• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.359-369
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• 2024

Korea prepares for potential floods by designating June 21st to September 20th as the flood season. However, many dams in Korea have suffered from extreme floods caused by different climate patterns, as in the case of the longest consecutive rain of 54 days in the 2020's flood season. In this context, various studies have tried to develop novel methodologies to reduce flood damage, but no study has ever dealt with the validity of the current statutory flood season thus far. This study first checked the validity of the current flood season through the observation data in the 21st century and proved that the current flood season does not consider the effects of increasing precipitation trends and the changing regional rainfall characteristics. In order to deal with these limitations, this study suggested seven new alternative flood seasons in the research area. The rigid reservoir operation method (ROM) was used for reservoir simulation, and the long short-term memory (LSTM) model was used to derive predicted inflow. Finally, all alternatives were evaluated based on whether if they exceeded the design discharge of the dam and the design flood of the river. As a result, the floods in the shifted period were reduced by 0.068% and 0.33% in terms of frequency and duration, and the magnitude also decreased by 24.6%, respectively. During this period, the second evaluation method also demonstrated that flood decreased from four to two occurrences. As the result of this study, the authors expect a formal reassessment of the flood season to take place, which will ultimately lead to the preemptive flood response to changing precipitation patterns.

• Water Engineering Research
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• v.3 no.2
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• pp.143-153
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• 2002

As the natural flows in rivers dramatically decrease during drought season in Korea, a deterioration of river water quality is accelerated. Thus, consideration of downstream water quality responding to changes in reservoir release is essential for an integrated watershed management with regards to water quantity and quality. In this study, water quality models based on artificial neural networks (ANNs) method were developed using historical downstream water quality (rm $\NH_3$-N) data obtained from a water treatment plant in Geum river and reservoir release data from Daechung dam. A nonlinear multiple regression model was developed and compared with the ANN models. In the models, the rm NH$_3$-N concentration for next time step is dependent on dam outflow, river water quality data such as pH, alkalinity, temperature, and rm $\NH_3$-N of previous time step. The model parameters were estimated using monthly data from Jan. 1993 to Dec. 1998, then another set of monthly data between Jan. 1999 and Dec. 2000 were used for verification. The predictive performance of the models was evaluated by comparing the statistical characteristics of predicted data with those of observed data. According to the results, the ANN models showed a better performance than the regression model in the applied cases.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.1
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• pp.121-131
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• 2018

Past climate change influences multiple environmental aspects, certain of which are specifically related to agricultural water resources such as water supply and demand. Changes on rainfall and hydrologic patterns can increases the occurrence of reservoir water shortage and affect the future availability of agricultural water resources. It is a main concern for sustainable development in agricultural water resources management to evaluate adaptation capability of water supply under the changing climate and farming methods in paddy field. The purpose of this study is an evaluation method of design frequency of drought and water supply safety for agricultural reservoirs to investigate evidence of climate change occurrences at a local scale. Thus, it is a recommended practice in the development of water supply management strategies on reservoir operation under changing climate and farming methods in paddy field.

• Advances in environmental research
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• v.7 no.3
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• pp.161-175
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• 2018

Krishna River is significantly affected due to Srisailam dam from past 30 years. The impact of this hydraulic structure drastically reduced the minimum flow regime on the downstream, which made the river nearing to decaying stage. In the present paper, Environmental Flow called minimum flow values released for the dam are estimated with the help of three hydrological methods viz., Range of variability Approach (RVA), Desktop Reserve Model (DRM), and Global Environmental Flow Calculator (GEFC). DRM method suggested considering the intermediate values obtained from among the three methods to preserve the ecosystem on the downstream of the river, which amounts to an average annual allocation of 9378 Million Cubic Meter (MCM) which is equal to 23.11% of mean annual flow (MAF). In this regard GEFC and RVA methods accounted for 22% and 31.04% of MAF respectively. The results indicate that current reservoir operation policy is causing a severe hydrological alteration in the high flow season especially in the month of July. The study concluded that in the case of non-availability of environmental information, hydrological indicators can be used to provide the basic assessment of environmental flow requirements. It is inferred from the results obtained from the study, that the new reservoir operations can fulfil human water needs without disturbing Environmental Flow Requirements.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.965-977
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.121-135
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• 2010

This study is to assess the effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water supply using the SLURP. Before the future analysis, the SLURP model was calibrated using the 6 years daily streamflow records (1998-200398 and validated using 3 years streamflow data (2004-200698 for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang8 and Gosam98located in Anseongcheon watershed. The calibration and validation results showed that the model was able to simulate the daily streamflow well considering the reservoir operation for paddy irrigation and flood discharge, with a coefficient of determination and Nash-Sutcliffe efficiency ranging from s 7 to s 9 and 0.5 to s 8 respectively. Then, the future potential climate change impact was assessed using the future wthe fu data was downscaled by nge impFactor method throuih bias-correction, the future land uses wtre predicted by modified CA-Markov technique, and the future ve potentiacovfu information was predicted and considered by the linear regression bpowten mecthly NDVI from NOAA AVHRR ima ps and mecthly mean temperature. The future (2020s, 2050s and 2e 0s) reservoir inflow, the temporal changes of reservoir storaimpand its impact to downstream streamflow watershed wtre analyzed for the A2 and B2 climate change scenarios based on a base year (2005). At an annual temporal scale, the reservoir inflow and storaimpchange oue, anagricultural reservoir wtre projected to big decrease innautumnnunder all possiblmpcombinations of conditions. The future streamflow, soossmoosture and grounwater recharge decreased slightly, whtre as the evapotransporation was projected to increase largely for all possiblmpcombinations of the conditions. At last, this study was analysed contribution of weather, vegetation and land use change to assess which factor biggest impact on agricultural reservoir and stream watershed. As a result, weather change biggest impact on agricultural reservoir inflow, storage, streamflow, evapotranspiration, soil moisture and groundwater recharge.

• Journal of Korea Water Resources Association
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• v.41 no.4
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• pp.433-444
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• 2008

In recent, the integrated water resources management should consider not only existing management objects such as water supply, power generation, and instream flows but also new management objects such as water quantity, water quality, and water habitats which management system is large and complex. Moreover, integrated basin plan or operation are needed for solving conflicts problems between basins and between water usages and to maximize water resources usages. To increase use of optimization method for actual operation and apply various objects, a reservoir operation rule was developed and the KModSim's hydrologic states for integrated water resources management were tested in this study. The simulation results show that the developed operation rules applied in hydrologic states good represent the actual storages of both the Yongdam and the Daecheong Reservoirs so, it is possible to improve the water allocation method usually used in the basin management and manage the integrated basin water resources if new operating rules are applied in optimized programming.

• Journal of Korea Water Resources Association
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• v.38 no.11
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• pp.937-946
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• 2005

The objective of the study is to develop a reservoir optimal operation model and to suggest the appropriate amount of additional water supply and optimal operation rule. The model uses multiple objective function and a global search method, SCE-UA method. The objective function is set up to maintain the storage at target level, to satisfy the water demand, and to maximize the hydropower product. To evaluate the model's applicability, the model was applied for allocating the optimal water depending on storage level changes of Seomjin dam. The results comparing optimal operation and historical data showed that hydropower product increased from $-2.29\%$ to $14.51\%$, $-5.94\%$ to $3.98\%$, and $-0.43\%$ to $6.35\%$ with varying target levels in wet, dry, and normal period, respectively. Also, The model was applied for assessing water supply capacity of Seomjin dam to satisfy increasing water demand. The dam was operated by the model on consideration of downstream flow as 0.17, 0.50, 0.70, 1.0, 1.5, and $3.0\;m^3/sec$. The results showed that in case of operating the dam with downstream flow less than $0.70\;m^3/sec$ and with target water level lower than 194.0 m, hydropower product was more than the historical operation data and existing amount of water supply was less influenced.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.3
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• pp.3-10
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• 2007

In general method to estimate the water supplies in the large-scale basin, indirect estimation method such as unit loading factor method has been used. However, the estimated water supplies are much different to the real water supplies used in the any basin because these general methods estimate them considering water supply demands only. Especially, water supplies for irrigation are big different to the real water supplies in which the water supplies for irrigation are depend on the weather conditions such as evaporation, basin conditions such as infiltration, the reservoir operation rule for irrigation water, and distribution methods. Thus, a new estimation method is developed to estimate the real water demands which is essential factors for the effective water resources operation in the basin. This method is for estimating the water supplies and return rates based on the survey of the irrigation reservoirs and the analysis of effects to the stream flows, return flows, and water supplies for irrigation which water supplies and return rates are used in the basin water management model. The water supply usages in each subbasin are validated by comparisons between the simulated discharges from the basin water management model and the discharges measured in the control points.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.3
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• pp.27-42
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• 1984

The complexity and expensiveness of water resources projects have made optimum operation and design by computer-based techniques of increasing interest in recent years. Water resources problems in real world need many decisions under numerous constraints. In addition there are nonlinearities in the state and return function. This mathematical and technical troublesome must be overcome so that the optimum operation polices are determined. Then traditional dynamic optimization method encountered two major-cruxes: variable discretization and appearance of constraints. Even several recent methods which based on the Differential Dynamic Programming(DDP) have some difficulties in handling of constraints. This paper has presented New DDP which is applicable to multi-reservoir control. It is intended that the method suggested here is superior to abailable alternatives. This belief is supported by analysis and experiments(New DDT does not suffer course of dimensionality and requires no discretization and is able to handle easily all constraints nonlinearity).