Many problems that are encountered in regards to water balance and resources management are related to challenges of economic development under limited resources and tough competition among various water uses. The development of major infrastructure like airports in remote areas that have limited water resources is becoming a common problem. In order to overcome these difficulties, water management has to articulate and combine several resources in order to respond to various demands while preserving the ecological quality of the environment. The paper discusses the interest in implementing the Smart Water Grid concept on Yeongjongdo Island, which is the location of Korea's main airport. This new concept is based on the connection of various water resources and their optimized management with new information technology solutions. The proposed system integrates water generated through rainfall, external water resources (i.e., metropolitan water distribution system), gray water and other types of alternative water resources. The paper analyses the feasibility of this approach and explores interest in the Smart Water Grid concept.
This study begins to address the need for a runoff model that is able to simulate runoffs at control points in a dam's upper and lower stream during the seasons of high and low water levels. We need to establish a synthetic management plan on water resources considering the runoff at the upper and lower streams to effectively manage the limited water resources in Korea. For this reason, we classified the Han River Basin into 24 subbasins and arranged a great amount of rainfall data using 151 rainfall observation stations so as to prepare for the spatial distribution of precipitation. We chose several dams as subjects for this study, which includes the Chungju Regulating Reservoir, Soyang, Chungju, Hoengseong, Hwacheon, Chuncheon, Euiam, Cheongpyeong, and Paldang Dams as main controlling points. Also, we made up input data of this model, selecting the Streamflow Synthesis and Reservoir Regulation (SSARR) model as a runoff model in the Han River Basin. We performed a sensitivity analysis of parameters using hydrological data from the year 2002. And as a result, the findings of this study showed that, among many parameters related to the basin runoff, the following have revealed greater sensitivity than any other parameters: soil moisture index-runoff percent, baseflow infiltration index-baseflow percent, and surface-subsurface separation. On the basis of the above sensitivity analysis, we have used hydrological data between 2001 and 2002 when drafts and floods broke out in Korea to verify and calibrate the parameters of the SSARR model. Furthermore, we verified and calibrated the 2000 data using corrected parameters and performed an analysis of annual water balance in the Han River Basin from 1996 to 2005 considering agricultural water.
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=aQ b , 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.
For the efficient management of water resources in the target basin, this study proposed a method to improve the reliability of a long-term hydrological simulation model by applying to the model agricultural water more approximate to actual water uses (than planned water demands) through their adjustment based on the effects of small-scale hydraulic structures. To verify agricultural water uses estimated using the proposed method, they were applied to a basin management model. And then, simulated runoff at main station points was compared with measured runoff. As a result, there occurred errors with large differences from measured data, mainly, at station points where their dependency on river water was high. To verify simulated return rate, return rate for a test zone was estimated, and then compared with the simulated return rate. Correlations between annual rainfall and runoff errors were analyzed. As a result, it was found that those errors were enlarged in dry years. Long-term runoff simulation analysis showed that simulated runoff came to be negative when a farming season began. This could be significantly improved using water uses adjusted to consider the effects of small-scale hydraulic structures. Also, correlation analysis quantitatively confirmed that simulated runoff after adjustment was more correlated with measured runoff than before adjustment. Finally, fitness tests for runoff simulations before and after adjustment were carried out through a residual analysis to analyze residual normality and independence. As a result, the fitness of runoff simulation after adjustment was significantly improved.
In this study the validities of runoff prediction methods are reviewed around ESP (Ensemble Streamflow Prediction) techniques. The improvements of runoff predictions on Yongdam river basin are evaluated by the comparison of different prediction methods including ESP incorporated with qualitative meteorological outlooks provided by meteorological agency as well as the runoff forecasting based on the analysis of the historical rainfall scenarios. As a result it is assessed that runoff predictions with ESP may give rise to more accurate results than the ordinary historical average runoffs. In deed the latter gave the mean of yearly absolute error as to be 60.86 MCM while the errors of the former ones amounted to 44.12 MCM (ESP) and 42.83 MCM (ESP incorporated with qualitative meteorological outlooks) respectively. In addition it is confirmed that ESP incorporated with qualitative meteorological outlooks could improve the accuracy of the results more and more. Especially the degree of improvement of ESP with meteorological outlooks shows rising by 10.8% in flood season and 8% in drought season. Therefore the methods of runoff predictions with ESP can be further used as the basic forecasting information tool for the purpose of the effective watershed management.
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