• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1125-1138
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• 2014

In this study, we applied an advanced non-parametric low-flow frequency analysis using boundary kernel by Representative Concentration Pathways (RCPs) climate change scenarios through Arc-SWAT long-term runoff model simulation at the Gwangdong storage reservoir located in Taeback, Gangwondo. The results show that drought frequency under RCPs was expected to increase due to reduced runoff during the near future, and the variation of low-flow time series was appeared greatly under RCP8.5 scenario, respectively. The result from drought frequency of Median flow in the near future (2030s) compared historic period, the case of 30-year low-flow frequency was increased (the RCP4.5 shows +22.4% and the RCP8.5 shows +40.4%), but in the distant future (2080s) expected increase of drought frequency due to the reduction of low-flow (under RCP4.5: -4.7% and RCP8.5: -52.9%), respectively. In case of Quantile 25% flow time series data also expected that the severe drought frequency will be increased in the distant future by reducing low-flow (the RCP4.5 shows -20.8% to -60.0% and the RCP8.5 shows -30.4% to -96.0%). This non-parametric low-flow frequency analysis results according to the RCPs scenarios have expected to consider to take advantage of as a basis data for water resources management and countermeasures of climate change in the mid-watershed over the Korean Peninsula.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.1
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• pp.89-102
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• 2010

Future uncertainty on water demand caused by future climate condition and water consumption leads a difficulty to determine the reservoir operation rule for supplying sufficient water to users. It is, thus, important to operate reservoirs not only for distributing enough water to users using the limited water resources but also for preventing floods and drought under the unknown future condition. In this study, the reservoir storage is determined in the first stage when future condition is unknown, and then, water distribution to users and river stream is optimized using the available water resources from the first stage decision using 2-stage stochastic linear programming (2-SLP). The objective function is to minimize the difference between target and actual water storage in reservoirs and the water shortage in users and river stream. Hedging rule defined by a precaution against severe drought by restricting outflow when reservoir storage decreases below a target, is also applied in the reservoir operation rule for improving the model applicability to the real system. The developed model is applied in a system with five reservoirs in the Han River basin, Korea to optimize the multi-reservoir system under various future water demand scenarios. Three multi-purposed dams - Chungju, Hoengseong, and Soyanggang - are considered in the model. Gwangdong and Hwacheon dams are also considered in the system due to the large capacity of the reservoirs, but they are primarily for water supply and power generation, respectively. As a result, the water demand of users and river stream are satisfied in most cases. The reservoirs are operated successfully to store enough water during the wet season for preparing the coming drought and also for reducing downstream flood risk. The developed model can provide an effective guideline of multi-reservoir operation rules in the basin.