River Basins In Korea Research Articles

Improving Water Supply Outlook in Korea with Ensemble Streamflow Prediction

The purpose of this study is to propose an alternative forecasting approach for improving the current water supply outlook in Korea. Using a rainfall-runoff model, the existing technique for the water supply outlook in Korea produces monthly low, average, and high runoff forecasts. The proposed technique is called Ensemble Streamflow Prediction (ESP), and is currently implemented by the National Weather Service in the U.S.A. ESP appears particularly valid in Korea where the historical rainfall record is much more comprehensive than the historical streamflow record. This study applies ESP to runoff forecasting for a river basin in Korea to examine its applicability. An ensemble of one-month ahead runoff forecasts at the Gongju gauging station in the Keum River basin, Korea, was generated for each month. The resulting ESP forecasts were compared with the corresponding observed runoff data as well as the existing forecasts. Although this study is limited to one case study, the following conclusions can be made: (1) the ESP technique dominates the existing forecasting techniques in terms of both systematic and random errors; and (2) ESP is more accurate when high flows occur.

Comparison of simple runoff models used in Korea for small watersheds

This study analysed runoff characteristics for three small watersheds in the Su-Young River basin in Korea using the storage function method, the linear reservoir cascade model, and the discrete linear input–output model. The models performed well for the watersheds. The runoff analysis of the observed flood events showed that the storage function method was the most accurate of the three, and was followed by the linear reservoir cascade model and the discrete linear input–output model. Copyright © 1999 John Wiley & Sons, Ltd.

Multiple reservoir system operational planning using multi-criterion decision analysis

Reservoir system operators must consider multiple quantitative and qualitative operational objectives with varying degrees of importance. A two-stage procedure combining multi-objective optimization and multi-criterion decision analysis techniques is presented for reservoir system operational planning. Objectives are divided into primary and secondary groups. In the first stage of the procedure, primary quantitative operational objectives are used to generate non-dominated alternatives via multi-objective optimization using successive linear programming and the ε-constraint method. In the second stage, primary and secondary operation objectives are combined within multi-criterion decision techniques to select the most preferred alternatives from the generated set. Four multi-criterion decision analysis techniques were evaluated in this study. The two-stage procedure is demonstrated by application to the Han River Basin in Korea.

らく東江水系（韓国）における河川水質汚濁とそのモニタリングの現状

River pollution in a developing country who has already took off for industrialization was studied. The study site was Naktong River basin in Korea. Major factors for the pollution were analyzed and problems associated with monitoring were pointed out. The pollution in Naktong River basin was not spread over the wide range of the stream and only a tributary running through the vicinity of Daegu, Geumho River, was polluted seriously by the activity around the city. The pollution was largely dependent on flow rate of Geumho river ; i.e. serious pollution was noted only in the low water. Also, the pollution in the main stream was observed only in the downstream of the junction of Geumho R. into Naktong R. for a short range by the self purification. Monitoring of the water, especially for chemical analyses such as BOD and COD was unreliable compared to flow rate measurement. The necessity of the training for chemical analysis and increase in the number of monitoring was pointed out.