Citation
Abstract
Integrating agricultural production with the identification and use of groundwater resources has been shown to reduce multidimensional poverty in semi-arid regions. Poverty reduction and socioeconomic growth depend on sustainable water supply, especially in developing countries with limited rainy seasons. Poverty eradication is a top priority among the 17 Sustainable Development Goals (SDGs), and its reduction in the 21st century has led to significant advances in research. This study used remote sensing, geographic information system (GIS), and geospatial decision support system (S-DSS) approaches to uncover potential groundwater zones. The Analytic Hierarchy Process (AHP) integrates geospatial data to create a groundwater potential zone map and suggests the best land requirements for groundwater abstraction for poverty alleviation programs. The groundwater potential zone maps indicate that the majority of the region was in the high-potential zone, covering 59.75 of the total area, followed by a moderate-potential zone at 23.21, an extremely high-potential zone at 14.6, a low-potential zone at 2.44, and an extremely low-potential zone at 0. In addition, the study emphasizes the need for alternative water sources and infrastructure development in dry seasons in areas with fewer drainage systems and proposes measures such as rainwater harvesting structures and small reservoirs. Diversifying income sources by promoting alternative livelihoods can help reduce poverty and vulnerability to fluctuations in agricultural productivity. The integration of socioeconomic data into the S-DSS framework will provide a comprehensive understanding of the complex relationship between groundwater resources, poverty, and socioeconomic development, enabling informed decision-making in water resource management for poverty reduction initiatives and the achievement of the 2030 Agenda for Sustainable Development Goals. © 2023 Elsevier B.V.
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Agriculture Faculty of Engineering |
DOI Number: | https://doi.org/10.1016/j.gsd.2023.101038 |
Publisher: | Elsevier |
Keywords: | Modeling; Groundwater; Poverty; Decision support systems; Jigawa; Nigeria |
Depositing User: | Ms. Nuraida Ibrahim |
Date Deposited: | 08 Feb 2024 06:49 |
Last Modified: | 08 Feb 2024 06:49 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/j.gsd.2023.101038 |
URI: | http://psasir.upm.edu.my/id/eprint/105675 |
Statistic Details: | View Download Statistic |
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