• Water for future
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• v.10 no.1
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• pp.53-70
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• 1977

The analysis performed here is aimed to increase the familiarity of hydrologic process especially for the small basins which are densely gaged. Kyung An and Mu Shim river basins are selected as a representative basin according to the criteria which UNESCO has established back in 1964 and being operated under the auspice of Ministry of Construction. The data exerted from these basins is utilized for the determination of characteristics of procipitation and runoff phenomena for the small basin, which is considered as a typical Korean samall watershed. The study found that the areal distribution of preciptation did not show any significant deviation from the point rainfall. Since the area studied is less than 20 km#, the pointrainfall may be safely utilized as a representative value for the area. Also the effect of elevation on the precipitation has a minor significance in the small area where the elevation difference is less than 200m. The methodology developed by Soil Conservation Service for determination of runoff value from precipitation is applied to find the suitability of the method to Korean river basin. The soil cover complex number or runoff curve number was determined by comsidering the type of soil, soil cover, land use and other factors such as antecedent moisture content. The average values of CN for Kyung An and Mushim river basins were found to be 63.9 and 63.1 respectively under AMC II, however, values obtained from soil cover complex were less than those from total precipitation and effective precipitation about 10-30%. It may be worth to note that an attention has to be paid in application of SCS method to Korean river basin by adjusting 10-30% increase to the value obtained from soil cover complex. Finally, the design flood hydrograph was consturcted by employing unit hydrograph technique to the dimensionless mass curve. Also a stepwise multiple regression was performed to find the relationship between runoff and API, evapotranspiration rate, 5 days antecedentprecipitation and daily temperature.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.3
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• pp.1-19
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• 2014

This study aims to assess the slope stability variation of Jeonbuk drainage areas by RCM model outputs based on A1B climate change scenario and infinite slope stability model based on the previous research by Choi et al.(2013). For a large-scale slope stability analysis, we developed a GIS-based database regarding topographic, geologic and forestry parameters and also calculated daily maximum rainfall for the study period(1971~2100). Then, we assess slope stability variation of the 20 sub-catchments of Jeonbuk under the climate change scenario. The results show that the areal-average value of safety factor was estimated at 1.36(moderately stable) in spite of annual rainfall increase in the future. In addition, 7 sub-catchments became worse and 5 sub-catchments became better than the present period(1971~2000) in terms of safety factor in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.2
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• pp.72-78
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• 2009

The demand for rainfall data in gridded digital formats has increased in recent years due to the close linkage between hydrological models and decision support systems using the geographic information system. One of the most widely used tools for digital rainfall mapping is the PRISM (parameter-elevation regressions on independent slopes model) which uses point data (rain gauge stations), a digital elevation model (DEM), and other spatial datasets to generate repeatable estimates of monthly and annual precipitation. In the PRISM, rain gauge stations are assigned with weights that account for other climatically important factors besides elevation, and aspects and the topographic exposure are simulated by dividing the terrain into topographic facets. The size of facet or grid cell resolution is determined by the density of rain gauge stations and a $5{\times}5km$ grid cell is considered as the lowest limit under the situation in Korea. The PRISM algorithms using a 270m DEM for South Korea were implemented in a script language environment (Python) and relevant weights for each 270m grid cell were derived from the monthly data from 432 official rain gauge stations. Weighted monthly precipitation data from at least 5 nearby stations for each grid cell were regressed to the elevation and the selected linear regression equations with the 270m DEM were used to generate a digital precipitation map of South Korea at 270m resolution. Among 1.25 million grid cells, precipitation estimates at 166 cells, where the measurements were made by the Korea Water Corporation rain gauge network, were extracted and the monthly estimation errors were evaluated. An average of 10% reduction in the root mean square error (RMSE) was found for any months with more than 100mm monthly precipitation compared to the RMSE associated with the original 5km PRISM estimates. This modified PRISM may be used for rainfall mapping in rainy season (May to September) at much higher spatial resolution than the original PRISM without losing the data accuracy.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1403-1407
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• 2005

In order to analyze the water storage of the Daecheong dam after constructing the Yongdam dam situated in upstream, a daily cascaded simulation model for analyzing water storages in the Yongdam-Daecheong dams was developed. Operation scenarios of the Yongdam dam were selected to 8 cases with the combinations of downstream outflows and water supplies to the Jeonju region. Daily water storages in the Daecheong dam was analyzed daily by simulating from 1983 to 2004. The results are summarized as follows. Firstly, water supplies from the Daecheong dam were analyzed to amount $1,964.2Mm^3$ on a yearly average in case without the Yongdam dam. In case with the Yongdam dam, water supplies from the Daecheong dam were analyzed to amount $1,858.7\~1,927.3Mm^3$ in case with downstream outflow of $5\;m^3$ is, and were analyzed to amount $1,994.9\~2,017.8Mm^3$ in case with downstream outflow of $10\;m^3/s $. These values are compared to $1,649Mm^3$ applied in design. Secondly, reservoir use rate which was defined rate of water supply to effective water storage reached $241.3\% in case without the Yongdam dam. In case with the Yongdam dam, reservoir use rate reached $228.3\~236.8\% In case with downstream outflow of $5\;m^3/s$, and reached $245.1\~247.9\% in case with downstream outflow of $10\;m^3/s$. Thirdly, runoff rate which is defined rate of dam inflow to areal rainfall reached $57.3\% in case without the Yongdam dam. In case with the Yongdam dam, reservoir use rate reached $62.0\~68.4\% in case with downstream outflow of $5\;m^3/s$, and reached $64.1\~68.5\% in case with downstream outflow of $10\;m^3/s$. Fourth, in case with downstream outflow of $10\;m^3/s$ is from the Yongdam dam, appropriate water supply amounts to the Jeonju region were analyzed to only $0.50Mm^3/day$ from the daily simulation of water storages in the Yongdam dam. Comprehensively, water supply capacity of the Daecheong dam was analyzed to affect in small amounts in spite of the construction of the Yonsdam dam. It is effected to achieve the effective water management of the Yongdam dam and the Daecheong dam by using the developed cascaded model.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.333-346
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• 2024

High-resolution medium-range streamflow prediction is crucial for sustainable water quality and aquatic ecosystem management. For reliable medium-range streamflow predictions, it is necessary to understand the characteristics of forcings and to effectively utilize weather forecast data with low spatio-temporal resolutions. In this study, we presented a comparative analysis of medium-range streamflow predictions using the distributed hydrological model, WRF-Hydro, and the numerical weather forecast Global Data Assimilation and Prediction System (GDAPS) in the Geumho River basin, Korea. Multiple forcings, ground observations (AWS&ASOS), numerical weather forecast (GDAPS), and Global Land Data Assimilation System (GLDAS), were ingested to investigate the performance of streamflow predictions with highresolution WRF-Hydro configuration. In terms of the mean areal accumulated rainfall, GDAPS was overestimated by 36% to 234%, and GLDAS reanalysis data were overestimated by 80% to 153% compared to AWS&ASOS. The performance of streamflow predictions using AWS&ASOS resulted in KGE and NSE values of 0.6 or higher at the Kangchang station. Meanwhile, GDAPS-based streamflow predictions showed high variability, with KGE values ranging from 0.871 to -0.131 depending on the rainfall events. Although the peak flow error of GDAPS was larger or similar to that of GLDAS, the peak flow timing error of GDAPS was smaller than that of GLDAS. The average timing errors of AWS&ASOS, GDAPS, and GLDAS were 3.7 hours, 8.4 hours, and 70.1 hours, respectively. Medium-range streamflow predictions using GDAPS and high-resolution WRF-Hydro may provide useful information for water resources management especially in terms of occurrence and timing of peak flow albeit high uncertainty in flood magnitude.