Management Of Groundwater Resources Research Articles

Investigating seawater intrusion and salinization using the integration of hydrochemical and geoelectrical techniques

Seawater intrusion poses a significant environmental threat to water resources, agriculture, and ecosystems. We investigate the extent of seawater intrusion and salinization in the eastern coastal aquifers of Saudi Arabia. Hydrochemical measurements and electrical resistivity tomography (ERT) techniques are used to assess groundwater quality and the subsurface extension of seawater intrusion. Two resistivity profiles, 475 m long each, are analyzed to gain insights into the subsurface geology and seawater intrusion. The inversion of the recorded resistivity data reveal four distinct subsurface layers. The uppermost layer consists of surficial deposits, followed by a sandy seawater intrusion layer, beneath which lies a marl layer, and at the bottom, a dolomitic limestone layer representing the brackish-water aquifer. The ERT results are integrated with hydrochemical and hydrogeologic results from 12 wells to overcome the limitations of the ERT. The findings of this study would facilitate the development of efficient mitigation strategies and sustainable management of the groundwater resources in the study area or similar coastal regions affected by seawater intrusion. Understanding and delineating the boundary between saline and fresh water is crucial for safeguarding water resources for agricultural purposes, preserving ecosystem health, and ensuring the long-term sustainability of water supplies in coastal areas.

Estimation of Groundwater Recharge in a Volcanic Aquifer System Using Soil Moisture Balance and Baseflow Separation Methods: The Case of Gilgel Gibe Catchment, Ethiopia

Understanding the recharge–discharge system of a catchment is key to the efficient use and effective management of groundwater resources. The present study focused on the estimation of groundwater recharge using Soil Moisture Balance (SMB) and Baseflow Separation (BFS) methods in the Gilgel Gibe catchment where water demand for irrigation, domestic, and industrial purposes is dramatically increasing. The demand for groundwater and the existing ambitious plans to respond to this demand will put a strain on the groundwater resource in the catchment unless prompt intervention is undertaken to ensure its sustainability. Ground-based hydrometeorological 36-years data (1985 to 2020) from 17 stations and satellite products from CHIRPS and NASA/POWER were used for the SMB method. Six BFS methods were applied through the Web-based Hydrograph Analysis Tool (WHAT), SepHydro, BFLOW, and Automated Computer Programming (PART) to sub-catchments and the main catchment to estimate the groundwater recharge. The streamflow data (discharge) obtained from the Ministry of Water and Energy were the main input data for the BFS methods. The average annual recharge of groundwater was estimated to be 313 mm using SMB for the years 1985 to 2020 and 314 mm using BFS for the years 1986 to 2003. The results from the SMB method revealed geographical heterogeneity in annual groundwater recharge, varying from 209 to 442 mm. Significant spatial variation is also observed in the estimated annual groundwater recharge using the BFS methods, which varies from 181 to 411 mm for sub-catchments. Hydrogeological conditions of the catchment were observed, and the yielding capacity of existing wells was assessed to evaluate the validity of the results. The recharge values estimated using SMB and BFS methods are comparable and hydrologically reasonable. The findings remarkably provide insightful information for decision-makers to develop effective groundwater management strategies and to prioritize the sub-catchments for immediate intervention to ensure the sustainability of groundwater.

Hydrochemical and Formation Mechanism Studies of Groundwater in Quaternary Aquifer in a Northern Plain of China: An Example of Beijing Plain

Beijing Plain is a very active part of Beijing city regarding the socio-economic and human activities of the region. Over the past four decades, Beijing’s economic development and the continuous drought for nearly 10 years in the 2000s have negatively impacted the groundwater quantity and quality. Therefore, it is necessary to investigate the present situation of groundwater chemistry in this region to develop a comprehensive database and orientation for future research on groundwater quality evaluation. Mathematical statistics, Piper’s trilinear diagram, Gibbs plots, the ion ratio method and PHREEQC software 3.7.3 were used to analyze the groundwater hydrogeochemical characteristics and formation mechanisms of the quaternary aquifers of the Beijing Plain area. Hydrogeochemical results indicated that the groundwater is slightly alkaline, with pH values ranging from 6.76 to 8.65 and an average value of 7.92. The order of major cations in groundwater was Ca2+ > Na+ > Mg2+ > K+ with average values of 66.54 mg/L, 50.58 mg/L, 23.78 mg/L, and 1.81 mg/L, respectively, while the order of major anions was HCO3− > SO42− > Cl− with average values of 284.89 mg/L, 52.1 mg/L and 35.5 mg/L, respectively. The groundwater chemical types are Mg-Ca-Cl-HCO3, Na-Ca-HCO3, Mg-Ca-HCO3 and Mg-Na-HCO3. Research on the main influencing factors and PHREEQC hydrogeochemical inverse simulations results along the four pathways selected confirmed that rock weathering with sulfate, silicate and carbonate rock mineral dissolution and Na+, Mg2+ and Ca2+ ion reaction exchange influenced groundwater hydrogeochemical characteristics of the quaternary aquifers of the Beijing Plain area. Understanding the formation mechanisms of hydrogeochemistry in quaternary plains provides guidance for future studies and, through suggestions and case studies, facilitates decision-making by policy-makers on the sustainable management of groundwater resources.

Assessment of groundwater resources from geophysical and remote sensing data in a basement complex environment using fuzzy-topsis algorithm

This study addresses the pressing global water challenge by focusing on a typical basement complex area experiencing acute water shortage. Indiscriminate well siting without reliable hydrogeological maps has resulted in failed attempts to address water shortages. To overcome these challenges, this research aims to enhance the accuracy and reliability of groundwater potential assessments by incorporating crucial groundwater-related factors.The Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) method was adopted due to its ability to improve multi-criteria decision-making (MCDM) techniques for effective groundwater resource management. Unlike TOPSIS, FTOPSIS better reflects decision-makers' intentions, especially concerning geological boundaries and natural phenomena. To achieve the objectives of the study, geophysical and remote sensing datasets were utilized. The study employed the electrical resistivity method, utilising the Vertical Electrical Sounding (VES) technique with the Schlumberger array while the remote sensing data used were the Digital Elevation Model (DEM) image and Landsat ETM image which were processed to generate key groundwater conditioning factors. These factors were integrated using the FTOPSIS algorithm. This algorithm facilitated the calculation of the groundwater potential indices by assigning weights based on their level of significance to influencing groundwater potential in order to generate the groundwater potential map (GPM). The GPM was classified into five zones of varying groundwater potential, with very low and low potential occupying 74 % of the total area. Validation with well data yielded an impressive 79 % accuracy, showcasing the model's enhanced precision. Beyond improved accuracy, the study's implications extend to practical applications in groundwater resource management. By providing a clearer understanding of groundwater potentiality, the research can inform more robust decision-making frameworks, promoting sustainable water use not only in the study area but also in similar geological settings of the world.

Hydrogeological assessment and aquifer potential of a coastal area, South Nigeria: insights from VES surveys and spatial analysis

ABSTRACT This study provides a comprehensive analysis of aquifer properties using vertical electrical sounding (VES) surveys conducted in Eket, Nigeria, to address the challenges of groundwater management in coastal areas. The VES method was employed for hydrogeo-electrical analysis and to investigate the hydrogeological dynamics of the region. The results reveal varying subsurface layers with distinct resistivity values. Spatial distribution analysis indicates densely settled areas exhibit lower resistivities, while sparsely settled regions show higher resistivities. The spatial location labeled EK2 features the largest aquifer, measuring 246.70 m, predominantly located in the central research area. Aquifer depths range from 87.10 to 250.20 m, with variations in thickness highlighting geographical heterogeneity and its impact on groundwater transport. These spatial differences in groundwater characteristics are crucial for understanding groundwater movement, storage, and extraction potential. The study underscores significant variability in porosity, reflecting differences in the aquifers’ water storage capacity and susceptibility to contamination. These findings have important implications for groundwater flow rates and extraction feasibility. The research provides essential data for hydrogeological investigations and groundwater resource management, emphasizing the intricate relationship among geological formations, aquifer properties, human activities, and the potential risks of contamination in variable porosity zones.

Exploring groundwater patterns in Souss-Massa Mountainous Basin, Morocco: A fusion of fractal analysis and machine learning techniques on gravity data

Groundwater potential in Morocco’s Souss-Massa mountainous basin (SMMB) is being identified using geospatial tools and geological data. We deployed four mathematical models, namely Data-Driven Multi-index Overlay (DMIO), Geometric Average (GA), Support Vector Machine (SVM), and Logistic Regression (LR), to establish data-driven patterns among the nine influencing factors, primarily drainage density, permeability, slope, distance to rivers, elevation, lineament density, distance to lineaments, intersection node density, and rainfall. Based on the Concentration-Area (C-A) fractal approach, the findings of the four models were developed and classified into five levels of potentiality ranging from very low to very high. The regions designated as having high and very high potentialities for the DMIO, GA, SVM, and LR models, respectively, account for 22.44 %, 9.80 %, 19.36 %, and 26.77 % of the overall basin. We validated the models by calculating each model's area under the ROC curve (AUC). The estimated AUC values are more than 70 %, suggesting the model performs well. The four models' performance was compared, revealing that the SVM model outperforms the others. Gravimetric data shows that possible groundwater zones closely coincide with gravimetric lineaments. The findings of this study can provide valuable insights to decision-makers, allowing them to improve decision-making processes and develop holistic groundwater resource management in the Souss-Massa mountainous basin (SMMB).

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

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

Quantitative Assessment and Validation of Groundwater Pollution Risk in Southwest Karst Area

AbstractGroundwater pollution risk assessment is a useful tool for groundwater pollution prevention and control. However, it is difficult to accurately quantify groundwater flow and contaminant fluxes in karst areas and different types of karst areas have different hydrogeological characteristics. Therefore, the assessment of groundwater pollution risk in karst areas must use different assessment indicator systems. This study developed a new methodology that modified the vulnerability assessment model PLEIK, determined pollutant fluxes considering hydrogeological conditions, and revised parameter weights using the random forest method. The resulting PLEIKD-RF model was used to assess the risk of groundwater contamination in the southwestern karst region and its validity was verified. The results showed that the groundwater pollution risk in the region was low, with 65.64% of the low and relatively low risk areas located in the middle and high mountainous regions. 11.81% of the high and relatively high risk areas were sporadically located in the western and central regions, which were mainly controlled by the distribution of the pollution sources and the karst development. The accuracy of the results of groundwater pollution risk assessment in the study area was 71.87% as verified by the horizontal difference method. The results of the sensitivity analysis indicated that accurate, detailed, and representative data on the protective layer, surface water-groundwater interactions, and pollution source loads would improve the accuracy of groundwater pollution risk zoning. This assessment method provided a reference for similar assessments and the results provide a basis for the protection and management of groundwater resources in the region.

Exploring the InSAR signature associated with river-sourced recharge in California’s San Joaquin Valley

Recharge is a critical component for understanding aquifer systems and the sustainable management of groundwater resources, yet this process is challenging to measure at policy-relevant spatiotemporal scales. Building upon previous research, we tested the hypothesis that InSAR can be used to observe river-sourced recharge if the underlying recharge pathways are associated with sufficient clay content. Our analysis leveraged the decomposition of InSAR time series with interpretations of 3D resistivity models derived from airborne electromagnetic (AEM) surveys. We focused our analysis on two study sites where high density AEM data were available and river-sourced recharge is determined to have occurred during wet years: (1) near Fresno, California and (2) near Visalia, California. Sediment type and hydrogeological structure from AEM supported our hypothesis with the InSAR signature attributed to river-sourced recharge occurring only in the study site with semi-confined to confined conditions and relatively high fraction of interbedded clay within recharge pathways. The timing to peak amplitude, the key feature we wanted to isolate in the InSAR data, near Visalia was interpreted as a pressure pulse front associated with river-sourced recharge propagating into the San Joaquin Valley. This study further validated the potential of InSAR, coupled with AEM data, to map and monitor river-sourced recharge in aquifer systems. As InSAR data become more accessible, this approach holds promise for broader applications in groundwater science and management worldwide.

Enhancing groundwater potential zone mapping with a hybrid analytical method: The case of semiarid basin

Groundwater resource management is a critical component of sustainable water use, necessitating accurate and nuanced mapping of groundwater potential zones. This study analyzed the groundwater potential of Algeria's 43,750 km2 Chelif Basin (more than 17% of the area of Northern Algeria) using a combination of both subjective and objective mapping techniques. The adopted approaches encompass the benchmark analytical Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and the DEcision MAking Trial and Evaluation Laboratory (DEMATEL) methodologies to quantify interdependencies of criteria related to groundwater potential. The analysis focused on ten criteria related to groundwater potential, including core moisture availability and key hydrological factors like distance to river, topographic wetness index, and hydrological soils. Fuzzy-AHP achieved slightly higher groundwater prospecting accuracy (AUC = 0.730) than classic AHP (0.716), with benchmarking against 15 related studies indicating robust performance. Instead of the most commonly used criteria in groundwater literature such as lineament, stream order, recharge rate, and drainage density, this study employed alternative factors to challenge and validate the efficacy of the proposed methodology. The decision to omit certain criteria facilitated a more focused and manageable analysis, yet still delivered a robust evaluation of groundwater potential in the studied area. Moreover, this approach underscores the adaptability of the proposed methodology to accommodate varying sets of criteria, tailored according to the availability of data and specific research objectives. Additionally, the DEMATEL evaluation reveals new insights into subtle prioritization divergences, specifically between domain specialist opinions and analytical assessments of the criteria. The integration of fuzzy logic and causal relationship mapping through DEMATEL provides a comprehensive and robust foundation for groundwater potential modeling.

Deciphering hydrogeochemical evolution in the multilayered Ilhas-São Sebastião aquifer system, Brazil: Implications for groundwater resources management

This study examines the hydrogeochemical processes shaping groundwater quality in the Ilhas-São Sebastião aquifer system, situated at the interface of the Central and Southern Recôncavo basins in the densely populated area near the Brazilian metropolis Salvador. Analysis of 71 groundwater samples reveals distinctive hydrogeochemical compositions in aquifers. In the São Sebastião aquifer, alkalis (Na+ + K+) and strong acids (Cl− and SO42−) prevail. Furthermore, a moderate correlation of Na+–Cl-marks an evolution from Mg–Ca–HCO3 to Mg–Ca–Cl and Na–Cl facies. In contrast, the Ilhas aquifer displays a Na+>Ca2+>Mg2+>K+ relationship for cations and HCO3− > Cl− > SO42− > CO32− for anions and a recharge-discharge trajectory from the Mg–Ca–HCO3 to the Ca–Na–HCO3 facies. Additionally, it presents greater mineralization and dispersion of physicochemical parameters, especially around sub-basin depocenters. Its hydrogeochemical signature is characterized by robust correlations between TDS and EC, and between these parameters and SO42−, HCO3−, Ca2+, and Mg2+, complemented by moderate correlations of EC with Na+ and Cl−. Bivariate Gibbs diagrams and ionic ratios indicate silicate weathering and ion exchange as the primary geochemical processes controlling solute concentrations in both aquifers. However, in the Ilhas aquifer, a subordinate contribution from reverse ion exchange is indicated by weak (TDS–Na+, TDS–K+, Na+–Ca2+, K+–Ca2+) and positive TDS–Ca2+ and TDS–Mg2+ correlations. Conversely, negative chloroalkaline indices and the moderate Na+–Cl- correlation indicate that reverse ion exchange processes are mostly absent in the São Sebastião aquifer. Instead, both chloroalkaline imbalance reactions and silicate weathering contribute equally to the observed geochemical patterns. Groundwater geochemical signatures indicate recharge on flexural margins, active water-rock interaction in large depocenters, and mixing of hydrogeochemical facies between aquifer units. These insights contribute to a comprehensive understanding of groundwater evolution, crucial for effective water resource management in the region.

Combination of remote sensing, GIS, AHP techniques and geophysical data to delineate groundwater potential zones in the Shiriya River Basin, South India

Shiriya River Basin (SRB) of Kasaragod district, Kerala, is one of the minor river basins that faces acute water shortage soon after the rainy season. Increasing the aquifer productivity of the SRB is the need of the hour. The present study is performed to determine the groundwater potential zones (GWPZ) of the SRB through Weighted Overlay Analysis. Different thematic layers (Geomorphology, Geology, Lineament density, Slope, Drainage density, LULC, and Soil) were prepared. Based on Saaty's scale, the rank and weightage assigned to each thematic layer and their respective features were standardized through the AHP techniques. Subsequently, GIS-based Weighted Overlay Analysis generated the ultimate GWPZ map, dividing SRB into 3 potential zones (poor, moderate, and good). To validate the GWPZ and understand the geoelectric characteristics of the SRB, 50 Schlumberger VES were performed and analyzed. Depth to water level data is also used to validate the GWPZ. The VES data indicated three distinct geoelectric layers, the topsoil, laterite, and weathered/fractured basement, overlying the resistive basement. In the SRB second layer (laterite) and, in some regions, the third layer (fractured charnockite) functions as an aquifer. The presence of groundwater potential region is indicated by resistivity values ranging from 50 to 200 ohm-m. The combination of surface and subsurface indicators of GWPZ will be much more reliable in locating the site for sustainable groundwater exploration and management of SRB groundwater resources.

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.

Assessment of groundwater quality in arid regions utilizing principal component analysis, GIS, and machine learning techniques

Assessing water quality in arid regions is vital due to scarce resources, impacting health and sustainable management.This study examines groundwater quality in Assuit Governorate, Egypt, using Principal Component Analysis, GIS, and Machine Learning Techniques. Data from 217 wells across 12 parameters were analyzed, including TDS, EC, Cl−, Fe++, Ca++, Mg++, Na+, SO4−−, Mn++, HCO3−, K+, and pH. The Water Quality Index (WQI) was calculated, and ArcGIS mapped its spatial distribution. Machine learning algorithms, including Ridge Regression, XGBoost, Decision Tree, Random Forest, and K-Nearest Neighbors, were used for predictive analysis. Higher concentrations of Na, K, Ca, Mg, Mn, and Fe were correlated with industrial and densely populated areas. Most samples exhibited excellent or good quality, with a small percentage unsuitable for consumption. Ridge Regression showed the lowest MAPE rates (0.22 % training, 0.26 % in testing). This research highlights the importance of advanced machine learning for sustainable groundwater management in arid regions. Thus, our results could provide valuable assistance to both national and local authorities involved in water management decisions, particularly for water resource managers and decision-makers. This information can aid in the development of regulations aimed at safeguarding and sustainably managing groundwater resources, which are essential for the overall prosperity of the country.

GIS-based multi-criteria decision making for delineation of potential groundwater recharge zones for sustainable resource management in the Eastern Mediterranean: a case study

In light of population growth and climate change, groundwater is one of the most important water resources globally. Groundwater is crucial for sustaining many vital sectors in Syria, including industrial and agricultural sectors. However, groundwater exploitation has significantly escalated to meet different water needs especially in the post-war period and the earthquake disaster. Therefore, the goal was this study delineation of the groundwater potential zones (GPZs) by integrating the analytic hierarchy process (AHP) method in a geographic information systems (GIS) within the AlAlqerdaha river basin in western Syria. In this study, ten criteria were used to map the spatial distribution of GPZs, including slope, geomorphology, drainage density, land use/land cover (LU/LC), lineament density, lithology, rainfall, soil, curvature and topographic wetness index (TWI). GPZs map was validated by using the location of 74 wells and the Receiver Operating Characteristic Curve (ROC). The findings suggest that the study area is divided into five GPZs: very low, 21.39 km2 (10.87%); low, 52.45 km2 (26.65%); moderate, 65.64 km2 (33.35%); high, 40.45 km2 (20.55%) and very high, 16.90 km2 (8.58%). High and very high zones mainly corresponded to the western regions of the study area. The conducted spatial modeling indicated that the AHP-based GPZs map showed a remarkably acceptable correlation with wells locations (AUC = 87.7%, n = 74), demonstrating the precision of the AHP–GIS as a rating method. The results of this study provide objective and constructive outputs that can help decision-makers to optimally manage groundwater resources in the post-war phase in Syria.

MAPPING THE GROUNDWATER POTENTIAL IN SUB-SAHARAN AFRICA: THE CASE OF THE COMMUNE OF LOUMBILA, BURKINA FASO

The objective of this study is to identify and map potential groundwater resource areas in the rural commune of Loumbila in order to assess the potential water accessibility in the area. A spatial data analysis was applied to identify potential groundwater resource areas for drilling. To this end, geomatics tools (Geographic Information Systems and Remote Sensing) and a multi-criteria analysis using the Analysis Hierarchy Process (AHP) technique were deployed. A total of eight (decision) factors with a strong influence on the groundwater storage potential (i.e., soil types, fracture network density, land use, slope, hydrogeology, alterity thickness and drainage density, precipitation) were selected and mapped. An appropriate weight has been assigned to each factor, which were further normalized using the Analytical Hierarchy Process (AHP). Based on the analysis, the rural commune of Loumbila was qualitatively classified into five groundwater potential zones: very low, low, medium, high and very high groundwater potential. The results obtained show that 9.80% (14.75 km2), 22.02% (33.16 km2), 30.68% (46.19 km2), 18.47% (27.81 km2) and 19.03% (28.65 km2) of the rural municipality of Loumbila have very high, high, medium, low and very low groundwater potential, respectively. The groundwater potential mapping aims to identify the areas with the highest potential for the sustainable management of groundwater resources, enabling informed decisions to be taken for its management and conservation.

Scrutinizing different predictive modeling validation methodologies and data-partitioning strategies: new insights using groundwater modeling case study

Groundwater salinity is a critical factor affecting water quality and ecosystem health, with implications for various sectors including agriculture, industry, and public health. Hence, the reliability and accuracy of groundwater salinity predictive models are paramount for effective decision-making in managing groundwater resources. This pioneering study presents the validation of a predictive model aimed at forecasting groundwater salinity levels using three different validation methods and various data partitioning strategies. This study tests three different data validation methodologies with different data-partitioning strategies while developing a group method of data handling (GMDH)-based model for predicting groundwater salinity concentrations in a coastal aquifer system. The three different methods are the hold-out strategy (last and random selection), k-fold cross-validation, and the leave-one-out method. In addition, various combinations of data-partitioning strategies are also used while using these three validation methodologies. The prediction model’s validation results are assessed using various statistical indices such as root mean square error (RMSE), means squared error (MSE), and coefficient of determination (R2). The results indicate that for monitoring wells 1, 2, and 3, the hold-out (random) with 40% data partitioning strategy gave the most accurate predictive model in terms of RMSE statistical indices. Also, the results suggested that the GMDH-based models behave differently with different validation methodologies and data-partitioning strategies giving better salinity predictive capabilities. In general, the results justify that various model validation methodologies and data-partitioning strategies yield different results due to their inherent differences in how they partition the data, assess model performance, and handle sources of bias and variance. Therefore, it is important to use them in conjunction to obtain a comprehensive understanding of the groundwater salinity prediction model's behavior and performance.

Unravelling the signatures of submarine groundwater discharge and seawater intrusion along the coastal plains of Odisha, India: a multi-proxy approach.

Submarine Groundwater Discharge (SGD) and Seawater Intrusion (SWI) are two contrary hydrological processes that occur across the land-sea continuum and understanding their nature is essential for management and development of coastal groundwater resource. Present study has attempted to demarcate probable zones of SGD and SWI along highly populated Odisha coastal plains which is water stressed due to indiscriminate-exploitation of groundwater leading to salinization and fresh groundwater loss from the alluvial aquifers. A multi-proxy investigation approach including decadal groundwater leveldynamics, LANDSAT derived sea surface temperature (SST) anomalies and in-situ physicochemical analysis (pH, EC, TDS, salinity and temperature) of porewater, groundwater and seawater were used to locate the SGD and SWI sites. A total of 340 samples for four seasons (85 samples i.e., 30 porewater, 30 seawater and 25 groundwater in each season) were collected and their in-situ parameters were measured at every 1-2km gap along ~ 145km coastline of central Odisha (excluding the estuarine region). Considering high groundwater EC values (> 3000 μS/cm), three probable SWI and low porewater salinities (< 32 ppt in pre- and < 25 ppt in post-monsoons), four probable SGD zones were identified. The identified zones were validated with observed high positive hydraulic gradient (> 10m) at SGD and negative hydraulic gradient (< 0m) at SWI sites along with anomalous SST (colder in pre- and warmer in post-monsoon) near probable SGD locations. This study is first of its kind along the Odisha coast and may act as initial basis for subsequent investigations on fresh-saline interaction along the coastal plains where environmental integrity supports the livelihood of coastal communities and the ecosystem.

Spatiotemporal recharge estimation in the upper Awash sub-basin, central Ethiopia

ABSTRACT Sustainable groundwater management decisions require an understanding of the spatial distribution and seasonal fluctuations of site-specific water budget computations. This study aims to estimate the spatiotemporal distribution of recharge in the upper Awash sub-basin where the groundwater is experiencing intensive abstraction for domestic, industrial, and irrigation water uses. We estimated the spatial and long-term average monthly, seasonal, and annual groundwater recharge using a GIS-based spatially distributed water balance WetSpass-M model. Distributed grid maps of physical parameters (land-use land cover, soil, and slope) and monthly climatological records (rainfall, maximum and minimum temperature, wind speed) were used as model inputs. The WetSpass-M model estimated recharge is validated with the independently computed recharge using the automated digital filtering baseflow separation method. Attributed mainly to variability in soil texture and land use, the annual precipitation (1,032 mm) is distributed as evapotranspiration (45%), surface runoff (42%), and groundwater recharge (11%). Forest and grass areas with loamy sand have high recharge, while built-up areas with clay soil have low recharge. August to September is estimated to have the largest recharge, while November to December has the lowest. Understanding the spatial and seasonal variability of groundwater recharge is important for sustainable utilization, proper management, and planning of groundwater resources.

Delineation of groundwater potential zones in coastal alluvial region using remote sensing, geographic information system and analytical hierarchy process techniques

Delineation of groundwater potential zone in coastal region is a challenging task. One of the reasons for that is lack of understanding of the geogenic factors in the coastal alluvial areas such as geomorphology, lithology etc. These factors can influence the locations of the groundwater potential zones over the coastal alluvial terrains. The present study is an attempt to analyse the multiple factors to delineate groundwater potential zones in the coastal region of Contai Sub-division, West Bengal, India. In this study, remote sensing, geographic information system (GIS) and multi-criteria decision analysis (MCDA) techniques have been utilized to delineate the groundwater potential zones. Weights were assigned to the parameters using the analytical hierarchical process (AHP) and different classes within each parameter have been ranked on the basis of their relative importance regarding groundwater potentiality. The results of the study were validated by water yield data, water level fluctuation data and geophysical survey. The outcome of validation reveals that a strong correlation (80%) exists between water yield data and groundwater potential zones. Similarly, a good relation occurs for the water level fluctuation data and groundwater potential zones, where the overall accuracy and kappa coefficients are 84.2% and 0.76 respectively. The output of the study reveals that geomorphologically older deltaic plain, older alluvial plain and older coastal plain are good indicators of high groundwater potential regions. Furthermore, the outcome of the study also unveils that lithologically the well sorted medium grained sand is important feature to delineate high groundwater potential regions in coastal alluvial areas. The findings, thus, could establish that present methodology using GIS and AHP techniques has a better potential to identify and map the groundwater potential zones more realistically and can be applied for future planning of groundwater resource management and groundwater exploration in wider coastal alluvial terrain.