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Abstract
Identifying shallow (near-surface) groundwater in arid and hyper-arid areas has significant societal benefits, yet it is a costly operation when traditional methods (geophysics and drilling) are applied over large domains. In this study, we developed and successfully applied methodologies that rely heavily on readily available temporal, visible, and near-infrared radar and thermal remote sensing data sets and field data, as well as statistical approaches to map the distribution of shallow (1–5 m deep) groundwater occurrences in Al Qunfudah Province, Saudi Arabia, and to identify the factors controlling their development. A four-fold approach was adopted: (1) constructing a digital database to host relevant geologic, hydrogeologic, topographic, land use, climatic, and remote sensing data sets, (2) identifying the distribution of areas characterized by shallow groundwater levels, (3) developing conceptual and statistical models to map the distribution of shallow groundwater occurrences, and (4) constructing an artificial neural network (ANN) and multivariate regression (MR) models to map the distribution of shallow groundwater, test the models over areas of known depth to groundwater (area of Al Qunfudah city and surroundings: 294 km2), and apply the better of the two models to map the shallow groundwater occurrences across the entire Al Qunfudah Province (area: 4680 km2). Findings include: (1) high performance for the ANN (92%) and MR (88%) models in predicting the distribution of shallow groundwater using temporal-derived remote sensing products (e.g., normalized difference vegetation index (NDVI), radar backscatter coefficient, precipitation, and brightness temperature) and field data (depth to water table), (2) areas witnessing shallow groundwater levels show high NDVI (mean and standard deviation (STD)), radar backscatter coefficient values (mean and STD), and low brightness temperature (mean and STD) compared to their surroundings, (3) correlations of temporal groundwater levels and satellite-based precipitation suggest that the observed (2017–2019) rise in groundwater levels is related to an increase in precipitation in these years compared to the previous three years (2014–2016), and (4) the adopted methodologies are reliable, cost-effective, and could potentially be applied to identify shallow groundwater along the Red Sea Hills and in similar settings worldwide.
Highlights
Groundwater accounts for 30.1% of the world’s fresh water supplies, 70% of which is used for agricultural purposes [1,2]
(1) We developed remote sensing-based methodologies that utilize a large number of remote sensing data sets (e.g., moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and land surface temperature (LST), radar backscatter coefficient (RBC) from Sentinel-1, soil moisture and ocean salinity (SMOS) measurements, global precipitation measurement (GPM), and tropical rainfall measuring mission (TRMM) estimates) in conjunction with hydrogeologic information (e.g., depth to water table (DTW)); and (2) we developed statistical models that relate the observed shallow groundwater occurrences over areas where field data are available to the remotely acquired observations and use these models to predict the distribution of shallow groundwater elsewhere
This study focused on developing statistical models to identify shallow groundwater occurrences over large areas using readily available remote sensing datasets
Summary
Groundwater accounts for 30.1% of the world’s fresh water supplies, 70% of which is used for agricultural purposes [1,2]. In arid and semi-arid regions, during wet climatic periods, fluvial systems and drainage networks develop, underlying aquifers recharge, rising groundwater tables discharge in lowlands and depressions, runoff and sediment loads increase, and interactions between surface runoff and groundwater flow systems intensify. The opposite happens in dry periods, where runoff is reduced, surface drainage patterns dry up, aquifer recharge is reduced and localized, groundwater tables are lowered, and groundwater discharge decreases in lowlands [4]. There have been reports of rising groundwater levels in many other parts of the arid world These reported occurrences of rising groundwater were found to be largely local in distribution and have been attributed to a lack of organized discharge systems, leakages from water supply systems or cesspools [11], and increased infiltration from precipitation or irrigation [12]
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