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The role of morphology in the spatial distribution of short-duration rainfall extremes in Italy

Authors :
P. Mazzoglio
I. Butera
M. Alvioli
P. Claps
Source :
Hydrology and Earth System Sciences, Vol 26, Pp 1659-1672 (2022)
Publication Year :
2022
Publisher :
Copernicus Publications, 2022.

Abstract

The dependence of rainfall on elevation has frequently been documented in the scientific literature and may be relevant in Italy, due to the high degree of geographical and morphological heterogeneity of the country. However, a detailed analysis of the spatial variability of short-duration annual maximum rainfall depths and their connection to the landforms does not exist. Using a new, comprehensive and position-corrected rainfall extreme dataset (I2-RED, the Improved Italian-Rainfall Extreme Dataset), we present a systematic study of the relationship between geomorphological forms and the average annual maxima (index rainfall) across the whole of Italy. We first investigated the dependence of sub-daily rainfall depths on elevation and other landscape indices through univariate and multivariate linear regressions. The results of the national-scale regression analysis did not confirm the assumption of elevation being the sole driver of the variability of the index rainfall. The inclusion of longitude, latitude, distance from the coastline, morphological obstructions and mean annual rainfall contributes to the explanation of a larger percentage of the variance, even though this was in different ways for different durations (1 to 24 h). After analyzing the spatial variability of the regression residuals, we repeated the analysis on geomorphological subdivisions of Italy. Comparing the results of the best multivariate regression models with univariate regressions applied to small areas, deriving from morphological subdivisions, we found that “local” rainfall–topography relationships outperformed the country-wide multiple regressions, offered a uniform error spatial distribution and allowed the effect of morphology on rainfall extremes to be better reproduced.

Details

Language :
English
ISSN :
10275606 and 16077938
Volume :
26
Database :
Directory of Open Access Journals
Journal :
Hydrology and Earth System Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.84ff13fc7c9a4a5ea5025caefd02c38c
Document Type :
article
Full Text :
https://doi.org/10.5194/hess-26-1659-2022