Home Trans-Niņo Research Site Index Contact Home Western Climate Home FEEL Research BioMicroMeteorology Trans-Niņo Research TNI Calculator 2006 AGU Presentation TNI Abstract TNI Executive Summary TNI Thesis BasinWide Hydrologics Vitae External Site Links Orion Imaging Corvallis Weather NOLA Oregon Bike Racing Other Links Research Portal Username Password Remember me Lost Password? No account yet? Register Trans-Niņo Executive Summary Written by AMK    Thursday, 31 August 2006 Article Index Trans-Niņo Executive Summary Methods Results Conclusions Recommendations Page 2 of 5 II.  Methods Hydrologic data for the Sprague and Williamson rivers were analyzed for trends and patterns useful to characterize interannual streamflow variability.  Annual runoff ratios, variance ratios, seasonal autocorrelation coefficients, and moving window 25-year average monthly hydrographs were computed for both basins.  This evaluation identified the current character of the hydrologic cycle and allowed a comprehensive understanding of the shifts occurring in the basin. To quantify the basin’s response to large-scale climate variability, six climate indices were evaluated for their association with seasonal streamflow and snow water equivalent (SWE) observations within and in the vicinity of Upper Klamath Basin.  These climate indices are based on atmospheric conditions or sea surface temperatures and are commonly used to monitor the El Niño and other large-scale variations in climate as well as support hydrologic predictions in the western US.  These indices included the well-established Southern Oscillation Index (SOI), the Niño 3.4 sea surface temperature index ,the Multivariate El Niño-Southern Oscillation Index (MEI), the Pacific Decadal Oscillation index (PDO), and the Pacific North American index (PNA), as well as a relatively new index, the Trans-Niño Index (TNI).  The TNI is the only large-scale climate variable strongly associated with hydrologic variability within the Upper Klamath Basin.  This index was updated and revised for use in real-time streamflow prediction models. November through May principal components based regression models were developed to predict Sprague and Williamson seasonal streamflow.  In addition to the conventional variables used (SWE, precipitation, and antecedent streamflow), new variables were identified, which included a groundwater index (Williamson River only), mean areal precipitation, mean areal temperature, and the TNI.  Attention was given to the physical meaningfulness of each variable, month-to-month variable consistency, and overall model performance as measured by the standard error. << Prev - Next >> Last Updated ( Monday, 04 September 2006 )   [ Back ]

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