Modelling of Groundwater Potential Zones in Semi-Arid Areas Using Unmanned Aerial Vehicles, Geographic Information Systems, and Multi-Criteria Decision Making

Nowadays, modelling groundwater potential zones (GWPZs) based on scientific principles and modern techniques is a major challenge for scientists around the world. This challenge is even greater in arid and semi-arid areas. Unmanned aerial vehicles (UAVs), geographic information systems (GISs), and multi-criteria decision making (MCDM) are modern techniques that have been applied in various fields, especially in groundwater exploration. This study attempts to apply a workflow for modelling the GWPZs using UAV technology, GIS, and MCDM in semi-arid areas. An aerial survey provided a high-resolution DEM of 4 cm. Six influencing factors, including elevation model, drainage density, lineament density, slope, flood zone, and topographic wetness index, were considered to delineate the GWPZs. Four classes of groundwater potential were identified, namely high (4.64%), moderate (23.74%), low (18.2%), and very low (53.42%). Three validation methods, namely borehole yield data, receiver operating characteristic area under the curve (ROC-AUC), and principal component analysis (PCA), were used and gave accuracies of 82.14%, 65.4%, and 72.49%, respectively. These validations indicate a satisfactory accuracy and justify the effectiveness of the approach. The mapping of GWPZs in semi-arid areas is very important for the availability and planning of water resources management and for sustainable development.

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Journal
Hydrology
Published
2025-03-14
DOI
https://doi.org/10.3390/hydrology12030058
Primary Topic
Groundwater and Watershed Analysis
Type
article
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article

Modelling of Groundwater Potential Zones in Semi-Arid Areas Using Unmanned Aerial Vehicles, Geographic Information Systems, and Multi-Criteria Decision Making

Wilson Y. Fantong, Blaise Pascal Gounou Pokam, Serges Raoul Kouamou Njifen, André Talla et al.
Hydrology
Groundwater and Watershed Analysis
article

Modelling of Groundwater Potential Zones in Semi-Arid Areas Using Unmanned Aerial Vehicles, Geographic Information Systems, and Multi-Criteria Decision Making

Wilson Y. Fantong, Blaise Pascal Gounou Pokam, Serges Raoul Kouamou Njifen, André Talla, Michel Mbessa, Marthe Mbond Ariane Gweth, Michel Constant Njock, Philippe Njandjock Nouck, Jorelle Larissa Méli’i, André Michel Pouth Nkoma
article en

Abstract

Nowadays, modelling groundwater potential zones (GWPZs) based on scientific principles and modern techniques is a major challenge for scientists around the world. This challenge is even greater in arid and semi-arid areas. Unmanned aerial vehicles (UAVs), geographic information systems (GISs), and multi-criteria decision making (MCDM) are modern techniques that have been applied in various fields, especially in groundwater exploration. This study attempts to apply a workflow for modelling the GWPZs using UAV technology, GIS, and MCDM in semi-arid areas. An aerial survey provided a high-resolution DEM of 4 cm. Six influencing factors, including elevation model, drainage density, lineament density, slope, flood zone, and topographic wetness index, were considered to delineate the GWPZs. Four classes of groundwater potential were identified, namely high (4.64%), moderate (23.74%), low (18.2%), and very low (53.42%). Three validation methods, namely borehole yield data, receiver operating characteristic area under the curve (ROC-AUC), and principal component analysis (PCA), were used and gave accuracies of 82.14%, 65.4%, and 72.49%, respectively. These validations indicate a satisfactory accuracy and justify the effectiveness of the approach. The mapping of GWPZs in semi-arid areas is very important for the availability and planning of water resources management and for sustainable development.

HydrologyVol. 12(3)
Université de Yaoundé I (CM), Institut de Recherches Géologiques et Minières (CM), National Radiation Protection Agency of Cameroon (CM), National Advanced School of Public Works (CM), University of Ngaoundéré (CM)
Openalex Percentile: Top 95%
Groundwater and Watershed Analysis
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