Author(s): Ana Adeva Bustos; Carole Rozier; Aurelie Gosset; Hans-Petter Fjeldstad; Knut Alfredsen
Linked Author(s): Ana Adeva-Bustos, Knut Alfredsen
Keywords: No Keywords
Abstract: Despite that hydromorphological restoration projects have been implemented since the 1940s, they key to improve the effectiveness of future restoration measures remains a challenge. This is in part related to the lack of adequate aims and objectives together with our limitations to understand the effects on the physical habitat and ecosystems from interventions. This study shows the potential of using remote sensing techniques to evaluate the success of mitigation measures using habitat suitability as a quantifiable objective. Airborne Light Detection and Ranging (LiDAR) was used to build a high resolution two-dimensional model for Ljungan River, Sweden, using HEC-RAS 5.0. 3. Two type of instream mitigation measures were simulated according to the actual actions carried out in the river: a) widening the main channel and removing current deflectors and b) opening a side channel. Both, the type of intervention and which reaches to improve were planned by the stakeholders group based on their potential of improvement for salmonid habitat. Preliminary results in one of the reaches under a discharge of 100 m /s depict changes after the mitigation measures in water surface extent, velocity and depth that match the expectations for which it was designed. Results will be contrasted against measurement data as water surface elevation and a georeferenced model from aerial pictures captured using an unmanned aerial system (UAS). Results from the hydraulic model in combination with fuzzy rules based on preference habitats will be used to calculate the amount of suitability habitat created after the instream modifications. The resulting suitability habitat will be used to calculate the Cost per Unit of Suitable Habitat (CUSH). Such a method could help to prioritize actions using evidence based mitigation measures instead of trial error methods and reduce uncertainty during the decision making process.
Year: 2018