Temporal Assessment of the Effect of Flooding Vulnerability on Agricultural Land Use in the Gambia

https://doi.org/10.22146/ijg.85232

Philip Mopnang Ibol(1*)

(1) Faculty of Arts and Science, University of the Gambia
(*) Corresponding Author

Abstract


Flooding is a significant environmental problem, projected to intensify from 2010 to 2030. This natural disaster has affected several regions globally, leading to loss of life and property, community disruption, economic loss, injuries, and deaths. Factors contributing to flooding include heavy rainfall, rising sea levels, lowlands, waterways, climatic variations, wetlands, soil types, and unplanned urban settlements. The most severe case in the history of the Gambia struck in 2022. Therefore, this study aimed to identify areas vulnerable to flooding and the effect on agricultural land in the Gambia, as well as suggest preventive measures. The method adopted included the collection of secondary data from Landsat ETM imagery, Digital Elevation Model, rainfall data, Copernicus Global Land Services (CGLS), and Food Agricultural Organisation soil maps. The satellite imageries were processed and classified using ArcGIS 10.7.1, generating land use and land cover, slope, drainage density, rainfall, and soil maps. ArcGIS, combined with the Analytic Hierarchy Process (AHP), was used to integrate these maps to produce a vulnerability map for the study. The results showed areas with very high, high, moderate, low, and very low vulnerability. Based on the classification, coastal and lowland regions were in the high category. Therefore, this study recommended the construction of water barricades in vulnerable coastal areas to mitigate the disaster.

 


Keywords


Flooding; Vulnerability; Elevation; Drainage Density; Soil; Satellite images; Rainfall; Slope

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References

Ali AJ, Mina A, Saied P, Saeid E (2022). Flooding Hazard, Vulnerability and Risk Mapping in GIS: Geodata
Analytical Process in Boolean AHP and Fuzzy Models. In Flooding Handbook. Taylor & Francis Group CRC Press. doi:10.1201/9780429463938-26

Balica SF, Wright NG, van der Meulen (2012). A flooding vulnerability index for coastal cities and its use in
assessing climate change impacts. Natural Hazrads (2012) 64:73-105

Ceesay EK (2020). Does Flooding Disaster lessen GDP Growth? Evidence from the Gambia's Manufacturing and Agricultural Sectors. Journal of Petroleum & Environmental Biotechnology 11:404.
doi:10.35248/2157.7463.20.11.404

Diaz-Sarachaga JM, Jato-Espino D (2020). Analysis of Vulnerability Assessment Frameworks
and methodologies in urban areas. Natural Hazards, 100(1), 437–457.

Eguaroje OE, Alaga TA, Ogbole JO, Omolere S, Alwadood J, Kolawole IS, Muibi KH, Nnaemeka D, Popoola
DS, Samson SA, Adewoyin JE, Jesuleye I, Badru RA, Atijosan A, Ajileye OO (2015). Flooding
Vulnerability Assessment of Ibadan City, Oyo State, Nigeria. World Environment 2015, 4(4): 149-159

Forkuo EK (2011). Flooding Hazard Mapping using Aster Image Data with GIS. International Journal of Geomaticsand Geosciences. Vol 1, No. 4, 2011

Humanitarian Response (2022). The Gambia Flooding Response NDMA Situational Report #005
http://www.humanitarianresponse.info./en/operations/gambiaReliefweb

Ibol PM (2022). Assessing the Change of Land Use and Land Cover in the Gambia. European Journal of Social Sciences Studies 2022, Vol. 8 No 1, 2022

Jaiteh MS, Sarr B (2011). Climate Change and Development in the Gambia. Challenges to Ecosystem Goods and Services. Center for International Earth Science Information Network (CIESIN)

Kumar D, Bhattacharjya, RK (2020). Review of different methods and techniques used for flooding vulnerability analysis. Natural Hazards and Earth System Sciences. https://doi.org/10.5194/ness-2020-297

Lee JS, Choi HI (2018). Comparison of flooding vulnerability assessments to climate change by construction frameworks for a composite indicator. Sustainability (Switzerland), 10(3).

Hagos YG, Andualem TG, Yibeltal M. Mengie AM (2022). Flooding hazard assessment and mapping using GIS integrated with multi‑criteria decision analysis in the upper Awash River basin, Ethiopia. Applied Water
Science (2022) 12:148. https://doi.org/10.1007/s13201-022-01674-8

National Disaster Management Agency (2011). Gambia Contingency Plan. National Disaster Management
Agency. Banjul, The Gambia

Ogato GS, Bantider A, Geneletti D (2020). Geographic information system (GIS)-Based multicriteria analysis of flooding hazard and risk in Ambo Town and its watershed, West Shoa zone, Oromia regional state, Ethiopia. Journal of Hydrology: Regional Studies 27 (2020) 100659

Rincon D, Khan UT, Armenalis C (2018). Flooding Risk Mapping Using GIS and Multi-Criteria Analysis: A
Greater Toronto Area Case Study. Geosciences 8(8), 275

Saaty TL (1980). The analytic hierarchy process. planning, priority setting, and resource allocation. McGraw Hill, New York, USA

Thapa P. Thapa N (2021). Mapping Flooding Risk and Assessing Flooding Vulnerability for Settlement Areas. Remote Sensing Applications: Society and Environment

United Nations Disaster Assessment and Coordination (2022). The Gambia Floodings: Rapid Needs Assessment Report and Response Recommendations 2022. United Nations Disaster Assessment and Coordination

Wondim YK (2016). Flooding hazard and risk assessment using GIS and remote sensing in the lower Awash sub-basin Ethiopia. J Environ Earth Sci 6(9):6986



DOI: https://doi.org/10.22146/ijg.85232

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