Spatial Data for Risk Management in Alpine Regions Helmut FUCHS and Reinfried MANSBERGER Institute of Surveying, Remote Sensing and Land Information Universität für Bodenkultur Wien A-1140 Peter Jordan-Strasse 82 helmut.fuchs@boku.ac.at mansberger@boku.ac.at Abstract. Austria is a tourism country within the Alps. The winter tourism as well as the summer tourism is increasing. Especially in the skiing resorts living space is limited and protection facilities against natural risks must be built to develop new building areas and recreation areas. Additionally the knowledge about potential natural disasters is required: Avalanches, landslides and floods must be predicted exactly in time and effects, whereas changing parameters (e.g. weather conditions, snow coverage, condition of vegetation) must be considered in a continuous process. Natural data used for modelling of disaster processes will be presented. But planning measures for disaster prevention and the disasters themselves make an impact to ownership rights. So the measures of risk management require amongst provisions of law also legal information about land. Databases describing the legal relations of land will be introduced in the paper. Three examples of dynamic processes for natural risk processes all developed at the Universität für Bodenkultur Wien - will be given in an overview: Runoff Simulation (HYDR 2 AC) with information about runoff amount in every point of the watershed area. Sediment transport (SEDTR 2 AC) considering also varying properties within the whole river network. (e.g. diverse segments of the river with different slopes) Avalanche Simulation (ELBA-SIM) based on a two dimensional Voellmy type model with variable flow parameters. Finally possibilities of a dynamic risk management are outlined. The inputs for this new kind of risk management are the results of simulated risk processes merged with legal databases. 1. Introduction The living area in Austria is restricted and endangered by approximately 9000 torrents and 5800 avalanches. 1023 of avalanches are potentially affecting settled areas, 141 are potentially affecting railroads and finally 1840 avalanches are potentially affecting road network. Therefore, recognition, registration and assessment of riskpotentials in alpine areas are important precaution tasks to protect human people as well as infrastructure from being damaged by avalanches, landslides and floods.
For an effective risk management many different data and parameters have to be collected and have to be considered to predict the dimensions of natural disasters or to enable the construction of protection facilities against avalanches, floods and landslides. GeoInformationSystems (GIS) will be used for the storage, analysis, post processing and finally for the visualisation of parameters, data and results of analysis. So GIS has a central role in risk-management. In most of alpine areas a conflict-situation arose within the last decades: On the one hand life of people is based on the use of natural resources and living space, on the other hand affluent society and almost unlimited mobility of people results in an increased use of - so long - remote and isolated areas. To meet the demands of tourism new building areas and recreation areas must be developed. The prevention of these areas from natural disasters lies in the responsibility of spatial planners and politicians. An objective, quantitative and comprehensible calculation of natural risks is absolute necessary. Most of the planning tools for natural risks - like danger area maps, land use zoning or spatial planning - are based on a static concept. But natural risks are dynamic processes occurring within hours (floods) or even seconds (avalanches). The activating of disasters depends strongly on a lot of natural or environmental parameters, like weather conditions or the condition of forests. Of course these parameters are time variant. The conclusion to be drawn from these considerations lies in the necessity to treat risk in a dynamic way. And the representation of dynamic risk processes also must have an impact to relevant legal databases. 2. Planning Fundamentals for Alpine Regions in Austria In general good planning requires experts and good decision-making fundamentals. High quality data are the basic for good decision-making fundamentals. As mentioned above the assessment of natural risks has to consider the dynamic processes of disasters and also the dynamic changes of nature and environment. Potential impacts of floods, avalanches and landslides are dependent on the changing parameters and the potential impacts can be predicted using suitable modelling techniques and algorithms simulate the processes. The approach of simulations to reality is dependent on a proper model and once again on high quality data describing the real world in the model. In Austria a lot of different analogue and digital data sets are available for planning purposes. Risk Management forces two different kinds of data: Different types of natural parameters are needed for the application of modelling techniques to simulate disasters to evaluate potential risks in the alpine areas. Legal based data are necessary to establish the relation of nature and environment to land owners or ownership rights, but also to restrict the rights for land regulation purposes. 2.1 Natural Data The most efficient methods to collect natural data are techniques of digital photogrammetry and remote sensing. Semi-automatic and automatic measurement using classification, segmentation and matching algorithms allow a quick assessment of topographic and of land cover data. But in spite of the high standard of images and collection software additional expensive and time-consuming fieldwork is indispensable. Data collection has to follow certain important criteria as: Objectivity Comprehensive acquisition process Evidential value
Spatially distributed Comparability of results Dynamically based. Fig. 1: Example of a DTM with breaklines One of the most important data-types is the Digital Terrain Model (DTM, see Fig.1). It is useful for the calculation of slopes, gradients, etc. For simulation and modelling techniques the accuracy and resolution has to be excellent. Usually a grid with one to five, and a mean square error of 0.1 m to 0.5 m accuracy is desired. Breaklines should be available. The reason for the strict requirements is the need of knowledge about the distinctive oblong form of watershed areas or about the spreading area of an avalanche (Fig. 2). Fig.2: Photogrammetric interpretation of spreading areas of an avalanche
The DTM also serves as fundamental data input for another important data set - the digital orthophoto. Digital orthophotos (Fig.3 and Fig.4) are mostly used as visualisation tools, such as background information within maps, or they are draped together over a DTM to receive photorealistic views. Finally orthophotos will be uses as basic information of animation videos. Fig.3: Orthophotomosaic Paznauntal (CIR) Fig.4: Orthophoto Paznauntal (Colour) Other types of data are mostly vector-based, like the documented spreading-area of avalanches or the deposition of sediment in a watershed area. In most cases a comparison of time-series must be done, as data collection for natural hazards requires besides the geometry information a very high interpretation part. Digital photogrammetry and - hopefully in future - high-resolution satellite imagery provide a powerful tool for this kind of data collection. Fig.5: Different types of natural data (soil hydro geology vegetation)
The predominant portions of data in risk-assessment are natural parameters (Fig.5). In case of simulating risk processes these data types strongly depend on the assumed physical or statistical model for the process. As an example, some of the most important parameters for a spatial distributed runoff-simulation are listed: Soil data, such as conductivity and pore volume. Hydro geological properties. Vegetation, like interception, capacity, albedo, root intensity. Weather conditions, like temperature, air moisture content. 2.2 Legal based data In Austria relevant legal based data are countrywide available and have public access. Some of the datasets are stored in a digital format and can be requested via Internet. Four different public datasets are helpful tools for the risk management: The Real Estate Data Base, the Digital Cadastral Map, Zoning Maps and Danger Area Maps. The Austrian Real Estate Data Base (GDB) contains information about the approximately 12 million parcels such as ownership, servitudes, mortgages, size and land use. Land Register Offices (Federal Ministry of Justice) maintain the data concerning ownership rights and the Regional Surveying Offices of the Federal Office of Surveying and Metrology (Federal Ministry of Transport, Innovation and Technology) are responsible for the maintenance of parcel properties. The Cadastral Maps represent the parcels in a graphical format (Fig 6). Within the next months the Federals Office of Surveying will finish the digitations of all analogue Cadastral Maps. During the process of the analogue to digital conversion all the maps have also been transformed to a common map projection (Gauss- Krüger). The new product, the Digital Cadastral Map (DKM), is linked to the Real Estate Data Base by the parcel number. Fig.6: Digital Cadastral Map (Extract); Source: Federal Office of Surveying and Metrology (BEV) The dedication of a specific parcel is pointed out in the Zoning Map (Fig 7). The Zoning Map is based on cadastral maps and has two different functions: Regulation function: Each dedication is related with different ownership-rights (e.g. the dedication Greenland implicates a building ban for the parcel).
Development function: Each dedication shows the potential use of parcels that must not be identically with the actual use (e.g. a parcel dedicated as Building Area is used as agricultural land at the moment). The preparation of Zoning Plans started some decades ago and lies in the responsibility of regional governments. Almost at the same time a further instrument for spatial planning was established to prevent the enlargement of settlement to risk areas. The Danger Area Plan (Fig.8) shows graphically various stages of endangerments for region visualised by polygons with different colours (red yellow blue violet brown). The different zones are related to the probabilities of disaster impact and/or kinds of risks. Parcels within the red zone the zone with the highest degree of potential damage by avalanches, floods, torrents or landslides - are not useable for settlements or traffic ways. Fig.7: Zoning Map (Extract) Source: City of Vienna (MA14) Fig.8: Danger Zone Map (Extract) Source: Homepage des Vereins der Diplomingenieure in der Wildbachund Lawinenverbauung 3. Simulation of natural risk processes 3.1 Runoff Simulation HYDR 2 AC Many existing runoff simulations only use data in the hydrological network and therefore only deliver so called - lumped results. That means at some points of the network the runoff values are available (e.g. at the point of receiving water). Better simulation programs work spatially distributed and this programs deliver the amount of runoff in every point of the watershed area (Fig 9).
Fig.9: Result of a runoff simulation step 3.2 Sedimenttransport SEDTR 2 AC The result of runoff simulation serves as input for a sediment transportation model. The simulation of sediment transport gives planners a better possibility to dimension the protection buildings. In alpine watershed areas one problem is the diverse segments of the river network including different slopes and properties. Not every physical model approach fits to every type of river segment. SEDTR 2 AC uses for every significant river segment the best fitting model approach and is optimised for alpine watershed areas. Fig.10: Amount of sediment in a series of different river segments
3.3 Avalanche simulation, ELBA-SIM The basic concepts of ELBA-SIM is a 2D Voellmy type avalanche model with variable flow parameters (Volk&Kleemayr,2000). The concept of Voellmy is one of the most widely applied models in avalanche runout calculation. Based on hydraulic theory the shear forces are consisting of two components, of which µ is a dry Coulomb-type sliding friction and ξ a parameter defining the velocity dependent dynamic drag. The simulation program is fully integrated in a GIS-environment and allows the runout calculation with respect to different weather conditions, snow heights, etc. in a very short time. Fig.11: Area covered by avalanche after 18 seconds from start Fig.12: Simulation results for different preconditions
4. Applications of dynamic disaster processes in risk management The simulation of risk processes opens new potentials in risk management. Some of the possibilities will be outlined in a short way. In general the public authorities cover the costs for the implementation of protection facilities against natural risks. In a mountainous country like Austria the demand on risk protection is much higher than the available financial means. So the authorities (in Austria the Federal Ministry of Environment, Agriculture and Forestry) have to decide about the specific projects. Due to the lack of knowledge about the potential of the disaster impacts in the past most of protection facilities were built in an oversized way. Now the modelling of risk processes can simulate the consequences for different stages of the disasters, including the maximum credible accident (MCA). As the projected protection facilities will be considered in the dynamic models, the building sites and dimensions of the specific prevention elements can be (cost) optimised in an interactive virtual process. So more projects can be financed. During the planning phase for protection facilities the risk process also can be merged with the data of cadastre and land register to evaluate the decrease of risk for relevant parcels. As the improvement of protection of parcels is related also to an increase of the parcel value, the owners of involved parcels can be forced to contribute to the building costs directly or by taxation. As said before the maximum credible disaster of dynamic risk processes can be simulated. As input for the modelling of this event the most unfavourable natural parameters will be assumed. Protection facilities in risk management are fitted to the statistical probability of occurrence and extent of a disaster. E.g. for avalanche barricades the planning activities are based on the so-called 150-year event the maximal disaster recorded in a time period of 150 years. In this case the simulation is calculated for the most unfavourable parameters that could appear within a time spread of 150 years. Besides the knowledge about the maximum credible disaster within a time period, information about the actual potential of natural risks is needed. In this case the actual natural and environmental condition - described by data - are considered and processed in the simulation model. Or it also can be seen as the maximum credible disaster within a very short period. Until yet long-term considerations of potential risk reflect in permanent restrictions to the use of land documented in the Zoning plans. The areas of danger are recorded in Danger Zone Plans. Zoning plans and Danger Zone plans are available at municipalities. The actual or short-period potential of risk can lead to temporal restrictions of land use. Warning and information signs directly at specific sites will do the information of public. By means of the presented simulation methods the areas of endangerment in can be calculated and visualised also for short-term risk management. The Dynamic Danger Plans will point out the degree of danger for each parcel. Merging this information with the Real Estate Data Base the landowners can be determined and finally the owner can be warned automatically about an existing risk. 5. Summary and Outlook Different data sets as fundamental tools for risk management and the simulation of three different dynamic risks processes were introduced in the paper. The quality of simulation increases with the quality of data and with the quality of the used models for the disaster process. In Austria most of the avalanches, landslides and floods are documented in detail and the collected data are analysed. So each disaster helps to improve the models and algorithms for simulation. So in 1999 many data
could be selected: In this year the frequency of avalanches was very high. Most of them were harmless, but one of them destroyed a part of a Tyrolean village (Galtür) and killed more than 30 people. In Austria commission appointed by municipalities have to decide continuously about the permission of access to areas that are endangered by avalanches. And they are always in a conflict situation: If they close regions for entry or roads to pass and no avalanche occurrence will happen, people will complain about needless restrictions. And people also will complain, if they do not prohibit the entry and an avalanche destroys human facilities or even kills human beings. Available natural data and better knowledge of avalanche processes stepwise improve the decision-making and exculpate the so called avalanche commissions from responsibility. The presented dynamic danger zone plans need direct access: People want to request the situation of danger immediately. A possible scenario: A person wants to know, if it is possible to downhill a beautiful hill covered with powder snow. With internet-technology and the new generation mobile phones (based on GPRS and equipped with GPS) the communication tools between a central data bases and remote users are available by now. The exact positioning of the person can be done by GPS- and INS- technology. The missing link at the moment is the detailed and online maintained information about the degree of danger. But until the realization of this scenario a lot of snow will fall upon the Austrian Alps. 6. References Fuchs H. & Pitterle A., 1999. GIS als Werkzeug im Risikomanagement alpiner Bereiche, Österreichische Zeitschrift für Vermessung und Geoinformation, Heft 2 und 3/1999. Magel H., 1999. Vermessungswesen vor neuen Herausforderungen Chancen für den Freien Beruf? Zeitschrift für Vermessungswesen, 124.Jahrgang, Heft 4/1999, pp 105-111. Verlag Konrad Wittwer GmbH. Stuttgart. Mansberger R. & Muggenhuber G., 1999. Spatial Data Bases as Tools for Land Use and Development. FIG Commission 3 Annual Meeting and Seminar. Budapest, Hungary, 21-23 October, 1999. http://fig3.boku.ac.at/am1999/mansberger.pdf Stolitzka G. & Mansberger R., 1999. Public and legally-binding data bases for the protection of natural resources. In Land Reform and Sustainable Development. Edited by Robert W. Dixon-Gough. International Land Management Series. Chapter 7. pp.69-76. Ashgate. Aldershot. Volk G. & Kleemayr K., 2000. 2-Dimensional Avalanche Modelling, Applying a Variable Parameter Voellmytype Avalanche Model. In FIEBIGER, G. (ed.) 2000: Proceedings of the International Workshop on Hazard Mapping in Avalanching Areas 2nd to 7th April 2000, St. Christoph am Arlberg. Young A., 1998. Land Ressources now and for the future. Cambridge University Press. Cambridge. Address of Authors: Ao.Univ.Prof. Dr. Helmut FUCHS Ass.Prof. Dr. Reinfried MANSBERGER A-1190 Wien, Peter-Jordan-Straße 82; A-1190 Wien, Peter-Jordan-Straße 82; Tel.: +43-1-47654-5130, Tel.: +43-1-47654-5115 Fax: +43-1-47654-5142 Fax: +43-1-47654-5142 E-mail: helmut.fuchs@boku.ac.at E-mail: mansberger@boku.ac.at