• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.963-972
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• 2009

The objective of this study is to evaluate an application of stochastic continuous storage function model with ensemble Kalman filter technique. The case study is performed at the upstream basin of Jibo streamflow gauge including Andong and Imha dam. Test period is for the rainy season during 2006 and 2007. Long term runoff analysis is feasible in the case of using deterministic model. Ensemble members for input data and parameters are generated using Monte Carlo simulation for the purpose of applying ensemble Kalman filter technique. The cumulative absolute errors of stochastic model to the deterministic one are improved for the amount of 17.5 %, 18.3 % and more than 40.0 % for Andong dam, Imha dam and Jibo station, respectively. The results indicate that the stochastic model improves the accuracy of the simulated discharge considerably.

• Journal of Korean Society on Water Environment
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• v.26 no.6
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• pp.1040-1048
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• 2010

An infiltration storage can be installed as a method of reducing runoff from catchment and increasing stream flow during the dry period by recharging groundwater. However, there is no proper model and method that can be used to design storage capacity of an infiltration storage in Korea. The purpose of the study is to evaluate capacities of infiltration storages planned on Jeju-do in Korea by modifying Storm Water Management Model (SWMM). The basic equations for the infiltration storage are same as those of the infiltration trench used in MIDUSS. Infiltration rates of the infiltration storages were first measured by double ring infiltrometers, and then the modified model was applied to evaluate adequacy for the capacities of three infiltration storages planned on Jeju-do in Korea. The application results show that the two infiltration storages with higher infiltration rates have adequate capacities to infiltrate the total water inflow to the storages. However, the other infiltration storage with lower infiltration rates has not sufficient capacity to infiltrate the total water inflow to the storage and release occurs to the downstream region. The simulation model and method applied can be used for capacity evaluation of future infiltration storages on highly pervious areas in Jeju-do.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.147-147
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• 2018

In this article, we use an open source software library: TensorFlow, developed for the purposes of conducting very complex machine learning and deep neural network applications. However, the system is general enough to be applicable in a wide variety of other domains as well. The proposed model based on a deep neural network model, LSTM (Long Short-Term Memory) to predict the river water level at Okcheon Station of the Guem River without utilization of rainfall - forecast information. For LSTM modeling, the input data is hourly water level data for 15 years from 2002 to 2016 at 4 stations includes 3 upstream stations (Sutong, Hotan, and Songcheon) and the forecasting-target station (Okcheon). The data are subdivided into three purposes: a training data set, a testing data set and a validation data set. The model was formulated to predict Okcheon Station water level for many cases from 3 hours to 12 hours of lead time. Although the model does not require many input data such as climate, geography, land-use for rainfall-runoff simulation, the prediction is very stable and reliable up to 9 hours of lead time with the Nash - Sutcliffe efficiency (NSE) is higher than 0.90 and the root mean square error (RMSE) is lower than 12cm. The result indicated that the method is able to produce the river water level time series and be applicable to the practical flood forecasting instead of hydrologic modeling approaches.

• Journal of Wetlands Research
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• v.19 no.4
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• pp.470-483
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• 2017

Changes in land cover or land use, such as changes in forest area, can cause changes in water and energy circulation, ultimately affecting overall hydrological cycle including stream flow, evapotranspiration, soil moisture, and base flow. In this study, the changes of the hydrological processes over the past long period were simulated by using large-scale surface hydrologic model along with various soil, land use, vegetation, and meteorological data. For this purpose, this study simulated and evaluated the changes in the hydrological cycle for the past 50 years (1955-2010) in East Asia including China, Japan and South Korea. In particular, this study used the land cover maps which can properly reflect the vegetation condition for each simulation period. As results, the mean runoff ratio of China was estimated to be 47.0% over the entiree period, 62.7% in Japan and 49.4% in South Korea. The mean soil moisture of China was estimated to be 22.2%, 35.6% in Japan and 23.9% in South Korea. Finally, the mean evapotranspiration rate was estimated to be 52.7% in China, 37.3% in Japan and 50.4% in South Korea. Especially, in China, the hydrological cycle was found to be changed very much for the entire simulation period. However, in Japan, the hydrological cycle was found to be very stable for the entire simulation period. The hydrological cycle was also found to become stable mainly due to the stabilization of the vegetation.

• Journal of Korea Water Resources Association
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• v.40 no.2 s.175
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• pp.147-158
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• 2007

This study attempted to determine a suitable hydrologic model for assessing the impact of climate change on water resources, and to assess the accuracy of streamflow scenarios simulated by the selected hydrologic model using the meteorological scenarios of the Seoul National University Regional Climate Model(SNURCM). Comparison of four water balance models and two daily conceptual rainfall-runoff models for the simulation capability of the Daecheong Dam inflow indicated that the abcd model performs the best among the tested water balance models and performs as well as SSARR that is popular as a daily rainfall-runoff model in Korea. Parameters of the abcd model were then estimated for 12 ungauged subbasins of the Geum River by the regionalization method. The model parameters were first calibrated at nine multi-purpose dams and were then regionalized using catchment characteristics for another four multi-purpose dams, which were assumed to be ungauged sites. The model efficiency(ME) coefficients of the simulated inflows for these four dams were at least 87%. The MEs of the hindcasted meteorological rainfall scenarios of the 12 subbasins of the Geum River were more than 60%. Moreover, the ME of the Daecheong Dam inflow simulated by the abcd model using the SNURCM rainfall scenarios was more than 80%. Therefore, this research concluded that the abcd model coupled with the SNU-RCM meteorological scenarios can be used for impact assessment studies of climate change on water resources.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.821-831
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• 2014

Stochastic rainfall generators or stochastic simulation have been widely employed to generate synthetic rainfall sequences which can be used in hydrologic models as inputs. The calibration of Poisson cluster stochastic rainfall generator (e.g. Modified Bartlett-Lewis Rectangular Pulse, MBLRP) is seriously affected by local minima that is usually estimated from the local optimization algorithm. In this regard, global optimization techniques such as particle swarm optimization and shuffled complex evolution algorithm have been proposed to better estimate the parameters. Although the global search algorithm is designed to avoid the local minima, reliable parameter estimation of MBLRP model is not always feasible especially in a limited parameter space. In addition, uncertainty associated with parameters in the MBLRP rainfall generator has not been properly addressed yet. In this sense, this study aims to develop and test a Bayesian model based parameter estimation method for the MBLRP rainfall generator that allow us to derive the posterior distribution of the model parameters. It was found that the HBM based MBLRP model showed better performance in terms of reproducing rainfall statistic and underlying distribution of hourly rainfall series.

• Korean Journal of Hydrosciences
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• v.8
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• pp.125-136
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• 1997

The simulation techniques of hydrologic data series have develped for the purposes of the design of water resources system, the optimization of reservoir operation, and the design of flood control of reservoir, etc. While the stochastic models are usually used in most analysis of water resources fields for the generation of data sequences, the indexed sequential modeling (ISM) method based on generation of a series of overlapping short-term flow sequences directly from the historical record has been used for the data generation in the western USA since the early of 1980s. It was reported that the reliable results by ISM were obtained in practical applications. In this study, we generate annual inflow series at a location of Hong Cheon Dam site by using ISM method and autoregressive, order-1 model (AR(1)), and estimate the drought characteristics for the comparison aim between ISM and AR(1).

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.79-90
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• 2006

The partitioning level of a catchment becomes an issue if the calculated results from different levels show the same performance regardless of the levels. This study aims to identify the proper processing level of spatial resolution for the SWMM model application in an urban area. Using GIS overlaying technique, the division of subcatchments as a hydrologic similarity unit (HSU) is achieved with a comprehensive consideration of surface slope conditions, flow directions of storm sewers, and current land cover situation. Three surface-sewer alternatives are made on the basis of three different levels of surface divisions as well as the number of sewer connections and used as runoff simulation fields for the application of SWMM. As the result, it is found that the effect of a spatial resolution on the surface runoff results is not significant. On the other hand, the accumulated pollution load from an unit subcatchment, which is built by aggregation of several unit subcatchments consisting of various land cover conditions is reduced through the deterioration of surface spatial resolution. Although overall runoff pattern and accumulated runoff are little affected by spatial resolution, the simulated runoff from sewer outlet shows slight difference at the peak appearance time. The gap between surface pollution load accumulated and it discharged from the sewer outlet in a surface-sewer alternative during runoff period is monitored but the level of error is less than 5-10% except the lowest spatial resolution case.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.733-745
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• 2010

Seasonality of hydrologic extreme variable is a significant element from a water resources managemental point of view. It is closely related with various fields such as dam operation, flood control, irrigation water management, and so on. Hydrological frequency analysis conjunction with partial duration series rather than block maxima, offers benefits that include data expansion, analysis of seasonality and occurrence. In this study, nonstationary frequency analysis based on the Bayesian model has been suggested which effectively linked with advantage of POT (peaks over threshold) analysis that contains seasonality information. A selected threshold that the value of upper 98% among the 24 hours duration rainfall was applied to extract POT series at Seoul station, and goodness-fit-test of selected GEV distribution has been examined through graphical representation. Seasonal variation of location and scale parameter ($\mu$ and $\sigma$) of GEV distribution were represented by Fourier series, and the posterior distributions were estimated by Bayesian Markov Chain Monte Carlo simulation. The design rainfall estimated by GEV quantile function and derived posterior distribution for the Fourier coefficients, were illustrated with a wide range of return periods. The nonstationary frequency analysis considering seasonality can reasonably reproduce underlying extreme distribution and simultaneously provide a full annual cycle of the design rainfall as well.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.910-915
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• 2009

The ecohydrologic characteristics according to planting in riparian zone for the riparian restoration are analyzed in this research. The ecohydrologic components due to land use change in riparian zone from existing land cover to planted area such as pasture and wildrye are simulated in the test basin with the integrated SWAT-MODFLOW model. After analysis of change of the hydrologic properties such as surface flow, lateral flow, transpiration and soil water in riparian zone, it is revealed that soil water is one of the key factors and planting of wildrye can increase soil water in riparian zone. The simulation performance of the SWAT-MODFLOW model is validated in this study and it is expected that this model can be used to evaluate various riparian restoration scenarios.