IWRA Proceedings

< Return to abstract list

MONTHLY SEASONAL MULTIVARIATE AUTOREGRESSIVE MODEL

IWRA World Water Congress 2011 Pernambuco Brazil
2. Water resources and global change
Author(s): Eloy Kaviski
MIRIAM RITA MORO MINE

Eloy Kaviski,MIRIAM RITA MORO MINE, UNIVERSIDADE FEDERAL DO PARANÁ, HIDRÁULICA E SANEAMENTO, MRMINE.DHS@UFPR.BR



Keyword(s): rainfall synthetic series,climate change,climate change,hydropower
Article: PDF

Abstract

Abstract

The objective of the research is to investigate how global climate changes will modify the guaranteed output of a system of interconnected hydropower plants. In particular it is proposed to analyze the performance of the hydropower plants system within the La Plata basin under a set of future climate scenarios. The method 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. The rainfall series obtained at monthly time scale need to be generated statistically by defining appropriate stochastic processes to represent them. The generation of synthetic rainfall series is done by the Monthly Seasonal Multivariate Autoregressive Model SMMAR (1) which deals with seasonal by standardizing rainfall and considers non-stationarity in the correlation structure. Time-varying parameters are required to include seasonal variability in the correlation structure. The SMMAR (1) model, applied to the South-Southeast of Brazil, can be satisfactory for the generation of future scenarios of precipitation.

Key-words: rainfall synthetic series, climate changes, hydropower