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- W2097432457 endingPage "1559" @default.
- W2097432457 startingPage "1543" @default.
- W2097432457 abstract "In a water-stressed region, such as the western United States, it is essential to have long lead times for streamflow forecasts used in reservoir operations and water resources management. Current water supply forecasts provide a 3-month to 6-month lead time, depending on the time of year. However, there is a growing demand from stakeholders to have forecasts that run lead times of 1 year or more. In this study, a data-driven model, the support vector machine (SVM) based on the statistical learning theory, was used to predict annual streamflow volume with a 1-year lead time. Annual average oceanic–atmospheric indices consisting of the Pacific decadal oscillation, North Atlantic oscillation (NAO), Atlantic multidecadal oscillation, El Niño southern oscillation (ENSO), and a new sea surface temperature (SST) data set for the ‘Hondo’ region for the period of 1906–2006 were used to generate annual streamflow volumes for multiple sites in the Gunnison River Basin and San Juan River Basin, both located in the Upper Colorado River Basin. Based on the performance measures, the model showed very good forecasts, and the forecasts were in good agreement with measured streamflow volumes. Inclusion of SST information from the Hondo region improved the model's forecasting ability; in addition, the combination of NAO and Hondo region SST data resulted in the best streamflow forecasts for a 1-year lead time. The results of the SVM model were found to be better than the feed-forward, back propagation artificial neural network and multiple linear regression. The results from this study have the potential of providing useful information for the planning and management of water resources within these basins. Copyright © 2012 John Wiley & Sons, Ltd." @default.
- W2097432457 created "2016-06-24" @default.
- W2097432457 creator A5014234994 @default.
- W2097432457 creator A5040698421 @default.
- W2097432457 creator A5041092456 @default.
- W2097432457 creator A5079141101 @default.
- W2097432457 creator A5082056046 @default.
- W2097432457 date "2012-05-02" @default.
- W2097432457 modified "2023-10-16" @default.
- W2097432457 title "Using large-scale climatic patterns for improving long lead time streamflow forecasts for Gunnison and San Juan River Basins" @default.
- W2097432457 cites W1500307396 @default.
- W2097432457 cites W1526327218 @default.
- W2097432457 cites W1563088657 @default.
- W2097432457 cites W1566436792 @default.
- W2097432457 cites W1578650557 @default.
- W2097432457 cites W1603712845 @default.
- W2097432457 cites W1968548780 @default.
- W2097432457 cites W1971984535 @default.
- W2097432457 cites W1972885052 @default.
- W2097432457 cites W1974195979 @default.
- W2097432457 cites W1974745025 @default.
- W2097432457 cites W1981251392 @default.
- W2097432457 cites W1985993867 @default.
- W2097432457 cites W1986140246 @default.
- W2097432457 cites W1986635454 @default.
- W2097432457 cites W1993378799 @default.
- W2097432457 cites W1995341919 @default.
- W2097432457 cites W1996374865 @default.
- W2097432457 cites W1997453817 @default.
- W2097432457 cites W1998490326 @default.
- W2097432457 cites W2000618668 @default.
- W2097432457 cites W2001991385 @default.
- W2097432457 cites W2003809610 @default.
- W2097432457 cites W2004041476 @default.
- W2097432457 cites W2007530751 @default.
- W2097432457 cites W2009067114 @default.
- W2097432457 cites W2010199964 @default.
- W2097432457 cites W2010220902 @default.
- W2097432457 cites W2014526681 @default.
- W2097432457 cites W2017547744 @default.
- W2097432457 cites W2018560916 @default.
- W2097432457 cites W2019451733 @default.
- W2097432457 cites W2020097894 @default.
- W2097432457 cites W2030223774 @default.
- W2097432457 cites W2031245149 @default.
- W2097432457 cites W2033158023 @default.
- W2097432457 cites W2037460094 @default.
- W2097432457 cites W2037561329 @default.
- W2097432457 cites W2037918450 @default.
- W2097432457 cites W2037931255 @default.
- W2097432457 cites W2038259075 @default.
- W2097432457 cites W2039091927 @default.
- W2097432457 cites W2041136829 @default.
- W2097432457 cites W2044553211 @default.
- W2097432457 cites W2049391535 @default.
- W2097432457 cites W2055522016 @default.
- W2097432457 cites W2056017484 @default.
- W2097432457 cites W2057970380 @default.
- W2097432457 cites W2060380076 @default.
- W2097432457 cites W2061328952 @default.
- W2097432457 cites W2068689590 @default.
- W2097432457 cites W2069416306 @default.
- W2097432457 cites W2071559765 @default.
- W2097432457 cites W2074021711 @default.
- W2097432457 cites W2076196252 @default.
- W2097432457 cites W2076216055 @default.
- W2097432457 cites W2076664186 @default.
- W2097432457 cites W2079881246 @default.
- W2097432457 cites W2087713497 @default.
- W2097432457 cites W2088313792 @default.
- W2097432457 cites W2094010935 @default.
- W2097432457 cites W2099336108 @default.
- W2097432457 cites W2103688971 @default.
- W2097432457 cites W2104609361 @default.
- W2097432457 cites W2108527489 @default.
- W2097432457 cites W2112566722 @default.
- W2097432457 cites W2114331883 @default.
- W2097432457 cites W2118527969 @default.
- W2097432457 cites W2120683298 @default.
- W2097432457 cites W2121238464 @default.
- W2097432457 cites W2128042370 @default.
- W2097432457 cites W2130091784 @default.
- W2097432457 cites W2131477567 @default.
- W2097432457 cites W2132995696 @default.
- W2097432457 cites W2135147683 @default.
- W2097432457 cites W2153014583 @default.
- W2097432457 cites W2155112295 @default.
- W2097432457 cites W2155728345 @default.
- W2097432457 cites W2156909104 @default.
- W2097432457 cites W2160203977 @default.
- W2097432457 cites W2165937826 @default.
- W2097432457 cites W2166886587 @default.
- W2097432457 cites W2171330319 @default.
- W2097432457 cites W2172836921 @default.
- W2097432457 cites W2174461843 @default.
- W2097432457 cites W2177917522 @default.
- W2097432457 cites W2178553074 @default.
- W2097432457 cites W3017323153 @default.