Soil erosion is an important issue in sloping areas where vineyards are typically grown. In vineyards, different soil management can be applied to reduce soil losses, although multiple factors affect this soil degradation process. The Revised Universal Soil Loss Equation (RUSLE) is one of the most widely used models to assess soil anagement role in reducing soil erosion at field scale. The RUSLE topographical LS factor can nowadays be derived from a Digital Elevation Model (DEM) in a GIS environment. Different algorithms have been developed to obtain LS automatically. Differences in the results between operator-measured and algorithm derived values available in SAGA GIS were tested for different DEM geometrical resolutions (5, 10 and 25 m). Linear regression helped identifying the best combination of both parameters. Additionally, SAGA algorithms provided information on the spatial variability of this factor within the field as well. The resulting soil losses were then computed with the ORUSCAL model (a simplified version of RUSLE2) for different fields within a hilly study area in the Alto Monferrato (NW Italy), considering different inter-row soil managements. As expected, DEMs with a higher resolution gave the best results (R2 >= 0.8) for all algorithms in both LS and soil loss estimates. In any case, results for soil loss estimates showed that an inter-row management having a consolidated grass-cover can significantly reduce soil erosion within the vineyard. Soil losses estimates equally displayed a certain degree of variability (average coefficient of variation: 30%), highlighting the importance of correctly assessing this factor using data characterised by a good geometric resolution.
Assessing soil erosion rates at vineyard scale: a study case in North-West Italy using different DEM resolutions for the LS factor computation
Francesco Palazzi;Marcella Biddoccu;Eugenio Cavallo
2022
Abstract
Soil erosion is an important issue in sloping areas where vineyards are typically grown. In vineyards, different soil management can be applied to reduce soil losses, although multiple factors affect this soil degradation process. The Revised Universal Soil Loss Equation (RUSLE) is one of the most widely used models to assess soil anagement role in reducing soil erosion at field scale. The RUSLE topographical LS factor can nowadays be derived from a Digital Elevation Model (DEM) in a GIS environment. Different algorithms have been developed to obtain LS automatically. Differences in the results between operator-measured and algorithm derived values available in SAGA GIS were tested for different DEM geometrical resolutions (5, 10 and 25 m). Linear regression helped identifying the best combination of both parameters. Additionally, SAGA algorithms provided information on the spatial variability of this factor within the field as well. The resulting soil losses were then computed with the ORUSCAL model (a simplified version of RUSLE2) for different fields within a hilly study area in the Alto Monferrato (NW Italy), considering different inter-row soil managements. As expected, DEMs with a higher resolution gave the best results (R2 >= 0.8) for all algorithms in both LS and soil loss estimates. In any case, results for soil loss estimates showed that an inter-row management having a consolidated grass-cover can significantly reduce soil erosion within the vineyard. Soil losses estimates equally displayed a certain degree of variability (average coefficient of variation: 30%), highlighting the importance of correctly assessing this factor using data characterised by a good geometric resolution.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
