• Title/Summary/Keyword: Water inflow

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Development of Open Water Management Program(OWMP) for Water Management Automation System with Open Architecture (물관리자동화시스템을 위한 개방형 운영 프로그램 개발)

  • 김선주;김필식;윤찬영;박재홍
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.43 no.5
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    • pp.83-92
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    • 2001
  • As a result of the recent water resources crisis, development of water management automation system becomes important. This system should be developed with open architecture in order to flexibly meet the spacial and time change of irrigation water demand. Thereby, water management automation system requires open architecture and suitable software program. This study presents an application of object-oriented methodology for Open Water Management Program(OWMP). Accordingly, OWMP provides a high degree of reliability which allows modification of parameters by change of region or time to be possible. OWMP consists of Data Base Management System(DBMS) and Model System. DBMS makes it possible to analyze data related with planning water schedule and establishing database. Model System calculates reservoir inflow, reservoir effluent and basin water demand. An operator decides the reservoir operation with results of Model System and DBMS. OWMP could be adapted to the planning and decision for saving water.

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Development of Han River Multi-Reservoir Operation Rules by Linear Tracking (선형추적에 의한 한강수계 복합 저수지 계통의 이수 조작기준 작성)

  • Yu, Ju-Hwan
    • Journal of Korea Water Resources Association
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    • v.33 no.6
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    • pp.733-744
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    • 2000
  • Due to the randomness of reservoir inflow and supply demand it is not easy to establish an optimal reservoir operation rule. However, the operation rule can be derived by the implicit stochastic optimization approach using synthetic inflow data with some demand satisfied. In this study the optimal reservoir operation which was reasonably formulated as Linear Tracking model for maximizing the hydro-energy of seven reservoirs system in the Han river was performed by use of the optimal control theory. Here the operation model made to satisfy the 2001st year demand in the capital area inputted the synthetic inflow data generated by multi-site Markov model. Based on the regressions and statistic analyses of the optimal operation results, monthly reservoir operation rules were developed with the seasonal probabilities of the reservoir stages. The comparatively larger dams which would have more controllability such as Hwacheon, Soyanggang, and Chungju had better regressions between the storages and outflows. The effectiveness of the rules was verified by the simulation during actually operating period.period.

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An Experimental Study for Reduction of Sedimentation Deposit in Combining Junction Manholes (합류맨홀에서의 유사퇴적 저감을 위한 실험적 연구)

  • Kim, Jung-Soo;Kim, Kyoung-Beom;Yoon, Sei-Eui
    • Journal of Korea Water Resources Association
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    • v.45 no.8
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    • pp.767-782
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    • 2012
  • Accumulation of sediment within pipelines, manholes, and other components of urban sewer systems can have a bad influence on sewerage arrangements, such as the resistance of the passage of flows, the cause of urban flooding and the premature operation of combined sewer overflows, and the inevitable pollution of watercourses. Therefore, it is necessary to understand the movements and sedimentation of sediment loads in combining junction manholes by experiments. In this study, hydraulic experimental apparatus which can change the manhole shapes (square, circle) were installed to measure deposited sedimentation quantity. The quantity of deposited sediment loads was measured by different conditions, for instance, the inflow conditions of sediment (continuous and certain period), the amount of inflow sediment, and the variation of inflow pipe of sediment. The combining junction manhole that was set up a inclined benching have the considerable effect of reduction of sedimentation in manholes without apropos of the change of manhole shapes. Therefore, the improved manhole could be increased the drainage capacity of sewerage arrangements in urban sewer systems.

Influence of Heavy Metal (Zn) Inflow on Species Composition and Morphological Abnormalities of Epilithic Diatom in the River (하천에서 중금속 아연(Zn) 유입이 부착규조의 종조성과 형태 변이에 미치는 영향)

  • Shin, Ra-Young;Ryu, Hui-Seong;Lee, Jung-Ho
    • Journal of Korean Society on Water Environment
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    • v.33 no.4
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    • pp.424-433
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    • 2017
  • The purpose of this study is to understand the changes on species composition of the epilithic diatoms and the appearance of morphological abnormalities in the upper region of the Nakdong River where heavy metal inflow is observed. The samples were collected once a week for a month of September 2016 from selecting 7 sampling stations. The heavy metals of cadmium (Cd) and arsenic (As) were not detected during the survey period, but zinc (Zn) was detected in st.4 - st.6 with the range of $0.015{\sim}0.188mg\;L^{-1}$. Metal sensitive species such as Achnanthes convergens, Cocconeis placentula, Cocconeis placentula var. euglypta, Cocconeis placentula var. lineata showed high dominance in st.1 - st.3, st.7. However, metal tolerant species such as Nitzschia palea, Achnanthes minutissima showed high dominance in st.4 - st.6. It is concluded that heavy metal inflow directly affects the changes in species composition of epilithic diatoms. As a result of CCA, the characteristics of the sampling sites were divided into 3 groups. Group 1 was represented the non-detected Zn sites with C. placentula, C. placentula var. euglypta, C. placentula var. lineata. Group 2 was showed the detected Zn sites with Navicula minima and Nitzschia palea. Group 3 was included st.3 - st.7 on 4th week that was stabilized the community structure. Total 8 taxa of abnormal frustules observed. This occurrence of abnormal frustules reflected the temporal and quantitative indicators of heavy metal pollution, in particular, it was confirmed that genus Fragilaria, which has a high abnormality according to heavy metal pollution, can be used as an indicator species.

Monthly Dam Inflow Forecasts by Using Weather Forecasting Information (기상예보정보를 활용한 월 댐유입량 예측)

  • Jeong, Dae-Myoung;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.37 no.6
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    • pp.449-460
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    • 2004
  • The purpose of this study is to test the applicability of neuro-fuzzy system for monthly dam inflow forecasts by using weather forecasting information. The neuro-fuzzy algorithm adopted in this study is the ANFIS(Adaptive neuro-fuzzy Inference System) in which neural network theory is combined with fuzzy theory. The ANFIS model can experience the difficulties in selection of a control rule by a space partition because the number of control value increases rapidly as the number of fuzzy variable increases. In an effort to overcome this drawback, this study used the subtractive clustering which is one of fuzzy clustering methods. Also, this study proposed a method for converting qualitative weather forecasting information to quantitative one. ANFIS for monthly dam inflow forecasts was tested in cases of with or without weather forecasting information. It can be seen that the model performances obtained from the use of past observed data and future weather forecasting information are much better than those from past observed data only.

Flood Inflow Forecasting on Multipurpose Reservoir by Neural Network (신경망리론에 의한 다목적 저수지의 홍수유입량 예측)

  • Sim, Sun-Bo;Kim, Man-Sik
    • Journal of Korea Water Resources Association
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    • v.31 no.1
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    • pp.45-57
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    • 1998
  • The purpose of this paper is to develop a neural network model in order to forecast flood inflow into the reservoir that has the nature of uncertainty and nonlinearity. The model has the features of multi-layered structure and parallel multi-connections. To develop the model. backpropagation learning algorithm was used with the Momentum and Levenberg-Marquardt techniques. The former technique uses gradient descent method and the later uses gradient descent and Gauss-Newton method respectively to solve the problems of local minima and for the speed of convergency. Used data for learning are continuous fixed real values of input as well as output to emulate the real physical aspects. after learning process. a reservoir inflows forecasting model at flood period was constructed. The data for learning were used to calibrate the developed model and the results were very satisfactory. applicability of the model to the Chungju Mlultipurpose Reservoir proved the availability of the developed model.

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Comparison of Characteristics of Outflow Hydrograph Using the Linear and Nonlinear Muskingum-Cunge Methods (선형과 비선형 Muskingum-Cunge법에 의한 유출곡선의 특성 비교)

  • Kim, Jin-Su;Kim, Jin-Hong
    • Journal of Korea Water Resources Association
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    • v.32 no.4
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    • pp.417-426
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    • 1999
  • A series of numerical experiments is performed to compare the characteristics of outflow hydrograph using linear and nonlinear Muskingum-Cunge methods for two cases: (a) sinusoidal inflow hydrographs and (b) rainfall inputs. The nonlinear method shows the steepening of the rising limb, coupled with a corresponding flattening of the receding limb. The linear method conserves mass exactly. In contrast, the nonlinear method is subject to a gain and a loss of mass. The loss of mass and the subsidence of peak outflow increases with a mild slope, a small baseflow $q_b$ and a large peak inflow to baseflow ratio $q_p/q_b$. A shock wave and associated numerical instability results in the increase of mass for a steep slope and a large $q_p/q_b$ ratio. While the linear method depends on the reference flow per unit-width, the nonlinear method depends on a baseflow and the $q_p/q_b$ ratio. It is found that, unlike for the sinusoidal inflow, the outflow for the rainfall inputs conserves mass fairly exactly in the nonlinear method.

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Analysis of Flood Control Capacity of Agricultural Reservoir Based on SSP Climate Change Scenario (SSP 기후변화 시나리오에 따른 농업용 저수지 홍수조절능력 분석)

  • Kim, Jihye;Kwak, Jihye;Hwang, Soonho;Jun, Sang Min;Lee, Sunghack;Lee, Jae Nam;Kang, Moon Seong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.63 no.5
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    • pp.49-62
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    • 2021
  • The objective of this study was to evaluate the flood control capacity of the agricultural reservoir based on state-of-the-art climate change scenario - SSP (Shared Socioeconomic Pathways). 18 agricultural reservoirs were selected as the study sites, and future rainfall data based on SSP scenario provided by CMIP6 (Coupled Model Intercomparison Project 6) was applied to analyze the impact of climate change. The frequency analysis module, the rainfall-runoff module, the reservoir operation module, and their linkage system were built and applied to simulate probable rainfall, maximum inflow, maximum outflow, and maximum water level of the reservoirs. And the maximum values were compared with the design values, such as design flood of reservoirs, design flood of direct downstream, and top of dam elevation, respectively. According to whether or not the maximum values exceed each design value, cases were divided into eight categories; I-O-H, I-O, I-H, I, O-H, O, H, X. Probable rainfall (200-yr frequency, 12-h duration) for observed data (1973~2020) was a maximum of 445.2 mm and increased to 619.1~1,359.7 mm in the future (2011~2100). For the present, 61.1% of the reservoirs corresponded to I-O, which means the reservoirs have sufficient capacity to discharge large inflow; however, there is a risk of overflowing downstream due to excessive outflow. For the future, six reservoirs (Idong, Baekgok, Yedang, Tapjung, Naju, Jangsung) were changed from I-O to I-O-H, which means inflow increases beyond the discharge capacity due to climate change, and there is a risk of collapse due to dam overflow.

Dam Inflow Prediction and Evaluation Using Hybrid Auto-sklearn Ensemble Model (하이브리드 Auto-sklearn 앙상블 모델을 이용한 댐 유입량 예측 및 평가)

  • Lee, Seoro;Bae, Joo Hyun;Lee, Gwanjae;Yang, Dongseok;Hong, Jiyeong;Kim, Jonggun;Lim, Kyoung Jae
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.307-307
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    • 2022
  • 최근 기후변화와 댐 상류 토지이용 변화 등과 같은 다양한 원인에 의해 댐 유입량의 변동성이 증가하면서 댐 관리 및 운영조작 의사 결정에 어려움이 발생하고 있다. 따라서 이러한 댐 유입량의 변동 특성을 반영하여 댐 유입량을 정확하고 효율적으로 예측할 수 있는 방안이 필요한 실정이다. 머신러닝 기술이 발전하면서 Auto-ML(Automated Machine Learning)이 다양한 분야에서 활용되고 있다. Auto-ML은 데이터 전처리, 최적 알고리즘 선택, 하이퍼파라미터 튜닝, 모델 학습 및 평가 등의 모든 과정을 자동화하는 기술이다. 그러나 아직까지 수문 분야에서 댐 유입량을 예측하기 위한 모델을 개발하는데 있어서 Auto-ML을 활용한 사례는 부족하고, 특히 댐 유입량의 예측 정확성을 확보하기 위해 High-inflow and low-inflow 의 변동 특성을 고려한 하이브리드 결합 방식을 통해 Auto-ML 기반 앙상블 모델을 개발하고 평가한 연구는 없다. 본 연구에서는 Auto-ML의 패키지 중 Auto-sklearn을 통해 홍수기, 비홍수기 유입량 변동 특성을 반영한 하이브리드 앙상블 댐 유입량 예측 모델을 개발하였다. 소양강댐을 대상으로 적용한 결과, 하이브리드 Auto-sklearn 앙상블 모델의 댐 유입량 예측 성능은 R2 0.868, RMSE 66.23 m3/s, MAE 16.45 m3/s로 단일 Auto-sklearn을 통해 구축 된 앙상블 모델보다 전반적으로 우수한 것으로 나타났다. 특히 FDC (Flow Duration Curve)의 저수기, 갈수기 구간에서 두 모델의 유입량 예측 경향은 큰 차이를 보였으며, 하이브리드 Auto-sklearn 모델의 예측 값이 관측 값과 더욱 유사한 것으로 나타났다. 이는 홍수기, 비홍수기 구간에 대한 앙상블 모델이 독립적으로 구축되는 과정에서 각 모델에 대한 하이퍼파라미터가 최적화되었기 때문이라 판단된다. 향후 본 연구의 방법론은 보다 정확한 댐 유입량 예측 자료를 생성하기 위한 방안 수립뿐만 아니라 다양한 분야의 불균형한 데이터셋을 이용한 앙상블 모델을 구축하는데도 유용하게 활용될 수 있을 것으로 사료된다.

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