scholarly journals Flash Flood Hazard Mapping Using GIS and Bivariate Statistical Method at Wadi Bada’a, Gulf of Suez, Egypt

2019 ◽  
Vol 07 (08) ◽  
pp. 372-385
Author(s):  
Sh. A. Abu El-Magd
Proceedings ◽  
2019 ◽  
Vol 48 (1) ◽  
pp. 6
Author(s):  
Mihnea Cristian Popa ◽  
Daniel Constantin Diaconu

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.


Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2116 ◽  
Author(s):  
Mihnea Cristian Popa ◽  
Daniel Peptenatu ◽  
Cristian Constantin Drăghici ◽  
Daniel Constantin Diaconu

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.


2016 ◽  
Vol 5 (3) ◽  
pp. 409-426
Author(s):  
Ali Omar ◽  
Mohamed Arnous ◽  
Mohamed El-Ghawaby ◽  
Abdalla Alshami ◽  
Mohamed El Zalaky

2015 ◽  
Vol 8 (3) ◽  
pp. 195-204 ◽  
Author(s):  
Da-wei Zhang ◽  
Jin Quan ◽  
Hong-bin Zhang ◽  
Fan Wang ◽  
Hong Wang ◽  
...  

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chhuonvuoch Koem ◽  
Sarintip Tantanee

Purpose Cambodia is considered one of the countries that are most vulnerable to adverse effects of climate change, particularly floods and droughts. Kampong Speu Province is a frequent site of calamitous flash floods. Reliable sources of flash flood information and analysis are critical in efforts to minimize the impact of flooding. Unfortunately, Cambodia does not yet have a comprehensive program for flash flood hazard mapping, with many places such as Kampong Speu Province having no such information resources available. The purpose of this paper is, therefore, to determine flash flood hazard levels across all of Kampong Speu Province using analytical hierarchy process (AHP) and geographical information system (GIS) with satellite information. Design/methodology/approach The integrated AHP–GIS analysis in this study encompasses ten parameters in the assessment of flash flood hazard levels across the province: rainfall, geology, soil, elevation, slope, stream order, flow direction, distance from drainage, drainage density and land use. The study uses a 10 × 10 pairwise matrix in AHP to compare the relative importance of each parameter and find each parameter’s weight. Finally, a flash flood hazard map is developed displaying all areas of Kampong Speu Province classified into five levels, with Level 5 being the most hazardous. Findings This study reveals that high and very high flash flood hazard levels are identified in the northwest part of Kampong Speu Province, particularly in Aoral, Phnum Srouch and Thpong districts and along Prek Thnot River and streams. Originality/value The flash flood hazard map developed here provides a wealth of information that can be invaluable for implementing effective disaster mitigation, improving disaster preparedness and optimizing land use.


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