Net Recharge Research Articles

Monitoring groundwater vulnerability for sustainable water resource management: A DRASTIC-based comparative assessment in a newly township area of Bangladesh

Groundwater is a vital source of freshwater in our daily lives. Global and local groundwater quality are degrading due to rapid urbanization, human interference, and policy variations, which is prominent in developing nations like Bangladesh. The major purpose of this research is to analyze aquifer vulnerability in Bangladesh's north-central area (Mymensingh) using conventional and modified DRASTIC modeling. Seven influencing hydrogeological factors were employed to develop and integrate conventional DRASTIC modeling: soil media, net recharge, aquifer depth, aquifer media, topography, hydraulic conductivity, and influence of vadose zone, while land use and lineament density were used with them for modified DRASTIC modeling. The findings from four vulnerability analysis detected 29.56% (93.35 sq.km), 22.24% (83.12 sq. km), 28.52 (106.93 sq. km), and 37.6% (140.55 sq.km) of the study area as high to very high vulnerable zones for groundwater pollution. Lower groundwater depth, higher hydraulic conductivity, moderate to high groundwater recharge, dense lineaments, dense settlement, agricultural land, and inland waterbodies together might indicate a high vulnerability in the research area. The validation results based on EC and nitrate levels show that conventional (r = 0.884, p ≤ 0.01; r = 0.951, p ≤ 0.01) and modified DRASTIC models (r = 0.868, p ≤ 0.01; r = 0.840, p ≤ 0.01) have a stronger association with unconfined aquifers, than confined aquifers. Modification with both additional parameters showed more accuracy compared to the conventional one. Frequent monitoring of groundwater quality in high and moderately vulnerable zones is recommended for earlier detection and prevention of potential aquifer degradation.

Application of the DRASTIC-LU/LC method combined with machine learning models to assess and predict the vulnerability of the Rmel aquifer (Northwest, Morocco)

The Rmel aquifer, located in the Tangier-Tetouan-Al Hoceima region of northwest Morocco, covers approximately 240 km2 and faces increasing pollution threats due to population growth and economic development. This study assesses aquifer vulnerability to pollution, and compares the performance of various machine learning models integrated with the DRASTIC-LU/LC method. The research used a dataset of 52 water samples analyzed for nitrate concentrations, considering eight factors influencing vulnerability: aquifer depth, net recharge, aquifer lithology, soil texture, topography, vadose zone impact, hydraulic conductivity, and land use. An information gain test was applied to evaluate the importance of these factors. Four machine learning algorithms were used with the DRASTIC-LU/LC method: multilayer perceptron (MLP), the bagging algorithm (BA), K-nearest neighbors (KNN), and extremely randomized trees (ERT). Model performance was assessed via the area under the ROC curve (ROC-AUC) to measure accuracy. The ERT model combined with DRASTIC-LU/LC achieved the highest accuracy (AUC = 0.929), followed by BA (AUC = 0.925), MLP (AUC = 0.852), and KNN (AUC = 0.787). In comparison, the original DRASTIC-LU/LC model had an AUC of 0.530. The results highlight significant vulnerability variation across the Rmel aquifer, with high to very high levels in the southern and northwestern regions, and moderate to low levels in the northeast and central areas. Vulnerability maps were validated by comparing the observed nitrate concentrations in the water samples, confirming model accuracy. Groundwater depth, net recharge, and hydraulic conductivity were identified as the most significant factors influencing vulnerability. This study demonstrates the effectiveness of integrating machine learning models with the DRASTIC-LU/LC method for accurate aquifer vulnerability assessment, offering valuable tools for public policy and groundwater management.

A coupled regional-scale numerical model for hydrological processes and interactions between groundwater and surface water in a controlled drainage district

Controlled drainage (CD) has emerged as an effective strategy to prevent field waterlogging and mitigate drought during crop growth by altering the hydrological process, while few studies have quantified its effect on groundwater-surface water interactions and groundwater recharge at a regional scale. In this study, a new model is developed for the coupled numerical simulation of water flow in ditches, soil, and underground aquifers under CD conditions. The domain is partitioned into horizontal sub-areas and two vertical layers, with ditches discretized into segments based on groundwater flow grids. The Saint-Venant equations, Richards equation, and MODFLOW are applied to describe water movement processes in ditches, soil, and underground aquifers, respectively. The proposed model is calibrated and validated using five years of observations of ditch water levels (DWL) and groundwater levels, demonstrating excellent agreement with observed data. Subsequently, water balance components of the shallow aquifer below 1 m depth (GW), 1 m of root layer soil profile (SW), and ditch water (DW) under seven scenarios with different control schemes during flood and dry seasons are analyzed to quantify variations in hydrological processes caused by CD. The results show that CD significantly impacts water within SW, GW, and DW, soil evaporation, infiltration, and net recharge from GW to SW (GtoS) by altering regional groundwater table depth (GWT) through the exchange between DW and GW (DtoG and GtoD). GWT and DW show moderate correlation with GtoD, while their correlation with DtoG varies significantly under different rainfall conditions. Smaller precipitation results that precipitation and GWT have a higher linear correlation with water balance components during the dry season compared to the flood season. The correlation values (r) between transpiration (T) and GWT range from −0.99 to 0.96 and −1 to −0.85 during the flood and dry seasons, respectively, indicating a pronounced influence of CD on crop growth. On average, a 1 m increase in DWL control scheme leads to a 0.51 m increase in DWL, and regional GWT decreases by 0.35 m and 0.24 m during flood and dry seasons, respectively. Furthermore, for every 1 m decrease in GWT, net GtoS increases by 36.1 mm and 28.1 mm, respectively, resulting in an increase in SW by 13.9 mm and 11.8 mm, respectively. Considering the varying main crop water stress and the impact of CD under different rainfall conditions, an appropriate CD scheme needs to be adjusted accordingly. These findings provide a quantitative reference for the effect of CD on regional hydrological process and serve as a typical case for similar areas aiming to implement CD strategies for waterlogging and drought control.

Assessment of groundwater susceptibility to contamination using GIS-based modified DRASTIC model in the Rib watershed, Upper Abay Basin, Ethiopia

ABSTRACT Groundwater is one of the most important sources of freshwater, contributing significantly for drinking and other domestic activities around the world. However, its quality is deteriorating over time due to overexploitation and anthropogenic activities. Rib watershed is located in the Tana basin (Ethiopia), is intensively cultivated and urbanizing area. Therefore, this study attempted to assess groundwater vulnerability to pollution using the GIS-based Modified DRASTIC Model. The modified DRASTIC model was selected due to it incorporates both hydrogeological parameters and anthropogenic factors for assessment. The necessary data were collected from the field, and downloaded from websites and laboratory experiments (No3 -). The results showed that more than 73.24% of the watershed is under medium to high vulnerability. Highly vulnerable areas of the watershed (22.48%) was confined to the Southern parts of the watershed (under built-up and cultivated areas). Based on single parameter sensitivity analysis, its vulnerability was highly influenced by aquifer media (24.1%), net recharge (21.75%), land use/land cover (15.1%), and depth of groundwater table (13.6%). The Modified drastic model was validated based on the observed data of nitrate concentration in groundwater. Based on the observed data of nitrate concentration, high-vulnerable areas were more contaminated than medium and low-vulnerable areas. The modified drastic index has a strong correlation with nitrate concentration with (r = 0.76) and (P < 0.043). Therefore, the result indicated that the area is vulnerable to contamination calling for appropriate groundwater management. Hence, this finding helps to plan and minimize future contamination of groundwater by considering its vulnerability before high-risk activities are allowed.

Assessing groundwater contamination risk in industrial zone of Ranipet district, Southern India: A modified DRASTIC and Fuzzy-AHP approach

Groundwater plays a substantial function in sustaining the water requirements of Ranipet district, Tamil Nadu, India, across a variety of domains, including drinking water, agriculture, and industry. However, rising demand and industrial activities have caused concern about groundwater pollution and susceptibility in the region. So, this study employed a modified DRASTIC model to find the regions that are most vulnerable to groundwater contamination. The model includes a novel parameter, "proximity to industry,” in addition to the seven traditional factors (depth to water level, net recharge, aquifer media, soil media, topography, impact of vadose zone and hydraulic conductivity) to account for the industrial nature of the study region. The fuzzy-analytical hierarchy process (FAHP) was used to compute parameter weights and ratings. All the parameters are overlayed in ArcGIS software to create the groundwater vulnerability map (GWVM). The map revealed that the central area along the Palar River is highly vulnerable to contamination. The southern and northern parts have medium to extremely low groundwater contamination risks. The depth of the water table was the most significant component impacting the vulnerability, as per the sensitivity analysis. The model is further validated by chromium concentrations, which were shown to be high in highly sensitive zones and low in low-risk zones. This study also suggests the need for extensive and periodic groundwater quality assessments in highly vulnerable zones for sustainable water resource management.

Spatial Mapping and Prediction of Groundwater Quality Using Ensemble Learning Models and SHapley Additive exPlanations with Spatial Uncertainty Analysis

The spatial mapping and prediction of groundwater quality (GWQ) is important for sustainable groundwater management, but several research gaps remain unexplored, including the inaccuracy of spatial interpolation, limited consideration of the geological environment and human activity effects, limitation to specific pollutants, and unsystematic indicator selection. This study utilized the entropy-weighted water quality index (EWQI), the LightGBM model, the pressure-state-response (PSR) framework and SHapley Additive exPlanations (SHAP) analysis to address the above research gaps. The normalized importance (NI) shows that NO3− (0.208), Mg2+ (0.143), SO42− (0.110), Cr6+ (0.109) and Na+ (0.095) should be prioritized as parameters for remediation, and the skewness EWQI distribution indicates that although most sampled locations have acceptable GWQ, a few areas suffer from severely poor GWQ. The PSR framework identifies 13 indicators from geological environments and human activities for the SMP of GWQ. Despite high AUROCs (0.9074, 0.8981, 0.8885, 0.9043) across four random training and testing sets, it was surprising that significant spatial uncertainty was observed, with Pearson correlation coefficients (PCCs) from 0.5365 to 0.8066. We addressed this issue by using the spatial-grid average probabilities of four maps. Additionally, population and nighttime light are key indicators, while net recharge, land use and cover (LULC), and the degree of urbanization have the lowest importance. SHAP analysis highlights both positive and negative impacts of human activities on GWQ, identifying point-source pollution as the main cause of the poor GWQ in the study area. Due to the limited research on this field, future studies should focus on six key aspects: multi-method GWQ assessment, quantitative relationships between indicators and GWQ, comparisons of various spatial mapping and prediction models, the application of the PSR framework for indicator selection, the development of methods to reduce spatial uncertainty, and the use of explainable machine learning techniques in groundwater management.

Using a comparative of DRASTIC and Bayesian weights of evidence approach to assess transboundary aquifer vulnerability in a data scarcity region: Tuli-Karoo aquifer

Study regionThe Tuli-Karoo Transboundary Aquifer system is shared among Botswana, South Africa and Zimbabwe. It hosts a complex aquifer predominately of sand, heavily tapped in South Africa and sandstone substantially used in Botswana threatening it’s quality. Study focusTwo vulnerability models, the classic DRASTIC (Depth to water table [D], Recharge to the aquifer [R], Aquifer media [A], Soil media [S], Topography [T], Impact of vadose zone [I], Conductivity [C]) and the bayesian based, Weights of Evidence (WofE), were used to delineate zones vulnerable to groundwater contamination under limited nitrate observations. New hydrological insights for the regionThe study revealed that the generic DRASTIC vulnerability results were comparable to the WofE, for the highly vulnerable zones, as both had an area under the curve (AUC) below 0.6. The high vulnerability was attributed to the shallow depth of water level, fractured geological condition (based on transmissivity) and high net recharge rate in and around the Tuli-Karoo Aquifer. However, there are differences in spatial variability in the low/medium vulnerability zones. WofE was superior in capturing spatial variability of groundwater vulnerability. Considerations must therefore be provided, under data scarcity, to incorporate proxies that include landuse-landcover and population density as evidential layers. Overall, WofE performs better due to better prediction power under data-scarcity conditions. This study recommends that under data scarcity, high predictive models like WofE should be used for environmental planning and groundwater protection strategies.

Aquifer vulnerability valorization via DRASTIC index-based assessment within litho-facies of a coastal environment

Determining the degree of an aquifer’s susceptibility to pollutants is an important tool for policy planning in subterranean water administration and conservation. In this work, subterranean water vulnerability was appraised with the use of DRASTIC methodology, which employs seven parameters: depth to groundwater (D); net groundwater recharge (R); aquifer media (A); soil media (S); topography (T); influence of vadose zone (I); and hydraulic conductivity (C). Different ratings were given to each parameter based on the hydro-geological and geo-electrical information obtained from the study area. Geo-electrostratigraphic data was acquired with vertical electrical soundings and electrical resistivity tomography surveys. The results demonstrated the existence of geoelectrical layers with variable resistivities ranging from high to low, with variable curve types. Longitudinal conductance measures indicated moderate subterranean water protective capacity. Analysis of DRASTIC vulnerability indices showed that the aquifer indicated moderate to high vulnerability to contamination. Vulnerability maps were generated to indicate locations of high vulnerability, the goal being to prevent indiscriminate haphazard and wildcat abstraction of groundwater in such locations. The quality category index (QCI) generated for the DRASTIC model indicated that underground water susceptivity is dependent on all 7 parameters employed in the model, with the most critical determinants being the depth to aquifer (D), net recharge (R), aquifer media (A), and impact of the vadose zone (I). The work recommends that anthropogenic activities that could contaminate groundwater resource be halted as the resource is indicated by DRASTIC models as being vulnerable.

Investigation of Aquifer Vulnerability under some Protective Measures in Ehime Mbano, South-Eastern Nigeria for Sustainable Groundwater Development

This study focuses on assessing aquifer vulnerability to contamination in Ehime Mbano South-Eastern Nigeria by applying the DRASTIC model. The data was obtained using (VES) vertical electrical sounding technique by applying Schlumberger configurations with AB/2 = 400 m. The VES data were interpreted using state of the art soft wares e.g. IP12WIN and Surfer 12 to obtain the final model for each VES, groundwater vulnerability map was also developed while aquifer media was gotten by taking into account, the depth at which water was struck and correlating those depths with the lithological description of the VES results obtained. The hydraulic conductivity was calculated from apparent resistivity of the aquifer. However, the net recharge, soil media, and topography was obtained from research documentaries. Aquifer vulnerability assessment carried out revealed areas with high, low and moderate vulnerability based on the DRASTIC Index. Locations with high vulnerability rating of 126 -165 includes: Umuokiri Umunumo and Ikperejere. Locations with moderate vulnerability rating of 86-125 includes: Ikpem, Ikweii Nzerem while locations with low vulnerability rating of 70-85 includes: Umuokara Uzinomi and areas close to Umueze II. The findings of the study can be used to identify regions of contamination of groundwater in the study area.

Remote sensing evapotranspiration in ensemble-based framework to enhance cascade routing and re-infiltration concept in integrated hydrological model applied to support decision making

Integrated hydrological models (IHMs) help characterize the complexity of surface–groundwater interactions. The cascade routing and re-infiltration (CRR) concept, recently applied to a MODFLOW 6 IHM, improved conceptualization and simulation of overland flow processes. The CRR controls the transfer of rejected infiltration and groundwater exfiltration from upslope areas to adjacent downslope areas where that water can be evaporated, re-infiltrated back to subsurface, or discharged to streams as direct runoff. The partitioning between these three components is controlled by uncertain parameters that must be estimated. Thus, by quantifying and reducing those uncertainties, next to uncertainties of the other model parameters (e.g. hydraulic and storage parameters), the reliability of the CRR is improved and the IHM is better suited for decision support modelling, the two key objectives of this work. To this end, the remotely sensed MODIS-ET product was incorporated into the calibration process for complementing traditional hydraulic head and streamflow observations. A total of approximately 150,000 observations guided the calibration of a 13-year MODFLOW 6 IHM simulation of the Sardon catchment (Spain) with daily stress periods. The model input uncertainty was represented by grid-cell-scale parameterization, yielding approximately 500,000 unknown input parameters to be conditioned. The calibration was carried out through an iterative ensemble smoother. Incorporating the MODIS-ET data improved the CRR implementation, and reduced uncertainties associated with other model parameters. Additionally, it significantly reduced the uncertainty associated with net recharge, a critical flux for water management that cannot be directly measured and rather is commonly estimated by IHM simulations.

Utilizing Geological and Geoelectrical methods in a GIS-based DRASTIC model of the Probable Groundwater Vulnerability in the Southern Nigerian Raffia Metropolis of Ikot Ekpene and its Surroundings

The city of Ikot Ekpene is facing a significant issue with groundwater contamination. This is due to the rising amount of home and industrial waste caused by the increasing human population and various business operations in the area. This study seeks to evaluate the susceptibility of groundwater in the metropolis of Ikot Ekpene and its surrounding areas in southern Nigeria. It will utilize integrated geoelectrical and geological approaches within the GIS-based DRASTIC model. A total of twenty vertical electrical soundings (VES) were conducted in the region using the Schlumberger array. Based on the geological drilling data, the interpretation of the VES data suggests that the area consists of 3-4 geoelectric layers. The lithological succession in the area exhibits a range of sediment types, including fine and coarse sand as well as gravelly sands. Additionally, there are localized occurrences of clay intercalations. The third geoelectric layer, located at a depth of 9.0–86.6 m, is the primary aquifer that can be utilized in the region. The DRASTIC model included seven environmental parameters, including depth to the water table, net recharge, aquifer medium, topography, impact of vadose zone, and hydraulic conductivity, with the purpose of conducting a vulnerability assessment. The assessment of groundwater vulnerability ratings (GVR) reveals that 75% of the research region is classified as high vulnerability, 20% as moderate vulnerability, and the remaining 5% as low vulnerability. The studied area is predominantly characterized by moderate to high Groundwater Vulnerability Rating (GVR), which is likely attributed to the generally gentle topography and the presence of highly permeable geomaterials in the upper levels of the water table.

Groundwater pollution vulnerability assessment using a modified DRASTIC model in Ho Chi Minh City, Vietnam

AbstractThe Pleistocene aquifer serves as a vital water source for various activities in Ho Chi Minh City, Vietnam, including concentrated and individual exploitation. In the present study, the DRASTIC (D, depth of water; R, net recharge; A, aquifer media; S, soil media; T, topography; I, impact of vadose zone; C, hydraulic conductivity) model was used to evaluate the groundwater sensitivity of the study area. To analyse Ho Chi Minh City's Upper‐Middle Pleistocene aquifer vulnerability, the analytic hierarchy process (AHP) method was used to optimize the DRASTIC score and include land use (LU) characteristics. Four distinct weights were used: DRASTIC, modified DRASTIC‐LU, AHP‐DRASTIC and modified AHP‐DRASTIC‐LU. This study identified low, moderate and high vulnerability for 12%, 55% and 33% of the DRASTIC‐LU index values, respectively. The AHP‐DRASTIC index classifies 61%, 26% and 13% of sites as low, moderate and highly vulnerable, respectively. The study reveals that 52%, 30% and 18% of the area are vulnerable to the modified AHP‐DRASTIC‐LU index classes. The most sensitive factors are shallow aquifer roofs, recharge and LU. The real‐world accuracy of the DRASTIC models was tested using 106 groundwater nitrate concentrations. The modified AHP‐DRASTIC‐LU is the most accurate and appropriate model for the current research region.

Using VES and GIS-Based DRASTIC Analysis to Evaluate Groundwater Aquifer Contamination Vulnerability in Owerri, Southeastern Nigeria

This study assesses groundwater vulnerability in Owerri, Nigeria, using Vertical Electrical Sounding (VES) and Geographic Information System (GIS)-based DRASTIC modeling. The research methodology includes literature review, field survey, geological feature mapping, hydrogeological assessment, geo-electrical sounding, and data interpretation. Owerri, a rapidly developing city with flat topography and a growing population, uses the DRASTIC model to construct a groundwater vulnerability map. The model evaluates the risk of groundwater contamination using seven critical criteria, including depth to water table, net recharge, aquifer media, soil media, topography, vadose zone impact, and hydraulic conductivity. Each parameter was given a weight and rating, and the DRASTIC Index (DI) was calculated by summing the products of the weights and ratings for each factor. The results of the vulnerability assessment indicated that approximately 49% of the study area falls into the high vulnerability category, around 45% is classified as moderate vulnerability, and the remaining 6% is labeled as low vulnerability. The study reveals moderate to high vulnerability zones in Owerri, Nigeria, due to factors like lower slope terrain, permeable aquifer media, and vadose zone impact. The use of VES and GIS-based DRASTIC mapping techniques provides insights into groundwater vulnerability, aiding in sustainable resource management and environmental protection. The findings emphasize the importance of understanding potential risks and the need for effective management strategies to safeguard clean water supplies. Further research and mitigation efforts should focus on highly vulnerable areas.

Estimation of Groundwater Storage Change and Groundwater Recharge Using GRACE data in Jedeb Watershed Under the Application of Google Earth Engine

Over exploitation of Ground Water (GW) has resulted in lowering of water table in the Jedeb watershed. In this study, water storage changes with GRACE satellite data and total annual precipitation with CHIRPS data in the Google Earth Engine system were investigated for the Jedeb watershed during 2003–2017. The groundwater recharge is estimated from a time series of groundwater storage using the water table fluctuation method. According to the results obtained from the GRACE satellite data on the fluctuations of annual water storage between 2003 and 2017, it was found that the biggest annual increase in water levels (15 cm) occurred in 2008, 2013, and 2015, and the biggest annual decrease (12.5 cm) occurred in 2012. The obtained net recharge rate varied from 18 to 25 cm/year for a 14-year period, and the average was 21 cm/year. This study indicates that the GRACE-based estimation of groundwater storage changes is skilled enough to provide monthly updates on the trend of groundwater storage changes for resource managers and policymakers in the Jedeb watershed.

Assessment of the Vulnerability of Groundwater to Biological Contamination in the Khartoum State, Sudan

This study aims to determine how vulnerable groundwater in Khartoum is to contamination. For this purpose, the DRASTIC Index idea was used. A descriptive cross-sectional analytical analysis is designed in this study. A total of 279 boreholes were sampled from a total of 1015 boreholes (27.5 percent). The following criteria were utilized to define the DRASTIC Index: depth, net recharge, aquifer media, soil texture, terrain, video media, and soil conductivity. Standard bacteriological test methodologies were used for groundwater. The biological data from the 279 boreholes revealed that total coliform, thermo-tolerant coliform, and E. coli were found in 34.4 percent, 18.6 percent, and 0.36 percent of the boreholes, respectively. Bacteriological contamination is common in Sharge Elnile, although only a few cases have been reported in Khartoum. According to the study, the bulk of boreholes in Khartoum State were built without any criteria. Many sources of contamination were discovered within a radius of less than 120 meters, which was deemed to violate Khartoum State’s Environmental Health Law of 2002. For this reason, bacteriological contamination is common in Sharge Elnile, although only a few cases have been reported in Khartoum.

Surface-groundwater interactions in hard rock, water-limited environments, simulated at very fine scale using long time-series observations and hydrotope-modeling concept

Hard rock systems are typically characterized by undulated landscapes, short flow path, dense drainage network, and low aquifer storage. If located in water-limited environments (WLE), then typically have variable rainfall characteristics, frequent floods and droughts, and savannah type of vegetation capable to uptake groundwater. In such environments, surface–groundwater interactions are of primary importance. In this study, surface–groundwater interactions are analyzed focusing on spatiotemporal net recharge dependence on hydrotopes, where a hydrotope is conceptualized as spatial unit (or object), which at a given scale of assessment can be assumed as internally homogeneous (e.g. tree canopy or rock outcrop), but hydro(geo)logically different than the adjacent area. The study was carried out in the small (7.6 ha) Trabadillo study area (TSA) in Spain, representative for hard rocks of WLE, using 3D-GSFLOW integrated hydrological model (IHM) at very fine grid (5x5m), extracted from coarser grid (100x100m) of Sardon 3D-GSFLOW model (Hassan et al., 2014, Journal of Hydrology 517, 390–410). The IHM was calibrated using: (i) 20-year head observation; (ii) 8-year soil moisture observations at 4 profiles, each at different hydrotope and each at 4 different depths; and (iii) MODIS satellite earth observation of evapotranspiration. Despite applying spatially uniform rainfall as forcing, surface–groundwater interactions were highly spatially variable, primarily, because of hydrotope-differences in rainfall interception loss and secondarily, because of differences in transpiration, in subsurface evaporation and in hydrological properties of subsurface. The high temporal variability of rainfall, ranging yearly from 310 to 925 mm, resulted in high temporal variability of all water fluxes, including groundwater fluxes; e.g. gross recharge (Rg) varied annually from 2 to 445 mm, net recharge (Rn), from −50 mm to + 89 mm, while the 20-year mean Rn was close to zero, because Rg was counterbalanced by groundwater exfiltration and less by groundwater evapotranspiration. The high temporal variability of groundwater fluxes and many dry years with largely negative Rn, in combination with low aquifer storage, emphasized TSA dependence on rainfall and its vulnerability to droughts. The hydrotope modeling concept applied at the very fine scale, emphasized also large Rn dependence on land cover type, especially on density and species composition of trees, invisible at coarser scale modeling. As such, the proposed hydrotope modelling approach can be applied as a tool to test whether in a given environment planting (or cutting) trees will result in increase or decrease of water resources.

USING GRACE AND GLDAS DRIVEN DATA TO ASSESS GROUNDWATER FLUCTUATIONS OF NIGER-SOUTH HYDROLOGICAL AREA OF NIGERIA

Gravitational Recovery and Climate Experiments Terrestrial Water Storage and Global Land Data Assimilation Systems Surface Water and Soil Moisture including Nigerian Hydrological Service Agencys Groundwater Level were used to assess the temporal groundwater fluctuations of Niger-south Hydrological Area of Nigeria. The study adopted a cross-sectional research design; descriptive and inferential statistics was used for data analysis; Table was used for presentation. The study finds that there is no statistical significant difference between average monthly net recharge and average month storage changes at 95% probability level, it further concluded that the use of these satellites to acquire data and make decision will mark a new era and bring about fewer causalities on natural event(s), and therefore recommended us to take advantage of this free available resource to ameliorate challenges trying to extinct the existence of man from earth surface; therefore, increasing groundwater levels in Niger-south Hydrological Area needed to be properly managed because of rising groundwater flooding. KEY WORDS: GRACE, GLDAS, QGIS, Groundwater, Fluctuation

Groundwater vulnerability assessment in central Iran: Integration of GIS-based DRASTIC model and a machine learning approach

The study try to evaluate the susceptibility of groundwater. The DRASTIC model was implemented through GIS. Various input variables, such as water table depth, net recharge, aquifer and soil media, topography, vadose zone impact, and hydraulic conductivity, were evaluated within the model to generate a groundwater vulnerability map. Subsequently, machine-learning algorithms (SVM, RF, and GLM) employed using the SDM package in R software to optimize the DRASTIC method. To assess the performance of groundwater pollution risk models, training and validation datasets were evaluated using the ROC curve. The results revealed that approximately 40% of the study area fell within the high vulnerability range, while around 30% exhibited moderate pollution risk. Evaluation of the machine learning models indicated their effectiveness in model development. The RF model demonstrated the highest predictive power, achieving an AUC of 0.98. Additionally, the GLM and SVM algorithms achieved AUC values of approximately 76%. These algorithms can serve as efficient techniques for evaluating and managing groundwater resources. The findings underscored relatively poor groundwater quality in the study area, with excessive aquifer exploitation by the agricultural sector and infiltration of urban sewage and industrial waste identified as the primary causes of groundwater pollution. The implications of these findings are crucial for devising strategies and implementing preventive measures to mitigate water resource vulnerability and associated health risks in central Iran.

Use of water quality index and DRASTIC index correlation for better assessment of groundwater vulnerability to pollution: a case study

Abstract DRASTIC method's vulnerability assessment for estimating the potential risk of contamination in shallow groundwater aquifers is the most acceptable technique. The method uses seven parameters, namely, depth to groundwater table, net recharge, aquifer media, soil media, topography, land use and land cover, and hydraulic conductivity to obtain vulnerability index values. These index values are validated with one or a few elements of water characteristics as pollution indicators. In most of the reported studies, the correlation coefficient between the DRASTIC index and the concentration of individual element(s) was low. The present study uses the water quality index (WQI) to correlate with the DRASTIC index value. In this paper, 11 physical and chemical water characteristics data of 31 well locations within the Faridabad District of Haryana, India are utilized to estimate the WQI. The correlation coefficients for single element concentration with DRASTIC index vary between the range of 0.104 to 0.304. The correlation coefficients for the concentration of NO3- and WQI are found to be 0.104 and 0.533, respectively. Thus, the DRASTIC index demonstrates a stronger correlation with the WQI when compared to single element concentration.

Penilaian Kerentanan Air Tanah terhadap Pencemaran dengan Menggunakan Metode DRASTIC di Daerah Imbuhan Cekungan Air Tanah Jakarta

The CAT Jakarta is a critical water resource that extends across several provinces in Indonesia, covering DKI Jakarta, Banten, and West Java. This basin comprises both recharge and discharge areas that support human settlements and various economic activities. The recharge area in CAT Jakarta covers 321.4 km2 and is densely populated, raising concerns about groundwater contamination. The study used the DRASTIC method to assess groundwater vulnerability, with seven parameters: Depth to Water Table (D), Net Recharge (R), Aquifer Media (A), Soil Media (S), Topography (T), Impact of the Vadose Zone (I), and Hydraulic Conductivity of the Aquifer (C). The vulnerability index obtained that 36.51% of the research area has a low vulnerability level, with values ranging from 101 to 119. The remaining 63.49% has a medium level of vulnerability, with values ranging from 120 to 157. These results suggest that the CAT Jakarta recharge area is at risk of contamination from pollutants with low to moderate intensity. Therefore, it is crucial to monitor and regulate activities that involve the use of groundwater in the area to prevent contamination. This study can guide policymakers and stakeholders in implementing effective management strategies for sustainable groundwater utilization in the CAT Jakarta basin.