Author:
Angulo-Martínez M.,López-Vicente M.,Vicente-Serrano S. M.,Beguería S.
Abstract
Abstract. Rainfall erosivity is a major causal factor of soil erosion, and it is included in many prediction models. Maps of rainfall erosivity indices are required for assessing soil erosion at the regional scale. In this study a comparison is made between several techniques for mapping the rainfall erosivity indices: i) the RUSLE R factor and ii) the average EI30 index of the erosive events over the Ebro basin (NE Spain). A spatially dense precipitation data base with a high temporal resolution (15 min) has been used. Global, local and geostatistical interpolation techniques were employed to produce maps of the rainfall erosivity indices, as well as mixed methods (regression plus local interpolation). To determine the reliability of the maps several goodness-of-fit and error statistics were computed, using a cross-validation scheme. All methods represented correctly the spatial patterns of both erosivity indices, but the mixed approaches tended to be better overall considering the validation statistics. Additionally, they allowed identifying statistically significant relationships between rainfall erosivity and other geographical variables, as elevation and distance to the water bodies. All models had a relatively high uncertainty, caused by the high variability of rainfall erosivity indices both in time and space, what stresses the importance of using the longest data series available with a good spatial coverage.
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