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  • Presentation | H12A: Advancements in Watershed Modeling to Support Water Management II Oral
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  • H12A-07: Dynamic Mixing with Unsteady Transit Time Theory Resolves Source-Specific Water Quality in a One-Water Reservoir
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  • Location Icon220-222
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Author(s):
Shantanu Bhide, Virginia Polytechnic Institute and State University (First Author, Presenting Author)
Stanley Grant, Virginia Polytechnic Institute and State University
Paolo Benettin, École Polytechnique Fédérale de Lausanne (EPFL)
Megan Rippy, Virginia Polytechnic Institute and State University
Ahmed Monofy, Virginia Polytechnic Institute and State University
Kirin Emlet Furst, Virginia Polytechnic Institute and State University
Sydney Shelton, University of Maryland
Sujay Kaushal, University of Maryland
Shalini Misra, Virginia Tech
Peter Vikesland, Virginia Tech
Erin Hotchkiss, Virginia Polytechnic Institute and State University
Todd Schenk, Virginia Tech
Harold Post, Occoquan Watershed Monitoring Laboratory
Dongmei Alvi, Occoquan Watershed Monitoring Laboratory
Admin Husic, Virginia Tech


Cities often draw drinking water from a lake or a reservoir that blends several sources at once: river water, storm runoff, and reclaimed wastewater released upstream. When these waters mix, it’s hard to tell which source is driving changes in water quality at the intake.


We built a simple, fast tool that traces how much each source contributes to the water quality at the drinking water intake and how long that water stays in the lake/reservoir. It avoids heavy, 3-D computer models and instead uses flow, storage and water quality information utilities already collect.


In Virginia’s Occoquan Reservoir, our predictions captured the familiar seasonal swings and showed where action matters most: winter salt surges are driven largely by road-salt runoff carried in by rivers and streams, while summer nitrogen levels are most influenced by the upstream reclaimed-water discharge.


Because the tool runs quickly, water managers can try “what if” scenarios—like reducing source specific pollutants—and see likely outcomes before acting. This helps communities choose targeted, cost-effective steps to protect drinking-water quality.




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