The Richland-Chambers Reservoir was first impounded in 1987, and now serves as a key drinking water reservoir in Texas that, like many other reservoirs, faces serious eutrophication problems.
Project type: Digital twin for operational forecasting
Place: Texas, USA
Partner: Baylor University
Nutrient rich reservoirs often experience frequent blooms of potentially toxin-producing cyanobacteria and also periods of bottom water anoxia. Periods of anoxia can lead to increased levels of manganese in the water, which can cause problems with memory, attention, and motor skills in both children and adults when used for drinking water over long periods of time.
In a collaboration with Baylor University, we applied the SWAT+ model to the watershed, and the GOTM-WET model to the reservoir itself. Models were implemented and coupled via the ASAP Platform by WaterWebTools, which effectively comprised an integrated digital twin for the Richland-Chambers Reservoir and its watershed and enabled operational 9-day forecasting of its water resource.
Forecasts of the hydrology and water quality of the Richland-Chambers Reservoir can improve decision making in relation to reservoir operations, and facilitate reduced risk of downstream flooding as well as a more stable and cost-efficient water supply.
Want to know more?
Contact project lead Dr. Anders Nielsen to learn more about the project or learn how we may be able to assist you.
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