Large wood (LW) plays a key role in physical, chemical, environmental, and biological processes in most natural and seminatural streams. However, it is also a source of hydraulic hazard in anthropised territories. Recruitment from fluvial processes has been the subject of many studies, whereas less attention has been given to hillslope recruitment, which is linked to episodic and spatially distributed events and requires a reliable and accurate slope stability model and a hillslope-channel transfer model. The purpose of this study is to develop an innovative LW hillslope-recruitment estimation approach that combines forest stand characteristics in a spatially distributed form, a probabilistic multidimensional slope stability model able to include the reinforcement exerted by roots, and a hillslope-channel transfer procedure. The approach was tested on a small mountain headwater catchment in the eastern Italian Alps that is prone to shallowlandslide and debris flow phenomena. The slope stabilitymodel (that had not been calibrated) provided accurate performances, in terms of unstable areas identification according to the landslide inventory (AUC= 0.832) and of LW volume estimation in comparison with LW volume produced by inventoried landslides (7702m3 corresponding to a recurrence time of about 30 years in the susceptibility curve). The results showed that mostLWpotentiallymobilised by landslides does not reach the channel network (only about 16%), in agreement with the few data reported by other studies, as well as the data normalized for unit length of channel and unit length of channel per year (0–116m3/km and 0–4m3/kmy−1). This study represents an important contribution to LW research. A rigorous and site-specific estimation of LW hillslope recruitment should, in fact, be an integral part of more general studies on LW dynamics, for forest planning and management, and positioning in-channel wood retention structures.

A probabilistic multidimensional approach to quantify large wood recruitment from hillslopes in mountainous-forested catchments

Rigon, Emanuel;Lenzi, Mario Aristide;Bischetti, Gian Battista
2018

Abstract

Large wood (LW) plays a key role in physical, chemical, environmental, and biological processes in most natural and seminatural streams. However, it is also a source of hydraulic hazard in anthropised territories. Recruitment from fluvial processes has been the subject of many studies, whereas less attention has been given to hillslope recruitment, which is linked to episodic and spatially distributed events and requires a reliable and accurate slope stability model and a hillslope-channel transfer model. The purpose of this study is to develop an innovative LW hillslope-recruitment estimation approach that combines forest stand characteristics in a spatially distributed form, a probabilistic multidimensional slope stability model able to include the reinforcement exerted by roots, and a hillslope-channel transfer procedure. The approach was tested on a small mountain headwater catchment in the eastern Italian Alps that is prone to shallowlandslide and debris flow phenomena. The slope stabilitymodel (that had not been calibrated) provided accurate performances, in terms of unstable areas identification according to the landslide inventory (AUC= 0.832) and of LW volume estimation in comparison with LW volume produced by inventoried landslides (7702m3 corresponding to a recurrence time of about 30 years in the susceptibility curve). The results showed that mostLWpotentiallymobilised by landslides does not reach the channel network (only about 16%), in agreement with the few data reported by other studies, as well as the data normalized for unit length of channel and unit length of channel per year (0–116m3/km and 0–4m3/kmy−1). This study represents an important contribution to LW research. A rigorous and site-specific estimation of LW hillslope recruitment should, in fact, be an integral part of more general studies on LW dynamics, for forest planning and management, and positioning in-channel wood retention structures.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3270352
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