Hydrosedimentary connectivity is a key concept referring to the potential fluxes of water and sediment moving throughout a catchment. In forested catchments, these fluxes are prone to alterations caused by anthropogenic and natural disturbances. In this study, we modelled the interannual spatiotemporal evolution of hydrosedimentary connectivity influenced by forest cover change over the last four decades in the Mont‐Louis catchment, a medium snow‐dominated mountainous catchment in eastern Canada, which had 62% of its total surface affected by forest disturbances (mainly logging, but also wildfires and diseases) between 1979 and 2017. Using a geomorphometric index of connectivity (IC) and a historical forest cover database, we produced one IC map per year that considered anthropogenic and natural disturbances affecting the forest cover of the studied catchment. To account for vegetation recovery, forest disturbances were weighted with local hydrological recovery rates. Over the four decades, the mean IC of the Mont‐Louis catchment dramatically increased by 35% in response to different types of disturbances. The spatial evolution of IC over the whole catchment and at the sub‐catchment scale revealed that disturbance location has a strong influence on hydrosedimentary connectivity to the main channel. Our results also highlight the sharp contrast between IC computed from topography‐based impedance to those computed from vegetation‐based impedance. Forest disturbances appear to connect hillslopes with the hydrological network by producing pathways for sediment and water. Finally, the proposed reproducible framework could be useful for predicting the potential impact of harvesting and preventing damage to fish habitat and sensitive river reaches.
Abstract. Remotely sensed data from fluvial systems are extensively used to document historical planform changes. However, geometric and delineation errors inherently associated with these data can result in poor or even misleading interpretation of measured changes, especially rates of channel lateral migration. It is thus imperative to take into account a spatially variable (SV) error affecting the remotely sensed data. In the wake of recent key studies using this SV error as a level of detection, we introduce a new framework to evaluate the significance of measured channel migration. Going beyond linear metrics (i.e. migration vectors between diachronic river centrelines), we assess significance through a channel polygon method yielding a surficial metric (i.e. quantification of eroded, deposited, or eroded-then-deposited surfaces). Our study area is a mid-sized active wandering river: the lower Bruche, a ∼20 m wide tributary of the Rhine in eastern France. Within our four test sub-reaches, the active channel is digitised using diachronic orthophotos (1950 and 1964), and the SV error affecting the data is interpolated with an inverse-distance weighting (IDW) technique. The novelty of our approach arises from then running Monte Carlo (MC) simulations to randomly translate active channels and propagate geometric and delineation errors according to the SV error. This eventually leads to the computation of percentage of uncertainties associated with each of the measured planform changes, which allows us to evaluate the significance of the planform changes. In the lower Bruche, the uncertainty associated with the documented changes ranges from 15.8 % to 52.9 %. Our results show that (i) orthophotos are affected by a significant SV error; (ii) the latter strongly affects the uncertainty of measured changes; and (iii) the significance of changes is dependent on both the magnitude and the shape of the surficial changes. Taking the SV error into account is strongly recommended even in orthorectified aerial photos, especially in the case of mid-sized rivers (<30 m width) and/or low-amplitude river planform changes (<1 m2m-1yr-1). In addition to allowing detection of low-magnitude planform changes, our approach is also transferable as we use well-established tools (IDW and MC): this opens new perspectives in the fluvial context (e.g. multi-thread river channels) for robustly assessing surficial channel changes.
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