• Journal of Korea Water Resources Association
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• v.43 no.9
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• pp.789-799
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• 2010

The objective of this study is to suggest an approach for estimating probability rainfall using climate scenario data based GCM and to analyze changes of flood characteristics like probability rainfall, flood quantile and flood water level under climate change. The study area is Namhan river basin. Probability rainfalls which is taken 1440 minutes duration and 100-year frequency are estimated by using IPCC SRES A2 climate change scenario for each time period (S0: 1971~2000; S1: 2011~2040; S2: 2041~2070; S3: 2071~2100). Flood quantiles are estimated for 17 subbasins and flood water level is analyzed in the main channel from the downstream of Chungju dam to the upstream of Paldang dam. Probability rainfalls, peak flow from flood quantile and water depth from flood water level have increase rate in the range of 13.0~15.1 % based S0 (142.1 mm), 29.1~33.5% based S0 ($20,708\;m^3/s$), 12.6~13.6% in each S1, S2 and S3 period, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.495-504
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• 2008

Evapotranspiration (ET) is an important state variable while simulating daily streamflow in hydrological models. In the estimation of ET, for example, when using FAO Penman Monteith equation, the LAI (Leaf Area Index) value reflecting the conditions of vegetation generally affects considerably. Recently in evaluating the vegetation condition as a fixed quantity, the remotely sensed LAI from MODIS satellite data is available, and the time series values of spatial LAI coupled with land use classes are utilized for ET evaluation. Four years (2001-2004) of MODIS LAI was prepared for the evaluation of Penman Monteith ET in the continuous hydrological model, SLURP (Semi-distributed Land Use-based Runoff Processes). The model was applied for simulating the dam inflow of Chungju watershed ($6661.3km^2$) located in the upstream of Han river basin. For four years (2001-2004) dam inflow data and meteorological data, the model was calibrated and verified using MODIS LAI data. The average Nash-Sutcliffe model efficiency was 0.66. The 4 years watershed average Penman Monteith ETs of deciduous, coniferous, and mixed forest were 639.1, 422.4, and 631.6 mm for average MODIS LAI values of 3.64, 3.50, and 3.63 respectively.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.4
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• pp.9-23
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• 2002

The purpose of this research was to develop a model that minimizes time and money for deriving topographical property factors and hydro-meteorological property factors, which are used in interpreting flood flow, and that makes it possible to forecast rainfall-runoff using a least number of factors. That is, the research aimed at suggesting a runoff interpretation method that considers the river branching characteristics but not the topographical and geological properties and the land cover conditions, which had been referred in general. The subject basin of the research was the basin of Yeongcheon Dam located in the upper reaches of the Kumho River. The parameters of the model were derived from the results of abstracting topological properties out of rainfall-runoff observation data about heavy rains and Digital Elevation Modeling(DEM). According to the result of examining calculated peak runoff, the Clark Model and the GIUH Model showed relative errors of 1.9~23.9% and 0.8~11.3%, respectively and as a whole, the peak values of hydrograph appeared high. In addition, according to the result of examining the time when peak runoff took place, the relative errors of the Clark Model and the GIUH Model were 0.5~1 and 0~1 hour respectively, and as a whole, peak flood time calculated by the GIUH Model appeared later than that calculated by the traditional Clark Model.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1067-1078
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• 2018

Water resources projection typically consists of several stages including emission scenarios, global circulation models (GCMs), downscaling techniques, and hydrological models, and each stage is a source of total uncertainty in water resources projection. Several studies proposed methods to quantify the relative contribution of each stage to total uncertainty, and we call such analysis uncertainty decomposition. Uncertainty decomposition enables us to investigate the stages yielding large uncertainties and to establish the uncertainty reduction plan that reflects them. Interactions between stages is one of the important issues to be considered in uncertainty decomposition. This study suggests a new uncertainty decomposition method considering interaction effect. The proposed method has an advantage of decomposing the total uncertainty to the uncertainty from each stage considering both the main and interactions effects. We apply the proposed method to streamflow projection for Chungju Dam basin. The results show that the uncertainties from the main effects are larger than the uncertainties from interaction effects in both summer and winter. Using the proposed uncertainty decomposition method, we show that the GCM stage is the largest source of the total uncertainty in summer and the downscaling technique stage is the one in winter among the following four stages: emission scenarios, GCMs, downscaling techniques, and hydrological models.