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Modeling windthrow effects on water runoff and hillslope stability in a mountain catchment affected by the VAIA storm.

L. Mauri,P. Tarolli

Published 2023 in Science of the Total Environment

ABSTRACT

Windthrows seriously affect forest landscapes, causing several issues in hydrological and geomorphological terms. In this regard, Airborne Laser Scanning (ALS) topographic data recently increased the opportunity to investigate in detail physical processes at the catchment scale. Moreover, topographically based hydrological and geomorphological models allows quantifying runoff alteration due to windthrows-driven land cover changes and detect the occurrence of land degradative processes at the sub-catchment scale. In this connection, accurate investigations about windthrows role in varying local runoff regimes over time are still obscure, as well as the possibility of predict terrain instabilities due to windstorm occurrence. This research aims to investigate the interaction between windthrows, runoff alterations and hillslope failures affecting a landslide-prone mountain catchment (northern Italy). Hydrological HEC-HMS and geomorphological RESS models were applied. Windthrows role in altering runoff regimes and hillslope stability was investigated starting from the elaboration of ALS-derived points clouds acquired before and after the occurrence of the Vaia storm. Digital Terrain Models (DTMs) were elaborated for the two scenarios to compare daily runoff variations and predict the activation of terrain instabilities by looking at land cover changes driven by the blowdown event at the sub-catchment detail. Results attested the key role of windstorms in altering local runoff, with a maximum relative runoff increment equal to 2.56 % and a maximum runoff difference equal to 3.12 mmh-1, as well as in encouraging the activation of the observed shallow landslide. The correlation between windthrows occurrence and runoff alterations was validated by performing regression analysis (R2 = 0.76), while the accuracy of instabilities predictions was tested through the Distance to Perfect Classification (D2PC) index and True Skill Statistic (TSS) score, respectively resulted equal to 0.076 and 0.898. This research represents a valid tool for investigating similar issues at a wider scale, also providing suggestions for promoting interventions in wind-disturbed forest areas.

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