Assessment of the Performance of Satellite-Based Precipitation Products for Flood Events across Diverse Spatial Scales Using GSSHA Modeling System
| dc.contributor.author | Furl, Chad | |
| dc.contributor.author | Ghebreyesus, Dawit | |
| dc.contributor.author | Sharif, Hatim O. | |
| dc.date.accessioned | 2021-04-19T15:09:18Z | |
| dc.date.available | 2021-04-19T15:09:18Z | |
| dc.date.issued | 2018-05-28 | |
| dc.date.updated | 2021-04-19T15:09:18Z | |
| dc.description.abstract | Accurate precipitation measurements for high magnitude rainfall events are of great importance in hydrometeorology and climatology research. The focus of the study is to assess the performance of satellite-based precipitation products against a gauge adjusted Next-Generation Radar (NEXRAD) Stage IV product during high magnitude rainfall events. The assessment was categorized across three spatial scales using watershed ranging from ~200–10,000 km2. The propagation of the errors from rainfall estimates to runoff estimates was analyzed by forcing a hydrologic-model with the satellite-based precipitation products for nine storm events from 2004 to 2015. The National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) Morphing Technique (CMORPH) products showed high correlation to the NEXRAD estimates in all spatial domains, and had an average Nash-Sutcliffe coefficient of 0.81. The Global Precipitation Measurement (GPM) Early product was inconsistent with a very high variance of Nash-Sutcliffe coefficient in all spatial domains (from −0.46 to 0.38), however, the variance decreased as the watershed size increased. Surprisingly, Tropical Rainfall Measuring Mission (TRMM) also showed a very high variance in all the performance statics. In contrast, the un-corrected product of the TRMM showed a relatively better performance. The errors of the precipitation estimates were amplified in the simulated hydrographs. Even though the products provide evenly distributed near-global spatiotemporal estimates, they significantly underestimate strong storm events in all spatial scales. | |
| dc.description.department | Civil and Environmental Engineering, and Construction Management | |
| dc.identifier | doi: 10.3390/geosciences8060191 | |
| dc.identifier.citation | Geosciences 8 (6): 191 (2018) | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12588/412 | |
| dc.rights | Attribution 4.0 United States | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | hydrology | |
| dc.subject | NEXRAD | |
| dc.subject | remote sensing | |
| dc.subject | GSSHA | |
| dc.subject | flooding | |
| dc.subject | GPM | |
| dc.title | Assessment of the Performance of Satellite-Based Precipitation Products for Flood Events across Diverse Spatial Scales Using GSSHA Modeling System | |
| dc.type | Article |