Abstract
The issue of soil erosion is considered highly important by local administrators of the Chianti region. Thus, a methodology for predicting the long-term average annual soil loss, by using the Revised Universal Soil Loss Equation (RUSLE) in a Geographical Information System framework was developed and assessed. The rainfall and runoff erosivity factor was calculated using 35 raingauges with an acquisition interval of 15min in the period from 1996 to 2010. The soil erodibility factor was estimated using a soil map at a scale of 1:50,000. The topographic factor was calculated from a 10m digital elevation model. Moreover, a methodology was proposed that took into account the vineyard row direction and slope. Soil loss field data (566 field sites) were measured over 6years using a topographical approach, and used to validate the model results. The statistical indices for the evaluation of the model were, respectively, the mean percent error (M%E), −0.1%, the ratio of the RMSE to the standard deviation of the observations (RSR), 23.7%; and the Nash–Sutcliffe coefficient (NCS), 0.9. Statistics indicated good predictions of long-term average annual soil losses at a field scale. The average annual soil loss for the study area was predicted up to 6.4t·ha−1·y−1. Approximately 13% of the study area was classified as high erosion (≥22t·ha−1·y−1). The identification of areas with the greatest erosion risk supports the possibility of using the model for land-use and land-management planning purposes. Moreover, this assists in the identification of those areas towards which conservation measures can be directed.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.