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Session
  • Presentation | H34D: Advancing Water Quality Monitoring and Management Through Remote Sensing and Artificial Intelligence II Oral
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  • H34D-05: Space-Based Tools for California’s Water Quality Challenges: Linking Satellites to Solutions (invited)
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  • Location Icon225-227
    NOLA CC
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Author(s):
Erin Hestir, University of California Merced (First Author, Presenting Author)
Christine Lee, Jet Propulsion Laboratory, California Institute of Technology
Amanda Lopez, NASA Jet Propulsion Laboratory, California Institute of Technology
Dulcinea Avouris, Kent State University Kent Campus
Brittany Lopez Barreto, University of California, Merced
Lori Berberian, Occidental College
Shobha Khanna, University of California Merced
Fabjola Kasaj, Organization Not Listed
Marc Beutel, University of California, Merced


This work uses satellite remote sensing and artificial intelligence to monitor water quality in California’s inland waters. By combining satellite data with machine learning, we can detect issues like harmful algal blooms, wildfire-related pollution, and sediment runoff in near real time. These tools improve water quality monitoring in areas where ground-based data are limited, helping managers respond faster and plan for long-term resilience.



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