Identification of urban flood vulnerability in eastern ... · Municipality, southern Thailand using GIS and satellite imagery. Yahayaet al., (2010) identified flood vulnerable areas

Urbanism Identification of urban flood vulnerability in easternSlovakia [...] • L. Gaňová et. al.

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IDENTIFICATION OF URBAN FLOOD VULNERABILITY INEASTERN SLOVAKIA BY MAPPING THE POTENTIAL

NATURAL SOURCES OF FLOODING - IMPLICATIONS FORTERRITORIAL PLANNING

Lenka GAŇOVÁPhD, Technical University of Košice, Faculty of Civil Engineering, e-mail:

[email protected]

Martina ZELEŇÁKOVÁAssociate Professor, PhD, Technical University of Košice, Faculty of Civil

Engineering, e-mail: [email protected]

Pavol PURCZPhD, Technical University of Košice, Faculty of Civil Engineering, e-mail:

[email protected]

Daniel Constantin DIACONULecturer, PhD, University of Bucharest, Faculty of Geography, e-mail:

[email protected]

Tomáš ORFÁNUSPhD, Institute of Hydrology, Slovak Academy of Sciences, e-mail:

[email protected]

Žofia KUZEVIČOVÁAssociate Professor, PhD, Technical University of Košice, Faculty of

Mining, Ecology, e-mail: [email protected]

Abstract. The aim of the presented study was to assess the distribution offlood-risk potential (FRP) at the regional scale. A progressive approachintegrating geographical information system (GIS) with two differentmethods of multicriteria analysis (MCA) – analytic hierarchy process(AHP) and ranking method (RM) was applied in the process. In theanalyses, the most causative factors for flooding were taken into account,urban spatial planning, such as soil type, daily precipitation, land use, sizeof the catchment and average basin slope. A case study of floodvulnerability identification in the Hornád and Bodrog catchments’ areas ineastern Slovakia has been employed to illustrate two different approaches.Spatial estimation of FRP should be one of the basic steps for complexgeoecological evaluation and delimitation of landscape considering waterresources management, groundwater pollution, prediction of soil erosionand sediment transport and some other important landscape-ecologicalfactors. The obtained results indicate that RM method shows better resultsas related to the existing floods in the recent years in Bodrog and Hornádcatchment than AHP method.

• Urbanism. Arhitectură. Construcţii • Vol. 8 • Nr. 4 • 2017

366

Key words: territorial planning, flood vulnerability, geographicalinformation system, multicriteria analysis.

1. IntroductionThe increase in damage due to naturaldisasters is directly related to the numberof people who live and work in hazardousareas and who continuously accumulateassets. Land-use planning authoritiestherefore have to manage effectively theestablishment and development ofsettlements in flood-prone areas in orderto prevent further increase in vulnerableassets (Petrow et al., 2006; Korytárová etal., 2007). Flood risk analysis provides arational basis for prioritizing resourcesand management actions. Risk analysiscan take many forms, from informalmethods of risk ranking and risk matricesto fully quantified analysis (Hall, 2010;Hassan et al., 2006).

Multicriteria analysis (MCA) methodshave been applied in several studies inflood risk assessment. Chandran and Joisy(2009) introduced an efficientmethodology to accurately delineate theflood hazard areas in Vamanapuram riverbasin in a GIS environment. Yalcin andAkyurek (2004) applied a GIS-basedmulticriteria evaluation in order toanalyse the flood vulnerable areas insouth-west coast of the Black Sea. Theranking method and pairwise comparisonmethod were introduced and applied inthis study. Tanavud et al., (2004) assess therisk of flooding and identified efficientmeasures to reduce flood risk in Hat YaiMunicipality, southern Thailand usingGIS and satellite imagery. Yahaya et al.,(2010) identified flood vulnerable areas inHadejia-Jama’are river basin Nigeria byusing a spatial multicriteria evaluationtechnique. Pairwise comparison method,analytical hierarchy process and rankingmethod were applied in the study.

Scheuer et al., (2011) present an approachto modeling multicriteria floodvulnerability which integrates theeconomic, social and ecological dimensionof risk and coping capacity (Pintilii et al.,2016). The approach is tested in an urbancase study, the city of Leipzing, Germany.Kandilioti and Makropoulos (2012)applied three different multicriteriadecision rules (analytic hierarchy process,weighted linear combination and orderedweighting averaging) to produce theoverall flood risk map of the area. A GIS-based multicriteria flood risk assessmentmethodology was developed and appliedfor the mapping of flood risk in theGreater Athens area and validated for itscentral and the most urban part. Meyer etal., (2009) developed a GIS-basedmulticriteria flood risk assessment andmapping approach (Shamsi 2002; Ramlaland Baban, 2003; Scolobig et al., 2008). Theapproach is applied to a pilot study for theRiver Mulde in Saxony, Germany. Twodifferent multicriteria decision rules, adisjunctive and an additive weightingapproach, were utilized for an overallflood risk assessment in the area (Șerban etal., 2016). Kenyon (2007) introduced studybuilds on existing deliberative processesto develop a new participant-ledmulticriteria method to evaluate flood riskmanagement options in Scotland. Theresults show that participants preferredregeneration or planting of nativewoodland to other flood managementoptions, and least preferred building floodwalls and embankments (Simonovic 2002).

Flood risk assessment remains a maindirection in scientific research to assistdecision indispensable in specificterritorial management decision making.


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In numerous studies it starts from asystemic approach to planning,presenting variable components on whichone can act to reduce imbalances (Petrisoret al., 2015a; 2015b; 2015c; Peptenatu et al.,2012a; 2012b; 2014; Ladzianska and Finka,2014; Ran and Nedovic-Budic, 2016; Tiraet al., 2006; Gourbesville and Laborde,2006; Van Alphen et al., 2009; Saelze andUrbina, 2015).

Fig. 1. Location of the study area with the Hornádand (Slovakian part of) Bodrog river basins

The aim of the presented study is toevaluate the applicability of two MCMfor the flood-risk assessment under thespecific conditions of eastern Slovakiaand to generate a composite floodvulnerability map of this region fordecision makers.

1.1. Study areaThe areas most endangered by floods inSlovakia lie in the eastern part of thecountry, particularly in the Bodrog andHornád river basins (Fig.1.). Themorphological type of terrain in theHornád valley is dominated by rollinghills, higher and lower uplands. Thesouthern sub-basin is part of the lowlandand the Slovakian Karst and is formed bymoderately higher uplands. Themorphological type of the relief is

predominantly flat in the southern partbut hilly in the northern part. Themountainous parts of the Bodrog basinare built mostly by flysh susceptible toquick runoff generation and subsequentsoil erosion, hillslope failures andsediment transport.

The Bodrog river basin has varied climaticconditions. Precipitations are highlydifferentiated. The highest annual totalsare mainly in the eastern bordermountains and Vihorlat where the rainfalltotals are about 1000 mm. Decrease in totalprecipitation is evident in direction tosouth, where the annual totals fall tobelow 800 mm (Zeleňáková and Gaňová,2011). As the climate has become moreextreme during the last three decades, theregion was more times affected by heavyrains, which together with the destabilizedflysh have caused several destructivefloods with loses on both, property andlives in the northern part of the basin.

The floods have a variegated course inthe territory of eastern Slovakia, which iscaused by their differing physical andgeographical conditions. It is with nodoubt, that in a distant past the territoryof eastern Slovakia was frequently theplace of flood disasters, as well. Cities asKosice, Presov, Trebisov, Humenne,Michalovce, Bardejov, Roznava, aredirectly exposed to flood risks.

From preserved records as such thecentury water in the drainage area ofBodrog river the one in 1888 can besupposed. From the biggest floods therecan be mentioned the hundred year waterin drainage area of Bodrog in 1924. Theextended floods occurred also in 1967,1974, 1979 or 1980 (Bajtoš et al., 2006). Thewhole drainage area of the Hornád andBodrog rivers was affected by the lastdisastrous flood in May and June 2010.


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Figure 2 presents the number of flooddays during the period 1990–2015 inSlovakia and in eastern Slovakia,respectively.

Fig. 2. Number of flood days during period 1990–2015

Costs of flood damages at property ofSlovak Water Management Enterprise,s.c. Košice in eastern Slovakia during theperiod 1990–2015 are decreasing (exceptthe extreme flood year 2010). It is causedby the construction of flood protectionmeasures in the catchments. Figure 3present some of flood protectionmeasures that were built in the lastperiod in eastern Slovakia.

2. Materials and methods

2.1. Structure and layoutWater resources management andterritorial planning is one of the fields inwhich multicriteria methods have beenused extensively. On their pioneeringwork in the Netherlands, Nijkamp andVos (1977) used MCA for the planning ofwater resources development. ThereafterMCA has been applied in various floodmanagement cases (Scolobig et al., 2008).GIS analysis has been developed toexamine spatial and temporal patternsand to find associations between variousgeographical factors (Ramlal and Baban,2003).

Fig. 3. Flood protection measures in easternSlovakia

We used two methods in determiningflood vulnerability – the ranking methodand the analytic hierarchy process. Theevaluation procedure consists of the stepspresented at the flowchart in Figure 4.

The analytical hierarchy process (AHP) isa flexible and yet structured methodologyfor analyzing and solving complexdecision problems by structuring theminto a hierarchical framework (Saaty,1980). The AHP procedure is employedfor rating/ranking a set of alternatives orfor the selection of the best in a set ofalternatives. The ranking is done withrespect to an overall goal, which shouldbe broken down into a set of criteria(objectives, attributes) (Boroushaki andMalczewski, 2008).

Ranking method (RM) is used if ordinalinformation about the decision makers’preferences on the importance of criteriais available. In the first step criteria areranked in the order of their importance.In a second step, ranking method is usedto obtain numerical weights from thisrank order (Meyer, 2009).

The initial data required for this studywere acquired from the Atlas of theSlovakian Landscape, and further datawere provided by Slovak WaterManagement Enterprise, s.c. Košice, SoilScience and Conservation Research


369

Institute, Slovak HydrometeorologicalInstitute.

Fig. 4. Methodology of flood vulnerability mapsbased on the natural sources of flooding

Basically two phases are applied in thisstudy to analyze flood vulnerability:firstly to identify the effective factorscausing floods – the potential naturalcauses of flooding, and secondly to applytwo methods of MCA in GIS environmentto evaluate the flood vulnerability of thearea.

2.2. Choosing the determinant factorsThe first step in assessing thevulnerability structure is to identify thefactors affecting flooding on the basis ofan analysis of existing studies andknowledge. We use set of causativefactors concerning mostly hydrologicaland geographical characteristics of thetarget area that can be measured andevaluated. The factors used in this studywere selected due to their relevance inthe study area, and these are listedbelow: soil type, daily rainfall, land use,catchment area, basin slope and spatialplanning of the cities.

GIS has been applied for managing,producing, analyzing and combiningspatial data. The data needed in this

study were produced from collected orexisting data using different kinds ofspatial functions and analysis. ArcGIS3.2 and ArcGIS 9.3 were used fortransferring data to the appropriate GISlayers.

Each factor was divided into classes.Inverse ranking was applied to thesefactor’s classes, with the least important =1, next least important = 2. Thisclassification shall enter into a narrative ornumeric character, as shown in Table 1.

Table 1. Factor’s class and his importanceFactors Factor’s

classesImportanceof factor’s

class(IFi,j)

Daily rainfall 0 – 1,8 mm1,8 – 2,0 mm2,0 – 2,2 mm2,2 mm and

more

1234

Soil type(content of

clay particles)

0 - 10 %10 -30 %30 - 45 %45 - 60 %

60 % and more

12345

Slope 0 - 15%15 - 30 %30 - 45 %45 - 80 %

80 % and more

1 2345

Land use forestagricultural

landurbanized area

12

3Catchment

area0 - 100 km2

100 – 500 km2500 – 1000 km21000 and more

km2

1234

The factor´s classes according Table 1 arepresented in the separate factors maps inFig. 5-8.

Two MCA methods were used fordefining the flood vulnerability in easternSlovakia.


370

2.3. Defining flood vulnerability areas usingMCA approaches

Ranking methodIn the ranking method (RM), everyfactor/criterion under consideration isranked in the order of the decision-maker’s preference. To generate factorvalues for each evaluation unit, eachfactor was weighted according to theestimated significance for flooding.

Fig.5 . Map of daily rainfall

Fig. 6. Map of soil type. Weigh-percentage of theparticles with diameter


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n is the number of criteria underconsideration (k = 1, 2, …, n),

and rj is the rank position of the criterion.

1+-= jrnW (2)

and then normalized by the sum ofweights, that is (Eq. 3)

å +- )1( krn (3)

Table 2 shows weight assessment by theranking method.

Resulting vulnerability was calculatedusing the following formula (Eq. 4):

)( 5544332211 WIFWIFWIFWIFWIFIV jjjjj ++++=å(4)

where:IV is index of vulnerability,IF1j, IF2j, IF3j, IF4j, IF5j are importance offactor’s class,and W1, W2, W3, W4, W5 are thenormalized weights for each criterion.

Fig. 9. Map of catchment area

Analytic hierarchy processThe second method for determining floodvulnerability is the analytic hierarchyprocess (AHP). This is a structured

technique for organizing and analyzingcomplex decisions. Nineteen riverstations in the Latorica, Laborec, Cirocha,Topľa, Ondava, Bodrog, Hornád andTorysa streams were assessed. For eachriver station a matrix 5 x 5 – factors xclass (1 – 5) was established. This matrixwas completed with values from 1 to 5,depending on the class of each factor forthe relevant river station in the followingway: e.g. when a river station is located inan area where rainfall is class one, thenumber 1 is written in column "1" for theline "rainfall", and other values on thisline are zero. In this way the wholematrix was completed for all factors. Anexample of a completed matrix for riverstation Michalovce is shown in Table 3.

Table 2. Weight assessment by the rank sum method

Criterion StraightRankWeight

(W)

Norma-lized

Weight(Wj)

Weight(%)

Daily rainfall 1 5 0.333 33.3Slope ofwatershed

2 4 0.267 26.7

Soil type 3 3 0.20 20.0Land use 4 2 0.134 13.4Size ofwatershed

5 1 0.066 6.6

Sum 15 1 100

Factor’s classes are usually proposedbased on expert knowledge, whichhowever is still the subjective method,which cannot be applied elsewhere. Wesolved this problem of weighting thefactors’ classes using the calculation ofentropy, as follows:A = (aij) decision matrix,i = 1, ..., m (m – number of factors),j = 1, ..., n (n – number of attribute),pij normalized values of jth attributeEj entropy of the set of normalized jthattribute,dj information diversification levelgiven by jth attribute,vj weigh of the jth attribute.


372

Table 3. Matrix for AHP assessmentClass

Station Factor1 2 3 4 5

Daily rainfall 0 2 0 0 0Soil type 0 0 3 0 0Land use 0 2 0 0 0

Basin slope 1 0 0 0 0Michalovce

Size of watershed 0 0 3 0 0

Calculation follows the next algorithm:We normalize the values of attributesfrom the decision matrix:

å=

= m

iij

ijij

a

ap

1

(5)

For each i, jIn the next step we calculate the entropyof the jth attribute:

)ln(ln

11

ij

m

iijj ppm

E å=

´-= (6)

For each jWe calculate the diversification levelgiven by jth attribute:

jj Ed -= 1 (7)

For each jThe result is normalized and the weightsare obtained:

å=

= n

ii

jj

d

dv

1

(8)

For each ji.e. for each evaluation category.

3. Results and DiscussionThe multicriteria analysis ends with amore or less stable ranking of the givenalternatives and hence a recommendationas to which alternative(s) should bepreferred. The spatial variability of floodvulnerability is an important part of floodrisk assessment on the national level, as

well as for application of spatiallydifferentiated approaches to flooddefense strategy (Solín and Skubinčan,2013).

Regarding our task of flood vulnerabilityassessment, the result will be a ranking orcategorization of areas with regard totheir flood vulnerability level, and hencea recommendation as to where floodmitigation action is most required. Theflood vulnerability was evaluated in fourclasses – acceptable, moderate,undesirable and unacceptable (Table 4) –arranged according to MILSTD 882DStandard practice for system safety.

Table 4. Vulnerability acceptability and itssignificance

Scale ofvulnerabilityVulnerabilityrate /

acceptability

Significance offlood

vulnerabilityin watershed AHP RM

1 / acceptable

Vulnerability inwatersheds are

acceptable –current practice

0 -0,025

1 -1,73

2 / moderate

Vulnerability inwatersheds are

moderate –condition of

continualmonitoring

0,0256- 0,050

1,73 -2,13

3 /undesirable

Vulnerability inwatersheds areundesirable –

flood protection

0,051 -0,075

2,13–

2,46

4 /unacceptable

Vulnerability inwatersheds areunacceptable –

immediateflood protection

0,076and

more

2,46and

more

Vulnerability´s classes were dividedusing Box plot method (Tukey, 1977).

A composite map showing the floodvulnerability created using the rankingmethod with ArcGIS 9.3 is presented inFigure 10. The calculated areapercentages of particular vulnerability


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classes were 18.43 % (acceptable), 40.25 %(moderate), 28.99 % (undesirable) and12.33 % (unacceptable) respectively.

Fig. 10. Map of flood vulnerability in the studyarea based on the ranking method

The resultant weightings with analytichierarchy process for all river stations areshown in Table 4. River stations areranked by the value of weightings fromlargest to smallest.

Table 4. Resultant weightings for river stations

Riverstation Weight

Riverstation Weight

Krásny Brod 0.102286 SpišskéVlachy 0.049978

Stropkov 0.080597 Horovce 0.049406

Michalovce 0.072222 KošickéOlšany 0.049406

SpišskáNová Ves 0.065754 Ždaňa 0.049406

Snina 0.055459 Bardejov 0.047895Hanušovce 0.055459 Ižkovce 0.029255

Prešov 0.055459 VeľkéKapušany 0.029255

Sabinov 0.055459 Kysak 0.027339

Svidník 0.055459 Streda nadBodrogom 0.018550

Humenné 0.051357

The flood vulnerability in the study areawas evaluated in four classes accordingTable 4. The obtained results fromsoftware ArcGIS 9.3 are presented in Fig.11.

The flood vulnerability assessment basedon the analytic hierarchy process showsthat the Bodrog and Hornád watershedsare formed mainly by areas with

moderate and undesirable floodvulnerability. Zones with unacceptableand acceptable level of floodvulnerability were also identified, butwith only relatively small areas. Theundesirable zone covers most of thenorthern part of eastern Slovakia andrepresents 65.51 % of the study area.

Fig. 11. Map of flood vulnerability in the studyarea based on the analytic hierarchy process

Unacceptable level of flood vulnerabilitywas found in the surroundings of KrásnyBrod and Stropkov and represents 3.43 %of the study area. The south-eastern partof Slovakia falls in the moderatevulnerability zone, and the percentagearea of this zone is 30.42 %. Acceptableflood vulnerability is found in a verysmall part of the territory covering 0.64 %of the assessed area. The area ofacceptable level of flood vulnerability wasdetected around Streda nad Bodrogom inthe southern part of Slovakia.

As described above, we created twomulticriteria vulnerability maps forBodrog and Hornád watershed. Our pilotstudy showed significant differencesbetween both methods shown in Figure12. The different results obtained fromthese two methods indicate theimportance of the decision maker indetermining the weights and the propermethod, and making the decision. Theweighting of the criteria significantlyaffects the results of the overall evaluation.


374

Flood vulnerability is a joint effect of twoindependent mechanisms naturalconditions and the human activities in thebasin. The primary impulses of floods areusually extremely intense precipitation.

The total catchment’s hydrologicalresponse to intense rainfall is determinedby its natural environment, a wholecomplex of characteristics of the riverbasin. Some of them may the processinitiated by the intense rain evenaccelerate, respectively amplified.

Although floods are natural phenomena,human activities and humaninterventions into the processes of nature,such as alterations in the drainagepatterns from urbanization, agriculturalpractices and deforestation, haveconsiderably changed the situation inwhole river basins (Watts, 2013). On theother hand, human activities such asconstruction of flood measures canreduce negative impacts of floods. Forexample if area with high vulnerabilityindex has a flood protection, indexvulnerability can become lower.

If we compare different methodregarding percentage area of floodvulnerability zone (Fig. 12) we can see,that the results obtained with the rankingmethod are more representative.

Fig. 12. Percentage area of each floodvulnerability zone

The results are mostly coincident with theresults from preliminary flood riskassessment which has to be done in the

Slovak Republic in 2011. The results ofmentioned assessment are presented inFig. 13. The geographical areas withexisting potentially significant flood riskare marked in red color. The geographicalareas with probable potentiallysignificant flood risk are marked inyellow color (MŽP SR, 2011).

Fig. 13. Geographical areas with potentiallysignificant flood risk (MŽP SR, 2011)

It should be noted that RM methodshows better results as related to theexisting floods in the recent years. In thiscase AHP method is not suitable foranalyzing the flood vulnerable area. Thedevelopment of RM method for wholeBodrog and Hornád catchment has theadvantage that there is a method which iseasy to apply.

4. ConclusionFlood disaster has a special place amongthe natural hazards and is considered as amajor environmental risk due to itsdevastating effects on the impacted area.Generating flood extent models andmapping flood vulnerable areas is one ofthe ways how to study the integralimpact of regional environmentalchanges on flooding at regional scale.

This paper presents work carried out inthe Hornád and Bodrog basins in easternSlovakia involving the use of GIS tools


375

and multicriteria analysis methods togenerate maps of flood vulnerable areas.

The level of flood vulnerability wasevaluated in four classes (acceptable,moderate, undesirable, andunacceptable). The composite maps (Fig.10, 11) showing the flood vulnerabilityprovide a comparison of results based onuse of the ranking method with thoseobtained through the analytic hierarchyprocess in ArcGIS 9.3. The rankingmethod manifested higher ability tofollow the real recent flood history inparticular subregions than does the AHP.

A flood-risk map can be a quick decisionsupport system tool to study the impactof either planned or unplanned humanactivities on the catchment area of theriver system. The future upgrading ofthese regional maps assumes theincorporation of the drainage density,evaporation, percolation as well as factorslike frequency of flood, inundation depth,duration of flood, etc.

ACKNOWLEDGEMENTThis work was supported by VEGAproject 1/0609/14.

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Received: 12 December 2016 • Revised: 21 December 2016 • Accepted: 23 December 2016

Article distributed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

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Identification of urban flood vulnerability in eastern ... · Municipality, southern Thailand using GIS and satellite imagery. Yahayaet al., (2010) identified flood vulnerable areas