H064
Geogenic Contamination in the Groundwater System: Advances (and Challenges) in Assessment, Water Quality Modeling, Uncertainty, and Water Supply Management
Session ID#: 85455
Session Description:
Compromised water quality can restrict availability for potable, agricultural, ecological, recreational, and other uses. Geogenic (geologic-sourced) contaminants in groundwater are a significant global threat to human health – a threat recognized for decades. Contaminants of particular concern are arsenic (As), fluoride (F), and manganese (Mn). Geochemical drivers (pH, redox), indicators (specific conductance, temperature), and climate also play a role in successfully assessing and modeling the complexity of geogenic contaminant occurrence, fate, and transport at relevant scales. Without appropriate assessment and modeling, effective management is not possible.
We solicit abstracts in the thematic areas for assessment, mitigation, and management of geogenic contaminants in groundwater: Advances in modelling approaches, including Machine Learning (ML)/ Artificial Intelligence (AI) applications; GIS and remote sensing; sensors; impacts of climate change on geogenic contaminants; and socio-economic impacts in the poor rural and urban areas. We also welcome methods that improve ML/AI and other model interpretability or uncertainty assessment.
Index Terms:
0240 Public health [GEOHEALTH]
1829 Groundwater hydrology [HYDROLOGY]
1831 Groundwater quality [HYDROLOGY]
1847 Modeling [HYDROLOGY]
Primary Convener: Basant Yadav, Cranfield University, Cranfield, MK43, United Kingdom
Conveners: Pankaj Kumar Gupta, University of Waterloo, Faculty of Environment, Waterloo, Canada, Julian Koch, Geological Survey of Denmark and Greenland, Copenhagen, Denmark and Katherine Marie Ransom, U.S. Geological Survey, Sacramento, CA, United States
Primary Liaison: Basant Yadav, Cranfield University, Cranfield, MK43, United Kingdom
Modeling and mapping high arsenic and manganese concentrations in the glacial aquifer system, northern USA: Using machine learning methods to predict water quality conditions in an extensive, stratigraphically complex, unconsolidated drinking water aquifer system (Invited) (485927)
Melinda L Erickson, U.S. Geological Survey, Upper Midwest Water Science Center, Minneapolis, MN, United States, Sarah M. Elliott, USGS Upper Midwest Water Science Center, Mounds View, MN, United States, Craig Brown, USGS New England Water Science Center, Northborough, United States, Paul E. Stackelberg, USGS New York Water Science Center Troy, Troy, NJ, United States and Katherine Marie Ransom, U.S. Geological Survey, Sacramento, CA, United States
Groundwater Assessment and Vulnerability Mapping of Vindhyan-Ganga Sedimentary formations around Mirzapur District in India (490959)
Manik Goel, Indian Institute of Technology Roorkee, Roorkee, India, Pankaj Kumar Gupta, University of Waterloo, Waterloo, ON, Canada and Brijesh K Yadav, Indian Institute of Technology, Roorkee, India
FLUORIDE IN BASIN-FILL AQUIFERS OF WESTERN U.S. AQUIFERS: PREDICTING CONCENTRATIONS AT DOMESTIC AND PUBLIC SUPPLY DEPTHS USING MACHINE LEARNING METHODS (497011)
Celia Rosecrans, USGS California Water Science Center Sacramento, Sacramento, CA, United States, Katherine Marie Ransom, U.S. Geological Survey, Sacramento, CA, United States and Paul E. Stackelberg, USGS New York Water Science Center Troy, Troy, NJ, United States
Predicting Geogenic Contaminants in Principal Aquifers of the United States (505700)
Paul E. Stackelberg, USGS Water Mission Area, Troy, NY, United States, Kenneth Belitz, USGS, San Diego, CA, United States and Katherine Marie Ransom, U.S. Geological Survey, Sacramento, CA, United States
Geogenic Contaminants in Ground Water Used for Public Supply in the Conterminous U.S. (507628)
Kenneth Belitz, USGS Headquarters, NAWQA, Reston, VA, United States, Bruce D Lindsey, USGS, New Cumberland, PA, United States, Paul E. Stackelberg, USGS New York Water Science Center Troy, Troy, NJ, United States and Miranda S Fram, USGS, Sacramento, CA, United States
Groundwater Environmental Risk Assessment of Underground Coal Mine in the Mine Life Cycle, A Case Study of Hongshan Coal Mine, Zibo City, Shandong Province, North China (518995)
Haibo Feng, China University of Geosciences Wuhan, Wuhan, China, Aiguo Zhou, China University of Geosciences, School of Environmental Studies, Wuhan, China, Jianwei Zhou, China University of Geoscience, Wuhan, China and Bo Chai, China University of Geosciences, Wuhan, School of Environmental Studies, Wuhan, China
Impact of managed aquifer recharge structures on fluoride in India (Invited) (519863)
Alison Parker1, Basant Yadav1, Kristell Le Corre Pidou2, Pablo Campo Moreno2, Ken Rushton2, Deepak Kashyap3, Vijay Anand4, Rakesh Sharma5 and Anupma Sharma6, (1)Cranfield University, Cranfield, MK43, United Kingdom, (2)Cranfield University, Cranfield, United Kingdom, (3)Fort Collins, CO, United States, (4)IIT Ropar, Ropar, India, (5)IIT Jodhpur, Jodhpur, India, (6)National Institute of Hydrology, Roorkee, India
Machine Learning Models to Predict the Occurrence of Arsenic in Domestic Wells throughout the Conterminous United States (521109)
Melissa A Lombard, USGS New England Water Science Center, Pembroke, NH, United States, Joseph Ayotte, USGS New England Water Science Center - New Hampshire Office, Pembroke, NH, United States, Matthew O Gribble, Emory University, Atlanta, United States, Maria Argos, University of Illinois at Chicago, Chicago, United States, Paul M Bradley, USGS South Atlantic Water Science Center, Columbia, SC, United States, Michael Joseph Focazio, USGS Headquarters, Reston, VA, United States and Patricia Toccalino, USGS Headquarters, Sacramento, United States
An approach of Multi-variate statistical design (Taguchi) and numerical tool (COMSOL) in exploring the arsenic sequestration potential of γ-Fe2O3 NPs in groundwater of Ballia district, Uttar-Pradesh, India (522631)
Ajay Kumar1, Himanshu Joshi1 and Anil Kumar2, (1)Indian Institute of Technology Roorkee, Hydrology, Roorkee, India, (2)Indian Institute of Technology Roorkee, Chemistry, Roorkee, India
Arsenic mobilization in aquifers affected by spills: detecting arsenic in groundwater using field-deployable analysis techniques (539737)
Isabelle Cozzarelli1, Emily Hicks2, Brady Ziegler3, Jeanne B Jaeschke4, Adam C Mumford1, Jared Trost5 and Chimone Dalton6, (1)USGS, Reston, VA, United States, (2)FredSense Technologies Corporation, Calgary, AB, Canada, (3)Trinity University, San Antonio, United States, (4)USGS Headquarters, Reston, United States, (5)USGS Minnesota Water Science Center, Mounds View, MN, United States, (6)Fredsense Technologies Incorporated, Calgary, AB, Canada
Comparison and Evaluation of the Effect of Water-Rock Reaction using Dissolution Experiments on Various Types of Rocks (565421)
Ho Jeong Jo1,2, Kyung-Seok Ko1, Dong-Chan Koh1 and Jong-Sik Ryu3, (1)Korea Institute of Geoscience and Mineral Resources, Daejeon, South Korea, (2)Chonbuk National University, Jeonju, South Korea, (3)Pukyong National University, Department of Earth and Environmental Sciences, Busan, South Korea
Groundwater arsenic risk assessment in Cambodia via machine learning methods (579765)
Zhen Tan1,2, Qiang Yang3, Kongkea Phan4, Benjamin C Bostick3 and Yan Zheng1,3, (1)Southern University of Science and Technology, School of Environmental Science and Engineering, Shenzhen, China, (2)Peking University, Institute of Water Sciences, Beijing, China, (3)Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, United States, (4)International University, Faculty of Science and Technology, Phnom Penh, Cambodia
Quality Assessment of stormwater through different sources of a sub-tropical town of India (580887)
Rajesh Kumar Vishwakarma, Roorkee, Uttarakhand, India, Himanshu Joshi, Indian Institute of Technology Roorkee, Hydrology, Roorkee, India and Ashantha Goonetilleke SR., Queensland University of Technology, Civil Engineering and Built Environment, Brisbane, QLD, Australia
Aqueous geochemistry in support of machine learning models for the glacial aquifer system, northern USA (584082)
Craig Brown, USGS New England Water Science Center, Northborough, United States, Paul E. Stackelberg, USGS New York Water Science Center Troy, Troy, NJ, United States, Melinda L Erickson, U.S. Geological Survey, Upper Midwest Water Science Center, Minneapolis, MN, United States and Sarah M. Elliott, USGS Upper Midwest Water Science Center, Mounds View, MN, United States
Management of geogenic As-contained groundwater in Taiwan (625973)
Sheng-Wei Wang1, Hui-Chen Chien2, Kuo-Su Chiu2, Hsien-Wen Ko2, Hsin-I Lu2, Wan-Fang Chan2, Feng-Jen Tsai2, Liang-Li Chang2, Chih-Chung Liu3 and Ying-Tzu Chen3, (1)Sinotech Environmental Technology Ltd., Taipei, Taiwan, (2)Soil and Groundwater Pollution Remediation Fund Management Board, Environmental Protection Administration, Taipei, Taiwan, (3)Sinotech Environmental Technology, Ltd., Taipei, Taiwan
