Modelling sediment delivery, namely the linkage between hillslope erosion and yield in river systems, is still a challenge. In this study, 1,075 publications from Elsevier's Scopus were analysed to trace the evolution from lumped to spatially distributed approaches. Results confirm that no single model type dominates, while several studies rely on simplified approaches, and data- and model-related errors remain unresolved. Artificial intelligence (AI) and remote sensing (RS) can address such limitations. However, although AI has emerged as either a complementary tool for generating new climate or land-use scenarios or a standalone framework, its adoption has not been transformative so far. Similarly, RS is increasingly used to characterise topography and land cover, but is poorly leveraged to determine other factors influencing sediment dynamics. This overview of existing and evolving methods provides useful insights to support river basin management and model selection. Overall, this study underscores the need for further integration of diverse data sources and processing methods, while future research should prioritise the trade-offs among model complexity, accuracy, and scalability.
Evolution of soil erosion and sediment delivery modelling over six decades: paradigms, limitations and new solutions
Costabile, P.;
2026-01-01
Abstract
Modelling sediment delivery, namely the linkage between hillslope erosion and yield in river systems, is still a challenge. In this study, 1,075 publications from Elsevier's Scopus were analysed to trace the evolution from lumped to spatially distributed approaches. Results confirm that no single model type dominates, while several studies rely on simplified approaches, and data- and model-related errors remain unresolved. Artificial intelligence (AI) and remote sensing (RS) can address such limitations. However, although AI has emerged as either a complementary tool for generating new climate or land-use scenarios or a standalone framework, its adoption has not been transformative so far. Similarly, RS is increasingly used to characterise topography and land cover, but is poorly leveraged to determine other factors influencing sediment dynamics. This overview of existing and evolving methods provides useful insights to support river basin management and model selection. Overall, this study underscores the need for further integration of diverse data sources and processing methods, while future research should prioritise the trade-offs among model complexity, accuracy, and scalability.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
