• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.867-880
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• 2006

Hydrological models with many parameters and complex model structures require a powerful and detailed model calibration/validation scheme. In this study, we proposed a multi-variable and multi-site calibration and validation framework for the Soil Water Assessment Tool (SWAT) model applied in the Gap-cheon catchment located downstream of the Geum river basin. The sensitivity analysis conducted before main calibration helped understand various hydrological processes and the characteristics of subcatchments by identifying sensitive parameters in the model. In addition, the model's parameters were estimated based on existing data prior to calibration in order to increase the validity of model. The Nash-Sutcliffe coefficients and correlation coefficient were used to estimate compare model output with the observed streamflow data: $R_{eff}\;and\;R^2$ ranged 0.41-0.84 and 0.5-0.86, respectively, at the Heuduck station. Model reproduced baseflow estimated using recursive digital filter except for 2-5% overestimation at the Sindae and Boksu stations. Model also reproduced the temporal variability and fluctuation magnitude of observed groundwater levels with $R^2$ of 0.71 except for certain periods. Therefore, it was concluded that the use of multi-variable and multi-site method provided high confidence for the structure and estimated parameter values of the model.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.191-200
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• 2017

A robust parameter set (ROPS) selection framework for an unsteady flow model was developed by combining Pareto optimums obtained by outcomes of model calibration using multi-site observations with the minimax regret approach (MRA). The multi-site calibration problem which is a multi-objective problem was solved by using an aggregation approach which aggregates the weighted criteria related to different sites into one measure, and then performs a large number of individual optimization runs with different weight combinations to obtain Pareto solutions. Roughness parameter structure which can describe the variation of Manning's n with discharges and sub-reaches was proposed and the related coefficients were optimized as model parameters. By applying the MRA which is a decision criterion, the Pareto solutions were ranked based on the obtained regrets related to each Pareto solution, and the top-rated one due to the lowest aggregated regrets of both calibration and validation was determined as the only ROPS. It was found that the determination of variable roughness and the corresponding standardized RMSEs at the two gauging stations varies considerably depending on the combinations of weights on the two sites. This method can provide the robust parameter set for the multi-site calibration problems in hydrologic and hydraulic models.

• 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.

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.629-642
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• 2021

Land-use change has an important role in the hydrologic characteristics of watersheds because it alters various hydrologic components such as interception, infiltration, and evapotranspiration. For example, rapid urbanization in a watershed reduces infiltration rates and increases peak flow which lead to changes in the hydrologic responses. In this study, a physical hydrologic model the soil and water assessment tool (SWAT) was used to assess long-term continuous daily streamflow corresponding to land-use changes that occurred in the Naesungchun river watershed. For a 30-year model simulation, 3 different land-use maps of the 1990s, 2000s, and 2010s were used to identify the impacts of the land-use changes. Using SWAT-CUP (calibration and uncertainty program), an automated parameter calibration tool, 23 parameters were selected, optimized and compared with the daily streamflow data observed at the upstream, midstream and downstream locations of the watershed. The statistical indexes used for the model calibration and validation show that the model performance is improved at the downstream location of the Naesungchun river. The simulated streamflow in the mainstream considering land-use change increases up to -2 - 30 cm compared with the results simulated with the single land-use map. However, the difference was not significant in the tributaries with or without the impact of land-use change.

• Journal of Wetlands Research
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• v.22 no.1
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• pp.15-23
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• 2020

The purpose of this study is to investigate how the degree of distribution influences the calibration of snow and runoff in distributed hydrological models using a multi-criteria calibration method. The Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) developed by NOAA-National Weather Service (NWS) is employed to estimate optimized parameter sets. We have 3 scenarios depended on the model complexity for estimating best parameter sets: Lumped, Semi-Distributed, and Fully-Distributed. For the case study, the Durango River Basin, Colorado is selected as a study basin to consider both snow and water balance components. This study basin is in the mountainous western U.S. area and consists of 108 Hydrologic Rainfall Analysis Project (HRAP) grid cells. 5 and 13 parameters of snow and water balance models are calibrated with the Multi-Objective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm. Model calibration and validation are conducted on 4km HRAP grids with 5 years (2001-2005) meteorological data and observations. Through case study, we show that snow and streamflow simulations are improved with multiple criteria calibrations without considering model complexity. In particular, we confirm that semi- and fully distributed models are better performances than those of lumped model. In case of lumped model, the Root Mean Square Error (RMSE) values improve by 35% on snow average and 42% on runoff from a priori parameter set through multi-criteria calibrations. On the other hand, the RMSE values are improved by 40% and 43% for snow and runoff on semi- and fully-distributed models.

• Korean Journal of Ecology and Environment
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• v.41 no.1
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• pp.43-53
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• 2008

This study was conducted to simulate storm hydrographs on a small forested watershed using TOPMODEL, which is a distributed hydrological model. The Myeongseong watershed, which is 58.3 ha in size, was selected to monitor rainfall and runoff data. The Monte Carlo simulation was also used to calibrate parameters of TOPMODEL. Six rainfall-runoff pairs collected at the watershed in the year 1997 were used for parameter calibration, and eight rainfall-runoff pairs collected during the period of $1998\sim1999$ were used for validation effort. The errors of runoff volume ranged from -2.74% to 1.81%, and an average value of model efficiency in terms of runoff volume was 0.92 for the calibration period. The average value of observed peak discharge was $0.324m^3\;s^{-1}$ for six rainfall-runoff pairs, while the prediction value was $0.295m^3\;s^{-1}$. The simulation errors of peak discharge varied according to rainfall characteristics and antecedent condition, within ranges of -27.65% to -1.13%. The model efficiency for the validation period was 0.92. For the validation period, observed peak discharges have an average value of $0.087m^3\;s^{-1}$ and average value of simulated peak discharge was $0.090m^3\;s^{-1}$. Observed and simulated values of time to peak for the calibration period were 18.3 hrs and 11.0 hrs, respectively, and 16.6 hrs and 13.5 hrs, respectively, for the validation period.

• Journal of Korea Water Resources Association
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• v.48 no.6
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• pp.425-438
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• 2015

The objective of this study was to evaluate simulation of agricultural water supply considering yearly variation of irrigation efficiency. The water supply data of the Idong reservoir from 2001 through 2009 was collected and used for this study. Total 6 parameters including irrigation efficiency (Es), drainage outlet height, and infiltration, were used for sensitivity analysis, calibration, and validation. Among the parameters, the Es appeared to be the most sensitivity parameter. The Es was calibrated on a yearly basis considering sensitivity and time-varying characteristic, while other parameters were set to fixed values. The statistics of percent bias (PBLAS), Nash-Sutcliffe efficiency (NSE), and root means square error to the standard deviation of measured data (RSR) for a monthly step were 2.7%, 0.93, and 0.26 for the calibration, and 3.9%, 0.89, and 0.32 for the validation, correspondently. The results showed a good agreement with the observations. This implies that the modeling only with appropriate parameter values, apart from modeling approaches, can simulate the real supply operation reasonably well. However, the simulations with uncalibrated parameters from previous studies produced poor results. Thus, it is important to use calibrated values, and especially, we suggest the Es's yearly calibration for simulating agricultural water supply.

• Journal of Korea Water Resources Association
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• v.53 no.5
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• pp.347-356
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• 2020

The main objective of the study is to propose the most efficient SWAT model calibration method using SWAT-CUP with less computing time and high performance. In order to achieve the goal, Case1-3 (250, 500, and 1,000 simulation runs) and Case4 (1,000 simulation runs in the first iteration and then 500 simulation runs for the following iterations) were defined to compare the results. When evaluating the values of the objective function, Case2 and Case3 reached the same value after the fourth iteration, and Case1 reached the closed value of Case2-3 after the eighth iteration. However, the final estimates of the parameters had different ranges in Cases1-3, and only the results of Case3 and Case4 converged similarly. Thus, it can be considered that the parameter calibration results are highly affected by the initial number of simulation runs. On the other hand, SWAT simulation results did not show the significant difference after the first iteration, unlike the parameter ranges. From the analysis results, we can conclude that the most suitable and effective method was to repeat one or two times of iterations with a sufficient number of simulation runs, as in Case4.

• Journal of Animal Environmental Science
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• v.18 no.sup
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• pp.81-90
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• 2012

This study was evaluated high end research grade Near infrared spectrophotometer (NIRS) to low end popular field grade multiple Near infrared spectrophotometer (NIRS) for rapid analysis at forage quality at sight with 241 samples of Italian ryegrass silage during 3 years collected whole country for evaluate accuracy and precision between instruments. Firstly collected and build database high end research grade NIRS using with Unity Scientific Model 2500X (650 nm~2,500 nm) then trim and fit to low end popular field grade NIRS with Unity Scientific Model 1400 (1,400 nm~2,400 nm) then build and create calibration, transfer calibration with special transfer algorithm. The result between instruments was 0.000%~0.343% differences, rapidly analysis for chemical constituents, NDF, ADF, and crude protein, crude ash and fermentation parameter such as moisture, pH and lactic acid, finally forage quality parameter, TDN, DMI, RFV within 5 minutes at sight and the result equivalent with laboratory data. Nevertheless during 3 years collected samples for build calibration was organic samples that make differentiate by local or yearly bases etc. This strongly suggest population evaluation technique needed and constantly update calibration and maintenance calibration to proper handling database accumulation and spread out by knowledgable control laboratory analysis and reflect calibration update such as powerful control center needed for long lasting usage of forage analysis with NIRS at sight. Especially the agriculture products such as forage will continuously changes that made easily find out the changes and update routinely, if not near future NIRS was worthless due to those changes. Many research related NIRS was shortly study not long term study that made not well using NIRS, so the system needed check simple and instantly using with local language supported signal methods Global Distance (GD) and Neighbour Distance (ND) algorithm. Finally the multiple popular field grades instruments should be the same results not only between research grade instruments but also between multiple popular field grade instruments that needed easily transfer calibration and maintenance between instruments via internet networking techniques.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.589-598
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• 2018

To maintain safety and reliability of reactors, redundant sensors are usually used to measure critical variables and estimate their averaged time-dependency. Nonhealthy sensors can badly influence the estimation result of the process variable. Since online condition monitoring was introduced, the online cross-calibration method has been widely used to detect any anomaly of sensor readings among the redundant group. The cross-calibration method has four main averaging techniques: simple averaging, band averaging, weighted averaging, and parity space averaging (PSA). PSA is used to weigh redundant signals based on their error bounds and their band consistency. Using the consistency weighting factor (C), PSA assigns more weight to consistent signals that have shared bands, based on how many bands they share, and gives inconsistent signals of very low weight. In this article, three approaches are introduced for improving the PSA technique: the first is to add another consistency factor, so called trend consistency (TC), to include a consideration of the preserving of any characteristic edge that reflects the behavior of equipment/component measured by the process parameter; the second approach proposes replacing the error bound/accuracy based weighting factor ($W^a$) with a weighting factor based on the Euclidean distance ($W^d$), and the third approach proposes applying $W^d$, TC, and C, all together. Cold neutron source data sets of four redundant hydrogen pressure transmitters from a research reactor were used to perform the validation and verification. Results showed that the second and third modified approaches lead to reasonable improvement of the PSA technique. All approaches implemented in this study were similar in that they have the capability to (1) identify and isolate a drifted sensor that should undergo calibration, (2) identify a faulty sensor/s due to long and continuous missing data range, and (3) identify a healthy sensor.