Forecasting of flooding and droughts will be improved (right) by integrating remote sensing information (left) with land surface models through the Virginia Tech HIDE data environment (center).
Technology developed in ECE laboratories is serving as the foundation of a new effort to improve flood and drought forecasting in the Ohio River Basin.
“Floods and droughts are two major natural hazards in the Ohio River Basin, and they have major impacts on the region’s agriculture, industries, commercial navigation, and residential communities,” said Yao Liang, an assistant ECE professor at the Advanced Research Institute (ARI) and principal investigator (PI) on the effort. “There are data and models available from different sources and different systems, that, if integrated, can significantly improve forecasting accuracy and help disaster management.”
The integration effort stretches across universities and government organizations, including the National Weather Service (co-PI Thomas Adams is a Virginia Tech alumnus), George Mason University, the University of Pittsburgh, and NASA Goddard Earth Sciences Data Information and Services Center.
The team is developing a system to integrate soil moisture data from NASA satellites and NASA-NOAA land surface models, and a spatial data assimilation framework recently developed at the University of Pittsburgh into the National Weather Service River Forecast System. Surface soil moisture data from multiple satellites in conjunction with the NASA-NOAA models and the data assimilation framework will significantly improve the evapotranspiration rate calculation, which plays a critical role in the river forecast system. The integration will be achieved by extending the hydrological integrated data environment (HIDE) developed by Liang and Nimmy Ravindran.
“Our ultimate goal is to enable the National Weather Service to seamlessly avail itself of the soil moisture data, that was previously unavailable,” Liang said. The project results are expected to be extendable to the national level, via the adoption of the system by river forecast centers at both national and regional levels. The $860,499 project is funded by NASA.