• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.37-44
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• 2018

Universal soil loss equation (USLE) had been employed to estimate potential soil loss since it was developed from the statewide data measured and collected in the United States. The equation had an origin in average annual soil loss estimation though, it was modified or improved to provide better opportunities of soil loss estimation outside the United States. The equation has five factors, most studies modifying them to adapt regional status were focused on rainfall erosivity factor and cover management factor. While the conservation practice factor (USLE P factor) is to represent distinct features in agricultural fields, it is challenging to find studies regarding the factor improvements. Moreover, the factor is typically defined using slopes. The factor defining approach was suggested in the study, the approach is a step-by-step method allowing USLE P factor definition with given condition. The minimum condition is slope and field location to provide an opportunity for using in any GIS software and to reflect regionally distinct features. If watershed location, slope, crop type, and mulching type on furrows are given, detailed definition of the factors are possible. The approach was developed from field survey in South-Korea, it is expected to be used for potential soil loss using USLE in South-Korea.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1317-1328
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• 2021

This study aims to provide a predictive model based on climate models for simulating continuous daily rainfall sequences by combining bias-correction and spatio-temporal downscaling approaches. For these purposes, this study proposes a combined modeling system by applying conditional Copula and Multisite Non-stationary Hidden Markov Model (MNHMM). The GloSea5 system releases the monthly rainfall prediction on the same day every week, however, there are noticeable differences in the updated prediction. It was confirmed that the monthly rainfall forecasts are effectively updated with the use of the Copula-based bias-correction approach. More specifically, the proposed bias-correction approach was validated for the period from 1991 to 2010 under the LOOCV scheme. Several rainfall statistics, such as rainfall amounts, consecutive rainfall frequency, consecutive zero rainfall frequency, and wet days, are well reproduced, which is expected to be highly effective as input data of the hydrological model. The difference in spatial coherence between the observed and simulated rainfall sequences over the entire weather stations was estimated in the range of -0.02~0.10, and the interdependence between rainfall stations in the watershed was effectively reproduced. Therefore, it is expected that the hydrological response of the watershed will be more realistically simulated when used as input data for the hydrological model.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.143-148
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• 2005

The main purpose of this study is to suggest and evaluate an operational method for assessing the potential impact of climate change on hydrologic components and water resources of regional scale river basins. The method, which uses large scale climate change information provided by a state of the art general circulation model(GCM) comprises a statistical downscaling approach and a spatially distributed hydrological model applied to a river basin located in Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about $7.6\% of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern and the analysis of the duration cure shows the mean of averaged low flow is increased while the averaged wet and normal flow are decreased for the climate change.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.4
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• pp.75-83
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• 2007

Urbanized area has complex terrain with many flow paths. Almost stormwater is drained through pipe network because most area is impervious. And overland flow from the pipe network reform the surface flow. Therefore, it should be considered the drainage system and surface runoff both in urban inundation analysis. It is analyzed by using MIKE FLOOD integrated 1 dimension - 2 dimension model about Incheon Gyo urbanized watershed and compared with the results of 1 dimension model and 2 dimension model. At the result this approach linking of 2 dimension and 1 dimension pipe hydraulic model in MIKE FLOOD give accuracy that offers substantial improvement over earlier approach and more information about inundation such as water dapth, velocity or risk of flood, because it is possible to present storage of overland flow and topographical characteristic of area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.327-340
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• 2015

General Circulation Models (GCMs) are the basic tool used for modelling climate. However, the spatio-temporal discrepancy between GCM and observed value, therefore, the models deliver output that are generally required calibration for applied studies. Which is generally done by Multi-Model Ensemble (MME) approach. Stochastic downscaling methods have been used extensively to generate long-term weather sequences from finite observed records. A primary objective of this study is to develop a forecasting scheme which is able to make use of a MME of different GCMs. This study employed a Nonstationary Hidden Markov Chain Model (NHMM) as a main tool for downscaling seasonal ensemble forecasts over 3 month period, providing daily forecasts. Our results showed that the proposed downscaling scheme can provide the skillful forecasts as inputs for hydrologic modeling, which in turn may improve water resources management. An application to the Nakdong watershed in South Korea illustrates how the proposed approach can lead to potentially reliable information for water resources management.

• Journal of Korean Society on Water Environment
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• v.36 no.4
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• pp.300-313
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• 2020

The Bayesian approach can be used to estimate hydrologic model parameters from the prior expert knowledge about the parameter values and the observed data. The purpose of this study was to compare the performance of the two Bayesian methods, the Metropolis-Hastings (MH) algorithm and the Generalized Likelihood Uncertainty Estimation (GLUE) method. These two methods were applied to the TANK model, a hydrological model comprising 13 parameters, to examine the uncertainty of the parameters of the model. The TANK model comprises a combination of multiple reservoir-type virtual vessels with orifice-type outlets and implements a common major hydrological process using the runoff calculations that convert the rainfall to the flow. As a result of the application to the Nam River A watershed, the two Bayesian methods yielded similar flow simulation results even though the parameter estimates obtained by the two methods were of somewhat different values. Both methods ensure the model's prediction accuracy even when the observed flow data available for parameter estimation is limited. However, the prediction accuracy of the model using the MH algorithm yielded slightly better results than that of the GLUE method. The flow duration curve calculated using the limited observed flow data showed that the marginal reliability is secured from the perspective of practical application.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.353-363
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• 2020

Hydrologic models can be classified into two types: those for understanding physical processes and those for predicting hydrologic quantities. This study deals with how to use the model to predict today's stream flow based on the system's knowledge of yesterday's state and the model parameters. In this regard, for the model to generate accurate predictions, the uncertainty of the parameters and appropriate estimates of the state variables are required. In this study, a relatively simple hydrologic partitioning model is proposed that can explicitly implement the hydrologic partitioning process, and the posterior distribution of the parameters of the proposed model is estimated using the Markov chain Monte Carlo approach. Further, the application method of the ensemble Kalman filter is proposed for updating the normalized soil moisture, which is the state variable of the model, by linking the information on the posterior distribution of the parameters and by assimilating the observed steam flow data. The stochastically and recursively estimated stream flows using the data assimilation technique revealed better representation of the observed data than the stream flows predicted using the deterministic model. Therefore, the ensemble Kalman filter in conjunction with the Markov chain Monte Carlo approach could be a reliable and effective method for forecasting daily stream flow, and it could also be a suitable method for routinely updating and monitoring the watershed-averaged soil moisture.

• Journal of Wetlands Research
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• v.11 no.2
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• pp.55-66
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• 2009

The increase of pollutant loadings from nonpoint sources affect the water quality of the major rivers in Korea. Consequently, the need for managing the nonpoint source (NPS) pollution becomes the main concern of the Korean Ministry of Environment (MOE). Recently, the policy was changed from pollutant concentration-restricting approach to the total maximum daily load (TMDL) approach to improve the water quality and protect the aquatic ecosystem. Part of the program is the construction of Best Management Practice (BMP) pilot facilities basically to control NPS. Most of the BMPs adopted were foreign technologies which could not be properly employed in the country due to some limitations such as climate, watershed characteristics, etc. In other words, to be able to apply the BMPs, research on its applicability is necessary. In this study, a three-year monitoring has been conducted to assess the treatment performance of the BMP installed in highway toll plaza and parking lot. The data gathered aid in the characterization of NPS pollutants in runoff and estimation of the pollutant removal efficiency of the BMP. The results will be used for the future implementation of BMP in different land uses as well as for the determination of optimum operation and maintenance.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.251-264
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• 2008

In this study, a nonhomogeneous markov model which is able to simulate hourly rainfall series is developed for estimating reliable hydrologic variables. The proposed approach is applied to simulate hourly rainfall series in Korea. The simulated rainfall is used to estimate the design rainfall and flood in the watershed, and compared to observations in terms of reproducing underlying distributions of the data to assure model's validation. The model shows that the simulated rainfall series reproduce a similar statistical attribute with observations, and expecially maximum value is gradually increased as number of simulation increase. Therefore, with the proposed approach, the non-homogeneous markov model can be used to estimate variables for the purpose of design of hydraulic structures and analyze uncertainties associated with rainfall input in the hydrologic models.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.1
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• pp.29-37
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• 2021

It is important to introduce a local adaptive water supply system for upper mountainous regions, which provide a margin of water supply. This can be done through the process of securing a water source, planning for optimal use, and combining it with a water source that can be linked. In particular, in a mountainous region located at the uppermost part of the watershed, an approach should be found to utilize the groundwater discharge supplied through valley water and lateral discharge. This study sought to improve the water supply system using sand dams in drought-prone areas in Chuncheon, in Gangwon Province. Our approach involved virtually installing a sand storage tank under the existing water source to perform modeling in consideration of the current water intake and calculating the amount of water that can be taken from the sand dam. When the sand dam was applied at a size four times larger than the existing water source, it was found that the groundwater drainage increased significantly with changes in water surface slope and hydraulic conductivity.