Advancements in groundwater potential mapping through remote sensing and GIS techniques
1 School of Environmental Science and Engineering, Suzhou University of Science and Technology, Suzhou 215009, PR China.
2 Department of Civil Engineering, College of Engineering, Salahaddin University-Erbil, Kurdistan Region, Iraq.
3 Jiangsu Collaborative Innovation Center of Technology and Material of Water Treatment, Suzhou 215009, PR China.
Review
World Journal of Advanced Engineering Technology and Sciences, 2024, 12(01), 331–350.
Article DOI: 10.30574/wjaets.2024.12.1.0234
Publication history:
Received on 29 April 2024; revised on 09 June 2024; accepted on 12 June 2024
Abstract:
Groundwater resources are crucial for the future, facing increasing demand due to environmental changes and population growth. Economical and efficient exploration methods are becoming increasingly important, especially for middle- and lower-income regions. Deeper exploration is necessary to ensure a sustainable supply for future generations. This study examines the state-of-the-art in groundwater potential mapping. By analyzing scientific articles, it explores the recent advancements in this technique, which utilizes geographic databases and remote sensing. From a methodological perspective, the rise of machine learning algorithms is particularly noteworthy. Combining these methods with human expertise offers significant potential advantages, and experts believe it will lead to more accurate mapping.
However, simply discovering groundwater is not enough. Water quality and quantity are equally important for sustainable use. Therefore, this study presents two case studies that demonstrate groundwater mapping and quality management techniques. Furthermore, due to the ever-increasing population and changing land use, continuous research is essential for a long-term perspective on groundwater availability in specific regions.
Keywords:
Groundwater; GIS; Remote sensing; Water management; Machine learning
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0