evaluating the prioritization of transportation network links under the flood damage: by...

8/13/2019 Evaluating the Prioritization of Transportation Network Links under the Flood Damage: by Vulnerability Value and Accessibility Indexs

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International Journal of Scientific Research in Knowledge (IJSRK), 1(12), pp. 557-569, 2013

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and repair of a certain facility and to establish a priority list of budget spending among the alternativemeasure. McAllister et al. (2000) attempted to

prioritize wetland restoration to optimize floodattenuation at regional scale. The decision criterion inthe study was the marginal decrease in totaldownstream flood volume per restoration dollar. Theycalculated the priority index, ranked sub units of theregion, and mapped those to show the spatialdistribution of the priority index over the region.

Similar to the analysis in this paper, lvs (1998)established an order of significance of links. Hemodeled escape ways of the building evacuationsystem as a network with links and nodes. Theanalysis is performed to identify the importance ofdifferent network components. According to the

author, a link or a node is important if its removal hasgreat implic ations on the systems performance.Different criteria are used to examine the importanceincluding structural importance of link cuts, structuralimportance of links, performance based importanceof links, and time dependence of importance. Many ofthem are the applications of measures used in thegraph theory. Even if it not about network system, thestudy of Davidson and Lambert (2001) shares thesimilarity with lvs (1998) in twofold. First, theirstudy tried to quantify the potential risk of eachcounty. Second, it attempted to set an order by the

magnitude of risk. They developed hurricane disasterrisk index to quantify the relative risk of economicand life loss in 15 different coastal counties in the US.Factors considered in calculating the index includehazard-related, exposure-related, vulnerability related, and emergency response and recoverycapability. Different weights are assigned to differentfactors based on the finding from the analyticalhierarchy process. According to the authors, the indexis expected to help resource allocation decision amongcounties.

The concept of vulnerability does not have a firmand commonly accepted definition for allcircumstances, but has to be defined depending on thecontext. In a road network context, Berdica (2006)defines vulnerability as a susceptibility to incidentsthat can result in considerable reductions in roadnetwork serviceability . The serviceability of a link /route / road network describes the possibility to usethat link /route/road net work during a given period.Instead of serviceability, the terms performance,capacity and operability have been used in the

literature. Other authors stress the sudden, unpredictedor infrequent occurrence of the events. This revealsthe dual characteristic of the concept: it has onecomponent of probability and one of consequence.

Normally, these components go hand in hand aninverse relationship, so that the greater theconsequence, the more rare is the event that triggers it.The part of the vulnerability concept that is onlyrelated to the consequence, we can exposure.

The criticality of a component (link, node, groupsof links and/ or nodes) is related to the vulnerability ofthe system in the way that the more critical thecomponent, the more severe is the damage to thesystem when it is lost. Criticality can be decomposedin the same way as vulnerability; in accordance with

Nicholson and Du (1994), we call a component weak

if the probability of an incident is high, and importantif the consequences are great. To be called critical, thecomponent has to be both weak and important.

3. METHODOLOGY

According to the above mentioned ideas, theresearch method is divided different stages.

modeling the road network of Golestan province, loading the road network of the province, determining the accessibility index for the

existing condition,

determining the accessibility index for differentscenarios (after occurrence the flood),

determining the different of accessibility beforeand after link loss for each of the links,

extracting the statistics related to the daily andinstantaneous maximum discharge, of the rivers in theregion in the annual statistical year,

assessing and analyzing the instantaneousmaximum discharge or flood peak based on differentreturn periods,

determining the capacity of water passing fromthe bridge sections,

determining the vulnerability value of thedestruction of bridges in the links understudy,

merging the vulnerability value with theaccessibility index,

Prioritization of the strengthening of thetransportation network links based on the new mergedindex.

The methodology of the present research could be process into the following:


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Khaki et al.Evaluating the Prioritization of Transportation Network Links under the Flood Damage: by Vulnerability Value and

Accessibility Indexs

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Fig. 1: Process of The prioritization of road network links based on the accessibility indexs

Fig. 2: Process of The prioritization of road network links based on the vulnerability value

Fig. 3: process of the prioritization of the transportation network links based on composed index

4. DETERMINING OF THE ACCESSIBILITYINDEXS

Accessibility is an indicator which is used to depictthe easiness of the relation between two or more

points or even between a point with more than one points and reverse. The accessibility indexs of the present study could be stages in to the following:

4.1. Determining of the accessibility index base ontravel time

The Hansen integral accessibility index (A i) forlocation (city) i may be written as

Equation (1) is often is used in a normalised form asfollows:

Accessibility index, which has been used in thisstudy, is base on travel time and as gravity model and


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Define as an exponential function and its relation is asfollows:

(3)

Which: A i = Area Accessibility I; B j = population ofcity j; T ij = Trip Time between areas i, j

Fig. 4: Results of Prioritization of transportation Network links based on Accessibility index (traffic volume)

Table 1: The correlation of completion of the flood peak in elected stations

4.2. Determining the accessibility index base ontraffic volume and distance

There are two effective parameters in determining theaccessibility index. The first is the distance betweenzones which has a reverse relationship. The second

parameter is the traffic volume which has a direct

relationship with the accessibility index. Variousinvestigations have been conducted considering thetwo parameters both singly and together, to determinethe accessibility index.Jungyul sohn (2006) proposed an index in which both

parameters were simultaneously considered:

23

124

1

24

1

24

1

23

124

1

24

1

24

1

)()1(*4** j K ik

ij

k K

j

K K

i

j K ik

ij

K K

j

K K

ii

t

t

P

P

P

P

d

d

P

P

P

P A

(4)In which; :i A Accessibility of zone I; : Weighted

coefficient) 10 ; :i P The population of zone

1; : 0.446632 (experimental coefficient); :ijd Theshortest path between i and j zones in differentscenarios; :*

ijd The shortest path between i and j

zones in the existing conditions

ij

n

m mmij d

d AADT t 1

.:

The average traffic volume between i and j zones:m AADT The average annual daily traffic in link m

:md The length of link m In the first part of the above-mentioned

relationship, the distance parameter has beenconsidered in determining the accessibility indicator.

In the second part, traffic volume indicator determinesthe accessibility index between origin and destination.The coefficient in this relationship is the coefficientwhose change, could change the percentage of effects


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of the two-mentioned parameters in determining theaccessibility could be either increased or decreased.For example, =1 means that only distance has beenutilized in determining the accessibility index =0demonstrates that the accessibility index is determinedsolely based on the parameter of traffic volume.

If we suppose that only Accessibility index hasinfluence on prioritization of the transportationnetwork links, then the results have been illustrated infigure 4.

According to the result of figure 4 the coefficientnears 1(The condition in which only distance is theinfluential factor in assessing and determining theaccessibility index), the amount of changes in theaccessibility in relation to the existing condition willdecrease. This is owing to the little sensitivity of

accessibility index in defined mathematicalrelationship to the distance parameter.in conditions in which the traffic volume parameter

play a role in determining the accessibility index ( i.e.=0, =0.25, =0.5, =0.75 , =1)those links in thenetwork have great level of importance whosedisruption will lead to considerable increase in trafficvolume in the substitute links for example linksnumber 3, 8 and 14.

in condition in which distance parameter is theonly influential factor in determining the accessibilityindex =1 , those links in the road network enjoy

greater significance which are the only accessibility

links in their zones and their disruption will cause thatthe substitute links in other zones and with longerdistance transfer the traffic volume . For example link3, 5 and 8.

4.3. Modeling the Road Network of GolestanProvince

In order to calculate the accessibility indexs ofdifferent zones, it is necessary to model the roadnetwork of Golestan Province (case study) along withthe trip production and attraction zones in this

province. To do this EMME2 Software was selected.EMME2 is software which has been increasinglyutilized in transportation planning. There are threetypes of databases in the understudy area, Golestan

Province Road Network.(1) Network (province road network)(2) Matrix (origin-destination matrix)(3) Functions (the mathematical formula ofaccessibility indexs)The modeled road network of Golestan province

has been illustrated in figure 5.Having modeled the road network of Golestan

Province in the Software of EMME2, the origin-destination matrix of daily trips throughout the

province was assigned to the network. The loadednetwork in the existing situation has been illustrated in

figure 6.

Fig. 5: The Modeled Road Network of Golestan Province

4.4. Assessment of the Accessibility index in theExisting Conditions (for the indexs of thepresented in this study)

In this stage, the manner of calculation of accessibilityindex, presented in the previous section, wasdetermined by QBasic Programming Language. Then,using the programming language of Macro net, the

existing characteristics in the province road networksystem, trip production and attraction zones weredetermined as the input of the program of QBasic andthe accessibility index in the existing condition wascalculated.


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4.5. Assessment of Accessibility index in differentLink-disruption conditions in the network. (Forthe indexs of the presented in this study)

In this section, assuming the flood occurrence in theroad network of the province, and loss of each of theexisting links of in the network, scenarios weredefined and developed. After that the origin-destination matrix was assigned to the new network,after the link-loss for each of the scenarios, theamount of the new accessibility index for all

production and attraction zones was assessed. Infigures and 7, 8 the loading of the province roadnetwork in the link-loss condition between (korkuy gorgan) and (gorgan Aliabad) has been illustrated(Correia and saraiva 1999a; Kim and boyee, 2002).

5. DETERMINING OF THE VULNERABILITYVALUE

For estimating vulnerability value of the present studycould be stages into the following:

5.1. The assessment of flood peak

According to find a flood peak for every station, giventhe fact that some of stations in a year or years do nothave a certain statistics. In order to complete the lackof current statistics, we planned to setup relation forstations having lack of statistics as shown in the table(1) and it is being presented. The next step was theflood peak calibrating and after those distributions of

probability in different return periods by the usage thehydrologic frequency analysis (HYFA) software wasestimated. Ahmad and simonovic (2001) themathematical relation between the flood peak andmaximum daily discharge could be defined asfollows:

Q P = a + b Q D & Q P = a Q D b

, n, r (5)In which: Q P the flood peak in the station/m3 per

second; Q D the maximum daily discharge in thestation/m 3 per second; N: the number of years whichhave the statistics related to the instantaneous anddaily maximum discharge; R: correlation coefficient;a and b: calibration coefficient of the model.

Fig. 6: The Loaded Network of Golestan Province in the Existing Condition

In order to assess the maximum instantaneousdischarge for different return periods, the hydrologicfrequency analysis (HYFA) software was used. In thismethod , different statistical distributions such as lognormal with 2 and 3 parameters , gambel , pearson,log pearson type 3 , gama with 2 parameters and etc.have been regressioned to the completed statistics of

maximum instantaneous and daily discharge in thehydrometric stations. According to the values of x 2

test and the least square method, the best normaldistribution have been selected and using them, themaximum instantaneous discharge has been assessed

in the selected hydrometric stations for differentreturn periods. The process of calibrating thecorrelational relationships for some of the hydrometricstations has been illustrated in the figure 9 to 10.

In the Table (2) the values of the flood peakassessed in the selected hydrometric station have beenshown for different return periods

5.2. The assessment of the vulnerability value oflinks of the road network


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If in the life time considered for technical structures,the flood amount exceeds the equivalent amount forthe hypothesized return period, the structure isdestroyed or at least is damage. If we consider p as the

probability of the occurrence of an incident, the valueof q will be the probability that the incident would nothappen:q = 1 p (6)The probability of flood not to happen in n year or thereliability of that would:R = (1 p) n (7)

Considering the definition of the return period offlood T, we can present the reliability as follows:Pr = (1 1/T) n (8) Therefore, the probability of the occurrence or thevulnerability value would be:Pv = 1 (1 1/T) n (9)

Considering what was mentioned before andregarding the previously mentioned equation vulnerability value for each of the under-study bridges have

been presented in table 3 based on the number of therelated links.

Fig. 7: The Loaded Road Network of Golestan Province in the condition of link-loss between

6. DETERMINING OF THE COMPOSED INDEXOF IN THIS STUDY AND PRIORITIZATIONOF THE TRANSPORTATION NETWORKLINKS

We can define the destruction effect of each link theamount of accessibility indexs of network and basedon this, we should calculate the accessibility index inthe network two different ways; one state is when thelink of in the current situation. (In the existingcondition) The other state is when the link is damagedand the differented as the effect of destruction on each

bridge. (In the link disruption condition)These relations can the shown as follows:A j= 24i=1A i-

24i=1A i

j= 24i=1(A i-A i j) (10)

A j: Simptoms due to the destruction of the link orlevel of destruction effect on link

A i: Accessibility of area i before the loss of link j A i

j: Accessibility of area i after the loss of link jAt this stage, the composed index of the bridge

destruction is utilized as a coefficient for theaccessibility index presented in this study or thecomposed index defined and determined based onvulnerability value multiplied by accessibility indexs

and the risk index is presented for prioritization of theroad transportation network links based on thefollowing equation.

R = P v *24

i=1(A i A j

i) (11)

Pv: the vulnerability value or the probability of link being damage.

R : composed index According to this the level of composed index for

different links of the transportation network areestimated in the Tables (4), (5).

7. RESULTS AND DISCUSSIONS

1-in condition in which distance parameter is the onlyinfluential factor in determining the accessibilityindex =1 , those links in the road network enjoygreater significance which are the only accessibilitylinks in their zones and their disruption will cause thatthe substitute links in other zones and with longerdistance transfer the traffic volume. For example link3, 18, 5 and 8.

2- in conditions in which the traffic volume parameter play a role in determining the accessibilityindex ( i.e. =0, =0.25, =0.5, =0.75 , =1)those


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links in the network have great level of importancewhose disruption will lead to considerable increase intraffic volume in the substitute links for example linksnumber 3, 8 and 14.

3- The results of prioritization in case =0.5 (i.e.the effects of two parameter of distance and trafficvolume in determining the accessibility index areequal) is presented. In graph no. 1, these are illustratedfor different volume of .

4- in the final p of Golestan province roadnetworks, it can be observed that the link no. 23 whichhas been considered the 3rd priority based onaccessibility index, in the present study has beenconsidered the 1st factor due to its high vulnerabilityvalue. Also, the link no. 8 has been placed in a higher

priority compared to link 23, this happened in the

opposite order based on accessibility index.

5- Amount of the flood peak of rivers in understudy region is indicative of the high precision of thecalibrated correlations in different hydrometricstation.

6- The result of the assessment of capacity of water passing in the existing rivers shows the high validityof manning relation.

7- The connections and links whose vulnerabilityvalue in times of disaster are more tolerant then therest of the links.

8- The result of the assessment of vulnerabilityvalue of links (bridge) shows the effect rule and safereturn period of flood.

9-According to supervision of some of the bridgeswhich were built based on manning coefficient(n=0.03) were observed.

Fig. 8: The Loaded Road Network of Golestan Province in the condition of link-loss between

Fig. 9: the correlation of the maximum instantaneous discharge in hydrometric station gonbad


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Table 2: The values of flood peak for safe return period

Table 3: The assessment of vulnerability value of the bridges

8. CONCLUSION

The usage of the index suggested in this study forgolestan province shows the use ability of this

procedure. Put this project in priority forreinforcement the link in network in case of the floodcrisis.

As there are two different indexs to prioritize thestrengthening in this paper, and the possibility of theindexs in different network to show not similar resultsof prioritization, In order to make it feasible for thedecision makers to choose a unit preference from all,it would be useful to introduce a proper method.

In this paper to trip assignment, the method ofshortest path is utilized; first of all it would be great to


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study about the method parameters according to thecountry situation, especially the situation of the tripswhich have done after the event. Secondly it isnecessary to propose a good method to tripassignment after the event in the country.

Finding of this paper are prioritizing thestrengthening or reinforcement of the transportationnetwork links after the flood crisis, based on theaccessibility index and combining it by the

vulnerability value. Generally, it can be concludedthat merely using the accessibility index does notsuffice in prioritizing the road network componentsagainst flood. Consequently, another index needs to

be assessed simultaneously with the accessibilityindex. This index is in fact vulnerability value of the

bridge due to flood. In the composed index, a mergedform of these two parameters has been presented.

Fig. 10: The correlation of the maximum instantaneous discharge in hydrometric station ramian

Table 4: The assessment of final composed index for different links of the road network based on travel time


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Table 5: The assessment of final composed index for different links of the road network based on traffic volume and distance

REFERENCES

Advanced EMME/2 Training Manual (2003). UrbanTransportation Research and AdvancementCentre, Toronto, Canada, July 2003.

Ahmad, S, Simonovic S (2001). Integration ofheuristic knowledge with analytical tools forthe selection of flood damage reductionmeasures. Canadian Journal of CivilEngineering, 28: 259 273.

Correia FN, Saraiva MG, Silva FN, Ramos I (1999a).Floodplain management in urban developingareas part I: urban growth scenarios and land-use controls. Water Resources Management,13(1): 1-22.

Correia FN, Saraiva MG, Silva FN, Ramos I (1999b).Floodplain management in urban developingareas part II: GIS-based flood analysis andurban growth modeling. Water ResourcesManagement, 13(1): 23-37.

Davidson RA, Lambert KB (2001). Comparinghurricane disaster risk of U.S. coastal countries.

Natural hazard review, 2: 132-142.Flood studies at Caspian coastal braid with

concentration on Golestan province, JapanInternational Cooperation Agency (JICA),2006, pp. 212-322.

Water resources Management Company (2004). pp.5-10 Guideline for determination design floodreturn Period in river works, Standards andtechnical criteria office, Iran.

Jungyul sohn (2006). Evaluating the significance ofhighway network links under the flood damage.Transportation research part A 40-491-506.

Kim TJ, Ham H, Boyee DE (2002). Economic

impacts of transportation network changes:implementation of a combined transportationnetwork and input-output model. Papers inRegional Science, 81: 223-246.

Lvs GG (1998). On the importance of the buildingevacuation system components. IEEEtanssactions on engineering management, 45:181-191.

Renyi L, Nan L (2002). Flood area and damageestimation in Zhejiang, china. Journal ofenvironment management, 66(1): 1-8.

Traffic volume statistics in Golestan province roads(2004). Iran road transportation andmaintenance organization.

Berdia K (2006). An introduction to roadvulnerability: what has been done, is done andshould be done. Transp policy, 9: 117-127.

Ahmad S, Simonovic S (2004). Integration ofheuristic knowledge with analytical tools forthe selection of flood damage reductionmeasures. Canadian Journal of CivilEngineering, 28: 259-273.

Lekuthai A, Vongvisessomjai S (2006). Intangibleflood damage quantification. Water ResourcesManagement, 15 (5): 343-362.

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McAllister LS, peniston BE, Leibowitz SG,Abbruzzese B, Hyman JB (2000). A synopticassessment for prioritizing wetland restorationefforts to optimize flood attenuation. Wetlands,20(1): 70-83.

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Associate professor Dr. Ali Mansour Khaki obtained his first degree from Iran University Science andTechnology in civil engineering in 1971.He later pursued master degree in road and transportationengineering in University of Kansas America and graduated in 1978. Dr. Khaki received his doctoratefrom University of Kansas America in1980. With major in Road and Transportation engineering. He has

published numerous refereed article in professional journals. Dr. Khaki also has conducted numerousconsultancies and research works at national and international level. His vast experience intransportation planning has enabled him to conduct numerous talks and seminars at national andinternational level.

Associate professor Dr. Afshin Shariat Mohaymany obtained his first degree from Iran university scienceand technology in civil engineering in 1990. He later pursued Master degree in transportation engineeringin Iran University Science and Technology and graduated in 1995. Dr. Shariat received his doctorate fromIran University Science and Technology in 2001 with major in transportation engineering. He has

published numerous refereed articles in professional journals. Dr Shariat also has conducted numerousconsultancies and research works at national and international level. His vast experience in transportation

planning has enabled him to conduct numerous talks and seminars at national and international level.

Seyyed Hossein Sadati Baladehi is a Ph.D candidate in transportation engineering at iran university ofscience and technology and a recipient of Islamic Azad University, Gorgan Branch scholarship. Hereceived his first degree from Islamic Azad University, Gorgan Branch in 1995 awarded in civilengineering. He obtained degree in Master of Science in transportation engineering from Iran Universityof Science and Technology in 1997 with major in transportation engineering. His current research isfocuses on vulnerability value and accessibility indexs. To date, he has published several scientific articlesrelated to transportation engineering field.

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