Study regionThis study focuses on three catchments located in the Oltrepò Pavese area of Northern Italy, a hilly landscape characterized by steep slopes, clay-marl lithologies, and extensive agricultural and viticultural land use. The region is prone to rainfall-induced soil erosion, making it an ideal setting to compare erosion modeling approaches.Study focusWe evaluate the complementary use of the empirical Revised Universal Soil Loss Equation (RUSLE), which provides long-term average erosion estimates, and a two-dimensional Rain-on-Grid (RoG) hydrodynamic model, which simulates event-based runoff dynamics and sediment transport capacity. These models were applied using harmonized inputs to assess their spatial agreement in identifying erosion-prone areas and compared with erosion inventory zones mapped after a major storm in 2009.New hydrogeological insights from the regionDespite operating at different temporal scales, the two approaches showed over 50% spatial overlap in detecting erosion-prone areas, particularly on steep slopes with concentrated runoff. RoG reproduced the mapped 2009 erosion zones more effectively than RUSLE, highlighting the dominant role of short-duration, high-intensity runoff-driven processes, while RUSLE better captured land-cover effects. Because validation is based on a single event with a different return period and includes processes not simulated by RoG, results should be interpreted as spatial-pattern agreement rather than quantitative predictive performance. The integrated use of both models offers a practical and transferable framework for data-scarce catchments.
Towards integrated short-term Rain-on-Grid modeling and long-term RUSLE estimates for improved erosion susceptibility assessment in the Oltrepò Pavese hills of Northern Italy
Costanzo, C.;Bordoni, M.;Costabile, P.;
2026-01-01
Abstract
Study regionThis study focuses on three catchments located in the Oltrepò Pavese area of Northern Italy, a hilly landscape characterized by steep slopes, clay-marl lithologies, and extensive agricultural and viticultural land use. The region is prone to rainfall-induced soil erosion, making it an ideal setting to compare erosion modeling approaches.Study focusWe evaluate the complementary use of the empirical Revised Universal Soil Loss Equation (RUSLE), which provides long-term average erosion estimates, and a two-dimensional Rain-on-Grid (RoG) hydrodynamic model, which simulates event-based runoff dynamics and sediment transport capacity. These models were applied using harmonized inputs to assess their spatial agreement in identifying erosion-prone areas and compared with erosion inventory zones mapped after a major storm in 2009.New hydrogeological insights from the regionDespite operating at different temporal scales, the two approaches showed over 50% spatial overlap in detecting erosion-prone areas, particularly on steep slopes with concentrated runoff. RoG reproduced the mapped 2009 erosion zones more effectively than RUSLE, highlighting the dominant role of short-duration, high-intensity runoff-driven processes, while RUSLE better captured land-cover effects. Because validation is based on a single event with a different return period and includes processes not simulated by RoG, results should be interpreted as spatial-pattern agreement rather than quantitative predictive performance. The integrated use of both models offers a practical and transferable framework for data-scarce catchments.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


