Real‐time reservoir flood operation during typhoon attacks

Wei-liang, Huang; Hsieh, Chi-Liang

doi:10.1029/2009wr008422

Cited by 25 publications

(12 citation statements)

References 23 publications

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“…For rolling horizon reservoir operation, this monotonic relationship generally suggests that the current release decision

r_{1}^{'}

will not increase if we set a higher

s_{T}^{'}

(i.e., to save more water for periods beyond FH). It is important to note that the monotonicity dependence relationship has been studied in supply chain management [e.g., Veinott , 1964; Huang and Ahmed , 2010]; this paper introduces the relationship to reservoir operation and extends it by considering the effects of utility discount and storage loss ().…”

Section: Evaluation Metrics Of Limited Inflow Forecast For Reservoir mentioning

confidence: 99%

“…[2] As advances in weather forecasting, hydrologic modeling, and hydro-climatic teleconnections have significantly reduced streamflow forecast uncertainty and prolonged the forecast horizon, streamflow forecasts are now a more promising tool for improving reservoir operation efficiency [Carpenter and Georgakakos, 2001;Faber and Stedinger, 2001;McCollor and Stull, 2008;Sankarasubramanian et al, 2009a]. In recent years, various optimization and simulation models have been developed to exploit streamflow forecasts for reservoir decision making [e.g., Yao and Georgakakos, 2001;Ajami et al, 2008;Huang and Hsieh, 2010;Valeriano et al, 2010]. However, Applications of streamflow forecasts to reservoir operation are constrained by their limited length.…”

Section: Introductionmentioning

confidence: 99%

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Identifying effective forecast horizon for real‐time reservoir operation under a limited inflow forecast

Zhao¹,

Yang²,

Cai³

et al. 2012

Water Resources Research

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[1] The use of a streamflow forecast for real-time reservoir operation is constrained by forecast uncertainty (FU) and limited forecast horizon (FH). The effects of the two factors are complicating since increasing the FH usually provides more information for decision making in a longer time framework but with increasing uncertainty, which offsets the information gain from a longer FH. This paper illustrates the existence of an effective FH (EFH) with a given forecast, which balances the effects of the FH and FU and provides the maximum information for reservoir operation decision making. With the assumption of a concave objective function, a monotonic relationship between current operation decision and ending storage is derived. Metrics representing the error resulting from a limited forecast relative to a perfect forecast are defined to evaluate reservoir performance. Procedures to analyze the complicating effect of FU and FH and to identify EFH are proposed. Results show that: (1) when FH is short, FH is the dominating factor for determining reservoir operation, and reservoir performance exhibits a quick improvement as FH increases; (2) when FH is long, the inflow information may be too uncertain to guide reservoir operation decisions and FU becomes the dominating factor; and (3) at a medium FH, reservoir performance depends on the complicating effects of FU and FH and EFH locates with a certain balanced level of FU and FH. The statistical characteristics of EFH are illustrated with case studies with deterministic forecast and ensemble forecast. Moreover, the impacts of temporal correlation of FU, inflow variability, evaporation loss, and reservoir capacity on EFH are explored.

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“…For rolling horizon reservoir operation, this monotonic relationship generally suggests that the current release decision

r_{1}^{'}

will not increase if we set a higher

s_{T}^{'}

Section: Evaluation Metrics Of Limited Inflow Forecast For Reservoir mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identifying effective forecast horizon for real‐time reservoir operation under a limited inflow forecast

Zhao¹,

Yang²,

Cai³

et al. 2012

Water Resources Research

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“…Floods greatly influence people's lives in China and are blamed for inflicting severe disasters, such as economic losses, social disruption, environmental/ecological destruction, or even human fatalities (Klein et al 2010;Huang and Hsieh 2010). Approximately 66.7 % of the Chinese territory is impacted by floods.…”

Section: Introductionmentioning

confidence: 99%

Risk analysis for the downstream control section in the real-time flood control operation of a reservoir

Chen

Zhong

Zhao

et al. 2015

Stoch Environ Res Risk Assess

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Many uncertainty factors are associated with the joint operation of a reservoir and its downstream river, which create risks in flood control decisions. Therefore, this paper proposes an analytical method for the estimation of the uncertainties and their risks in real-time flood control decisions. Three uncertainty factors, including reservoir discharge errors, forecasting errors of lateral inflows and river food routing errors are proposed and modeled as stochastic processes, and their internal transforming formulas are derived based on the theory of routing before combination. The definition and calculation formulas for the risks of each moment and the integrated risk of the entire flood process at the downstream flood control section are proposed by an analytical approach based on the combination theory of stochastic processes. The Dahuofang reservoir in northern China is selected as the study case. The results indicate that the risk of the flood peak is higher than that of other moments under the same controlled flood discharge and that the risk that arises from the uncertainties of the reservoir discharge and lateral inflow is decreased by the river storage function. Compared with the Monte Carlo method, the proposed method is effective and efficient for performing risk analysis of the downstream control section in the real-time flood control operation of a reservoir. The risk analysis results could provide important information regarding flood risks for the operators to implement flood control arrangements.

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“…Due to the intrinsic complexity, risks encountered in reservoir flood control based on forecasted information are not well understood (Huang and Hsieh 2010). The uncertainty and risk evaluation for forecastbased operation is different from its traditional operation counterpart because of new risk factors and forecast errors, which play a significant role in the flood routing process.…”

mentioning

confidence: 99%

Streamflow Forecast Errors and Their Impacts on Forecast-based Reservoir Flood Control

Liu

Guo

Wang

et al. 2015

Water Resour Manage

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To make full use of water captured by reservoirs in flood seasons, methods such as forecast-based reservoir flood control (i.e., reservoir operation during flood periods based on precipitation or inflow forecasts) have been developed in China in the past few decades. The success of forecast-based reservoir flood control depends heavily on the precision of the precipitation or inflow forecasts. This study analyzes the sources of uncertainty and quantifies it in the process of reservoir flood control based on forecasts. First, flood inflow series is regarded as a random process with the forecasted flood inflows as its expectation process; the flood inflow error series, which is the difference between the observed inflow process and the forecasted inflow process, is obtained according to the statistical characteristics of the flood forecasts. Second, reservoir flood routing simulations are carried out using the Monte Carlo method with the flood inflow error series as an input to obtain output water level and discharge series. Finally, the frequency distributions of the maximum water level (MWL) reached during the passage of floods are used to evaluate the uncertainties and the corresponding risks associated with forecast-based flood control. These uncertainties and risks are what the operators of the reservoirs care about the most.

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Real‐time reservoir flood operation during typhoon attacks

Cited by 25 publications

References 23 publications

Identifying effective forecast horizon for real‐time reservoir operation under a limited inflow forecast

Identifying effective forecast horizon for real‐time reservoir operation under a limited inflow forecast

Risk analysis for the downstream control section in the real-time flood control operation of a reservoir

Streamflow Forecast Errors and Their Impacts on Forecast-based Reservoir Flood Control

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