Real-time flood control operations of a cascade reservoir system under emergency conditions can reduce the social and economic loss caused by natural disasters. This paper proposes a risk-based model for real-time flood control operation of reservoirs under emergency conditions and uncertainties. The proposed model consists of three modules: emergency scenarios establishing, Monte Carlo simulations, and risk analysis. The emergency scenarios considered are earthquakes, extreme floods and failure of the spillways of a reservoir. The uncertainty factor considered is the forecast error of reservoir inflows, arising from model structural uncertainty and parameter estimating. The Monte Carlo simulations conduct the real-time flood control operation of reservoirs considering the proposed emergency events and uncertainties. The module of risk analysis performs the assessment of the operation schedules and calculates the risk of dam overtopping, based on the results from Monte Carlo simulations. The proposed model is applied to a cascade reservoir system in the upper reaches of Daduhe river basin in China. The results show that the maximum initial water level of the Shuangjiangkou reservoir is 2447 m a.s.l. (meters above sea level) using the release capacity model and is 2444.5 m a.s.l. using the command model under the scenario of upstream dam break. The integrated risk of the reservoir increases with the initial water level and the uncertainty degree of the reservoir inflows. The decision-makers can choose the operation models according to the actual initial water level of the reservoir under different emergency scenarios.

Identifying changes in runoff and quantifying the impacts of climate change and human activities are of great significance for water resources planning and management in a river basin. In this study, an inflow series of the Three Gorges Reservoir observed from 1951 to 2016 is used to identify the trend and abrupt change point by using statistical methods. Based on the meteorological data, soil type data, and land use data during the same period, the Soil and Water Assessment Tool (SWAT) model is established to quantitatively attribute changes in the Three Gorges Reservoir inflow to climate change and human activities separately and discuss the differences between the two-stage method, which divides the whole study period into two stages to analyze the reasons for runoff evolution, and multi-stage method, which divides the whole study period into more stages to consider the temporal and spatial variation of land use/cover (LULC). The results show: (1) During the study period, a significant decrease is detected in the Three Gorges Reservoir inflow and the decrease rate is 7.7 km³ per ten years, annual total precipitation decreases by −13.5 mm per ten years, and annual average temperature increases by 0.1 °C per ten years. (2) Contribution of climate change and human activities is around 7:3. Climate change is the main reason for the decrease in the Three Gorges Reservoir inflow. (3) Results of stages in multi-stage method are different from the result of two-stage method. Accumulative results of multi-stage method and result of two-stage method are consistent. There are some changes in results of every stage, which are different from the accumulative results.

The uncertainty of forecasted runoffs brings risks of water shortages to water users in the intake area of long-distance water transfer projects, and the uncertainty of spot market prices may cause them to buy water at high prices. In order to hedge these risks, this paper proposes a risk hedging model for decision-making in water option trading from the viewpoint of water users. With the objective of maximizing the expected revenue of water users, the proposed model was solved by an analytical method and an optimal water option strategy was obtained for the users. The proposed model is applied to an intake area of an inter-basin water transfer project in China. The results show that the proposed water option trading model can provide water users with an optimal option strategy. The optimal options trading strategy can effectively reduce the risk caused by the uncertainties of forecasted runoffs and water prices. We also explored the influence of the uncertainty degree of the forecasted runoffs and water price on the option trading strategy. The results show that the expected revenue of water users increases as the variances of the errors of forecasted runoffs and water prices increase.