Switzerland: Forest Fire Research in the Swiss National Park (IFFN No. 16)

Forest Fire Research in the Swiss National Park:
An Overview

(IFFN No. 16 – January 1997, p. 6-9)


In the Swiss national park (Engadine Valley) nature and its processes are completely protected from human activity; visitors must remain on official hiking trails (Federal national park law 1980 [Eigenössisches Nationalparkgesetz]). As forest fires may be caused by natural events (e.g. lightning ) and be part of the forest ecosystem they are not necessarily extinguished but treated according to park law wherever possible. However, the Swiss national park is small (170 km2), situated close to human settlements, and liable damage to third parties may be caused (park regulation of the canton of Grison 1983 [Kantonale Parkordnung]). In order to fulfill obligations park authorities need fire management strategies which take this particular legal situation into account and focus on the needs of protected areas. Tools for decision making must be available to allow individual treatment of each wildfire situation and to provide for ecological as well as economical aspects.

As forest fires are spatial processes Geographical Information Systems (GIS) are applied as tools to achieve an operational forest fire management system. The Division of Spatial Data Handling (University of Zurich) which is also responsible for the GIS of the Swiss national park, works on the following topics: (1) Implementation of fire spread modeling into GIS (Schöning 1996), (2) Development of fuel models for Switzerland and introduction to spread modeling (Harvey 1996), (3) Forest fire management (Rüegsegger 1996) with special emphasis on protected areas, including risk analysis and damage potential (Schöning 1996).

Forest Fire Modeling 

The basis for the fire behaviour modeling is the Rothermel model for the behaviour of surface fires (Rothermel 1972). It calculates for any given point local intensity and spread parameters for the head of a surface fire. Inputs for the model are a two-dimensional wind field, terrain parameters (digital elevation model), fuel moisture and a detailed description of the fuel bed. Based on the local behaviour output by the Rothermel model and on a model for the local shape of fire spread (Anderson 1983), the spread from a set of source locations can be simulated. The influence of barriers (streets, rivers, fuel breaks, etc.) is addressed with a probabilistic model based on the width of the barrier and the flame length. The spread simulation also allows the calculation of flame length on the entire fire perimeter, which in turn is an important index for the success of various types of fire suppression activities (Rothermel 1983). Once all the required data is available for the Swiss national park, the model can be used to evaluate different climatic and management scenarios. The fire spread model is implemented in SPARKS (Schöning 1996), a prototype fire behaviour modelling application. It is fully integrated with a commercial Geographical Information System (ARC/INFO), built on its raster modeling and applications development functionalities (Fig.1 and 2).

click to enlarge (337 KB)

Fig.1. Simulation of a forest fire in the Ofenpass area
(Swiss national park), looking north from Munt la Schera.
Slate grey = burned area, dark grey = fire front

click to enlarge (248 KB)

Fig.2. Part of the user interface of SPARKS

In order to estimate the uncertainty introduced in the model results due to uncertain inputs, sensitivity and error analysis, the Monte-Carlo simulation was also implemented into SPARKS. This allows the examination – in tabular form or graphically – of the relative importance of each input parameter for a selected output. Also, the uncertainty in the calculated fire behaviour can be calculated for interactively selected points, based on estimated uncertainties of the input parameters.

Fuel models for Switzerland 

As there are no fuel models available for Switzerland investigations were made in the canton of Ticino and the Swiss national park. Both areas represent potential wildfire sites in Switzerland: The forests of Ticino are dominated by chestnut (Castanea sativa) and are particularly sensitive to wildfires during winter (particularly February and March) when little precipitation occurs and when the chestnut leaves form a homogeneous fuel bed. The Engadine Valley, with the Swiss national park in it’s middle is representative for the dry inner alpine valleys covered mainly by pine needle forests and little precipitation (600 – 900 mm per year). In order to keep human impact low, the methods for fuel estimation were developed outside of the Swiss national park. Together with the Sottostazione Sud delle Alpi (Bellinzona, Switzerland) of the Swiss Federal Institute for Forest, Snow and Landscape Research (Birmensdorf, Switzerland) Harvey (1996) adapted the methods of the US Forest Service to the forests of the southern Alps. Three fuel models were derived: Chestnut (Castanea sativa), frequently burned areas (various fern [Polypodium] and broom [Genista] species) and (cultivated) conifer forests. During summer 1996 intensive field studies were carried out in the Swiss national park to obtain typical fuel models for the alpine conifer forests. Due to the general shape of the trees a special branch index was introduced to estimate the potential for vertical fire spread and thus the potential of a crown fire (Harvey and Allgöwer, in prep.).

Forest Fire Management (Risk Analysis and Damage Potential)

Through the integration of fire behaviour models with GIS models, new understanding of the fire danger situation in a management area can be gained. As an important factor of a risk analysis the damage potential that arises from fires starting at a certain point in the landscape can be estimated. Damage potential clearly depends on the proximity of the starting point to sensitive objects and areas such as buildings, railway lines, fire-sensitive ecosystems, etc. Proximity is a concept which is used in a great many GIS-related models. However, in the mentioned example proximity can not be modeled as a straight-line distance, but must take into account the behaviour of the fire spreading over the landscape. In this approach, the spread simulation is used to calculate the time it takes a fire starting from any point in the landscape to reach an object, under given environmental conditions. This is accomplished by inverting the spread simulation, working from a reached object backwards to all possible sources. The delay times from any given point to all objects can then be input to a potential model, used in the GIS realm for assessing accessibility. The model weighs the influence of any reached object on the point’s damage potential based on the delay time and the damage susceptibility of the object. The index for fire damage potential arising from the point is then obtained by simply adding the weighted influences of all objects. This index could be further combined with fire occurrence estimations, probability for early detection, accessibility etc. to give a more complete image of the fire danger situation.


Anderson, H. E. 1983. Predicting wind-driven wild land fire size and shape. Research Paper INT-305. Ogden, UT: US Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station

Harvey, S. 1996. Brandgutdaten in der Waldbrandmodellierung. Diplomarbeit. Universität Zürich, Abt. für Geographische Informationsverarbeitung / Kartographie <Fuel data in forest fire modeling (in Switzerland). Master’s thesis. Department of Geography University of Zurich, Division of Spatial Data Handling>

Harvey, S., and B. Allgöwer. Fuel models for the Swiss National Park (in prep.)

Nationalparkgesetz 1980. Bundesgesetz über den Schweizerischen Nationalpark im Kanton Graubünden (Nationalparkgesetz) vom 19. Dezember 1980

Nationalparkordnung 1983. Kantonale Verordnung über den Schutz des Schweizerischen Nationalparks vom 23. Februar 1983

Rothermel, R. C. 1972. A mathematical model for predicting fire spread in wildland fuels. Research Paper INT-115. Ogden, UT: US Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station

Rothermel, R. C. 1983. How to predict the spread and intensity of forest and range fires. General Technical Report INT-143. Ogden, UT: US Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment

Rüegsegger, M. 1996. Waldbrandmanagement mit GIS. Strategien und ausgewählte Beispiele. Diplomarbeit. Universität Zürich, Abt. für Geographische Informationsverarbeitung / Kartographie <Forest fire management with GIS. Strategies and examples. Master’s thesis. Department of Geography University of Zurich, Division of Spatial Data Handling>.

Schöning, R. 1996. Modellierung der potentiellen Waldbrandausbreitung. Diplomarbeit. Universität Zürich, Abt. für Geographische Informationsverarbeitung / Kartographie <Modeling of potential forest fire spread with GIS. Master’s thesis. Department of Geography University of Zurich, Division of Spatial Data Handling>.

From: Britta Allgöwer, Andreas Bachmann, Stephan Harvey, Marianne Rüegsegger, and Reto Schöning

Department of Geography, Division of Spatial Data Handling
Winterthurerstrasse 190
CH – 8057 Zurich
e-mail: britta@geo.unizh.ch, bachmann@geo.unizh.ch, reto@geo.unizh.ch

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