Study Region: The study was conducted across a hydro-climatic gradient spanning the Bologna Apennines and adjacent lowlands in Northern Italy, a region severely affected by the catastrophic floods of 2023 and 2024.Study Focus: Extreme rainfall events are increasingly driving hydrological hazards, yet disentangling the roles of climate, soil, and land cover remains challenging. We used the 1D hydrological model FLOWS, based on the Richards equation, to quantify their relative contributions to rainfall partitioning. Simulations were performed for 268 soil profiles representing six climatic zones and agricultural and forest land covers over 2020–2024. Across three complementary experimental designs, we distinguished between runoff-generation magnitude and runoff efficiency.New Hydrological Insights for the Region: ANOVA showed that climate accounted for the largest variance in runoff-generation magnitude, explaining 54%–76%, with higher values occurring in wetter years and under extreme conditions. Soil properties primarily influenced the spatial variability of hydrological partitioning. In contrast, land cover mainly regulated runoff efficiency: under identical soil and climatic conditions, forest cover reduced event-scale flux-to-runoff coefficients by 9%–25% relative to agricultural land, while increasing evapotranspiration. These results indicate that climate primarily governs runoff-generation magnitude, soil contributes to its spatial differentiation, and land cover regulates partitioning efficiency. By providing soil-explicit, process-based information, the framework can support the identification of areas where vegetation-based interventions and other NBS may enhance hydrological regulation.
Disentangling climate, soil and land-cover controls on hydrological response under extreme rainfall in Northern Italy
Coppola, Antonio;Bancheri, Marialaura
2026-01-01
Abstract
Study Region: The study was conducted across a hydro-climatic gradient spanning the Bologna Apennines and adjacent lowlands in Northern Italy, a region severely affected by the catastrophic floods of 2023 and 2024.Study Focus: Extreme rainfall events are increasingly driving hydrological hazards, yet disentangling the roles of climate, soil, and land cover remains challenging. We used the 1D hydrological model FLOWS, based on the Richards equation, to quantify their relative contributions to rainfall partitioning. Simulations were performed for 268 soil profiles representing six climatic zones and agricultural and forest land covers over 2020–2024. Across three complementary experimental designs, we distinguished between runoff-generation magnitude and runoff efficiency.New Hydrological Insights for the Region: ANOVA showed that climate accounted for the largest variance in runoff-generation magnitude, explaining 54%–76%, with higher values occurring in wetter years and under extreme conditions. Soil properties primarily influenced the spatial variability of hydrological partitioning. In contrast, land cover mainly regulated runoff efficiency: under identical soil and climatic conditions, forest cover reduced event-scale flux-to-runoff coefficients by 9%–25% relative to agricultural land, while increasing evapotranspiration. These results indicate that climate primarily governs runoff-generation magnitude, soil contributes to its spatial differentiation, and land cover regulates partitioning efficiency. By providing soil-explicit, process-based information, the framework can support the identification of areas where vegetation-based interventions and other NBS may enhance hydrological regulation.
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