Groundwater Productivity Research Articles

Groundwater productivity analysis with geology in the Geumgang River region, Korea

Groundwater productivity analysis with geology in the Geumgang River region, Korea

Groundwater Characteristics’ Assessment for Productivity Planning in Al-Madinah Al-Munawarah Province, KSA

In recent times, drilling groundwater wells for irrigation, domestic, and industrial uses is increasing at a high rate in Saudi Arabia, meaning that groundwater is becoming a primary water resource. In the study region, over-exploitation and unsustainable performance severely deteriorate groundwater. Therefore, it is important to monitor the groundwater levels and quality as well as to detect the hydraulic parameters in order to plan and maintain groundwater sustainability. Knowledge of aquifer hydraulic parameters and groundwater quality is essential for the productivity planning of an aquifer. Therefore, this study carried out a thorough analysis on measured depth to groundwater data (2017 and 2022), borehole pumping test records, and chemical analysis of the collected water samples, especially in the presence of overexploitation and scarcity of recharge scale. To accomplish this aim, measurements of 113 groundwater wells (including 103 water samples) and analysis of 29 pumping tests between step and long-duration tests were made of all aquifer characteristics. These parameters consist of well loss, formation loss, well efficiency, specific capacity, transmissivity, hydraulic conductivity, resulted drawdown, and physiochemical parameters. Thematic maps were generated for all parameters using the geographic information system (GIS) and diagrams to strategize the groundwater productivity in Al-Madinah Al-Munawarah Province. The estimated hydraulic parameters are highly variable. Four distinct portions were identified for aquifer potentiality based on these varying ranges. Both the north and east of the region are good for groundwater productivity due to good aquifer materials, whereas the southwestern and western portions have relatively poor values. The analyzed groundwater was categorized as fresh to slightly salty water, with two primary chemical types identified showing a prevalence of mixed NaCl and Ca-Mg-SO4/Cl water. Finally, groundwater productivity assessment predicts that the aquifers can support the Al-Madinah Al-Munawarah Province demand for several years if certain well distributions are adopted and for a few hours/day of pumping rate. The maps that have been created can be examined to aid in making decisions related to hydrology.

Modeling of groundwater productivity in the Alfred Nzo District, South Africa, using relative frequency ratio and Shannon entropy models

Study regionAlfred Nzo District, Eastern Cape Province, South Africa. Study focusThe study aimed to identify groundwater potential zones in the Alfred Nzo District using advanced geographic information systems and remote sensing applications by integrating relative frequency ratio (RF) with predictor rate and Shannon entropy (SE) models. Seven influential factors that are thought to control groundwater availability in the Alfred Nzo District were considered to identify groundwater potential zones. These factors are drainage density, lineament density, rainfall, slope, land use and land cover, lithology, and soil class. The factors were weighted in the RF and SE approaches. About 70 % of boreholes were used as training datasets, and 30 % were used for validation. Groundwater potential zones were delineated by integrating all these factors and their corresponding weights in ArcGIS software. The accuracy of each model was evaluated using receiver operating characteristic curve and area under curve techniques. New hydrological insights for the regionFive groundwater potential zones were found in the research area, which includes very poor, poor, moderate, good, and very good, by RF and SE models. The results of the models revealed that the SE model, with a success rate of 79.80 %, performed better than the RF, with a success rate of 75.10 %. The results of this research could be helpful in adequately managing groundwater resources in the research area.

STUDY ON HYDROGEOLOGICAL ASPECT OF GALANG SUB-DISTRICT, BATAM CITY FOR ACCEPTANCE OF PROSPECTIVE NPP SITES

This is a preliminary study in the selection of Nuclear Power Plant (NPP) site in Batam's Barelang area to support industrial growth in the area in the future. The initial site selection was conducted in 2015 and 2017 in the pre-survey phase, considering hydrogeological aspect. The results of previous research showed four potential areas, namely Pasir Panjang Beach, Tanjung Batu, Dapur 3 and Tanjung Rame. The hydrogeological aspect plays an important role in the consideration of site acceptance. This is related to the consideration of potential flow of radioactively contaminated groundwater seepage in the site area, in the event of a potential release. The acceptance of the NPP site from the hydrogeological aspect is based on the site’s permeable geological formation and porosity condition, where groundwater can be stored. The purpose of the study was to assess the potential site in Galang Sub-district, Batam City based on hydrogeological aspects which include surface geology, groundwater productivity and rock porosity. Research methods include primary and secondary data collection, literature review and ranking analysis. The results showed that Tanjung Batu, Dapur 3 and Tanjung Rame could be chosen as the potential sites for NPP based on the hydrogeological aspect. The three regions have surface geology in the form of sandstone, clay and claystone rock with medium rock porosity level and medium groundwater productivity. Pasir Panjang Beach is less preferable because it has a high porosity of rocks with the productivity of aquifers is being spread widely.

Fracturing and Groundwater Productivity Linkages in the Koumfab Watershed in Northern Togo

The Koumfab watershed, located in the Dapaong region of northern Togo, overlies the sandstone-pelite formations of the lower megasequence of the Volta Basin and the granito-migmatitic bedrock of the south-eastern edge of the West African Craton. All of these Precambrian formations have a dense network of lineaments or fractures, giving them the characteristics of discontinuous and highly exploited aquifers. The lineament map of the Koumfab watershed, obtained from aerial photographs and the digital terrain model, identifies three main families of fractures running N-S to NE-SW (N0° to N40°), NE-SW to ESE-WNW (N60° to N110°) and ESE-WNW to SE-NW (N120° to N180°). Analysis of the correlation between lineaments and borehole flow rates has enabled us to identify areas with high storage potential. This potential is mainly controlled by lithological and lineament parameters. Boreholes drilled along kilometre-long lineaments underlain by crystalline and sandstone formations are more productive, with generally high flow rates (Q > 5m3/h). The basement formations found throughout the Koumfab catchment are major reservoirs with hydrogeological potential that are already in great demand.

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

RQD modeling using statistical-assisted SRT with compensated ERT methods: Correlations between borehole-based and SRT-based RMQ models

In complex tropical granitic terrains, foundation rocks’ bearing strength is important in infrastructure design, while bedrock fractures that adversely impact engineering structures can boost groundwater productivity. Consequently, rock quality designation (RQD) can characterize these features effectively. This technique is difficult to determine in boreholes and relatively costly for a large area. As a result, novel approaches were employed to effectively determine RQD over a large aerial extent using statistically optimized borehole and seismic P-wave velocity (Vp) data with compensated resistivity modeling. This study was carried out in the typical granitic terrain of Penang Island, Malaysia. The first stage involves evaluating and developing borehole-based RQD models, and the results were correlated with Vp data and were regressively analyzed to develop lithology-based empirical relations. These empirical relations were used for developing 2D/3D SRT (seismic refraction tomography) based RQD models and were treated as novel models. Integrating the borehole-based and SRT-based RQD models with compensated resistivity models effectively delineate the surficial-to-subsurface soil-rock profiles based on their rock mass quality (RMQ) and conditions, as residual soil, completely weathered rock, relatively weathered rock, and integral/fresh granitic bedrock, including different directional and multiple axial fractures. Based on these results, the highlighted suitable sections for founding the foundations of infrastructure are pinned on the fresh bedrock at the depths of 8–25 m, with >2400 m/s, >2000 Ω m, and RQD >90%. The deep-weathered/fractured zones, with depth >35 m at localized sections, are water-bearing proposed for groundwater development. Overall, the methods and lithology-based empirical relationships can be adopted in granitic terrains to rapidly estimate RQD for a vast area with few and no borehole data.

Characterization and Productivity of Alluvial Aquifers in Sustainability Oasis Areas: A Case Study of the Tata Watershed (Southeast Morocco)

Groundwater from alluvial aquifers is a critical source of water supply for rural agriculture, particularly in semi-arid and arid regions. Effective management of these aquifers requires an understanding of the factors that influence their water resources. In this study, we present a case study of the Tata watershed in southeastern Morocco, where the economy is heavily dependent on agriculture and relies exclusively on groundwater. We demonstrate the importance of integrating geological, hydrogeological, and geophysical methods to characterize the aquifer and evaluate groundwater productivity. Analysis of 64 data wells tapping into the aquifer revealed significant disparities in flow yields, ranging from 0.05 to 15.50 L per second. The highest yields were found between depths of 12 and 43 m, which correspond to the alluvium and the altered and fractured part of its substrate. The maximum alluvial thickness of 57 m was determined using geo-electrical prospecting. A piezometric map was created to define the recharge zones, which correspond to the lateral contributions of the bordering Georgian limestones, and infiltration of both rain and surface water along the Tata wadi. Since 1987, there has been a continuous drop in groundwater level, which can be attributed to the increase in irrigated areas following financial incentives provided by the Moroccan government to the agricultural sector. A proposal has been made for the construction of a recharge dam to enable the recharge of the alluvial aquifer. This development is expected to serve a dual purpose by mitigating the deleterious impacts of flooding and facilitating the gradual water infiltration of the alluvial aquifer. This case study provides insights into the hydrodynamics of the aquifer and establishes a simplified model of its functioning. These findings have important implications for the management of alluvial aquifers in similar 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.

Integrated GIS, Remote Sensing, and Electrical Resistivity Tomography Methods for the Delineation of Groundwater Potential Zones in Sangaw Sub-Basin, Sulaymaniyah, KRG-Iraq

In the Sangaw region, groundwater is the primary supply of water for drinking, residential purposes, livestock, and summer farming activities. Therefore, the main objective of this research is to delineate groundwater potential zones (GWPZs) in the Sangaw sub-basin, Sulaymaniyah, KRG-Iraq, by integrating geographic information system (GIS), remote sensing (RS), analytical hierarchy process (AHP), and electrical resistivity tomography (ERT) techniques. Seven different thematic layers, including geology, rainfall, slope, lineament density, land use/land cover, drainage density, and topographic position index, were chosen as the prediction factors. The analytical method of an analytical hierarchy process pair-wise matrix was used to evaluate the normalized weight of these thematic layers. All the layers and their corresponding classes were assigned ranks and weights based on their impact on groundwater potential. Using ArcGIS, these thematic maps were combined to precisely determine the groundwater potential map within the research area. Five different potential zones were generated for the resulting map, namely, very low (55.4 km2), low (90.4 km2), moderate (68.1 km2), high (100 km2), and very high (62.4 km2). The findings revealed that almost 43.2% of the study region is characterized by high to very high groundwater potential zones. In contrast, the very low to low groundwater potential covers around 38.7%, and the moderate groundwater potential occupies 18.1% of the study region. The final map was then validated using results from the two-dimensional inverse sections of eight electrical resistivity tomography profiles. The validation data confirmed that groundwater potential classes strongly overlap with the subsurface water-bearing or non-bearing lithology, and groundwater productivity zones in the given area. The novelty of this research lies in the application of electrical resistivity tomography validation to the groundwater potential mapping approach, which illustrates the robustness of the overall methodology for data-scarce areas. Furthermore, this is one of the very few groundwater potential studies in Iraq and the first in the Sangaw sub-basin, which can assist decision-makers with groundwater prospecting and management, and enable further exploration in the region.

Assessing regional variation in yield from weathered basement aquifers in West Africa and modelling their future groundwater development and sustainability

A data-driven modelling approach was applied to quantify the potential groundwater yield from weathered crystalline basement aquifers in West Africa, which are a strategic resource for achieving water and food security. To account for possible geological control on aquifer productivity, seven major geological domains were identified based on lithological, stratigraphic, and structural characteristics of the crystalline basement. Extensive data mining was conducted for the hydrogeological parameterisation that led to the identification of representative distributions of input parameters for numerical simulations of groundwater abstractions. These were calibrated to match distributions of measured yields for each domain. Calibrated models were then applied to investigate aquifer and borehole scenarios to assess groundwater productivity. Considering the entire region, modelling results indicate that approximately 50% of well-sited standard 60-m-deep boreholes could sustain yields exceeding 0.5 L/s, and 25% could sustain the yield required for small irrigation systems (> 1.0 L/s). Results also highlighted some regional differences in the ranges of productivities for the different domains, and the significance of the depth of the static water table and the lateral extent of aquifers across all geological domains. This approach can be applied to derive groundwater maps for the region and provide the quantitative information required to evaluate the potential of different designs of groundwater supply networks.

Strategi Rintisan Pariwisata Terintegrasi dan Berkelanjutan di Kota Semarang

Gunungpati District has an ex-JSDF land area of 73.2 ha consisting of 67 parcels of land spread across 12 Sub-Districts. The ex-JSDF land area was originally a poverty alleviation program and critical land conservation in the City of Semarang in collaboration with the JSDF (Japanese Social Development Fund), Worldbank and the City Government of Semarang. The development of several ex-JSDF land locations has developed into agro-tourism areas such as those managed by the Agriculture Service in Cepoko Village. However, several other locations managed by farmer groups were abandoned and then experienced land conversion. So that the potential of the ex-JSDF in the region was identified to obtain a pilot strategy for sustainable tourism in the city of Semarang. The research was carried out by identifying tourist attractions and tourism development factors so that directions for developing integrated and sustainable tourism areas in Gunungpati District could be obtained. the results of the analysis of the suitability of cultivated land in the former JSDF land locations spread across 12 sub-districts, 11 of which have an S1 suitability class, namely its use is very suitable for cultivating fruit crops. Meanwhile, one other location, namely Sumurrejo Village, has a Masters degree of suitability (quite appropriate). In general, the limiting factors in the heavy research sites were soil texture and fertility which were in class S3. Another mild limiting factor is temperature and groundwater productivity which are in class S2. Sustainability analysis found that the level of sustainability of fruit cultivation on ex-JSDF land in the Gunungpati District area was in a less sustainable status, the resulting index value only reached 58.94. Integrated tourism development area in Kec. Gunungpati with the main tourism zones covering, 1) Agroeduwisata Kandri Tourism Village, 2) Kreo Cave & Jatibarang Reservoir, 3) Kandri Boat Tourism, 4) Ngrembel Asri, and 5) Firdaus Fatimah Zahra.

Groundwater exploitation in Southern Johor Bahru, Malaysia: Prospects and challenges while drilling and its mitigation measures

Exploration of groundwater sources are increasing worldwide due to the water scarcity. In this study, groundwater exploitation was carried out around Southern Johor Bahru in Malaysia, to understand the subsurface geology, identify potential high yielding aquifers, assess the drilling challenges and determine required mitigation to deal with these challenges. Three exploratory wells were developed for this purpose; 2 wells located in volcanic-sedimentary rock and 1 in Older alluvium. It was found that the volcanic-sedimentary rocks have higher potential for groundwater extraction compared to Older alluvium in Southern Johor Bahru. The fracture with major opening (>4 cm) and litho-contact dominantly control the groundwater occurrence and productivity of volcanic-sedimentary rocks. In addition, the nature of fissures or fractures such as density and aperture influence the groundwater productivity. Whereas the primary porosity of rocks (<5%) is found not to control groundwater productivity except at completely weathered to residual soil zones (up to 47%). Also, the thickness of weathered layer does not substantially contribute to the groundwater productivity at the study area. The optimum depth for well development is more than 150 m for an approximate yield of 37–60 m3/hr at the study area. The length of casing is approximately 30 m depending on the thickness of weathered zone. Finally, the drilling issues such as air loss and mud loss were encountered in volcanic-sedimentary rock and Older Alluvium respectively.

Mapping of groundwater productivity potential with machine learning algorithms: A case study in the provincial capital of Baluchistan, Pakistan

Although groundwater (GW) potential zoning can be beneficial for water management, it is currently lacking in several places around the world, including Pakistan's Quetta Valley. Due to ever increasing population growth and industrial development, GW is being used indiscriminately all over the world. Recognizing the importance of GW potential for sustainable growth, this study used to 16 GW drive factors to evaluate their effectiveness by using six machine learning algorithms (MLA's) that include artificial neural networks (ANN), random forest (RF), support vector machine (SVM), K- Nearest Neighbor (KNN), Naïve Bayes (NB) and Extreme Gradient Boosting (XGBoost). The GW yield data were collected and divided into 70% for training and 30% for validation. The training data of GW yields were integrated into the MLA's along with the GW driver variables and the projected results were checked using the Receiver Operating Characteristic (ROC) curve and the validation data. Out of six ML algorithms, ROC curve showed that the XGBoost, RF and ANN models performed well with 98.3%, 96.8% and 93.5% accuracy respectively. In addition, the accuracy of the models was evaluated using the mean absolute error (MAE), root mean square error (RMSE), F-score and correlation-coefficient. Hydro-chemical data were evaluated, and the water quality index (WQI) was also calculated. The final GW productivity potential (GWPP) maps were created using the MLA's output and WQI as they identify the different classification zones that can be used by the government and other agenciesto locate new GW wells and provide a basis for water management in rocky terrain.

Groundwater Potential Zone Assessment using GIS and Remote Sensing

Over-exploitation of groundwater and marked changes in climate over the years have imposed immense pressure on the global groundwater resources. As demand of water increases across the globe for human consumption, agriculture and industrial uses, the need to evaluate the groundwater potential and productivity of aquifers also increases. This paper aimed to delineate the groundwater potential zones using GIS and remote sensing. Overlay analysis technique is used to develop the groundwater potential prospect zones by integrating different groundwater contributing thematic layers. The thematic layers of land use and land cover, drainage density, lineament density, soil, geology, slope and rainfall were prepared and used for groundwater potential map development by assigning weights to each thematic layer and features. The weights of each thematic layer were assigned based on their importance and relationship with groundwater recharge. Finally, the thematic maps were integrated by Raster calculator tool to develop groundwater potential zones.

Convolutional neural network and long short-term memory algorithms for groundwater potential mapping in Anseong, South Korea

Study regionThe study area was the Anseong-si area that located in the southernmost part of Gyeonggi-do Province at 127°19′ E, 36°82′ N. Anseong has a transitional climate between that the north and the south regions. Its climate is characterized by the geographical conditions of forming expansive plains that stretch from the Charyeong Range. The entire area of the city is surrounded by many high and low mountains to the south and the west, late-middle age and old age hills are spread, while there are many plains due to the development of rivers. Study focusIn this study, machine learning algorithms were used based on convolutional neural network (CNN) and long short-term memory (LSTM) to generate a groundwater potential map in Anseong, South Korea. A total of 295 wells locations were divided by the median value of transmissivity data (T) and produced “1” point with high groundwater productivity data and “0” as the point with the low groundwater productivity and divided into 70:30 for training and validation the model. 14 groundwater potential related factors were used in this study such as topo-hydrological and geo-environmental factors to define the spatial correlation with the high groundwater productivity data. The validation of the model is evaluated using the receiver operating characteristics (ROC) curve analysis method. The area under the ROC curve (AUC) is calculated to test the model. New hydrological insight for the regionThe results shows a good accuracy, as the AUC values were all higher than 0.8. Finally, the groundwater potential maps generated by CNN and LSTM can be used to analyze the areas that potentially provided groundwater in Anseong, South Korea. This study could help the local environment to manage groundwater resources and can be used to assist development planners and decision-makers in groundwater sustainability planning.

Mapping of Groundwater Productivity in Entire South Korea using Probabilistic Model

In this study, the correlation between specific capacity (SPC) and transmissivity (T) values of groundwater and various geological, topographical, soil, clinical, and forest-related factors was calculated using a probability technique-frequency ratio. Then, the groundwater potential maps were created using the frequency ratio model with a resolution of 30 m for the entire South Korea. The maps were validated using the quantitative ROC (Receiver Operating Characteristic)-AUC (Area Under the Curve) method and the results showed the accuracy of 83.52% for specific capacity and 81.92% for Transmissivity. The groundwater potential maps can be used as basic data of groundwater development and downloaded free of charge from the environmental big data platform (www.bigdata-environment.kr).

Groundwater Sustainability and the Divergence of Rock Types in a Typical Crystalline Basement Complex Region, Southwestern Nigeria

This study investigates the relationship among the various types of rock within the basement complex region and their possible yield in term of groundwater productivity. Four different rock types were considered at various locations in Akure metropolis. Electrical resistivity method was adopted using Horizontal Profiling utilizing Wenner array as well as Vertical Electrical Sounding (VES) technique using Schlumberger configuration. The Horizontal Profiling technique was used to determine areas characterized by structural features associated with weak zones that may be diagnostics of cracks, joints, fractures or highly weathered geologic material, while VES was used as a follow up to identified weak zones as a confirmatory test as well as delineation of layer stratification and geologic materials associated with layer parameters that maybe applicable for groundwater occurrence. The results derived from geoelectric parameters were used to determine the second order parameters (Dar-zarouk) for groundwater productivity modeling. The finding reflects the various yield capacity of the different rock types that were considered for this study and without prejudice to fracture/thick weathered basement.

Application of Support Vector Regression and Metaheuristic Optimization Algorithms for Groundwater Potential Mapping in Gangneung-si, South Korea

The availability of groundwater is of concern. The demand for groundwater in Korea increased by more than 100% during the period 1994–2014. This problem will increase with population growth. Thus, a reliable groundwater analysis model for regional scale studies is needed. This study used the geographical information system (GIS) data and machine learning to map groundwater potential in Gangneung-si, South Korea. A spatial correlation performed using the frequency ratio was applied to determine the relationships between groundwater productivity (transmissivity data from 285 wells) and various factors. This study used four topography factors, four hydrological factors, and three geological factors, along with the normalized difference wetness index and land use and soil type. Support vector regression (SVR) and metaheuristic optimization algorithms—namely, grey wolf optimization (GWO), and particle swarm optimization (PSO), were used in the construction of the groundwater potential map. Model validation based on the area under the receiver operating curve (AUC) was used to determine model accuracy. The AUC values of groundwater potential maps made using the SVR, SVR_GWO, and SVR_PSO algorithms were 0.803, 0.878, and 0.814, respectively. Thus, the application of optimization algorithms increased model accuracy compared to the standard SVR algorithm. The findings of this study improve our understanding of groundwater potential in a given area and could be useful for policymakers aiming to manage water resources in the future.

Groundwater Productivity and Rehabilitation of Radial Collector Wells for Agriculture near Okseong Underground Dam

When a radial collector well is installed and operated for agricultural purposes, negative impacts may be observed over time due to the clogging of horizontal arms, such as reduced groundwater discharge and water quality deterioration. When radial collector well No. 2 was rehabilitated using the high-pressure impulse generation technique, the specific capacity and transmissivity were increased by 43.1 and 100.6%, respectively. In contrast, according to air surging, the specific capacity and transmissivity increased by 33.8 and 85.8%, respectively, compared to the initial rate before rehabilitation. During the operation of radial collector wells since construction, the time of well rehabilitation can be effectively determined by continuously monitoring the groundwater level and pumping rate of the radial collector wells, thereby preventing a decrease in productivity.