Data Entry: Please note that the research database will be replaced by UNIverse by the end of October 2023. Please enter your data into the system https://universe-intern.unibas.ch. Thanks

Login for users with Unibas email account...

Login for registered users without Unibas email account...

 
Rainfall erosivity in Italy: a national scale spatio-temporal assessment
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 3707023
Author(s) Borrelli, Pasquale; Diodato, Nazzareno; Panagos, Panos
Author(s) at UniBasel Borrelli, Pasquale
Year 2016
Title Rainfall erosivity in Italy: a national scale spatio-temporal assessment
Journal International Journal of Digital Earth
Volume 9
Number 9
Pages / Article-Number 835-850
Keywords Earth observation, GIS, digital earth, meteorology, soil erosion
Abstract

Soil erosion by water is a serious threat for the Mediterranean region. Raindrop impacts and consequent runoff generation are the main driving forces of this geomorphic process of soil degradation. The potential ability for rainfall to cause soil loss is expressed as rainfall erosivity, a key parameter required by most soil loss prediction models. In Italy, rainfall erosivity measurements are limited to few locations, preventing researchers from effectively assessing the geography and magnitude of soil loss across the country. The objectives of this study were to investigate the spatio-temporal distribution of rainfall erosivity in Italy and to develop a national-scale grid-based map of rainfall erosivity. Thus, annual rainfall erosivity values were measured and subsequently interpolated using a geostatistical approach. Time series of pluviographic records (10-years) with high temporal resolution (mostly 30-min) for 386 meteorological stations were analysed. Regression-kriging was used to interpolate rainfall erosivity values of the meteorological stations to an Italian rainfall erosivity map (500-m). A set of 23 environmental covariates was tested, of which seven covariates were selected based on a stepwise approach (mostly significant at the 0.01 level). The interpolation method showed a good performance for both the cross-validation data set ( = 0.777) and the fitting data set ( R 2 = 0.779).

Publisher Taylor & Francis
ISSN/ISBN 1753-8947 ; 1753-8955
edoc-URL http://edoc.unibas.ch/52883/
Full Text on edoc No
Digital Object Identifier DOI 10.1080/17538947.2016.1148203
ISI-Number WOS:000382199700002
Document type (ISI) Article
 
   

MCSS v5.8 PRO. 0.353 sec, queries - 0.000 sec ©Universität Basel  |  Impressum   |    
03/05/2024