Stochastic approach to analyzing the uncertainties and possible changes in the availability of water in the future based on scenarios of climate change

Abstract

The objective of this study was to analyze the changes and uncertainties related to water availability in the future (for the purposes of this study, the period between 2011 and 2040 was adopted), using a stochastic approach, taking as reference a climate projection from climate model Eta CPTEC/HadCM3. The study was applied to the Ijuí River basin in the south of Brazil. The set of methods adopted involved, among others, correcting the climatic variables projected for the future, hydrological simulation using artificial neural networks (ANNs) to define a number of monthly flows and stochastic modeling to generate 1000 hydrological series with equal probability of occurrence. A multiplicative type stochastic model was developed in which monthly flow is the result of the product of four components: (i) long-term trend component; (ii) cyclic or seasonal component; (iii) time-dependency component; and (iv) random component. In general, the results showed a trend to increased flows. The mean flow for a long period, for instance, presented an alteration from 141.6 m3 s−1 (1961–1990) to 200.3 m3 s−1 (2011–2040). An increment in mean flow and in the monthly standard deviation was also observed between the months of January and October. Between the months of February and June, the percentage of mean monthly flow increase was more marked, surpassing the 100 % index. Considering the confidence intervals in the flow estimates for the future, it can be concluded that there is a tendency to increase the hydrological variability during the period between 2011 and 2040, which indicates the possibility of occurrence of time series with more marked periods of droughts and floods.