HR: 1340h
AN: H43A-0962    [Abstracts]
TI: Application of LDAS-era land surface models for drought characterization and prediction in Washington State
AU: * Shukla, S
EM: shraddhanandshukla@gmail.com
AF: University of Washington, Wilson Ceramic Laboratory Box 352700, Seattle, WA 98195-2700, United States
AU: Wood, A
EM: aww@hydro.washington.edu
AF: University of Washington, Wilson Ceramic Laboratory Box 352700, Seattle, WA 98195-2700, United States
AB: Accurate appraisal of the current and future status of drought is still a major challenge for scientists and water managers. No ubiquitous definition of drought exists and different indices of meteorological and hydrological elements yield different perspectives on drought. Although traditional drought indices are based on meteorological inputs, hydrologic variables such as soil moisture and runoff, the by-products of the hydro- meteorological process affecting a watershed, can be used to derive indicators of drought status, and are arguably more closely related to the societal impacts of drought than the drought indices based on the meteorological variables only. This presentation compares drought metrics based on modeled soil moisture and runoff with the conventional drought indices and other independent measures, including observed or naturalized streamflow and reservoir levels. Hydrologic fields used for this analysis are simulated by a physically- based, semi-distributed hydrologic model, the Variable Infiltration Capacity model, for Washington State We also show that ensemble hydrologic predictions of these fields can be used to extend both traditional and model- based drought indices into the future and provide uncertainty estimates for the future evolution of a drought. The significant similarities between the model-based metrics and the traditional indicators of drought suggest that the hydrologic models are at least as capable of characterizing drought as traditional meteorological indices, and offer a way forward toward developing a capacity for drought prediction.
UR: http://www.hydro.washington.edu/forecast/sarp/
DE: 1812 Drought
DE: 1866 Soil moisture
DE: 3238 Prediction (3245, 4263)
SC: Hydrology [H]
MN: 2007 Fall Meeting