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Flood Hazard Mapping Using the Flood and Flash-Flood Potential Index in the Buzău River Catchment, Romania
The importance of identifying the areas vulnerable for both floods and flash-floods is an important component of risk management. The assessment of vulnerable areas is a major challenge in the scientific world. The aim of this study is to provide a methodology-oriented study of how to identify the areas vulnerable to floods and flash-floods in the Buzău river catchment by computing two indices: the Flash-Flood Potential Index (FFPI) for the mountainous and the Sub-Carpathian areas, and the Flood Potential Index (FPI) for the low-altitude areas, using the frequency ratio (FR), a bivariate statistical model, the Multilayer Perceptron Neural Networks (MLP), and the ensemble model MLP−FR. A database containing historical flood locations (168 flood locations) and the areas with torrentiality (172 locations with torrentiality) was created and used to train and test the models. The resulting models were computed using GIS techniques, thus resulting the flood and flash-flood vulnerability maps. The results show that the MLP−FR hybrid model had the most performance. The use of the two indices represents a preliminary step in creating flood vulnerability maps, which could represent an important tool for local authorities and a support for flood risk management policies.
Flood Hazard Mapping Using the Flood and Flash-Flood Potential Index in the Buzău River Catchment, Romania
The importance of identifying the areas vulnerable for both floods and flash-floods is an important component of risk management. The assessment of vulnerable areas is a major challenge in the scientific world. The aim of this study is to provide a methodology-oriented study of how to identify the areas vulnerable to floods and flash-floods in the Buzău river catchment by computing two indices: the Flash-Flood Potential Index (FFPI) for the mountainous and the Sub-Carpathian areas, and the Flood Potential Index (FPI) for the low-altitude areas, using the frequency ratio (FR), a bivariate statistical model, the Multilayer Perceptron Neural Networks (MLP), and the ensemble model MLP−FR. A database containing historical flood locations (168 flood locations) and the areas with torrentiality (172 locations with torrentiality) was created and used to train and test the models. The resulting models were computed using GIS techniques, thus resulting the flood and flash-flood vulnerability maps. The results show that the MLP−FR hybrid model had the most performance. The use of the two indices represents a preliminary step in creating flood vulnerability maps, which could represent an important tool for local authorities and a support for flood risk management policies.
Flood Hazard Mapping Using the Flood and Flash-Flood Potential Index in the Buzău River Catchment, Romania
Mihnea Cristian Popa (author) / Daniel Peptenatu (author) / Cristian Constantin Drăghici (author) / Daniel Constantin Diaconu (author)
2019
Article (Journal)
Electronic Resource
Unknown
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