• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.59-72
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• 2024

Agricultural reservoirs supply water for various purposes such as irrigation, maintenance, and living. Since agricultural reservoirs respond sensitively to seasonal and climate changes, it is essential to estimate supply and inflow for efficient operation, and water management should be done based on these data. However, in the case of agricultural reservoirs, the measurement of supply and inflow is relatively insufficient compared to multi-purpose dams, and inflow-supply analysis in agricultural reservoirs through water balance analysis is necessary for efficient water management. Therefore, rainfall-runoff analysis models such as ONE model and Tank model have been developed and used for reservoir water balance analysis, but the applicability analysis for ungauged watersheds is insufficient. The ONE model is designed for daily runoff calculation, and the model has one parameter, which is advantageous for calibration and ungauged watershed analysis. In this study, the water balance was analyzed through the ONE model and the Tank model for 15 watersheds upstream of dams, and R² and NSE were used to quantitatively compare the performance of the two models. The simulation results show that the ONE model is suitable for predicting the inflow of agricultural reservoirs with the ungauged watershed

• Korean Journal of Environmental Agriculture
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• v.30 no.3
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• pp.268-274
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• 2011

BACKGROUND: A large scale of sediment load delivered from watershed causes substantial waterway damages and water quality degradation. Controlling sediment loading requires the knowledge of the soil erosion and sedimentation. The various factors such as watershed size, slope, climate, land use may affect sediment delivery processes. Traditionally sediment delivery ratio prediction equations have been developed by relating watershed characteristics to measured sediment yield divided by predicted gross erosion. However, sediment prediction equations have been developed for only a few regions because of limited sediment data. Besides, little research has been done on the prediction of sediment delivery ratio for asia monsoon period in mountainous watershed. METHODS AND RESULTS: In this study Tank model was expanded and applied for estimating sediment yield to Oship River of east coast. The rainfall-runoff in 2006 was verified using the Tank model and we derived good result between observed and calculated discharge in 2009 at the same conditions. In relation to sediment yield, the sediment delivery rate of 2006 was very high than 2009 regardless of methods for estimating sediment load. It was thought to be affected by heavy rainfall due to the typhoon. CONCLUSION(s): For estimating sediment volume from watershed, long-term monitoring data on discharge and sediment is needed. This model will be able to apply to predict discharge and sediment yield simultaneously in ungauged area. This approach is more effective and less expensive method than the traditional method which needs a lot of data collection.

• Journal of Wetlands Research
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• v.11 no.2
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• pp.107-121
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• 2009

Many rainfall-runoff models have been used for the flood forecasting. However, the determination of rainfall-runoff model parameters is very difficult. In this study, we investigated the efficiency of flood forecasting models by studying the optimization techniques for parameter calibration of SFM, Tank, and SSARR models. We analyzed the correlations between parameters in optimization techniques, then classified the parameters into parameter groups. For this we applied the sequential calibration method through the sensitivity analysis. As the results of the analysis, the parameter groups clibration method showed better result for peak flow and clibtation time.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.36-36
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• 2022

2010년대 후반에 딥 러닝 관련 기술이 발전하고 복잡한 강우-유출 현상을 모의하는데 적합하다는 점이 알려지면서 많은 수문관련 연구에서 딥러닝 기법을 통하여 수문모델링을 대체 가능함을 제시하여 왔다. 그러나, 이러한 가능성은 단순 모의효율을 통한 분석이므로 실제 수문관리 현장에 대한 적용을 위한 고찰이 필요한 시점이다. 이에 본 연구에서는 딥러닝 기법을 통하여 수문모의의 가능성을 고찰하고 개선점을 고찰하고자 한다. 이를 위하여 수문자료에 많이 적용되는 LSTM 기법과 수문모형인 TANK모형을 이용하여 경상남도의 형산강 유역을 대상으로 2013년부터 2020년까지의 유출량을 모의하고 그 결과를 비교 분석하였다. 형산강 유역에 대한 수문모의를 수행한 결과, LSTM 기법을 이용한 수문모의가 TANK모형에 비하여 높은 모의효율을 보여주었다. 그러나, 높은 모의효율에도 불구하고 유역의 물리적인 강우-유출과정을 모사하는 수문모형과 달리 LSTM 기법은 인간이 이해할 수 없는 과정을 통하여 학습하고 구조화되므로 기존과 다른 경향의 입력자료로 인한 예측오류가 발생할 가능성과 그에 따른 인간의 판단불가에 따른 문제를 내포하고 있음을 고찰하였다. 따라서, 딥러닝을 이용하여 수문모델링 분야에 수문모형을 전면적으로 대체하기에는 어려움이 있을 것이다. 본 연구에서는 현재까지의 딥러닝을 이용하여 수문모형을 대체하기 위해서는 ① 국민의 생활에 직접적으로 영향을 미치는 분야가 아닌 단순 연구목적이나 위험성 분석 등에 적용하거나, ② 딥러닝의 모의결과에 대해 사용자가 검토하거나 판단할 수 있는 의사결정 체계를 구축하거나, ③ 도출된 결과에 대한 윤리적 검토나 책임소재에 대한 사회적 합의 등이 선결되어야 할 것이다.

• Spatial Information Research
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• v.4 no.2
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• pp.147-157
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• 1996

A rural water quality management information system(RWQMIS) by integrating Geo¬graphic Information System(GIS) with the existing models (pollutants transport and river water quality) is described. A simple pollutant load model to calculate delivered pollutants to stream, Tank model to generate daily runoff and QUAL2E model to predict river water quality, were incorporated into GIS. The system was applied to $80km^2$ watershed in Icheon Gun and Yongin Gun, Kyonggi Do. The spatial distributions of produced pollutant load, discharged pollutant load, delivered ratio to the stream, and the river water quality status for given sites were successfully generated.

• Proceedings of the Korean Geotechical Society Conference
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• 1995.10a
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• pp.15.1-20
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• 1995

일반적으로 일반 및 유해폐기물 매립지에서 진흙층의 기능적 수행목적은 다음과 같다고 할 수 있다. 지표면 유출의 증진을 위하고, 우수의 침투억제 및 폐기물의 표면 노출 시 완충작용, 따라서 최종복토의 붕괴는 이러한 중요 기능을 마비시키고 있다. 본 연구는 추운 날씨상태의 폐기물 매립지 최종복토의 거동을 수행하였으며, 실제로 설계된 세 개의 거대한 실험실 Tank에서 복토에 대한 실험이 시행되었다. 이 거대한 실험장비의 제원은 0.75m x 2.4m와 2.0m 깊이로 되어 있다. Tank안은 시방서적으로 폐기물 매립지가 요구하는 진흙층과 최종복토를 위한 물질로 채워졌다. 그들의 실험결과는 동질/융해에 따른 진흙과 복토층의 붕괴현상은 물리적, 공학적인 측면에 영향을 주는 것으로 나타났다. 본문은 실험에 사용된 복토층의 묘사, 그들의 실험결과들과 실험을 통한 결과분석 및 결론을 설명하고 있다. 실험결과로서는 각 모형들의 우수와 침출수 자료, 온도변화의 배경과 최종복토에서의 Water Balance를 포함하고 있다. 또한 결과로서 시험된 세 개의 모형들은 매립지에서의 동결깊이(29cm~32cm)를 나타내주며 그들 중 하나의 모형은 배수층을 가지고 있어 침출수억제에 효과적이므로 다른 모형보다 복토층으로서 우위에 있다는 것을 지적하고 있다.

• Journal of Korea Water Resources Association
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• v.36 no.3 s.134
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• pp.423-436
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• 2003

The objective of this study is to propose an automatic parameter estimation scheme considering runoff components of Tank model. It estimates model parameters by Powell's automatic algorithm based on the runoff component separation of the observed hydrograph by using digital filter method. The selected study areas are the 4 main dam sites on the Han River. The simulated flows are compared with the observed flows depending on whether runoff component consideration or not. As a result, the estimated model parameters from classical Powell's method only can relatively well simulate the time variation of total runoff, but gives poor runoff component simulations. Therefore, it can be concluded that the proposed automatic parameter estimation scheme in this study Is more reliable and objective.

• Journal of Korea Water Resources Association
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• v.40 no.9
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• pp.687-696
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• 2007

Preference ordering approach is applied to optimize the parameters of Tank model using multi-objective genetic algorithm (MOGA). As more than three multi-objective functions are used in MOGA, too many non-dominated optimal solutions would be obtained thus the stakeholder hardly find the best optimal solution. In order to overcome this shortcomings of MOGA, preference ordering method is employed. The number of multi-objective functions in this study is 4 and a single Pareto-optimal solution, which is 2nd order efficiency and 3 degrees preference ordering, is chosen as the most preferred optimal solution. The comparison results among those from Powell method and SGA (simple genetic algorithm), which are single-objective function optimization, and NSGA-II, multi-objective optimization, show that the result from NSGA-II could be reasonalby accepted since the performance of NSGA-II is not deteriorated even though it is applied to the verification period which is totally different from the calibration period for parameter estimation.

• Water for future
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• v.17 no.1
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• pp.45-56
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• 1984

The whole process from the model design to the results of the test, of hydraulic model test of restricted entry surge tank of Hapcheon dam, is reviewed with the respect to the flowchart of the experiment. And the experimental results are compared with the numerical values which are calculated by Runge-Kutta-Gill scheme. The comparision show a reasonable agreement. In final design, it doesn't matter that only numerical values are considered in case of the short design period, or difficulties of budget, and or the comparably simple type surge tank as Hapcheon dam.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.412-418
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• 2000

The purpose of this study is estimation of daily runoff in the watershed with insufficient hydrological data using tank model. In order to estimate, twentysix watersheds were selected to calibrate tank model parameters that were defined by a trial and error method. Results were correlated with characteristics of watershed. Relationships between the parameters and the watershed characteristics were derived by a multiple regression analysis. The simulation results were in agreement with the observed data.