• Journal of Korea Water Resources Association
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• v.50 no.4
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• pp.241-252
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• 2017

This study aims to evaluate applicability of both online and offline parameter calibration techniques on rainfall-runoff modeling using a conceptual lumped hydrologic model. To achieve the goal, the storage function model was selected and then two different automatic calibration techniques: SCE-UA (offline method) and particle filter (online method) were applied to calibrate the optimal parameter sets for 9 rainfall events in the Cheoncheon catchment, upper area of the Yongdam multi-purpose dam. In order to assess reproducibility of hydrographs from the parameter sets of both techniques, the observed discharge of each event was divided into low flow (below average flow) and high flow (over average flow). The results show that the particle filter method, updating the parameters in real-time, provides more stable reproducibility than the SCE-UA method regardless of low and high flow. The optimal parameters estimated by SCE-UA are very sensitive to the selected objective functions used in this study: RMSE and HMLE. In particular, the parameter sets from RMSE and HMLE demonstrate superior goodness-of-fit values for high flow and low flow periods, respectively.

• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.311-321
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• 2009

Long-Term Hydrologic Impact Assessment (L-THIA) was modified to improve runoff and pollutant load prediction for Korean watersheds with changes in land use classification and event mean concentration produced from observed data in Korea. The L-THIA model was linked with SCE-UA, which is one of the global optimization techniques, to automatically calibrate direct runoff. Modified L-THIA model was applied to Gumho River Basins to analyze spatial distribution of nonpoint source pollution. The results of model calibration during 1991~2000 and validation during 1981~1990 for direct runoff represented high model efficiency of 0.76 for calibration and 0.86 for validation. As a results of spatial analysis of nonpoint source pollution, the BOD was mainly loaded from urban area but SS, TN, and TP from agricultural area which is mainly located along the stream. Modified L-THIA model improve its accuracy with minimum imput data and application efforts. From this study, we can find out the L-THIA model is very useful tool to predict direct runoff and pollutant loads from the watershed and spatial analysis of nonpoint source pollution.

• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.245-255
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• 2009

CN values are changed by various surface condition, which is cover type or treatment, hydrologic condition, or percent impervious area, even the same combination of land use and hydrologic soil group. In this study, CN parameters were regionalized for Nakdong River Basin by Long-Term Hydrologic Impact Assessment (L-THIA) coupled with SCE-UA, which is one of the global optimization technique. Six watersheds were selected for calibration (optimization) and periodic validation and two watersheds for spatical validation as ungauged watershed within Nakdong River Basin. Nash-Sutcliffe (NS) values were 0.66~0.86 for calibration, 0.68~0.91 for validation, and 0.60 and 0.85 for ungauged watersheds, respectively. Urban area for the selected watersheds covered high impervious area with 85% for residential area and 92% for commercial/industrial/transportation area. Hydrologic characteristics for crop area was similar to row crop with contoured treatment and poor hydrologic condition. For the forested area, hydrologic characteristics could be clearly distinguished from the leaf types of plant. Deciduous, coniferous, and mixed forest showed low, moderate, and high runoff rates by representing wood with fair and poor hydrologic condition, and wood-grass combination with fair hydrologic condition, respectively. CN parameters from this study could be strongly recommended to be used to simulate runoff for ungauged watershed.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.3
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• pp.3-13
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• 2005

The conceptual rainfall-runoff models are used to predict complex hydrological effects of a basin. However, to obtain reliable results, there are some difficulties and problems in choosing optimum model, calibrating, and verifying the chosen model suitable for hydrological characteristics of the basin. In this study, Genetic Algorithm and SCE-UA method as global optimization methods were applied to compare the each optimization technique and to analyze the application for the rainfall-runoff models. Modified TANK model that is used to calculate outflow for watershed management and reservoir operation etc. was optimized as a long term rainfall-runoff model. And storage-function model that is used to predict real-time flood using historical data was optimized as a short term rainfall-runoff model. The optimized models were applied to simulate runoff on Pyeongchang-river watershed and Bocheong-stream watershed in 2001 and 2002. In the historical data study, the Genetic Algorithm and the SCE-UA method showed consistently good results considering statistical values compared with observed data.

• Journal of Korea Water Resources Association
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• v.45 no.11
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• pp.1169-1186
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• 2012

Storage function method has been used for flood forecasting in the major rivers in Korea, however, the researches on the relationship between the parameters and runoff characteristics was not sufficient. In addition, there has been a controversy about the optimized parameters without the consideration of the physical characteristics of the basin. Therefore, in this study, the SCE-UA method is used to optimize the parameters and the proposed method was applied with two stage optimization in the Jeongseon and Yeongwol watersheds located in the most upstream in the South Han river. The contour map was developed to investigate parameters and the error surface calculated from the runoff. The proposed parameters is to provide a range of the possible parameter set in a watershed, rather than a specific value. However, the applicability is examined using the average value of the proposed ranged parameters. In this study, the criticism about the optimization technique to find an optimal value having no physical meaning on a watershed is tried to avoid. The objective of this study is to provide a range of parameters for the flood forecasting model and the intuition about the behavior of the parameters, so the efficiency of flood forecasting is increased.

• Proceedings of the Korea Water Resources Association Conference
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• 1999.05a
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• pp.232-237
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• 1999

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1322-1326
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• 2010

확산-유추 지형학적 순간단위도는 통계물리적인 모형으로 이론적 물리적으로 뛰어난 모형임에도 불구하고 유역의 동적 매개변수인 특성유속과 확산계수의 산정이 어려워 실제적인 사용이 제한되어 왔다. 이러한 난제를 해결하기 위하여 본 연구에서는 금강수계의 보청천 산성유역을 대상으로 전역최적화 기법인 SCE-UA를 이용하여 확산-유추 지형학적 순간단위도 모형의 동적 매개변수 산정하였으며, 모형의 재현성을 3개의 수문사상을 이용하여 검토하였다. 매개변수의 최적화 결과 차수 단계별 특성유속 및 확산계수의 증감은 변동을 보이지만, 전체적인 경향성은 특성유속의 경우 하천차수가 커질수록, 즉 하류방향에 대해 증가 경향을 나타내며, 반대로 확산계수는 감소되는 경향을 나타냈다. 본 연구에서 적용한 최적화 방법에 향후 지체시간, 분산 및 왜곡도 등의 통계적인 제약조건과 동적 매개변수의 공간적 변화 등의 물리적인 의미를 갖는 제약조건 등이 결합된다면 좀 더 발전된 모형으로 개선될 수 있을 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.529-533
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• 2016

미국 환경청의 SWMM 5(storm water management model 5)는 유역의 홍수유출 모의 및 연속 유출 모의를 할 수 있는 모형으로서 국내뿐만 아니라 세계적으로 많이 사용되고 있는 모형이다. SWMM 5와 같은 유역 유출모형에서 결과의 적절성을 향상시키기 위해서는 모형에 사용되는 매개변수를 올바르게 추정할 필요가 있다. 하지만, 외국의 정교한 유역 유출모형들이 우리나라에서 제대로 적용되고 있지 못하는 이유 중 하나는 적절한 매개변수의 추정이 이루어지지 못하고 있는 점이다. 이러한 문제를 해결하고자 SWMM 5의 매개변수 추정 지원 시스템을 개발하였다. SWMM 5의 매개변수 추정지원 시스템은 민감도 분석, 최적화 기법에 의한 모형 자동보정, 매개변수 할당 및 도움 모듈로 이루어져 있다. SWMM 5의 매개변수 추정 지원 시스템에 사용되는 최적화 기법은 전역최적화 기법 중 하나인 SCE-UA(shuffled complex evolution-University of Arizona) 이다. SWMM 5의 매개변수 추정 지원 시스템의 개발은 국내 수자원 기술자들의 SWMM 5에 대한 이해 및 활용도를 더욱 향상시켜줄 것으로 기대한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.428-428
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• 2017

In this study, three optimization techniques efficiency is assessed for calibration of the GR4J model for streamflow simulation in Selmacheon, Boryeong Dam and Kyeongancheon watersheds located in South Korea. The Penman-Monteith equation is applied to estimate the potential evapotranspiration, model calibration, and validation is carried out using the readily available daily hydro-meteorological data. The Shuffled Complex Evolution-University of Arizona(SCE-UA), Uniform Adaptive Monte Carlo (UAMC), and Coupled Latin Hypercube and Rosenbrock (CLHR) optimization techniques has been used to evaluate the robustness, performance and optimized parameters of the three catchments. The result of the three algorithms performances and optimized parameters are within the recommended ranges in the tested watersheds. The SCE-UA and CLHR outputs are found to be similar both in efficiency and model parameters. However, the UAMC algorithms performances differently in the three tested watersheds.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.83-83
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• 2020

지속되고 있는 기후변화의 영향으로 발생하는 기상현상들이 사회적 문제로 대두되고 있으며, 기후변화에 따른 국지적 극한 사상에 대한 전망은 수자원 활용 계획을 수립하고 대응하는 데 있어 필수적인 요소로 인식되고 있다. 이에 기후, 수문, 지리, 생태 및 환경 등의 다양한 영역에서 신뢰할 수 있는 공간적 강수량의 요구가 증가하고 있지만 지형의 약 70%가 산악 지형인 우리나라의 경우 기존의 일반적 공간보간 기법인 IDW 및 크리깅 방법은 고도가 높은 지역의 기상인자를 추정하는 데 한계가 있는 것으로 평가 받고 있다. 프리즘(Precipitation-Elevation Regressions on Independent Slopes Model, PRISM) 기법은 지형적 특성을 고려한 격자형태의 기상인자를 생산할 수 있는 유용한 방법으로서 미계측 유역에 대한 신뢰할 수 있는 일 단위 강수량 추정을 위하여 SCE-UA (Shuffled Complex Evolution-University of Arizona) 기법을 활용하여 최적화 하였다. 본 연구결과는 PRISM 기법의 국내 적용 시 정확도 향상에 기여할 것으로 기대된다.