gsp dry wells .com

About 1.5 million residents of California’s Central Valley rely on private domestic wells for drinking water, and many of these wells can, and oftentimes do, fail during drought or as the result of unsustainable groundwater management. This project uses hydrologic modeling, statistical learning, and data science to predict how groundwater level changes will impact domestic well failure and provides estimated information on drinking water shortages for underserved populations. Decision makers and local agencies can use this information to prevent well failure and inform water resource management and planning.

View the project here, made possible with support from the AI for Earth Innovation Program Grant provided by Global Wildlife Conservation and Microsoft Corporation. See press release.

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Rich Pauloo, PhD
Hydrologist and data scientist

My interests include hydrogeology, data science and web technologies, 3D groundwater flow and contaminant transport simulation, building simple solutions to complex problems, and expedition behavior.

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