• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.308-308
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• 2011

하천에서 유량을 산정하기 위해서 전자파표면유속계를 이용하여 표면유속을 측정하고 수심평균유속환산계수 0.85를 일률적으로 적용하여 수심평균유속을 산정하고 있다. 이 수심평균유속환산계수 0.85의 적절성에 대한 논의가 지속되어져 왔으나 그 동안에는 이에 대한 현장검증을 할 수 있는 방법이 없었던 실정이다. 하지만 최근 들어서는 ADCP(Acoustic Doppler Current Profiler)의 하천용 Application인 StreamPro ADCP가 개발되어 이를 이용하면 홍수기에 수심별 유속을 측정할 수 있다. 다만 홍수기에 StreamPro ADCP의 적용시에는 여러 가지 높은 위험성이 상존하는 것은 인지의 사실이지만, 그 외의 별다른 방법이 없는 실정이다. 따라서 홍수기에 StreamPro ADCP를 이용하여 수심별 유속을 측정하고 이와 동시에 측정한 표면유속을 이용하여 수심평균유속환산계수를 산정하여 기존에 환산계수로 적용하고 있는 0.85의 적절성을 파악하고자 하였다. 흐름조건별 수심평균유속환산계수 산정을 위하여 평수기 용담 수자원시험유역의 동향지점에서 수심평균유속환산계수를 산정한 결과 0.632~1.352로 넓게 분포하고 있음을 파악하였다. 이렇게 계수가 실제 적용하는 0.85와는 크게 차이가 나는 이유로는 수심이 얕아서 바닥마찰의 영향이 크기 때문인 것으로 판단되었다. 이에 본 연구에서는 여러 지점에서 홍수기 수심별 유속의 실측을 통하여 수심평균유속환산계수 분포정도를 산정하고자 하였다. 대청댐 상류의 수통수위표가 위치해 있는 적벽대교지점에서 StreamPro ADCP를 이용하여 수심평균유속환산계수를 산정한 결과 0.735~0.986 사이에 분포하고 있다. 측정한 결과의 수심평균유속환산계수의 평균값은 0.853으로 기존에 수심평균유속의 산정을 위하여 적용하고 있는 0.85와 거의 일치함을 보이고 있다. 측정당시 수심이 3.6 m에 이르고 있고 유속 또한 1.55 m/s에 이르고 있어 홍수시 일반하천에서 발생하는 수위와 유속임을 감안할 때, 0.735~0.986의 수심평균유속환산계수는 홍수시 순간적인 변화의 폭이 큼을 알 수 있다. 이렇게 순간적인 변화가 큰 이유로는 난류의 성분이 강해서 나타나는 것으로 이를 평균하면 0.853으로 나타나고 있어 홍수시에 수심평균유속환산계수를 0.85를 사용하여도 무방함을 알 수 있다. 동향지점에서 홍수기에 수심별 유속의 실측을 통하여 수심평균유속환산계수를 산정하고자 하였다. 그러나 이 지점은 강한 와류로 인하여 ADCP가 심하게 흔들림으로 인하여 순간적인 유속의 차이가 최대 4배까지 보임을 알 수 있다. 이로 인하여 수심평균유속환산계수의 범위는 0.233~0.983에 이른다. 측정당시 표면유속이 2.07 m/s 인 것을 감안하여 이 표면유속에 상응하는 수심별 유속 자료만을 이용하여 산정시, 수심평균유속환산계수는 0.876이다. 하천의 하류지점에서 수심별 유속을 측정하여 수심평균유속환산계수를 산정하고자 한강하류로 유입하는 굴포천의 구교 및 박촌1교 지점에서 유속측정을 실시하였다. 이들 두 지점은 홍수기에 조차도 유속이 1 m/s 에 이르지 못하는 지점으로, 수심평균유속환산계수를 산정한 결과 각각 0.826, 0.833을 나타내고 있어, 수심평균유속환산계수 0.85가 홍수기뿐만 아니라 평 갈수기에도 적용할 수 있는 가능성을 확인하였다.

• Journal of Korean Society of Disaster and Security
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• v.15 no.1
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• pp.1-12
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• 2022

An automatic optimization technique is used to estimate the optimal parameters of the hydrologic model, and different hydrologic response results can be provided depending on objective functions. In this study, the parameters of the event-based rainfall-runoff model were estimated using various objective functions, the reproducibility of the hydrograph according to the objective functions was evaluated, and appropriate objective functions were proposed. As the rainfall-runoff model, the storage function model(SFM), which is a lumped hydrologic model used for runoff simulation in the current Korean flood forecasting system, was selected. In order to evaluate the reproducibility of the hydrograph for each objective function, 9 rainfall events were selected for the Cheoncheon basin, which is the upstream basin of Yongdam Dam, and widely-used 7 objective functions were selected for parameter estimation of the SFM for each rainfall event. Then, the reproducibility of the simulated hydrograph using the optimal parameter sets based on the different objective functions was analyzed. As a result, RMSE, NSE, and RSR, which include the error square term in the objective function, showed the highest accuracy for all rainfall events except for Event 7. In addition, in the case of PBIAS and VE, which include an error term compared to the observed flow, it also showed relatively stable reproducibility of the hydrograph. However, in the case of MIA, which adjusts parameters sensitive to high flow and low flow simultaneously, the hydrograph reproducibility performance was found to be very low.

• Journal of Life Science
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• v.17 no.5 s.85
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• pp.634-640
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• 2007

Our previous study suggested that n-3 fatty acid deficiency was associated with significantly reduced spatial learning as assessed by Morris water maze test. Here we investigated an effect of n-3 fatty acid deficiency on rat brain, retina and serum fatty acyl compositions at 15 wks age using a first generational artificial rearing technique. Newborn Rat pups were separated on day 2 and assigned to two artificial rearing groups or a dam-reared control group. Pups were hand fed artificial milk via custom-designed nursing bottles containing either 0.02%(n-3 Deficient) or 3.1% (n-3 Adequate) of total fatty acids as a-linolenic acid(LNA). At day 21, rats were weaned to either n-3 deficient or n-3 adequate pelleted diets and fatty acid compositions of brain, retina and liver were analyzed at 15 wks age. Brain docosahexaenoic acid(DHA) was lower(58% and 61%, P<0.05) in n-3 deficient in comparison to n-3 adequate and dam-reared groups, receptively, while brain docosapentaenoic acid(DPAn-6) was increased in the n-3 deficient group. In retina and serum fatty acid compositions, the decreased precentage of DHA and increased precentage of DPAn-6 were observed. These results suggested that artificial rearing method can be used to produce n-3 fatty acid deficiency in the first generation and that adequate brain DHA levels are required for optimal brain function.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.761-774
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• 2022

Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.