Prediction of contamination potential of groundwater. Descriptive statistics helped to .
Prediction of contamination potential of groundwater. The detection of As Gwangju Institute of Science and Technology - Cited by 3,819 - arsenic - risk assessment Apr 10, 2025 · Groundwater also exfiltrates into rivers and lakes, meaning that groundwater contamination may also lead to eutrophication of surface waters. Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network(Q44421378) Jun 10, 2019 · The potential nitrate concentrations in seepage water and groundwater recharge are determined by a simple land use differentiated division of the N surplus (Bach et al. This study proposes an interpretable stacking ensemble learning (SEL) framework for enhancing and interpreting groundwater nitrate spatial predictions by integrating the two-level heterogeneous SEL model and SHapley Additive exPlanations (SHAP). 4 e As concentration versus redox potential, showing Groups A and B. -W. However, traditional methods oft… Oct 23, 2023 · This study makes a significant contribution to the field of groundwater potential mapping (GWPM) by exploring the application of ensemble learning models (ELMs), specifically boosting ensemble mode Aug 1, 2021 · The day-to-day demand for groundwater is increasing in the aforementioned fields, which is exhausting the known natural aquifers (Adeyeye et al. Therefore, modeling approaches for As concentration using conventional on-site measurement data can be an alternative to quantify the As contamination. This study aims to compare three machine Feb 16, 2024 · This research aims to evaluate various traditional or deep machine learning algorithms for the prediction of groundwater level (GWL) using three key input variables specific to Izeh City in the Khuzestan province of Iran: groundwater extraction rate (E), rainfall rate (R), and river flow rate (P Dec 3, 2021 · Here we outline a vision for a global groundwater platform for groundwater monitoring and prediction and identify the key technological and data challenges that are currently limiting progress. The results indicate that the PC-ANN model outperforms the others Aug 27, 2011 · Request PDF | Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network | The arsenic (As) contamination of groundwater has Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network. K. Dec 2, 2024 · In this study, in order to evaluate the groundwater vulnerability of Kerman–Baghin plain aquifer, two developed indicators including composite DRASTIC index (CD) and nitrate vulnerability index Nov 1, 2011 · The arsenic (As) contamination of groundwater has increasingly been recognized as a major global issue of concern. Groundwater is a complex and fuzzy system with many uncertainties, which is impacted by different geological and hydrological factors. Advanced AI models can yield improved predictions of groundwater behavior, identify vulnerable areas prone to pollution and depletion, prompt proactive interventions, and foster collaborative platforms among scientists, policymakers, and local communities. Machine-learning tools have the potential to improve groundwater prediction, thus enabling resource planners to: (1) anticipate water quality in unsampled areas or depth zones; (2) design targeted monitoring programs; (3) inform groundwater protection strategies; and (4) evaluate the sustainability Fig. Dec 1, 2015 · Assessment and prediction of potential contamination of groundwater in exploration and production of oil and gas Nikolai Stoyanov, Petar Gerginov, Aleksei Benderev, Klara Boyadjieva, Vladimir Hristov, Aug 1, 2025 · We summarize research on automating data processing and model training using groundwater sensor data. The expense associated with Jan 13, 2023 · Can we hope for autonomous (self-contained in situ) sensing of subsurface soil and groundwater pollutants to satisfy relevant regulatory criteria? Global advances in sensors, communications, digital technologies, and computational capacity offer this potential. Apr 13, 2021 · Groundwater contamination is a global public health challenge, and the prediction of groundwater contaminant presence would help in creating proactive mitigation policies (Burri et al. Thus, there is an urgent need for effective and consistent monitoring and prediction of surface and groundwater quality. In this study, based on 156 groundwater samples collected in 2021 in the study area were analyzed for hydrochemical characterization and controlling factors. Nov 1, 2024 · Groundwater is a crucial water supply source in Chengdu City, western China, a region experiencing significant water scarcity. Sthiannopkao, Y. It reveals that a Feb 22, 2024 · Advanced AI models can yield improved predictions of groundwater behavior, identify vulnerable areas prone to pollution and depletion, prompt proactive interventions, and foster collaborative Jul 1, 2024 · Subsequently, groundwater health risk zones were delineated based on an optimal prediction model, and demographic analysis was conducted in both the direct and potential groundwater risk zones. In the last two decades, the application of machine learning (ML) techniques for groundwater quality (GWQ) modeling has grown exponentially. Since the need to protect ground water from pollution was recognized, researchers have made progress in understanding the vulnerability of ground water to contamination. Oct 16, 2024 · The main objective of this study is to map and evaluate groundwater potential zones (GWPZs) using advanced ensemble machine learning (ML) models, notably Random Forest (RF) and Support Vector Machine (SVM). The data come from a range of well types, including those for observation, domestic tap water, and public water supply. Abstract Groundwater contamination is a serious threat to water supply. compiled a large database of US groundwater observations as the basis for a model to estimate the probability of PFAS contamination based on well depth. In this context, groundwater samples were taken from 26 sampling points during the irrigation season and heavy metal parameters such as Ag, Al, B, Ba Mar 28, 2023 · Accurately identifying groundwater contamination sites is vital for groundwater protection and restoration. In the current study, groundwater quality was thoroughly appraised using various indexing methods, including the drinking water quality index (DWQI), pollution index of heavy metals (HPI), pollution index (PI), metal index (MI), degree of contamination (Cd), and risk indicators, like Related References Kördel, W. Dec 24, 2024 · The precise prediction of groundwater levels is a challenging task due to the complex relationships between hydrological parameters and the lack of in situ climate data. The prediction of water quality with high accuracy is the key to control water pollution and the improvement of water management. This study aims to develop and evaluate a novel ensemble framework that integrates multiple machine learning (ML) models, including support vector regression (SVR), adaptive neuro-fuzzy inference systems (ANFIS), and long Aug 24, 2024 · Under these circumstances, the precise spatial mapping and prediction of GWQ is essential for identifying pollution sources and informing comprehensive water management strategies for sustainable groundwater management. Pachepsky, K. Dec 23, 2024 · The 2030 projection indicates a minimal change in the vulnerability distribution but anticipates an increase in high- and very-high-vulnerability areas, particularly in regions with land use changes, potentially increasing the groundwater contamination risk. , 2021). Feb 27, 2019 · Unless we drill a well, how can we know the quality of the groundwater below? Learn about how the USGS is using sophisticated techniques to predict groundwater quality and view national maps of groundwater quality. In Pakistan, it is a major freshwater source, especially in arid and semi - arid areas. Firstly, six classical ML algorithms, including logistic regression, decision tree Nov 1, 2024 · Abstract Machine learning (ML) is revolutionizing groundwater quality research by enhancing predictive accuracy and management strategies for contamination. For example, leaching potential index [groundwater ubiquity score (GUS)] [4] is calculated using the below formula: Assessing and predicting quality of groundwater is crucial in managing groundwater availability effectively. The risks of heavy metal pollution in groundwater and the degrees and potential ecological risks of heavy metal pollution in sediments were assessed. It evaluates the predictive performance of four models: multiple linear regression (MLR), principal component regression (PCR), artificial neural network (ANN), and a hybrid approach (PC-ANN). For example, both water and certain contaminants flow in the direction of the topogra-phy from recharge areas to discharge areas. However, groundwater is a natural resource that must accumulate over many years and cannot be recovered after a short Jul 11, 2024 · Prediction of fluoride in groundwater using supervised machine learning algorithms is explored in Indian states. Feb 7, 2025 · Accurate prediction of groundwater levels (GWL) is crucial for effective resource management and addressing challenges such as water scarcity and aquifer sustainability. The main health concern regarding nitrate in drinking water for many years has been methemoglobinemia, also known as blue baby disease (Ward et al. Interpretive Summary: Arsenic (As) contamination of groundwater has increasingly been recognized as a major global issue of concern. As groundwater resources are one of… Nov 1, 2011 · The arsenic (As) contamination of groundwater has increasingly been recognized as a major global issue of concern. Typically, an insufficient supply of surface water resources for domestic, industrial, and agricultural needs is supplemented with groundwater resources. Aug 28, 2024 · This approach marks the first application of a non-parametric kernel for groundwater quality pollution index prediction in Saudi Arabia, offering a significant advancement in the field. This paper aims to investigate the heavy metal pollution in groundwater and the sediments, and the spatial distribution characterization of the heavy metals in water system. This paper presents a machine learning-based approach to improve groundwater monitoring networks by providing predictions of groundwater contamination in space. However, with economic growth, groundwater quality has started to deteriorate, posing a threat to human health, especially in emerging economies [5]. As groundwater resources are one of… Aug 1, 2021 · To ensure safe drinking water sources in the future, it is imperative to understand the quality and pollution level of existing groundwater. ; Klein, M. This study focuses on only naturally occurring fluoride, i. Dec 27, 2023 · Groundwater is crucial for drinking, agriculture, and industry in many countries. Aug 27, 2011 · The arsenic (As) contamination of groundwater has increasingly been recognized as a major global issue of concern. However, the migration of pollutants into groundwater is a comple Decision makers in groundwater development and management will benefit from the resulting groundwater potential map to find acceptable areas for water resource exploitation. Jan 1, 2023 · A natural extension of rural environmental monitoring is the prediction of groundwater and drinking water contamination in rural areas that may otherwise be excluded or underrepresented in direct sampling campaigns. Jan 1, 2002 · Prediction of potential groundwater contamination by herbicides: integrated use of a leaching model and GIS in the north of Italy Oct 15, 2024 · National assessments of groundwater contamination risks are crucial for sustaining high-quality groundwater supplies. May 5, 2022 · Groundwater is a crucial resource across agricultural, civil, and industrial sectors. The prediction of groundwater pollution due to various chemical components is vital for planning, policymaking, and management of groundwater resources. The original DRASTIC model (ODM) is one of the most widely used and accepted approaches to vulnerability analysis. Machine learning methods are increasingly used in water studies. In the current study, groundwater quality was thoroughly appraised using various indexing methods, including the drinking water quality Mar 29, 2018 · Prediction Modeling and Mapping of Groundwater Fluoride Contamination throughout India Joel ,† ,∇ , E. Dec 1, 2015 · The territory of Northern Bulgaria is an object for searching oil and natural gas. Oct 8, 2024 · Contamination Prevention: Predicting and mitigating the risk of groundwater contamination from mining chemicals, tailings, and waste materials. " by K. Jan 1, 2016 · Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network Water Res. In order to deal with the uncertainty in the risk assessment of groundwater Mar 26, 2024 · Groundwater contamination have been widely concerned. Oct 24, 2024 · Tokranov et al. The present research proposed an integrated machine learning model for groundwater level prediction based on long short-term memory (LSTM) along with principal component analysis (PCA) and discrete wavelength transform (DWT However, groundwater contamination is differs from surface water contamination in that it is unseen, and recovery of the resource is difficult and expensive at the current technological level [16]. In the SEL model, five commonly used Aug 1, 2023 · Full profile contamination process simulation and risk prediction of synthetic musk from reclaimed water receiving river to groundwater via vadose zone: A case study of Chaobai River May 1, 2024 · Therefore, sulfate pollution has gradually become a global problem that requires further attention. The use of ML in delineating these contaminants is vital in enhancing the resilience of groundwater resources and safeguarding human health [4]. Semantic Scholar extracted view of "Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network. As groundwater resources are one of most important freshwater sources for water supplies in Southeast Asian countries, it is important to investigate the spatial distribution of As contamination and evaluate the health risk of As for these countries. The prediction of migration opportunities in groundwater of pesticides in dif-ferent soil and climatic conditions could be carried out by a number of indices. ; Riparbelli, C. Groundwater contamination vulnerability mapping uses hydrogeologic conditions to predict vulnerable areas. Aug 30, 2023 · The development of civilization and the preservation of environmental ecosystems are strongly dependent on water resources. This review Jan 24, 2019 · 2. A new and upcoming technique for groundwater prediction is the use of machine learning techniques. Aug 22, 2025 · Researchers have made substantial progress in understanding pollution mechanisms, developing simulation and prediction methods, and advancing related technologies. This comprehensive review explores the evolution of ML technologies and their integration into environmental science, assessing 230 papers to understand the advancements and challenges in groundwater quality research. S. Jan 1, 2023 · The prediction showed that by 2042, the eastern region of Kiambu County will have a decline in groundwater potential. 2019; Singh 2018). 45 (17):5535-5544. , 45 (17) (2011), pp. Consequently, there Apr 1, 2014 · The potential of RF for generating a vulnerability map to nitrate pollution is assessed considering multiple criteria related to variations in the algorithm parameters and the accuracy of the maps. Kim, “Prediction of Contamination Potential of Groundwater Arsenic in Cambodia, Laos, and Thailand The detection of As contamination in groundwater resources, however, can create a substantial labor and cost burden for Southeast Asian countries. Identifying the risks to groundwater quality in this regard is a very engaging process that needs to consider the source and nature of groundwater contamination from the perspective of In the future, AI holds significant promise in groundwater management. Jan 20, 2025 · The diffusion of heavy metal pollutants in polluted industrial areas can cause severe environmental pollution in surrounding areas. This review Nov 17, 2020 · Predicting groundwater availability is important to water sustainability and drought mitigation. Electrical resistivity tomography (ERT) has become a powerful tool because of its high sensitivity to hydrochemical parameters, as well as its advantages of non-invasiveness, spatial continuity, and cost Mar 19, 2025 · Towards a better groundwater management, developing a prediction model for groundwater quality is of utmost importance. The method is demonstrated through a practical application in Central Spain, where nitrate was used as a proxy for groundwater Aug 1, 2021 · Thus, groundwater quality assessment and monitoring are highly necessary concerning the potential risk of groundwater contamination and its effects on suitability for human consumption. While the rapid depletion is attributed to pervasive groundwater abstraction for agriculture, industrial, and domestic use, contamination from various Nov 7, 2024 · Effective monitoring of groundwater contamination is crucial to protect human livelihoods and ecosystems. May 29, 2025 · Abstract and Figures Accurate prediction of groundwater nitrate concentrations is important for safe drinking of groundwater in the future and effective safeguarding of regional water resources. Any global platform of this type must be interdisciplinary and cannot be achieved by the groundwater modeling community in isolation. However, arsenic contamination in groundwater is a significant problem, threatening water quality and human health. H. Podgorski,* Pawan Labhasetwar,‡ Dipankar Saha,§ and Michael Berg † May 1, 2024 · Therefore, sulfate pollution has gradually become a global problem that requires further attention. Over the past two decades, significant progress has been made in GWL prediction using machine learning (ML) models. It is of great significance to understand how groundwater chemistry evolves, to predict the risks of the elevated sulfate levels in groundwater, and to implement early warnings for sulfate pollution in groundwater as well. Due to human and natural activities, chemicals and pollutants may be found in groundwater. Current statistical methods have several drawbacks. Descriptive statistics helped to Aug 14, 2024 · Geogenic arsenic (As) contamination in groundwater is a pressing global environmental health issue, particularly affecting south and southeast Asian countries [1, 2, 3]. Long-term Sustainability: Assessing how mining might alter groundwater systems over time, including potential impacts on nearby communities, agriculture, or natural habitats. This is combined with Jan 1, 2022 · The evaluation of aquifer vulnerability or potential pollution is a crucial procedure in groundwater resource management to protect groundwater against pollution (Busico et al. Feb 1, 2023 · Investigating the potential of groundwater pollution vulnerability is an effective approach to protect groundwater resources (Zhang et al. The conventional method of measuring groundwater quality data often associated with errors due to the lengthy duration of investigation of the parameters as well as the tremendous effort and time involved in gathering and analysing the samples. To reliably conduct risk assessment, it is essential to accurately delineate the contaminant distribution and hydrogeological condition. The prediction showed that by 2042, the eastern region of Kiambu County will have a decline in groundwater potential. Kim and J. Vulnerability assessment methods use statistical, numerical-based, or overlay index techniques (Goyal et al. For example, leaching potential index [groundwater ubiquity score (GUS)] [4] is calculated Nov 3, 2022 · The accurate evaluation of groundwater contamination vulnerability is essential for the management and prevention of groundwater contamination in the watershed. In this study, 131 groundwater samples were collected, and three machine learning models [Random Forest (RF), Logistic Regression (LR), and Artificial Neural Network (ANN)] were employed to predict As concentration. As groundwater resources are one of most important freshwater sources for water supplies in Southeast Asian countries, it is important to investigate the spatial distribution of As cont … Nov 1, 2011 · The arsenic (As) contamination of groundwater has increasingly been recognized as a major global issue of concern. 2006: Prediction of leaching and groundwater contamination by pesticidesPure and Applied Chemistry 78 (5): 1081-1090 Bonomi, T. Sep 18, 2024 · Groundwater vulnerability to geogenic groundwater contamination underlies the complex interplay between various intrinsic geological, hydrogeological, and geochemical characteristics in an aquifer system. The performance of the RF is also evaluated in comparison to the logistic regression (LR) method using different efficiency measures to ensure their generalization ability. The percolation of nitrate depends on several hydrogeological conditions of the valley. Yet, there are substantial uncertainties in the vulnerability assessment methods now available. Oct 29, 2024 · Groundwater nitrate contamination poses a potential threat to human health and environmental safety globally. It is possible to predict, to some degree, the transport within an aquifer of those substances that move along with ground water flow. Groundwater level prediction involves estimating future water table or potentiometric surface elevations based on historical data, climatic inputs, hydrogeological characteristics, and anthropogenic factors. A. Prediction of the risk of ground and surface water contamination with pesticides and its danger to human health in areas with irrigation farming The prediction of migration opportunities in groundwater of pesticides in different soil and climatic conditions could be carried out by a number of indices. As groundwater resources are one of most important freshwater sources for water supplies in Southeast Asian countries, it is important to investigate the spatial distribution of As Jun 1, 2024 · The occurrence of contaminants like arsenic (As), fluoride (F), nitrate (NO3), and salinity in global groundwater poses an alarming risk to human health [1∗∗,2, 3]. Therefore, groundwater potential (GWP) mapping may be critical in the creation of water-basin management plans. " Jun 17, 2015 · Groundwater contamination with arsenic (As) is one of the major issues in the world, especially for Southeast Asian (SEA) countries where groundwater is the major drinking water source, especially The arsenic (As) contamination of groundwater has increasingly been recognized as a major global issue of concern. G. The sources of inorganic pollutants in groundwater and their potential health risks are of great concern. The Risk assessment of groundwater contamination is determined by the following three factors: (1) the reasonable data used to reflect the vulnerability and contamination of groundwater, (2) hazard identification and transport prediction of contami-nants, (3) credible suggestions and measures for environ-mental protection and prevention (Calò and Feb 15, 2021 · A survey based on geo-referenced spontaneous potential measurements was combined with measurements of anoxic conditions (Eh-pH and O 2 equilibrating partial pressure) in the groundwater and leachates, in order to highlight a pollution plume and its geometry. Nov 12, 2024 · Groundwater, a finite and vital resource, is pivotal in our daily lives. , geogenic sources of fluoride contamination in groundwater. The random forest . Unfortunately, quantification of groundwater As contamination is another burden for those countries because it requires sophisticated equipment, expensive analysis, and well-trained Mar 3, 2025 · These findings underscore the potential health risks associated with groundwater consumption in this area and provide a foundation for informed policy decisions to mitigate these risks. Oct 1, 2023 · Therefore, the development of a numerical model for pollutant transport in the coupled unsaturated–saturated (variable-saturated) zones of soil-groundwater system in polluted industrial sites is significant for better prediction of pollution risk trends, effective protection of regional ecologies and safer utilization of resources. ML models can handle large datasets with rapid and accurate predictions that can Apr 15, 2023 · Groundwater is a crucial resource across agricultural, civil, and industrial sectors. Sep 15, 2024 · Assessing and predicting quality of groundwater is crucial in managing groundwater availability effectively. Several review articles have been published, reporting the advances in this field up to 2018. ; Clerici, E. 1995 Aug 24, 2024 · Comprehensive evaluation and prediction of groundwater quality and risk indices using quantitative approaches, multivariate analysis, and machine learning models: An exploratory study Apr 15, 2023 · The prediction of groundwater pollution due to various chemical components is vital for planning, policymaking, and management of groundwater resources. Aug 22, 2025 · Then this study summarizes the research status of soil–groundwater pollution simulation and prediction at the level of multi-scale numerical simulation and the pollutant transport mechanism. Water Research. The results showed areas in the Southwest region had low to very low potential and the central region had high to very high potential for all the years and there were little changes between the years. However, the existing review Jan 9, 2025 · Groundwater arsenic (As), contamination is a significant issue worldwide including China and Pakistan, particularly in canal command areas. - "Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network. Prediction results show Jan 1, 2021 · The rapid groundwater depletion and the deterioration in groundwater quality in the major aquifers around the globe due to anthropogenic stress and natural causes have raised serious concerns over the usable groundwater resources worldwide. Cho et al. , 2018). Risk assessment of groundwater contamination is an effective way to protect the safety of groundwater resource. GWPZs are identified by considering essential factors such as geology, drainage density, slope, land use/land cover (LULC), rainfall, soil, and lineament density. Jun 7, 2022 · Developing accurate soft computing methods for groundwater level (GWL) forecasting is essential for enhancing the planning and management of water resources. ; Booty, W. Our research underscores the transformative potential of machine learning to revolutionize long-term groundwater monitoring and contamination detection, providing valuable insights for future research and practical applications. Cho, S. This study aims to use a machine learning (ML) approach to identify groundwater contamination sites with total petroleum hydrocarbons (TPH) as target contaminants in a case study of gas stations in China. Jun 2, 2018 · Groundwater nitrate contamination in the Central Valley (CV) aquifer of California is widespread throughout the valley because of excess nitrogen fertilizer leaching down into the aquifer. , 2020, Abunada et al. 2002: Prediction of potential groundwater contamination by herbicides; integrated use of a leaching model and GIS in the north of ItalyIAHS-AISH Publication 273: 55-61 Crowe, A. e. , 2019). , 2016) and the respective water quantities. pH, EC, bicarbonate, chloride, total alkalinity, sodium and sulfate are major factors influencing the occurrence of fluoride in groundwater. 5535 - 5544 Mar 3, 2024 · Model predictions of redox conditions in groundwater produced in this study may help identify regions of the country with elevated groundwater vulnerability and stream vulnerability to groundwater-derived contaminants. These challenges highlight the urgent need for accurate identification of Groundwater Potential Zones (GWPZs), essential for sustainable groundwater resource management Assessing and predicting quality of groundwater is crucial in managing groundwater availability effectively. Here we review past efforts to advance subsurface investigation techniques and technologies, and computational efforts to create a Jul 22, 2025 · This study aims to determine the current status of groundwater in terms of heavy metal pollution in Harran Plain, which has been subjected to agricultural irrigation for over thirty years and is exposed to point and diffuse pollutant pressure. Dec 20, 2023 · Nitrate contamination in groundwater poses a significant threat to water quality and public health, especially in regions with limited data availabili… May 1, 2018 · Arsenic (As)-contaminated groundwater is a global concern with potential detrimental effects on the health of hundreds of millions of people worldwide… Jul 20, 2025 · Groundwater depletion has become a critical global issue, particularly in hard rock terrains, where rapid urbanization, over-extraction, and unregulated land use practices have exacerbated both water scarcity and contamination. Despite extensive research [4, 5, 6], the mechanisms driving As mobilization and the prediction of its concentrations remain elusive due to irregular distribution of As and the limited availability of data. Essential aspect of these activities is prediction and estimation of impact on groundwater and its protection To address these limitations, the development of reliable predictive models for groundwater levels is becoming increasingly critical. This paper Jun 1, 2016 · Groundwater contamination with arsenic (As) is one of the major issues in the world, especially for Southeast Asian (SEA) countries where groundwater is the major drinking water source, especially in rural areas. The study investigates arsenic (As) contamination in groundwater resources in Southeast Asia, focusing on Cambodia, Laos, and Thailand. 9wu n3aq n4i c6c 9uxh knxh5m ockb snqd 6cdxp3 doze