Stochastic transfer function model applied to combined reservoir management and flow routing

Abstract

The paper presents an application of a Stochastic Transfer Function (STF) approach and a nonlinear transformation of model variables to combined reservoir management and flow routing on the Upper Narew River, northeast Poland. The management objective is to reach the required flow conditions in the reaches of an ecologically valuable river. A 1-D distributed flow routing model was designed for the study. However, both optimization methods and reservoir management analysis require numerous model realizations which are computationally very expensive. A much more efficient solution consists of the application of a simplified STF simulator of river flow, which is calibrated on historical data and simulated flows via a distributed model for those parts of the river where observations are not available. The model is stochastic, enabling the derivation of a simulator prediction uncertainty in a straightforward manner. The optimal control policy obtained is tested on a fully distributed model. Obviously, the simulator's predictive uncertainty is larger than the uncertainty of the original distributed model. Therefore, in this application the original model is used to derive probability maps of inundation extent at high- and low-flow conditions under optimized reservoir discharges, following the Generalized Likelihood Uncertainty Estimation procedure. The main advantage of using the simulator lies in the much shorter computation times required by the water management optimization problem, which would be very difficult to solve with a distributed model used for flow routing. Additionally, the simulator may be used for the estimation of probability maps of inundation extent in the case where a distributed flow routing model cannot be run in a Monte Carlo set-up. Citation Romanowicz, R. J., Kiczko, A. & Napiórkowski, J. J. (2010) Stochastic transfer function model applied to combined reservoir management and flow routing. Hydrol. Sci. J. 55(1), 27–40.