[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118611-en":3,"doc-seo-118611-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118611,1374391974585,"Genevieve","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","A systematic review of machine learning in groundwater monitoring - research overview","With increasing concerns about water scarcity, groundwater is central to freshwater supply, yet human and natural activities can contaminate it and make it unsafe. Contamination creates major health risks, driving a need for more accurate monitoring and contamination detection. Machine learning can handle complex, high-volume environmental data, but comprehensive reviews focused on groundwater monitoring remain limited. This paper surveys machine-learning methods, highlighting limitations and future potential, and summarizes work on automating data processing and model training using groundwater sensor data.","Environmental Modelling and Software 192 (2025) 106549  \nContents lists available at ScienceDirect  \nEnvironmental Modelling and Software  \njournal [homepage: www.elsevier.com/locate/envsoft](homepage: www.elsevier.com/locate/envsoft)  \n| A systematic review of machine learning in groundwater monitoring |  |  |  |\n| --- | --- | --- | --- |\n| Mrunmayee Dhaprea, Shrikant Jadhavb,* , Debanjana Dasc, Jehanzeb Khan b, Youngsoo Kim d, Sen Chiaoc, Thomas Danielsone\u003Cbr>a Department of Computer Science, San Jose State University, USA b Department of Electrical Engineering, San Jose State University, USA\u003Cbr>c NOAA Center for Atmospheric Sciences and Meteorology (NCAS-M), Howard University, USA d Department of Electrical Engineering, University of Minnesota Duluth, USA\u003Cbr>e Department of Environmental Sciences and Dosimetry, Savannah River National Laboratory, USA |  |  |  |\n| A R T I C L E I N F O |  | A B S T R A C T |  |\n| Keywords:\u003Cbr>Groundwater contamination Groundwater/environment monitoring Machine learning\u003Cbr>Artificial intelligence\u003Cbr>AI/ML\u003Cbr>Feature engineering |  | With increasing concerns about water scarcity, groundwater has become crucial since this resource provides most of the freshwater needs. However, various human and natural activities often contaminate the groundwater, making it unsuitable for use. Over the years, scientists and engineers have used many methods to predict and track groundwater contamination as part of environmental monitoring. Consequently, there is an urgent need for improved methods, particularly in the face of increasing contamination. Machine learning has sometimes been used to monitor groundwater, air quality, and climate. Traditional methods must be improved due to the complexity and large amount of environmental data. This includes using hybrid models that combine traditional and new techniques. Despite the use of machine learning in many scientific areas, there is a lack of comprehensive reviews focusing on its use in environmental monitoring, especially groundwater monitoring. We aim to fill this gap by exploring machine-learning applications in groundwater monitoring. We discuss relevant methods, their limitations, and future potential. We summarize research on automating data processing and model training using groundwater sensor data. 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. |  |\n\n1. Introduction  \nGroundwater, a vital water source, is stored in aquifers, porous rock layers beneath the earth’s surface. It serves as a crucial supply for wells, springs, and various public and private water systems in the United States. The US Geological Survey estimates that the country utilizes a staggering 82.3 billion gallons of fresh groundwater daily, including public and private supply, irrigation, livestock, manufacturing, mining, thermoelectric power, and more. The Centers for Disease Control (CDC) reports that approximately 44 % of the US population, around 145 million people, rely on groundwater sources. Despite this, the National Ground Water Association (NGWA) points out that while about 90 % of our freshwater supplies are underground, these sources provide less than 27 % of the water used, highlighting the underutilization of groundwater. The utilization and sustainability of groundwater are discussed ina survey conducted by IIT, Kharagpur (Mukherjee, A. et al., 2021).  \nGroundwater contamination is primarily caused by human activities,  \na grave issue that significantly contributes to the underutilization of this vital resource. Accidental chemical spills, improper disposal of industrial waste and wastewater, landfills, and underground storage tanks are all sources of contaminants that seep into the groundwater. Serious health risks stem from these contaminants, ranging from heavy metals to microbial pathog","cbCaibsbxZeVhTBO","https://ap.wps.com/l/cbCaibsbxZeVhTBO","pdf",6074306,1,27,"English","en",105,"# Introduction\n## Groundwater importance and utilization\n## Sources and health impacts of contamination\n## Groundwater plumes and remediation needs\n# Machine learning for environmental monitoring\n## Rationale for hybrid and improved methods\n## Gap in existing reviews","[{\"question\":\"Why is groundwater monitoring important in the document?\",\"answer\":\"Groundwater underpins much of the freshwater supply, but contamination from human and natural activities can make it unsafe. The document highlights the urgent need to detect and manage contamination effectively.\"},{\"question\":\"What problem does the paper aim to address?\",\"answer\":\"It notes a lack of comprehensive reviews on machine learning specifically for environmental monitoring, particularly groundwater monitoring. The paper fills this gap by surveying applications and methods.\"},{\"question\":\"What topics does the review cover regarding machine learning methods?\",\"answer\":\"It discusses relevant machine-learning approaches, their limitations, and future potential, with emphasis on automating data processing and model training using groundwater sensor data.\"}]","A systematic review of machine learning in groundwater monitoring - research overview | PDF",1785684504,68,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"a-systematic-review-of-machine-learning-in-groundwater-monitoring-research-overview","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-systematic-review-of-machine-learning-in-groundwater-monitoring-research-overview/118611/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-02",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is groundwater monitoring important in the document?","Question",{"text":75,"@type":76},"Groundwater underpins much of the freshwater supply, but contamination from human and natural activities can make it unsafe. 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