Abstract
Annual maximum rainfall intensity for several duration and return periods has been analyzed according to the Gumbel distribution. The Intensity-Duration-Frequency (IDF) curves before and after 1980 have been computed and compared. For the city of Toronto, it is shown that the rainfall intensities after 1980 are lower than those from before this date. This is especially clear for those of short duration. Comparing our results with those of other authors, it appears that, for the moment, no general law on the impact of global warming on the curves intensity duration frequency cannot be made. It appears that the impact of global warming on rainfall varies with geographic location and that it is not possible to draw some general conclusions across the planet.
Highlights
Regarding civil engineering, the knowledge and understanding of climate change is important because, if there are changes in the variables related to hydrological systems, it could imply changes in design criteria, as these are frequently based upon the assumption of the hydrological series stationary
The IDF (Intensity Duration Frequency) relationship constitutes an objective tool to quantify precipitation uncertainty, especially in circumstances when a design rainfall event must be determined for a particular water resources project
They computed rainfall depth for a return period of 500 years and concluded that rainfall depth obtained for the period 1961 to 2010 are overall higher than 15% than estimated from the rainfall series from 1901 to 1970 for all stations in Switzerland
Summary
The knowledge and understanding of climate change is important because, if there are changes in the variables related to hydrological systems, it could imply changes in design criteria, as these are frequently based upon the assumption of the hydrological series stationary. (2016) Impact of Global Warming on Intensity-Duration-Frequency (IDF) Relationship of Precipitation: A Case Study of Toronto, Canada. The IDF (Intensity Duration Frequency) relationship constitutes an objective tool to quantify precipitation uncertainty, especially in circumstances when a design rainfall event must be determined for a particular water resources project. The prediction of uncertain environmental variables is often a hydrologic problem of significance in water resources management and water resources design projects. The Gumbel distribution, named after one of the pioneer scientists in practical applications of the Extreme Value Theory (EVT), the German mathematician Emil Gumbel (1891-1966), has been extensively used in various fields including hydrology for modeling extreme events [1]-[3]. The objective of this present work is to study the impact of this increase on the intensity of the rainfall at Toronto for several return periods and durations
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