dental clinic823 PHH Public Facility Health Hospital824 PHL Public Facility Health Laboratory821 PHC Public Facility Health Medical Clinic826 PHPh Public Facility Health Pharmacy825 PHP Public Facility Health Private practice827 PHV Public Facility Health Veterinary clinic

82 PH Public Facility Health834 PRCt Public Facility Religious Cemetery831 PRC Public Facility Religious Chaitya832 PRCh Public Facility Religious Church833 PRCr Public Facility Religious Crematorium835 PRF Public Facility Religious Funerary house837 PRMn Public Facility Religious Monastery/Bahi/Bahal836 PRM Public Facility Religious Mosque838 PRS Public Facility Religious Stupa839 PRT Public Facility Religious Temple

83 PR Public Facility Religious841 PSA Public Facility Social Asylum842 PSC Public Facility Social Club843 PSN Public Facility Social Nursery844 PSNh Public Facility Social Nursing home

84 PS Public Facility Social851 PTA Public Facility Transportation Airport852 PTB Public Facility Transportation Bus terminal853 PTP Public Facility Transportation Parking Lot

85 PT Public Facility Transportation91 NP Recreational Park

921 RcAT Recreational Sport facilities Athletic track922 RcBVC Recreational Sport facilities Basketball/Volleyball court923 RcC Recreational Sport facilities Coliseum924 RcG Recreational Sport facilities Gymnasium925 RcP Recreational Sport facilities Playground926 RcF Recreational Sport facilities Soccer/Cricket field927 RcSt Recreational Sport facilities Stadium928 RcSP Recreational Sport facilities Swimming Pool

92 RcS Recreational Sport facilities93 RcZ Recreational Zoo

101 RA Residential Apartment1021 RHU Residential Hostel College/University1022 RHE Residential Hostel Elem. Boarding1023 RHS Residential Hostel Sec. Boarding

102 RHt Residential Hostel103 RH Residential Single house



84

Annex 1-5: Major uses of the buildings

Annex 1-6: Building characteristics and codes

Structural type Code Load Bearing walls LBW Mixed MX RCC frame structure RCC Temporary structure TS Age Code 0-10 1 10-30 3 30-50 5 Malla M Older O Shah-Rana SR Mortar Type Code Cement Sand 1 Mud 2 Lime Surkhi 3 Wall material Code Industrial mud bricks (local) 1 Industrial mud bricks (Chinese) 2 Sun dried mud bricks 3 Hollow Concrete blocks 4 Other 5 Geometric form Code Regular <=1:3 1 Regular > 1:3 2 Irregular 3

Space uses Codes Residential RH Residential apartment RHa Residential single house RHs Educational EDU General educational (class rooms) EDUsc Educational hostels EDUrh Institutional INS Industrial Ind Commercial shops CS Public Facilities PF Commercial Hotel/restaurant CHR



85

Annex 1-7: Building classification by structural type

Building Classes Codes Description

Adobe AD Sun-dried bricks (earthen) with mud mortar

Brick in Mud: BM Brick with mud mortar

Brick in Cement BC Brick with cement or lime mortar

Reinforced Concrete Frame 4 RCC4 Reinforced Concrete Frame having four or more storeys

Reinforced Concrete Frame 3 RCC3 Reinforced Concrete Frame having three or less storeys



86

ANNEX II

Annex 2-1: MMI scale

MMI Description of damageI Not felt except by a very few under especially favourable conditions.II Felt only by a few persons at rest, especially on upper floors of buildings.

IIIFelt quite noticeably by persons indoors, especially on upper floors of buildings. Many people do not recognize it as an earthquake. Standing motor cars may rock slightly. Vibrations similar to the passing of a truck. Duration estimated.

IV

Felt indoors by many, outdoors by few during the day. At night, some awakened. Dishes, windows, doors disturbed; walls make cracking sound. Sensation like heavy truck striking building. Standing motorcars rocked noticeably.

VFelt by nearly everyone; many awakened. Some dishes, windows broken. Unstable objects overturned. Pendulum clocks may stop.

VIFelt by all, many frightened. Some heavy furniture moved; a few instances of fallen plaster. Damage slight.

VIIDamage negligible in buildings of good design and construction; slight to moderate in well-built ordinary structures; considerable damage in poorly built or badly designed structures; some chimneys broken.

VIII

Damage slight in specially designed structures; considerable damage in ordinary substantial buildings with partial collapse. Damage great in poorly built structures. Fall of chimneys, factory stacks, columns, monuments, walls. Heavy furniture overturned.

IXDamage considerable in specially designed structures; well-designed frame structures thrown out of plumb. Damage great in substantial buildings, with partial collapse. Buildings shifted off foundations.

XSome well-built wooden structures destroyed; most masonry and frame structures destroyed with foundations. Rails bent.

XIFew, if any (masonry) structures remain standing. Bridges destroyed. Rails bent greatly.

XII Damage total. Lines of sight and level are distorted. Objects thrown into the air.



87

ANNEX III

Annex 3-1 Geometric form of the buildings

Regular <=1:395%

Regular > 1:31%

Irregular4%

Annex 3-2 Wall materials used in the buildings

Industrial mud bricks (local)

94.1%

Hollow concrete blocks0.2%

Sun dried mud bricks0.3%Industrial mud

bricks (Chinese)3.9%

Others1.4%

Annex 3-3: Roof materials used in the buildings

Plastic/cloth0.4%

Tin roof32.1%

Tiles5.8%

RCC f lat roof61.7%



88

Annex 3-4: Floor materials used in the buildings

Cement72.3%

Mud26.8%

Wood0.9%

Annex 3-5: Time periods assumed for the study Time of the day Actual times Morning 6.00 am to 9.00 am Day 9.00 am to 5.00 pm Evening 5.00 pm to 8.00 pm Night 8.00 pm to 6 .00 am

Annex 3-6: Temporal distribution of population by space uses

Annex 3-7: Activities by age and gender

Male Female Total Male Female Total Male FemaleTotal Male Female Total Male Female Total Male FemaleTotal %

<5 years 0 0 0 8 2 10 0 0 0 0 0 0 5 10 15 13 12 25 4

6 to 13 3 1 4 43 27 70 0 0 0 0 0 0 3 2 5 49 30 79 12

14 to 18 8 3 11 34 21 55 0 4 4 0 0 0 0 2 2 42 30 72 11

19 to 59 180 56 236 31 20 51 13 122 135 0 6 6 14 3 17 238 207 445 67

>60 10 4 14 0 0 0 4 13 17 0 1 1 6 1 7 20 19 39 6

Total 201 64 265 116 70 186 17 139 156 0 7 7 28 18 46 362 298 660 100

% 56 21 40 32 23 28 5 46.6 24 0 2 1 8 6 7 55 45 100

Handicapped Others TotalAge groupActivities

Working Studying HH activities

Space Use Morning % Day % Evening % Night % Residential (RH) 10,301 58 5,816 36 9,808 68 10,301 72 Institutional (Ins) 174 1 782 5 174 1 87 1 Industrial (Ind) 120 1 300 2 60 0 60 0 Commercial (CS) 632 4 843 5 843 6 548 4 Commercial Hotel/restaurant (CHR) 100 1 220 1 160 1 100 1 Public facilities (PF) 308 2 793 5 176 1 132 1 Education class (EDUsc) 4,140 23 5,943 37 197 1 0 0 Education hostels(EDUrh) 2,051 12 1,420 9 2,997 21 2,997 21 Total 17,826 100 16,117 100 14,415 100 14,225 100



89

Annex 3-8: Population by floor and space uses

Annex 3-9: Work or study places of people

Percentage of population Age

group Within ward

Out of the ward but within valley

Out of valley but within country Out of Country

Total

<5 67 33 0 0 100 6-13 61 39 0 0 100 14-18 43 57 0 0 100 19-59 32 60 5 3 100 >60 80 10 0 10* 100 Total% 37 56 4 3 100

*Out of 10, 1 person was reported studying/working out of the country.



90

ANNEX IV

Annex 4-1: Existing damage matrix prepared by NSET and JICA for different types of building in Kathmandu (The values represent percentage of buildings with the same material type)



91

Annex 4-2: Weights for building parameters/conditions for earthquake vulnerability

Building conditions Condition Individual weight Comparative weights

Yes 1 Wall Cracks No 0

0.121

Yes 1 Floor cracks/settlements No 0

0.115

Yes 1 Dampness No 0

0.109

Yes 1 Soft storey No 0

0.073

Yes 1 Upper partial floors No 0

0.067

Structural bands Yes 0 Plinth No 1

0.097

Yes 0 Lintel No 1

0.103

Yes 0 Roof No 1

0.091

Yes 0 Gable No 1

0.085

Geometric form Code Regular <=1:3 1 0 Regular > 1:3 2 0.5

Irregular 3 1

0.079

Age Code 0-10 1 0 10-30 2 0.3 30-50 3 0.5 Malla 4 1 Older 5 1 Shah-Rana 6 0.7

0.061



92

ANNEX V

Annex 5-1: Casualties by building types due to different earthquake scenarios

AD BM BC RCC3 RCC4 Total AD BM BC RCC3 RCC4 Total AD BM BC RCC3 RCC4 TotalM 33 677 306 247 606 1869 22 425 138 116 272 973 8 199 35 36 81 358D 48 454 319 238 543 1602 32 284 145 112 244 817 12 132 36 35 72 288E 12 732 209 191 474 1619 8 458 96 90 213 866 4 214 24 28 63 333N 11 739 204 186 467 1607 8 463 94 87 210 862 3 216 24 27 62 333M 17 339 153 123 303 934 11 212 69 58 136 486 4 99 17 18 40 179D 24 227 159 119 272 801 16 142 72 56 122 408 6 66 18 18 36 144E 6 366 105 96 237 809 4 229 48 45 106 433 2 107 12 14 32 166N 6 370 102 93 234 804 4 232 47 44 105 431 2 108 12 13 31 166M 4 85 38 31 76 234 3 53 17 15 34 122 1 25 4 4 10 45D 6 57 40 30 68 200 4 35 18 14 30 102 1 17 5 4 9 36E 2 91 26 24 59 202 1 57 12 11 27 108 0 27 3 3 8 42N 1 92 25 23 58 201 1 58 12 11 26 108 0 27 3 3 8 42M 8 169 76 62 151 467 5 106 34 29 68 243 2 50 9 9 20 90D 12 113 80 59 136 401 8 71 36 28 61 204 3 33 9 9 18 72E 3 183 52 48 118 405 2 115 24 22 53 216 1 53 6 7 16 83N 3 185 51 46 117 402 2 116 23 22 52 215 1 54 6 7 16 83S

ever

ity 4

Sev

erity

3S

ever

ity 2

Sev

erity

1

Bld_typeEq. North BagmatiMid NepalMMI IX



93

Annex 5-2: Casualties by space uses due to different earthquake scenarios Casualties by the use of buildings due to different scenario earthquakes

Scenario Earthquakes Assumed (MMI_IX) Mid Nepal (MMI_VIII)


Building damage cases

Collapse Damage Collapse Damage Collapse Damage Severity

levels Time

Use Number of casualties RH 1156 43 614 24 234 10 Ins 33 2 16 1 6 0 Ind 16 1 8 0 2 0 CS 85 3 44 2 16 1 EDUsc 342 17 158 10 45 3 EDUrh 206 6 117 4 48 2 PF 23 1 13 0 6 0 CHR 8 0 4 0 1 0

Mor

ning

: (6.

00 a

m to

9.0

0 am

)

Total 1869 73 973 41 358 16 RH 715 27 377 15 143 6 Ins 74 4 35 2 12 1 Ind 36 2 18 1 6 0 CS 70 3 37 2 13 1 EDUsc 497 25 232 14 66 5 EDUrh 142 4 80 2 33 1 PF 55 2 32 1 13 1 CHR 13 1 6 0 2 0

Day

(9.0

0 am

to 5

.00

pm)


Eve

ning

(5.0

0 pm

to 8

.00

pm)

Total 1619 59 866 33 333 14 RH 1175 44 624 25 239 10 Ins 26 1 13 1 5 0 Ind 9 0 4 0 1 0 CS 81 3 42 2 15 1 EDUsc 0 0 0 0 0 0 EDUrh 298 8 169 5 69 3 PF 11 0 6 0 3 0 CHR 8 0 4 0 1 0 S

ever

ity L

evel

1: I

njur

ies

requ

iring

bas

ic m

edic

al a

id i.

e. b

anda

ges

or

obse

rvat

ion

for e

.g. a

spr

ain,

a

seve

re c

ut re

quiri

ng s

titch

es, a

min

or b

urn

or a

bum

p on

the

head

with

out l

oss

of c

onsc

ious

ness

.

Nig

ht (8

.00

pm to

6 .0

0 am

Total 1607 58 862 33 333 14 Contd….



94

Contd...

Casualties by the use of buildings due to different scenario earthquakes




Collapse Damage Collapse Damage Collapse Damage Severity levels Time


Mor

ning

: (6.

00 a

m to

9.0

0 am

)


Day

(9.0

0 am

to 5

.00

pm)


Eve

ning

(5.0

0 pm

to 8

.00

pm)


Sev

erity

Lev

el 2

: Inj

urie

s re

quiri

ng a

gre

ater

deg

ree

of m

edic

al c

are

i.e. x

-ray

s or

sur

gery

, but

not

exp

ecte

d to

pro

gres

s to

a li

fe th

reat

enin

g st

atus

, e.g

. bur

ns o

ver

larg

e pa

rts o

f the

bod

y, a

bum

p on

the

head

that

ca

uses

loss

of c

onsc

ious

ness

, fra

ctur

ed b

one,

deh

ydra

tion

or e

xpos

ure

etc.

Nig

ht (8

.00

pm to

6 .0

0 am

Total 804 6 431 3 166 1



95

Contd…..






levels Time


Mor

ning

: (6.

00 a

m to

9.0

0 am

)


Day

(9.0

0 am

to 5

.00

pm)


Eve

ning

(5.0

0 pm

to 8

.00

pm)


Sev

erity

Lev

el 3

: Inj

urie

s th

at p

ose

an im

med

iate

life

thre

aten

ing

cond

ition

if n

ot tr

eate

d ad

equa

tely

and

ex

pedi

tious

ly, e

.g. u

ncon

trolle

d bl

eedi

ng, p

unct

ured

org

an, o

ther

inte

rnal

inju

ries,

spi

nal c

olum

n in

jurie

s, o

r cr

ush

synd

rom

e et

c.

Nig

ht (8

.00

pm to

6 .0

0 am

Total 201 0 108 0 42 0



96






levels Time


Mor

ning

: (6.

00 a

m to

9.0

0 am

)


Day

(9.0

0 am

to 5

.00

pm)


Eve

ning

(5.0

0 pm

to 8

.00

pm)


Sev

erity

Lev

el 4

: Ins

tant

aneo

usly

kill

ed o

r mor

tally

inju

red

Nig

ht (8

.00

pm to

6 .0

0 am

Total 402 0 215 0 83 0



97

ANNEX VI

Annex: 6-1: Awareness, preparedness and capacity indices for residential floors

SN

Building IDs

Awareness index

Awareness level

Preparedness index

Preparedness level

Capacity index

Capacity level

1 200012 0.64 Medium 0.08 Low 0.346 Low2 200014 0.38 Low 0.10 Low 0.232 Low3 200050 0.64 Medium 0.10 Low 0.358 Low4 200054 0.67 Medium 0.00 Low 0.319 Low5 200088 0.70 Medium 0.11 Low 0.391 Low6 200099 0.28 Low 0.10 Low 0.186 Low7 200100 0.57 Medium 0.00 Low 0.270 Low8 200109 0.79 Medium 0.21 Low 0.480 Low9 200122 0.64 Medium 0.05 Low 0.331 Low

10 200128 0.47 Low 0.14 Low 0.297 Low11 200142 0.75 Medium 0.08 Low 0.393 Low12 200167 0.60 Medium 0.12 Low 0.347 Low13 200179 0.72 Medium 0.06 Low 0.372 Low14 200187 0.70 Medium 0.17 Low 0.419 Low15 200188 0.70 Medium 0.00 Low 0.331 Low16 200198 0.87 Medium 0.10 Low 0.469 Low17 200204 0.78 Medium 0.18 Low 0.462 Low18 200206 0.49 Low 0.05 Low 0.260 Low19 200207 0.65 Medium 0.21 Low 0.416 Low20 200211 0.45 Low 0.05 Low 0.241 Low21 200225 0.67 Medium 0.16 Low 0.402 Low22 200226 0.53 Medium 0.15 Low 0.328 Low23 200256 0.29 Low 0.05 Low 0.163 Low24 200260 0.38 Low 0.01 Low 0.187 Low25 200262 0.56 Medium 0.04 Low 0.287 Low26 200275 0.74 Medium 0.10 Low 0.405 Low27 200284 0.95 Medium 0.10 Low 0.504 Medium28 200287 0.37 Low 0.05 Low 0.204 Low29 200303 0.89 Medium 0.10 Low 0.476 Low30 200308 0.77 Medium 0.10 Low 0.421 Low31 200329 0.59 Medium 0.08 Low 0.320 Low32 200330 0.52 Medium 0.00 Low 0.246 Low33 200334 0.49 Low 0.00 Low 0.233 Low34 200341 0.57 Medium 0.16 Low 0.356 Low35 200352 0.81 Medium 0.05 Low 0.411 Low36 200359 0.65 Medium 0.00 Low 0.307 Low37 200361 0.43 Low 0.00 Low 0.206 Low38 200364 0.80 Medium 0.10 Low 0.431 Low39 200367 0.70 Medium 0.10 Low 0.385 Low40 200371 0.34 Low 0.00 Low 0.161 Low41 200378 0.49 Low 0.00 Low 0.233 Low42 200386 0.78 Medium 0.05 Low 0.396 Low43 200387 0.78 Medium 0.05 Low 0.396 Low44 200388 0.89 Medium 0.14 Low 0.495 Low45 200389 0.73 Medium 0.10 Low 0.397 Low46 200403 0.46 Low 0.24 Low 0.345 Low47 200409 0.95 Medium 0.10 Low 0.507 Medium48 200411 0.79 Medium 0.16 Low 0.454 Low49 '200418 0.72 Medium 0.10 Low 0.394 Low50 200439 0.87 Medium 0.10 Low 0.469 Low

Contd……



98

SN

Building IDs

Awareness index

Awareness level

Preparedness index

Preparedness level

Capacity index

Capacity level

51 200492 0.76 Medium 0.15 Low 0.441 Low52 200518 0.79 Medium 0.11 Low 0.434 Low53 200520 0.70 Medium 0.05 Low 0.358 Low54 200527 0.78 Medium 0.16 Low 0.455 Low55 200537 0.22 Low 0.00 Low 0.105 Low56 200538 0.47 Low 0.28 Low 0.369 Low57 200541 0.30 Low 0.10 Low 0.195 Low58 200545 0.49 Low 0.21 Low 0.341 Low59 200548 0.48 Low 0.05 Low 0.255 Low60 200550 0.37 Low 0.10 Low 0.229 Low61 200557 0.81 Medium 0.17 Low 0.475 Low62 200569 0.71 Medium 0.19 Low 0.435 Low63 200572 0.90 Medium 0.20 Low 0.532 Medium64 200584 0.55 Medium 0.21 Low 0.370 Low65 200587 0.78 Medium 0.15 Low 0.448 Low66 200588 0.95 Medium 0.22 Low 0.565 Medium67 200594 0.54 Medium 0.09 Low 0.307 Low68 200595 0.78 Medium 0.15 Low 0.448 Low69 200648 0.68 Medium 0.16 Low 0.407 Low70 200670 0.63 Medium 0.15 Low 0.379 Low71 200675 0.49 Low 0.05 Low 0.260 Low72 200680 0.84 Medium 0.10 Low 0.454 Low73 200685 0.36 Low 0.00 Low 0.171 Low74 200693 0.89 Medium 0.10 Low 0.473 Low75 200702 0.57 Medium 0.15 Low 0.346 Low76 200722 0.70 Medium 0.05 Low 0.355 Low77 200725 0.78 Medium 0.14 Low 0.443 Low78 200730 0.78 Medium 0.00 Low 0.369 Low79 200752 0.36 Low 0.07 Low 0.208 Low80 200757 0.68 Medium 0.05 Low 0.347 Low81 200780 0.89 Medium 0.18 Low 0.515 Medium82 200788 0.78 Medium 0.15 Low 0.448 Low83 200811 0.89 Medium 0.10 Low 0.473 Low84 200812 0.73 Medium 0.05 Low 0.371 Low85 200819 0.64 Medium 0.20 Low 0.409 Low86 200827 0.78 Medium 0.10 Low 0.423 Low87 200829 0.78 Medium 0.10 Low 0.423 Low88 200832 0.43 Low 0.07 Low 0.240 Low89 200836 0.72 Medium 0.10 Low 0.394 Low90 200838 0.78 Medium 0.15 Low 0.448 Low91 200843 0.69 Medium 0.11 Low 0.381 Low92 200844 0.78 Medium 0.14 Low 0.443 Low93 200862 0.39 Low 0.14 Low 0.257 Low94 200925 0.53 Medium 0.12 Low 0.313 Low95 200932 0.34 Low 0.13 Low 0.231 Low96 200935 0.70 Medium 0.15 Low 0.411 Low97 200941 0.53 Medium 0.19 Low 0.353 Low98 200952 0.22 Low 0.19 Low 0.206 Low99 200960 0.29 Low 0.11 Low 0.198 Low

100 200970 0.45 Low 0.20 Low 0.322 Low101 200984 0.69 Medium 0.20 Low 0.433 Low



99

Annex: 6-2: Awareness, preparedness and capacity indices for non-residential floors

Annex: 6-3: Correlation between capacity components and casualties in residential floors due to intensity IX earthquake

Annex: 6-4: Correlation between capacity components and casualties in non-residential floors due to intensity IX earthquake

Annex: 6-5: Combination of casualties and capacity components



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Annex 6-6: Combination of casualties due to intensity IX earthquake and level of awareness/preparedness in sampled residential building floors

Legend: Casualty +awareness/ preparedness



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Annex 6-7: Combination of casualties due to intensity IX earthquake and level of awareness/preparedness in sampled non-residential building floors

Legend: Casualty +awareness/ preparedness

seismic vulnerability and capacity assessment at ward ... · ganesh kumar jimee thesis submitted to...

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