Articles | Volume 19, issue 9
https://doi.org/10.5194/hess-19-3845-2015
https://doi.org/10.5194/hess-19-3845-2015
Research article
 | 
11 Sep 2015
Research article |  | 11 Sep 2015

Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

F. Todisco, L. Brocca, L. F. Termite, and W. Wagner

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Cited articles

Akaike, H.: New look at the statistical model identification, IEEE Transactions on Automatic Control, AC-19, 716–723, 1974.
Bagarello, V. and Ferro, V.: Plot-scale measurement of soil erosion at the experimental area of Sparacia (southern Italy), Hydrol. Process., 18, 141–157, 2004.
Bagarello, V., Di Piazza, G. V., Ferro, V., and Giordano, G.: Predicting unit soil loss in Sicily, south Italy, Hydrol. Process., 22, 586–595, 2008.
Bagarello, V., Ferro, V., and Giordano, G.: Testing alternative erosivity indices to predict event soil loss from bare plots in southern Italy, Hydrol. Process., 24, 789–797, 2010.
Bagarello, V., Di Stefano, C., Ferro, V., Kinnell, P. I. A., Pampalone, V., Porto, P., and Todisco, F.: Predicting soil loss on moderate scope using an empirical model for sediment concentration, J. Hydrol., 400, 267–273, 2011.
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We developed a new formulation of USLE, named Soil Moisture for Erosion (SM4E), that directly incorporates soil moisture information. SM4E is applied here by using modeled data and satellite observations obtained from the Advanced SCATterometer (ASCAT). SM4E is found to outperform USLE and USLE-MM models in silty–clay soil in central Italy. Through satellite data, there is the potential of applying SM4E for large-scale monitoring and quantification of the soil erosion process.