Spatial scan statistics in vulnerability assessment: an application to mountain hazards

In the European Alps, the concept of risk has increasingly been applied in order to reduce the susceptibility of society to mountain hazards. Risk is defined as a function of the magnitude and frequency of a hazard process times consequences; the latter being quantified by the value of elements at risk exposed and their vulnerability. Vulnerability is defined by the degree of loss to a given element at risk resulting from the impact of a natural hazard. Recent empirical studies suggested a dependency of the degree of loss on the hazard impact, and respective vulnerability (or damage-loss) functions were developed. However, until now, only little information is available on the spatial characteristics of vulnerability on a local scale; considerable ranges in the loss ratio for medium process intensities only provide a hint that there might be mutual reasons for lower or higher loss rates. In this paper, we therefore focus on the spatial dimension of vulnerability by searching for spatial clusters in the damage ratio of elements at risk exposed. By using the software SaTScan, we applied an ordinal data model and a normal data model in order to detect spatial distribution patterns of five individual torrent events in Austria. For both models, we detected some significant clusters of high damage ratios, and consequently high vulnerability. Moreover, secondary clusters of high and low values were found. Based on our results, the assumption that lower process intensities result in lower damage ratios, and therefore in lower vulnerability, and vice versa, has to be partly rejected. The spatial distribution of vulnerability is not only dependent on the process intensities but also on the overall land use pattern and the individual constructive characteristics of the buildings exposed. Generally, we suggest the use of a normal data model for test sites exceeding a minimum of 30 elements at risk exposed. As such, the study enhanced our understanding of spatial vulnerability patterns on a local scale.

[1]  D. Mileti.  Disasters by Design: A Reassessment of Natural Hazards in the United States , 1999 .

[2]  M. Keiler,et al.  Assessing physical vulnerability for multi-hazards using an indicator-based methodology , 2012 .

[3]  Susan L. Cutter,et al.  Using Building Permits to Monitor Disaster Recovery: A Spatio-Temporal Case Study of Coastal Mississippi Following Hurricane Katrina , 2010 .

[4]  Sven Fuchs,et al.  Editorial for the special issue: vulnerability to natural hazards—the challenge of integration , 2011 .

[5]  C. J. van Westen,et al.  The application of numerical debris flow modelling for the generation of physical vulnerability curves , 2011 .

[6]  Michael Bründl,et al.  The risk concept and its application in natural hazard risk management in Switzerland , 2009 .

[7]  M. Anderson,et al.  Landslide hazard and risk , 2005 .

[8]  Andreas Paul Zischg,et al.  Avalanche risk assessment – a multi-temporal approach, results from Galtür, Austria , 2006 .

[9]  Christian Scheidl,et al.  The Application of the Risk Concept to Debris Flow Hazards , 2008 .

[10]  M Edwin.  “Avalanche risk assessment a multi temporal approach, results from Galtür, Austria“, de M. Keiler, R. Sailer, P. Jörg, C. Weber, S. Fuchs, A. Zischg, and S. Sauermoser , 1970 .

[11]  S. Cutter,et al.  Temporal and spatial changes in social vulnerability to natural hazards , 2008, Proceedings of the National Academy of Sciences.

[12]  A. K. Turner,et al.  Landslides : investigation and mitigation , 1996 .

[13]  S. Chainey,et al.  Mapping Crime: Understanding Hot Spots , 2014 .

[14]  Olav Slaymaker,et al.  The distinctive attributes of debris torrents , 1988 .

[15]  S. Fuchs,et al.  Space and time: coupling dimensions in natural hazard risk management? , 2013 .

[16]  J. Hübl,et al.  Towards an empirical vulnerability function for use in debris flow risk assessment , 2007 .

[17]  W. Z. Savage,et al.  Guidelines for landslide susceptibility, hazard and risk zoning for land-use planning , 2008 .

[18]  David O'Sullivan,et al.  Geographic Information Analysis , 2002 .

[19]  Johann Stötter,et al.  Development of avalanche risk between 1950 and 2000 in the Municipality of Davos, Switzerland , 2004 .

[20]  M. Kulldorff.  A spatial scan statistic , 1997 .

[21]  T. Glade,et al.  Physical vulnerability assessment for alpine hazards: state of the art and future needs , 2011 .

[22]  Hans Kienholz,et al.  Aspects of integral risk management in practice: Considerations with respect to mountain hazards in Switzerland , 2004 .

[23]  D. Varnes.  Landslide hazard zonation: A review of principles and practice , 1984 .

[24]  M. Kulldorff,et al.  International Journal of Health Geographics Open Access a Scan Statistic for Continuous Data Based on the Normal Probability Model , 2022 .

[25]  Andreas Paul Zischg,et al.  Temporal variability of damage potential on roads as a conceptual contribution towards a short-term avalanche risk simulation , 2005 .

[26]  M. Holub,et al.  Benefits Of Local Structural Protection ToMitigate Torrent-related Hazards , 2008 .

[27]  Inkyung Jung,et al.  A spatial scan statistic for ordinal data , 2007, Statistics in medicine.

[28]  Johannes Hübl,et al.  TOWARDS A FREQUENCY-MAGNITUDE RELATIONSHIP FOR TORRENT EVENTS IN AUSTRIA , 2011 .

[29]  Andreas Paul Zischg,et al.  Modelling the system behaviour of wet snow avalanches using an expert system approach for risk management on high alpine traffic roads , 2005 .

[30]  Xilin Liu.  Site-specific vulnerability assessment for debris flows: Two case studies , 2006 .

[31]  Sven Fuchs,et al.  Susceptibility versus resilience to mountain hazards in Austria - paradigms of vulnerability revisited , 2009 .

[32]  Sven Fuchs,et al.  Variability of Natural Hazard Risk in the European Alps: Evidence from Damage Potential Exposed to Snow Avalanches , 2008 .

[33]  Sven Fuchs,et al.  Vulnerabilitätsanalyse und monetäre Schadensbewertung von Wildbachereignissen in Österreich , 2007 .

[34]  Markus Holub,et al.  Mitigating mountain hazards in Austria – legislation, risk transfer, and awareness building , 2009 .

[35]  Josef Strobl,et al.  GIS und Sicherheitsmanagement , 2005 .

[36]  Sven Fuchs,et al.  A quantitative vulnerability function for fluvial sediment transport , 2011 .

[37]  J. Knight,et al.  Climate change and geomorphological hazards in the eastern European Alps , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[38]  Edwin Butt Eckel,et al.  Landslides and engineering practice , 1958 .

[39]  J. Pinkowski.  Disaster Management Handbook , 2008 .

[40]  Sven Fuchs,et al.  Vulnerability To Torrent Processes , 2008 .

[41]  Su-Chin Chen,et al.  The efficiency of a risk reduction program for debris-flow disasters – a case study of the Songhe community in Taiwan , 2010 .

[42]  Andreas Paul Zischg,et al.  The long-term development of avalanche risk in settlements considering the temporal variability of damage potential , 2005 .

[43]  Michael Bründl,et al.  Avalanche Hazard Mitigation Strategies Assessed by Cost Effectiveness Analyses and Cost Benefit Analyses—evidence from Davos, Switzerland , 2007 .

[44]  Andreas Paul Zischg,et al.  Avalanche related damage potential - changes of persons and mobile values since the mid-twentieth century, case study Galtür , 2005 .