4.6 Article

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

Journal

APPLIED SCIENCES-BASEL
Volume 11, Issue 12, Pages -

Publisher

MDPI
DOI: 10.3390/app11125652

Keywords

flood vulnerability; spatial analysis; logistic regression; ROC analysis; flood detection

Funding

  1. Water Management Research Program - Ministry of Environment of Korean government [127568]

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

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