• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.671-680
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• 2019

Many researches illustrated that the magnitude and frequency of hydrological event would increase in the future due to changes of hydrological cycle components according to climate change. However, few studies performed quantitative analysis and evaluation of future rainfall in North Korea, where the damage caused by extreme precipitation is expected to occur as in South Korea. Therefore, this study predicted the extreme precipitation change of North Korea in the future (2020-2060) compared to the current (1981-2017) using stationary and nonstationary frequency analysis. This study conducted nonstationary frequency analysis considering the external factors (mean precipitation of JFM (Jan.-Mar.), AMJ (Apr.-Jun.), JAS (Jul.-Sept.), OND (Oct.-Dec.)) of the HadGEM2-AO model simulated according to the Representative Concentration Pathway (RCP) climate change scenarios. In order to select external factors that have a similar tendency with extreme rainfall events in North Korea, the maximum annual rainfall data was obtained by using the ensemble empirical mode decomposition (EEMD) method. Correlation analysis was performed between the extracted residue and the external factors. Considering selected external factors, nonstationary GEV model was constructed. In RCP4.5, four of the eight stations tended to decrease in future extreme precipitation compared to the present climate while three stations increased. On the other hand, in RCP8.5, two stations decreased while five stations increased.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.647-655
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• 2019

Although problems such as river management and flood control have occurred continuously in the Imjin and Bukhan river basin, which are shared by South and North Korea, efforts to manage the basin have not been carried out consistently due to limited cooperation. As the magnitude and frequency of hydrologic phenomena are changing due to global climate change, it is necessary to prepare countermeasures for the rainfall variation in the shared river basin area. Therefore, this study was aimed to project future changes in extreme precipitation in South-North Korea shared river basin by applying 13 Global Climate Models (GCM). Results showed that the probability rainfall compared to the reference period (1981-2005) of the shared river basin increased in the future periods of 2011-2040, 2041-2070 and 2071-2100 under the Representative Concentration Pathways (RCP)4.5 and RCP8.5 scenarios. In addition, the rainfall frequency over the 20-year return period was increased in all periods except for the future periods of 2041-2070 and 2071-2100 under the RCP4.5 scenario. The extreme precipitation in the shared river basin has increased both in magnitude and frequency, and it is expected that the region will have a significant impact from climate change.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1183-1192
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• 2020

Economic analysis is a basic step in establishing disaster mitigation measures, but it is difficult to verify the results due to uncertainty. Therefore, the scope of investigation and analysis is wide. However, it is difficult to predict the amount of damage caused by flooding because the collection of relevant data is limited in the ungauged basin. In this study, distributed runoff analysis and flooding analysis were performed, and a method of estimating the amount of flood damage in the ungauged basin was proposed using collectible social and economic indicators and flood analysis results. For distributed runoff analysis and flooding analysis, GRM (Grid based Rainfall-runoff Model) and G2D (Grid based 2-Dimensional land surface flood model) developed by Korea Institute of Civil engineering and Building Technology were used. The method of substituting collectible social and economic indicators into the simple method and improvement method was used to estimate the amount of flood damage. As a result of the study, it was possible to estimate the amount of flood damage using satellite data and social and economic indicators in the ungauged basin.