|
Titel |
Are drought occurrence and severity aggravating? A study on SPI drought class transitions using log-linear models and ANOVA-like inference |
VerfasserIn |
E. E. Moreira, J. T. Mexia, L. S. Pereira |
Medientyp |
Artikel
|
Sprache |
Englisch
|
ISSN |
1027-5606
|
Digitales Dokument |
URL |
Erschienen |
In: Hydrology and Earth System Sciences ; 16, no. 8 ; Nr. 16, no. 8 (2012-08-28), S.3011-3028 |
Datensatznummer |
250013443
|
Publikation (Nr.) |
copernicus.org/hess-16-3011-2012.pdf |
|
|
|
Zusammenfassung |
Long time series (95 to 135 yr) of the 12-month time scale Standardized Precipitation Index
(SPI) relative to 10 locations across Portugal were studied with the aim of investigating if
drought frequency and severity are changing through time.
Considering four drought severity classes, time series of drought
class transitions were computed and later divided into several
sub-periods according to the length of SPI time series. Drought class
transitions were calculated to form a 2-dimensional contingency
table for each sub-period, which refer to the number of transitions among drought severity classes. Two-dimensional log-linear models were fitted
to these contingency tables and an ANOVA-like inference was then
performed in order to investigate differences relative to drought
class transitions among those sub-periods, which were considered as
treatments of only one factor. The application of ANOVA-like
inference to these data allowed to compare the sub-periods in terms of probabilities of transition between drought
classes, which were used to detect a possible trend in droughts frequency and severity. Results for a number of locations show some
similarity between alternate sub-periods and differences between consecutive ones regarding the
persistency of severe/extreme and sometimes moderate droughts. In global terms, results do not
support the assumption of a trend for progressive aggravation of
drought occurrence during the last century, but rather suggest the
existence of long duration cycles. |
|
|
Teil von |
|
|
|
|
|
|