Hursuong Vongsachang, D S Friedman, A Inns, A M Kretz, M R Mukherjee, J Callan, M Wahl, M X Repka, M E Collins
Parent and Teacher Perspectives on Factors Decreasing Participation in School-Based Vision Programs
Ophthalmic epidemiology
urban flood risk assessment delivers invaluable information regarding flood management well preventing associated risks urban areas present study prepares flood risk map evaluate practices lowimpact development lid intended decrease flood risk shiraz municipal district 4 fars province iran study investigate flood vulnerability using mcdm models indices including population density building age socioeconomic conditions floor area ratio literacy elderly population number building floors map thematic layers affecting urban flood hazard including annual mean rainfall land use elevation slope percentage curve number distance channel depth groundwater channel density prepared gis conducting multicollinearity test data mining models used create urban flood hazard map urban flood risk map produced using arcgis 108 evaluation vulnerability models shown use boolean logic topsis vikor models effective identifying urban flooding vulnerable areas data mining models also evaluated using roc precisionrecall curves indicating accuracy rf model importance input variables measured using shapley value showed curve number land use elevation important flood hazard modeling according results 378 percent area falls high high categories terms flooding risk study used stormwater management model swmm simulate node flooding provide management scenarios rainfall events return period ranging 2 50 years five rainstorm events use lid practices flood management found effective rainfall events return period less 10 years particularly twoyear events however effectiveness lid practices decreases increase return period applying combined approach region covering approximately 10 percent total area shiraz municipal district 4 reduction 2228 percent node flooding achieved analysis data mining mcdm models physical model revealed 60 flooded nodes classified high high risk categories rfvikor rftopsis risk models