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Integrated machine learning and remote sensing for groundwater potential mapping in the Mekong Delta in Vietnam

  • Research Article - Hydrology and Hydraulics
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Abstract

Evaluating groundwater potential is critical for the socioeconomic development of Vietnam. This research aims to assess the underground water potential in the country’s Mekong Delta using the machine learning (ML) such as support vector machines (SVM), CatBoost (CB), K-nearest neighbors (KNN), random forest (RF) and AdaBoost (ADB). The problem of exploitation of groundwater resources in the delta is aggravated due to global warming and growth of population. In total, 146 groundwater points and 14 drivers (namely elevation, aspect, curvature, slope distance to river and river density, land use, normalized difference built-up index, flow accumulation, rainfall, soil type, normalized difference vegetation index, stream power index, terrain roughness index, and topographic wetness index) were used to assess groundwater potential. Each proposed model was evaluated utilizing area under curve (AUC), root mean square error, coefficient of determination (R2), and mean absolute error. The findings showed that the RF outperformed the others in building of a groundwater potential map. In which, AUC value was estimated at 0.99 and R2 value was estimated at 0.63 then came CB (AUC = 0.98, R2 = 0.56), ADB (AUC = 0.92, R2 = 0.50), SVM (AUC = 0.91, R2 = 0.57), and KNN (AUC = 0.75, R2 = 0.45). The results illustrate the power of ML in assessing groundwater potential and can support decision makers, planners, and local authorities responsible for sustainable groundwater planning in the Mekong Delta and beyond.

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Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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Authors and Affiliations

  1. Faculty of Geography, University of Science, Vietnam National University, Ha Noi, 334 Nguyen Trai, Thanh Xuan District, Hanoi, Vietnam

    Huu Duy Nguyen, Quoc-Huy Nguyen & Quang-Thanh Bui

  2. Faculty of Hydrology, Meteorology, and Oceanography, University of Science, Vietnam National University, Ha Noi, 334 Nguyen Trai, Thanh Xuan District, Hanoi, Vietnam

    Dinh Kha Dang & Tien Giang Nguyen

  3. Institute of Vietnamese Studies and Development Sciences, Vietnam National University (VNU), Hanoi, 10000, Vietnam

    Quang Hai Truong

  4. Institute of Geography, Vietnam Academy of Science and Technology, 18 Hoang Quoc Viet Str., Cau Giay Str., Hanoi, 100000, Vietnam

    Van Hong Nguyen

  5. Faculty of Geography, Graduate University of Science and Technology, 18 Hoang Quoc Viet Str., Cau Giay Dist., Hanoi, 100000, Vietnam

    Van Hong Nguyen

  6. Faculty of Humanities, Department of Geography, Valahia University of Targoviste, 130004, Targoviste, Romania

    Petre Bretcan

  7. Faculty of Geography, Babes-Bolyai University, Cluj-Napoca, Romania

    Gheorghe Șerban

  8. Doctoral School of Urban Planning, Ion Mincu University of Architecture and Urbanism, 010014, Bucharest, Romania

    Alexandru-Ionut Petrisor

  9. Department of Architecture, Faculty of Architecture and Urban Planning, Technical University of Moldova, 2004, Chisinau, Moldova

    Alexandru-Ionut Petrisor

  10. National Institute for Research and Development in Constructions, Urbanism and Sustainable Spatial Development URBAN-INCERC, 21652, Bucharest, Romania

    Alexandru-Ionut Petrisor

  11. National Institute for Research and Development in Tourism, 50741, Bucharest, Romania

    Alexandru-Ionut Petrisor

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  1. Huu Duy Nguyen
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  2. Quoc-Huy Nguyen
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  6. Van Hong Nguyen
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  9. Quang-Thanh Bui
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  10. Alexandru-Ionut Petrisor
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Huu Duy Nguyen, Dinh Kha Dang, Van Hong Nguyen, Quoc-Huy Nguyen, Quang-Thanh Bui. The first draft of the manuscript was written by Huu Duy Nguyen, Quoc-Huy Nguyen, Quang-Thanh Bui, Tien Giang Nguyen, Alexandru-Ionut Petrisor; Petre Bretcan, Gheorghe Șerban. Huu Duy Nguyen and Quang Hai Truong also made an overall revision of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Huu Duy Nguyen.

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Edited by Dr. Khabat Khosravi (ASSOCIATE EDITOR) / Prof. Jochen Aberle (CO-EDITOR-IN-CHIEF).

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Nguyen, H.D., Nguyen, QH., Dang, D.K. et al. Integrated machine learning and remote sensing for groundwater potential mapping in the Mekong Delta in Vietnam. Acta Geophys. (2024). https://doi.org/10.1007/s11600-024-01331-5

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