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- W1738673657 abstract "No study has systematically evaluated streamflow modelling between monthly and daily time scales. This study examines streamflow from seven watersheds across the USA where five different precipitation products were used as primary input into the Soil and Water Assessment Tool (SWAT) to generate simulated streamflow. Time scales examined include monthly, dekad (10 days), pentad (5 days), triad (3 days), and daily. The seven basins studied are the San Pedro (Arizona), Cimarron (north-central Oklahoma), mid-Nueces (south Texas), mid-Rio Grande (south Texas and northern Mexico), Yocano (northern Mississippi), Alapaha (south Georgia), and mid-St. Francis (eastern Arkansas). The precipitation products used to drive simulations include rain gauge, NWS Multisensor Precipitation Estimator, Tropical Rainfall Measurement Mission (TRMM), Multi-Satellite Precipitation Analysis, TRMM 3B42-V6, and Climate Prediction Center Morphing Method (CMORPH). Understanding how streamflow varies at sub-monthly time scales is important because there are a host of hydrological applications such a flood forecast guidance and reservoir inflow forecasts that reside in a temporal domain between monthly and daily time scales. The major finding of this study is the quantification of a strong positive correlation between performance metrics and time step at which model performance deteriorates. Better performing simulations, with higher Nash–Sutcliffe values of 0.80 and above can support modeling at finer time scales to at least daily and perhaps beyond into the sub-daily realm. These findings are significant in that they clearly document the ability of SWAT to support modeling at sub-monthly time steps, which is beyond the capability for which SWAT was initially designed. Copyright © 2012 John Wiley & Sons, Ltd." @default.
- W1738673657 created "2016-06-24" @default.
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- W1738673657 date "2012-03-19" @default.
- W1738673657 modified "2023-09-23" @default.
- W1738673657 title "Temporal analysis of Soil and Water Assessment Tool (SWAT) performance based on remotely sensed precipitation products" @default.
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- W1738673657 doi "https://doi.org/10.1002/hyp.9252" @default.
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