Flood Extent Delineation and Exposure Assessment in Senegal Using the Google Earth Engine: The 2022 Event

Author:

Sy Bocar1ORCID,Bah Fatoumata1,Dao Hy23ORCID

Affiliation:

1. Laboratory of Applied Geomatic (LAG), Department of Geoscience and Environment, Polytech Diamniadio, Université Amadou Mahtar Mbow, Rue 21*20, 2ème Arrondissement, Pole Urbain de Diamniadio, Dakar 15258, Senegal

2. Department of Geography and Environment, Geneva School of Social Sciences, University of Geneva, 66 Boulevard Carl-Vogt, 1205 Geneva, Switzerland

3. Institute for Environmental Sciences, University of Geneva, Boulevard Carl-Vogt 66, 1205 Geneva, Switzerland

Abstract

This study addresses the pressing need for flood extent and exposure information in data-scarce and vulnerable regions, with a specific focus on West Africa, particularly Senegal. Leveraging the Google Earth Engine (GEE) platform and integrating data from the Sentinel-1 SAR, Global Surface Water, HydroSHEDS, the Global Human Settlement Layer, and MODIS land cover type, our primary objective is to delineate the extent of flooding and compare this with flooding for a one-in-a-hundred-year flood event, offering a comprehensive assessment of exposure during the period from July to October 2022 across Senegal’s 14 regions. The findings underscore a total inundation area of 2951 square kilometers, impacting 782,681 people, 238 square kilometers of urbanized area, and 21 square kilometers of farmland. Notably, August witnessed the largest flood extent, reaching 780 square kilometers, accounting for 0.40% of the country’s land area. Other regions, including Saint-Louis, Ziguinchor, Fatick, and Matam, experienced varying extents of flooding, with the data for August showing a 1.34% overlap with flooding for a one-in-a-hundred-year flood event derived from hydrological and hydraulic modeling. This low percentage reveals the distinct purpose and nature of the two approaches (remote sensing and modeling), as well as their complementarity. In terms of flood exposure, October emerges as the most critical month, affecting 281,406 people (1.56% of the population). The Dakar, Diourbel, Thiès, and Saint-Louis regions bore substantial impacts, affecting 437,025; 171,537; 115,552; and 77,501 people, respectively. These findings emphasize the imperative for comprehensive disaster preparation and mitigation efforts. This study provides a crucial national-scale perspective to guide Senegal’s authorities in formulating effective flood management, intervention, and adaptation strategies.

Publisher

MDPI AG

Reference47 articles.

1. Ndehedehe, C. (2023). Hydro-Climatic Extremes: Climate change and human influence. Hydro-Climatic Extremes in the Anthropocene, Springer International Publishing.

2. UNISDR-CRED (2015). The Human Cost of Weather-Related Disasters 1995–2015, The United Nations office for Disaster Risk Reduction (UNISDR) and Centre for Research on the Epidemiology of Disasters (CRED).

3. EM-DAT (2024, January 24). The OFDA/CRED International Disaster Database. Available online: https://public.emdat.be/data.

4. Urban flood risk warning under rapid urbanization;Chen;Environ. Res.,2015

5. Reconstituting past flood events: The contribution of citizen science;Sy;Hydrol. Earth Syst. Sci.,2020

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3