NASA Grant Supports Satellite Data uses in Flood Modeling
When hydrologists forecast floods, they rely heavily on a combination of meteorological data, modeling tools and remote sensing observations. The accuracy of such forecasts is often quite good over data-rich regions. But predictions are more challenging in mountainous areas characterized by complex geographic features and inadequate ground observations.
Dr. Emmanouil Anagnostou, professor of Civil & Environmental Engineering and the Northeast Utilities Endowed Chair in Environmental Engineering, an internationally renowned expert in the area of hydrometeorology and precipitation remote sensing, was recently awarded a $360,000 grant from NASA to advance his research aimed at improving the use of satellite-derived rainfall data in hydrologic modeling of complex terrain basin floods. The work will build upon his extensive platform of ongoing hydro-meteorological experiments around the globe.
In particular, his work will focus on the development of models that accurately predict flooding caused by heavy precipitation events in medium-size basins having complex terrains. Flooding in such locales is especially dangerous and poses a significant threat to human life and property. Dr. Anagnostou explains that he will incorporate Ground Validation (GV) products from his field experiments to enhance the quantitative accuracy of satellite-derived rainfall that will consequently improve flood prediction. In NASA’s lexicon (see Global Precipitation Measurement Mission), hydrologic GV “products” include experimental observations from networks of dual-polarization weather radars, radar profilers, and in situ disdrometers and rain gauges.
In geographic basins having steeply sloped hillsides and a mixture of vegetation, built landscape and soil types, flash floods can arise in a few hours, leaving little time to warn residents of impending danger. Dr. Anagnostou’s NASA-funded work will focus squarely on such scenarios with the aim of developing improved high-resolution satellite rainfall estimates that would improve the efficiency of flood warning systems. He will also seek to understand, and develop corrections for, errors in current regional-scale flood basin models that often result from inaccurate satellite rainfall forcing and scale effects.