A real-time operation optimization model for flood management in river-reservoir systems

In this paper, a new methodology has been developed for real-time flood management in river-reservoir systems. This methodology is based upon combining a Genetic Algorithm (GA) reservoir operation optimization model for a cascade of two reservoirs, a hydraulic-based flood routing simulation model in downstream river system, a Geographical Information System (GIS) based database, and application of K-Nearest Neighbor (K-NN) algorithm for development of optimal operating rules. The GA optimization model estimates the optimal hourly reservoirs' releases to minimize the flood damages in the downstream river. GIS tools have also been used for specifying different land-uses and damage functions in the downstream floodplain and it has been linked to the unsteady module of HEC-RAS flood routing model using Hec-GeoRAS module. An innovative approach has also been developed using K-NN algorithm to formulate the optimal operating rules for a system of two cascade reservoirs based on optimal releases obtained from the optimization model. During a flood event, the K-NN algorithm searches through the historical flood hydrographs and optimal reservoir storages determined by the optimization model to find similar situations. The similarity between the hydrographs is quantified based on the slopes of rising and falling limbs of inflow hydrographs and reservoir storages at the beginning of each hourly time step during the flood events for two cascade reservoirs. The developed methodology have been applied to the Bakhtiari and Dez River-Reservoir systems in southwest of Iran. The results show that the proposed models can be effectively used for flood management and real-time operation of cascade river-reservoir systems.