A new procedure to estimate the RUSLE EI30 index, based on monthly rainfall data and applied to the Algarve region, Portugal

Loureiro, Nuno de Santos; Coutinho, Miguel de Azevedo

doi:10.1016/s0022-1694(01)00387-0

Cited by 154 publications

(48 citation statements)

References 2 publications

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“…Unfortunately, the technical brief attached to the map of ICONA did not report enough details allowing for a deeper comparison. The R factor values found for the area are similar to the ones published by other authors for the Mediterranean region: 697.4 to 3741.8 MJ mm ha −1 h −1 y −1 in Portugal (De Santos Loureiro and De Azevedo Coutinho, 2001); 471 and 3214 MJ mm ha −1 h −1 y −1 in Italy (Diodato, 2004); 339 to 818 MJ mm ha −1 h −1 y −1 in Central Spain (Boellstorff and Benito, 2005); or 419.01 to 1124.36 MJ mm ha −1 h −1 y −1 in Sicily (Onori et al, 2006). We are not aware of previous studies analyzing the spatial distribution of the average EI 30 index.…”

Section: Discussionsupporting

confidence: 88%

Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)

Angulo‐Martínez

López‐Vicente

Vicente‐Serrano

et al. 2009

Hydrol. Earth Syst. Sci.

108

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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 EI 30 index of the erosive events over the Ebro basin (NE Spain). A spatially dense precipitation data base with a high temporal resolution (15 min) was used. Global, local and geostatistical interpolation techniques were employed to produce maps of the rainfall erosivity indices, as well as mixed methods. To determine the reliability of the maps several goodness-of-fit and error statistics were computed, using a cross-validation scheme, as well as the uncertainty of the predictions, modeled by Gaussian geostatistical simulation. All methods were able to capture the general spatial pattern of both erosivity indices. The semivariogram analysis revealed that spatial autocorrelation only affected at distances of ∼15 km around the observatories. Therefore, local interpolation techniques tended to be better overall considering the validation statistics. All models showed high uncertainty, caused by the high variability of rainfall erosivity indices both in time and space, what stresses the importance of having long data series with a dense spatial coverage.

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Section: Discussionsupporting

confidence: 88%

Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)

Angulo‐Martínez

López‐Vicente

Vicente‐Serrano

et al. 2009

Hydrol. Earth Syst. Sci.

108

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“…In the context of varying soil erosion susceptibility caused by seasonal changes in the protective vegetation cover (Panagos et al, 2011), the temporal distribution throughout the year and the timing of the most severe events is an important characteristic of rainfall erosivity. In many studies the 168 K. Meusburger et al: Spatial and temporal variability of rainfall erosivity factor for Switzerland rainfall erosivity calculation is limited to either time-series analysis of single stations (Mikos et al, 2006;Verstraeten et al, 2006) or for larger spatial scales to regional approximation equations (Bollinne et al, 1979;Rogler and Schwertmann, 1981;Renard and Freimund, 1994;Strauss and Blum, 1994;De Santos Loureiro and De Azevedo Coutinho, 2001;Bellocchi, 2007, 2010;Capolongo et al, 2008). The original method to calculate the erosivity values for a storm event requires pluviographic records (Wischmeier, 1978).…”

Section: Introductionmentioning

confidence: 99%

Spatial and temporal variability of rainfall erosivity factor for Switzerland

Meusburger

Steel

Panagos

et al. 2012

Hydrol. Earth Syst. Sci.

225

120

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“…There have been many attempts worldwide to establish correlations between the R-factor calculated by the prescribed method and more readily available rainfall data, such as daily and monthly precipitation (Renard and Freimund, 1994;Yu and Rosewell, 1996;Loureiro and Coutinho, 2001;Yu et al, 2001;Colotti, 2004;Diodato, 2004;Petkovšek and Mikoš, 2004;Diodato and Bellochi, 2007;Salako, 2008;Angulo-Martínez and Beguería, 2009;Bonilla and Vidal, 2011;Lee and Heo, 2011). Nonetheless, most of the obtained equations have limited application outside of the areas in which they were developed without a thorough validation analysis.…”

Section: Introductionmentioning

confidence: 99%

Estimate of the (R)USLE rainfall erosivity factor from monthly precipitation data in mainland Spain

Hernando

Romana

2016

Journal of Iberian Geology

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Calculation of the rainfall erosivity factor (R-factor) of the (R)USLE model requires continuous recording rain gauges, which may limit its use in areas without good temporal data coverage. In mainland Spain, the Nature Conservation Institute (ICONA) determined the Rfactor at few selected pluviographs, so simple estimates of the R-factor are definitely of great interest. The objectives of this study were: (1) to identify a readily available estimate of the R-factor for mainland Spain; (2) to discuss the applicability of a single (global) estimate based on analysis of regional results; (3) to evaluate the effect of record length on estimate precision and accuracy; and (4) to validate an available regression model developed by ICONA. Four estimators based on monthly precipitation were computed at 74 rainfall stations throughout mainland Spain. The regression analysis conducted at a global level clearly showed the modified Fournier index (MFI) ranked first among all assessed indexes. Applicability of this preliminary global model across mainland Spain was evaluated by analyzing regression results obtained at a regional level. It was found that three contiguous regions of Eastern Spain (Catalonia, Valencian Community and Murcia) could have a different rainfall erosivity pattern, so a new regression analysis was conducted by dividing mainland Spain into two areas: Eastern Spain and Plateau-lowland area. A comparative analysis concluded that the bi-areal regression model based on MFI for a 10-year record length provided a simple, precise and accurate estimate of the R-factor in mainland Spain. Finally, validation of the regression model proposed by ICONA showed that R-ICONA index overpredicted the R-factor by approximately 19%.Keywords: rainfall erosivity, R-factor, Universal Soil Loss Equation, modified Fournier index, soil erosion, Spain Resumen La necesidad de disponer de un registro continuo de la precipitación dificulta el cálculo del índice de erosión pluvial (factor R) del modelo (R)USLE en zonas sin un buen registro temporal. En la España peninsular, el Instituto para la Conservación de la Naturaleza (ICONA) determinó el factor R en un reducido número de pluviógrafos, por lo que es de gran interés disponer de una herramienta que permita estimar el factor R de manera sencilla. Los objetivos de este estudio fueron: (1) identificar un estimador del factor R en la España peninsular; (2) discutir la aplicabilidad de un único modelo de estimación global a partir de los resultados obtenidos a nivel regional; (3) analizar el efecto de la longitud del intervalo de cálculo en la precisión y exactitud de las estimaciones; y (4) evaluar el modelo de regresión disponible propuesto por ICONA. Para ello se calcularon cuatro estimadores basados en la precipitación mensual en 74 estaciones pluviométricas repartidas por la geografía peninsular. El análisis de regresión llevado a cabo demostró que el índice de Fournier modificado (MFI) es el mejor estimador. La aplicabilidad del modelo global generado inicialmente se eva...

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A new procedure to estimate the RUSLE EI30 index, based on monthly rainfall data and applied to the Algarve region, Portugal

Cited by 154 publications

References 2 publications

Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)

Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain)

Spatial and temporal variability of rainfall erosivity factor for Switzerland

Estimate of the (R)USLE rainfall erosivity factor from monthly precipitation data in mainland Spain

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