Modeling Protective Forests for Gravitational Natural Hazards and How It Relates to Risk-Based Decision Support Tools

Abstract

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 forests’ 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.

Risk-Based Decision Support for Protective Forest and Natural Hazard Management

“…1. the Flow-Py simulation tool for gravitational mass flows (GMF; [30,31]) can be used to model forests with a direct object protective function and to estimate their potential for reducing natural hazards' energy (see also chapter [10] of this book),…”

“…For example, Xu et al [9] developed a geospatial web platform that considers combined risks of multiple water-related hazards using serious gaming techniques to involve a variety of decision-makers and to foster a holistic and collaborative planning process. Like natural hazard models (see chapter [10] of this book), the features and characteristics of risk models vary widely. For example, operating at different scales requires to adopt different approaches for data collection and model complexity as well as influences the representation and precision of the results, which determines the applicability and effectiveness of a tool itself.…”

“…In this and two other chapters of this book [10,27], we introduce four easy-toapply DSS that were developed in the frame of the Interreg Alpine Space project GreenRisk4ALPs [28] to support and foster ecosystem-based and integrated…”

Geodata Requirements for Mapping Protective Functions and Effects of Forests

“…Note that there is a different meaning of the wordings "object protective function of forest," since this may also refer to other current land use than forest, and "forest with an object protective function. " To identify areas with an object protective function of forest hazard starting, transit and runout zones (hazard potential) that are associated with endangering assets (damage potential) are overlayed with the current forest use as well as with the areas suitable for future forest use (growth) (see also chapter [9] of this book). Current forest use land with an object protective and/or a site (soil) protective function (see also chapters [1,12] of this book) is legally classified as Geodata Requirements for Mapping Protective Functions and Effects of Forests DOI: http://dx.doi.org/10.5772/intechopen.99508 protective forest and protected from deforestation in the Alpine Space if the additional legal requirements dependent on national law are met (see [34]).…”

“…The "damage potential" describes the probability and the relevance of damages to assets like infrastructures due to their exposure and vulnerability -the other two components of risk (see chapter [2] of this book). However, approaches of forest function mapping (e.g., [3][4][5][6][7][8] and see also book chapters [9][10][11]) often simplify the hazard intensity as well as the damage potential since they are difficult to assess reliably on a regional scale [5].…”