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Estimating the rainfall erosivity factor from monthly precipitation data in the Madrid Region (Spain)

Open Access
|Jan 2015

Abstract

The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (Rfactor) of the Universal Soil Loss Equation in regions without good spatial and temporal data coverage. In particular, the R-factor is only known at 16 rain gauge stations in the Madrid Region (Spain). The objectives of this study were to identify a readily available estimate of the R-factor for the Madrid Region and to evaluate the effect of rainfall record length on estimate precision and accuracy. Five estimators based on monthly precipitation were considered: total annual rainfall (P), Fournier index (F), modified Fournier index (MFI), precipitation concentration index (PCI) and a regression equation provided by the Spanish Nature Conservation Institute (RICONA). Regression results from 8 calibration stations showed that MFI was the best estimator in terms of coefficient of determination and root mean squared error, closely followed by P. Analysis of the effect of record length indicated that little improvement was obtained for MFI and P over 5- year intervals. Finally, validation in 8 additional stations supported that the equation R = 1.05·MFI computed for a record length of 5 years provided a simple, precise and accurate estimate of the R-factor in the Madrid Region.

DOI: https://doi.org/10.1515/johh-2015-0003 | Journal eISSN: 1338-4333 | Journal ISSN: 0042-790X
Language: English
Page range: 55 - 62
Submitted on: Mar 5, 2014
Accepted on: Aug 21, 2014
Published on: Jan 28, 2015
Published by: Slovak Academy of Sciences, Institute of Hydrology; Institute of Hydrodynamics, Czech Academy of Sciences, Prague
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2015 David Hernando, Manuel G. Romana, published by Slovak Academy of Sciences, Institute of Hydrology; Institute of Hydrodynamics, Czech Academy of Sciences, Prague
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.