Evaluating the impact of emerging hydro-geophysical technologies on sustainable water resource management

Emerging hydrogeophysical technologies are revolutionizing the management of water resources, providing unprecedented insights and enhancing sustainability practices. This article examines recent advancements in hydrogeophysical methods, focusing on time-lapse electromagnetic techniques, unmanned aerial vehicles (UAVs), and artificial intelligence (AI). Through a comprehensive review of the literature and practical case studies, including notable implementations in Africa, the paper highlights how these innovations improve groundwater monitoring, resource management, and predictive capabilities. Time-lapse electromagnetic methods have achieved up to 1-meter resolutions, significantly enhancing groundwater mapping accuracy (Binley & Kemna, 2005). With their high-resolution remote sensing capabilities, UAVs have facilitated detailed hydrological surveys, while AI-driven analyses optimize groundwater predictions and management strategies (Rennie et al., 2021). The study presents a cost-benefit analysis showing a 20-30% reduction in operational costs and a 40% increase in data accuracy. Challenges such as technical limitations and high initial costs are discussed, alongside potential solutions and prospects. The findings underscore the transformative potential of these technologies for achieving sustainable water resource management, offering actionable insights for policymakers, researchers, and practitioners in the field.

Authors

Publication Details

Journal
International Journal of Science and Research Archive
Published
2024-09-30
DOI
https://doi.org/10.30574/ijsra.2024.13.1.1756
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
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article

Evaluating the impact of emerging hydro-geophysical technologies on sustainable water resource management

Benard Ifeanyi Odoh, Ifeanyi Peter Ezealaji, Chetanna Jude Chukwuneke
International Journal of Science and Research Archive
Reservoir Engineering and Simulation Methods
article

Evaluating the impact of emerging hydro-geophysical technologies on sustainable water resource management

Benard Ifeanyi Odoh, Ifeanyi Peter Ezealaji, Chetanna Jude Chukwuneke
article en

Abstract

Emerging hydrogeophysical technologies are revolutionizing the management of water resources, providing unprecedented insights and enhancing sustainability practices. This article examines recent advancements in hydrogeophysical methods, focusing on time-lapse electromagnetic techniques, unmanned aerial vehicles (UAVs), and artificial intelligence (AI). Through a comprehensive review of the literature and practical case studies, including notable implementations in Africa, the paper highlights how these innovations improve groundwater monitoring, resource management, and predictive capabilities. Time-lapse electromagnetic methods have achieved up to 1-meter resolutions, significantly enhancing groundwater mapping accuracy (Binley & Kemna, 2005). With their high-resolution remote sensing capabilities, UAVs have facilitated detailed hydrological surveys, while AI-driven analyses optimize groundwater predictions and management strategies (Rennie et al., 2021). The study presents a cost-benefit analysis showing a 20-30% reduction in operational costs and a 40% increase in data accuracy. Challenges such as technical limitations and high initial costs are discussed, alongside potential solutions and prospects. The findings underscore the transformative potential of these technologies for achieving sustainable water resource management, offering actionable insights for policymakers, researchers, and practitioners in the field.

International Journal of Science and Research ArchiveVol. 13(1)
Openalex Percentile: Top 79%
Reservoir Engineering and Simulation Methods
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Evaluating the impact of emerging hydro-geophysical technologies on sustainable water resource management — Benard Ifeanyi Odoh, Ifeanyi Peter Ezealaji, et al. · International Journal of Science and Research Archive (2024) | TGRS Research Map | TGRS