6533b7d6fe1ef96bd12663c8

RESEARCH PRODUCT

Testing the Modified Sediment Delivery Model (MOSEDD) at SPA2 Experimental Basin, Sicily (Italy)

Vito FerroCostanza Di Stefano

subject

Sediment yieldHydrologyScale (ratio)Calibration (statistics)0208 environmental biotechnologySoil ScienceSediment04 agricultural and veterinary sciences02 engineering and technologyDevelopmentStructural basin020801 environmental engineeringModel validation040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental ChemistryEnvironmental scienceSediment transportEvent scaleGeneral Environmental Science

description

A new version of a spatially distributed sediment delivery model taking into account the hillslope sediment transport efficiency, named MOSEDD, is presented. This model gives estimates of basin sediment yield at event scale, which are more reliable than those obtained by the original SEDD. For SPA2 basin discretized into morphological units, four different calculation schemes of MOSEDD, including the original SEDD version, were applied. All parameterization schemes of the model were calibrated using 15 events measured at the outlet of the experimental basin in the period February 2005–February 2010. The model calibration was used to determine a relationship between the coefficient βₑ of the model and the erosivity factor. For the model validation, other six measured events, collected in the period March 2010–February 2014, were used. At event scale, the comparison between measured sediment yield values and calculated ones showed that the three calculation schemes of MOSEDD using a rainfall–runoff erosivity factor (MODB, MODC and MODD) have the best performance in estimating sediment yield with respect to the original version of SEDD. The analysis was also developed at annual scale, for the period 2005–2014, and a relationship between the annual value of the coefficient, βₐ, of the model and the corresponding erosivity factor was established. This last analysis showed that the sediment delivery distributed approach has also a good predictive ability at annual scale. Copyright © 2016 John Wiley & Sons, Ltd.

https://doi.org/10.1002/ldr.2684