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United States Department of Agriculture

Agricultural Research Service

Title: Stochastic Daily Rainfall Generation in Southeast Arizona; An Example from Walnut Gulch Experimental Watershed 1554

Authors
item Hsieh, Huey-Hong - DIWAN COLLEGE OF MGMT.
item Stone, Jeffry
item Guertin, D. - UNIVERSITY OF ARIZONA
item Slack, D. - UNIVERSITY OF ARIZONA

Submitted to: First Interagency Conference on Research in the Watersheds
Publication Type: Proceedings
Publication Acceptance Date: August 20, 2003
Publication Date: September 20, 2003
Citation: Proc. 1st Interagency Conf. on Research in the Watershed, Oct. 27-30, 2003, Benson, AZ., pp. 139-145.

Interpretive Summary: The thunderstorm rainfall in southeast Arizona has high spatial and temporal variation. Using areal-averaged rainfall for watershed modeling has caused over or under estimations in erosion and runoff peak. This is a common problem usually faced by watershed researchers. This study had presented a series of analyses to identify spatial characteristics of thunderstorm rainfall based on statistical analyses on Walnut Gulch Experimental Watershed (WGEW) rainfall records. A stochastic daily summer rainfall generator was constructed and calibrated based on derived statistical characteristics and selected events. This rainfall generator can be used for advanced hydrological modeling.

Technical Abstract: The thunderstorm rainfall in southeast Arizona has high spatial and temporal variation. Using areal-averaged rainfall for watershed modeling has caused over or under estimations in erosion and runoff peak. This is a common problem usually faced by watershed researchers. This study had presented a series of analyses to identify spatial characteristics of thunderstorm rainfall based on statistical analyses on Walnut Gulch Experimental Watershed (WGEW) rainfall records. A stochastic daily summer rainfall generator was constructed and calibrated based on derived statistical characteristics and selected events. This rainfall generator can be used for advanced hydrological modeling.

Last Modified: 12/19/2014
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