Flood Risk Assessment in the Lower Valley of Ouémé, Benin  

作　　者：Yaovi Aymar Bossa Octave Djangni Yacouba Yira Jean Hounkpè Angèle D. Avossè Luc Ollivier Sintondji Yaovi Aymar Bossa;Octave Djangni;Yacouba Yira;Jean Hounkpè;Angèle D. Avossè;Luc Ollivier Sintondji(National Institute of Water, University of Abomey-Calavi, Abomey Calavi, Benin;Africa Centre of Excellence for Water and Sanitation, University of Abomey-Calavi, Abomey Calavi, Benin;Hydro-Climate Services, Ouagadougou, Burkina Faso;Applied Science and Technology Research Institute-IRSAT/CNRST, Ouagadougou, Burkina Faso)

机构地区：[1]National Institute of Water, University of Abomey-Calavi, Abomey Calavi, Benin [2]Africa Centre of Excellence for Water and Sanitation, University of Abomey-Calavi, Abomey Calavi, Benin [3]Hydro-Climate Services, Ouagadougou, Burkina Faso [4]Applied Science and Technology Research Institute-IRSAT/CNRST, Ouagadougou, Burkina Faso

出　　处：《Open Journal of Modern Hydrology》2024年第2期130-151,共22页现代水文学期刊（英文）

摘　　要：In response to the increased frequency of flood events in recent years, it has become crucial to enhance preparedness and anticipation through precise flood risk assessments. To this end, this study aims to produce updated and precise flood risk maps for the Lower Valley of Ouémé River Basin, located in the South of Benin. The methodology used consisted of a combination of geographical information systems (GIS) and multi-criteria analysis, including Analytical Hierarchy Process (AHP) methods to define and quantify criteria for flood risk assessment. Seven hydro-geomorphological indicators (elevation, rainfall, slope, distance from rivers, flow accumulation, soil type, and drainage density), four socio-economic vulnerability indicators (female population density, literacy rate, poverty index, and road network density), and two exposure indicators (population density and land use) were integrated to generate risk maps. The results indicate that approximately 21.5% of the Lower Valley is under high and very high flood risk, mainly in the south between Dangbo, So-Ava, and Aguégués. The study findings align with the historical flood pattern in the region, which confirms the suitability of the used method. The novelty of this work lies in its comprehensive approach, the incorporation of AHP for weighting factors, and the use of remote sensing data, GIS technology, and spatial analysis techniques which adds precision to the mapping process. This work advances the scientific understanding of flood risk assessment and offers practical insights and solutions for flood-prone regions. The detailed flood risk indicator maps obtained stand out from previous studies and provide valuable information for effective flood risk management and mitigation efforts in the Lower Valley of Ouémé.In response to the increased frequency of flood events in recent years, it has become crucial to enhance preparedness and anticipation through precise flood risk assessments. To this end, this study aims to produce updated and precise flood risk maps for the Lower Valley of Ouémé River Basin, located in the South of Benin. The methodology used consisted of a combination of geographical information systems (GIS) and multi-criteria analysis, including Analytical Hierarchy Process (AHP) methods to define and quantify criteria for flood risk assessment. Seven hydro-geomorphological indicators (elevation, rainfall, slope, distance from rivers, flow accumulation, soil type, and drainage density), four socio-economic vulnerability indicators (female population density, literacy rate, poverty index, and road network density), and two exposure indicators (population density and land use) were integrated to generate risk maps. The results indicate that approximately 21.5% of the Lower Valley is under high and very high flood risk, mainly in the south between Dangbo, So-Ava, and Aguégués. The study findings align with the historical flood pattern in the region, which confirms the suitability of the used method. The novelty of this work lies in its comprehensive approach, the incorporation of AHP for weighting factors, and the use of remote sensing data, GIS technology, and spatial analysis techniques which adds precision to the mapping process. This work advances the scientific understanding of flood risk assessment and offers practical insights and solutions for flood-prone regions. The detailed flood risk indicator maps obtained stand out from previous studies and provide valuable information for effective flood risk management and mitigation efforts in the Lower Valley of Ouémé.

关 键 词：Flood Hazard Exposure VULNERABILITY Risk Lower Valley of Ouémé 

分 类 号：P33[天文地球—水文科学]