• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.488-488
• /
• 2015

Intermittent streamflow is common phenomenon in arid and semi-arid regions. To manage water resources of intermittent streamflows, stochactic simulation data is essential; however the seasonally stochastic modeling for intermittent streamflow is a difficult task. In this study, using the periodic Markov chain model, we simulate intermittent monthly streamflow for occurrence and the periodic gamma autoregressive and copula models for amount. The copula models were tested in a previous study for the simulation of yearly streamflow, resulting in successful replication of the key and operational statistics of historical data; however, the copula models have never been tested on a monthly time scale. The intermittent models were applied to the Colorado River system in the present study. A few drawbacks of the PGAR model were identified, such as significant underestimation of minimum values on an aggregated yearly time scale and restrictions of the parameter boundaries. Conversely, the copula models do not present such drawbacks but show feasible reproduction of key and operational statistics. We concluded that the periodic Markov chain based the copula models is a practicable method to simulate intermittent monthly streamflow time series.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2005.05b
• /
• pp.143-148
• /
• 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 Korea Water Resources Association
• /
• v.44 no.11
• /
• pp.853-861
• /
• 2011

The objective of this study is to assess Sejong University River Forecast (SURF) model which consists of a continuous rainfall-runoff model and measured streamflow assimilation using ensemble Kalman filter technique for streamflow forecast on Nakdong river basin. The study area is divided into 43 subbasins. The forecasted streamflows are evaluated at 12 measurement sites during flood season from 2006 to 2007. The forecasted ones are improved due to the impact of the measured streamflows assimilation. In effectiveness indices corresponding to 1~5 h forecast lead times, the accuracy of the forecasted streamflows with the assimilation approach is improved by 46.2~30.1% compared with that using only the rainfall-runoff model. The mean normalized absolute error of forecasted peak flow without and with data assimilation approach in entering 50% of the measured rainfall, respectively, the accuracy of the latter is improved about 40% than that of the former. From these results, SURF model is able to be used as a real-time river forecast model.

• Journal of Korea Water Resources Association
• /
• v.40 no.3
• /
• pp.251-263
• /
• 2007

In this paper, we constructed the integrated watershed model system, SWAT-Nak Dong that include areal mean precipitaiton, runoff and water balance components in the Nak Dong river basins and with this model system we are capable of estimating streamflows for ungaged river stations and analyzing the variations of the streamflows. SWAT(Soil and Water Assessment Tool) is a conceptual, continous time model that was developed in the early 1990s to assist water resource managers in assessing the impact of management and climate on water supplies and non-point source pollution III watersheds and large river basins. Using the SWAT-Nak Dong system and various scenarios, we analyzed and evaluated the dams and water uses effects on the streamflows.

• Journal of Korea Water Resources Association
• /
• v.42 no.2
• /
• pp.161-168
• /
• 2009

The purpose of this study is to evaluate the variation of probability flood according to the flow regulation by multi-purpose dams (Soyang and Chungju) in the Han-river basin, Korea. SWAT-K (Soil and Water Assessment Tool-Korea) was used in order to generate regulated and unregulated daily streamflows upstream of Paldang dam. Simulated flow regulated by the Soyang and Chungju dams was calibrated by comparison with the observed inflow data at Paldang reservoir. Generally the ratio of flood flows to daily streamflows is known to decrease with drainage area in a watershed. Regulated and unregulated flood flows were obtained from the relationship between flood flows and daily streamflows. Extreme Type-I distribution was applied for flood frequency analysis and L-moment method was used for parameter estimation. This is a novel approach capable of understanding the variation in flood frequency with dam operation for the relatively large watershed scale, and this will helps improve the applicability of daily stream flow data for use in flood control as well as in water utilization.

• Water for future
• /
• v.25 no.3
• /
• pp.105-113
• /
• 1992

The purpose of this paper is to introduce and to apply the artificial neural network theory to real hydrologic system for forecasting daily streamflows during flood periods. The hydrologic dynamic process of rainfall-runoff is identified by the iterated estimation of system parameters that are determined by adjusting the weights of the network according to the non-linear response characteristics which is formed the model. Back propagation algorithm of neural network model is applied for the estimation of system parameters with past daily rainfall and runoff series data, and streamflows are forecasted using the parameters. The forecasted results are analyzed by statistical methods for the comparison with the observed.

• Water for future
• /
• v.18 no.2
• /
• pp.153-161
• /
• 1985

The methods for hydrologic prediction of streamflows for more efficient and functional operations and automation of the flood warning and forecasting system have been studiedand which have been widely used in the control engineering have been studied and investigated for representation of the dynamic behavior of rainfall-runoff precesses, and formulated into mathematical model form. The applicabilities of the model using the adaptive Kalman filter algorithm to the on-line, real-time prediction of river flows have been worked out. The computer programs in FORTRAN which are developed here can be utilized for more efficient operations and better prediction abilities of flood warning and forecasting systems, and also should be modified for better model performance.

• Proceedings of the Korea Water Resources Association Conference
• /
• 1992.07a
• /
• pp.411-418
• /
• 1992

The purpose of this study is to develop dynamic-stochastic models that can forecast the inflow into reservoir during low/drought periods and flood periods. For the formulation of the models, the discrete transfer function is utilized to construct the deterministic characteristics, and the ARIMA model is utilized to construct the stochastic characteristics of residuals. The stochastic variations and structures of time series on hydrological data are examined by employing the auto/cross covariance function and auto/cross correlation function. Also, general modeling processes and forecasting method are used the model building methods of Box and Jenkins. For the verifications and applications of the developed models, the Chungju multi-purpose reservoir which is located in the South Han river systems is selected. Input data required are the current and past reservoir inflow and Yungchun water levels. In order to transform the water level at Yungchon into streamflows, the water level-streamflows rating curves at low/drought periods and flood periods are estimated. The models are calibrated with the flood periods of 1988 and 1989 and hourly data for 1990 flood are analyzed. Also, for the low/drought periods, daily data of 1988 and 1989 are calibrated, and daily data for 1989 are analyzed.

• Journal of Korea Water Resources Association
• /
• v.41 no.11
• /
• pp.1095-1106
• /
• 2008

Climate change and global warming are prevalent all over the world in this century and many researchers including hydrologists have studied on the climate change. This study also studied the impact of climate change on streamflows of a basin in Korea. The SWAT model was used to assess the impacts of potential future climate change on the streamflows of the Daecheong Dam Basin. Calibration and validation of SWAT were performed on a monthly basis for the year of 1982-1995 and 1996-2005, respectively. The impact of seven 15-year(1988-2002) scenarios were then analyzed for comparing it to the baseline scenario. Among them, scenario 1 was set to show the result of doubling $CO_2$, scenario 2-6 were set to show the results of temperature and precipitation change, and scenario 7 was set to show the result of the combination of climatologic components. A doubling of atmospheric $CO_2$ concentration is predicted to result in an maximum monthly flow increase of 11 percent. Non-linear impacts were predicted among precipitation change scenarios of -42, -17, 17, and 42 percent, which resulted in average annual flow changes in Daecheong Dam Basin of -55, -24, 25, and 64 percent. The changes in streamflow indicate that the Daecheong Dam Basin is very sensitive to potential future climate changes and that these changes could stimulate the increased period or severity of flood or drought events.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2005.05b
• /
• pp.1219-1223
• /
• 2005

This study was accomplished to confirm the possibility of supplying stream minimum flow from detention storage which was determined to reduce peak flows of flood within developing planned district. The results analyzed was summarized as follows; Firstly, Sin-gil district situated in Ansan city was selected, of which watershed area has $0.56km^2$. And detention storage was determined to $5,370m^3$ from analyzing flood volume by the SCS unit hydrograph method. Secondly, using Visual Basic ver 6.0, a detention storage water balance model was developed, in which simulation was based on conditioning storage inflow and outflow according to streamflow volume or rate state. And streamflow was simulated using the DAWAST model. Thirdly, detention operation scenarios were consisted of the combinations with inflow referencing streamflow of 5mm/day, 10mm/day and outflow referencing streamflow of 1mm/day, 2mm/day. The developed detention storage water balance model was operated to simulate daily water storages of detention sized on flood by scenarios. Stream minimum flows were able to be supplied during 209 days to 237 days per a year, total volume of stream minimum flows supplied for this period was analyzed to reach 27 to $55\% of yearly streamflow volume. If inflow criteria of streamflows to detention was considered to be established on a theoretical condition, it is expected to supply stream minimum flows of 20 to $30\% of yearly streamflow from stream to detention. Also to maximize function of supplying urban stream minimum flow from detention storages, sewage waters within developing planned district have to be treated and entered to detention inflow together with streamflows to enrich function of detention planned to reduce flood volumes.