• Journal of Environmental Science International
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• v.24 no.4
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• pp.437-447
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• 2015

Estimation of runoff peak is needed to assess water availability, in order to support the multifaceted water uses and functions, hence to underscore the modalities for efficient water utilization. The magnitude of storm rainfall acts as a primary input for basin level runoff computation. The rainfall-runoff linkage plays a pivotal role in water resource system management and feasibility level planning for resource distribution. Considering this importance, a case study has been carried out in the Hancheon basin of Jeju Island where distinctive hydrological characteristics are investigated for continuous storm rainfall and high permeable geological features. The study aims to estimate unit hydrograph parameters, peak runoff and peak time of storm rainfalls based on Clark unit hydrograph method. For analyzing observed runoff, five storm rainfall events were selected randomly from recent years' rainfall and HEC-hydrologic modeling system (HMS) model was used for rainfall-runoff data processing. The simulation results showed that the peak runoff varies from 164 to 548 m3/sec and peak time (onset) varies from 8 to 27 hours. A comprehensive relationship between Clark unit hydrograph parameters (time of concentration and storage coefficient) has also been derived in this study. The optimized values of the two parameters were verified by the analysis of variance (ANOVA) and runoff comparison performance were analyzed by root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE) estimation. After statistical analysis of the Clark parameters significance level was found in 5% and runoff performances were found as 3.97 RMSE and 0.99 NSE, respectively. The calibration and validation results indicated strong coherence of unit hydrograph model responses to the actual situation of historical storm runoff events.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.5
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• pp.81-93
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• 2018

The Kajiyama formula, which is an empirical formula based on the maximum flood data at Korean watersheds, has been widely used for the design of hydraulic structures and management of watersheds. However, this formula was developed based on meteorological data and flow measured during early 1900s so that it could not consider the recently changed rainfall pattern due to climate changes. Moreover, the formula does not provide the monthly coefficients for 5 months including July and August (flood season), which causes the uncertainty to accurately interpret runoff characteristics at a watershed. Thus, the objective of this study is to enhance the monthly coefficients based on the recent meteorological data and flow data expanding the range of rainfall classification. The simulated runoff using the enhanced monthly coefficients showed better performance compared to that using the original coefficients. In addition, we evaluated the applicability of the enhanced monthly coefficient for future runoff prediction. Based on the results of this study, we found that the Kajiyame formula with the enhanced coefficients could be applied for the future prediction. Hence, the Kajiyama formula with enhanced monthly coefficient can be useful to support the policy and plan related to management of watersheds in Korea.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.98-106
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• 2019

The coefficient and exponent of the MUSLE(Modified Universal Soil Loss Equation) runoff factor in the SWAT(Soil and Water Assessment Tool) model are 11.8 and 0.56 respectively, which are equally applied to the estimation of soil erosion regardless of land use. they could derive overestimation or underestimation of soil erosion, which can cause problems in the selection of soil erosion-vulnerable area and evaluation of reduction management. However, there are no studies about the estimation of coefficients and exponent for the MUSLE runoff factor by land use and their applicability to the SWAT model. Thus, in order to predict soil erosion and sediment behavior accurately through SWAT model, it is necessary to estimate the coefficient and exponent of the MUSLE runoff factor by land use and evaluate its applicability. In this study, the coefficient and exponent of MUSLE runoff factor by land use were estimated for Gaa-cheon Watershed, and the differences in soil erosion and sediment from SWAT model were analyzed. The coefficient and exponent of runoff factor estimated by this study well reflected the characteristics of soil erosion in domestic highland watershed. Therefore, in order to apply the MUSLE which developed based on observed data of US agricultural basin to the domestic watershed, it is considered that a sufficient modification and supplementation process for the coefficient and exponent of the MUSLE runoff factor depending on land use is necessary. The results of this study can be used as a basic data for selecting soil erosion vulnerable area in the non-point source management areas and establishing and evaluating soil erosion reduction management.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.107-116
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• 2004

A GIS-based paddy inundation simulation system which is capable of simulating temporal and spatial inundation processes was established and applied in this paper. The system is composed of HEC-GeoHMS, and HEC-GeoRAS modules which interface the GIS and flood runoff models, and HEC-HMS, and HEC-RAS models which estimate the flood runoff. It was used to simulate storm runoff and inundation for a small rural watershed, the Baran HP#7, which is 10.69 $km^2$ in size. The simulated peak runoff, time to peak, and total direct runoff for eight storms were compared with the observed data. The results showed that the coefficient of determination ($R^2$) for the observed peak runoff was 0.99 and an error, RMSE, 11.862 $m^3$/s for calibration stages. In the model verification, $R^2$ was 0.99 and RMSE 1.296 $m^3$/s. Paddy inundation for each paddy growing stages in study watershed were estimated using verified inundation simulation system when probability rainfall was applied.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.6
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• pp.119-127
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• 2003

This paper documents recent efforts to validate the GIS-based hydrologic models, HEC-HMS and HEC-GeoHMS by the US Army Corps of Engineers. HMS and Geo-HMS were used to simulate storm runoff from a small rural watershed, the Balan HS#6. The watershed is 3.85 $\textrm{km}^2$ in size. The watershed topographic, soils, and land use data were processed using the GIS tool fur the models. Input parameters were retrieved and calibrated with the field data. The simulated peak runoff, time to peak, and total direct runoff fer twenty three storms were compared with the observed data. The results showed that the coefficient of determination($R^2$) for the observed peak runoff was 0.95 and an error, RMSE, 3.08 $\textrm{m}^3$/s for calibration stages. In the model verifications, $R^2$ was 0.89 and RMSE 6.79 $\textrm{m}^3$/s, which were slightly less accurate than the calibrated data. The simulated flood hydrographs were well compared to the observed. It was concluded that HMS and GeoHMS are applicable to flood analyses for rural watersheds.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.51-57
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• 2008

This study has been performed to define the standard of runoff coefficients which are applicable to the process of route design or various public facilities design. The application of accurate runoff coefficients is very important in construction works due to the fact that the abnormal weather and torrential downpour are raising. However, in Korea society, as planner's subjective judgement of an object region status would make the application of erroneous runoff coefficients, many problems have been occurred. Consequently, in this study, we could perform terrain analysis and rainfall basins extraction with GIS technoques and suggest the application standard of runoff coefficients in accordiance to terrain characteristics and the land covers. By having the application of the study results to past flooded areas, we could suggest improved plans.

• Journal of Korean Society on Water Environment
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• v.24 no.2
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• pp.221-229
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• 2008

This study revised a model for hydrologically analyzing rainwater harvesting facilities considering their rainfall-runoff properties and the data available. This model has only a few parameters, which can be estimated with rather poor measurements available. The model has a non-linear module for rainfall loss, and the remaining rainfall excess (effective rainfall) is assumed to be inflow to the storage tank. This model has been applied for the rainwater harvesting facilities in Seoul National University, Korea Institute of Construction Technology, and the Daejon World Cup Stadium. As a result, the runoff coefficients estimated were about 0.9 for the building roof as a rainwater collecting surface and about 0.18 for the playground. This result is coincident with that for designing the rainwater harvesting facilities to show the accuracy of model and the simulation results.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.6
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• pp.3-14
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• 2005

Accurate estimation of the spatial distribution of rainfall is critical to the successful modeling of hydrologic processes. The objective of this study is to evaluate the applicability of spatially distributed rainfall data. Spatially distributed rainfall was calculated using Kriging method and Thiessen method. The application of spatially distributed rainfall was appreciated to the runoff response from the watershed. The results showed that for each method the coefficient of determination for observed hydrograph was $0.92\~0.95$ and root mean square error was $9.78\~10.89$ CMS. Ordinary Kriging method showed more exact results than Simple Kriging, Universal Kriging and Thiessen method, based on comparison of observed and simulated hydrograph. The coefncient of determination for the observed peak flow was 0.9991 and runoff volume was 0.9982. The accuracy of rainfall-runoff prediction depends on the extent of spatial rainfall variability.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.4
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• pp.67-74
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• 2007

Rational method has been widely used to calculate peak runoff drainage design or small watershed because of simplicity and convenience. Runoff coefficient(C) is the most important parameter in the rational method which varies according to rainfall intensity, return period, rainfall duration time and soil characteristics. In practice, constant which is value of C in rational formula has been used from the table, originally based on ASCE. These table value does not consider the upper conditions of the depending factors, hence peak runoff calculation could be in correct. Therefore to calculate C in this paper we have devised an improved formula, considering relationship with rainfall duration, return period and CN of NRCS method. This formula is considered to be more reliable and helpful to the hydrologists and engineers to predict correct peak runoff.

• Journal of Korean Society on Water Environment
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• v.22 no.5
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• pp.856-864
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• 2006

For estimating the minimum discharge to maintain a river, low flow analysis is required and long term runoff records are needed for the analysis. However, runoff data should be estimated to run a hydrologic model for ungaged river basin. For the reason, parameter estimation is crucial to simulate rainfall-runoff events for those basins using Tank model. In this study, only runoff data recorded for dry season are used for parameter estimation, which is different to other methods based on runoff data recorded for wet and dry seasons. The Harmony Search algorithm is used to determine the optimum parameters for Tank model. The coefficient of determination ($R^2$) is served as the objective function in the Harmony Search. In cases that recorded data are insufficient, the recording interval is changed and Empirical CDF is adopted to analyze the estimated parameters. The suggested method is applied to Yongdam dam, Soyanggang dam, Chungju dam and Seomjingang dam basins. As results, the higher $R^2s$ are obtained when the shorter recording interval, the better recorded data quality, and the more rainfall events recorded along with certain rainfall amount is. Moreover, when the total rainfall is higher than the certain amount, $R^2$ is high. Considering the facts found from this study for the low flow analysis, it is possible to estimate the parameters for Tank model properly with the desired confidence level.