ranging scales in spatial landslide hazard and risk analysis · ranging scales in spatial landslide...

Ranging scales in spatial landslide hazard andrisk analysis

T, GladeDepartment of Geog~aphy, Univemip of Bonn, Germany,

Abstract

Landslides are part of the natural environment and affect economy andcommunities worldwide at various scales. Consequently, methods of assessinglandslide risk depend heavily on specific demands, Within this frame, spatiallandslide hazard and risk assessments are an important tool to support local andregional communities, These assessments include hazard and risk analysis, riskperception and a sustainable risk management,In Bildudalur, Iceland, hazard analysis was performed at 1:5,000 scale and isbuild on landslide hazard determined by a combination of heuristic analysis, inparticular geomorphological assessment, and process modelling, Theinvestigation was focussed on debris flows and rock falls only, Resultinglandslide maps give run-out distances of different sized landslide events. Thisinformation is assigned to hazard classes expressing through its magnitude theprobability of occurrence of a given magnitude within a given region.Risk analysis in Rheinhessen, Germany is based on landslide hazard derivedfrom multivariate statistical analysis at scale 1:25,000. Landslide types were notdifferentiated specifically, however, most landslides in this region are shallow,translational earth and debris slides and flows. Risk elements were mapped andcategorized from aerial photographs and land use plans, Potential damage wascalculated as average values based on official German statistics sources, Due tomissing information, vulnerability was assigned as 1 (highly vulnerable) - thusanalysis returns a worst case scenario. Resulting landslide risk map identifieshigh risk areas in urban settings.Within their scale of investigation, both approaches demonstrate theirimportance for prevention strategies, in particular for planning and mitigationpurposes, The examples are linked to an overall scheme of landslide riskassessment, which has the potential to include other natural hazards andconsequently might lead to a mutli-natural risk assessment.

© 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved.Web: www.witpress.com Email [email protected] from: Risk Analysis III, CA Brebbia (Editor).ISBN 1-85312-915-1

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1 Introduction

Generally, landslides are single processes affecting local areas only.Consequently, detailed analyses need specific methods, which are commonlybased on physical models well implemented and developed within engineeringand geoscience disciplines, However, if these processes are triggered by a largeevent, landslides occur numerous in the respective area, Therefore, despite itslocalized impact, landslides have the potential to affect wide areas. For example,many landslides have been triggered by earthquakes in Japan [1] or USA [2] orby rainstorms in USA [3], Columbia [4], Italy [5; 6] and New Zealand [7], toname a few regions and some references only, All these landslides havingenormous environmental, economical, and social impacts in the respectiveregion. As Brabb and Harrod [8] have shown, these large spatial inputs ofnumerous landslides are not only a problem of the regions mentioned above, theyare a phenomenon occurring worldwide and causing extensive economic andsocio-cultural problems,To investigate the spatial extend of landslides, they have to be mapped andinventoried [9], Based on historical data, past landslide occurrence can beobtained and together with additional information, the landslide hazard can bedetermined. Hazard is herein defined as the probability of occurrence of aspecific magnitude event within a predefine time in a given region,Spatial landslide hazard assessments have been developed over the last decades.A review of most common natural hazard assessments based on heuristic,geomorphologic, deterministic, statistical, and physically-based models is givenby Soeters and van Westen [1O], and Aleotti and Chowdhury [11], The presentstudy focuses on rainfall-triggered landslides only including earth and debrisflows and slides as well as rock falls (Landslide terminology refers to Dikau etal, [12], and Cruden and Varnes [13].

2 Landslide Risk Assessment

Hollenstein [14] developed a method for a comprehensive natural riskassessment. The method involves risk analysis mostly approached using methodsbased on engineering and natural science, Risk evaluation and perceptionstudies mainly use social science approaches. The combination of both riskanalysis and evaluation ultimately leads to a sustainable risk management.Traditional landslide risk assessments have been developed based on engineeringand natural science perspectives [15], Most recent research involves geomorphicmethods to determine landslide risk [16]. Within this study, landslide risk isdefined as a fimction of landslide hazard, elements at risk including their damagepotential, and respective vulnerability [17], Herein, vulnerability is rangingbetween highly susceptible and not vulnerable towards the respective processes,corresponding to Oand 1,In contrast, research based on social science methods such as risk perception,risk communication and network analysis, to name some research areas only,have rarely been applied to landslide issues (e.g. [18; 19].


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This study focuses on different scaled landslide risk anaiysis, thus implementingone part of Hollenstein’s [14] methodology only. Case studies demonstratepossibilities of using different landslide hazard and risk methods. Furtherinvestigations addressing risk evaluation and landslide risk management are inprogress.

3 Landslide hazard andrisk studies

3.1 Landslide hazard in Westfjords, Iceland

The Icelandic study area is located in Bildudalur, Westfjords (Figure 1). Firstsettlements have been founded in sheltered areas of the Fjord in the 18th century.Fishery is the main economic factor. Natural conditions include a lithologyconsisting of basaltic layers. The parallel and nearly horizontal bedding wasincised by glaciers during the last glaciation and resulted in classic u-shapedvalleys. Since glacier retreat, slope erosional processes such as rock falls anddebris flows dominate Iandform evolution. The current vertical slope profileconsists of a flat valley floor, a moderate to steep talus slope and very steep rocksurfaces. A distinct crest divides the steep upper sIope from the flat plateau,which is at an altitude of 350m a.s.l.. Vegetation consists mainly of grass andmoss and therefore, is of minor importance for landslide processes. Annualrainfall is approx. 1,250mm and average air temperature is 3“C.

Figure 1: Location of Bildudalur, Westfjords in Iceland.


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Geomorphic field mapping at scale 1:5,000 identified landslide sources, travelpaths and deposition areas. Specific focus was given on debris flows and rockfalls. Modelling of landslide run-outs is based onprocess-based and empiricalapproaches, describedin detail by Glade and Jensen [20], Combination of bothanalyses lead to a landslide run-out map, on which areas of short, medium andIong travel distances are indicated, These travel distances vary due to differentprocess magnitudes, thus a short run-out distances is characterised by low rockweights or small debris flow volumes with high ffequency of occurrence, andlong run-outs to heavy rocks and large debris flow volumes with low frequencyrespectively.Rock fall size and consequent weight has been determined through fieldassessments. Debris flow volumes have been calculated for each catchrnent,Analyses is based on specific catchment size and different sized rainfall eventswith 2, 10 and 50 year return periods corresponding to 68, 92, and 117rnmrainfall magnitudes respectively, Because debris flow volumes vary withdifferent catchment sizes, the rainfall event is used as a similar criteria in thefollowing, To each of the rock fall sizes and debris flow triggering rainstormmagnitudes, specific hazard classes have been assigned as proposed in Table 1,The very high hazard class is defined for small rock and debris magnitude, butoccuring in high frequency, In contrast, the low hazard class is defined by highmagnitudes, occurring rarely only.Consequently, each rock and debris volume corresponds to specific traveldistances. The landslide run-out map can thus be transferred into an hazard map(Figure 2), which could be used as basis for forthcoming landslide risk analyses.

Table 1. Hazard classes assigned to respective run-out distances,

Hazard Class Rock weight [t] Debris flow triggeringrainstorm [mm / Ret. period]

Very High <1.9 68/ 2yrHigh 1.9- 11,3 92/10yr

Medium 11.3 -38.7 117/5ovrLow >38.7 >117/5oyr

The landslide hazard map at 1:5,000 scale differentiates areas with highprobability of landslide occurrence fi-om those showing low probability. This isan essential information in order to determine areas potentially endangered bylandslide processes. However, if defence structures are to be build to protectendangered elements at risk, it is most important to model processes based onsite-specific, local parameters in order to allow an appropriate design of thecounter measure,The landslide hazard map is available to responsible agencies and operationalorganisations and might support local land-use and planning procedures.


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I

Figure 2: Landslide hazard map based on process-based rock fall anddeterministic debris flow run-out scenarios.

To determine landslide risk, fiture work includes the combination of spatiallandslide hazard and specific risk elements including assigned damage potentialand specific vulnerability.

3.2 Landslide risk in Rheinhessen, Germany

The Rheinhessen study area located in SW Germany (Figure 3) has beenextensively used as a wine growing region since Roman times. This land usage isbased on its favorable, mild climate and fertile soils, Underlying lithologycompromises Oligocene marls and clays, covered with a Miocene calcatrouslayer of about 10 to 15m. The whole area is part of the Rhine graben structure.Despite the overall depression of the Rhine graben, the northwestern part namedMainzer Becken is being uplifted throughout the Quatemary. Continuous erosionled to classical Tertiary escarpments with low angle pediments and foot slopes,medium angle mid slopes and steep upper slopes with a sharp crest to theadjacent plateau, The slopes below the escarpment are most prone to landslides[21].First historical landslide records dates back to Pleistocene [22]. Since then,landslides occurred sporadically in the Rheinhessen region, However, historicalrecords are sparse, because no continuous data capture has been undertaken inhistoric times. Until now, landslides are recorded by the Geological SurveyRheinland-Pfalz only, when specific requests from local communities or specificland owners have been given. Spatial analysis of landslide occurrence startedwith the hydrological event in Winter 1981/82, where more than 240 landslides



were triggered by a rainstorm accompanied with snow melt. The 1981/82 eventhas been mapped by Krauter [23], and this data has been available for a researchproject entitled Mass Movements in South and West Germany (MABIS) [24].Within the frame of this project, Jager [25] calculated a spatial landslide hazardmap based on multivariate techniques with a grid resolution of 40m. Thisanalysis was again performed by Dikau and Kuntsche [26] using a higherresolution Digital Terrain Model resulting in a 20m landslide hazard map whichwas the basis~or this study.

RIIddmmsll

Figure 3: Location of the Rheinhessen study area [21].

Although hazard is not considered explicitly in Jager’s [25] analysis, it isinherent through the recurrence interval of the triggering event [27]. The 1981/82climatic event has a return period of 50 years, thus the calculated map gives theprobability of landslide occurrence in Rheinhessen for a 50 year period.This spatial landslide hazard information was applied as one input layer forlandslide risk analysis [28]. Elements at risk such as houses, infrastructure lines(e.g. roads, power supply, etc.) and objects (e.g. hospitals, stadium, school,kindergarten, etc.), as well as agricultural land-use have been classified anddigitized from aerial photographs and regional land-use maps. An averagepotential damage value has been assigned to each risk element using officialGerman statistics and data from regional flood hazard assessment [29].


Risk Analysis I11 725 The resulting layer has been combined by classifying each combination of landslide hazard and risk element into low, medium and high risk. Herein, vulnerability is always assigned to be one assuming that as soon as one risk element is affected by landsliding, it is totally demolished. Figure 4 indicates, that the highest landslide risk is in the villages. Consequently, strategies to minimise landslide risk should focus on these delineated areas.

Levels of Risk Wage LOW Medium High Very high

Cartography and analysis: U. Davertzhofen

Figure 4: Regional landslide risk in northwest Rheinhessen, Germany [28].


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4 Conclusions and perspectives

Both examples of spatial landslide analysis give an overview of landslideoccurrence within a respective region, and are thus of major importance forassessing regional hazard as well as risk. Both maps might assist involvedagencies and institutions, such as decision makers and land-use planners, tocompile appropriate plans for sustainable land management, taking the dominantprocesses into account.However, an overall landslide risk assessment would also include an analysis ofrisk perception and evaluation, which was not performed in either region.Therefore, it is envisaged to carry out fhrther research on the integration of riskperception and evaluation in order to determine overall landslide risk in bothregions.In addition, the need to develop the strategy of landslide risk assessment fiu-thertowards a multi-natural risk support system is evident. The system willeventually support a sustainable land use and management considering allnatural processes involved.

Acknowledgements

This study benefited greatly through the contributions of Ursula Davertzhofen,Rainer Bell and Esther Jensen. Kirsten Hennrich gave helpfi,d comments on anearlier draft. Financial support has been given by the German ScienceFoundation (DFG - contract no. Di 414/9-2) and the Icelandic MeteorologicalOrganisation (IMO).

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