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Deterministiclandslidehazardassessmentatregionalscale

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Deterministic landslide hazard assessment at regional scale

F. Cotecchia1, F. Santaloia2, P. Lollino2, C. Vitone1, G. Mitaritonna1

1 Department of Civil and Environmental Engineering, Technical University of Bari, Via Orabona 4, 70125, Bari, Italy; PH +39 080 5963338; email: f.cotecchia@poliba.it; c.vitone@poliba.it; g.mitaritonna@poliba.it. 2 Research Institute for Hydrogeological Protection, National Research Council, Via Amendola 122/I, 70126, Bari, Italy; PH +39 080 5929596; email: f.santaloia@ba.irpi.cnr.it; p.lollino@ba.irpi.cnr.it. ABSTRACT The paper presents a new methodology for the deterministic assessment of landslide hazard at the regional scale in geologically complex chain areas. The methodology entails site specific geo-mechanical studies, as background of any hazard prediction application, and the creation of a Regional Landslide Manual portraying the geo-mechanical knowledge about the slope conditions across the region. The search in the regional manual of the landslide mechanisms which may correspond to the combination of landslide factors recorded at the local scale results in the hazard prediction. The testing of the methodology in the Daunia Apennines is discussed. INTRODUCTION

Landslide risk is still very high in extensive mountainous populated regions, despite the research progresses concerning the comprehension and modelling of slope failure processes at large scale (site specific, 1:2000-1:10000). This observation generates doubts about the efficacy of the approaches currently adopted to assess regional landslide risk (small scale, 1:50000-1:100000).

As outlined by Terzaghi (1950), the internal landslide factors that influence the landslide mechanism (i.e. the processes connecting landslide factors and event) are: the slope geometry and geo-structural set-up, the mechanical properties of the materials, their permeability and the slope boundary conditions, whereas the external factors are all those causing a change in the slope equilibrium conditions. Indeed, in the last decades significant developments have involved acquisition techniques of part of the landslide factors (as for: topography, weather conditions, vegetation; van Westen et al. 2008) at the regional scale. Hence, implementing these data in geographical information systems (GIS) may be a starting point for a regional landslide hazard assessment (Chacón at al. 2008). However, in order to yield an appropriate landslide hazard assessment, such GIS platform should be completed with the remaining factors and with appropriate algorithms relating the factors (that are GIS information levels), in order to derive quantitative assessments of the slope stability and of the possible failure mechanism. Nonetheless, accounting for quantitative landslide factor-event relations is commonly considered not feasible at the regional scale (Fell et al. 2008), that is a scale at which hazard assessments are usually carried out with either heuristic or statistical methods (Yin & Yan, 1988; Aleotti & Chowdhury 1999, Dai et al. 2002; Nadim et al. 2005; Fall et al. 2006). It seems like that ignoring the landslide mechanisms is an important reason for the

inefficacy of landslide hazard assessment methods and mitigation strategies at the regional scale, especially so in geologically complex chain areas.

The present paper discusses the results of an on-going research for the formulation of a methodology for Regional Quantitative Landslide Hazard Assessment, QHA (Guzzetti et al. 1999; Ho et al. 2000; Cotecchia et al. 2009a) within geologically complex areas. Such methodology is meant to make small scale hazard assessments benefit from site specific geo-mechanical interpretations of landsliding. PROPOSED METHODOLOGY

The proposed small scale methodology is based on site specific geo-mechanical studies of landslide mechanisms. These studies can be carried out at three levels: I, or preliminary, based on analyses of all the slope factors, possibly by means of field investigations, which result in phenomenological interpretations of the failure processes (Skempton & Hutchinson 1969; Hutchinson 1988); II, or intermediate, consisting in limit equilibrium analyses of the slope geotechnical model (Chandler & Skempton 1974; Chandler 1984); III level, or advanced, which involve both numerical modelling (Potts et al. 1997; Griffiths & Lane 1999; Fenton & Griffiths 2008) and field monitoring of the landslide activation and evolution. These studies should be widespread across the region and represent the 1st phase of the methodology (Figure 1a). This embodies a process of selection of the representative slope features within the region, since it is intended to characterize the representative sets of geo-hydro-mechanical factors for the slopes in the region and the representative slope failures.

The objectives of the 1st phase studies are pursued if two hypotheses are validated (Figure 1a): hypotheses 1, that a limited number of representative geo- hydro-mechanical set-ups can be identified in the region, despite the variability of the landscape, along with, hypotheses 2, few representative failure mechanisms. In homogeneous regions, even only a single landslide mechanism may be found to occur repeatedly (Montgomery and Dietrich, 1994, Cascini et al., 2003, Savage et al., 2004), so that its geo-mechanical characterization allows for the regional landslide hazard assessment. In regions of variegated landscape, hypotheses 1 and 2 can be found to be valid if mechanics is used as a means to characterize the soil masses, since soils and rocks part of different geological formations can exhibit similar mechanical response. Hence, different geological sequences can be part of the same class of geo-hydro-mechanical set-up. In the research here of reference, hypotheses 1 and 2 have been validated in a geologically complex region, the Daunia Apennines (Southern Italy), as discussed later.

Step 1 of the 1st phase (Figure 1a) consists in the creation of a regional analytical database of all the landslide factors. This should include not only the data generally detected and computerized at the regional scale for either heuristic or statistical databases, but also data logged at the large scale in site specific studies, e.g. the soil hydro-mechanical properties. This analytical database should be then converted into a regional GIS database (Mancini et al. 2008). Thereafter, the analysis of such data should aim at the geo-hydro-mechanical classification of the soil masses, (GMi classes) across the region (Figure 1a). The outline of such GMi classes should

Figure 1. F

a)

be reported covering the g

Step 2 between the ithe active failandslide meaforementionequilibrium bavailable in which are noprovide quanthe mobilizedanalyses conslandslide proand their styinterpretation

The threpresentativreported in thsuited for thebe of use tooutlined in ththe assessmetopographic accounted forII and III leve& Griffiths, interpretation

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low chart of the proposed methodology (a: 1st phase, b: 2nd phase).

in a Regional Landslide Manual (RLM), meant to be the handbook eo-mechanical knowledge about the slope features across the region.

of the 1st phase (Figure 1a) entails the recognition of the connections nternal factors, characterizing the GMi classes, the external factors and lure processes. Therefore, this step concerns the interpretation of the chanisms, that can be developed through either of the three

ed levels of study. In particular, the II level analyses should be limit ack-analyses of active sliding processes, carried out using the data

the GIS database and considering as variable parameters the factors t characterized by the available data. The II level analyses should

titatively based indications of the geometry of the landslide bodies, of strengths at failure and of the failure predisposing factors. The III level ist of either direct in-situ monitoring or numerical modelling of active

cesses and investigate the landslide predisposing and triggering factors le of activity. Both II and III level studies should validate the I level s for representative processes in the region. ird step (Figure 1a) of the 1st phase involves the classification of the

e landslide mechanisms recognized in the 2nd step (Mi). These should be e RLM, together with the algorithms and modelling procedures best

ir interpretation. Thereafter, the RLM and the regional GIS database will interpret the landslide susceptibility of any slope in the region, as e 2nd phase of the methodology. For hazard predictions, it required also nt of the time of failure. For this, also data reported in multiple-year maps and aerial photos, together with monitoring data should be in the analyses (Guzzetti et al, 1999; Dai et al, 2002). So, for example, l analyses implementing either expected or statistical variations (Fenton 2008) with time of the landslide predisposing factors would result in s of the failure activation and evolution times.

The hazard assessment within a given portion of the region represents the 2nd phase of the methodology (Figure 1b). Later in the paper the hazard assessment within urban areas (medium scale, 1:10000-1:25000) of the Daunia Apennines (Figure 2a) is discussed.

Step 1 of the 2nd phase involves the creation of a medium scale analytical database, more detailed than that created in the 1st phase. It will include data representing the landslide factors, with particular emphasis on those recognized to be predisposing of landsliding in the 1st phase. The RLM should provide indications about the procedures of acquisition of such database, citing, for example, the main data sources. The database will also include data about the slope movements available in the area of interest, such as: topographic, interferometer, inclinometer monitoring data and structure damage data. In particular, the experience gathered in urban areas has shown that the detection of structural damages gives evidence of slow landslide activity otherwise not detected. The methodology entails the merging of the analytical database in a local GIS database.

Joined consultation of the local GIS database and of the RLM (Step 3), should lead to the identification of the possible landslide mechanisms in the area of application. In fact, the combination of the different GIS layers within a given territorial cell reports the site-specific set of landslide factors. A search in the RLM for a combination of factor values similar to that reported for the territorial cell of interest should allow for the recognition of both: the class of geo-hydro-mechanical set-up (GMi) and the class of instability scenario (Mi) that are likely to occur in the territorial cell. Such recognition provides clues about how and why the slope could fail (landslide susceptibility), and possibly when (landslide hazard).

Step 4 of the 2nd phase involves the validation of the hazard assessment deduced as above by means of specific I, II and III level analyses.

TEST SITE OF THE PROJECT: THE DAUNIA APENNINES

The research test site is the sum of the hilly urban areas within the Daunia Apennines (Figure 2a). Their current geological setting is closely related to the geological history of the Apennine chain, a Neogene and Quaternary thrust belt within the central Mediterranean orogenic system (Malinverno and Ryan, 1986). At present, the Southern Apennines are made of a stack of Meso-Cenozoic tectonic units, covered by Neogene-Quaternary thrust-sheet-top deposits, that are all mainly marine sedimentary sequences, where limestones and/or sandstones are interbedded with clayey marls, clays and silty-clays. This is the case of the Faeto Flysch and the Red Flysch formations, whose outcroppings are the most widespread in the Daunia Apennines. In general, the tectonic events have modified the original sedimentary set-up of the geological formations, changing their soil structure, from the mega to the micro-level. Therefore, the sedimentary successions are found to be affected by different fissuring intensity and remoulding degree (Figure 2).

In particular, the Daunia clays are often fissured. The highest fissuring intensity affects the Red Flysch clays (FYR), whose meso-structure is made up of millimetre lenses of clay, the scales, as result of extremely large shear strains generated by tectonic processes. FYR scaly clays (clay fraction CF = 55-70%) are of medium-high plasticity (plasticity index IP ≅ 40-100%; liquid limit wL ≅ 60-140%)

and activity (A ≅ 0.75-1.4). Medium intensity fissuring (clay elements of about 27 cm3 volume; Vitone et al. 2009) affects the Toppo Capuana clays (TPC; CF≅50-60%), that are of high plasticity (PI ≅ 30-40%; wL ≅ 30-75%) and medium activity (A= 0.5-0.7). The unfissured clays of the Faeto Flysch (FAE; CF ≅ 65-75%) are of high plasticity (PI ≅ 60-70%; wL ≅ 100%) and activity (A ≅ 0.75-1). Both the fissured structure and the composition of the Daunia clays are factors predisposing the soil mechanical properties to be very poor (e.g. average peak and residual strength parameters: TPC: cp’=0-50 kPa, φ’p=18-20° and φ’r= 9.6°; FAE: cp’=0-25 kPa, φ’p= 18-22° and φ’r= 8.7°; FYR: : cp’=0-20 kPa, φ’p=15-25° and φ’r= 5-9°).

Figure 2. Schematic structural map of Italy (a) and Daunia flysch formations: b)

stratified limestone and c) rock blocks in a fissured clayey matrix.

ApenninesSouthern

Northern

Adriatic Sea

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Apenninic foredeep

Apulian foreland

Daunia Apennines

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1st PHASE APPLICATION: PRELIMINARY RESULTS

In the 1st phase, studies have been carried out across all the Daunia urban areas (twenty-five small towns), disregarding the conditions of free-field slopes. The topographic, lithological and geo-structural features of the slopes, the hydraulic and mechanical soil properties and the activity of landslides have been characterized based upon the analysis of regional topographic and geological maps (1:50000-1:100000), together with available site-specific geological and geotechnical reports and results of in-situ surveys. All the analysis results have been implemented in a regional GIS database, covering the twenty-five urban centres (Step 1, Figure 1a). Based upon the study of these data, all the soil lithotypes have been included in solely two classes, accounting for their mechanical behaviour and for its impact on landsliding, irrespective of their specific geological features. These classes are defined as: 1) rock class (Figure 3a), including stiff, high-strength materials, such as: limestones, sandstones or conglomerates interbedded with few thin clayey strata, or marly rocks and weakly cemented sands, pebbles and rocky blocks dispersed within a scarce fine matrix; 2) soil class, of deformable and weak materials, for which the ratio between the soil and the rock portion is much higher than one and the overall mechanical behaviour is controlled by the soil portion. The soil class materials happen to be mainly clays, often fissured.

Thereafter, three recurrent geo-hydro-mechanical set-ups have been recognized in the region, named GM1, GM2 and GM3 in Figure 3a (result of Step 1), which differ mainly for the trend of the contact between rock class and soil class materials. All the GMi set-ups in the region appear to host seepage domains with shallow water table (no more than 4-5 m below ground level). The geo-mechanical set-up GM1 (Figure 3a), is characterized by a sub-horizontal contact between an upper rock class slab and a lower soil class stratum (generally clayey), whereas a monoclinal contact between the rock and soil class portions applies to GM2. Only GM3 includes solely soil class materials, but with monoclinal bedding. In general, the contact between the materials is either stratigraphic or tectonic. GM2 appears to be the most recurrent. The oldest part of most towns lies on rock class outcroppings, since only from the beginning of last century buildings have been founded on soil class outcroppings.

Figure 3. (a) Geomechanical set-ups and (b) landslide mechanisms; key:

(1) rock and (2) soil class materials. In the 2nd Step of the 1st phase, all the available data about landsliding, such

as: data reported in both national and regional landslide inventories, literature data, displacement and failure data from site-specific geotechnical reports, information about damages of structures and results of on-purpose in-situ surveys, have been implemented in the regional GIS database. Based upon these data, extensive I level studies of landsliding have been carried out, which have resulted in the recognition of four main classes of landslide mechanism (Step 3, Figure 1a), shown as M1-M4 in Figure 3b. These I level interpretations have been also checked by means of several II and III level site specific analyses.

Class M1 (Figure 3b) includes compound slides, usually deeper than 30 m, whose length is comparable with the width. The sliding surfaces are about rotational, single or multiple, and become flatter in the accumulation zone. They are characterised by a distinct headward evolution. Class M2 corresponds to mudslides that can have one or more source areas and whose body can be either elongate or lobate. They may appear flow-like, but the studies have demonstrated the occurrence of sliding; their slip surfaces can be from medium depth to deep. The third class, M3, includes the most complex landslides, that involve a shallow earth sliding-flow (Corominas, 2004) or flow-slide (Hutchinson, 2004), and a deeper extremely slow sliding. The last landslide class, M4, is represented by a deep rotational landslide

M3

M1 M2

b)

M4

a)

2 1

GM1

GM2

GM3

mechanism evolving into an earth-flow downslope. The main scarps of most M1 to M4 landslides involve the borders of towns.

According to the 1st phase procedure, the characterization of both the GMi and the Mi classes has been reported in the Daunia Apennines Landslide Manual (DALM), together with the relations between landslide factors and mechanisms recognized through the different level studies. So far, results of I, II and III level studies appear to suggest that most M1 to M4 movements in the region are slow to very slow (v < 5*10-3

mm/s) reactivation of landslides, that involve primarily soil class materials and extend to rock class materials secondarily, due to retrogression processes. The reactivation of M1 and M2 processes, that are the most recurrent, is mainly seasonal, since it occurs between January and May. Both the deep M1 and M4 landslides occur within high energy relief landscapes, where the stiffer and less fissured clayey flysch occur. Both II and III level analyses have confirmed that the highest strengths are mobilized by this types of mechanisms. M1 landslides appear to be most prone to a retrogressive evolution, causing very active depletion zones, whereas M4 landslides are often characterized by an advancing activity.

M2 sliding processes are generally shallower (≥ 20 m) than M1 and M4 (≥ 30-40 m) and occur within less steep slopes and weaker soil class materials. Indeed, for either M1, M2 or M4 landslides, limit equilibrium analyses have confirmed that the decrease in stability factor with depth is more significant the larger is the intercept cohesion characterizing the soil strength envelope. Furthermore, the deepest M1 and M2 landslides have been found to occur in slopes where soil plasticity increases with depth and influences a decrease in intrinsic strength of the soil (Lollino et al. 2010).

M3 landslides are those of most difficult interpretation. Indeed, limit equilibrium is not suited for their analysis; rather site investigations and finite difference modelling (Santaloia et al. 2001; Cotecchia et al. 2000; Cotecchia et al. 2009b) have shown that the lack of homogeneity of the soils is crucial for this type of landslide mechanism. In general, the soil mechanical properties, together with the seepage conditions (shallow water tables), are essential predisposing factors of the reactivation of M1 to M4 processes (II and III level results). 2ND PHASE APPLICATION: LANDSLIDE HAZARD AT VOLTURINO

Both an analytic and a GIS database have been created for the urban area of Volturino (2nd phase), according to the DALM. The combined consultation of such database and of the DALM has allowed for the recognition of the location at Volturino of a GM2 set-up (Figure 3a), mainly result of the presence of monoclinal contacts (mainly NW-SE) between FAE and TPC to the West, FAE and FYR to the East (Figure 4) and, further to the East, between FYR and the Subappennine Clays (ASP). Both FAE and TPC formations are here made up of both rock and soil class materials: calcareous strata, clayey marls and clays for FAE and clays and clayey marls, with few thin calcareous intervals for TPC. Almost all the urban centre is founded on FAE rock class materials. Only since last century, urbanisation has involved the western slopes, where either TPC or FAE soil class materials outcrop (Figure 4; FAE: cp’=12-36 kPa, φp’=24°-26°; TPC: cp’=15 kPa and φp’= 18.5°). According to the 1st phase results reported in the DALM, it appears that the most

recurrent landslide mechanism at Volturino is M2, followed by few M3 and M4 cases. The several source areas of M2 mudslides affect the gentle western slopes, where highly fissured TPC clays and FAE clays outcrop. An example of this mechanism is the Fontana Monte mudslide (1 in Figure 4) that involves mainly TPC clays. According to I level regional studies (DALM), the depth of this mudslide would be ≥ 20 m; both stratigraphic and inclinometer monitoring data (boreholes I1 and I2, Figure 4), recorded last winter, have given evidence to a shear band of more than 40 m maximum depth. Also, an increase in plasticity index (PI) and a decrease in consistency index (CI) have been recorded with depth down borehole I1, which suggest that the soil properties are predisposing factor for deep instability processes in the slope. M3 and M4 type mechanisms are found to involve both FYR and ASP clays within gentle slopes located to the East. Instead, large M4 depletion zones involve steeper slopes in FAE clays interbedded with rock layers.

Most of the landslides at Volturino are reactivation processes, whose first failure occurred before last century and was influenced by torrential erosion at the slope toes. The current landslide activity is most important in the depletion zones bordering the urban centre and is about seasonal, probably connected to the water table variations occurring in winter (water table rising of about two metres recorded in winter 2009). The landslide mechanism interpretations deduced by the application of the 1st phase results and outlined above have been validated by means of limit equilibrium and finite element modelling (II and III level; Lollino et al. 2010).

Figure 4. Geological map of Volturino. Key: 1) ASP, 2) TPC, 3) FAE, 4) FYR, 5) (a) stratigraphic and (b) tectonic contacts, 6) landslide (a: crown, b: body), 7) (a)

piezometers and (b) inclinometers installed in 2008, (c) previous boreholes).

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