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ARS Home » Pacific West Area » Tucson, Arizona » SWRC » Research » Publications at this Location » Publication #174734


item MORIN, E.
item Goodrich, David - Dave
item MADDOX, R.
item GAO, X.
item GUPTA, H.

Submitted to: Journal of the Atmospheric Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/18/2004
Publication Date: 2/22/2005
Citation: Morin, E., Goodrich, D.C., Maddox, R.A., Gao, X., Gupta, H., Sorooshian, S. 2005. RAINFALL MODELING FOR INTEGRATING RADAR INFORMATION INTO HYDROLOGICAL MODEL. Journal of the Atmospheric Sciences. 6: 23-30.

Interpretive Summary: Arid and semiarid regions account for approximately one-third of the land mass of earth and study of water resources and the hydrology of these regions is important if we are to continue to populate and use them. Water is a critical resource in these regions, many of which are experiencing population growth at a far greater rate than more humid areas. Detailed rainfall estimates from National Weather Service radar shown daily on popular news forecasts are being used for water resource decisions and hydrology models. However, the methods to estimate rainfall from radar to use in runoff models often produce rainfall that is highly variable. In this study we developed a way to extract the essential rainstorm information from the radar data and ignore the 'noisy' data that makes it difficult to interpret radar-rainfall patterns. Using this simplified data produces the same runoff from a computer model as was produced from the full set of radar data. More importantly, this approach allows flood managers to examine the storms which produce runoff and how they move over a watershed. This is important information for flash flood forecasting in semi-arid regions.

Technical Abstract: A spatial rainfall model was applied to radar data of air mass thunderstorms to yield a rainstorm representation as a set of convective rain cells. The modeled rainfall was used as input into hydrological model, instead of the standard radar grid data. This approach allows a comprehensive linkage between runoff responses and rainfall structures.