• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.32 no.4B
• /
• pp.221-232
• /
• 2012

In this study, the model enhancing the safety of reservoirs and reducing the downstream flood damage by reservoirs system operation during abnormal flood was developed. Linear programming was used for the optimal reservoirs system operation during an abnormal flood and fuzzy inference system was introduced to solve the uncertainty problem which is included in hydrological factors like inflow, water level and inflow variation of reservoir operation. The linear programming model determined the optimal reservoir system operation rules and could be used in situation where water demands varies rapidly during the abnormal flood events using fuzzy control technique. In this study, the optimal reservoirs system operation for Andong and Imha reservoirs located in the upper basin of Nakdong river was performed in order that the design flood discharge at Andong city would not be exceeded for the design flood of 100 year and PMF(Probable Maximum Flood). And the model that determines the release according to the downstream flow discharge, the reservoir storage, the inflow and the inflow variation of each reservoir was developed using the optimal system operation result and fuzzy control technique. The developed model consisted of 224 fuzzy rules according to the conditions of Andong reservoir, Imha reservoir and Andong city. And the release from each reservoir could be determined when the current data are used as input data through the developed GUI.

• Journal of Korea Water Resources Association
• /
• v.45 no.8
• /
• pp.839-851
• /
• 2012

When we evaluate the water supply capacity of a river basin, it is a common practice to gradually increase the water demand and check if the water demands are met. This practice is not only used in the simulation approach, but also in the optimization approach. However, this trial and error approach is a tedious task. Hence, we propose a two-phase method. In the first phase, by assuming that the decision maker has complete information on inflow data, we use a goal programming model that can generate the maximum water supply capacity at one time. In the second phase, we simulate the real-time operation for the critical period by utilizing the water supply capacity given by the goal programming model under the condition that there is no foresight of inflow. We applied the two-phase method to the Geum-River basin, where multi-purpose weirs were newly constructed. By comparing the results of the goal programming model with those of the real-time simulation model we could comprehend and estimate the effect of perfect inflow data on the water supply capacity.

• Journal of Distribution Science
• /
• v.11 no.10
• /
• pp.73-79
• /
• 2013

Purpose - This study examines the impact of oil price volatility on economic activities in Korea. The new millennium has seen a deregulation in the crude oil market, which invited immense capital inflow into Korea. It has also raised oil price levels and volatility. Drawing on the recent theoretical literature that emphasizes the role of volatility, this paper attends to the asymmetric changes in economic growth in response to the oil price movement. This study further examines several key macroeconomic variables, such as interest rate, production, and inflation. We come to the conclusion that oil price volatility can, in some part, explain the structural changes. Research design, data, and methodology - We use two methodological frameworks in this study. First, in regards to the oil price uncertainty, we use an Exponential-GARCH (Exponential Generalized Autoregressive Conditional Heteroskedasticity: EGARCH) model estimate to elucidate the asymmetric effect of oil price shock on the conditional oil price volatility. Second, along with the estimation of the conditional volatility by the EGARCH model, we use the estimates in a VECM (Vector Error Correction Model). The study thus examines the dynamic impacts of oil price volatility on industrial production, price levels, and monetary policy responses. We also approximate the monetary policy function by the yield of monetary stabilization bond. The data collected for the study ranges from 1990: M1 to 2013: M7. In the VECM analysis section, the time span is split into two sub-periods; one from 1990 to 1999, and another from 2000 to 2013, due to the U.S. CFTC (Commodity Futures Trading Commission) deregulation on the crude oil futures that became effective in 2000. This paper intends to probe the relationship between oil price uncertainty and macroeconomic variables since the structural change in the oil market became effective. Results and Conclusions - The dynamic impulse response functions obtained from the VECM show a prolonged dampening effect of oil price volatility shock on the industrial production across all sub-periods. We also find that inflation measured by CPI rises by one standard deviation shock in response to oil price uncertainty, and lasts for the ensuing period. In addition, the impulse response functions allude that South Korea practices an expansionary monetary policy in response to oil price shocks, which stems from oil price uncertainty. Moreover, a comparison of the results of the dynamic impulse response functions from the two sub-periods suggests that the dynamic relationships have strengthened since 2000. Specifically, the results are most drastic in terms of industrial production; the impact of oil price volatility shocks has more than doubled from the year 2000 onwards. These results again indicate that the relationships between crude oil price uncertainty and Korean macroeconomic activities have been strengthened since the year2000, which resulted in a structural change in the crude oil market due to the deregulation of the crude oil futures.

• Journal of Korea Water Resources Association
• /
• v.50 no.7
• /
• pp.475-488
• /
• 2017

To simulate accurate drought, a drought index is needed to reflect the hydrometeorological phenomenon. Several studies have been conducted in Korea using the Modified Surface Water Supply Index (MSWSI) to simulate hydrological drought. This study analyzed the limitations of MSWSI and quantified the uncertainties of MSWSI. The influence of hydrometeorological components selected as the MSWSI components was analyzed. Although the previous MSWSI dealt with only one observation for each input component such as streamflow, ground water level, precipitation, and dam inflow, this study included dam storage level and dam release as suitable characteristics of the sub-basins, and used the areal-average precipitation obtained from several observations. From the MSWSI simulations of 2001 and 2006 drought events, MSWSI of this study successfully simulated drought because MSWSI of this study followed the trend of observing the hydrometeorological data and then the accuracy of the drought simulation results was affected by the selection of the input component on the MSWSI. The influence of the selection of the probability distributions to input components on the MSWSI was analyzed, including various criteria: the Gumbel and Generalized Extreme Value (GEV) distributions for precipitation data; normal and Gumbel distributions for streamflow data; 2-parameter log-normal and Gumbel distributions for dam inflow, storage level, and release discharge data; and 3-parameter log-normal distribution for groundwater. Then, the maximum 36 MSWSIs were calculated for each sub-basin, and the ranges of MSWSI differed significantly according to the selection of probability distributions. Therefore, it was confirmed that the MSWSI results may differ depending on the probability distribution. The uncertainty occurred due to the selection of MSWSI input components and the probability distributions were quantified using the maximum entropy. The uncertainty thus increased as the number of input components increased and the uncertainty of MSWSI also increased with the application of probability distributions of input components during the flood season.

• Journal of Korea Water Resources Association
• /
• v.51 no.spc
• /
• pp.1135-1148
• /
• 2018

Previous studies on reservoir operation have been assumed that the climate in the future would be similar to that in the past. However, in the presence of climate non-stationarity, Robust Optimization (RO) which finds the feasible solutions under broader uncertainty is necessary. RO improves the existing optimization method by adding a robust term to the objective function that controls the uncertainty inherent due to input data instability. This study proposed Robust-SDP that combines Stochastic Dynamic Programming (SDP) and RO to estimate dam operation rules while coping with climate non-stationarity. The future inflow series that reflect climate non-stationarity were synthetically generated. We then evaluated the capacity of the dam operation rules obtained from the past inflow series based on six evaluation indicators and two decision support schemes. Although Robust-SDP was successful in reducing the incidence of extreme water scarcity events under climate non-stationarity, there was a trade-off between the number of extreme water scarcity events and the water scarcity ratio. Thus, it is proposed that decision-makers choose their optimal rules in reference to the evaluation results and decision support illustrations.

• Journal of Korea Water Resources Association
• /
• v.44 no.12
• /
• pp.991-1000
• /
• 2011

The relationship between discharge (Q) and suspended sediment (SS) concentration often is used for the estimation of inflow SS concentration in reservoir turbidity modeling in the absence of actual measurements. The power function, SS=aQb, is the most commonly used empirical relation to determine the SS load assuming the SS flux is controlled by variations of discharge. However, Q-SS relation typically is site specific and can vary depending on the season of the year. In addition, the relation sometimes shows hysteresis during rising limb and falling limb for an event hydrograph. The objective of this study was to examine the hysteresis of Q-SS relationships through continuous field measurements during flood events at inflow rivers of Yongdam Reservoir and Soyang Reservoir, and to analyze its effect on the bias of SS load estimation. The results confirmed that Q-SS relations display a high degree of scatter and clock-wise hysteresis during flood events, and higher SS concentrations were observed during rising limb than falling limb at the same discharge. The hysteresis caused significant bias and underestimation of SS loading to the reservoirs when the power function is used, which is important consideration in turbidity modeling for the reservoirs. As an alternative of Q-SS relation, turbidity-SS relation is suggested. The turbidity-SS relations showed less variations and dramatically reduced the bias with observed SS loading. Therefore, a real-time monitoring of inflow turbidity is necessary to better estimate of SS influx to the reservoirs and enhance the reliability of reservoir turbidity modeling.

• Journal of Korea Water Resources Association
• /
• v.37 no.3
• /
• pp.195-206
• /
• 2004

One of the main factors which reduces the efficiency of a sewage treatment plant is the Inflow/Infiltration(Ⅰ/Ⅰ) in the sewer First we must calculate the quantity of Ⅰ/Ⅰ via the investigation of each sewer to establish the reduction plan of Ⅰ/Ⅰ. However, in Korea, we apply the results of a surveyed sample to the entire study area to establish the reduction plan of Ⅰ/Ⅰ. This methodology just considers the total Ⅰ/Ⅰ for the entire study area but it does not consider the quantity of Ⅰ/Ⅰ for the individual sewer systems. Therefore, we may need the model to consider the Ⅰ/Ⅰ in the individual sewer systems and we develop the model to calculate the Ⅰ/Ⅰ that happen in urban sewer systems. We estimate the Ⅰ/Ⅰ of individual systems by the developed model and the estimated Ⅰ/Ⅰ are utilized as the basic data for the establishment of Ⅰ/Ⅰ reduction plan. The observed Ⅰ/Ⅰ for the entire study area is distributed into the individual sewer systems according to their defect states. Here, the weights of defect elements are calculated using AHP(Analytic Hierarchy Process) and we perform the uncertainty analysis for considering the errors using MCS(Monte Carlo Simulation).

• Journal of Korea Water Resources Association
• /
• v.55 no.12
• /
• pp.1115-1124
• /
• 2022

The impact of climate change on water resources was evaluated for Chungju Dam and Soyang-gang Dam basins by constructing an integrated modeling framework consisting of a dam inflow prediction model based on the Variable Infiltration Capacity (VIC) model, a distributed hydrologic model, and an LSTM based dam outflow prediction model. Considering the uncertainty of future climate data, four models of CMIP6 GCM were used as input data of VIC model for future period (2021-2100). As a result of applying future climate data, the average inflow for period increased as the future progressed, and the inflow in the far future (2070-2100) increased by up to 22% compared to that of the observation period (1986-2020). The minimum value of dam discharge lasting 4~50 days was significantly lower than the observed value. This indicates that droughts may occur over a longer period than observed in the past, meaning that citizens of Seoul metropolitan areas may experience severe water shortages due to future droughts. In addition, compared to the near and middle futures, the change in water storage has occurred rapidly in the far future, suggesting that the difficulties of water resource management may increase.

• Korean Journal of Agricultural Science
• /
• v.47 no.1
• /
• pp.19-28
• /
• 2020

This study proposed a simple estimation method for irrigation return flow from paddy fields using the water balance model. The merit of this method is applicability to other paddy fields irrigated from agricultural reservoirs due to the simplicity compared with the previous monitoring based estimation method. It was assumed that the unused amount of irrigation water was the return flow which included the quick and delayed return flows. The amount of irrigation supply from a reservoir was estimated from the reservoir water balance with the storage rate and runoff model. It was also assumed that the infiltration was the main source of the delayed return flow and that the other delayed return flow was neglected. In this study, the amount of reservoir inflow and water demand from paddy field are calculated on a daily basis, and irrigation supply was calculated on 10-day basis, taking into account the uncertainty of the model and the reliability of the data. The regression rate was calculated on a yearly basis, and yearly data was computed by accumulating daily and 10-day data, considering that the recirculating water circulation cycle was relatively long. The proposed method was applied to the paddy blocks of the Jamhong and Seosan agricultural reservoirs and the results were acceptable.

• Journal of Korean Society of Water and Wastewater
• /
• v.25 no.3
• /
• pp.293-305
• /
• 2011

A special concern is paid to the risks with which small-sized water resources systems are confronted in supplying water in the far future. Taking the Gwangdong dam reservoir as a case study, the authors seek to understand demand-side and supply-side disturbances of a reservoir, which, respectively, corresponds to effects of water demand changes on the intake amount and those of climate changes on the inflow amount. In result, it is demonstrated that both disturbances in the next 50 years are almost unpredictable. Yet the projection ranges, thought of as relatively reliable information that models offer, reveal that severity and period of water shortage is very likely to change. It is therefore concluded that water resources management requires more rigorous approaches to overcoming high uncertainties. The methods and models for projecting those disturbances are selected, based on practicality and applicability. Nevertheless, they show a large usefulness, especially in dealing with data shortage and reducing the needs for expensive modeling resources.