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Titel |
Stochastic approach to analyzing the uncertainties and possible changes in the availability of water in the future based on scenarios of climate change |
VerfasserIn |
G. G. Oliveira, O. C. Pedrollo, N. M. R. Castro |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1027-5606
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Digitales Dokument |
URL |
Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 8 ; Nr. 19, no. 8 (2015-08-17), S.3585-3604 |
Datensatznummer |
250120791
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Publikation (Nr.) |
copernicus.org/hess-19-3585-2015.pdf |
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Zusammenfassung |
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. |
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