Detecting Areas Vulnerable to Flooding Using Hydrological-Topographic Factors and Logistic Regression

As a result of rapid urbanization and population movement, flooding in urban areas has become one the most common types natural disaster, causing huge losses both life property. To mitigate prevent damage caused by recent increase floods, number measures are required, such as installing flood prevention facilities, or specially managing vulnerable to flooding. In this study, we presented technique for determining susceptible using hydrological-topographic characteristics purpose areas. begin, collected digital topographic maps stormwater drainage system data regarding study area. Using data, surface, locational, resistant factors were analyzed. addition, maximum 1-h rainfall an inducing factor assigned all grids through spatial interpolation. Next, logistic regression analysis was performed inputting historical inundation trace each grid independent dependent variables, respectively, which model calculating vulnerability area established. The performance evaluated analyzing receiver operating (ROC) curve maps, it found be improved when that changes according events also considered. method can used not only reasonably efficiently select target sites but pre-detect real-time forecasting.