چکیده (انگلیسی):

Preserving soils is a major challenge in ensuring sustainable agriculture for the future. Soil erosion by water is a critical issue in the Mediterranean regions and usually occurs when high-erosive precipitation is in temporal association with poor vegetation cover and density. Modelling soil erosion risks over large spatial scales suffers from the scarcity of accurate information on land cover, rainfall erosivity and their intra-annual dynamics. We estimated the soil erosion risk on arable land in a Mediterranean area (Grosseto Province, southern Tuscany, Italy) and investigated its potential reduction as a response to the change in intra-annual distribution of land cover due to the increase of perennial forage crops. A GIS-based (R)USLE model was employed and a scenario analysis was performed by setting criteria for raising the performance of perennial forage crops. Statistical data on agricultural crops provided an insight into current intra-annual land cover dynamics. Rainfall erosivity was computed on the basis of 22-year hourly precipitation data. The model was used to: i) quantify the potential soil losses of arable land in the study area, ii) identify those areas highly affected by erosion risks iii) explore the potential for soil conservation of perennial crops, thereby enabling appropriate preventive measures to be identified. The erosion rates, averaged over an area of about 140’000 ha, are estimated to 33.42 Mg ha−1 y−1. More than 59% of the study area was subjected to soil losses higher than 11 Mg ha−1 y−1 (from moderate to severe erosion) and the highest rates are estimated for steep inland areas. Arable land with severe soil erosion rates (higher than 33 Mg ha−1 y−1) represent about 35% of the whole study area. The risk of soil loss by water erosion in the study area is estimated to be reduced on average by 36% if perennial crops are increased in terms of 35% of the total arable land. The soil erosion data produced compared well with the published local and regional data. This study thus provides useful preliminary information for landscape planning authorities and can be used as a decision support tool in quantifying the implications of management policies.