Integration of geospatial-based algorithms for groundwater potential characterization in Keiskamma Catchment of South Africa

IF 4.9 Q2 ENGINEERING, ENVIRONMENTAL Groundwater for Sustainable Development Pub Date : 2024-06-29 DOI:10.1016/j.gsd.2024.101262
Kgabo Humphrey Thamaga , Sinesipho Gom , Gbenga Olamide Adesola , Naledzani Ndou , Nndanduleni Muavhi , Mthunzi Mndela , Phila Sibandze , Hazem Ghassan Abdo , Thabang Maphanga , Gbenga Abayomi Afuye , Benett Siyabonga Madonsela , Hussein Almohamad
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Abstract

Groundwater supports over 2.4 billion people across the globe and is critical to food security. The spatial dynamics of groundwater vary from place to place. The irregularity of groundwater resource exploitation is recognized in drought-prone areas, putting pressure on the resource. Hence, accurate groundwater potential characterization is critical for sustainable development and management of groundwater, particularly in drought-prone environments. Therefore, this study aimed at utilizing remote sensing satellite data and geospatial-based (analytical hierarchy process (AHP) and frequency ratio (FR)) algorithms to characterize groundwater potential zones (GWPZs) in the Keiskamma Catchment of South Africa. Seven (7) selected factors, including geology, soil type, slope, rainfall, drainage density, lineament density, and land use land cover, were assigned weights based on the AHP and FR algorithms. The validation results showed that the FR model performed better than the AHP, with the area under curve (AUC) accuracies of 62% and 50%, respectively. Based on the findings of this study, we infer that FR is more reliable than AHP when characterizing GWPZ. Lastly, GWPZ maps produced will be beneficial for improving efficient planning, management strategies, and decision-making.

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整合基于地理空间的算法,确定南非 Keiskamma 集水区的地下水潜力特征
地下水支撑着全球 24 亿多人口,对粮食安全至关重要。地下水的空间动态因地而异。在干旱多发地区,地下水资源开发的不规律性已得到公认,这对资源造成了压力。因此,准确的地下水潜力特征描述对于地下水的可持续开发和管理至关重要,尤其是在易旱环境中。因此,本研究旨在利用遥感卫星数据和基于地理空间的算法(层次分析法(AHP)和频率比(FR))来描述南非 Keiskamma 集水区的地下水潜力区(GWPZs)。根据 AHP 和 FR 算法,对所选的七 (7) 个因素(包括地质、土壤类型、坡度、降雨量、排水密度、线状密度和土地利用土地覆盖)分配了权重。验证结果表明,FR 模型的性能优于 AHP,其曲线下面积(AUC)精确度分别为 62% 和 50%。根据这项研究的结果,我们推断在描述 GWPZ 特征时,FR 比 AHP 更可靠。最后,绘制的 GWPZ 地图将有助于提高规划、管理策略和决策的效率。
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来源期刊
Groundwater for Sustainable Development
Groundwater for Sustainable Development Social Sciences-Geography, Planning and Development
CiteScore
11.50
自引率
10.20%
发文量
152
期刊介绍: Groundwater for Sustainable Development is directed to different stakeholders and professionals, including government and non-governmental organizations, international funding agencies, universities, public water institutions, public health and other public/private sector professionals, and other relevant institutions. It is aimed at professionals, academics and students in the fields of disciplines such as: groundwater and its connection to surface hydrology and environment, soil sciences, engineering, ecology, microbiology, atmospheric sciences, analytical chemistry, hydro-engineering, water technology, environmental ethics, economics, public health, policy, as well as social sciences, legal disciplines, or any other area connected with water issues. The objectives of this journal are to facilitate: • The improvement of effective and sustainable management of water resources across the globe. • The improvement of human access to groundwater resources in adequate quantity and good quality. • The meeting of the increasing demand for drinking and irrigation water needed for food security to contribute to a social and economically sound human development. • The creation of a global inter- and multidisciplinary platform and forum to improve our understanding of groundwater resources and to advocate their effective and sustainable management and protection against contamination. • Interdisciplinary information exchange and to stimulate scientific research in the fields of groundwater related sciences and social and health sciences required to achieve the United Nations Millennium Development Goals for sustainable development.
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