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Evaluation of Short‐to‐Medium Range Streamflow Forecasts Obtained Using an Enhanced Version of SRM 1
Author(s) -
Harshburger Brian J.,
Humes Karen S.,
Walden Von P.,
Moore Brandon C.,
Blandford Troy R.,
Rango Albert
Publication year - 2010
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.2010.00437.x
Subject(s) - streamflow , snowmelt , snowpack , snow , environmental science , precipitation , meteorology , climatology , water year , hydrometeorology , flood forecasting , range (aeronautics) , surface runoff , stream flow , drainage basin , hydrology (agriculture) , geology , geography , ecology , materials science , cartography , geotechnical engineering , composite material , biology
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 km 2 . 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.