universiti putra malaysia - psasir.upm.edu.mypsasir.upm.edu.my/34086/1/fk 2012 9r.pdf · abstract...
TRANSCRIPT
UNIVERSITI PUTRA MALAYSIA
MAJID MIRZAEI
FK 2012 9
UNCERTAINTY ANALYSIS OF EXTREME HYDROLOGICAL EVENTS IN THE SEMI-ARID ZAYANDEROOD BASIN, CENTRAL IRAN
© COPYRIG
HT UPM
I
UNCERTAINTY ANALYSIS OF EXTREME HYDROLOGICAL EVENTS IN
THE SEMI-ARID ZAYANDEROOD BASIN, CENTRAL IRAN
By
MAJID MIRZAEI
Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia,
in Fulfilment of the Requirement for the Degree of Doctor of Philosophy
May 2012
© COPYRIG
HT UPM
II
Dedication
This work is dedicated to my parents
© COPYRIG
HT UPM
III
Abstract of thesis presented to the Senate of Universiti Putra Malaysia in fulfilment
of the requirement for the degree of Doctor of Philosophy
UNCERTAINTY ANALYSIS OF EXTREME HYDROLOGICAL EVENTS IN
THE SEMI-ARID ZAYANDEROOD BASIN, CENTRAL IRAN
By
MAJID MIRZAEI
May 2012
Chairman: Professor Ir. Lee Teang Shui, PhD
Faculty: Engineering
Stream flow, which is a part of the integrated process of atmospheric and topographic
processes, is of prime importance to water resources planning. Hydrologic simulation
models for stream flow have implicit uncertainty in their handling of processes.
Uncertainty may occur during data collection, modeling, and analysis of the
engineering system and model predictions. Common methods for stream flow
forecasting use historical discharge data series at some reach of the river in the
watershed. It is universally believed that climate and landuse change can affect the
spatial and temporal distribution of water resources and also change hydrological
parameters such as intensities and frequencies of extreme hydrological events.
Distributed watershed models are increasingly being used to support decisions about
alternative management strategies in the areas of land use change and climate change.
In this study, the kinematic runoff and erosion model KINEROS2 which is an event
© COPYRIG
HT UPM
IV
oriented, physically based model was used for rainfall-runoff simulation. The main
objective of this study is to investigate the effects of uncertainty in rainfall and models
input parameters for extreme events in a semi-arid region and quantifying the
uncertainties in frequency analysis of extreme rainfall events which are associated
with Depth Duration Frequency (DDF) curves. The calibration scheme is carried out
under the Generalized Likelihood Uncertainty Estimation (GLUE) framework to
quantify uncertainty in the rainfall-runoff modelling process. These uncertainties are
presented in the rainfall-runoff modeling for investigation of uncertainty effects in
discharge and volumes of extreme hydrological events and subsequently embedded
into guidelines for risk based design and management of urban water infrastructure.
The uncertainty in the rainfall input data was studied using the rainfall data of 16
gauging stations in the Zayanderood basin, central Iran. The 36 rainfall series were
generated based on rainfall at each of the gauging stations. Statistical evaluations for
stream flow prediction indicate that there is good agreement between the measured
and simulated flows with Nash Sutcliffe values of efficiency of 0.85 and 0.79 for
calibration and validation periods respectively. Uncertainty analysis was carried out
on the new distribution of input parameters and various duration and frequency of
rainfall for extreme events are considered. The watershed was simulated for each event
using Monte Carlo sampling from statistical distribution of input parameters.
Uncertainty analysis applied to the hydrologic model indicated that uncertainty in
input parameters affects the results significantly. The uncertainty in output is
expressed through peak discharge values and stream flow volumes. For peak
discharges the amounts of upper uncertainty is reduced with increasing rainfall
duration, for all return periods. Maximum reduction was with the return period of 100
© COPYRIG
HT UPM
V
years that was reduced from 1327m3/s for 24 hour rainfall duration to 582m3/s for 120
hours rainfall duration. By increasing rainfall duration, the difference between upper
limit of uncertainty and predicted value declines. In fact, model accuracy in discharge
calculation increases with rainfall duration. However for stream volumes, the variation
of upper uncertainty band does not have a recognizable trend with increased rainfall
duration for all return periods. The difference between upper limit of uncertainty and
predicted values is significant for all return periods and rainfall durations. This
difference slightly increases with increase of rainfall duration for all return periods.
The validated KINEROS2 model enables predicting streamflow volume for extreme
events with reliable accuracy without uncertainty analysis. The findings pointed out
that extreme discharges prediction should not be static tools but instead should
undergo continuous adaptation with uncertainty analysis, relative to possible changes
in watershed hydrology.
Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai
memenuhi keperluan untuk Ijazah Doktor Falsafah
© COPYRIG
HT UPM
VI
ANALISIS KETIDAKPASTIAN PERISTIWA HIDROLOGI LAMPAU DI
LEMBANGAN SEPARA GERSANG ZAYANDEROOD, IRAN TENGAH
oleh
MAJID MIRZAEI
Mai 2012
Pengerusi: Profesor Ir. Lee Teang Shui, PhD
Fakulti: Kejuruteraan
Aliran sungai, sebahagian proses sepadu proses atmosfera dan proses topografi,
penting kepada perancangan sumber air. Model penyelakuan hidrologi untuk aliran
sungai berketidakpastian tersirat dalam prosesnya, ketidakpastian yang mana boleh
berlaku semasa proses pengumpulan data, pemodelan, dan analisis ramalan model
sistem kejuruteraan. Kaedah biasa untuk ramalan aliran sungai menggunakan sejarah
data aliran pada sebahagian sungai di dalam lembangan. Adalah dipercayai
semestanya bahawa perubahan iklim dan kegunaan tanah berpengaruh terhadap
pengedaran ruang dan masa sumber air serta juga mengubah parameter hidrologi
selain daripada keamatan dan kekerapan peristiwa hidrologi melampau. Model teragih
legeh semakin banyak diguna demi menyokong keputusan strategi pengurusan pilihan
di kawasan kegunaan tanah berubah dan iklim berubah. Dalam kajian ini, air larian
kinematik dan model hakisan KINEROS2 sebagai model yang berasas fizikal dan
© COPYRIG
HT UPM
VII
terperistiwa guna untuk perselakuan hujan-air larian. Kajian ini bertujuan menyiasat
kesan ketidakpastian berkaitan hujan dan ketidakpastian parameter input model
hidrologi peristiwa melampau di kawasan separa gersang dan menilaikan
ketidakpastian dalam analisis kekerapan peristiwa hujan melampau yang berkaitan
dengan lengkung Dalaman-Jangkamasa-Kekerapan. Skema tentukur yang
dilangsungkan bawah rangkaian Anggapan Ketidakpastian Kebolehjadian Umum
untuk menilaikan ketidakpastian dalam proses permodelam hujan-air larian.
Ketidakpastian kemudian dipakai dalam permodelan hujan-air larian untuk menyiasat
kesan ketidakpastian keatas aliran dan isipadu peristiwa hidrologi melampau dan
berikutannya dimasuk ke dalam garispanduan untuk rekabentuk berdasar risiko dan
pengurusan infrastruktur air bandar.
Ketidakpastian data input hujan dikaji menggunakan data hujan sebanyak 16 stesyen
ukuran di Lembangan Zayanderood, Pusat Iran. 36 siri hujan dijana berdasarkan hujan
di setiap stesyen ukuran. Penilaian statistik untuk ramalan aliran sungai menunjuk
bahawa ujudnya bandingan keputusan baik di antara aliran yang diukur dan yang
terselaku dengan nilai kecekapan Nash Sutcliffe sebanyak 0.85 dan 0.79 untuk
penentukuran dan pengesahan masing masing. Analisis ketidakpastian dibuat ke atas
pengedaran baru parameter input dan berbagai jangkamasa dan kekerapan hujan
peristiwa melampau dikaji. Legeh itu diselaku bagi setiap peristiwa mengguna
pengsampelan Monte Carlo daripada pengedaran statistik parameter input. Analisis
ketidakpastian dibuat keatas model hidrologi menggambarkan bahawa ketidakpastian
parameter input berkaitan berkesan ke atas keputusan. Ketidakpastian dalam hasil
dihuraikan melalui nilai aliran kemuncak dan isipadu aliran sungai. Bagi aliran
kemuncak banyaknya ketidakpastian had teratas dikurangkan berkadar dengan naik
© COPYRIG
HT UPM
VIII
jangkamasa hujan untuk semua kala kembali. Penurunan maksimum berlaku untuk
kala kembali 100 tahun di mana ianya dikurangkan daripada 1327 m3/s bagi 24 jam
jangakmasa hujan ke 582 m3/s bagi 120 jam jangkamasa hujan. Dengan tambahan
jangkamasa hujan maka perbezaan di antara had teratas ketidakpastian dan nilai
diramalkan turun, bahkan kejituan model dalam kiraan aliran bertambah dengan
tambahan jangka masa hujan. Akan tetapi, bagi isipadu sungai, perubahan jalur had
atas ketidakpastian tidak bersifat jelas tren bagi tambahan jangkamasa hujan untuk
semua kala kembali. Perbezaan diantara had teratas dan nilai diramalkan bermakna
bagi semua kala kembali dan jangkamasa hujan. Perbezaan ini bertambah sedikit
sekadar dengan tambahan jangkamasa hujan bagi semua kala kembali. Model tersebut
membolehkan ramalan isipadu sungai untuk peristiwa melampau dengan kejituan
bolehharap tanpa analisis ketidakpastian. Keputusan menggambarkan bahawa ramalan
aliran melampau tidak saja sebagai alat statik bahkan sebaliknya diubahsuai
berterusan dengan analisis sekadar dengan segala perubahan boleh di dalam hidrogi
legeh.
ACKNOWLEDGEMENTS
© COPYRIG
HT UPM
IX
Foremost, I would like to express my sincere gratitude to my Supervisor Professor Ir.
Lee Teang Shui, PhD for the continuous support of my PhD study and research, for
his patience, motivation, enthusiasm, and immense knowledge. His guidance helped
me in all the time of research and writing of this thesis. I could not have imagined
having a better advisor and mentor for my PhD study.
Besides my advisor, I would like to thank the rest of my thesis committee: Prof. Madya
Dr. Abdul Halim Bin Ghazali, Professor Teymour Sohrabi and Dr. Badronnisa
bt.Yusuf, for their encouragement, insightful comments, and hard questions.
I am especially thankful to my parents for their financial and strong mental supports.
Also thanks my dear brother Ali and my dear sisters Maryam and Sara for their words
of encouragement in the hard time of my study.
I would like to thank my dear friends: Dr. Ehsan Goodarzi in Georgia Institute of
Technology, Ehsan Bakhshipour in University Technology of Petronas, Dr. Mehdi
Zieai in Universiti Teknologi Malaysia, Dr. Behnam Ababaei in University of Tehran
and Mina Faghih in University Putra Malaysia.
My deep acknowledgement is duly expressed to my dear friend Azadeh Bakhshipour
in University Putra Malaysia for her help at each stage of my work.
APPROVAL
I certify that an examination committee has met on date of viva to conduct the final
examination of Majid Mirzaei on his Doctor of Philosophy thesis entitled “Uncertainty
© COPYRIG
HT UPM
X
Analysis of Extreme Hydrological Events in The Semi-Arid Zayanderood Basin,
Central Iran” in accordance with Universiti Pertanian Malaysia (higher Degree) Act
1980 and Universiti Pertanian Malaysia (Higher Degree) Regulations 1981. The
Committee recommends that the candidate be awarded the relevant degree. Members
of the Examination committee are as follows:
Name of Chairperson, PhD Title (e.g. Professor/Associate Professor/Ir)
Name of Faculty
Universiti Putra Malaysia
(Chairman)
Name of Examiner 1, PhD
Title (e.g. Professor/Associate Professor/Ir)
Name of Faculty
Universiti Putra Malaysia
(Internal Examiner)
Name of Examiner 2, PhD
Title (e.g. Professor/Associate Professor/Ir)
Name of Faculty
Universiti Putra Malaysia
(Internal Examiner)
Name of Examiner 3, PhD
Title (e.g. Professor/Associate Professor/Ir)
Name of Department and/or Faculty
Name of Organization (university and/or Institute)
Country
(External Examiner)
_______________________________________
BUJANG KIM HUAT, Ph.D
Professor and Deputy Dean School of Graduate Studies
Universiti Putra Malaysia
Date:
This thesis was submitted to the Senate of Universiti Putra Malaysia and has been
accepted as fulfilment of the requirements for the degree of Doctor of Philosophy.
The members of the Supervisory Committee were as follows:
© COPYRIG
HT UPM
XI
Lee Teang Shui, PhD, Ir
Professor
Faculty of Engineering
University Putra Malaysia
(Chairman)
Abdul Halim Ghazali, Ph.D
Associate Professor
Faculty of Engineering
University Putra Malaysia
(Member)
Badronnisa bt.Yusuf, PhD
Senior Lecturer
Faculty of Engineering
Universiti Putra Malaysia
(Member)
Teymour Sohrabi, PhD
Professor
Faculty of Agricultural Engineering & Technology
College of Agriculture & Natural Resources,
University of Tehran, Karaj, Iran.
(Member)
_______________________________________
BUJANG BIN KIM HUAT, PhD
Professor and Dean
School of Graduate Studies
Universiti Putra Malaysia
Date :
DECLARATION
© COPYRIG
HT UPM
XII
I declare that the thesis is my original work except for equations and citations, which
have been duly acknowledged. I also declare that it has not been previously and is not
currently submitted for any other degree at Universiti Putra Malaysia or other
institutions.
MAJID MIRZAEI
Date: 28 May 2012
TABLE OF CONTENTS
Page
© COPYRIG
HT UPM
XIII
ABSRACT III
ABSTRAK VI
ACKNOWLEDGEMENTS IX
APPROVAL X
DECLARATION XII
LIST OF TABLES XVII
LIST OF FIGURES XIX
LIST OF ABBREVIATION XXV
CHAPTER
1 INTRODUCTION
1.1 Introduction............................................................................... 1
1.2 Statement of problem ................................................................ 2
1.3 Objectives of the Research ....................................................... 3
1.4 Thesis Outline ........................................................................... 4
2 LITERATURES REVIEW
2.1 Introduction............................................................................... 5
2.2 Rainfall-Runoff Modelling ....................................................... 5
2.2.1 Modelling Types and Procedures .................................. 6
2.2.1.1 Classification of Rainfall-Runoff Models .. 6
2.2.1.2 Model Type Selection ................................ 9
2.2.2 GIS-Based Hydrologic Modeling ................................ 10
2.2.2.1 The Automated Geospatial Watershed
Assessment (AGWA) ............................... 12
2.3 Uncertainty ............................................................................. 16
2.3.1 Introduction .................................................................... 16
2.3.2 Types of Uncertainty ..................................................... 17
2.3.2.1 Intrinsic Uncertainty ................................ 17
2.3.3 Uncertainty in Hydrology ............................................. 18
2.3.3.1 Introduction .............................................. 18
2.3.3.2 Classifications of Uncertainty in Hydrology
.................................................................. 19
2.3.4 Uncertainty Analysis Methods in Hydrology ............ 24
2.3.4.1 Historical Developments .......................... 24
2.3.4.2 Understanding, Quantification and
Reducing Uncertainty .............................. 27
2.3.4.3 Classification of Uncertainty Analysis
Methods .................................................... 30
2.3.4.4 Selection of Uncertainty Analysis Methods
.................................................................. 31
2.3.4.5 Generalize Likelihood Uncertainty
Estimation (GLUE) .................................. 32
2.3.5 Depth-Duration-Frequency (DDF) Curves ................ 34
2.3.5.1 The Probability Distribution for Extreme
Rainfall ..................................................... 35
© COPYRIG
HT UPM
XIV
2.3.4.6 Uncertainty in DDF Curves ..................... 36
2.4 Summary ................................................................................. 38
3 METHODOLOGY
3.1 Introduction............................................................................. 40
3.1.1 Framework of Study ........................................................... 41
3.2 Case Study .............................................................................. 43
3.2.1 Zayanderood Basin ........................................................ 43
3.2.2 Study Area ...................................................................... 45
3.2.2.1 Surface Elevation ..................................... 45
3.2.2.2 Land Cover ................................................... 47
3.2.2.3 Soil ................................................................ 48
3.3 Rainfall ................................................................................... 50
3.3.1 Rainfall Stations ............................................................ 50
3.3.2 Annual Maximum Daily Rainfall ................................ 53
3.3.3 Depths Duration Frequency Curves (DDF) ............... 55
3.3.3.1 Design Using DDF Curves ...................... 57
3.3.3.2 Creating a DDF Curve ............................. 57
3.3.3.3 Confidence Intervals on a Frequency
Curves ...................................................... 58
3.3.4 Time Distributions of Storm Rainfall ......................... 59
3.3.4.1 Huff Design Storm Method ..................... 60
3.4 Rainfall Runoff Modeling....................................................... 64
3.4.1 Introduction .................................................................... 64
3.4.2 KINEROS2 (Kinematic Runoff and Erosion Model)64
3.4.3 The Automated Geospatial Watershed Assessment
Tool (AGWA2) .............................................................. 66
3.4.3.1 Watershed Delineation and Discretization 68
3.4.3.1 Parameter Estimation ............................... 70
3.4.3.2 Rainfall Input ........................................... 72
3.4.3.3 Modeling .................................................. 73
3.5 Uncertainty Analysis Methods ............................................... 74
3.5.1 Introduction .................................................................... 74
3.5.2 The Generalized Likelihood Uncertainty Estimation
methodology (GLUE) ................................................... 74
3.5.2.1 Likelihood Measures ................................ 78
3.6 Monte Carlo Simulation........................................................... 82
4 RESULTS AND DISCUSSION
4.1 Introduction............................................................................. 84
4.2 Rainfall .................................................................................... 84
4.2.1 Rainfall Depth-Duration-Frequency (DDF) .............. 84
4.2.1.1 Regional Variability in Extreme Rainfall
Statistics ................................................... 84
4.2.1.2 Fitting a GEV Distribution ...................... 85
4.2.1.3 Regional Estimation and Modeling of GEV
Parameters ................................................ 89
© COPYRIG
HT UPM
XV
4.2.2 Depth Duration Frequency (DDF) Analysis for
Chelgerd Station ............................................................ 90
4.2.2.1 GEV Parameters as a Function of Duration
for Chelgerd Station ................................. 91
4.2.2.2 Derivation of DDF Curves for Chelgerd
Station ...................................................... 94
4.2.2.3 Modelling Uncertainty in Chelgerd Station
DDF Curves ............................................. 96
4.2.3 Depth Duration Frequency (DDF) Analysis for
Damaneh Station ........................................................... 98
4.2.3.1 GEV Parameters as a Function of Duration
for Damaneh Station ................................ 99
4.2.3.2 Derivation of DDF Curves for Damaneh
Station .................................................... 101
4.2.3.3 Modelling Uncertainty in Damaneh Station
DDF Curves ........................................... 102
4.2.4 Depth Duration Frequency (DDF) Analysis for
Shahrukh Palace Station ............................................. 104
4.2.4.1 GEV Parameters as a Function of Duration
for Shahrukh Palace Station ................... 105
4.2.4.2 Derivation of DDF Curves for Shahrukh
Palace Station ......................................... 107
4.2.4.3 Modelling Uncertainty in Shahrukh Palace
Station DDF Curves ............................... 108
4.2.5 Depth Duration Frequency (DDF) Analysis for Sade
Zayanderood Station ................................................... 110
4.2.5.1 GEV Parameters as a Function of Duration
for Sade Zayanderood Station ................ 111
4.2.5.2 Derivation of DDF Curves for Sade
Zayanderood Station .............................. 113
4.2.5.3 Modelling Uncertainty in Sade
Zayanderood Station DDF Curves ......... 114
4.2.6 Time Distributions of Storm Rainfall ........................ 116
4.3 Rainfall-Runoff Modeling .................................................... 121
4.3.1 Application of KINEROS2 ......................................... 121
4.3.2 Evaluation Procedure .................................................. 125
4.3.2.1 Parameters Sensitivity ............................ 125
4.3.3 Calibration of Rainfall-Runoff Model Using GLUE 126
4.3.3.1 The GLUE Framework ........................... 126
4.3.3.2 Storm Events Selection for Calibration and
Validation ............................................... 129
4.3.3.3 GLUE Analysis ..................................... 131
4.4 Uncertainty Analysis in Modeling of Hydrological Extreme
Event ..................................................................................... 136
4.4.1 Uncertainty Analysis for 24 Hour Rainfall Event ... 138
4.4.2 Uncertainty Analysis for 48 Hour Rainfall Event ... 144
4.4.3 Uncertainty Analysis for 72 Hour Rainfall Event ... 149
4.4.4 Uncertainty Analysis for 96 Hour Rainfall Event ... 154
4.4.5 Uncertainty Analysis for 120 Hour Rainfall Event . 159
4.4.6 Uncertainty Analysis for Different Return Periods 164
© COPYRIG
HT UPM
XVI
4.4.6.1 Peak Discharge Analysis ....................... 164
4.4.6.2 Stream volume Analysis ........................ 167
5 SUMMARY AND CONCLUSIONS
5. 1 Summery ...................................................................................... 169
5.2 Conclusions ................................................................................... 170
5.2 Recommendations for Future Work ............................................. 171
REFERENCES .................................................................................. 173
BIODATA OF STUDENT ............................................................... 190
LIST OF PUBLICATIONS ............................................................. 191