• Journal of Korea Water Resources Association
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• v.48 no.12
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• pp.1037-1049
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• 2015

The most of natural disasters that occur in North Korea are flood, typhoon and damage from heavy rain. The damage caused by those disasters since the mid-1990s is aggravating North Korea's economic difficulties every year. By recognizing the seriousness of the damages from the floods, the North Korean government has carried out the river maintenance, farmland restoration, land readjustment and afforestation projects since the last-1990s, but it has failed preventing the damages. In order to estimate the degree of flood risk regarding damage from chronic floods that occur inveterately in North Korea, this research conducted an additional simulation for rainfall-runoff analysis to reflect the characteristics of the ungauged area that make foreign countries hard to obtain the hydrological data and do not open the topographical data to public. In addition, this research estimates the degree of flood risk by selecting the factors of the hazard, exposure and vulnerability by following the standards of the Intergovernmental Panel on Climate Change (IPCC).

• Journal of Wetlands Research
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• v.26 no.2
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• pp.147-159
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• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.325-340
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• 2008

This study employs Bayesian multiple regression analysis using the ordinary least squares method for regional low flow frequency analysis. The parameter estimates using the Bayesian multiple regression analysis were compared to conventional analysis using the t-distribution. In these comparisons, the mean values from the t-distribution and the Bayesian analysis at each return period are not significantly different. However, the difference between upper and lower limits is remarkably reduced using the Bayesian multiple regression. Therefore, from the point of view of uncertainty analysis, Bayesian multiple regression analysis is more attractive than the conventional method based on a t-distribution because the low flow sample size at the site of interest is typically insufficient to perform low flow frequency analysis. Also, we performed low flow prediction, including confidence interval, at two ungauged catchments in the Nakdong River basin using the developed Bayesian multiple regression model. The Bayesian prediction proves effective to infer the low flow characteristic at the ungauged catchment.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.955-968
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• 2021

A water resource plan is routinely based on a natural flow and can be estimated using observed streamflow data or a long-term continuous rainfall-runoff model. However, the watershed with the natural flow is very limited to the upstream area of the dam. In particular, for the ungauged watershed, a rainfall-runoff model is established for the gauged watershed, and the model is then applied to the ungauged watershed by transferring the associated parameters. In this study, the GR4J rainfall-runoff model is mainly used to regionalize the parameters that are estimated from the 14 dam watershed via an optimization process. In terms of optimizing the parameters, the Bayesian approach was applied to consider the uncertainty of parameters quantitatively, and a number of parameter samples obtained from the posterior distribution were used for the regionalization. Here, the relationship between the estimated parameters and the topographical factors was first identified, and the dependencies between them are effectively modeled by a Copula function approach to obtain the regionalized parameters. The predicted streamflow with the use of regionalized parameters showed a good agreement with that of the observed with a correlation of about 0.8. It was found that the proposed regionalized framework is able to effectively simulate streamflow for the ungauged watersheds by the use of the regionalized parameters, along with the associated uncertainty, informed by the basin characteristics.

• Magazine of the Korean Society of Agricultural Engineers
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• v.19 no.2
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• pp.4377-4384
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• 1977

The curvilinear hydrograph can be replaced by an equivalent triangular hydrograph which is more easily constructed and, for routing through reservoirs or stream channels, gives results about as accurate as those obtained using the curvilinear hydrograph. A synthetic hydrograph is prepared using the data from a number of watersheds to develop a dimensionless unit hydrograph applicable to ungauged watersheds. The dimensionless unit hydrograph for the NakDong River Basin was prepared from the unit hydrographs of a variety of nine subwatersheds. The equation for the peak rate of flow (unit volume of runoff in 1.0mm) was derived as {{{{ { q}_{p } = { 0.21AR} over { {T }_{p } } }}}} The results summarized in this study are as follows: 1) It found that the watershed lag time (Lg, hrs) could be expressed by Lg=0.253(L.Lca)0.4171 The product L.Lca is a measure of the size and shape of the watershed. Correlation coefficient for Lg was 0.97 which defined with high significance. 2) The base length of the unitgraph, in hours, was adopted as Tb=17.51+2.073Lg with high significant correlation coefficient, 0.92. 3) Time in hour from start of rise to peak rate (TP) generally occured at the position of 0.289 Tb with some indication of higher values for larger watershed. 4) Triangular hydrograph is a dimensionless unitgraph prepared from the 40 unitgraphs. The equation is shown as {{{{ { q}_{p } = { K.A.R} over { { T}_{p } } }}}}. The constant K=0.21 is defined to NakDong River basin. 5) In the light of the results analyzed in this study, average errors in the peak discharge of the Trjangular unitgraph was estimated as 5.34 percent to the peak of observed average unitgraph. Each ordinate of the Triangular unitgraph was approached closely to the observed one.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.1
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• pp.77-84
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• 2011

The methods of the rational formula and Kajiyama formula have been widely used for estimating the peak flood for design to all kind of hydraulic structure. However, there are many limitations and we have to apply these methods to ungauged basin. These methods require to calculate the Probable Maximum Precipitation (PMP) before determining the Probable Maximum Flood (PMF). Creager's method (Creager et al., 1945) is a kind of estimation of specipic flood and this method provided nonlinear equations based on relationship between the drainage area and PMF in order to calculate the PMF of multipurpose dams over medium-sized. But this method has not much applied in Korea. Creager's coefficient is not clear about its application because this method has never been applied to dams in Korea. Based on the PMP for rainfull-runoff models with the PMF of small and larger dams in this research, the range and standard of Creager's coefficients with parameters are proposed to apply basin areas in Korea.

• Journal of Korea Water Resources Association
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• v.41 no.11
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• pp.1107-1121
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• 2008

The simple equation of GIUH are frequently used in many researches instead of the derived equation of GIUH. However it is still unknown whether the simple equation of GIUH is adaptable for estimating IUHs for basins with various geomorphologic conditions. To verify the applicability of the simple equation of GIUH, in this research, four basins which were Bangrim, Sanganmi, Museong, and Byeongcheon were selected and each basin was assumed as the third and fourth stream order basin according to variable resolutions. After than, IUHs were estimated using the derived and simple equations of GIUH. Eight to sixteen hydrographs were estimated from the each IUH, compared with observed graphs. In case of that the basin is assumed as a third order stream, the derived equation underestimated the peak flows while the simple equation overestimated them. When the basin is assumed as a fourth order stream, the simple equation generally overestimated the peak flows whereas the derived equation produced peak flows good agreement with the observed peak flow. Moreover, the simple equation showed various deviations in accuracy whereas the derived equation produced stable results. Based on the fact found from this research, it can be concluded that the derived equation of GIUH brings better results than the simple equation of GIUH to estimate IUHs for ungauged basins.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.829-833
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• 2006

갈수량(low flow)은 과거 자연상태 하천에서 갈수기에 흘렀던 유량으로서 자연과 사람이 공유할 수 있는 최소한의 유량이며, 이수측면에서 하천수의 공급능력을 평가하여 취수량을 설정하는 기준 유량이다. 일본과 국내에서는 지금까지 일유량의 유황곡선(flow duration curve)을 분석하여 평균갈수량, 기준갈수량 등을 결정하고 이를 갈수량의 지표로 이용하여 왔다. 그러나 미국과 영국 등에서는 7일 동안의 유량을 통계분석하여 만든 10년빈도 7일 최저유량$(7Q_{10})$을 갈수량 지표로 사용하고 있다. 본 연구에서는 위의 두 지표를 실험을 통해 비교하여 서로의 장단점을 우선 고찰하여 보았다. 갈수량 산정을 위해서는 과거의 관측 유량자료가 필요하나 국내에는 수위 관측시설이 한정되어 있을 뿐 아니라 홍수기에 비해 갈수기 자료가 턱없이 부족하여 갈수량 산정에 많은 어려움을 겪고 있다. 국내에서는 대부분 유역면적을 이용한 비유량법으로 계측유역으로부 터 미계측유역의 갈수량을 산정하고 있다. 본 연구에서는 미계측유역(ungauged basin)의 갈수량을 산정하기 위한 방법으로 지역회귀기법(regional regression method)을 국내에 적용하여 보았다. 이를 위해 9개 수위관측소 유역과 7개 댐 유역의 과거 유량자료를 이용하였으며, 교차검증(cross validation)을 통해 갈수량 산정결과의 정확도 검증을 실시하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1216-1220
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• 2006

최근 들어 기상이변으로 인해 집중호우가 빈번히 발생하여 막대한 홍수피해를 야기하고 있으며, 이에 자연재해에 대한 방재대책의 중요성 및 수공구조물들의 설계빈도를 상향조정하는 등의 대책마련이 절실히 요구되고 있는 실정이다. 특히 2002년 여름 강릉지역에 발생한 태풍 '루사'로 인한 집중호우는 기존 PMP(가능 최대강수량) 규모를 초과하는 사상 초유의 24시간 최대 강수량(880mm)을 기록하여 기존 댐 등과 같은 수공구조물의 설계기준에 대한 재고가 불가피 하게 되었다. 이에 본 연구에서는 미계측 유역인 상관저수지 유역을 대상으로 지속시간별 PMP를 산정한 후 임계지속시간을 고려한 PMF(가능최대홍수량)를 산정하여 유역내 대표적인 수공구조물인 저수지의 수문학적 치수안정성 여부를 검토하였다. 분석 대상유역인 상관저수지 유역의 PMP는 전국 전계절별 PMP도로부터 호우중심의 PMP와 유역중심의 PMP를 동일하게 하여 지속시간별 PMP를 산정하였다. 산정된 PMP로부터 Huff의 4분위법을 이용하여 강우를 시간분포 시킨 후 상관저수지 유역의 PMF를 산정하였으며, 이 때 이용된 유역의 홍수량추정 기법으로는 Clark 단위도법이다. 또한 본 연구에서는 수공구조물의 치수안정성을 검토하기 위하여 HEC-5모형을 이용한 저수지 홍수추적을 실시하였으며, 검토 결과 상관저수지의 수문학적 안정성은 확보된 것으로 분석되었다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.2
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• pp.57-65
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• 1986

The need of forecasting river flows arised whenever a river authority must make controls to protect the life and property from the flood and maintain the adequate flows for water use. This study is on the real time flood forecasting from the gauged and ungauged rainfall input and identification of second-order autoregressive(AR(2)) which is used as system model. A Kalman filter is used to obtain the values of the system parameters needed for the optimal control strategy. This system model was applied to the data at the Naiu gauging station in Young san river basin to check the accuracy and efficiency of prediction. One step ahead prediction is checked by stochastic analysis and the order of autoregressive model is proved to be satisfied, Discussions on interesting features of the model are presented.