Dynamic control of flood limited water level for reservoir operation by considering inflow uncertainty

According to the Chinese Flood Control Act, reservoir water levels generally are not allowed to exceed the flood limited water level (FLWL) during flood season in order to offer adequate storage for flood prevention. However, the operation rules based on the current FLWL have neglected meteorological and real-time flood forecasting information and give too much priority to low probability floods. For floodwater utilization, dynamic control of reservoir FLWL is a valuable and effective methodology to compromise between flood control and conservation for reservoir operation during the flood season. The dynamic control bound is a fundamental key element for implementing reservoir FLWL dynamic control operation. In this paper, a dynamic control operation model that considers inflow uncertainty, i.e. the inflow forecasting error and uncertainty of the flood hydrograph shape is proposed and developed. The model consists of three modules: the first one is a pre-release module, which is used to estimate the upper boundary of dynamic control bound on basis of inflow forecasting results; the second one is a refill operation module, which is used to retain recession flood, and the third one is a risk analysis module, which is used to assess flood risk. The acceptable flood control operation risk constraints and quantificational analysis methods are given, and the dynamic control bound of reservoir FLWL is estimated by using Monte Carlo simulation. The China's three gorges reservoir (TGR) is selected as a case study. A multiple-input single-output linear systematic model is chosen for inflow forecasting of the TGR, and the future inflows are derived from gauged records by assuming that the inflow forecasting error follows a normal distribution. The application results show that the dynamic control of reservoir FLWL can effectively increase hydropower generation and the floodwater utilization rate without increasing flood control risk. (c) 2010 Elsevier B.V. All rights reserved.