Luiz Fernando Nascimento Ferreira,MIRIAM RITA MORO MINE,Heinz Dieter Fill,Fernando Weigert Machado, UNIVERSIDADE FEDERAL DO PARANÁ, , MRMINE.DHS@UFPR.BR
Abstract
This paper presents the results of an Artificial Neural Networks - ANN model for the monthly rainfall-runoff transformation in the context of CLARIS LPB Project. One of the objectives of the CLARIS LPB Project is to investigate how global climate changes will modify the guaranteed output of a system of interconnected hydroplants in La Plata Basin. In particular it is proposed to analyze the performance of the hydroplants system within the La Plata basin under a set of future climate scenarios. The methodology should be based on Monte Carlo simulations using synthetic streamflow series representing future scenarios of global climate changes. These series should be obtained from synthetic rainfall series using standard rainfall-runoff models at a monthly time scale. A monthly rainfall-runoff model available is Artificial Neural Networks - ANN for the rainfall-runoff transformation. The case study is being conducted for the interconnected power system South-Southeast of Brazil
Key-words: Artificial Neural Network, climate changes impact, hydropower