The role of morphology in the spatial distribution of short-duration rainfall extremes in Italy
| Autor: | Paola Mazzoglio, Ilaria Butera, Pierluigi Claps, Massimiliano Alvioli |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Hydrology and earth system sciences (Online) 26 (2022): 1659–1672. doi:10.5194/hess-26-1659-2022 info:cnr-pdr/source/autori:P. Mazzoglio(1), I. Butera(1), M. Alvioli(2), P. Claps(1)/titolo:The role of morphology on the spatial distribution of short-duration rainfall extremes in Italy/doi:10.5194%2Fhess-26-1659-2022/rivista:Hydrology and earth system sciences (Online)/anno:2022/pagina_da:1659/pagina_a:1672/intervallo_pagine:1659–1672/volume:26 |
| ISSN: | 1607-7938 |
| DOI: | 10.5194/hess-26-1659-2022 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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