Increasing demand for better information related to the flow of streams and rivers across the United States prompted the National Center for Atmospheric Research to create a high-resolution National Water Model in 2016, and a researcher at The University of Texas at Arlington is working to improve the quality of forecasts based on the model.
Seongjin Noh, assistant professor for research in UTA’s Civil Engineering Department, will use a two-year, $209,564 National Oceanic and Atmospheric Administration grant to create a streamflow data assimilator to improve the National Weather Service’s ability to monitor and predict floods and droughts in the nation’s rivers and streams.
Civil Engineering Professor D.J. Seo is co-principal investigator on the project. The National Center for Atmospheric Research and the NWS Office of Water Prediction will collaborate with the UTA team.
The National Water Model is a next-generation forecasting model which simulates the flow of rivers and streams over the entire continental United States. To date, NOAA’s water flow forecasts have been available for only about 4,000 river locations, including 335 in the NWS’s West Gulf River Forecast Center’s service area which consists most of Texas and a majority of New Mexico. The model greatly expands forecast points to 2.7 million stream locations nationwide, which would provide much more detailed information, but also presents a large challenge in keeping the model states consistent with the unfolding reality.
Noh will use data assimilation, which takes real-time observations and incorporates them into mathematical models to improve the accuracy of NWM forecasts.
“Observations often provide the best information about the current state of the dynamic system but they do not tell, by themselves, what the future may look like. If we…