Mapping Groundwater Research Articles

The effects of relative position of anomalous body and topography on the semi-airborne transient electromagnetic survey

The semi-airborne transient electromagnetic method using short-offset has the characteristics of high signal-to-noise ratio and large detection depth, which can adapt to environmental monitoring, groundwater mapping and metal survey in complex terrain. The terrain effects will modulate semi-airborne transient electromagnetic method response. Most terrains effects studies assume that the anomalous body is located below the centre of topography or under the slope, however, in the direction of electromagnetic propagation, several scenarios exist regarding the position of an anomalous body relative to a topography, and different situations will have different anomalous characteristics. In this study, the time-domain finite-element modelling using unstructured mesh is used to investigate the distribution of the electromagnetic response of different time channels of different anomalous bodies in different positions relative to a topography under two conditions: mountains and valleys. The results show that (1) The influence of the relative position of the anomalous body and the topography is similar in the mountain and valley. When the anomalous body is located on the side of the topography far from the transmitter, it is more affected by the topography than when the anomalous body is located on the side of the topography near the transmitter, and (2) in the early stage, the distribution of the electromagnetic response is primarily determined by the topography, in the middle stage, the coupling between anomalous bodies at different locations and the topography results in an extremely complex response distribution, in the late stage, the response distribution primarily originates from the eddy current of the anomalous body, and the effect of the topography is moderate. When using semi-airborne transient electromagnetic method for environmental monitoring and shallow resources survey in complex terrain, data processing and interpretation should be performed based on the position of the anomalous body relative to the topography.

Multi-collinearity Based Parameter Optimization and Comparison among Multi-criteria Decision Analysis to Map Groundwater Potential Zones

Abstract Zonation of groundwater potential is a vital technique for long-term water governance and urban planning, particularly in agrarian countries such as India. As a result, the present groundwater potential mapping study was carried out in Tiruvannamalai district, Tamil Nadu, India to assess the capability of the aquifer using 21 groundwater conditioning parameters. An overlay analysis was performed to create a database for multicollinearity analysis to optimize the parameters. Normalization, weight allocation, and ranking of locations based on the assessment value were performed using Multi Criteria Decision Analysis (MCDA) techniques such as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Multi-Objective Optimization based on Ratio Analysis (MOORA). The results of MCDA techniques were integrated with Remote Sensing (RS) and Geographical Information System (GIS) for the identification of groundwater potential zones. Based on the TOPSIS, 5.17 % of the area was classified as very high potential and 9.38 % of the area was classified as a very low potential zones. Similarly, the MOORA technique classified 5.54% of zones as very high and 13.55% as very low potential. Validation of results were done using groundwater level and groundwater draft data and prediction accuracy of MOORA and TOPSIS was found to be more than 80%.

Groundwater mapping and locally engaged water governance in a small island terrain: Case study of Karainagar island, Northern Sri Lanka

AbstractGroundwater is a vital resource under threat in island communities. Karainagar, a 22 km2island, is one of seven islands off the coast of Jaffna in Northern Sri Lanka, with its population of just about 11,000 persons, experiences seasonal water shortage, and salinity in groundwater as twin threats impacting on their lives. This paper reports on a 3‐year study (October 2019 to September 2022) to map groundwater dynamics of Karainagar island spatially and seasonally and discusses the patterns revealed in terms of community needs, policy implications, and governance ideas that could already be considered by relevant authorities and citizens jointly. Thirty‐six dug wells used for drinking, domestic, agricultural, and public purposes were selected, and water level, salinity, and pH changes recorded along with daily rainfall. This paper offers a thorough description of the geography, land use, distribution of wells, and water bodies, followed by discussion of the current status of the groundwater in Karainagar island. Year‐to‐year differences in rainfall pattern resulted in different rates of change and range in water level with a corresponding reverse pattern seen in salinity with some exceptions across the island. Cumulative rainfall required to reach full capacity of wells ranged from 652 to 892 mm over the 3 years with an average figure of 739 mm of rain. This implies that any further rainfall during early phase of the main rainy season is potential surface water for storage and runoff. Practices such as unregulated pumping and construction of tube wells are argued to be contributing to increase in salinity levels with health implications for residents. A participatory governance approach that overcomes limitations of the existing institutional approach is proposed. Its success based on broad stakeholder engagement, improved equity, and transparency when supported by adequate policies and village level aquifer monitoring will enable sustainability of groundwater resources in Karainagar.

Mapping Groundwater Potential Zones in the Habawnah Basin of Southern Saudi Arabia: An AHP- and GIS-based Approach

The excessive depletion of groundwater resources and significant climate change have exerted immense pressure on global groundwater reserves. Owing to the rising global demand for drinking water, as well as its use in agriculture and industry, there is an increasing need to evaluate the capacity and effectiveness of underground water reservoirs (aquifers). Recently, GIS has gained significant attention for groundwater exploration because of its ability to provide rapid and comprehensive information about resources for further development. This study aims to assess and map the groundwater potential of a large basin located in the southern region of Saudi Arabia. Techniques such as GIS and AHP were employed in this study. To perform the delineation for the groundwater potential zones (GWPZ), seven thematic layers were prepared and analyzed. These layers include geology, slope, land use, lineament densities, soil characteristics, drainage density, and rainfall. These variables were carefully considered and examined to identify and categorize areas based on their respective groundwater potentials. The assigned weights to each class in the thematic maps were determined using the well-known analytic hierarchy process (AHP) method. This methodology considered the characteristics of each class and their capacity to influence water potential. The results’ precision was verified by cross-referencing it with existing information about the area’s potential for groundwater. The resulting GWPZ map was classified into the following five categories: very low, low, moderate, high, and very high. The study revealed that approximately 42.56% of the basin is classified as having a high GWPZ. The low and moderate potential zones cover 36.12% and 19.55% of the area, respectively. Very low and very high potential zones were found only in a limited number of areas within the basin. This study holds global importance as it addresses the pressing challenge of depleting groundwater resources. With rising demands for drinking water, agriculture, and industry worldwide, the effective evaluation and management of underground water reservoirs are crucial. By utilizing GIS and AHP techniques, this study provides a valuable assessment and the mapping of groundwater potential in a large basin in southern Saudi Arabia. Its findings and methodology can serve as a model for other regions, supporting sustainable water resource management globally.

Mapping Ground Water Potential Recharge Zones of Wadi Al-Batin Alluvial Fan, Using Remote Sensing and GIS Techniques, Southwestern Iraq

Groundwater potential recharge (GWPR) zones are an important process in managing water resources. Six thematic layers were used to produce GWPR mapping for Wadi Al-Batin alluvial fan, Southwestern Iraq with GIS environment and analytical hierarchical process (AHP), including geology, lineaments density, slope gradient, drainage density, soil, and slope aspect. Based on the importance, the thematic layers are ranked, which control the GWPR. Drainage density, lineament density, slope aspect, and slope gradient maps are classified into five classes, whereas, geology and soil are classified into six classes. The classes are weighted based on the magnitude of groundwater recharge potential. The AHP technique divides the entire into three zones based on GWPR values: high, moderate, and low. The final GWPR map demonstrated that the western and northwestern parts of the alluvial fan have greater groundwater recharge potentials with 70% of the total area due to the increase in the infiltration rates as a result of the gravely and sandy soils besides the agricultural land use in the present areas. However, the other part of the fan ranged between moderate and low with 25% and 5% of the total area, indicating suitable zones for groundwater artificial recharge processes.

Mapping groundwater recharge potential zones in arid region using remote sensing and GIS perspective, Central Tunisia

Mapping groundwater recharge potential zones in arid region using remote sensing and GIS perspective, Central Tunisia

Delineating bedrock topography with geophysical techniques: An implication for groundwater mapping

Bedrock topography delineation is essential for shallow groundwater mapping because the bedrock surface is the lower boundary of the unconsolidated aquifer system and is difficult to map if covered by thick surficial deposits. Non-invasive geophysical techniques are suitable tools for quantifying the depth to bedrock at a single point location or the bedrock topography using an interpolation between multiple measurements, borings, outcrops, and knowledge of the local bedrock’s brittle and ductile structure. In this study, first, we developed a high-resolution bedrock topography map for the southern coast of Rhode Island, USA, with a wide range of available lithological data. Second, we employed the Horizontal to Vertical Spectral Ratio (HVSR) seismic method to develop a power-law regression between the resonance frequency and the depth to bedrock, and we demonstrated statistical techniques to refine the relationship. Like in most other formerly glaciated regions worldwide, the surficial deposits are glacial outwash and till. It was found that the predictive performance of HVSR was better for glacial outwash than till mixed outwash. In addition, we highlighted the importance of the HVSR technique in interpreting the electrical resistivity profiles for groundwater mapping in both inland and coastal aquifers. Though the quantitative results are site-specific, the approach and insights are generalizable to any unconfined aquifers.

Estimation of Fluoride Concentrations and Fluoride Mapping of Groundwater and All Drinking Water Sources in Kothamangalam Taluk, Kerala, India

Estimation of Fluoride Concentrations and Fluoride Mapping of Groundwater and All Drinking Water Sources in Kothamangalam Taluk, Kerala, India

Application of Deep Learning Neural Network for Mapping Groundwater Productivity Potential: Case of Cheliff Basin-Algeria

Application of Deep Learning Neural Network for Mapping Groundwater Productivity Potential: Case of Cheliff Basin-Algeria

Mapping Groundwater Recharge Potential in High Latitude Landscapes Using Public Data, Remote Sensing, and Analytic Hierarchy Process

Understanding where groundwater recharge occurs is essential for managing groundwater resources, especially source-water protection. This can be especially difficult in remote mountainous landscapes where access and data availability are limited. We developed a groundwater recharge potential (GWRP) map across such a landscape based on six readily available datasets selected through the literature review: precipitation, geology, soil texture, slope, drainage density, and land cover. We used field observations, community knowledge, and the Analytical Hierarchy Process to rank and weight the spatial datasets within the GWRP model. We found that GWRP is the highest where precipitation is relatively high, geologic deposits are coarse-grained and unconsolidated, soils are variants of sands and gravels, the terrain is flat, drainage density is low, and land cover is undeveloped. We used GIS to create a map of GWRP, determining that over 83% of this region has a moderate or greater capacity for groundwater recharge. We used two methods to validate this map and assessed it as approximately 87% accurate. This study provides an important tool to support informed groundwater management decisions in this and other similar remote mountainous landscapes.

Groundwater vulnerability assessment for drinking water suitability using Fuzzy Shannon Entropy model in a semi-arid river basin

Groundwater protection against geogenic and anthropogenic diffuse pollutants are of preeminent importance for convoying groundwater-dependent hydro-aquatic ecosystems and safeguarding human health by securing a safe and sustainable water security plan. Mapping groundwater vulnerability to pollution represents a topical area of research where traditional models suffer from inherent prejudices. A novel approach to identify groundwater vulnerable zones is thus presented in this study by combining Fuzzy Shannon Entropy (FSE) with a decision support algorithm to replace DRASTIC, GOD and other related methods. We proposed a contemporary “FSE-GVI″ framework for assessing aquifer vulnerability, which for the first time expands and redesigns the seven original geological and hydrogeological parameters with geochemical and anthropogenic factors. Applying such technique weights of 13 geo-environmental and hydrogeological factors (slope, soil, pH, recharge), and anthropogenic factors (land use land cover, population density, groundwater based schemes for irrigation) has been optimized. The computed map has been categorized into very high (10.82%), high (23.20%), moderate (29.29%), low (25.02%) and very low (11.64%).The groundwater of the river basin is rated on a scale of excellent, good, poor, very poor and unfit for consumption. The model is compared to 74 groundwater quality data, and the findings demonstrate an excellent correlation between water quality index (r = 0.84), Total dissolve solids (70%), iron (72%), hardness (85%) and alkalinity levels (75%).The findings of the research reveals 27.3 % of the sampling sites (villages) under poor water quality and 23.21% of very high vulnerable zone which requires competent planning, development, managerial technique to safeguard groundwater resources.

Mapping groundwater’s susceptibility to pollution in the Triffa Plain (Eastern Morocco) using a modified method based on the DRASTIC, RIVA, and AHP models

Mapping groundwater’s susceptibility to pollution in the Triffa Plain (Eastern Morocco) using a modified method based on the DRASTIC, RIVA, and AHP models

MAPPING GROUNDWATER POTENTIAL ZONES USING RELATIVE FREQUENCY RATIO, ANALYTIC HIERARCHY PROCESS AND THEIR HYBRID MODELS IN NZHELELE-MAKHADO AREA, SOUTH AFRICA

The water deficit in Nzhelele-Makhado area calls for an efficient assessment to delineate and map existing alternative water resources for future extraction. We are of a view that the identification of groundwater potential zones (GWPZ) in an area is as equally important as determining the most effective groundwater mapping models for the efficient production of reliable GWPZ maps. Consequently, relative frequency ratio (RF), with predictor value, and analytic hierarchy process (AHP) models, including two RF-AHP hybrid models (HM-A and HM-B) were applied and compared to evaluate their effectiveness and accuracy in groundwater potential mapping of Nzhelele-Makhado area. HM-A model is based on the ranks of classes of groundwater controlling factors that were computed by RF model and weights of controlling factors computed by AHP model. Meanwhile, for HM-B model it was vice versa. Eight groundwater controlling factors (slope, geomorphology, lithology, lineament density, soil, rainfall and land use land cover) were considered for this assessment. These were derived and extracted from conventional and remotely sensed datasets. The resultant GWPZ maps computed by the four models were classified into five categories: very low, low, moderate, high and very high groundwater potential zone. The RF, AHP, HM-A and HM-B has an area coverage of 13.62%, 21.50%, 14.56% and 19.62%, respectively, in very high potential zone. The area under curve (AUC) was used to assess the accuracy of the four models and evaluate the resultant maps using 37 geosites in the area. The RF, AHP, HM-A and HM-B show the AUC value of 72.47%, 60.55%, 71.96% and 49.85%, respectively. The models based on RF-derived ranks show better accuracies than models based on AHP-derived ranks. This suggest that the ranks have more influence in the performance of models than weights. The weights derived by AHP and RF models were generally consistent; thus, confirming that the ranks have more influence on the resultant maps. The maps generated from RF-derived ranks can therefore be used for further ground-based investigation of groundwater potential sources in the area.

The potential evaluation of groundwater by integrating rank sum ratio (RSR) and machine learning algorithms in the Qaidam Basin.

Groundwater is a vital resource in arid areas that sustains local industrial development and environmental preservation. Mapping groundwater potential zones and determining high-potential regions are essential for the responsible use of the local groundwater resource. When utilizing machine learning or deep learning algorithms to forecast groundwater potential in arid areas, difficulties such as inaccurate and overfitting predictions might occur due to a shortage of borehole samples. In this study, a database of groundwater conditioning factors with a size of 275,157 × 9 was created in the Qaidam Basin, and 85 known borehole samples were collected. The groundwater potential was evaluated using a combination of rank sum ratio (RSR), projection pursuit regression (PPR) and random forest (RF) algorithms, resulting in four models: PPR, RSR-PPR, RSR-RF, and RF. Results indicated that the groundwater potential was higher in mountainous regions surrounding the Qaidam Basin and decreased progressively towards the central and northwestern regions where most industries and facilities are located. The two primary factors, according to the PPR and RF models, were evapotranspiration (0.246, 0.225) and landform (0.176, 0.294). In terms of their ability to accurately forecast the borehole samples, the four models ranked as follows: RF > RSR-RF > RSR-PPR > PPR. The accuracy of the four models in the low-potential area was 0.73 (PPR), 0.60 (RSR-PPR), 0.87 (RSR-RF), and 0.80 (RF), respectively. However, the RF model showed overfitting due to a lack of samples, especially in high-potential regions, which limits its applicability. The RSR-RF method was applied directly to evaluate the entire factor database, avoiding the risk of overfitting caused by a limited number of training samples. The results demonstrate that the RSR-RF model is effective for classifying groundwater potential types in samples and mapping groundwater potential of the study area. This research presents a novel approach for groundwater potential predictions in areas with insufficient sample sizes, providing a reference for policymakers and researchers.

Integrated Geospatial and Geophysical Approaches for Mapping Groundwater Potential in the Semi-Arid Bukombe District, Tanzania

The rapid growth of civil societies coupled with population influx due to the artisanal mining industry in the Bukombe district (BD) has triggered a high demand for water resources. The daily consumption of water resources in the district surpasses the supply from available surface water sources. Thus, the situation has raised the demand for groundwater resources as an alternative. Despite the importance of groundwater resources, no current studies have spatially assessed groundwater potential to locate optimal points for borehole development. This study intended to investigate and map the groundwater potential areas (GWPAs) in the semi-arid BD using remote sensing (RS), the geographic information system (GIS), and the analytic hierarchy process (AHP) to help local communities access clean and safe water. Rainfall, geology, slope, drainage density, land use/land cover and lineament density were prepared to delineate the map of GWPAs. The map was categorized into poor (0.21%), moderate good (51.39%), good (45.70%) and very good (2.70%). Finally, the GWPA map was validated using Vertical Electrical Sounding (VES), 2-D sections and a drilled borehole. The validation results confirmed that the applied approach provides significant results that can help in planning the sustainable utilization of groundwater resources.

Mapping Groundwater Potential Zone Based on Remote Sensing and GIS Using Analytical Hierarchy Process (AHP) in Tana Righu, West Sumba, Indonesia

This study aims to delineate groundwater potential zones in Tana Righu. Multiple thematic maps were prepared using RS and GIS techniques and was assigned suitable weights on the Saaty’s scale. The assigned weights of the thematic maps were then normalized using the AHP technique. Ultimately, these thematic maps were integrated with a weighted overlay technique in GIS. The results showed that about 42% of the study area has “moderate” potential; 35.86% of the study area has “high” potential; 28,82% of the study area has ”low” potential. 3.57.1% of the study area has “very high” potential; and 1.56.1% of the study area The “very low” potential. Overall, this study provides more efficient approach to mapping the potential groundwater availability. The results of this study are expected to assist in the planning, management and better utilization of groundwater resources.

Real‐Time Monitoring and Postprocessing of Thermal Infrared Video Images for Sampling and Mapping Groundwater Discharge

AbstractGroundwater discharge along channels can affect stream discharge, chemistry, and ecological communities. Although the spatial distribution of groundwater springs along wide rivers can be investigated by areal thermal infrared (TIR) remote sensing, this technique is difficult to apply to mapping at a high spatial resolution and under riparian tree canopies. We present a real‐time monitoring and postprocessing method of ground‐based TIR video for determining groundwater discharge sampling points and mapping the surface water temperature. We applied this method to mapping two headwater streams in Hokkaido, Japan, in the summer. The first site was a 1.3‐km‐long reach underlain by Pleistocene andesite lava. Almost all of the springs were colder and had a different chemistry compared to that of the stream water, which supports the usefulness of TIR monitoring for determining groundwater discharge zones. Video postprocessing showed that cold groundwater springs were spaced every ∼100 m, and their distribution did not follow the topography. At the second site, cold and warm springs were underlain by Holocene volcanic ash. The cold springs mainly seeped from hyporheic and riparian zones downstream, while warm springs were at the footslope. Some cold springs had much higher solute concentrations than the stream and warm springs, which suggests that the water temperature is useful for inferring sources of groundwater discharge. At this site, the video postprocessing could map not only the locations of the cold springs but also the spatial heterogeneity of the stream temperature associated with groundwater inputs.

Multi-Sensor Remote Sensing Data and GIS Modeling for Mapping Groundwater Possibilities: A Case Study at the Western Side of Assiut Governorate, Egypt

Groundwater is an essential natural resource and it has a significant role in the development of dry lands. It is the main source of fresh water in arid and semi-arid regions. The present study investigates groundwater potentiality in the western part of Assiut Governorate, Egypt using advanced remote sensing and geospatial techniques along with hydrological data and field validation. The adopted method provides a low-cost and highly effective tool that can be combined with the conventional land-based approach for mapping Groundwater Potentiality. The study aims to determine the groundwater probability and recharging zones based on the contribution of some physiographic variables that influence groundwater storage. Therefore, multi-sensors remote sensing data from ASTER, Landsat-8, MODIS, Shuttle Radar Topography Mission (SRTM), Tropical Rainfall Measuring Mission (TRMM), and Radarsat-1 were accustomed to extract several geospatial thematic layers (variables). These layers include elevation, slope, curvature, drainage density, topographic wetness index, surface roughness, frequency of thermal anomaly, accumulated precipitation, Land Use/Land Cover (LULC), and lineament density. The produced layers are then scaled and weighted based on their contributions to the recharge of near-surface (unconfined) groundwater aquifers through infiltration and percolation processes. The Simple Additive Weight (SAW) method was utilized to aggregate all the weighted layers for creating the Groundwater Potentiality map. This aggregated grouped map was then classified into 5 classes, from very high to very low groundwater potentiality zones. The results show that the high Groundwater Potentiality was associated with low terrain, high surface ruggedness, high drainage and lineament densities, and relatively close to thermal anomalies in wadi deposits, and adjacent sandy areas. The remote sensing results were validated using comprehensive field observations including, pumping tests, water wells data, and vegetation patterns in the study area. The study concluded that a groundwater possibility map based on geospatial techniques and remote sensing data can provide a robust tool in groundwater exploration, and consequently, it can be adopted elsewhere in arid regions.

Mapping Groundwater Prospective Areas Using Remote Sensing and GIS-Based Data Driven Frequency Ratio Techniques and Detecting Land Cover Changes in the Yellow River Basin, China

Groundwater is an essential resource that meets all of humanity’s daily water demands, supports industrial development, influences agricultural output, and maintains ecological equilibrium. Remote sensing data can predict the location of potential water resources. The current study was conducted in China’s Yellow River region, Ningxia Hui Autonomous Region (NHAR). Through the use of a GIS-based frequency ratio machine learning technique, nine layers of evidence influenced by remote sensing data were generated and integrated. The layers used are soil characteristics, aspect, and roughness index of the terrain, drainage density, elevation, lineament density, depressions, rainfall, and distance to the river from the location. Six groundwater prospective zones (GWPZs) were found to have very low (13%), low (30%), moderate (25%), high (16%), very high (11%), and extreme potentiality (5.26%) values. According to well data used to validate the GWPZs map, approximately 40% of the wells are consistent to very high to excellent zones. Information about groundwater productivity was gathered from 150 well locations. Using well data that had not been used for model training, the resulting GWPZs maps were validated using area-under-the-curve (AUC) analysis. FR models have an accuracy rating of 0.759. Landsat data were used to characterize the study area’s changes in land cover. The spatiotemporal differences in land cover are detected and quantified using multi-temporal images which revealed changes in water, agricultural, and anthropogenic activities. Overall, combining different data sets through a GIS can reveal the promising areas of water resources that aid planners and managers.

Thematic Park Congruence Analysis with Ecological Threshold Analysis Method, Case Study Çanakkale

Thematic Parks are defined as open or closed spaces located in urban open green spaces, enabling people to live and work in a healthy way in urban life, reunification with nature, to get away from mental disorders and to do recreational activities. The most important difference of Thematic Parks from other recreational areas can be defined as the benefits they provide to the country's economy. Within the framework of planning criteria for Çanakkale-Center Thematic Park, which was chosen as the study area, a Thematic Park congruence analysis was carried out for Çanakkale with the Ecological Threshold Analysis Method using Geographic Information Systems (GIS). Land capability map, land use map, aspect map, slope map, elevation map, groundwater map and transportation map were created by classifying them in 1/25.000 scale from the maps to be used as a base in the analysis study. The maps used to determine the potential theme park area were divided into 1x1 km2 grids and scored with a criterion value of 4 for each grid. As a result of the scoring, one each I. and II. degree potential area and three III. degree potential area has been determined. As a result, within the scope of this study, suitable site selection for a Thematic Park that can be applied in Çanakkale has been determined.