Estimation of nonfluctuating reservoir inflow from water level observations using methods based on flow continuity

The accurate estimation of "true" reservoir inflow is important for hydrological forecasting and efficient operation of reservoirs. However, reservoir inflow estimated using the conventional simple water balance method is not always accurate because the estimation is very sensitive to errors in reservoir water level observations and uncertainty in the stage-storage relationship. An analytical method (AM) and a method using the ensemble Kalman filter (EnKF) are proposed to determine nonfluctuating reservoir inflow based on the concept of inflow continuity; that is, that inflow should not change much within a short time period. The AM is developed based on the simultaneous minimization of both the estimated reservoir water level error and the inflow variation. The EnKF, which is built on state equations (inflow continuity and water balance equations) and an observation equation (the reservoir stage-storage relationship), is used to update inflow states by assimilating water level observations. The two proposed methods are evaluated using a synthetic experiment with various conditions including water level observation error, reservoir stage-storage relationship error, and the influence of water surface slope. The AM outperforms the EnKF under all conditions. Case studies of the Gaobazhou and Danjiangkou Reservoirs in China demonstrate that both of the proposed methods can derive an hourly inflow without fluctuations. The results indicate that the AM and the EnKF method can improve reservoir inflow estimation compared with conventional methods. (C) 2015 Elsevier B.V. All rights reserved.