• Proceedings of the Korean Society of Agricultural Engineers Conference
• /
• 1998.10a
• /
• pp.359-365
• /
• 1998

A global optimization method known as the Shuffled Complex Evolution method from the University of Arizona(SCE-UA) was used for calibrating a Tank model. The model was calibrated with error-free synthetic data, and the SCE-UA method was found to effectively search optimal parameters. Historical data from an agricultural watershed was used to calibrate and validate the model parameters. The simulated results were in good agreement with the observed.

• Journal of Korea Water Resources Association
• /
• v.35 no.5
• /
• pp.541-552
• /
• 2002

Two global optimization methods, the SCE-UA method and the Annealing-Simplex(A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. In synthetic data study, 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The Downhill Simplex method was converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed, which puts more weight on the low flows.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.44 no.7
• /
• pp.1-13
• /
• 2002

Two global optimization methods, the SCE-UA method and the Annealing-simplex (A-S) method for calibrating a daily rainfall-runoff model, a Tank model, was compared with that of the Downhill Simplex method. The performance of the four objective functions, DRMS (daily root mean square), HMLE (heteroscedastic maximum likelihood estimator), ABSERR (mean absolute error), and NS (Nash-Sutcliffe measure), was tested and synthetic data and historical data were used. In synthetic data study. 100% success rates for all objective functions were obtained from the A-S method, and the SCE-UA method was also consistently able to obtain good estimates. The downhill simplex method was unable to escape from local optimum, the worst among the methods, and converged to the true values only when the initial guess was close to the true values. In the historical data study, the A-S method and the SCE-UA method showed consistently good results regardless of objective function. An objective function was developed with combination of DRMS and NS, which putted more weight on the low flows.

• Journal of Korea Water Resources Association
• /
• v.39 no.8 s.169
• /
• pp.677-690
• /
• 2006

The LH-OAT (Latin Hypercube One factor At a Time) method for sensitivity analysis and SCE-UA (Shuffled Complex Evolution at University of Arizona) optimization method were applied for the automatic calibration of SWAT model in Bocheong-cheon watershed. The LH-OAT method which combines the advantages of global and local sensitivity analysis effectively identified the sensitivity ranking for the parameters of SWAT model over feasible parameter space. Use of this information allows us to select the calibrated parameters for the automatic calibration process. The performance of the automatic calibration of SWAT model using SCE-UA method depends on the length of calibration period, the number of calibrated parameters, and the selection of statistical error criteria. The performance of SWAT model in terms of RMSE (Root Mean Square Error), NSEF (Nash-Sutcliffe Model Efficiency), RMAE (Relative Mean Absolute Error), and NMSE (Normalized Mean Square Error) becomes better as the calibration period and the number of parameters defined in the automatic calibration process increase. However, NAE (Normalized Average Error) and SDR (Standard Deviation Ratio) were not improved although the calibration period and the number of calibrated parameters are increased. The result suggests that there are complex interactions among the calibration data, the calibrated parameters, and the model error criteria and a need for further study to understand these complex interactions at various representative watersheds.

• Journal of Korea Water Resources Association
• /
• v.34 no.5
• /
• pp.543-549
• /
• 2001

This research estimated stream discharges indirectly by hydraulic channel routing. Only stage data from three stage stations and river cross section data were used to estimate Manning roughness coefficients and to compute stream discharges. When the discharges were estimated a stage-stage set of conditions was used for upstream-downstream boundary conditions. The research used the data from the upper Mississippi River. The hydraulic channel routings were performed by DWOPER (operational dynamic wave model). The global optimization program of SCE-UA was used to improve the roughness coefficient estimation module of the modified Newton-Raphson method in DWOPER. The results from SCE-US were better. For the case study of a flood, most estimated discharges except a few show errors within 10%.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.53 no.5
• /
• pp.9-16
• /
• 2011

Curve Numbers (CN) for the combination of land use and hydrologic soil group were regionalized at Imha Watershed using Long-term Hydrologic Impact Assessment (L-THIA) coupled with SCE-UA. The L-THIA was calibrated during 1991-2000 and validated during 2001-2007 using monthly observed direct runoff data. The Nash-Sutcliffe (NS) coefficients for calibration and validation were 0.91 and 0.93, respectively, and showed high model efficiency. Based on the criteria of model calibration, both calibration and validation represented 'very good' fit with observe data. The spatial distribution of direct surface runoff by L-THIA represented runoff from Thiessen pologen at Subi and Sukbo rain gage station much higher than other area due to the combination of poor hydrologic condition (hydrologic soil C and D group) and locality heavy rainfall. As a results of hydrologic condition and treatment for land use type based on calibrated CNs, forest is recommended to be hydrologically modelled dived into deciduous, coniferous, and mixed forest due to the hydrological difference. The CNs for forest and upland showed the poor hydrologic condition. The steep slope of forest and alpine agricultural field make high runoff rate which is the poor hydrologic condition because CN method can not consider field slope. L-THIA linded with SCE-UA could generated a regionalized CNs for land use type with minimized time and effort, and maximized model's accuracy.

• Journal of Korea Water Resources Association
• /
• v.50 no.4
• /
• pp.241-252
• /
• 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 The Korean Society of Agricultural Engineers
• /
• v.47 no.3
• /
• pp.3-13
• /
• 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
• /
• v.45 no.11
• /
• pp.1169-1186
• /
• 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.

• Journal of Korea Water Resources Association
• /
• v.37 no.8
• /
• pp.631-641
• /
• 2004

The objective of this study is to test the applicability of SLURP (Semi-distributed Land Use-based Runoff Process) on Soyanggang-dam watershed. SLURP model is a conceptual semi-distributed form model that can be used to examine irrigation plan and the effects of proposed changes in water management within a basin or to see what effects external factors such as climate change or changing land cover might have on various water users. Topographical parameters were derived from DEM using TOPAZ and SLURPAZ. Monthly NDVIs were calculated from multi-temporal NOAA/AVHRR images during four years (1998 ∼ 2001). Weather elements (dew-point temperature, solar radiation, maximum/minimum temperature and relative humidify) were obtained from five meteorological stations within and near the study area. To simulate daily hydrograph during 1998 ∼ 2001, the model parameters of each land cover class were optimized by sensitivity analysis and SCE-UA method. Test result of SLURP was summarized by various statistics method (WMO volume error, Nash-Sutcliffe efficiency, mean error and coefficient of variation).