WIT Press

Trends in Rainfall and Streamflow Series: Portuguese Case Studies

Price

Free (open access)

Paper DOI

10.2495/SAFE-V4-N3-221-248

Volume

Volume 4 (2014), Issue 3

Pages

27

Page Range

221 - 248

Author(s)

M.M. PORTELA, J.F. SANTOS & A.T. SILVA

Abstract

During the history of the Earth, numerous large-scale climate changes occurred, some of them with a cyclic nature. The majority of such changes happened in periods of hundreds, thousands or even mil- lions of years as a result of natural causes, like small variations in Earth’s orbit that change the amount of solar energy received by the planet. However, in recent decades, it has been progressively accepted by the scientific community that the emission of greenhouse gases into the atmosphere is the major driving force of the climate change that presumably is occurring since the last century and mainly since the last 50–75 years. However, if there was a change in such a recent and short period, then the time series of the hydrologic variables more directly related to the climate, as the rainfall or the temperature, should denote signs of it, in the form of trends or non-homogeneities. In the previous scope, several studies have been conducted for mainland Portugal aiming at identifying trends in long hydrological time series and at trying to understand those trends from a climate change perspective. Some of the models applied for that purpose, as well as some of the results thus achieved, are briefly summarized. In general terms, the studies showed that the analyzed time series do not show the trends that are generally pointed out as denoting signs of the climate change, possibly due to their pronounced natural variability and to the insufficient length of the recording periods. There was only one exception, the rainfall in March which, in relative terms, denotes a significant decrease over mainland Portugal, such a decrease being however very small when considered in absolute terms

Keywords

climate change, Gumbel law, hydrologic time series, kernel technique, trend detection, Mann–Kendall test, moving average, statistical models