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Assessing the Performance of SuDS in the Mitigation of Urban Flooding: The Industrial Area of Sesto Ulteriano (MI)
Open AccessProceedings

Flood and Flash Flood Hazard Mapping Using the Frequency Ratio, Multilayer Perceptron and Their Hybrid Ensemble

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Centre for Integrated Analysis and Territorial Management, University of Bucharest, 010041 Bucharest, Romania
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Simion Mehedinți “Nature and Sustainable Development” Doctoral School, University of Bucharest, 010041 Bucharest, Romania
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Department of Meteorology and Hydrology, Faculty of Geography, University of Bucharest, 010041 Bucharest, Romania
*
Author to whom correspondence should be addressed.
Presented at the 4th International Electronic Conference on Water Sciences, 13–29 November 2019; Available online: https://ecws-4.sciforum.net/.
Proceedings 2020, 48(1), 6; https://doi.org/10.3390/ECWS-4-06429
Published: 12 November 2019
(This article belongs to the Proceedings of The 4th International Electronic Conference on Water Sciences)
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. Adaptation and mitigation have generally been treated as two separate issues, both in public politics and in practice, in which mitigation is seen as the attenuation of the cause, and studies of adaption look into dealing with the consequences of climate change. Studies on the impact of climate change on flood risk are mostly conducted at the river basin or regional scale. Remote sensing and GIS technologies, together with the latest modelling techniques, can contribute to our ability to predict and manage floods. Various methods are commonly used to map flood sensitivity. Recent methods such as multicriteria evaluation, decision tree analysis (DT), fuzzy theory, weight of samples (WoE), artificial neural networks (ANN), frequency ratio (FR) and logistic regression (LR) approaches have been widely used by many researchers.
Keywords: flash-flood potential index; Multilayer Perceptron Neural Networks; hybrid model flash-flood potential index; Multilayer Perceptron Neural Networks; hybrid model
MDPI and ACS Style

Popa, M.C.; Diaconu, D.C. Flood and Flash Flood Hazard Mapping Using the Frequency Ratio, Multilayer Perceptron and Their Hybrid Ensemble. Proceedings 2020, 48, 6.

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