Development of ecosystem-based risk governance concepts with respect to natural hazards and climate impacts – from ecosystem-based solutions tointegrated risk assessment.


Forests and mountain ecosystems can play an important role in reducing natural hazards and risks in the Alpine Space, as they are able to protect against avalanches, torrents, landslides or rock-fall. However, few strategies or policy concepts have been developed on how to integrate forests and ecosystem services in risk governance. Therefore, GreenRisk4ALPs developed an ecosystem-based concept to support risk governance regarding natural hazards and climate impacts by focusing on forests as affordable and long-term risk solution. The project partners developed new tools and recommendations for practitioners and policy makers to contribute to a sustainable and safe Alpine risk management.


  • 2014 – 2020
  • Liveable
  • Enhance the protection, the conservation and the ecological connectivity of Alpine Space ecosystems
    • Group 8: To improve risk management and to better manage climate change, including major natural risks prevention
  • 04/2018
  • 08/2021
  • 2.421.337 EUR
  • 2.050.711 EUR


Federal Research and Training Centre for Forests, Natural Hazards and Landscape Austria (Lead partner)
  • Lead partner
  • Austria
  • Tirol
  • Innsbruck
    Austrian Service for Torrent and Avalanche Control
    • Austria
    • Tirol
    • Innsbruck
        Forestry company Franz Mayr-Melnhof-Saurau
        • Austria
        • Steiermark
        • Frohnleiten
            National Research Institute for Agriculture, Food and the Environment
            • France
            • Rhône-Alpes
            • Villeurbanne
                European Academy of Bozen-Bolzano – EURAC Research
                • Italy
                • Provincia Autonoma di Bolzano/Bozen
                • Bolzano
                    Safe Mountain Foundation
                    • Italy
                    • Valle d'Aosta/Vallée d'Aoste
                    • Courmayeur
                        Department of Agricultural, Forest and Food Sciences, University of Turin
                        • Italy
                        • Piemonte
                        • GRUGLIASCO
                            Slovenian Forest Service
                            • Slovenia
                            • Zahodna Slovenia
                            • Ljubljana
                                University of Ljubljana, Biotechnical Faculty, Department for Forestry and Renewable Resources
                                • Slovenia
                                • Zahodna Slovenia
                                • Ljubljana
                                    Swiss Federal Institute for Forest, Snow and Landscape Research WSL
                                    • Switzerland
                                    • Zürich
                                    • Birmensdorf
                                        University of Göttingen
                                        • Germany
                                        • Schwaben
                                        • Göttingen
                                            Bavarian State Institute of Forestry
                                            • Germany
                                            • Oberbayern
                                            • Freising
                                                • 47.268863511.3948986
                                                • 47.265713811.3974397
                                                • 47.26547220000000515.322183491438523
                                                • 45.77335734.8868454
                                                • 46.494530211.3472734
                                                • 45.78742486.9730618
                                                • 45.0680467.57762
                                                • 46.052666214.480088002780466
                                                • 46.04898975000000414.503956692895823
                                                • 47.3604432000000068.455244384036696
                                                • 51.55837579.9560718
                                                • 48.3994440511.716943743980217


                                                • Road map for a multiple actor and decision targeted information process

                                                  The GreenRisk4Alps project examines innovative forest-based solutions in support of the Alpine risk management. Risk management is related to gravitational natural hazards – snow avalanches, rock fall and landslides, and this document is about tailoring risk management solutions.
                                                  Firstly, by “Diagnosis” an individual actor is estimating the relevance of the GR4A scientific information for his own risk management or forest use. An estimation of relevance depends on (i) the specific problem the actor is dealing with, (ii) the potential allies the actor could win for implementing solution(s) in praxis and (iii) the link between praxis solution(s) and currently relevant public goals. Only in the case that the relevance is estimated as high it makes sense to go to the second step. Secondly, by “Consultation” an individual actor estimates the soundness of the scientific information while consulting researchers. Actor gets into direct contact with researchers, either through already existing channels, like meeting places, or by creating new ones. Within such integration forums the actor gets the possibility to estimate the limits of scientific results and better evaluate own science-based solution. Further on, the own solution can be fine-tuned in a close science-praxis discourse. Finally, the credibility can be checked, i.e. in how far the research was adhering to the principles of good scientific practice. Thirdly, in the preparation for the “Implementation”, the actor is checking the legal framework and the economic resources for the preferred solution. In addition, this solution has to be well embedded into democracy and good governance.

                                                • Protective forest assessment tool

                                                  The Protective Forest Assessment Tool (FAT) is a decision support tool that was created within the Interreg Alpine Space project - GreenRisk4ALPs (ASP 635). The innovative tool offers user-tailored support for practitioners involved in ecosystem-based natural hazard risk management.
                                                  FAT is an innovative decision support tool that offers user-tailored support for practitioners involved in ecosystem-based natural hazard risk management.
                                                  To get to know FAT, watch the tutorial video!
                                                  FAT’s overarching goal is to estimate the value mountain forest has for protecting buildings and infrastructure against gravitational natural hazards such as snow avalanches, rockfall and shallow landslides. This is achieved with the replacement cost method, which is comparing the protective effects of forests with the protection offered by artificial measures.
                                                  The web platform was designed for different user groups such as local and regional public authorities and other decision makers working in the field of natural hazard risk management.

                                                • Decision oriented risk assessment for natural hazards in Alpine Space

                                                  For more information on the approaches mentioned in the video please consult the project deliverables and the Forest Handbook Vol. 1 available at the link below:

                                                • Floy-Py Simulation tool

                                                  The open-source simulation tool Flow-Py was developed and applied in GreenRisk4ALPs to identify forests with a direct object protective function for snow avalanches, rockfall and shallow landslides.

                                                  Flow-Py employs a data-based run-out angle modelling approach to identify process areas and corresponding intensities of gravitational mass flows by combining models for routing and stopping, which depend on local terrain and prior movement. The only required input data are a digital elevation model, the positions of starting zones and a minimum of four model parameters. The model equations are implemented via the Python computer language allowing users to address specific questions by keeping the parameterization flexible and the ability to include custom model extensions.

                                                  The Flow-Py code and manual can be downloaded from the  Flow-Py repository.
                                                  Please cite as:  Neuhauser, M., D'Amboise, C., Teich, M., Kofler, A., Huber, A., Fromm, R., Fischer, J.-T. (2021). Flow-Py: routing and stopping of gravitational mass flows (1.0). Zenodo.
                                                  More information on model equations, implementation and validation, performance, and modularity and expandability of Flow-Py can be found in: D'Amboise, C. J. L., Neuhauser, M., Teich, M., Huber, A., Kofler, A., Perzl, F., Fromm, R., Kleemayr, K., and Fischer, J.-T. (2022). Flow-Py v1.0: A customizable, open-source simulation tool to estimate runout and intensity of gravitational mass flows. Geosci. Model Dev., 15, 2423–2439.