Flood Hazard Mapping Using the Flood and Flash-Flood Potential Index in the Buzau River Catchment, Romania

被引:49
|
作者
Popa, Mihnea Cristian [1 ,2 ]
Peptenatu, Daniel [1 ]
Draghici, Cristian Constantin [1 ]
Diaconu, Daniel Constantin [1 ,3 ]
机构
[1] Univ Bucharest, Ctr Integrated Anal & Territorial Management, Bucharest 010041, Romania
[2] Univ Bucharest, Simion Mehedinti Nat & Sustainable Dev Doctoral S, Bucharest 010041, Romania
[3] Univ Bucharest, Fac Geog, Dept Meteorol & Hydrol, Bucharest 010041, Romania
关键词
Flash-Flood Potential Index; Flood Potential Index; bivariate model; frequency ratio; Multilayer Perceptron Neural Networks; hybrid model; LANDSLIDE SUSCEPTIBILITY ASSESSMENT; ARTIFICIAL NEURAL-NETWORKS; ENSEMBLE BIVARIATE; SPATIAL PREDICTION; FREQUENCY RATIO; RISK; MODELS; ADAPTATION; WEIGHTS; EROSION;
D O I
10.3390/w11102116
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 Buzu 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.
引用
收藏
页数:25
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