A University of Texas at Arlington civil engineer is leading a statewide initiative to use more accurate forecasting to guide reservoir storage and release to improve water supply reliability and reduce flood damages.
Yu Zhang, a UT Arlington associate professor in the Department of Civil Engineering, is heading a new project—“Advancing Forecast-Informed Drought Planning for the West Gulf Region Through Integration of Climate Forecasts and Predictions of Reservoir Water Balance Predictions”—funded by the National Oceanic and Atmospheric Administration (NOAA)’s Climate Program Office. UTA received nearly $560,000 of the $719,000 grant.
Zhang is helping the state of Texas adopt what’s called Forecast-Informed Reservoir Operations (FIRO), in collaboration with Texas Water Development, U.S. Army Corps of Engineers, NOAA, the National Weather Service and the U.S. Bureau of Reclamation (USBR). Successful implementation of FIRO, according to Zhang, is predicated on accurate forecasts of reservoir inflow across a range of lead times, including at seasonal time scales of three to nine months.
“We want to introduce forecasts from dynamic climate models to complement and expand current climatology-based ensemble forecasts,” Zhang said. “We will develop forecasts for water withdrawals, diversions and lake evaporation to better represent weather/climate varying water demand.”
Zhang said the results of the research should inform the development of FIRO strategies and implementation of drought measures. The project also contains a dimension of informing USBR on its diversion project that supplies water to New Mexico and Texas. The ultimate aim is to help address water supply challenges in those two states.
Zhang is a leader in Texas in water management projects and developing better weather forecasting models. He is working with the General Land Office to develop a sediment management plan for the state, which includes assessing the amount of sediment transported from Texas rivers into the Gulf of Mexico. He also is working on a NASA-funded project to help forecasters better predict extreme weather events using a variety of existing NASA data sources.
