Michaela Teich

By Christopher James Laplante D’Amboise, Michaela Teich, Anne Hormes, Stefan Steger and Frédéric Berger

Simulation tools and their integrated models are widely used to estimate potential starting, transit and runout zones of gravitational natural hazards such as rockfall, snow avalanches and landslides (i.e., gravitational mass flows [GMFs]). Forests growing in areas susceptible to GMFs can influence their release and propagation probabilities (i.e., frequency and magnitude of an event) as well as their intensity. If and how well depends on the GMF type, the topography of the terrain and the forest’s structure. In this chapter, we introduce basic concepts of computer models and state-of-the-art methods for modeling forest interactions with rockfall, snow avalanches and landslides. Furthermore, an example of a protective forest routine embedded in the runout angle-based GMF simulation tool Flow-Py will be presented together with its parameterization for forest-GMF interactions. We applied Flow-Py and two custom extensions to model where forests protect people and assets against GMFs (the protective function) and how forests reduce their frequency, magnitude and/or intensity (the protective effect). The goal of this chapter is to describe protective forest models, so that practitioners and decision makers can better utilize them and their results as decision support tools for risk-based protective forest and ecosystem-based integrated risk management of natural hazards.

Part of the book: Protective Forests as Ecosystem-based Solution for Disaster Risk Reduction (Eco-DRR)

By Michaela Teich, Cristian Accastello, Frank Perzl and Frédéric Berger

Mountain forests are an efficient Forest-based Solution (FbS) for Ecosystem-based Disaster Risk Reduction (Eco-DRR) by lowering the frequency, magnitude, and/or intensity of natural hazards. Technical protection measures are often poor solutions as stand-alone measures to reduce disaster risk limited by material wear and fatigue or financial resources and aesthetical values. Protective forests should therefore be considered as key elements in integrated risk management strategies. However, the definition of protective forests and the understanding and assessment of their protective functions and effects differ greatly among Alpine Space countries. In this chapter, we present a short introduction to the concept of Eco-DRR and companion terms and propose a definition of FbS as a specific case of Nature-based Solutions for an ecosystem-based and integrated risk management of natural hazards. That is, we guide the reader through the maze of existing definitions and concepts and try to disentangle their meanings. Furthermore, we present an introduction to forest regulations in the Alpine Space and European protective forest management guidelines. Our considerations and recommendations can help strengthen the role of protective forests as FbS in Eco-DRR and the acknowledgment of the key protective function they have and the crucial protective effects they provide in mountain areas.

Part of the book: Protective Forests as Ecosystem-based Solution for Disaster Risk Reduction (Eco-DRR)

By Cristian Accastello, Francesca Poratelli, Kathrin Renner, Silvia Cocuccioni, Christopher James Laplante D’Amboise and Michaela Teich

Protective forests are an effective Forest-based Solution (FbS) for Ecosystem-based Disaster Risk Reduction (Eco-DRR) and are part of an integrated risk management (IRM) of natural hazards. However, their utilization requires addressing conflicting interests as well as considering relevant spatial and temporal scales. Decision support systems (DSS) can improve the quality of such complex decision-making processes regarding the most suitable and accepted combinations of risk mitigation measures. We introduce four easy-to-apply DSS to foster an ecosystem-based and integrated management of natural hazard risks as well as to increase the acceptance of protective forests as FbS for Eco-DRR: (1) the Flow-Py simulation tool for gravitational mass flows that can be used to model forests with protective functions and to estimate their potential for reducing natural hazards’ energy, (2) an exposure assessment model chain for quantifying forests’ relevance for reducing natural hazard risks, (3) the Rapid Risk management Appraisal (RRA), a participatory method aiming to identify IRM strengths and points for improvement, and (4) the Protective Forest Assessment Tool (FAT), an online DSS for comparing different mitigation measures. These are only a few examples covering various aims and spatial and temporal scales. Science and practice need to collaborate to provide applied DSS for an IRM of natural hazards.

Part of the book: Protective Forests as Ecosystem-based Solution for Disaster Risk Reduction (Eco-DRR)