GIS-Based Approach Applied to Study of Seasonal Rainfall Influence over Flood Vulnerability

Flooding occurrence is one of the most common phenomena that impact urban areas, and this intensifies during heavy rainfall periods. Knowing the areas with the greatest vulnerability is of paramount importance as it allows mitigating actions to be implemented in order to minimize the generated impacts. In this context, this study aimed to use Geographic Information System (GIS) tools to identify the areas with greater flooding vulnerability in Esp&iacute:rito Santo state, Brazil. The study was based on the following methodological steps: (1) a Digital Elevation Model (DEM) acquisition and watersheds delimitation: (2) maximum and accumulated rainfall intensity calculations for the three studied periods using meteorological data: (3) a land use and occupation map reclassification regarding flood vulnerability and fuzzy logic application: (4) an application of Euclidean distance and fuzzy logic in hydrography and water mass vector variables: (5) a flood vulnerability model generation. Based on the found results, it was observed that the metropolitan and coastal regions presented as greater flood vulnerability areas during the dry season, as in these regions, almost all of the 9.18% of the state&rsquo:s area was classified as highly vulnerable, while during rainy season, the most vulnerable areas were concentrated in Capara&oacute: and in the coastal and immigration and metropolitan regions, as in these regions, almost all of the 12.72% of the state&rsquo:s area was classified as highly vulnerable. In general, by annually distributing the rainfall rates, a greater flood vulnerability was observed in the metropolitan and coastal and immigration regions, as in these areas, almost all of the 7.72% of the state&rsquo:s area was classified as highly vulnerable. According to the study, Esp&iacute:rito Santo state was mostly classified as a low (29.15%) and medium (28.06%) flood vulnerability area considering the annual period, while its metropolitan region has a very high flood vulnerability risk. Finally, GIS modeling is important to assist in decision making regarding public management and the employed methodology presents worldwide application potential.