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Session Proposal: Actionable Insights from Remote Sensing: Advancing the Integration of Spatial Analytics, AI, and Participatory Approaches with Water Management Planning (AGU25)

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Actionable Insights from Remote Sensing: Advancing the Integration of Spatial Analytics, AI, and Participatory Approaches with Water Management Planning

Session ID#: 251834

Session Description:
Geospatial analysis is revolutionizing water resources modeling and management, enabling advanced assessments of water availability, quality, and ecosystem health under changing climate and human pressures. This session invites research that integrates remote sensing (satellite and airborne observations), spatial statistics, machine learning, and data assimilation with hydrologic and water management models. We seek contributions that leverage satellite and airborne observations, geospatial data fusion, and predictive analytics to improve decision-making, inform policy, and enhance sustainability. Studies addressing land use change, climate variability, and socio-hydrological interactions—particularly their implications for human and ecosystem health—are encouraged. We particularly encourage contributions that focus on public health indicators and approaches that emphasize participatory methods, co-production of knowledge, and accessible dissemination of scientific evidence to support vulnerable communities and decision-makers. By bridging geospatial science, modeling, and equitable water governance, this session aims to foster interdisciplinary dialogue and drive actionable insights for resilient and just water systems.
Co-Sponsor(s):
  • GH - GeoHealth
Index Terms:

0240 Public health [GEOHEALTH]
1855 Remote sensing [HYDROLOGY]
1871 Surface water quality [HYDROLOGY]
1942 Machine learning [INFORMATICS]
Primary Convener:  Romina Díaz Gómez, Stockholm Environment Institute, US Water, Davis, CA, United States
Convener:  Dr. Antarpreet Singh Jutla, PhD, University of Florida, Environmental Engineering Sciences, Ft Walton Beach, FL, United States
Student/Early Career Convener:  Marina Reyes Lopez Mautner, Stockholm Environment Institute, US Water, Davis, CA, United States
 
Dissolved organic carbon in groundwater: a geospatial analysis in the lower Himalayan industrial region (1845937)
Utsav Rajput1, Deepak Swami1 and Nitin Joshi2, (1)Indian Institute of Technology Mandi, School of Civil and Environmental Engineering, Mandi, India, (2)Indian Institute of Technology Jammu, Department of Civil Engineering, Jammu, India
 
Remote Sensing Applications in Alfalfa Phenology and Irrigation Estimation (1895524)
Swatantra Kumar Sharma and Mesfin Mergia Mekonnen, University of Alabama, Department of Civil, Construction and Environmental Engineering, Tuscaloosa, United States
 
Spatial Identification and Dynamics of Groundwater-Dependent Ecosystems in the North China Plain: An Integrated Random Forest and Multi-Criteria Decision Analysis Approach (1897168)
Baigali Batsuuri, Tsinghua University, Department of Hydraulic Engineering, Beijing, China
 
A Remote Sensing Data Fusion Approach for Automatic Identification of Ancient Subsurface Water Systems (1922455)
Deepak Kumar1, Hemanth Kumar1, Bvn P Kambhammettu1, Satish Kumar Regonda2 and Umashankar B1, (1)Indian Institute of Technology Hyderabad, Department of Civil Engineering, Hyderabad, India, (2)Indian Institute of Technology Hyderabad, Department of Civil Engineering and Department of Climate Change, Hyderabad, India
 
Bridging Numbers and Narratives: Engineering Diplomacy for Actionable Water Insights (Invited) (1924727)
Shafiqul Islam, Tufts Univ Civil & Environ Eng, Medford, MA, United States
 
Dielectric Permittivity Measurement Using a Soil TDR Probe and Vector Network Analyzer Across Multiple Frequency Ranges (1938004)
Sona Tokuyama, Meiji University, Kawasaki, Japan, Kosuke Noborio, Meiji University, Agriculture, Kawasaki, Japan and Daiki Kobayashi, NTT Access Network Service Systems Laboratories, Tsukuba, Japan
 
A Machine Learning Pipeline for Identifying Managed Aquifer Recharge Locations in Satellite Imagery (1976654)
Shuang Yu1, Ate Visser2, Indrasis Chakraborty3, Gemma Jayne Anderson1 and Jory Lerback3, (1)Lawrence Livermore National Laboratory, Livermore, CA, United States, (2)Lawrence Livermore National Laboratory, Nuclear and Chemical Sciences Division, Livermore, CA, United States, (3)Lawrence Livermore National Laboratory, Livermore, United States
 
Impact of Hydropower on Flood Risk and Food Production – Insights from Satellite Observations and the new GRAIN Dataset (1978408)
Sarath Suresh and Faisal Hossain, University of Washington Seattle Campus, Department of Civil and Environmental Engineering, Seattle, United States
 
Remote Sensing and GeoAI-Based Predictive Analysis in Hydrology and Climate Models (Invited) (1979819)
Aqil Tariq, Mississippi State University, Department of Wildlife, Fisheries and Aquaculture, Mississippi State, MS, United States, Davis Brian J., Mississippi State University, Department of Wildlife, Fisheries and Aquaculture, Mississippi State, United States, Muhammad Bilawal Junaid, King Saud University, Riyadh, Saudi Arabia, Rana Waqar Aslam, Wuhan University, State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, China., Wuhan, China and Rida Bokhari, Queensland University of Technology, Brisbane, Australia
 
Global Snow Attribute Mapping Tool (Global‑SAM) (1986948)
Nawa Raj Pradhan1, Saurav Bhattarai2, Gene Kloss3, Anna M Wagner4, Rocky Talchabhadel5, Elias J Deeb6, Jodi L. Ryder7, Ahmad Tavakoly3, Zoe Courville8, Venkataraman (Venkat) Lakshmi9, Michael Paquette10, Dhiren Khona10, Michael Lewis10 and Grace Carravone11, (1)US Army Corps of Engineers, Engineer Research and Development Center, Coastal and Hydraulics Laboratory, Vicksburg, United States, (2)Jackson State University, Department of Civil and Environmental Engineering, Jackson, MS, United States, (3)US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, Vicksburg, United States, (4)Cold Regions Research and Engineering Laboratory (CRREL), Fort Wainwright, AK, United States, (5)Jackson State University, Department of Civil and Environmental Engineering, Jackson, United States, (6)U.S. Army Corps of Engineers, Cold Regions Research and Engineering Laboratory, Hanover, United States, (7)US Army Engineer Research and Development Center, Environmental Laboratory, Vicksburg, MS, United States, (8)Cold Regions Research and Engineering Laboratory, Hanover, NH, United States, (9)University of Virginia, Civil and Environmental Engineering, Charlottesville, United States, (10)US Army Corps of Engineers Geospatial Research Laboratory, Alexandria, United States, (11)US Army Engineer Research and Development Center, Vicksburg, United States
 
Refining Flood Forecasts with Remote Sensing and Machine Learning: A Case Study of Hurricane Ida in New Jersey (1987513)
Zhoobin Rahimi, Stevens Institute of Technology, Department of Civil, Environmental and Ocean Engineering, Union City, NJ, United States
 
Exploring Vegetation Responses in an Amazonian Region Affected by Forest Fires, Based on ECOSTRESS and Satellite-Derived PM2.5 (2000153)
Freddy Ángel Soria, Universidad Católica Boliviana San Pablo, Environmental Engineering, La Paz, Bolivia and Vidfa Carolina Garvizu
 
An interactive framework for quantifying the potential for future water conflicts in Indiana (2002111)
Laura C Bowling, Purdue University, Agronomy, West Lafayette, IN, United States and Keith Aric Cherkauer, Purdue University, Agricultural & Biological Engineering, West Lafayette, IN, United States
See more of: Hydrology
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