• Journal of Korea Water Resources Association
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• v.46 no.1
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• pp.59-71
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• 2013

The lack of sufficient flood data being kept across Korea has made it difficult to assess reliable estimates of the design flood while relatively sufficient rainfall data are available. In this regard, a rainfall simulation based derivation technique of flood frequency curve has been proposed in some of studies. The main issues in deriving the flood frequency curve is to develop the rainfall simulation model that is able to effectively reproduce extreme rainfall. Also the rainfall-runoff modeling that can convey uncertainties associated with model parameters needs to be developed. This study proposes a systematic approach to fully consider rainfallrunoff related uncertainties by coupling a piecewise Kernel-Pareto based multisite daily rainfall generation model and Bayesian HEC-1 model. The proposed model was applied to generate runoff ensemble at Daechung Dam watershed, and the flood frequency curve was successfully derived. It was confirmed that the proposed model is very promising in estimating design floods given a rigorous comparison with existing approaches.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.414-414
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• 2015

최근 지구온난화로 인한 기상변동성 증가로 인해 극한기후현상의 발생빈도가 점차 증가하고 있으며 유역단위의 수자원을 효율적으로 운영하는데 문제점을 해소하고자 다양한 측면에서 체계적인 수자원 운영을 위한 연구가 이루어지고 있다. 수공구조물을 설계하는데 있어서 가장 일반적인 가정 사항은 수문모형에 사용되는 강우의 빈도와 유출의 빈도가 동일하다는 가정에 근거한다. 즉, 유역의 초기함수조건, 강우강도, 강우의 시간적 분포와 관계없이 동일한 빈도로 고려되는 문제점이 있다. 이러한 점에서 비교적 장기간의 자료를 확보하고 있는 계측유역에 대해서 다변량 확률밀도함수를 적용하여 비선형관계를 고려한 수문빈도해석기법을 개발하고자 한다. 본 연구에서는 이변량 분석기법(bivariate analysis) 중 전통적인 이변량 분포에 비해 주변분포형(marginal distribution)을 자유롭게 선택할 수 있는 장점이 있는 추계학적 Copula 모형을 활용하여 댐 및 저수지 상류유역의 강우량과 유입량을 대상으로 이변량 분석을 수행하고자 한다. 최종적으로 비선형 관계에 있는 강수량과 유출량 사이에 이변량 빈도해석 모형을 개발하고 기존 해석방법과의 종합적인 비교를 실시하였다.

• Journal of the Korean Society of Safety
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• v.29 no.6
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• pp.104-110
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• 2014

The Han River is the only waterway in Korea where estuary is not blocked by dykes so that tidal water is flowing in and out through the tidal reach. The extreme tidal range in the Yellow Sea causes an intense flood current, stretching over horizontal extents of tens of kilometers into the rivers. To elucidate the flow reversal by discharge conditions and transient tidal level in the Han river, numerical simulations were conducted under 7 boundary conditions for two days with 10 minute time step. As the flow conditions changed from low discharge and high tidal difference to high discharge and low tidal difference, the flow reversals became weaker and the velocity of forward flow direction became higher due to the increased flow momentums and decreased tidal differences. In the case of normal flow, the maximum reverse velocity was 0.4 m/s, which was equivalent to the maximum forward velocity. In addition, the pattern of the development and decay of forward and reverse flow was presented.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.479-485
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• 1999

This study was conducted to derived design floods by Generalized Extreme Value(GEV) distributiion for the annual maximum series at ten watersheds along Han, Nagdong, Geum , Yeongsan and Seomjin river systems. Adequency for the analysis of flood data used in this study was established by the test of Independence, Homogeneity , detection of Outliers. Coefficient of variation , skewness and kurtosis were calculated by the L-Moment, and LH-Moment ratio respectively. Parameters were estimated by the Method of L-Method of LH-Moment. Design floods obtained by Method of L-Moments and LH-Moments using different methods for plotting positions in GEV distributions and were compared with those obatined using the Method of L-Moments and LH-Moments by the Relative Mean Errors and Realtive Absoulte Errors. It was found that desgin floods derived by the method of L-Moments and LH-Moments using Cunnane plotting position foumula in the GEV distribution are much closer to those of the observed data in comparison with those obtained by methods of L-moments and LH-moments using the other formula for poltting postions from the viewpoint of Relative Mean Errors and Relative Absoulte Errors. In view of the fact that hydraulic structures indcluding dams and levees are generally usiong design floods with the return period of two hundred years or so, design floods derived by LH-Moments are seemed to be more reasonable than those of L-Moments in the GEV distribution.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1467-1471
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• 2009

홍수사상은 크게 첨두홍수량, 홍수용적, 지속기간 등과 같은 서로 상관된 세 가지 요소로 구성되어 있다. 그러나 그동안 홍수의 규모와 크기를 판단하고 예측하기 위하여 수행되어 온 홍수빈도 해석에서는, 서로 상관되어있는 요소들 간의 관계를 고려하지 않은 채 주로 첨두홍수량 하나만을 가지고 단변량 빈도 해석을 수행하였다. 이와 같은 단변량 홍수빈도 해석은 특정 홍수의 특성을 종합적으로 표현하는 데 한계를 가지고 있다. 따라서 본 연구에서는 홍수빈도 해석에 있어 첨두홍수량뿐만 아닌 홍수용적까지도 함께 고려하였다. 소양강댐의 35개년 일유입량 자료를 대상으로 홍수사상을 각각의 강우량 자료와 연계하여 분리한 후 Gumbel 혼합모형을 적용하여 이변량 홍수빈도 해석을 수행함으로써 과거의 극한 홍수사상을 평가 분석하였다. 이변량 빈도해석을 수행하여 홍수사상 요소들 간의 결합분포, 결합 재현기간 등을 추정하였다. 단변량 홍수빈도 해석 결과와 비교함으로써 특정 홍수에 대한 홍수심도를 분석하는 등 극한 홍수사상 평가를 위한 이변량 홍수빈도 해석기법의 적용성에 관하여 검토하였다. 이러한 연구 결과는 기존의 제방 중심 치수사업의 대안으로 제시된 유역종합치수계획에서 선정된 다양한 홍수방어 시설들의 설계 및 운영, 치수효과 평가 등에 유용하게 적용될 수 있을 것이다.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.2
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• pp.9-17
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• 2011

Based on the statistical annual report, there are 17,649 reservoirs are operating for the purpose of agricultural water supply in Korea. 58 % of entire agricultural reservoirs had been constructed before 1948 which indicate the termination of required service life and rest of those reservoirs have also exposed to the dam break risk by extreme flood event caused by current ongoing climate change. To prevent damages from dam failure accident of these risky small size dams, it is necessary to evaluate and manage the structural and hydrological safety of the reservoirs. In this study, a simplified evaluation method for hydrologic safety of dam is suggested by using Rational and Creager formula. Hydrologic safety of small scale dams has evaluated by calculating flood discharge capacity of the spillway and compares the results with design frequency of each reservoir. Applicability and stability of suggested simplified method have examined and reviewd by comparing the results from rainfall-runoff modeling with dam break simulation using HEC-HMS. Application results of developed methodology for three sample reservoirs show that simplified assessment method tends to calculate greater inflow to the reservoirs then HEC-HMS model which lead lowered hydrologic safety of reservoirs. Based on the results of application, it is expected that the developed methodology can be adapted as useful tool for small scale reservoir's hydrologic safety evaluation.

• Water for future
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• v.52 no.8
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• pp.56-66
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• 2019

Nepal is bestowed with abundant water. With more than 1500 mm average annual rainfall in the country, a vast quantity of underutilized groundwater in the Terai belt, and the water stored in snowcaps in the Himalayas, aquifers in the mountains and glacial lakes, Nepal is potentially in an advantageous position in terms of per capita availability. However, low emphasis in management aspect of water and high emphasis in infrastructural developments related to water resources management has resulted in conversion of water in Nepal from a resource to a burden. The global climate change, reduction in number of rainy days, increase in intensity of rainfall during wet monsoon season, encroachment of river banks for settlement, inadequate release of environmental flows from hydropower plants, and attempt to tame the mighty and high velocity rivers of Nepal have resulted in increasing number of water induced disasters (flood and landslide), rise in conflict between local residents and hydropower developers, higher number of devastating landslides, and in some extreme cases mass migration of residents resulting in climate refugees. There is a ray of hope; the awareness level of the people regarding sustainable use of water resources is increasing, the benefit sharing mechanism is gradually being implemented, the role of interdisciplinary and integrated water resources management is appreciated at a higher level and the level of preparedness against flood and landslides is at a higher degree compared to a couple of decades ago. With the use of renewable energy sources, the possibilities for sustainable and productive use of water are on the rise in Nepal.

• Journal of Korea Water Resources Association
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• v.48 no.7
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• pp.567-579
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• 2015

This study performed the non-stationary flood frequency analysis considering time-varying parameters of a probability density function. Also, return period and risk under non-stationary condition were estimated. A stationary model and three non-stationary models using Generalized Extreme Value(GEV) were developed. The only location parameter was assumed as time-varying parameter in the first model. In second model, the only scale parameter was assumed as time-varying parameter. Finally, the both parameters were assumed as time varying parameter in the last model. Relative likelihood ratio test and Akaike information criterion were used to select appropriate model. The suggested procedure in this study was applied to eight multipurpose dams in South Korea. Using relative likelihood ratio test and Akaike information criterion it is shown that the inflow into the Hapcheon dam and the Seomjingang dam were suitable for non-stationary GEV model but the other six dams were suitable for stationary GEV model. Also, it is shown that the estimated return period under non-stationary condition was shorter than those estimated under stationary condition.

• Ecology and Resilient Infrastructure
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• v.9 no.2
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• pp.83-92
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• 2022

The 2020 summer extreme flood severely disturbed the riparian ecosystem of the Seomjin River. Some trees were killed by the flood impact, whereas others have recovered through epicormic regeneration after the disturbance. At the same time, several tree individuals newly germinated. This research aimed to explain the recovery of the riparian ecosystem by spatial proximity between each tree individual of different characteristics, such as "dead", "recovered", and "newly germinated". A spatial point pattern analysis based on K and g-functions revealed that the newly germinated trees and the existing trees were distributed in the spatially clumping patterns. However, further detailed analysis revealed that the new trees were statistically less attracted to the recovered trees than the dead trees, implying competitive interactions hidden in the facilitative interactions. Habitat amelioration by the existing trees positively affected the growth of the new trees, while "living" existing trees were competing with the new trees for resources. This research is expected to provide new knowledge in this era of rapid climate change, which likely induces stronger and more frequent natural disturbance than before. Environmental factors have been widely used for ecosystem modeling, but species interactions, represented by the relative spatial distribution of plant individuals, are also valuable factors explaining ecosystem dynamics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.303-314
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• 2020

The hydrological characteristics of watersheds and hydraulic systems of urban and river floods are highly nonlinear and contain uncertain variables. Therefore, the predicted time series of rainfall-runoff data in flood analysis is not suitable for existing neural networks. To overcome the challenge of prediction, a NARX (Nonlinear Autoregressive Exogenous Model), which is a kind of recurrent dynamic neural network that maximizes the learning ability of a neural network, was applied to forecast a flood in real-time. At the same time, NARX has the characteristics of a time-delay neural network. In this study, a hydrological model was constructed for the Taehwa river basin, and the NARX time-delay parameter was adjusted 10 to 120 minutes. As a result, we found that precise prediction is possible as the time-delay parameter was increased by confirming that the NSE increased from 0.530 to 0.988 and the RMSE decreased from 379.9 ㎥/s to 16.1 ㎥/s. The machine learning technique with NARX will contribute to the accurate prediction of flow rate with an unexpected extreme flood condition.