EventsThe 4th International Electronic Conference on Water Sciences
Published
This submission belongs to the session A. Managing Water Resources from Aquifers, Rivers and Lakes of the event The 4th International Electronic Conference on Water Sciences
Published date
12 Nov, 2019
Citation
Daniel Constantin Diaconu, Cristian Mihnea Popa, Flood and Flash Flood hazard mapping using the Frequency Ratio, Multilayer Perceptron and their hybrid ensemble, in Proceedings of The 4th International Electronic Conference on Water Sciences, 13 November–29 November 2019, MDPI: Basel, Switzerland, doi: 10.3390/ECWS-4-06429
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Flood and Flash Flood hazard mapping using the Frequency Ratio, Multilayer Perceptron and their hybrid ensemble

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1. “Simion Mehedinți—Nature and Sustainable Development” Doctoral School, University of Bucharest, 010041 Bucharest, Romania
2. Centre for Integrated Analysis and Territorial Management, University of Bucharest, 010041 Bucharest, Romania
3. University of Bucharest, Faculty of Geography, Department of Hydrology and Meteorology, Romania
Abstract

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 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 and the areas 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 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.

Keywords
Flash-Flood Potential Index
Multilayer Perceptron Neural Networks
hybrid model
Manuscript
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