Flood Forecasting in Regulated Basins Using the Ensemble Extended Kalman Filter with the Storage Function Method

Abstract

An ensemble extended Kalman filter (EEKF) formulation is applied to a regulated basin. The existing event-based storage function method for the prediction of flow is enhanced to incorporate continuous soil water accounting and to be suitable for application in large watersheds with several tributaries. The formulation is complemented by EEKF, which utilizes flow and reservoir level observations to update catchment soil water and channel states, and reservoir storage estimates predicted by the model. The formulated forecast is suitable for operational application. Ensemble precipitation predictions are generated to serve as input to the forecast system, and the results are intercompared using two different statistical approaches. These predictions together with parametric uncertainty models constitute the basis of the ensemble flow predictions by the model. A case study is presented that demonstrates the implementation and evaluation of the method with respect to the prediction of large flow events in a