• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.587-596
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• 2011

The interest in hydrological modeling has increased significantly recently due to the necessity of watershed management, specifically in regards to lumped models, which are being prosperously utilized because of their relatively uncomplicated algorithms which require less simulation time. However, lumped models require empirical coefficients for hydrological analyses, which do not take into consideration the heterogeneity of site-specific characteristics. To overcome such obstacles, a distributed model was offered as an alternative and the number of researches related to watershed management and distributed models has been steadily increasing in the recent years. Thus, in this study, the feasibility of a grid-based rainfall-runoff model was reviewed using the flood runoff process in the Han River basin, including the ChungjuDam, HoengseongDam and SoyangDam watersheds. Hydrological parameters based on GIS/RS were extracted from basic GIS data such as DEM, land cover, soil map and rainfall depth. The accuracy of the runoff analysis for the model application was evaluated using EFF, NRMSE and QER. The calculation results showed that there was a good agreement with the observed data. Besides the ungauged spatial characteristics in the SoyangDam watershed, EFF showed a good result of 0.859.

• Journal of Korean Society on Water Environment
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• v.29 no.6
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• pp.730-738
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• 2013

In recent years, low impact development (LID) has emerged as an effective approach to control stormwater in an urban area, and watershed and stormwater managers need modeling tools to evaluate alternative plans for controlling stormwater. This study illustrates how to design and evaluate the effect of non-point pollutant management using SUSTAIN which is developed by USEPA. SUSTAIN can provide evaluating, selecting, and placing LID facilities in an urban catchment based on user-defined cost-effectiveness criteria. Also, this paper suggests a minimal methodology for estimating model parameters for modeling an ungauged urban catchment to reflect the situation of typical Korean urban interested catchments which are usually ungauged. In addition, the optimal length of various LID facilities and the optimal number of units in our test catchment are estimated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.407-416
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• 2016

The purpose of this study is to develop regional regression models to estimate mean low flow for ungauged basins. The unregulated streamflow data observed at 12 multipurpose dams and 4 irrigation dams were analyzed for determining mean low flows. Various types of regression models were developed using the relationship between mean low flows and various sets of watershed characteristics such as drainage area, average slope, drainage density, mean annual precipitation, runoff curve number. The performance of each regression model for estimating mean low flows was assessed by comparison with the results obtained from the observed data. It was found that a regional regression model explained by drainage area, the mean annual precipitation, and runoff curve number showed the best performance. The regression model presented in this study also gives better estimates of mean low flow than the estimates by the drainage-area ratio method and the previous regression model.

• Journal of Wetlands Research
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• v.19 no.3
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• pp.335-344
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• 2017

In this study, We proposed a method to estimate the design flood by area ratio in an ungauged basin. For that, the discharge parameters was determined by calibration of observed data at the watershed outlet and then peak flow was estimated by area ratio. In order to verify suggested method, peak flow was compared the observed discharge of the small river basin and the design flood discharge of river implementation projects. The results were summarized as follows. As a result of comparing the discharge by the area ratio and observed discharge, the difference of peak flows were analysed 14 ~ 25%. When the discharge calculated with area ratio of small river was compared with the design flood discharge of river implementation projects, the relative error was analyzed to be less than 20%. It means that suggested method in this study is appropriate.

• Journal of Korea Water Resources Association
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• v.46 no.5
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• pp.519-530
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• 2013

To provide a reliable tool for runoff simulations of ungauged watersheds upstream of reservoirs, a daily runoff simulation model, Tank model, is restructured, the parameter regionalization of the model is conducted, and the model's applicability is evaluated. Taking into account the characteristics of runoffs from the watersheds, a three-tank model is employed. The percolation process of the model's third tank is eliminated, considering the water budgets of the watersheds, and its evapotranspiration component is improved, reflecting the conditions of meteorological observation in South Korea. The sensitivity analysis of the model shows that the model's behaviors, varying with a sensitive parameter, ${\alpha}$, are reasonable. The regional parameter estimation equations are determined, using the characteristics and land uses of the watersheds as variables. The model is applied for the runoff simulations of three watersheds and the water stage simulation of one reservoir, and the simulation results are then compared with the observed values, which prove to be in close agreement with the observations. In addition, the results from simulating inflows of twenty-four reservoirs using the model show that the averages of evapotranspiration rate and runoff rate are 42.8% and 56.6%, respectively, which are resonable. Consequently, it is concluded that the model is practically applicable to simulating runoffs from watersheds upstream of reservoirs, and simulated inflow data are useful for watershed management and reservoir planning, design, and operation.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.151-163
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• 2018

The objective of this study was to estimate LOADEST (LOAD Estimator) coefficients for simulating pollutant loads in ungauged watersheds. Regression models of LOADEST were used to simulate pollutant loads, and the multiple linear regression (MLR) was used for coefficients estimation on watershed characteristics. The fifth and third model of LOADEST were selected to simulate T-N (Total-Nitrogen) and T-P (Total-Phosphorous) loads, respectively. The results and statistics indicated that regression models based on LOADEST simulated pollutant loads reasonably and model coefficients were reliable. However, the results also indicated that LOADEST underestimated pollutant loads and had a bias. For this reason, simulated loads were corrected the bias by a quantile mapping method in this study. Corrected loads indicated that the bias correction was effective. Using multiple regression analysis, a coefficient estimation methods according to the watershed characteristic were developed. Coefficients which calculated by MLR were used in models. The simulated result and statistics indicated that MLR estimated the model coefficients reasonably. Regression models developed in this study would help simulate pollutant loads for ungauged watersheds and be a screen model for policy decision.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.5
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• pp.11-18
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• 2016

The objective of this study was to develop the simple method to estimate ungauged river section for flood stage analysis. Damage prediction should be prioritized using hydrological modeling to reduce flood risk. Mostly, the geographical data using hydrological modeling depends on national river cross-section survey. However because of the lack of measured data, it is difficult to apply to many local streams or small watersheds. For this reason, this study suggest the method to estimate unguaged river cross-section. Simple regression equations were derived and used to estimate river cross-section by analyzing the correlation between the river cross-sectional characteristics (width, height and area). The estimated cross-sections were used to simulate flood level by HEC-RAS (Hydrologic Engineering Center's River Analysis System). The applicability of this method was verified by comparing simulated flood level between measured and estimated cross-section. The water surface elevation of the flood stage analysis was 6.56-7.24 m, 5.33-5.95 m and 6.12-6.75 m for measured cross section, for estimated cross section and for estimated cross section based on DEM elevation, respectively. Further study should consider other factors for more accurate flood stage analysis. This study might be used one of the guidelines to estimate ungauged river section for flood stage analysis.

• Journal of Korea Water Resources Association
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• v.43 no.4
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• pp.353-365
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• 2010

Generally, river discharge is measured at flood forecasting points, upstream dam points, large rivers, and important points over a basin, and it is hard to estimate discharge of medium or small stream and small catchment. Physically based rainfall-runoff model with geographical parameters can simulate discharge at all the points within a basin with optimized parameters for a point in the basin. In this study, GRM (Grid based Rainfall-runoff Model) calibrated at the outlet is applied. The discharge at upstream point is estimated and the possibility of model regionalisation is examined for ungauged catchment of small or medium stream within a river system. Wicheon and Boksu watershed in Nakdonggang (Riv.) and Yudeungcheon (Riv.) respectively are selected. The discharge at Miseong and Sindae station is simulated with the parameters estimated at Museong and Boksu station. The results of Miseong and Sindae station show good agreement with observed hydrographs in peak discharge and peak time and consistently linear relationships with high correlations in discharge volume, peak discharge, and peak time. And it shows GRM could be applied to estimate discharge at ungauged catchments along a river system.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.6
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• pp.153-159
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• 2009

In order to estimate release water from reservoirs located on ungaged watersheds, an algorithm was suggested based on hydrologic reservoir routing and real time calibrating watershed parameters. A prototype - simple computer program was developed to implement the algorithm with Genetic Algorithm technic. The program was applied to a mid-size reservoir and its ungauged watershed area using observed rainfall data, spillway gates operation data and reservoir water stage time series data under a existing storm event. The result shows that the algorithm and the prototype would be useful to simulate released water from reservoirs.