Using Multiple Index Comprehensive Method to Assess Urban Rainstorm Disasters Risk in Jiangsu Province, China

Transcription

1 0 Artcle Usng Multple Index Comprehensve Method to Assess Urban Ranstorm Dsasters Rsk n Jangsu Provnce, Chna Junfe Chen,,, *, Mengchen Chen and Pe Zhou State Key Laboratory of Hydrology-Water Resources and Hydraulc Engneerng, Hoha Unversty, Nanng 00, Chna; Insttute of Management Scence, Hoha Unversty, Nanng 00, Chna; Natonal Engneerng Research Center of Water Resources Effcent Utlzaton and Engneerng Safety, Hoha Unversty, Nanng 00, Chna; * Correspondence: chenunfe@hhu.edu.cn; Tel.: Abstract: A new model for rsk assessment of urban ranstorm dsasters, based on nformaton dffuson method and varable fuzzy sets (IDM-VFS) was proposed. In addton, an ntegrated ndex system of urban ranstorm rsk was establshed. In the proposed model, IDM was employed to calculate the classfcaton standards of urban ranstorm rsk levels, then the VFS was adopted to assess the dangerousness, senstvty, vulnerablty and comprehensve rsk of urban ranstorm dsasters. In the present study, the urban ranstorm rsk of Jangsu provnce was evaluated wth the proposed model. The results show that Wux, Changzhou, Nanng and Suzhou have hgher dangerousness, due to sustaned ranfall and strong ranfall ntensty n short duraton; Wux, Changzhou and Nanng have hgher senstvty because of lower dsaster resstance ablty; and Wux and Suzhou have hgher vulnerablty because these ctes have hgher potental losses n face of urban ranstorm dsasters. The comprehensve rsk zonng map of urban ranstorm shows apparent regonal characterstcs: the northwestern ctes have lower rsk than the southern ctes. Moreover, most ctes of the Jangsu provnce are of the moderate urban ranstorm rsk level. The results are consstent wth the actual stuaton of Jangsu provnce, and the study can provde some decson-makng references for the urban ranstorm management. Keywords: urban ranstorm dsasters; rsk assessment; nformaton dffuson method (IDM); varable fuzzy sets (VFS); Jangsu provnce 0. Introducton Wth the global clmate change and the rapd developments of the urbanzaton, many ctes are suffered extreme ranstorm events frequently []. About % of the global populaton s under the threat of the ranstorm dsasters as a consequence of combned mpacts of clmate change phenomenon and rapd populaton growth, also the ranstorm events tend to ncrease both n frequency and magntude [-]. Accordng to EM-DAT and Munch RE dsaster databases, flood losses account for % of the total global dsaster losses. Now the urban ranstorm dsasters occur more frequently n bg ctes n the world, whch causes great mpacts on urban traffc safety and brngs about severe economc losses [,]. In Chna, more than 00 ctes are exposed to frequent floodng, whch has a huge socal, economc and envronmental mpact []. Frequent urban ranstorms have severely restrcted the stablty of Chna s urban developments []. Therefore, t s mportant to assess the rsk of urban ranstorm dsasters, whch can help to mprove the predcton ablty and to reduce the losses caused by urban ranstorm dsasters. 0 by the author(s). Dstrbuted under a Creatve Commons CC BY lcense.

2 of In order to assess the rsk of urban ranstorm dsasters, t need buld a reasonable and effectve assessment system. Over the years, several dsaster rsk assessment systems of urban ranstorm have been developed. Urban ranstorm s a multvarate phenomenon whch s always assessed by many ntegrated ndces, ncludng economc loss data, socal mpact and emergency performance, etc [-]. Lyu et al. [] selected rany season, average ranfall, average rany days, elevaton and slope, rver proxmty, rver densty, land use, metro lne proxmty, metro lne densty and road network proxmty and densty to construct a rsk assessment system of metro systems, and took Guangzhou metro system as an example to conduct an emprcal study. Alfa [] proposed a flood rsk assessment of Ofu rver catchment n Ngera, ncludng elevaton, slope, proxmty and sol type. Weerasnghe et al [] put forward the rsk assessment system of ranstorm for the Western Provnce of Sr Lanka, and use a statstcal expresson of hazard, exposure and vulnerablty to assess the combned flood rsk levels. These researches lad a good foundaton for the rsk assessment ndex system of urban ranstorm dsasters. Therefore, n order to assess the rsk of urban ranstorm dsasters effectvely, ths paper establshes the urban ranstorm assessment system wth dangerousness ndces of hazardformatve factors, senstvty ndces of hazard-nducng envronments, and vulnerablty ndces of hazard-affected bodes. Then n order to assess the rsk of urban ranstorm dsasters properly, t s necessary to adopt scentfc and effectve methods. Many studes have focused on hydrologcal and meteorologcal models or tradtonal assessment methods to assess the rsk of urban ranstorm dsasters. For example, Jonkman et al. [] proposed a model for the estmaton of damage caused by ranstorm n the Netherlands. Ths ntegratve character of the presented model s featured by the combnaton of nformaton on land use and economc data, and data on flood characterstcs and stage-damage functons. Wang et al. [] developed a generalzed rsk assessment model of ppelne network, n combnaton wth crtcal data of urban plan, as well as hydrologc data, and used Storm Water Management Model (SWMM) to optmally analyze on the rate of mpervous area of upper catchments areas as well as the desgn standard of lower dranage ppelne. Shao et al. [] used the methodology of gray fxed weght cluster analyss to assess the dsaster losses from 00 to 00 based on the 0 hstorcal sample data. Some advanced technologes such as GIS (Geographc Informaton System) and remote-sensng magery [-] are used for rsk assessment of urban ranstorm dsasters. Whle urban ranstorm dsasters are dffcult to quantfy accurately manly because of the lack of suffcent data []. So fuzzy and uncertanty theores can be ntroduced nto the rsk assessment of urban ranstorm dsasters, such as fuzzy comprehensve evaluaton [], nformaton dffuson [], varable fuzzy sets (VFS) []. However, there are some drawbacks n these methods, for example, the fuzzy comprehensve evaluaton cannot well resolve the duplcaton nformaton caused by related evaluaton ndces; the establshment of the relatve membershp functon of the varable fuzzy sets depends on physcal analyss and experts udgments []. Hence, takng these factors nto consderaton, t can combne the advantages of dfferent methods to construct a new approach. Urban ranstorm dsasters lack enough data to assess, whle the nformaton dffuson method (IDM) can compensate for the ncomplete nformaton of small samples. And the rsk of urban ranstorm dsasters s ambguous and uncertan, t have many dfferent ndces to calculate. So t can use the varable fuzzy sets (VFS) to elmnate the border effect on assessment results effectvely and make full use of varous ndces data to obtan comprehensve rsk evaluaton results. In ths paper, IDM was combned wth VFS as an ntegrated model to assess the rsk of urban ranstorm dsasters.the IDM s employed to calculate the level classfcaton standards of assessment ndces, and then the VFS s adopted to assess the comprehensve rsk of urban ranstorm. Through ntegrated assessment system and IDM-VFS model, Jangsu provnce n Chna can be taken as a case study area. The paper s organzed as follows. Secton descrbes the overvew of study area, then the data and methods are followed n Secton. Secton depcts the man results and analyss. The dscusson and conclusons of the study are presented n Secton.

3 of 0. Overvew of Study Area Ths paper takes Jangsu provnce as the study area. Jangsu provnce (Fgure ), whch s located between E- E and 0 N- 0 N, the total land area s.0 0 km, accountng for.% of the total area of Chna. The geomorphology of Jangsu s manly plans, coverng % of the total area. The elevaton of most area s lower than 0m []. There are prefecture-level ctes n Jangsu provnce, ncludng Nanng (provncal captal cty), Wux, Xuzhou, Changzhou, Suzhou, Nantong, Lanyungang, Hua an, Yancheng, Yangzhou, Zhenang, Tazhou and Suqan. Jangsu provnce has become one of the most urbanzed regons, all the ctes n Jangsu provnce are prosperous ctes n Chna. In recent years, urban ranstorm dsasters have occurred frequently and caused huge losses n each cty of Jangsu provnce. Thus, urban ranstorm has become one of the most mportant factors that restrct the development of Jangsu provnce. Jangsu provnce belongs to the subtropcal monsoon clmate, t s usually hot and rany n summer, and most of the large-scale precptaton n Jangsu provnce s n summer. Thus, n order to better show the actual stuatons of the urban ranstorm dsasters of Jangsu provnce, ths paper emphaszes on the perod whch s from June to August. 0 Fgure. Geographc locaton of Jangsu Provnce, Chna.. Data and Methods.. Data Sources Ths paper uses Jangsu Statstcal Yearbook data and Chna Cty Statstcal Yearbook data from the Natonal Bureau of Statstcs of Chna to collect the statstcal nformaton of all ctes n Jangsu provnce ncludng economc, socal, demographc,, urban constructon, envronmental and other related cty statstcs. The meteorologcal data and the ranfall statstcs are collected from the meteorologcal statons of ctes n Jangsu provnce. Some other hstorcal precptaton statstcs are provded from the Jangsu clmate center... Weght of Index System The rsk assessment ndex system of urban ranstorm dsaster ncludes a lot of ndces. The ndex weght reflects the relatve mportance of each ndex n the rsk assessment ndex system. In ths paper, the AHP (Analytc Herarchy Process) and entropy weght method are combned to calculate

4 of 0 the weghts of ndces. The AHP s a subectve method to determne the weght of ndces based on experts experence []. The entropy weght method s an obectve method that determnes the mportance of ndex based on the data nformaton []. Ths combned method can reduce the nterference of the ndvdual's subectve udgments on the weghts of ndces. Therefore, t can make the weghts more realstc and relable relatvely [0]. The dea of calculatng weghts s to calculate the subectve weghts of ndces by AHP, and then to establsh the entropy model of expert's own weghts by usng the subectve weghts of ndces as attrbute matrces through the dea of nformaton entropy. The weghts of the ndces are corrected by the weghts of the experts, and the fnal combnaton weghts are obtaned. Suppose the weghts calculated by AHP are the subectve weghts of ndces. The subectve weghts of ndces can be represented as follows: where the z z ( w, w, w ) T W, = () z z W s the subectve weght vector, then the 0 w < and w = ( s =,,, r; z =,,, v ). zr < zs Then the expert's own weghts are calculated by entropy weght method, t can be shown as follows: where the S ( S, S, ) T S, S v r s= = () s expert's own weght vector and, and 0 S < ( z =,,, v ) and S =. Fnally, the weght fuson vector of subectve weghts and expert's own weghts can be W w, w,, w r expressed as ( ) T < z =, and t can be calculated as follows: v z= zs z w s = v ( wzs Sz ) z= () 0 0 where 0 w <, w = and s =,,, r; z =,,, v. < s r s= s.. Informaton Dffuson Method (IDM) Ths paper uses normal nformaton dffuson method, IDM s a knd of fuzzy mathematcal processng method whch can be used to optmze the fuzzy nformaton of samples by means of approprate dffuson model []. When the sample s ncomplete, the method can make the dffuson estmaton closer to the real relatonshp than the non-dffuson estmaton. Ths method can establsh the level classfcaton standards of the urban ranstorm dsasters assessment ndces to mprove the evaluaton accuracy []. Based on the hstorcal data of Jangsu provnce, the dfferent rsk levels of ndces were determned accordng to classfcaton standards. The prncple of nformaton dffuson method can be expressed as follows: suppose X ( { n} When the X s ncomplete, there exsts an approprate dffuson functon ( x u) correspondng operator γ ', whch can transform X nto a fuzzy sample ( ) X= x, x,, x ) s a gven sample, t can be used to estmate a relatonshp on a doman U. f, and the D X, so that the nformaton wth a value of from the sample X can be dffused around the sample followng the f x, u, and the dffuson estmate R s closer to the real relatonshp than the non- functon ( ) dffuson estmate ˆR [-]. It can be shown n the Fgure.

5 of 0 Fgure. The prncple of nformaton dffuson method. The calculaton steps of the nformaton dffuson are shown as follows: Frstly, the rsk levels of urban ranstorm dsasters are dvded nto fve levels, that s lowest rsk, lower rsk, moderate rsk, hgher rsk and hghest rsk. The nformaton carred by x ( =,,, n ) whch can be chosen from the sample X can be dffused nto u ( =,,, m ) from the doman U accordng to Equaton (). f ( u ) exp h π ( x u ) = where h s the dffuson coeffcent whch can be calculated by dfferent szes and values of the samples. f s Secondly, n order to make each set of sample values dentcal, the dffuson functon ( ) u normalzed to be the dffuson functon g ( u ): g ( u ) f ( u ) f ( u ) = m = h () () So the probablty of samples located n F ( u ) u can be represented as follows: n g = = m n = = ( u ) g ( u ) Fnally, the exceedng probablty F * ( u ) can be obtaned through Equaton (): () 0 m ( u ) = F( u k ) F * () Accordng to the classfcaton standards of exceedng probablty, the crtcal value of each evaluaton ndex correspondng to the rsk level of urban ranstorm s obtaned, so the level classfcaton standards of urban ranstorm rsk assessment ndces can be obtaned... Varable Fuzzy Set (VFS) Varable fuzzy set theory s manly used n the dynamc analyss of fuzzy phenomena n the system []. As ts core, relatve membershp functon, relatve dfference functon and varable fuzzy set quantfy the process of changng thngs from quantty to qualty and descrbe t wth mathematcal k =

6 of languages. By changng model and model parameters, the credblty and relablty of evaluaton, dentfcaton and decson-makng can be ncreased, whch provdes new deas for rsk assessments n many felds [, ]. Fuzzy varable evaluaton method calculates the evaluaton level of urban ranstorm dsasters scentfcally by changng the model and ts parameter combnaton, and t can mprove the relablty of rsk assessment results. The fuzzy varable evaluaton method manly ncludes the followng steps: () Generatng ndex egenvalue matrx Suppose there s a sample set Y = y, y,, y } consstng of n samples of natural dsasters. { n y = y, y,, yr, number of sample ndces. Then the sample set can be express as Y ( y s ) r n 0 0 The ndex egenvalue of the sample can be expressed as ( ) T s =,,, r; =,,, n. where r s the =, where () Establshng ndex standard egenvalue matrx Suppose there are m levels of assessment classfcaton standards. And sample set s dentfed accordng to dfferent standards of egenvalues of r sample ndces, and then the standard egenvalue matrx of the frst order ndex s obtaned. () Calculatng the relatve membershp matrx of ndex level The nterval matrx and the bound matrx of varable set of ndces can be determned by referrng to the standard value matrx of ndces and the actual stuaton of the area. Then accordng to the dfferent egenvalues of samples L, so relatve membershp degree matrx can be calculated as follows: y, the dfferent degree ( ) A s ( y ) s = + LA ( y ) s A y s μ () () Determnng the weght of each ndex and the relatve membershp degree Accordng to the Equaton (), the non-normalzed relatve membershp degree can be calculated as follows: 0 where w s ( s,,, r) T * h = + r s= r [ w ( μ ( y ))] s= s [ w μ ( y )] s A A = s the ndex weght that can be calculated by Equaton (). And r s the dentfy number of ndces, h s the rsk level number where parameter( α =, ), P s the dstance parameter, P = s Hammng dstance and P = s s s P α P () h =,,, m,α s the optmal rule Eucldean dstance. Then the normalzed relatve membershp degree can be calculated as follows: T T * h = h m * Th h= Fnally, accordng to the prncple of the largest degree of membershp, we can obtan the rsk levels of urban ranstorm dsasters. (0)

7 of 0 0. Results and Analyss.. Rsk Index System of Urban Ranstorm The reasonable assessment ndces of urban ranstorm dsasters should be able to accurately descrbe the rsk of urban ranstorm dsasters. Therefore, In ths paper, an ntegrated rsk assessment ndex system of urban ranstorm dsasters was establshed (see Table ). The ndex system s dvded nto three subsystems ncludng dangerousness, senstvty and vulnerablty. The dangerousness ndces reflect the abnormal condtons and factors of external natural envronment. The rsk of urban ranstorm dsasters can be attrbuted to short-term ranfall far exceedng normal stuatons or long-term ranfall n ctes, whch wll lead to the arranged dscharge of ranwater beyond the capacty of urban dranage network. Generally, the larger the dangerousness s, the hgher the rsk of urban ranstorm dsasters s. Ths paper chooses contnuous ranfall days (I: days), heavy ran days (I: days), maxmum ranfall n h (I: mm), monthly total ranfall (I: mm) and precptaton anomaly percentage (I: %) as the evaluaton ndces of dangerousness. The senstvty ndces represent that a partcular regon s potental to the destructon and nfluence of dsasters due to varous natural and socal factors []. Jangsu provnce s located n the plan area wth low alttude, and t s easy to cause floods once t encounters ranstorms. And rapd urbanzaton leads to the change of urban surface attrbutes. The urban surface s mostly mpervous and hardened surface, whch leads to the rapd convergence of surface ranwater under extreme ranstorms. The constructon of dranage ppelne network n ctes also has not kept pace wth the development of the cty. So the urban average elevaton (I: m), urban green coverage rate (I: %), urban dranage network densty (I: km/km ), urban water area percentage (I: %) and mpermeable constructon land (I: km ) were selected as the senstvty ndces. The vulnerablty ndces descrbe the potental losses of the area exposed to the rsk [0]. It refers to the possble mpact of urban ranstorm dsasters n the urban, that s, the level of loss caused by urban ranstorm. It s generally beleved that densely populated, ndustrally developed ctes suffer greater rsks and losses n face of the urban ranstorm dsasters. The vulnerablty ndces nclude the densty of affected populaton (I: people/km ), GDP of unt area (I:00 mllon yuan/km ), dsaster relef nvestment level (I:%) and publc emergency response capablty (I). Table. Rsk assessment ndex system of urban ranstorm dsaster. Target layer Prmary ndces Secondary ndces Dangerousness Contnuous Ranfall Days(I:days) Heavy Ran Days (I:days) Maxmum Ranfall n h (I:mm) Monthly Total Ranfall (I:mm) Precptaton Anomaly Percentage (I:%) Urban Average Elevaton (I:m) Urban Ranstorm Dsaster Rsk Urban Green Coverage Rate (I:%) Senstvty Urban Dranage Network Densty (I:km/km ) Urban Water Area Percentage (I:%) Impermeable Constructon Land (I:km ) Densty of Affected Populaton (I:people/km ) Vulnerablty GDP of Unt Area (I:00 mllon yuan/km ) Dsaster Relef Investment Level (I:%) Publc Emergency Response Capablty (I) 0.. Rsk Evaluaton Based on IDM-VFS Model Based on the rsk assessment ndex system and IDM-VFS model, frstly the AHP was combned wth entropy method to determne the weghts of the rsk ndces of urban ranstorm dsasters; then the IDM was adopted to determne the classfcaton standards of the rsk ndces; and the dsaster rsk values n dangerousness, senstvty and vulnerablty can be calculated by the VFS model respectvely. Fnally, the comprehensve dsaster rsk levels were obtaned and the rsk zonng map was drawn.

8 of... Determne the Weghts of Rsk Indces Indces weghts are determned by combned AHP and entropy weght method. The weghts of rsk assessment ndces are shown n Table. Table. The ndex weghts of urban ranstorm dsasters. Prmary ndces Dangerousness Senstvty Vulnerablty Secondary ndces Weght ω Contnuous Ranfall Days(days) 0.00 Heavy Ran Days (days) 0.0 Maxmum Ranfall n h (mm) 0.0 Monthly Total Ranfall (mm) 0.0 Precptaton Anomaly Percentage (%) 0.0 Urban Average Elevaton (m) 0.0 Urban Green Coverage Rate (%) 0.0 Urban Dranage Network Densty (km/km ) 0.0 Urban Water Area Percentage (%) 0.0 Impermeable Constructon Land (km ) 0. Densty of Affected Populaton (people/km ) 0.0 GDP of Unt Area (00 mllon yuan/km ) 0.0 Dsaster Relef Investment Level (%) 0.0 Publc Emergency Response Capablty Calculate the Level Classfcaton Standards of Indces The level classfcaton standards of each rsk assessment ndex of urban ranstorm dsasters are determned by IDM. Frstly, the ndex values can be taken as samples of nformaton dffuson, then the exceedng probablty of each ndex also can be calculated. Fnally, the level classfcaton standards of each rsk assessment secondary ndces are obtaned (see Table ). Table. Level classfcaton standards of rsk assessments secondary ndces. Secondary Indces Frst Level Lowest Second Level Lower Thrd Level Moderate Forth Level Hgher Ffth Level Hghest Contnuous Ranfall Days(days) < ~ ~ ~ > Heavy Ran Days (days) < ~ ~ ~ > Maxmum Ranfall n h (mm) < ~0 0~00 00~00 >00 Monthly Total Ranfall (mm) <0 0~ ~ ~ > Precptaton Anomaly Percentage(%) < ~ ~0 0~00 >00 Urban Average Elevaton (m) > ~0 0~0 0~ < Urban Green Coverage Rate (%) >0 0~0 0~0 0~0 <0 Urban Dranage Network Densty (km/km ) > ~ ~ ~0 <0 Urban Water Area Percentage (%) >0 0~0 0~ ~0 <0 Impermeable Constructon Land (km ) <0 0~ ~ ~0 >0 Densty of Affected Populaton (people/km ) < ~ ~ ~0 >0 GDP of Unt Area(00 mllon yuan/km ) <0. 0.~..~ ~ > Dsaster Relef Investment Level (%) > ~ ~ ~ < Publc Emergency Response Capablty >0 0~0 0~0 0~0 <0... Calculate the Dsaster Rsks of Three Subsystems Accordng to Table, the nterval matrx, bound matrx are establshed, and then, based on Equatons ()-(0), the relatve membershp degree matrx and ntegrated membershp degree are obtaned, and fnally the rsk values can be calculated n terms of dangerousness, senstvty and vulnerablty respectvely. For demonstraton purposes, Nanng has been chosen as an example to dscuss the rsk assessment of urban ranstorm dsasters n detal. The rsk values of urban ranstorm dsasters n Nanng n 0 are shown n Table.

9 of 0 Table. Rsk values from June to August n 0 n Nanng. Month Dangerousness Senstvty Vulnerablty June... July... August... Average... As we can see from the Table, dangerousness ndces have dfferent rsk values due to dfferent monthly ranfall and ranfall days. Whle senstvty and vulnerablty ndces reman bascally unchanged n one year. Adoptng the same methods and procedures, we can obtan rsk values of the urban ranstorm n Nanng from 00 to 0 n terms of dangerousness, senstvty and vulnerablty respectvely (see Table ). Table. Rsk values of urban ranstorm from 00 to 0 n Nanng. Year Dangerousness Senstvty Vulnerablty Average... From the Table, the average rsk value of dangerousness s., the average rsk value of senstvty s., and the average rsk value of vulnerablty s.. The dangerousness of 0 s hgher than other years because the precptaton was hgher than the normal level (Fgure (a)), t had sustaned ranfall and strong ranfall ntensty n short duraton. Whle the senstvty and vulnerablty had an upward tendency because of the acceleraton of urbanzaton (Fgure (b),(c)). The mpervous constructon area of the ctes s gradually ncreasng, but the dranage facltes and greenng constructons are not matched, and the densty of affected populaton and GDP were also ncreasng from 00 to 0. Rsk Values Rsk Values Year (a) Year (b)

10 0 of 0 0 Rsk Values Year (c) Fgure. Varaton tendency of rsk values n terms of three subsystems from 00 to 0. (a) dangerousness; (b) senstvty; (c) vulnerablty. By calculatng the average rsk values n dfferent ctes n terms of dangerousness, senstvty and vulnerablty, and weghtng the three subsystems wth weghts, the rsk level of urban ranstorm dsasters can be shown n Table. Table. Comprehensve rsk level n Jangsu provnce. Cty Dangerousness Senstvty Vulnerablty Rsk level Nanng... Wux... Xuzhou... Changzhou...0 Suzhou..0. Nantong...0 Lanyungang... Yancheng... Yangzhou.0.. Zhenang...0 Tazhou... Hua an... Suqan..0. The dangerousness of Wux, Changzhou, Nanng and Suzhou are hgher, whle Xuzhou, Hua an and Suqan are lower from 00 to 0. The maor nfluence factors of dangerousness are sustaned ranfall and strong ranfall ntensty n short duraton. And the precptaton decreased from south to north gradually. The senstvty of Wux, Changzhou and Nanng are hgher, whle Xuzhou and Suqan are lower. The senstvty of urban ranstorm dsasters manly depends on the natural and socal envronment of the ctes and the dsaster resstance level. The condtons of the dfferent ctes n Jangsu provnce are uneven. Because dfferent ctes have dfferent natural and socal envronments, Zhenang, Xuzhou and Suqan have hgher alttudes and less mpervous constructon area whch makes them have lower senstvty. Wux, Changzhou and Nanng are more advanced so they have more mpervous constructon area whch decreased the ablty of dsaster resstance, resultng n hgher senstvty. Lanyungang, Yancheng and Suqan are located n the lowest vulnerablty area, whle Wux and Suzhou are the hghest ctes. The vulnerablty of urban ranstorm s the reflecton of the vulnerable degree of socal economy and human socety capablty to dsasters. Lanyungang, Yancheng and Suqan have lower GDP of unt area and affected populaton densty so they belong to the lower dsaster vulnerablty ctes. The GDP of unt area n Wux and Suzhou s more than 00 mllon yuan/ km and the populaton densty s hgher, leadng to the hghest urban ranstorm vulnerablty. The comparsons of dfferent ctes n terms of dangerousness, senstvty, and vulnerablty respectvely n Jangsu provnce were shown n Fgure.

11 of Rsk Values Cty Dangerousness Senstvty Vulnerablty Fgure. Comparsons of dfferent ctes n terms of dangerousness, senstvty, and vulnerablty respectvely n Jangsu provnce. Based on the assessment results, the comprehensve rsk zonng map n Jangsu provnce can be drawn (Fgure ). From the Fgure, t can be seen that the comprehensve rsks of urban ranstorm n Jangsu provnce have apparent regonal characterstcs. The comprehensve rsk level of urban ranstorm n Wux, Changzhou and Nanng s hgher, whle Xuzhou and Suqan s lower. The rsk levels n the northwestern ctes are lower than the southern ctes n the Jangsu provnce. Moreover, most ctes of Jangsu provnce experence moderate rsk level. 0 Fgure. Dstrbuton of urban ranstorm rsk n Jangsu provnce.. Dscusson and Conclusons

12 of Because the urban ranstorm dsasters are occurrng more frequently n Chna, so the rsk assessment of urban ranstorm dsasters s very mportant for urban ranstorm management. However, urban ranstorm s a fuzzy phenomenon and there s a lack of suffcent data. It s dffcult to depct t accurately through tradtonal statstcs, especally n small sample problems. Therefore, the method bult n ths paper can be developed to assess the rsk of urban ranstorm dsasters. The VFS can make full use of varous ndex data to obtan comprehensve rsk evaluaton results. The IDM can transform a sample observed value nto a fuzzy set and s capable of dealng wth small sample problems. Meanwhle, IDM can extract useful nformaton and establsh the level classfcaton standards of the rsk assessment ndces, whch s helpful to determne the relatve membershp functon of VFS. Accordng to the natural dsaster system theory and actual stuaton of Jangsu provnce, an ntegrated rsk assessment system of urban ranstorm dsasters wth dangerousness ndces, the senstvty ndces and the vulnerablty ndces are establshed. Consderng the ntegrated mpact of dangerousness, senstvty and vulnerablty ndces, to establsh an ntegrated rsk ndex system of urban ranstorm dsasters n Jangsu provnce s helpful to support rsk management and develop effectve mtgaton strateges n ths regon. In addton, most ctes of Jangsu provnce are located n a moderate rsk regon. The results are consstent wth the actual stuaton of the Jangsu provnce and can provde reference and decson-makng for management departments of ranstorm dsasters. However, the assessment of urban ranstorm dsasters s quetly complex. It needs to be studed further n formaton mechansm, rsk factors and losses of dsasters. Author Contrbutons: J.C. had the orgnal dea for the study; M.C. and P.Z. were responsble for data collecton, M.C. and J.C. analyzed the data and wrote the paper. P.Z. provded gudance, comments and key suggestons; J.C. and M.C. revewed the paper. Fundng: Ths research was funded by the Natonal Natural Scence Foundaton of Chna (Grant No. and 000), the Humantes and Socal Scences Fund of Mnstry of Educaton of Chna (Grant No. YJA000), the Key Support Proects of Maor Research Programs of the Natonal Natural Scence Foundaton of Chna (Grant No. 0), the Natonal Key R&D Program of Chna (Grant No. 0YFC0000), the Fundamental Research Funds for the Central Unverstes (Grant No. 0B). Conflcts of Interest: The authors declare no conflct of nterest. References. Lao, X.; Zheng, J.; Huang, C.; Huang, G. Approach for evaluatng LID measure layout scenaros based on random forest: Case of Guangzhou Chna. Water. 0, 0,.. Koop, S.H.A.; Van Leeuwen, C.J. The challenges of water, waste and clmate change n ctes. Envronment, Development and Sustanablty. 0,, -.. Jerneck, A.; Olsson, L.; Ness, B.; Anderberg, S.; Baer, M. Clark, E; Hckler, T; Hornborg, A; Kronsell, A; Lövbrand, E. Structurng sustanablty scence. Sustanablty Scence. 00,, -.. Hegger, D.L.T.; Dressen, P.P.J.; Depernk, C. Werng, M; Raadgever, G.T; Van, Rswck; H.F.M.W. Assessng stablty and dynamcs n flood rsk governance. Water Resources Management. 0,, -.. Quan, R. Rsk assessment of flood dsaster n Shangha based on spatal-temporal characterstcs analyss from to 000. Envronmental Earth Scences. 0,,-.. Huang, Z.W.; Zhou, J.Z.; Song, L.X.; Lu, Y.L.; Zhang, Y.C. Flood dsaster loss comprehensve evaluaton model based on optmzaton support vector machne. Expert Systems wth Applcatons. 00,, 0-.. L, Z.; Dong, M.; Wong, T.; Wang, J.; Kumar, A.; Sngh, R.P. Obectves and ndexes for mplementaton of sponge ctes A case study of Changzhou cty, Chna. Water. 0, 0,. Zhang, D.; Wang, L. Research on urban emergency management n Beng based on complex System Theory. Cty. 0,, -.. Slva, M.M.G.T.D.; Kawasak, A. Socoeconomc Vulnerablty to Dsaster Rsk: A Case Study of Flood and Drought Impact n a Rural Sr Lankan Communty. Ecologcal Economcs. 0,, -0.

13 of Peng, C.; Zhang, J.; Sun, Y. Research on emergency rescue of urban flood dsaster based on wargame smulaton. Journal of the Indan Socety of Remote Sensng. 0., -.. Ca, Y.; L, L.; Elah, E.; Qu, Y. Selecton of polces on typhoon and ranstorm dsasters n Chna: A content analyss perspectve. Sustanablty. 0, 0,.. Lyu, H.M.; Sun, W.J.; Shen, S.L,; Arulraah, A. Flood rsk assessment n metro systems of mega-ctes usng a GIS-based modelng approach. Scence of The Total Envronment. 0,, Alfa, M.I.; Abke, M.A.; Daff, R.E. Applcaton of analytc herarchy process and geographc nformaton system technques n flood rsk assessment: a case of Ofu rver catchment n Ngera. Journal of Degraded and Mnng Lands Management. 0,, -.. Weerasnghe, K.M.; Gehrels, H.; Arambepola, N.M.S.I.; Vaa, H.P.; Herath, J.M.K.; Atapattu, K.B. Qualtatve flood rsk assessment for the western provnce of Sr Lanka. Proceda Engneerng, 0,, Jonkman, S.N.; Bočkarova, M.; Kok, M.; et al. Integrated hydrodynamc and economc modellng of flood damage n the Netherlands. Ecologcal Economcs. 00,, -0.. Wang, J.; Zhao, L.; Zhang, H.; Nu, W. Research on optmzaton of urban dranage ppelnes carryng capacty based on SWMM model. Chna Rural Water and Hydropower. 0,, -.. Shao M, Gong Z, Xu X. Rsk assessment of ranstorm and flood dsasters n Chna between 00 and 00 based on gray fxed weght cluster analyss. Natural Hazards. 0,, Goetz, J. Forest harvestng s assocated wth ncreased landslde actvty durng an extreme ranstorm on Vancouver Island, Canada. Natural Hazards and Earth System Scences. 0,, -0.. Lyu, H.M.; Wang, G.F.; Cheng, W.C.; Shen, S.L. Tornado hazards on June n Jangsu Provnce, Chna: prelmnary nvestgaton and analyss. Natural Hazards. 0,, Strzeleck, M.C.; Long, A.J.; Lloyd, J.M. Post-lttle ce age development of a hgh arctc paraglacal beach complex. Permafrost & Perglacal Processes. 0,, -.. Lu, X.; L, X.Y.; Dang, S. Spatal pattern of precptaton change n the man sedment-yeldng area of the Yellow Rver basn n recent years. Journal of Hydraulc Engneerng, 0,, -.. L, J.; Tan, S.; We, Z. A new method of change pont detecton usng varable fuzzy sets under envronmental change. Water Resources Management. 0,,.. Sun, Z.Y.; Zhang, J.Q.; Zhang, Q.; Hu, Y.; Yan, D.H. Wang, C.Y. Integrated rsk zonng of drought and waterloggng dsasters based on fuzzy comprehensve evaluaton n Anhu Provnce, Chna. Natural Hazards. 0,, -.. Zou, L.J.; Zhong, M.; Yang, X.H.; Lu, X.F. Usng nformaton dffuson to analyze the membershp degree n rsk assessment of flash flood. Journal of Water Resources Research. 0, 0, -0.. Ren, Y.F.; Lu, G.D.; Zhou, L.; Zhang, C.M. Rsk evaluaton of Chengdu's flood hazard based on evdence theory and varable fuzzy sets theory. Transactons of the Chnese Socety of Agrcultural Engneerng. 0, 0, -.. Guo, E.L.; Zhang, J.Q.; Ren, X.H.; Zhang, Q.; Sun, Z.Y. Integrated rsk assessment of flood dsaster based on mproved set par analyss and the varable fuzzy set theory n central Laonng Provnce, Chna. Natural Hazards. 0,, -.. Du, X.; Jn, X.; Yang, X.; Yang, X.; Zhou, Y. Spatal pattern of land use change and ts drvng force n Jangsu provnce. Internatonal Journal of Envronmental Research and Publc Health. 0,,.. Saaty, T.L. Decson-makng wth the AHP: Why s the prncpal egenvector necessary. European Journal of Operatonal Research. 00,, -.. Zhao, D.; Zhang, Y.; Ma, J. Fuzzy Rsk Assessment of entropy-weght coeffcent method appled n network securty. Computer Engneerng. 00, 0, :-. 0. Xu, J.; Feng, P.; Yang, P. Research of development strategy on Chna s rural drnkng water supply based on SWOT-TOPSIS method combned wth AHP-Entropy: a case n Hebe Provnce. Envronmental Earth Scences. 0,,.. Zhang, L.J.; L, W.; Zhang, D Y. Meteorologcal dsaster rsk assessment method based on nformaton dffuson theory. Scenta Geographca Snca. 00,, 0-.. Wang, J.D.; Huang, C.F. Informaton dffuson method relevant n fuzzy nformaton processng and ts applcaton. Journal of Northwest Unversty.,,.. Huang, C.F. Prncple of nformaton dffuson. Fuzzy Sets and Systems.,, -0.

14 of 0. L, Q. Flood Rsk Assessment Based on the Informaton Dffuson Method. Advances n computer scence, envronment, econformatcs and educaton: Sprnger Berln Hedelberg, German, 0, -.. Nagata, K.; Shrayama, S. Method of analyzng the nfluence of network structure on nformaton dffuson. Physcal A Statstcal Mechancs & Its Applcatons. 0,, -.. Chen, S.Y. Theory and model of engneerng varable fuzzy set-mathematcal bass for fuzzy hydrology and water resources. Journal of Dalan Unversty of Technology. 00,, 0-.. Huang, S.; Chang, J.; Leng, G.; Huang, Q. Integrated ndex for drought assessment based on varable fuzzy set theory: A case study n the Yellow Rver basn, Chna. Journal of Hydrology. 0,, 0-.. Zhou, H.C.; Dan, Z. Assessment model of drought and flood dsasters wth varable fuzzy set theory. Transactons of the Chnese Socety of Agrcultural Engneerng. 00,, -.. Denton, F. Clmate change vulnerablty, mpacts, and adaptaton: Why does gender matter?. Gender & Development. 00, 0, Hufschmdt, G. A comparatve analyss of several vulnerablty concepts. Natural Hazards, 0,, -.