• Water Engineering Research
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• v.3 no.1
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• pp.57-62
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• 2002

This research is intended to integrate long-term operation rules and real time operation policy for conservation & flood control in a reservoir. The familiar Yield model has been modified and used to provide long-term rule curves. The model employs linear programming technique under given physical conditions, i.e., total capacity, dead storage, spillways, outlet capacity and their respective elevations to find required and desired minimum storage fur different demands. To investigate the system behavior resulting from the above-mentioned operating policy, i.e., the rule curves, the simulation model was used. Results of the simulation model show that the results of the optimization model are indeed valid. After confirmation of the above mentioned rule curves by the simulation models, gate operation procedure was merged with the long term operation rules to determine the optimum reservoir operating policy. In the gate operation procedure, operating policy in downstream flood plain, i.e., determination of damaging and non-damaging discharges in flood plain, peak floods, which could be routed by reservoir, are determined. Also outflow hydrograph and variations of water surface levels for two known hydrographs are determined. To examine efficiency of the above-mentioned models and their ability in determining the optimum operation policy, Esteghlal reservoir in Iran was analyzed as a case study. A numerical model fur the solution of two-dimensional dam break problems using fractional step method is developed on unstructured grid. The model is based on second-order Weighted Averaged Flux(WAF) scheme with HLLC approximate Riemann solver. To control the nonphysical oscillations associated with second-order accuracy, TVD scheme with SUPERBEE limiter is used. The developed model is verified by comparing the computational solutions with analytic solutions in idealized test cases. Very good agreements have been achieved in the verifications.

• Water for future
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• v.29 no.5
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• pp.223-233
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• 1996

Daily streamflow model, DAWAST, considering the meteorologic and geographic characteristics of the Korean watersheds has been developed to simulate the daily streamflow with the input data of daily rainfall and pan evaporation. The model is the conceptual one with three sub-models which are optimization, generalization, and regionalization models. The conceptual model consists of three linear reservoirs representing the surface, unsaturated, and saturated soil zones and water balance analysis was carried out in each soil zones on a daily basis. Optimization model calibrates the parameters by optimization technique and is applicable to the watersheds where the daily streamflow data are available Generalization model predicts the parameters by regression equations considering the geographic, soil type, land use, and hydrogeologic characteristics of watershed and is appicable to ungaged medium or small watersheds. Regionalization model cites the parameters from the analysed ones considering river system, latitude and longitude, and is applicable to ungaged large watersheds.

• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.123-132
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• 2000

In the study the instantaneous unit hydrographs (IUHs) based on the linear Nash (1957) and the nonlinear Diskin (1964) models are derived and compared for the Soyang river basin. Total 14 rainfall runoff events are used for the study and the model parameters are estimated by minimizing the sum of square error considering runoff hydrograph ordinates as relative weights. The representative IUHs for both models are decided to show an average shape of derived IUHs. In the application of the representative IUHs of Nash and Diskin, Diskin model shows better performances in reproducing the observed outflows, especially the peak flow. In the comparison of two Diskin models little difference could be found between the IUHs with the same or different number of two characteristic reservoirs.rvoirs.

• Journal of Korean Society on Water Environment
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• v.33 no.3
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• pp.326-333
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• 2017

The lakes and reservoirs have been reported as important sources of carbon emissions to the atmosphere in many countries. Although field experiments and theoretical investigations based on the fundamental gas exchange theory have proposed the quantitative amounts of Net Atmospheric Flux (NAF) in various climate regions, there are still large uncertainties at the global scale estimation. Mechanistic models can be used for understanding and estimating the temporal and spatial variations of the NAFs considering complicated hydrodynamic and biogeochemical processes in a reservoir, but these models require extensive and expensive datasets and model parameters. On the other hand, data driven machine learning (ML) algorithms are likely to be alternative tools to estimate the NAFs in responding to independent environmental variables. The objective of this study was to develop random forest (RF) and multi-layer artificial neural network (ANN) models for the estimation of the daily $CO_2$ NAFs in Daecheong Reservoir located in Geum River of Korea, and compare the models performance against the multiple linear regression (MLR) model that proposed in the previous study (Chung et al., 2016). As a result, the RF and ANN models showed much enhanced performance in the estimation of the high NAF values, while MLR model significantly under estimated them. Across validation with 10-fold random samplings was applied to evaluate the performance of three models, and indicated that the ANN model is best, and followed by RF and MLR models.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.839-852
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• 2018

The purpose of this study is to predict monthly agricultural reservoir storage by developing weather data-based Multiple Linear Regression Model (MLRM) with precipitation, maximum temperature, minimum temperature, average temperature, and average wind speed. Using Naïve-Bayes classification, total 1,559 nationwide reservoirs were classified into 30 clusters based on geomorphological specification (effective storage volume, irrigation area, watershed area, latitude, longitude and frequency of drought). For each cluster, the monthly MLRM was derived using 13 years (2002~2014) meteorological data by KMA (Korea Meteorological Administration) and reservoir storage rate data by KRC (Korea Rural Community). The MLRM for reservoir storage rate showed the determination coefficient ($R^2$) of 0.76, Nash-Sutcliffe efficiency (NSE) of 0.73, and root mean square error (RMSE) of 8.33% respectively. The MLRM was evaluated for 2 years (2015~2016) using 3 months weather forecast data of GloSea5 (GS5) by KMA. The Reservoir Drought Index (RDI) that was represented by present and normal year reservoir storage rate showed that the ROC (Receiver Operating Characteristics) average hit rate was 0.80 using observed data and 0.73 using GS5 data in the MLRM. Using the results of this study, future reservoir storage rates can be predicted and used as decision-making data on stable future agricultural water supply.

• Journal of Ecology and Environment
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• v.40 no.2
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• pp.125-135
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• 2016

Background: The objectives of this study were to establish a swimming capability model for largemouth bass using the FishXing (version 3) program, and to determine the swimming speed and feasibility of fish passage through a waterway tunnel. This modeling aimed to replicate the waterway tunnel connecting the Andong and Imha Reservoirs in South Korea, where there is a concern that largemouth bass may be able to pass through this structure. As largemouth bass are considered an invasive species, this spread could have repercussions for the local environment. Results: Flow regime of water through the waterway tunnel was calculated via the simulation of waterway tunnel operation, and the capability of largemouth bass to pass through the waterway tunnel was then estimated. The swimming speed and distance of the largemouth bass had a positive linear function with total length and negative linear function with the flow rate of the waterway tunnel. The passing rate of small-size largemouth bass (10-30 cm) was 0%at a flow of $10m^3/s$ due to rapid exhaustion from prolonged upstream swimming through the long (1.952 km) waterway tunnel. Conclusions: The results of FishXing showed that the potential passing rate of large size largemouth bass (>40 cm) through the waterway tunnel was greater than 10%; however, the passage of largemouth bass was not possible because of the mesh size ($3.4{\times}6.0cm$) of the pre-screening structures at the entrance of the waterway tunnel. Overall, this study suggests that the spread of largemouth bass population in the Imha Reservoir through the waterway tunnel is most likely impossible.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.389-394
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• 2008

The purpose of this research was to develop a methodology to determine whether conjunctive surface water and groundwater management could significantly reduce deficits in a river basin with a relatively limited alluvial aquifer. The Geum River basin is one of major river basins in South Korea. The upper region of the Geum River basin is typical of many river basins in Korea where the shape of river basin is narrow with small alluvial aquifer depths from 10m to 20m and where most of the groundwater pumped comes quickly from the steamflow. The basin has two surface reservoirs, Daecheong and Yongdam. The most recent reservoir, Yongdam, provides water to a trans-basin diversion, and therefore reduces the water resources available in the Geum River basin. After the completion of Yongdam reservoir, the reduced water supply in the Geum basin resulted in increasing conflicts between downstream water needs and required instream flows, particularly during the low flow season. Historically, the operation of groundwater pumping has had limited control and is administered separately from surface water diversions. Given the limited size of the alluvial aquifer, it is apparent that groundwater pumping is essentially taking its water from the stream. Therefore, the operation of the surface water withdrawals and groundwater pumping must be considered together. The major component of the conjunction water management in this study is a goal-programmin g based optimization model that simultaneously considers surface water withdrawals, groundwater pumping and instream flow requirements. A 10-day time step is used in the model. The interactions between groundwater pumping and the stream are handled through the use of response and lag coefficients. The impacts of pumping on streamflow are considered for multiple time periods. The model is formulated as a linear goal-programming problem that is solved with the commercial LINGO optimization software package.

• Korean Journal of Environmental Biology
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• v.26 no.3
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• pp.252-263
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• 2008

The purpose of this study was to determine trophic state, based on nutrients (TN, TP), transparency (SD), and chlorophyll-${\alpha}$ (Chl) and identify their empirical relations of TN-Chl, TP-Chl and Chl-SD depending on the dataset used along with dynamics of conductivity and suspended solids. Analysis of trophic states showed that more than half of 36 reservoirs were judged as eutrophic-hypertrophic conditions depending on the trophic variables. Seasonal values of TP varied by nearly 500% and showed greater in August than any other months. In contrast, TN varied within less than 90% and all monthly mean values of TN were never fall less than 1.2 mg L$^{-1}$ indicating low seasonal variations and high ambient concentrations (eutrophic-hypertrophic state). Analysis of empirical relations in the trophic variables showed that transparency had greater functional relations with Chl (R$^2$=0.31, p<0.001) than TP (R$^2$=0.15, p<0.001) and TN (R$^2$=0.20, p<0.001). Ratios of TN : TP in the ambient water indicated that most reservoirs showed a potential phosphorous limitation on the algal growth. Thus, algal biomass, based on Chl values, was more regulated by phosphorous than nitrogen. Analysis of linear regression model, based on log-transformed annual mean values, showed that only 30% in the variation of Chl was explained by TP (R$^2$=0.295, p=0.001, n=36) and 15% by TN (R$^2$=0.151, p=0.019, n=36). However, linear regression model, based on individual system, showed that Chl-TP model had strong positive relations (R$^2$=0.62, p=0.002, n=12), whereas the model had no any relations (p=0.892, n=12). Overall, our data suggested that averaging effect in the empirical model developments may influence the significance in the statistical analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.107-120
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• 2010

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 was assessed using the SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. The fundamental input data (elevation, meteorological data, land use, soil, vegetation) was collected to calibrate and validate of the SLURP model for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang and Gosam) located in Anseongcheon watershed. Then, the CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change) was used to assess the future potential climate change. The future weather data for the year, m ms, m5ms and 2amms was downscaled by Change Factor method through bias-correction using 3m years (1977-2006) weather data of 3 meteorological stations of the watershed. In addition, the future land uses were predicted by modified CA (cellular automata)-Markov technique using the time series land use data fromFactosat images. Also the future vegetation cover information was predicted and considered by the linear regression between monthly NDVI (normalized difference vegetation index) from NOAA AVHRR images and monthly mean temperature using eight years (1998-2006) data.

• Journal of Korea Water Resources Association
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• v.42 no.8
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• pp.643-657
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• 2009

The major reason to construct large dams is to store surplus water during rainy seasons and utilize it for water supply in dry seasons. Reservoir storage has to meet a pre-defined target to satisfy water demands and cope with a dry season when the availability of water resources are limited temporally as well as spatially. In this study, a Hedging rule that reduces total reservoir outflow as drought starts is applied to alleviate severe water shortages. Five stages for reducing outflow based on the current reservoir storage are proposed as the Hedging rule. The objective function is to minimize the total discrepancies between the target and actual reservoir storage, water supply and demand, and required minimum river discharge and actual river flow. Mixed Integer Linear Programming (MILP) is used to develop a multi-reservoir operation system with the Hedging rule. The developed system is applied for the Han River basin that includes four multi-purpose dams and one water supplying reservoir. One of the fours dams is primarily for power generation. Ten-day-based runoff from subbasins and water demand in 2003 and water supply plan to water users from the reservoirs are used from "Long Term Comprehensive Plan for Water Resources in Korea" and "Practical Handbook of Dam Operation in Korea", respectively. The model was optimized by GAMS/CPLEX which is LP/MIP solver using a branch-and-cut algorithm. As results, 99.99% of municipal demand, 99.91% of agricultural demand and 100.00% of minimum river discharge were satisfied and, at the same time, dam storage compared to the storage efficiency increased 10.04% which is a real operation data in 2003.