Criteria for identification of areas at risk of landslides in Europe: the Tier 1 approach

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Criteria for identification of areas at risk of landslides in Europe: the Tier 1 approach Andreas Günther 1, Paola Reichenbach 2, Fausto Guzzetti 2, Andreas Richter 1 1 Bundesanstalt für Geowissenschaften und Rohstoffe (BGR) Section B 2.7 (Geohazards, GIS applications) Stilleweg 2, 30655 Hannover, Germany a.guenther@bgr.de 2 Consiglio Nazionale delle Ricerche Istituto di Ricerca per la Protezione Idrogeologica via della Madonna Alta 126, 06128 Perugia, Italy paola.reichenbach@irpi.cnr.it, fausto.guzzetti@irpi.cnr.it ESPON Disclaimer: Texts and maps stemming from research projects under the ESPON programme presented in this report does not necessarily reflect the opinion of the ESPON Monitoring Committee

Content 1. Landslide hazard and risk 2. Landslide susceptibility assessment 3. Tiers and common criteria formulated by SIWG 4. Existing European landslide hazard evaluation 5. Proposed requirements for Tier 1 analysis 6. Case example for Tier 1 analysis: Germany 7. Conclusion 8. Some questions on Tier 1

Landslide hazard and risk Landslide Hazard H L = P (A L ) P (N L ) S P (A L ): Probability of landslide size, a proxy for magnitude P (N L ): Probability of temporal occurrence of a landslide S: Landslide susceptibility probability / possibility of spatial occurrence Specific landslide Risk R s = H L V L V L : the degree of loss to an element at risk (E) resulting from the occurrence of a landslide of given magnitude (Varnes and IAEG commission on landslides, 1984). E for common soil threat: the soil itself E landslide threat: All vulnerable elements exposed to landslide hazard (including soil) Risk driver for common soil threat: Environmental / human induced factors Risk driver landslide threat: mobilized slope mass material (including soil)

Landslide susceptibility assessments Methodological overview Method Direct Indirect Qualitative Quantitative Geomorphologic mapping Heuristic analysis (Index-based) Analysis of inventories Statistical modeling Process based modeling (Guzzetti, 2006)

Landslide susceptibility assessments Applied techniques for nation-wide assessments Method Requirements Benefit Deficit Heuristic analysis Thematic data on factors controlling terrain stability High benefitcost ratio Subjective, uncertain Analysis of Inventories Landslide inventory maps Comparable, quantitative Limited measure on susceptibility Statistical modelling Inventories, thematic data Objective, quantitative Empirical, complex

Tiers and common criteria formulated by SIWG Tiers in risk area identification Tier Description Characteristics Tier 1 Risk area identification -Data must be available -Low spatial resolution (1:1 Mil.) -Qualitative approach, or Model approach combined with thresholds Tier 2 Measures/implementation plans within the risk zones -Higher spatial resolution -Any approach (or combinations) -Enhanced data need to allow model application (Eckelmann et al., 2006)

Tiers and common criteria formulated by SIWG Common criteria for landslides Common criteria occurrence/density of existing landslides Bedrock soil properties Slope land cover/land use Climate Data source/type of information statistics nature of material + presence of fissures and pores texture, structure, permeability classes: 0-10 ; 10-30 ; >30 infrastructure; cultivation density/pressure, mining likelihood of heavy rainfall events NUTS III Map of Geology 1:1,000,000 not required for in Tier 1 250m Data Quality /Resolution Tier 1 Tier 2 Non relevant for Tier 1 daily events (e.g. < 10, 10-70, >70 mm/day) larger-scale regional/local assessments higher resolution maps classification/grouping according to? same or higher 100m same or higher seismic risk threshold? threshold? (Eckelmann et al., 2006)

Existing European landslide hazard evaluation Source: EPSON (European Spatial Planning Observation Network) project http://www.gtk.fi/projects/espon/landslides.htm

Proposed requirements for Tier 1 analysis Indispensable data Criteria Data source Type of information Resolution Soil / bedrock European soil / geological databases Material properties (composition, thicknesses, discontinuities, ) 1:1 Mill. Topography NASA SRTM DEM 1st order topographic attributes (slope, ) 90 m Additional data Criteria Data source Type of information Resolution Topography NASA SRTM DEM 2nd order topographic attributes (wetness indices, ) 90 m Land use / land cover CORINE Infrastructure, cultivation, population density, 100 m Climate MARS Precipitation sums 50 km Seismicity European earthquake Isoseismals?? 50 km catalogue

Case example for Tier 1 analysis: Germany Data situation ¾ No national-level landslide inventory map with associated database available ¾ Data on landslides are mandatory at the state geological surveys ¾ Discussion on possible data harmonization and structuring on federal level had begun ¾ High-quality nation-wide data on soil / bedrock material properties is available none in some regions regional, state-level under development ¾ High-quality nation-wide data on topography is available A nation-wide landslide susceptibility assessment for Germany can up to now only be conducted using heuristic classifications of ground conditional properties Landslide information on the state level

Case example for Tier 1 analysis: Germany Used thematic data Ground material conditions from German Soil database 1: 1 Mill. 72 Nation-wide soil/bedrock associations ranked into 6 landslide susceptibility classes using: Type of soil/ parental material Degree of weathering Soil / regolith thicknesses Permeability contrasts Presence of discontinuities Digital Elevation Model Topographic slope derived from DGM 50 dataset (resolution: 50 m) Ranked into 6 slope classes

Case example for Tier 1 analysis: Germany Map preparation Weighted average map overlay (50 % each map) + = Susceptibility none very low low moderate high very high Slope classes < 5 5-10 10-20 20-30 30-40 > 40 Nation-wide soil / bedrock associations qualitatively classified to landslide susceptibility Classified topographic slope map from DGM 50 data

Case example for Tier 1 analysis: Germany Landslide studies in Germany Area % of susceptibility very low (30%) none (44%) Landslide susceptibility none very low low moderate high very high low (22%) high, very high (1%) moderate (3%) To be evaluated! Jasmund peninsula: Inventory, susceptibility Southern Lower Saxony: Some inventory Part of upper Harz Mountains: Inventory, susceptibility Part of Hessen / Thüringen: Some inventory Bonn region: Inventory, susceptibility Part of Elbsandsteingebirge: Inventory Part of upper Werra valley: Inventory, susceptibility Rheinhessen area: Inventory, susceptibility Part of Fränkische Alb: Inventory Part of Schwäbische Alb Inventory, susceptibility Bayrische Alpen: Inventory

Case example for Tier 1 analysis: Germany NUTS 3 level analysis Landslide hazard low high Susceptibility Susceptibility none very nonelow low moderate enhanced high very high very high ESPON, 2006. All rights reserved ESPON NUTS 3 landslide hazard evaluation Reclassified NUTS 3 NUTS maximum 3 median of of landslide susceptibility susceptibility classes EuroGeographics Association 2001 for the administrative boundaries

Conclusions On Tier 1, the landslide threat might be best assessed with landslide susceptibility evaluations European-level Tier 1 landslide susceptibility assessments must be conducted without distributed landslide information Only heuristic susceptibility zonings are feasible at the moment and the required pan-european data is available Implementation of adequate rule-based data exploration schemes could possibly enhance speculative zonings European-scale heuristic zonings can at least delineate areas not relevant for inventory-based Tier 2 assessments In any case, Tier 1 assessments must be evaluated / validated with representative landslide data

Some questions on Tier 1 Can we agree what available pan-european data should be used for heuristic Tier 1 zonings and how? Can we establish European-level ranking / scoring schemes for Tier 1 susceptibility zonings? Can we define an appropriate mapping unit or grid cell size for the required 1:1 Mil. resolution? Can we agree on adequate evaluation / validation strategies for qualitative Tier 1 zonings? Thank you for your attention!

Example for a Tier 11/2 approach Landslide density combined with qualitative susceptibility Landslide overview map of the conterminous United States 0 500 1.000 Kilometers Radbruch-Hall et al. (1982): USGS Prof. Paper 1183 Godt (1997): USGS Open-File Report 97-0289 http://landslides.usgs.gov/learning/nationalmap/