• Journal of Climate Change Research
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• v.9 no.1
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• pp.47-58
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• 2018

In this study, we evaluated the uncertainty in the process of selecting GCM and downscaling method for assessing the impact of climate change, and influence of user-centered climate change information on reproducibility of Chungju Dam inflow was analyzed. First, we selected the top 16 GCMs through the evaluation of spatio-temporal reproducibility of 29 raw GCMs using 30-year average of 10-day precipitation without any bias-correction. The climate extreme indices including annual total precipitation and annual maximum 1-day precipitation were selected as the relevant indices to the dam inflow. The Simple Quantile Mapping (SQM) downscaling method was selected through the evaluation of reproducibility of selected indices and spatial correlation among weather stations. SWAT simulation results for the past 30 years period by considering limitations in weather input showed the satisfactory results with monthly model efficiency of 0.92. The error in average dam inflow according to selection of GCMs and downscaling method showed the bests result when 16 GCMs selected raw GCM analysi were used. It was found that selection of downscaling method rather than selection of GCM is more is important in overall uncertainties. The average inflow for the future period increased in all RCP scenarios as time goes on from near-future to far-future periods. Also, it was predicted that the inflow volume will be higher in the RCP 8.5 scenario than in the RCP 4.5 scenario in all future periods. Maximum daily inflow, which is important for flood control, showed a high changing rate more than twice as much as the average inflow amount. It is also important to understand the seasonal fluctuation of the inflow for the dam management purpose. Both average inflow and maximum inflow showed a tendency to increase mainly in July and August during near-future period while average and maximum inflows increased through the whole period of months in both mid-future and far-future periods.

• Korean Journal of Remote Sensing
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• v.24 no.1
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• pp.25-33
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• 2008

To investigate the hydrologic impacts of climate changes on dam inflow for Soyanggangdam watershed $(2694.4km^2)$ of northeastern South Korea, SLURP (Semi-distributed Land Use-based Runoff Process) model and the climate change results of CCCma CGCM2 based on SRES A2 and B2 were adopted. By the CA-Markov technique, future land use changes were estimated using the three land cover maps (1985, 1990, 2000) classified by Landsat TM satellite images. NDVI values for 2050 and 2100 land uses were estimated from the relationship of NDVI-Temperature linear regression derived from the observed data (1998-2002). Before the assessment, the SLURP model was calibrated and verified using 4 years (1998-2001) dam inflow data with the Nash-Sutcliffe efficiencies of 0.61 to 0.77. In case of A2 scenario, the dam inflows of 2050 and 2100 decreased 49.7 % and 25.0 % comparing with the dam inflow of 2000, and in case of B2 scenario, the dam inflows of 2050 and 2100 decreased 45.3 % and 53.0 %, respectively. The results showed that the impact of land use change covered 2.3 % to 4.9 % for the dam inflow change.

• Computers and Concrete
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• v.33 no.5
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• pp.559-572
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• 2024

Problems of under-sized dams (small dams with large basin area) could get worse under the global warming condition. This study evaluates the possible change of these problems with the Namgang Dam, an under-sized dam in Korea. For this purpose, first, this study simulates the dam inflow data using a rainfall-runoff model, which are then used as input for the reservoir operation. As a result, daily dam storage, dam release, and dam water supply are derived and compared for both past observed period (1973~2022) and future simulated period (2006~2099) based on the global warming scenarios. Summarizing the results are as follows. First, the inflow rate in the future is expected to be increased significantly. The maximum inflow could be twice of that observed in the past. As a result, it is also expected that the frequency of the water level reaching the high level is increasing. Also, the amount and frequency of dam release are to be increased in the future period. More seriously, this increase is expected to be concentrated on rather extreme cases with large dam release volume. Simply, the condition for flood protection in the downstream of the Namgang Dam is becoming worse and worse. Ironically, the severity of water shortage problem is also expected to become much worse. As the most extreme case, the frequency of no water supply was zero in the observed period, but in the future period, it becomes once every five years. Both the maximum consecutive shortage days and the total shortage volume are expected to become more than twice in the future period. To prevent or mitigate this coming problem of an under-sized dam, the only countermeasure at this moment seems to be its redevelopment. Simply a bigger dam with larger dam reservoir can handle this adverse effect more easily.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.361-372
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• 2016

Reliable long-term dam inflow prediction is necessary for efficient multi-purpose dam operation in changing climate. Since 2000s the teleconnection between global climate indices (e.g., ENSO) and local hydroclimate regimes have been widely recognized throughout the world. To date many hydrologists focus on predicting future hydrologic conditions using lag teleconnection between streamflow and climate indices. This study investigated the utility of teleconneciton for predicting dam inflow with 1-month lead time at Andong dam basin. To this end 40 global climate indices from NOAA were employed to identify potential predictors of dam inflow, areal averaged precipitation, temperature of Andong dam basin. This study compared three different approaches; 1) dam inflow prediction using SWAT model based on teleconneciton-based precipitation and temperature forecast (SWAT-Forecasted), 2) dam inflow prediction using teleconneciton between dam inflow and climate indices (CIR-Forecasted), and 3) dam inflow prediction based on the rank of current observation in the historical dam inflow (Rank-Observed). Our results demonstrated that CIR-Forecasted showed better predictability than the other approaches, except in December. This is because uncertainties attributed to temporal downscaling from monthly to daily for precipitation and temperature forecasts and hydrologic modeling using SWAT can be ignored from dam inflow forecast through CIR-Forecasted approach. This study indicates that 1-month lead dam inflow forecast based on teleconneciton could provide useful information on Andong dam operation.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.9-18
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• 2017

The objective of this study was to estimate the climate change impact on inflow to Namgang Dam using SWAT (Soil and Water Assessment Tool) model. The SWAT model was calibrated and validated using observed flow data from 2003 to 2014 for the study watershed. The $R^2$ (Determination Coefficient), RMSE (Root Mean Square Error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (Relative Mean Absolute Error) were used to evaluate the model performance. Calibration results showed that the annual mean inflow were within ${\pm}5%$ error compared to the observed. $R^2$ were ranged 0.61~0.87, RMSE were 1.37~7.00 mm/day, NSE were 0.47~0.83, and RMAE were 0.25~0.73 mm/day for daily runoff, respectively. Climate change scenarios were obtained from the HadGEM3-RA. The quantile mapping method was adopted to correct bias that is inherent in the climate change scenarios. Based on the climate change scenarios, calibrated SWAT model simulates the future inflow and evapotranspiration for the study watershed. The expected future inflow to Namgang dam using RCP 4.5 is increasing by 4.8 % and RCP 8.5 is increasing by 19.0 %, respectively. The expected future evapotranspiration for Namgang dam watershed using RCP 4.5 is decreasing by 6.7 % and RCP 8.5 is decreasing by 0.7 %, respectively.

• Water for future
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• v.18 no.4
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• pp.347-359
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• 1985

This study aims at the development of DP-Model for the establishment of monthly optimal operation policy of single multi-puppose reservoir by which the water demand of downstream can be satisfied under the various physical constraints. Series, A. B. C. of inflow are selected out of future monthly inflow data which are simulated form the past monthly average inflow of Andong dam site. the neight possible alternatives in each inflow series are established in order that Andong dam can supply the water demand of Nagdong main stream of 30% to 100%. Nextly, the reservoir rule curves is derived for each alternative by the detailed seguential analysis of stroage, future inflow and water demand based on the reservoir continuite equation. Then, and alternative which can satisfy the objective function of system based on the rule curves in the exteream is determined as an optimal operation policy from the application of developed DP=Model.

• Journal of Korea Water Resources Association
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• v.52 no.7
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• pp.451-461
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• 2019

The dam reservoir inflow prediction is utilized to ensure for water supply and prevent future droughts. In this study, we predicted the dam reservoir inflow and analyzed how seasonal weather forecasting affected the accuracy of the inflow for even multi-purpose dams. The hindcast and forecast of GloSea5 from KMA were used as input for rainfall-runoff models. TANK, ABCD, K-DRUM and PRMS models which have individual characteristics were applied to simulate inflow prediction. The dam reservoir inflow prediction was assessed for the periods of 1996~2009 and 2015~2016 for the hindcast and forecast respectively. The results of assessment showed that the inflow prediction was underestimated by comparing with the observed inflow. If rainfall-runoff models were calibrated appropriately, the characteristics of the models were not vital for accuracy of the inflow prediction. However the accuracy of seasonal weather forecasting, especially precipitation data is highly connected to the accuracy of the dam inflow prediction. It is recommended to consider underestimation of the inflow prediction when it is used for operations. Futhermore, for accuracy enhancement of the predicted dam inflow, it is more effective to focus on improving a seasonal weather forecasting rather than a rainfall-runoff model.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.107-116
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• 2019

Multi-purpose dams in Korea play a very important role in water management such as supplying water for living, industrial water, and discharging instream flow requirement to maintain the functions of river. However, the vulnerability of dam water supply has been increased due to extreme weather events that are possible linked to climate change. This study attempts to project the future dam inflow of six multi-purpose dams by using dynamically downscaled climate change scenarios with high resolution. It is found that the high flows are remarkably increased under global warming, regardless of basins and climate models. In contrast, the low flows for Soyangang dam, Chungju dam, and Andong dam that dam inflow are originated from Taebaek mountains are significantly decreased. On the other hand, while the low flow of Hapcheon dam is shown to increase, those of Daecheong and Sumjingang dams have little changes. But, the low flows for future period have wide ranges and the minimum value of low flows are decreased for all dams except for Hapcheon dam. Therefore, it is necessary to establish new water management policy that can respond to extreme water shortages considering climate change.

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

• Water for future
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• v.14 no.2
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• pp.22-25
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• 1981