• Journal of Korean Society on Water Environment
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• v.27 no.1
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• pp.61-72
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• 2011

In order to assess hydrologic and nonpoint source pollutant behaviors in a watershed with Soil and Water Assessment Tool (SWAT) model, the accuracy evaluation of SWAT model should be conducted prior to the application of it to a watershed. When calibrating and validating hydrological components of SWAT model, the Nash-Sutcliffe efficiency coefficient (EI) has been widely used. However, the EI value has been known as it is affected sensitively by big numbers among the range of numbers. In this study, a Web-based flow clustering EI estimation system using K-means clustering algorithm was developed and used for SWAT hydrology evaluation. Even though the EI of total streamflow was high, the EI values of hydrologic components (i.e., direct runoff and baseflow) were not high. Also when the EI values of flow group I and II (i.e., low and high value group) clustered from direct runoff and baseflow were computed, respectively, the EI values of them were much lower with negative EI values for some flow group comparison. The SWAT auto-calibration tool estimated values also showed negative EI values for most flow group I and II of direct runoff and baseflow although EI value of total streamflow was high. The result obtained in this study indicates that the SWAT hydrology component should be calibrated until all four positive EI values for each flow group of direct runoff and baseflow are obtained for better accuracy both in direct runoff and baseflow.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.3
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• pp.37-48
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• 2010

The purpose of this paper is to evaluate how the rainfall field effect on a runoff simulation using grid radar rainfall data and ground gauge rainfall. The Gwangdeoksan radar and ground-gauge rainfall data were used to estimate a spatial rainfall field, and a hydrologic model was used to evaluate whether the rainfall fields created by each method reproduced a realistically valid spatial and temporal distribution. Pilot basin in this paper was the Naerin stream located in Inje-gun, Gangwondo, 250m grid scale digital elevation data, land cover maps, and soil maps were used to estimate geological parameters for the hydrologic model. For the rainfall input data, quantitative precipitation estimation(QPE), adjusted radar rainfall, and gauge rainfall was used, and then compared with the observed runoff by inputting it into a $Vflo^{TM}$ model. As a result of the simulation, the quantitative precipitation estimation and the ground rainfall were underestimated when compared to the observed runoff, while the adjusted radar rainfall showed a similar runoff simulation with the actual observed runoff. From these results, we suggested that when weather radars and ground rainfall data are combined, they have a greater hydrological usability as input data for a hydrological model than when just radar rainfall or ground rainfall is used separately.

• Journal of Korea Water Resources Association
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• v.53 no.5
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• pp.383-393
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• 2020

The main objective of this study is to provide a robust model for estimating parameters of the Clark unit hydrograph (UH) using the observed rainfall-runoff data in the Soyangang dam basin. In general, HEC-1 and HEC-HMS models, developed by the Hydrologic Engineering Center, have been widely used to optimize the parameters in Korea. However, these models are heavily reliant on the objective function and sample size during the optimization process. Moreover, the optimization process is carried out on the basis of single rainfall-runoff data, and the process is repeated for other events. Their averaged values over different parameter sets are usually used for practical purposes, leading to difficulties in the accurate simulation of discharge. In this sense, this paper proposed a hierarchical Bayesian model for estimating parameters of the Clark UH model. The proposed model clearly showed better performance in terms of Bayesian inference criterion (BIC). Furthermore, the result of this study reveals that the proposed model can also be applied to different hydrologic fields such as dam design and design flood estimation, including parameter estimation for the probable maximum flood (PMF).

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.83-96
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• 2017

This study presented a surface water quality modeling framework considering the spatial resolution of pollutant load estimation to better represent stream water quality characteristics in the Saemangeum watershed which has been focused on keeping its water resources sustainable after the Saemangeum embankment construction. The watershed delineated into 804 sub-watersheds in total based on the administrative districts, which were units for pollutant load estimation and counted as 739 in the watershed, Digital Elevation Model (DEM), and agricultural structures such as drainage canal. The established model consists of 7 Mangyung (MG) sub-models, 7 Dongjin (DJ) sub-models, and 3 Reclaimed sub-models, and the sub-models were simulated in a sequence of upstream to downstream based on its connectivity. The hydrologic calibration and validation of the model were conducted from 14 flow stations for the period of 2009 and 2013 using an automatic calibration scheme. The model performance to the hydrologic stations for calibration and validation showed that the Nash-Sutcliffe coefficient (NSE) ranged from 0.66 to 0.97, PBIAS were -31.0~16.5 %, and $R^2$ were from 0.75 to 0.98, respectively in a monthly time step and therefore, the model showed its hydrological applicability to the watershed. The water quality calibration and validation were conducted based on the 29 stations with the water quality constituents of DO, BOD, TN, and TP during the same period with the flow. The water quality model were manually calibrated, and generally showed an applicability by resulting reasonable variability and seasonality, although some exceptional simulation results were identified in some upstream stations under low-flow conditions. The spatial subdivision in the model framework were compared with previous studies to assess the consideration of administrative boundaries for watershed delineation, and this study outperformed in flow, but showed a similar level of model performance in water quality. The framework presented here can be applicable in a regional scale watershed as well as in a need of fine-resolution simulation.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.5
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• pp.1-9
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• 2010

Evapotranspiration (ET) is one of the basic components of the hydrologic cycle and is essential for estimating irrigation water requirements. In this study, artificial neural network (ANN) models for reference crop evapotranspiration ($ET_0$) estimation were developed on a monthly basis (May~October). The models were trained and tested for Suwon, Korea. Four climate factors, daily maximum temperature ($T_{max}$), daily minimum temperature ($T_{min}$), rainfall (R), and solar radiation (S) were used as the input parameters of the models. The target values of the models were calculated using Food and Agriculture Organization (FAO) Penman-Monteith equation. Future climate data were generated using LARS-WG (Long Ashton Research Station-Weather Generator), stochastic weather generator, based on HadCM3 (Hadley Centre Coupled Model, ver.3) A1B scenario. The evapotranspirations were 549.7 mm/yr in baseline period (1973-2008), 558.1 mm/yr in 2011-2030, 593.0 mm/yr in 2046-2065, and 641.1 mm/yr in 2080-2099. The results showed that the ANN models achieved good performances in estimating future reference crop evapotranspiration.

• Water for future
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• v.26 no.1
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• pp.51-62
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• 1993

The most significant factor in estimating annual runoff must be the precipitation. But in the previous study, the watershed area instead of precitation was included as an independent variable in regression model in the process of checking accurate data. The criterion of accurate data was the runoff ratio in the range of 20% to 100%. In this study the valid range of evapotranspiration was adopted as a criterion of accurate data and the same data were reexamined. It came up with following model which has a high coefficient of determination and conforms to hydrologic theory. R=-518.25+0.8834P where, R: runoff depth(mm) P: precipitation(mm) This regression model was found to be stable by cross-validation and is proposed as annual runoff estimation model applicable to ungaged small and medium watersheds in Korea.

• Water for future
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• v.25 no.4
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• pp.87-95
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• 1992

The validity of the estimate of runoff depth and peak runoff by the basin runoff curve numbers(CN-II for AMC-II condition and CN-III for AMC-III condition) obtained from hydrologic soil-cover complexs is investigated by making use of the observed curve numbers(median curve number and optimum curve number) computed from rainfall-runoff records. For gaged basins the median curve numbers are recommended for the estimation of runoff depth and peak runoff. For ungaged basins, found is that for the estimate of runoff depth CN-III is adequate and for the peak runoff CN-II is adequate. Also investigated is the variation of curve numbers during rainfall, which is turned out to improve the estimates of both depth and peak of runoff.

• Journal of Wetlands Research
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• v.6 no.3
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• pp.47-54
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• 2004

A hydraulically and hydrologically based estimation method of pollutant delivery load for water quality modeling is proposed. The proposed method works on grid basis and routes overland flows from one cell to the next following the maximum downslope directions. The method is able to consider spatially-varied data of source pollutant, topography, land slopes, soil characteristics, land use and aspects, which can be extracted from geographic information systems (GIS) and from digital elevation models (DEMs). Because of this feature, the proposed method can be expected to be used for evaluating the impacts of various practices on watershed management for water quality.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.1
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• pp.89-97
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• 2007

Simple regression models for pollutants load estimation of paddy developed by the Ministry of Environment in 1995 were tested with the data (T-N, T-P, $COD_{Mn}$, and SS) collected from Yeongsan and Seomjin river watersheds, and improvement measures were suggested. Overall, the simulated values showed a great difference from the measured values except for T-P according to the statistical analyses (RMSE, root mean square error; RMAE, root mean absolute error; RB, relative bias; EI, efficiency index). Such difference was assumed due to the fact that the models use only hydrologic factors (quantity factor) associated with precipitation and run-off as input parameters, but do not consider other factors which are likely to affect pollutant concentration (quality factor) including days after fertilization. In addition, in terms of accessibility of the models, some parameters in the models such as run-off depth and run-off amount which can not be obtained from the weather database but should be collected by on-site measurements need to be replaced with other variables.

• KCID journal
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• v.13 no.2
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• pp.262-273
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• 2006

The Soil and Water Assessment Tool (SWAT) model has been widely used in hydrology and sediment simulation worldwide. In most cases, the SWAT model is first calibrated with adjustments in model parameters, and then the validation is performed. However, very little study regarding the effects on SWAT estimation of subwatershed delineation was performed. Thus, the SWAT model was applied to the Doam-dam watershed with various threshold values in subwatershed delineation in this study to examine the effects on the number of subwatershed delineated on SWAT estimation. It was found the flow effect of subwatershed delineation is negligible. However there were huge variations in SWAT estimated sediment, T-N, and T-P values with the use of various threshold value in watershed delineation. Sometimes these variations due to watershed delineation are beyond the effects of parameter adjustment in model calibration and validation. The SWAT is a semi-distributed modeling system, thus, the subwatershed characteristics are assumed to be the same for all Hydrologic Response Unit (HRU) within that subwatershed. This assumption leads to variations in the SWAT estimated sediment and nutrient output values. Therefore, it is strongly recommended the SWAT users need to use the HUR specific slope length and slope value in model runs, instead of using the slope and the corresponding slope length of the subawatershed to exclude the effects of the number of subwatershed delineated on the SWAT estimation.