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http://dx.doi.org/10.3741/JKWRA.2006.39.3.261

Probabilistic Medium- and Long-Term Reservoir Inflow Forecasts (I) Long-Term Runoff Analysis  

Bae, Deg-Hyo (Water Resources Institute, Dept. of Civil & Envirn. Engrg., Sejong University)
Kim, Jin-Hoon (Graduate Student, Dept. of Civil & Envirn. Engrg., Sejong University)
Publication Information
Journal of Korea Water Resources Association / v.39, no.3, 2006 , pp. 261-274 More about this Journal
Abstract
This study performs a daily long-term runoff analysis for 30 years to forecast medium- and long-term probabilistic reservoir inflows on the Soyang River basin. Snowmelt is computed by Anderson's temperature index snowmelt model and potenetial evaporation is estimated by Penman-combination method to produce input data for a rainfall-runoff model. A semi-distributed TOPMODEL which is composed of hydrologic rainfall-runoff process on the headwater-catchment scale based on the original TOPMODEL and a hydraulic flow routing model to route the catchment outflows using by kinematic wave scheme is used in this study It can be observed that the time variations of the computed snowmelt and potential evaporation are well agreed with indirect observed data such as maximum snow depth and small pan evaporation. Model parameters are calibrated with low-flow(1979), medium-flow(1999), and high-flow(1990) rainfall-runoff events. In the model evaluation, relative volumetric error and correlation coefficient between observed and computed flows are computed to 5.64% and 0.91, respectively. Also, the relative volumetric errors decrease to 17% and 4% during March and April with or without the snowmelt model. It is concluded that the semi-distributed TOPMODEL has well performance and the snowmelt effects for the long-term runoff computation are important on the study area.
Keywords
long-term runoff analysis; snowmelt model; potential evaporation; semi-distributed TOPMODEL;
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Times Cited By KSCI : 1  (Citation Analysis)
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