Different approaches were used to model soil losses in the Sele River basin (southern Italy) characterized by data scarcity. The suitability of models interpolating different sources of data was evaluated with the aim to suggest similar methodologies in other regions where data availability is not sufficient to use the more complex and detailed models. The first approach is based on the concept of the balance between driving and resisting forces. Rainfall is considered as both a driving and resisting factor: the rain erosivity not only increases with its amount and intensity but also enhances the protective effect of vegetation. The long-term erosion rate of the basin resulted mainly affected by local land-cover conditions that showed a more dramatic effect than the variability of rain erosivity. In the period during which soils were protected by natural woodlands, net erosion rates were extremely low, while the elimination of forest (AD 1780-1810) increased erosion that reached annual rates from 20 to 300 Mg km(-2). The second approach is a revised and scale-adapted Foster-Meyer-Onstad model suitable for scarce input data (CliFEM = Climate Forcing and Erosion Modelling). This new idea was addressed to develop a monthly Net Erosion model (NER) and gross erosion was estimated from the sediment delivery ratio (SDR). From this approach it is clear that the erosion regime was clearly autumnal with a mean rate of 8 Mg ha(-1) per month. The long-term average soil erosion highlighted, since 1990, a more irregular temporal pattern, with the highest annual erosion (200 Mg ha(-1)) in 2002. The third approach combines the revised universal soil loss equation (RUSLE) with GIS-geospatial technology. Regression Ordinary Kriging (ROK)-based maps of erosive rainfall were made on annual and monthly basis. The months following soil tillage (from August to November) have become even more hazardous for soil erosion, with values higher than 80% of total yearly soil losses, because in this period the highest rainfall erosivity is coupled to the lowest soil cover due to soil tillage at the end of summer. In these conditions soil can be protected only by the agro-environmental measures aimed at reducing soil erodibility and at increasing soil cover, such as conservative soil tillage (i.e. sod seeding) and perennial cover crops in orchards and vineyards.
An overview of soil erosion modelling compatible with RUSLE approach
Alberico Ines;
2012
Abstract
Different approaches were used to model soil losses in the Sele River basin (southern Italy) characterized by data scarcity. The suitability of models interpolating different sources of data was evaluated with the aim to suggest similar methodologies in other regions where data availability is not sufficient to use the more complex and detailed models. The first approach is based on the concept of the balance between driving and resisting forces. Rainfall is considered as both a driving and resisting factor: the rain erosivity not only increases with its amount and intensity but also enhances the protective effect of vegetation. The long-term erosion rate of the basin resulted mainly affected by local land-cover conditions that showed a more dramatic effect than the variability of rain erosivity. In the period during which soils were protected by natural woodlands, net erosion rates were extremely low, while the elimination of forest (AD 1780-1810) increased erosion that reached annual rates from 20 to 300 Mg km(-2). The second approach is a revised and scale-adapted Foster-Meyer-Onstad model suitable for scarce input data (CliFEM = Climate Forcing and Erosion Modelling). This new idea was addressed to develop a monthly Net Erosion model (NER) and gross erosion was estimated from the sediment delivery ratio (SDR). From this approach it is clear that the erosion regime was clearly autumnal with a mean rate of 8 Mg ha(-1) per month. The long-term average soil erosion highlighted, since 1990, a more irregular temporal pattern, with the highest annual erosion (200 Mg ha(-1)) in 2002. The third approach combines the revised universal soil loss equation (RUSLE) with GIS-geospatial technology. Regression Ordinary Kriging (ROK)-based maps of erosive rainfall were made on annual and monthly basis. The months following soil tillage (from August to November) have become even more hazardous for soil erosion, with values higher than 80% of total yearly soil losses, because in this period the highest rainfall erosivity is coupled to the lowest soil cover due to soil tillage at the end of summer. In these conditions soil can be protected only by the agro-environmental measures aimed at reducing soil erodibility and at increasing soil cover, such as conservative soil tillage (i.e. sod seeding) and perennial cover crops in orchards and vineyards.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
