River flow forecast for reservoir management through neural networks

Abstract River flow forecasts are required to provide basic information for reservoir management in a multipurpose water system optimisation framework. An accurate prediction of flow rates in tributary streams is crucial to optimise the management of water resources considering extended time horizons. Moreover, runoff prediction is crucial in protection from water shortage and possible flood damages. In this paper, a neural approach is used to model the rainfall-runoff process when different time step durations have to be considered in reservoir management. Numerical comparisons with observed data are provided for runoff prediction in the Tirso basin at the S.Chiara section in Sardinia (Italy).

[1]  A. W. Minns,et al.  Artificial neural networks as rainfall-runoff models , 1996 .

[2]  T.,et al.  Training Feedforward Networks with the Marquardt Algorithm , 2004 .

[3]  Robert J. Abrahart,et al.  Investigating the role of saliency analysis with a neural network rainfall-runoff model , 2001 .

[4]  Ronny Berndtsson,et al.  Spatial and temporal scales in rainfall analysis ― some aspects and future perspectives , 1988 .

[5]  Alessandra Fanni,et al.  Alternative Neural Network Models for the Rainfall-Runoff Process , 2002 .

[6]  C. W. Thornthwaite.  An Approach Toward a Rational Classification of Climate , 1948 .

[7]  A. Shamseldin.  Application of a neural network technique to rainfall-runoff modelling , 1997 .

[8]  Alessandra Fanni,et al.  Dynamic neural networks for the water flow forecasting , 2000 .

[9]  Ian Flood,et al.  Neural Networks in Civil Engineering. I: Principles and Understanding , 1994 .

[10]  Murray Smith,et al.  Neural Networks for Statistical Modeling , 1993 .

[11]  P. Young,et al.  Recursive estimation: A unified approach to the identification estimation, and forecasting of hydrological systems , 1985 .

[12]  C. W. Thornthwaite.  An approach toward a rational classification of climate. , 1948 .

[13]  Calculation of mean areal depth of precipitation , 1971 .

[14]  Christian W. Dawson,et al.  Hydrological modelling using artificial neural networks , 2001 .

[15]  M. Lorrai,et al.  Neural nets for modelling rainfall-runoff transformations , 1995 .

[16]  Holger R. Maier,et al.  Neural networks for the prediction and forecasting of water resource variables: a review of modelling issues and applications , 2000, Environ. Model. Softw..