Groundwater for Sustainable Development最新文献

{"title":"Experimental and numerical study of cadmium fate and transport mechanisms during artificial recharge in agricultural regions","authors":"","doi":"10.1016/j.gsd.2024.101327","DOIUrl":"10.1016/j.gsd.2024.101327","url":null,"abstract":"<div><p>Agricultural Managed Aquifer Recharge (AgMAR) uses agricultural lands and floodwater to enhance groundwater recharge, but its effectiveness can be hindered by heavy metals like cadmium (Cd), which pose risks to groundwater quality. Cd is particularly concerning due to its high mobility and persistence in the environment. This study investigates Cd's fate and transport in agricultural regions during MAR, focusing on sandy loam soils through batch and column experiments. Equilibrium and kinetic batch studies were conducted under varying Cd concentrations and exposure times to quantify the adsorption capacity and rate. HYDRUS-2D was used to simulate Cd's transport in soil under various ponding depths and Cd concentrations. Results showed a maximum Cd adsorption capacity of 439.58 mg/kg, with the Freundlich isotherm providing a better fit (R² = 0.98) and indicating heterogeneous adsorption sites (<em>n</em> = 0.389). The kinetic experiment indicated chemisorption as the predominant mechanism, with an equilibrium adsorption capacity of 236.49 mg/kg. The pseudo-second-order kinetic model (rate constant 0.0016 h⁻¹, R² = 0.99) suggested that adsorption kinetics are influenced by Cd concentration and available adsorption sites. The column experimental findings supported by HYDRUS-2D modeling successfully explained the fate and transport of Cd within the soil columns. The model fitted parameter values for Freundlich adsorption isotherm coefficient (KF), linearity factor (Nu), and kinetic rate coefficient are (α) 47.37 L/kg, 0.00389 cm³/ppm and 0.0029 min⁻¹, respectively. Modeling scenarios further elucidated the transport dynamics of Cd under simulated AgMAR conditions. Modeling scenarios indicated that with constant ponding of 5 cm over a year, Cd at 20 and 40 ppb concentrations in floodwater could potentially migrate below root zone systems. This study highlights the critical role of understanding Cd fate and transport in optimizing AgMAR systems and reducing Cd pollution risks, providing valuable insights for developing effective monitoring and management strategies.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142168320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating seasonal variability of hydrogeochemistry, qualitative and corrosion-scaling effects of groundwater in southern region of NCT of Delhi, India","authors":"","doi":"10.1016/j.gsd.2024.101331","DOIUrl":"10.1016/j.gsd.2024.101331","url":null,"abstract":"<div><p>Groundwater is the most relied source of freshwater in the unplanned areas of southern region of NCT of Delhi. The present study envisions to evaluate the seasonal variability of the hydrogeochemical and qualitative nature of the groundwater, where its suitability was further checked through groundwater quality index (GWQI) and water stability indices for corrosion-scaling effects. About 12 physiochemical parameters were analysed with a total number of 102 samples in pre-monsoon (PRM) and post-monsoon (POM) seasons. Spatially, higher ranges of the quality parameters viz., EC, TDS, HCO₃⁻, Cl⁻, NO₃⁻, F⁻, Ca²⁺, and Mg²⁺ were observed in both the seasons particularly in north, northeastern, and southeastern parts and has nearest dumping or industrial units such as printing, trade and textile effluent, food, and fruit processing industry etc. The hydrogeochemical characteristics of the groundwater showed that regulating processes is predominant by carbonate weathering process followed by silicate weathering under alluvial plains of the study area. Strong correlations and positive loadings (&gt;0.8) among EC, TDS, HCO₃⁻, Cl⁻, Na⁺, and moderate loadings of F⁻, potassium (K⁺) and Mg²⁺ were attributed to mixed pollution factors released from geogenic and anthropogenic inputs. GWQI based classification showed that more than 50% of the sampling sites showed poor to unsuitable groundwater quality at sites like Malviya Nagar, Okhla, Jasola, Shaheen Bagh, Badarpur and Greater Kailash for potability. The entire area is prone to groundwater contamination, particularly northeastern, and southeastern region, falls under Yamuna flood and alluvial plains with shallower groundwater table. Water stability indices (LSI, RSI, PSI, LS, and AI) based corrosion-scaling effects have revealed that groundwater samples in PRM showed low to insignificant scaling and corrosive potential compared to POM season. Therefore, the findings of the study highlight the key areas that needs to formulate the strategies to sustain the quality of groundwater within the region.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352801X24002546/pdfft?md5=0d761d502ac5cb3c9b78a32b54df4ab9&pid=1-s2.0-S2352801X24002546-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142162938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of machine learning and fuzzy AHP for identification of suitable groundwater potential zones using field based hydrogeophysical and soil hydraulic factors in a complex hydrogeological terrain","authors":"","doi":"10.1016/j.gsd.2024.101329","DOIUrl":"10.1016/j.gsd.2024.101329","url":null,"abstract":"<div><p>The eastern section of West Bengal grapples with limited surface water availability in its hard rock terrain, compounded by a semi-arid climate, variable rainfall, and a plateau topography, prompting communities to adapt groundwater water-use practices, leading to unsustainable extraction and misuse. Thus, the novel objective of the present research was to produce groundwater potential maps by comparing machine learning techniques with a Fuzzy MCDM model using specific field-based conditioning factors. In the first step, 285 wells were identified, of which 70 percent were used for training and 30 percent for the validation of the models. Secondly, field-based conditioning factors including, longitudinal conductance (SC), longitudinal resistance (ρl), transverse resistance (TR), coefficient of electrical anisotropy (λ), resistivity of formation (ρm), fracture porosity (φf), reflection coefficients (r), hydraulic conductivity (K), transmissivity(T<em>r</em>), bulk density, porosity, permeability, soil moisture content and water holding capacity were used to analyze the association between these conditioning factors and groundwater occurrences. In the following steps, the XGBoost, Random Forest, and Naïve Bayes models were executed using the training dataset, and factor weights were calculated using Fuzzy Analytical Hierarchy Process of Extent analysis method. To validate and compare the performance of four models, ROC curves, AUCs, MCAs, and correlation plots were used. In general, all four models were successful in evaluating the potential of groundwater occurrences. The predictive capability of the XGBoost techniques with the highest AUC values (0.79) and the highest correlation value (0.78) is superior to those of other machine learning and MCDM models. Geophysical survey revealed that transmissivity and hydraulic conductivity of the aquifer of the river basin range from 1.55 to 440.11 m/day and 10.15–2253 m²/day, indicating a moderate to good hydrodynamic potential. Planners and engineers can use such groundwater potential maps to manage water resources effectively.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142168417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating GEE and IWQI for sustainable irrigation: A geospatial water quality assessment","authors":"","doi":"10.1016/j.gsd.2024.101332","DOIUrl":"10.1016/j.gsd.2024.101332","url":null,"abstract":"<div><p>The surface and sub-surface water quality is one of the decisive parameters for sustainable agriculture and water resources management. Deteriorating water quality impacts the irrigation, crop production, and human health. Therefore, the present work made an attempt to identify the water suitability for irrigation using the contemporary approach i.e. Irrigation Water Quality Index (IWQI) and Zone mapping using GIS techniques, and demonstrated for case of Wadhwan, Gujarat India. Three indices i.e., NDVI, NDWI, and LSWI were mapped using Landsat satellite imagery, whereas, Watermask index was mapped using Sentinel II satellite imagery for the assessment of the availability of water in different forms. The IWQI has applied to categorize the water quality as severe, high, moderate, low, and no restriction. The IWQI in the study area ranges from 6.4 to 62.5. The overall the water quality of study area shows that the 13.64 % of the region in severe restriction range, 56.82% in high restriction range, and 29.54% in moderate restriction range, which is in alarming for farmers and policy makers. The GIS zoning map effectively visualized the spatial distribution of IWQI, helping decision-makers to identify severity zones. Furthermore, the Piper diagram analysis has been performed, which shows that the water quality of the study area falls under mixed Ca²⁺-Mg²⁺-Cl^-, mixed Ca²⁺-Na⁺-HCO₃^-, and Na-HCO₃ types. The results revealed that major areas are in moderate to severe restriction zones, lying under deteriorated water quality, and need immediate attention for improvement before use. The IWQI advances SDG 2 (Zero Hunger) by optimizing water quality for crop production and SDG 6 (Clean Water and Sanitation) by ensuring sustainable water resource management, while indirectly supporting SDG 15 (Life on Land) through improved soil health and land management practices.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of groundwater potential zones for sustainable groundwater resource management using an integrated approach in Sirkole watershed, Western Ethiopia","authors":"","doi":"10.1016/j.gsd.2024.101328","DOIUrl":"10.1016/j.gsd.2024.101328","url":null,"abstract":"<div><p>The increasing population in the Sirkole watershed has led to a higher demand for groundwater resources essential for socio-economic development. To ensure sustainable groundwater management, accurate quantitative assessments are necessary, which can be achieved by utilizing scientific principles and modern techniques. This article discusses the use of RS and GIS techniques to evaluate Groundwater Potential Zones in a section of the Sirkole watershed in Western Ethiopia. The study analyzed various spatial data layers involving drainage density, land use, lineaments, slope, lithology, rainfall, geomorphology, and soil type to understand the factors influencing groundwater occurrence and movement. The eight thematic layers were weighted according to their significance. Additionally, a hierarchical ranking was performed using a pairwise comparison matrix (PCM) within the analytic hierarchy process (AHP) to determine the final normalized weights of these layers. Lineaments were extracted using PCI Geomatica and Rockwork software, and their orientations were determined. The sub-basin was divided into five zones based on the resulting GWPZ map: very high, high, moderate, low, and very low. The watershed was divided into two categories: high to very high potential for 22.8% of the area and very low to low potential for 45.4% of it. Validation against existing pumping wells showed a prediction accuracy of 75.9%, affirming the reliability of the GIS and RS techniques have been utilized for the identification of potential zones in the research area. The findings of this study can be utilized for the sustainable development of groundwater resources by pinpointing areas with high groundwater potential.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nanotechnology advancements in groundwater remediation: A comprehensive analysis of current research and future prospects","authors":"","doi":"10.1016/j.gsd.2024.101330","DOIUrl":"10.1016/j.gsd.2024.101330","url":null,"abstract":"<div><p>Groundwater contamination is a critical environmental issue with vital health implications. This review evaluates the advancements in nanotechnology for groundwater remediation, highlighting major findings and their relevance to Sustainable Development Goals (SDGs). Key findings include the superior adsorption capabilities of multi-walled carbon nanotubes functionalized with various groups for removing heavy metals and aromatic pollutants, outperforming traditional sorbents. The review also discusses the potential of nanomaterials like zero-valent iron nanoparticles for effective contaminant degradation. Despite promising results in the studies, challenges such as the movement and dispersion of engineered nanomaterials in porous media and the need for innovative delivery methods are identified. Furthermore, this review explores the environmental and health risks associated with the use of nanomaterials, emphasizing the need for risk assessments to ensure safe application. The novel delivery methods assessed, such as the use of groundwater circulation wells and the combination of nanoremediation with other techniques like bioremediation, demonstrate potential to enhance remediation efficiency. The integration of nanotechnology in groundwater remediation directly contributes to Clean Water and Sanitation by providing innovative solutions for the purification of water resources. Advanced nanomaterials not only improve contaminant removal efficiency but also promote sustainable water management practices. Additionally, the environmental benefits align with Life on Land, as the reduction of hazardous substances in groundwater protects terrestrial ecosystems and promotes biodiversity conservation. This review study aims to enhance understanding and identify future opportunities for nanotechnology in groundwater remediation. By addressing current challenges and proposing innovative solutions, this review underscores the importance of interdisciplinary research and collaboration in advancing sustainable development.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142168319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatio-temporal analysis of hydrometeorological variables for terrestrial and groundwater storage assessment","authors":"","doi":"10.1016/j.gsd.2024.101333","DOIUrl":"10.1016/j.gsd.2024.101333","url":null,"abstract":"<div><p>Groundwater is a vital resource supporting various sectors such as agriculture, industry, and drinking water supplies. Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) can accurately assess variations in terrestrial water storage (TWS) at a regional scale, exhibiting precise measurements of spatio-temporal variations. This study aims to integrate GRACE/GRACE-FO and hydrometeorological variables to understand groundwater storage trends in Pakistan from 2002 to 2023. Precipitation, soil moisture, temperature, potential evapotranspiration, snow water equivalent, and Normalized Difference Vegetation Index (NDVI) are examined to understand the fluctuations in groundwater storage (GWS). Google Earth Engine (GEE) has been used for data collection and pixel-based Sen's slope analysis. The analysis revealed a consistent decline in terrestrial and groundwater storage in Pakistan over the study period. The soil moisture levels and snow water equivalent have decreased, while the levels of NDVI and precipitation have increased. Between 2002 and 2010, the study area experienced variations in TWS, while after 2012, the region faced severe water scarcity as the TWS decreased to 36 cm over the past 22 years. Trend analysis indicates a significant decline in groundwater storage (GWS) in Punjab province's highly urbanized and irrigated areas, averaging −1.41 cm per year. In contrast, the northern and coastal regions of the study area are experiencing an upward trend in GWS. Additionally, ground validation has been performed, yielding an R² value of 0.31. These findings emphasize the urgent need for effective urbanization policies and informed groundwater management. Implementing water conservation strategies in agriculture is essential to tackle water scarcity throughout Pakistan.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the adsorption of catechol and resorcinol onto Croton caudatus activated carbon: An integrated experimental and theoretical approach","authors":"","doi":"10.1016/j.gsd.2024.101325","DOIUrl":"10.1016/j.gsd.2024.101325","url":null,"abstract":"<div><p>The present work aimed to examine the process for adsorption of Catechol (CT) and Resorcinol (RS) onto activated carbon that was obtained from <em>Croton caudatus</em> biomass (CAB). Using a batch method, the maximum removal efficiencies of 99.23 % for CT and 98.68 % for RS was achieved at adsorbent dosage-0.2 g L⁻¹, reaction time-60 min; concentration-100 mgL⁻¹ CT and 80 mgL⁻¹ RS; and pH 6.0 CT and pH 4.0 RS, respectively. A maximum equilibrium adsorption of 56.05 mgg⁻¹ and 61.85 mgg⁻¹ was achieved at pH 6.0 and pH 4.0 for CT and RS. The adsorption behavior of both adsorbates on activated carbon were best described by the Langmuir model (correlation coefficients (R²) = 0.996 for CT and 0.995 for RS) and the pseudo-second order kinetic model. The values of ΔG, ΔS, and ΔH suggest that the adsorption process is spontaneous and endothermic. Additionally, the adsorption process is easily reversible, enabling the reuse of the adsorbate even after fifth cycle. Further, density functional theory (DFT) simulations demonstrated that the CT and RS adsorption onto the AC adsorbent is favorable. Among the oxygen functional groups analysed, the carboxyl group showed the greatest effect on the adsorption process, exhibiting the most negative adsorption energy at −44.869 (CT) and −45.082 kJmol^-1 (RS), respectively. Therefore, the activated carbon derived from CAB has significant potential for effectively removing phenolic contaminants from wastewater.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142122631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Protection of groundwater resources from multi-hazards: An integration of risk assessment and watershed management","authors":"","doi":"10.1016/j.gsd.2024.101326","DOIUrl":"10.1016/j.gsd.2024.101326","url":null,"abstract":"<div><p>Mining areas are abundant in this basin and were allocated high values of <em>H</em> and low to high values of <em>V</em>, requesting implementation of groundwater monitoring and periodic inspection of mining sites, even more because groundwater contamination with iron could be clearly associated with the presence of mine-tailings. The improving groundwater resource protection depends on aligning contamination risk mapping with aquifer protection measures. However, existing methods often fail to align with aquifer protection goals, hindering practical implementation. The study demonstrated integrating vulnerability assessment, hazard evaluation, and groundwater protection initiatives using an L-Matrix approach. Testing this model in a well-documented watershed with multiple hazards to illustrates its applicability, providing a reference for similar scenarios. The risk was assessed through evaluation of aquifer vulnerability, using the DRASTIC method, coupled with the evaluation of a hazard potential considering industrial, livestock/agriculture and urban infrastructure sources in separate. The L-Matrix diagrams consisted of cartesian representations of V versus H, ranging from 0 to 1, segmented into four quadrants bounded by the cut-off lines V = 0.5 and H = 0.5. The quadrants were then linked to aquifer protection measures, with site inspection (high V and H), groundwater monitoring (low V and high H), land use planning (high V and low H), and tolerable expansion of hazardous activities (low V and H). The Paraopeba River basin was used as test site. Mining areas are abundant in this basin and were allocated high values of <em>H</em> and low to high values of <em>V</em>, requesting implementation of groundwater monitoring and periodic inspection of mining sites, even more because groundwater contamination with iron could be clearly associated with the presence of mine-tailings. In the results, it was observed that the DRASTIC vulnerability map of the aquifers has a mean vulnerability around the central value (V = 0.48 ± 0.08). Regarding the distribution of hazards, the average rounds to the value for to (H_industry = 0.41 ± 0.37, H_agriculture = 0.33 ± 0.09 and H_{infrastructure} = 0.27 ± 0.14). Thus, it is noted that for industrial activities, the risk of contamination could be moderate to high, while for agricultural and livestock activities, the risk lies between low and moderate contamination impact.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352801X24002492/pdfft?md5=71d259e68c918eefb47589891de5cd3b&pid=1-s2.0-S2352801X24002492-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A generalized machine learning approach for cost-effective monitoring of irrigation suitability: A demonstration case in El Fahs aquifer (Tunisia)","authors":"","doi":"10.1016/j.gsd.2024.101324","DOIUrl":"10.1016/j.gsd.2024.101324","url":null,"abstract":"<div><p>This study develops and evaluates the performance of machine learning (ML) regression models, namely the Support Vector Regression (SVR), Random Forest (RF), k-Nearest Neighbors (kNN) and eXtreme Gradient Boosting (XgBoost), for estimating the Irrigation Water Quality Index (IWQI) based on groundwater samples collected from El Fahs aquifer in Tunisia. The groundwater data are used as predictors for training and testing the machine learning models. Results indicate that sodium concentration has the most influence on the IWQI estimations for all ML models. The best-performing algorithms are found to be the SVR and XgBoost. Different datasets are also collected from existing studies, and merged to generate a single dataset that is used to develop generalized machine learning models. Despite regional variations, the generalized models performed adequately when tested against the unseen data, particularly the data collected from El Fahs case site. This work highlights the potential of using ML models, together with established metrics, as screening tools for predicting and classifying the irrigation suitability of groundwater based on available literature, even when metrics are not universally applicable. The findings of this study can be used by the water authorities in data scarce environments as cost-effective monitoring tools to assess water suitability for irrigation purposes.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352801X24002479/pdfft?md5=f607bd0aa02da4ea05e044ade4f0ce94&pid=1-s2.0-S2352801X24002479-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}