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Evaluation of Short-to-Medium Range Streamflow Forecasts Obtained Using an Enhanced Version of SRM1
Authors:Brian J Harshburger  Karen S Humes  Von P Walden  Brandon C Moore  Troy R Blandford  Albert Rango
Institution:1. Respectively, Researcher-Graduate Student (Harshburger), Professor (Humes), Associate Professor (Walden), and Researcher (Moore, Blandford), Department of Geography, University of Idaho, Moscow, Idaho 83844-3021;2. Research Hydrologist (Rango), U.S. Department of Agriculture, Agricultural Research Service, Jornada Experimental Range, Las Cruces, New Mexico 88003
Abstract:Harshburger, Brian J., Karen S. Humes, Von P. Walden, Brandon C. Moore, Troy R. Blandford, and Albert Rango, 2010. Evaluation of Short-to-Medium Range Streamflow Forecasts Obtained Using an Enhanced Version of SRM. Journal of the American Water Resources Association (JAWRA) 46(3):603-617. DOI: 10.1111/j.1752-1688.2010.00437.x Abstract: As demand for water continues to escalate in the western United States, so does the need for accurate streamflow forecasts. Here, we describe a methodology for generating short-to-medium range (1 to 15 days) streamflow forecasts using an enhanced version of the Snowmelt Runoff Model (SRM), snow-covered area data derived from MODIS products, data from Snow Telemetry stations, and meteorological forecasts. The methodology was tested on three mid-elevation, snowmelt-dominated basins ranging in size from 1,600 to 3,500 km2. To optimize the model performance and aid in its operational implementation, two enhancements have been made to SRM: (1) the use of an antecedent temperature index method to track snowpack cold content, and (2) the use of both maximum and minimum critical temperatures to partition precipitation into rain, snow, or a mixture of rain and snow. The comparison of retrospective model simulations with observed streamflow shows that the enhancements significantly improve the model performance. Streamflow forecasts generated using the enhanced version of the model compare well with the observed streamflow for the earlier leadtimes; forecast performance diminishes with leadtime due to errors in the meteorological forecasts. The three basins modeled in this research are typical of many mid-elevation basins throughout the American West, thus there is potential for this methodology to be applied successfully to other mountainous basins.
Keywords:snow hydrology  water supply  surface water hydrology  quantitative modeling
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