Modelagem hidrodinâmica para mapeamento de áreas inundáveis no Baixo Rio São Francisco - Bahia, Diogo dos Santos Gonçalves (2024)
The occurrence of floods has become more and more frequent over the years, especially in riverside areas and large urban centers. These phenomena are directly related to the volume of rainfall, lack of urban planning, poor drainage, low altimetry, flat slope, in addition to being characterized by anthropogenic actions such as soil sealing, deforestation with consequent climate change, improper occupation of riverine areas, construction of dams along the riverbed and opening of their floodgates in cases of extreme flow. All these factors define the greater or lesser susceptibility of an area to flooding and consequently can put people's safety at risk, cause destruction, and relevant environmental and socioeconomic risks. The problem is accentuated when densely occupied areas or areas of great economic importance are affected. Thus, the current work aimed to apply the HAC-RAS software in an integrated way with geoprocessing tools to map floodable urban riverine areas along the Lower São Francisco, thus configuring a valuable risk management tool. After the characterization of the area, the digital elevation model (MDE) was generated with images from the ALOS PALSAR satellite, obtained directly from the NASA website. The SisCAH software was used to estimate the maximum flows of the river for the return periods of 10, 20, 30, 50 and 100 years, through the probability density functions Gumbel, Log-Normal II, Log-Normal III, Pearson III and LogPearson III. The mapping of the 8 established flood areas was done through the integration of the hydrodynamic modeling carried out with the HEC-RAS and geoprocessing tools. The ALOS PALSAR image proved to be an efficient tool in the generation of the MDE because it is free, easy to acquire, and has one of the best altimetric resolutions (12.5m) among the free images available. The Gumbel distribution provided a better fit in the estimation of the maximum flows with a probability level of 95%, while the hydrodynamic model satisfactorily represented the flood spot for the study areas, with the estimated flows for the determined return times, indicating that it is an important tool to support urban planning and to alert and prevent the most densely occupied regions.