Mapping Groundwater Research Articles

Fusion of Remotely Sensed Data with Monitoring Well Measurements for Groundwater Level Management

In the realm of hydrological engineering, integrating extensive geospatial raster data from remote sensing (Big Data) with sparse field measurements offers a promising approach to improve prediction accuracy in groundwater studies. In this study, we integrated multisource data by applying the LMC to model the spatial relationships of variables and then utilized block support regularization with collocated block cokriging (CBCK) to enhance our predictions. A critical engineering challenge addressed in this study is support homogenization, where we adjusted punctual variances to block variances and ensure consistency in spatial predictions. Our case study focused on mapping groundwater table depth to improve water management and planning in a mixed land use area in Southeast Brazil that is occupied by sugarcane crops, silviculture (Eucalyptus), regenerating fields, and natural vegetation. We utilized the 90 m resolution TanDEM-X digital surface model and STEEP (Seasonal Tropical Ecosystem Energy Partitioning) data with a 500 m resolution to support the spatial interpolation of groundwater table depth measurements collected from 56 locations during the hydrological year 2015–16. Ordinary block kriging (OBK) and CBCK methods were employed. The CBCK method provided more reliable and accurate spatial predictions of groundwater depth levels (RMSE = 0.49 m), outperforming the OBK method (RMSE = 2.89 m). An OBK-based map concentrated deeper measurements near their wells and gave shallow depths for most of the points during estimation. The CBCK-based map shows more deeper predicted points due to its relationship with the covariates. Using covariates improved the groundwater table depth mapping by detecting the interconnection of varied land uses, supporting the water management for agronomic planning connected with ecosystem sustainability.

Interpolation methods for spatial distribution of groundwater mapping electrical conductivity

This study was carried out to develop a conceptual framework for determining the best interpolation method which mainly is employed to calculate the variability maps of electrical conductivity (EC) in neighboring regions. The considered case study is parts of the Khorasan Razavi province, Iran (including five aquifers Kashmar, Fariman, Doruneh, Sarakhs and Joveyn). In the first step, the empirical variogram (semi-variogram) was computed for the study area. The methods of the variability of a variable with spatial or temporal distance were considered to measure the semi-variogram function. In the next step, the best variogram model (e.g. spherical, exponential or Gaussian) was considered in the Geographic Information System (GIS) environment and f for the Environmental Sciences (GS+) software. By plotting the semi-variogram in GS+ program based on different method as Global Polynomial Interpolation (GPI), Inverse distance weighing (IDW), Radial basis function (RBF), Kriging method, Global Polynomial Interpolation (GPI), Local Polynomial Interpolation (LPI), the best variogram model fitted to spatial structure of the EC. Finally, by considering the acceptable range for different parameters which impact on EC and evaluating their impacts by scaling, the best interpolation method has been selected for that area for employing their neighborhood basin. Result indicated that the precipitation located within the range of 140 to 180 mm, RBI has the priority. This process is continued for all 14 parameters and eventually one method gets the most points.

Assessment of groundwater potential zones in Kuwait’s semi-arid region: a hybrid approach of multi-criteria decision making, Google earth engine, and geospatial techniques

Recently, the use and management of water resources have become a critical issue, especially in arid and semi-arid surroundings. In such areas, the importance of mapping groundwater potential zones is unmeasurable since water is a critical human resource. Focused on the semi-arid region of Kuwait, our research integrates Google Earth Engine and multi-criteria decision-making (MCDM), offering a robust admission to identifying groundwater potential zones. To this end, thirteen criteria including geology, slope, rainfall, elevation, Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Land Surface Temperature (LST), drainage density, Land Use and Land Cover (LULC), lineament density, topographic wetness index (TWI), geomorphology, and the water table were integrated to reach a wise decision through AHP-MCDM. Our findings revealed that Kuwait’s groundwater potential zones are extremely well suited to the country’s north and east. Appropriate potential zones with high and moderate degrees encompass 12% and 37%, respectively, while extremely high suitability is less than 1.5%. These findings are based on the input data (mainly rainfall, NDVI, NDWI, and LST). The likelihood of groundwater potential is higher in the lower regions of the country. Over 7500 km2—nearly 50% of the total area—are classified as low potential. Furthermore, Our research shows that combining more factors can increase precision while ensuring the stability of the detection process of GWPZs. Around 242 km2 as promising targets for future groundwater exploitation within Kuwait. Rigorously validated through on-site field observations and corroborated by maps showing the distribution of productive groundwater wells in Kuwait, our results exhibit a considered alignment. It is recommended that we extend the application of our methodology beyond the borders of the studied terrain and urge decision-makers to consider our findings in their strategic planning processes.

Spatial interpolation and mapping groundwater quality using geostatistical method: case study in Jakham River Basin

Spatial interpolation and mapping groundwater quality using geostatistical method: case study in Jakham River Basin

Multivariate and Spatial Study and Monitoring Strategies of Groundwater Quality for Human Consumption in Corsica

Groundwater, widely used for supplying drinking water to populations, is a vital resource that must be managed sustainably, which requires a thorough understanding of its diverse physico-chemical and bacteriological characteristics. This study, based on a 27-year extraction from the Sise-Eaux database (1993–2020), focused on the island of Corsica (72,000 km2), which is diverse in terms of altitude and slopes and features a strong lithological contrast between crystalline Corsica and metamorphic and sedimentary Corsica. Following logarithmic conditioning of the data (662 water catchments, 2830 samples, and 15 parameters) and distinguishing between spatial and spatiotemporal variances, a principal component analysis was conducted to achieve dimensionality reduction and to identify the processes driving water diversity. In addition, the spatial structure of the parameters was studied. The analysis notably distinguishes a seasonal determinism for bacterial contamination (rain, runoff, bacterial transport, and contamination of catchments) and a more strictly spatial determinism (geographic, lithological, and land use factors). The behavior of each parameter allowed for their classification into seven distinct groups based on their average coordinates on the factorial axes, accounting for 95% of the dataset’s total variance. Several strategies can be considered for the inventory and mapping of groundwater, namely, (1) establishing quality parameter distribution maps, (2) dimensionality reduction through principal component analysis followed by two sub-options: (2a) mapping factorial axes or (2b) establishing a typology of parameters based on their behavior and mapping a representative for each group. The advantages and disadvantages of each of these strategies are discussed.

Groundwaterscapes: A Global Classification and Mapping of Groundwater's Large‐Scale Socioeconomic, Ecological, and Earth System Functions

AbstractGroundwater is a dynamic component of the global water cycle with important social, economic, ecological, and Earth system functions. We present a new global classification and mapping of groundwater systems, which we call groundwaterscapes, that represent predominant configurations of large‐scale groundwater system functions. We identify and map 15 groundwaterscapes which offer a new lens to conceptualize, study, model, and manage groundwater. Groundwaterscapes are derived using a novel application of sequenced self‐organizing maps that capture patterns in groundwater system functions at the grid cell level (∼10 km), including groundwater‐dependent ecosystem type and density, storage capacity, irrigation, safe drinking water access, and national governance. All large aquifer systems of the world are characterized by multiple groundwaterscapes, highlighting the pitfalls of treating these groundwater bodies as lumped systems in global assessments. We evaluate the distribution of Global Groundwater Monitoring Network wells across groundwaterscapes and find that industrial agricultural regions are disproportionately monitored, while several groundwaterscapes have next to no monitoring wells. This disparity undermines the ability to understand system dynamics across the full range of settings that characterize groundwater systems globally. We argue that groundwaterscapes offer a conceptual and spatial tool to guide model development, hypothesis testing, and future data collection initiatives to better understand groundwater's embeddedness within social‐ecological systems at the global scale.

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.

A Multi-criterian Approach to Identify Groundwater Potential Zones in the Subarnarekha River Basin Using Integrated Analytical Hierarchy Process and Geospatial Technology

The intense extraction of groundwater and changing climate patterns have strained global groundwater supplies. As the demand for drinkable water rises worldwide, assessing groundwater availability and aquifer output becomes increasingly important. Geographic information systems (GIS) are being used more frequently for groundwater exploration due to their speed and provision of preliminary data. This study focuses on mapping groundwater availability in a minor tropical river basin in India, using a combination of GIS and the analytical hierarchy process (AHP). Ten thematic layers were generated and analyzed, including Geology, Geomorphology, Land use and land cover (LULC), Lineament density, Drainage density, Rainfall, Soil type, Slope, Topographic Wetness Index ( TWI), and curvature to delineate groundwater potential zones. AHP was employed to assign weights to each category based on their water retention properties. The resulting map was validated against existing groundwater data, demonstrating an accuracy of approximately 85%. The groundwater potential zones were classified as high, moderate, and, low. The moderate potential zone covered 59% of the basin, while the low and high potential zones constituted 29% and 11% respectively. High and low potential regions were limited to small sections of the basin. In conclusion, this research successfully mapped the groundwater availability in the Rarhu River watershed using GIS and AHP. The findings highlight the distribution of different groundwater potential zones, providing valuable information for sustainable water resource management in the area.

Integrated approach-based groundwater mapping in sohag governorate, upper Egypt, using remote sensing and aeromagnetic data

Integrated approach-based groundwater mapping in sohag governorate, upper Egypt, using remote sensing and aeromagnetic data

Analytical prediction of the formation factor for anisotropic mono-sized unconsolidated porous media

The rectangular Representative Unit Cell (RUC) models for mono-sized isotropic unconsolidated porous media have been extended to anisotropic media. Volume averaging was applied to Ohm's law in order to propose analytical expressions for the formation factor for electrical conduction in terms of the pore-scale linear dimensions. The formation factor, crucial for understanding electrical conduction in porous media, has significant applications in subsurface geophysics, petroleum reservoir characterization, and the durability assessment of construction materials. These analytical models provide valuable insights for optimizing the electrical properties of porous structures in various engineering fields, for example in mapping groundwater resources, differentiating oil-bearing zones in reservoirs, and predicting ion migration in concrete. Aspect ratios of the cell and solid dimensions have been introduced, and the formation factor expressed in terms thereof for five different arrays, i.e. a regular, a non-overlapping streamwisely fully staggered, an overlapping streamwisely fully staggered, a non-overlapping transversally fully staggered, and an overlapping transversally fully staggered array. The Laplace equation has furthermore been solved numerically for two-dimensional versions of the different arrays and the formation factor computed for several values of the aspect ratios. The proposed analytical models have been validated against the generated numerical data and compared to experimental and numerical data obtained from the literature. The proposed models have also been adapted to include a percolation threshold porosity in order to improve the model predictions for very low porosity media.

Identification of groundwater potential zones using geospatial technologies in Meki Catchment, Ethiopia

ABSTRACT Mapping groundwater potential zones helps in precisely planning well drilling. The Meki Catchment is currently experiencing irrigation expansion and water scarcity challenges, creating a strong need for groundwater exploitation. The goal of this study was to identify groundwater potential zones (GWPZs) in the Meki Catchment using geospatial technologies to enhance water resource management and support sustainable development in the region. Eight thematic components were used in this analysis. Analytical Hierarchy Process (AHP) method was applied to ensure consistency in judgments through paired comparisons. Weighted overlay analysis was then used to evaluate the GWPZs. The study found that out of the total Meki Catchment area (226,333.26 ha), 30.68% (69,448.31 ha) has high potential, and 34% (76,963.33 ha) has good potential. Validation was conducted using ground truth data, considering existing water point field data from borewells and springs. The results of this study can help prioritize strategies to ensure the sustainable use of groundwater in the area. Drilling organizations can utilize these findings as a resource for feasibility studies in groundwater prospecting projects to locate well sites. The validation results demonstrate that potential groundwater zones can be identified more accurately using GIS and RS approaches at a lower cost.

Electrical resistivity and magnetic methods in mapping groundwater on the western margin of the Central Main Ethiopian Rift- A case study in the Belesa area, eastern Lemmo Woreda, Ethiopia

Electrical resistivity and magnetic methods in mapping groundwater on the western margin of the Central Main Ethiopian Rift- A case study in the Belesa area, eastern Lemmo Woreda, Ethiopia

Integrating in-situ data and spatial decision support systems (SDSS) to identify groundwater potential sites in the Esan plateau, Nigeria

Establishing suitable groundwater resource areas is a challenging endeavour across the globe. However, novel spatial technologies have emerged as valuable tools for the effective strategy, management, and assessment of groundwater resources, especially in data-scarce emerging economies. The current study used spatial decision support systems (SDSS) for evaluating and defining groundwater potential sites (GPSs) in Nigeria's Edo central region to promote sustainable governance of groundwater. By merging multiple groundwater contributing theme layers, a leading-edge information-based multiparametric analytical hierarchy process (AHP) was applied to define the groundwater prospective areas. By systematically assigning weights to every subject-specific layer and feature, the subject matter layers of geology, geomorphology, drainage density, slope, soil properties, landuse/landcover, rainfall distribution, hydraulic conductivity, transmissivity, curvature, proximity to surface water bodies, and elevation were generated and used for groundwater potential map generation. Each thematic layer's weights were allocated and adjusted depending on their qualities and relevance to groundwater recharge. The multicollinearity (MC) analysis was used to evaluate the model's predictive capacity. Finally, groundwater potential sites were created by integrating the theme-specific maps with the weighted total overlay computation tool. The study area contained three separate groundwater potential sites: low, moderate, and high. According to the regional geographic distribution, the largest portion of the area (65%) fell within the moderately significant groundwater potential geographical area. The high and low GPSs, which both have a low curvature and a valley plain characteristic, account for 25% and 10%, respectively, of the entire area. The outcomes were contrasted with the yield of groundwater from boreholes gathered in the study region. The validation analysis found an acceptable 88.89% similarity. This highlights the potential for the groundwater map's significant prediction. Therefore, the applied approach is a viable choice for the advancement of groundwater in the central Edo region and with comparable geology all over the globe.

LithoSFR Model for Mapping Groundwater Potential Zones Using Remote Sensing and GIS

Groundwater is a significant source of water supply, especially with depleted and quality-deteriorated surface water. The number of drilled boreholes for groundwater has been increased, but erroneous results often occur while selecting sites for digging boreholes. This makes it necessary to follow a science-based method indicating potential zones for groundwater storage. The LithoSFR Model is a systematic approach we built to create an indicative map with various categories for potential groundwater sites. It is based mainly on retrieved geospatial data from satellite images and from available thematic maps, plus borehole data. The geospatial data were systematically manipulated in a GIS with multi-criteria applications. The novelty of this model includes the empirical calculation of the level each controlling factor (i.e., weights and rates), as well as the LithoSFR Model, adopting new factors in its design. This study was applied on a representative Mediterranean region, i.e., Lebanon. Results showed that 44% of the studied region is characterized by a very high to high potentiality for groundwater storage, mainly in areas with fractured and karstified carbonate rocks. The obtained results from the produced map were compared with datasets which were surveyed from representative boreholes to identify the discharge in the dug boreholes, and then to compare them with the potential zones in the produced map The reliability of the produced map exceeded 87%, making it a significant tool to identify potential zones for groundwater investment.

Mapping Groundwater Potential Zones for Sustainable Agricultural Development in Entre Ríos, Ecuador

Mapping Groundwater Potential Zones for Sustainable Agricultural Development in Entre Ríos, Ecuador

Novel Ensemble Models Based on the Split‐Point Sampling and Node Attribute Subsampling Classifier for Groundwater Potential Mapping

AbstractGroundwater potential maps are crucial tools for effectively managing water resources, particularly in agriculturally focused countries such as Vietnam. However, creating these maps is a challenging task that requires reliable data and methods. In this study, we integrated the Split‐Point Sampling and Node Attribute Subsampling Classifier (SPAARC) with the Bagging (B), MultiBoostAB (MBAB), and Random Subspace (RSS) ensemble learning techniques and developed three ensemble models: B‐SPAARC, MBAB‐SPAARC, and RSS‐SPAARC. We selected 13 geoenvironmental factors based on their availability, relevance, and association with groundwater potential in the Sesan River basin of Vietnam. We assessed the models' performance using various metrics such as area under the curve (AUC), accuracy, sensitivity, specificity, and RMSE. The findings indicated that the ensemble models performed better than the single SPAARC model in mapping groundwater potential. The MBAB‐SPAARC model demonstrated the highest accuracy with an AUC value of 0.891, followed by B‐SPAARC (AUC = 0.844), RSS‐SPAARC (AUC = 0.871), and the single SPAARC (AUC = 0.853) models. The results also highlighted that elevation, rainfall, land use/cover, and altitude were the most significant factors for mapping groundwater potential in the Sesan River basin. The innovative ensemble models and reliable potential maps developed in this study assist water resource managers in planning water usage based on the benefits and costs for various users and in devising sustainable strategies for using, protecting, and managing groundwater.

Mapping Groundwater Potential Zones with GIS-RS-AHP Under Climate Change: Case of Mostaganem Plateau, Northwest Algeria

Mapping Groundwater Potential Zones with GIS-RS-AHP Under Climate Change: Case of Mostaganem Plateau, Northwest Algeria

Mapping groundwater dynamics in Iraq: integrating multi-data sources for comprehensive analysis

Mapping groundwater dynamics in Iraq: integrating multi-data sources for comprehensive analysis

Groundwater mapping of urban and coastal areas in Brunei

Groundwater mapping plays an important role in effective water resource management, sustainable development, and environmental protection. In the tropical Brunei Darussalam (north Borneo Island), groundwater mapping is yet to be provided. The aim of the study is to provide groundwater mapping of Brunei, particularly for the urban and coastal areas of the Brunei-Muara capital district. The study uses a GIS interpolation technique to generate a groundwater contour map based on groundwater data from 572 sacrificial boreholes located in the study area. Remote sensing data and published maps from secondary sources were digitised in ArcGIS software to produce thematic layers for further hydrological evaluations. Results showed that groundwater levels in the study area are generally high and shallow, ranging from 0 to 18 m below ground level with a mean value of 2.9 m. According to the evaluation of geo-thematic layers and groundwater contours, groundwater flows towards the South China Sea in the coastal areas and towards the Brunei River further inland. Hydraulic gradients towards the South China Sea also vary between 0.004 and 0.08. Thus, assuming surface aquifer thickness in the weathered zone between 10 to 20 m, hydraulic conductivities ranges from 1∙10−5 to 1∙10−4 m∙s−1, a submarine groundwater discharge (SGD) flux between 4.7∙10−7 to 4.0∙10−4 m3∙s−1 per unit width can be estimated for the shallow aquifer. This study provides valuable insights into the groundwater system dynamics so important, which are critical for its future utilisation and protection, aiming to contribute to the national water security in Brunei Darussalam.

Determination of the Groundwater Potential Zones in Babylon Using Remote Sensing & GIS Techniques

Freshwater found underground in the tiny spaces (pores) of soil and rocks is known as groundwater. Groundwater is a valuable resource that considerably contributes to the yearly supplies. To preserve water quality and oversee groundwater systems, evaluation of the potential zone of groundwater recharge is crucial. Using remote sensing and Geographic Information System (GIS) tools, groundwater potential zones are identified. This study proposes to use satellite imagery and the software program (ArcGIS) to find a groundwater potential zone in Babylon City, Iraq. A groundwater map has been created using various data, namely slope, drainage density, lineament density, land use/land cover, geology type, soil type, and rainfall map. All these data are collected using a weighted overlay tool. Five categories were created based on the groundwater results: very poor, poor, moderate, good, and exceptional. The 'good' class covers about 32% of the study area. The current study shows that excellent groundwater class exists in Al-Hindiyah Dam, Al-Muhaweel, Al-Midhatiyah, Al-Kifil, and Al-Mashrua’a. The excellent groundwater class in Al-Shommali covers approximately 198.0054 km2. Certain areas like Al-Musaib Center, Al-Hilla Center, Al-Hashimiyah, and Abi Garaq don't have much groundwater. The moderate and excellent classes cover around 19% of the study area. The main conclusion is that Remote Sensing and GIS have gained recognition as a practical approach to mapping groundwater potential zones due to their ability to integrate diverse spatial data.