geomorphic hazard and risk in platani’s basin: landslide ... · geomorphic hazard and risk in...

Geomorphic hazard and risk in Platani’s basin: landslide risk valuation

V. Liguori & D. Mortellaro Dipartimento di Ingegneria Strutturale e Geotecnica, Università di Palermo, Italy

Abstract

Hydrogeological risk is a more and more widespread matter because of the growing increase of damage and victims that landslides and floods have been provoking in the world. The methodology used to identify the “risk” and its components is one of the issues most studied in the literature. The methods adopted in Italy are mainly found on qualitative evaluations. Such methods make possible the mapping of the territory according to classes of hazard and relatively different risk. Nowadays, GIS technologies are used as the support for performing analyses of stability of the slopes based on probabilistic and statistic methods. These technologies are essentially achieved through the amount of data available and from the necessity to enjoy dynamically all information. A statistical analysis represents a quantitative and even more objective approach to value the landslide risk, as it provides a detailed synthesis of information on the landslides incidence. After an excursus of the methodologies adopted to determine the risk, a methodology is requested for the evaluation of the landslide risk in Platani’s basin. The final result is a risk map. The model is validated by comparing the risk map with the map of the landslides found and mapped, and verifying if the areas subject to landslides are located indeed in the zones where the landslide risk is very high. The risk map represents a useful tool, during the planning of the basin, for the realization of non structural interventions (normative and planners) as a defense against the hydrogeologic risk. Keywords: hazard, evaluation, prevention, mitigation, risk, landslide.

1 Introduction

The methodology used to identify the hydrogeologic “risk” and its components is one of the issues most studied by the literature. The actions of hydrogeologic

© 2004 WIT Press, www.witpress.com, ISBN 1-85312-736-1Risk Analysis IV, C. A. Brebbia (Editor)

protection have to be directed to the elaboration of suggestions that contains, together with the identification of the causes and the effects of the disorder and with the location of the potentially subject to landslide areas, the necessary elements for the prevision and prevention of the calamitous events. In the present work is applied a qualitative methodology of evaluation of the landslide risk in the basin. The goal is to individualize in the examined territory the more risk areas, and therefore to establish a classification of intervention in the activity of the territory protection. The use of methodologies, techniques of intervention and the experimentation of systems capable to study completely the territory, allows to individualize precisely the areas where the landslide risk is elevated, concentrating in this zones the direct investigations. The zonation constitutes the base of the risk management; the management foresees the interpretation of the information and the description of the operational decisions for the risk mitigation.

2 Methodologies for the valuation of landslide risk

A research is developed on the methods of valuation risk [1] and it has been examined a series of methodologies both qualitative and quantitative. The qualitative methods are based on matrix or technical tabular, while those quantatives are based on statistic analyses that allow a more objective interpretation of the studied phenomenon.

2.1 Qualitative method

In Italy, in order to calculate the risk, every region follows the emanated norms in the decree of the 29/9/1998 that confirms the methodologies to adopt for the zonation of the areas exposed to landslide risk . Moreover, it determines the risk R as a result of the three factors: Hazard P, Entity of the risky elements E and Vulnerability V of these elements e defines the classes of R, P and E. The methods for the calculation of the factors are different and the authors approached to their evaluation through different methodologies. The P is the quantification, temporal and spatial, of the probability of necessity in the subject to landslide phenomenons requires; the V depends on the intensity of calamitous event and almost always it is supposed the greatest one, that is equal to 1. In general P can be estimated as the state and the type of activity or as the time of recurring of the considered phenomenon [2], while the landslide intensity is essentially based on the assignment of relative speed classes for unity of volume. From the intersection of these parameters the classes of P are given. Afterwards, the given values are combined with the E classes, to get the total risk. The values obtained on the risk map will be reproduced in opportune scale, with the zonation of the areas exposed to risk R4-R3-R2-R1. As for the evaluation of the hydrogeological risk in the areas exposed to landslide phenomenons [3,4], other authors, from the census of these phenomenons [5], assign a scale on four levels hazard P defined on the basis of the phenomenon typology and the relative state of activity as resultant from the homogenization of the achieved documentation.


164 Risk Analysis IV

In order to have an evaluation of the risk level characterizing every risky area and in order to establish a priority of intervention classification, leading the prevention and protection activity, the marked areas in the Map of the geomorphologic hazard [6] (achieved by classifying the identified areas in the Map of the proneness to real landslides according to the specific level of geomorphologic hazard) can be crossed, with matrix technical, with the Map of the E, to get the total risk for every possible combination of P with E. The risk can be expressed [7] through the matrix combination of the hazard P connected with the disorder and the expected damage D, given by multiplying V by the partner-economic value of the good exposed E. In Sicily , in order to evaluate the landslide P, plays a decisive role the intensity I or magnitudo M (considered as mechanical and geometric severity of the potentially destructive phenomenon) and the state of activity, that provides a temporal and even probabilistic evaluation. The values of M are found by crossing the values related to the surface of the disorder or to the volume of the landslide, for the collapse landslides, with the typology. Other authors avail themselves of empirical methods [8] for the evaluation of M. Actually, to determine the I of a landslides, it would be necessary to take into consideration the speed of movement, the dimensions of the subject to landslides phenomenon, the kinetic energy developed by the landslide [9,10], the geo-technical characteristic, the mass on movement and the kinematics and surface of sliding [11,12]. Correlating the values of obtained M and the state of activity of the subject to landslides phenomenon it is possible to obtain an indicative evaluation of P. Eventually, combining the factors of P and E, it is drawn R. Other authors estimate R and the landslide P, by using basically as tool the inventory of the subject to landslides phenomenons extended to the basin [13]. The inventory map shows the distribution of the events of landslide already verified or just in progress, drawn by the photogeologic multistepped and multitemporal interpretation of aerial photos or from surveys on the ground or other acquired information. From the inventory, using notes in literature techniques of spatialization, the areal evaluation of the landslide P on the basin can be deduced.

2.2 Quantitative method

In the last years, the diffusion of the GIS technologies has facilitated the application of quantitative techniques for the valuation of landslide risk [14]. The GIS represents an useful tool to achieve the “Map of the Hazard”, making possible the elaboration of basic data in short times. In literature some methods are described to carry out the analysis of slopes stability using such technologies: these analyses are really linked to the quality of the introduced data. In general, to realize a map of the potential hazard of the slopes, direct and indirect methods can be used. The first one consists essentially in a geomorphological cartography based on the past and present observations; with reference to the abilities of surveyor, the areal and temporal prevision of the return of the conditions predisposing the geomorphological instability. The second one includes two different approaches: heuristic (Heuristic index) and


Risk Analysis IV 165

statistic. In the heuristic method (intuitive, analogical) the factors of instability are selected and weighed according to their assumed or expected importance in causing mass-movement. In the statistic method (or probabilistic) the weight of each factor is determined on the basis of the areal distribution of the past and present movements. Varied techniques are used that essentially differ from the statistical procedure used (univariate or multivariate). A statistic analysis represents a quantitative and more objective approach some problem list of the stability of the slopes. The techniques of multivariate regression for the landslide hazard zonation and prediction has mostly been developed in Italy [14,15,16,17]. In the realizations, the area of study is covered by a square grid; the square cell becomes the samples unit for the regression analysis. The input data of the model, in raster format, is constituted by the different layers of the spatial information digitized on the map, to es: geology, use of the soil, slope, etc; each value of the cell represents a class of slope or geology, etc.. The “black-box” multivariate model [14], eqn (1), is constituted by an equation where the varying independent Xi are the geo-environmental factors of instability, considered predictor of the subject to landslides phenomenon, Bi are the coefficients that maximize the ability predictor of the same model and the dependent variable L is represented by the presence\absence of deposits of landslide (areal percentage) in each geomorphology homogeneous terrain unit.

L = B0 + B1X1 + B2X2 + ….. + BmXm. (1) The Bi, the unknown parameters, must be estimated from the input data through techniques that depend on the statistical tool selected. A coefficient of regression Bi estimated negative, shows that the presence of the corresponding variable is connected with a safe area, while a positive value involves the possibility of an exposed area to landslide risk. The variables with coefficient next to zero have little effect in the prediction of an area with possibility of landslide risk. The model must be calibrated with the data of the inventory landslides map. It does not provide any information about the distribution of the landslides inside the territorial unity and about the intensity or the kinematics of the subject to landslides phenomenon; but it individualizes, in quantitative way, the actual spatial distribution of those phenomenon. Among the quantitative methods, there are the probabilistic models [18,19]. In the probabilistic models the probability of event in space and/or in time is researched, inside the system slope, on the basis of the existing relationships between causes and effects (landslides).

3 Description of the applied methodology

To determine each factor included in the evaluation of the landslide risk R, eqn (2): R = P ⋅V ⋅E (2)



it is selected to follow methods used by varied sources, every now and then mentioned, to get a procedure as more objective and significant as possible the evaluation. The complete analysis of the risk provides: description of the state of the nature, evaluation of the hazard P, definition of the elements to risk E, evaluation of the vulnerability V, evaluation of the risk R, definition of the acceptable risk and management of the risk. The data collection for the description of the nature state is synthesized in thematic map and in an inventory landslides map. The maps are sometimes identified by the expression “map of the danger”, but substantially they are analytical maps in which the state of fact is recorded. From their interpretation it is possible to derive the necessary parameters to quantify the danger. All the achieved data will be inserted in a Territorial Informative System that not only allows the association of data banks to geographical elements, but also it allows a fast and constant data updating. The principal maps are: the DEM and derived maps (slope and aspect); the geologic-structural map, the geomorphological, the use of the soil, the pedologic and of the vegetation, the map inventory subject to landslides phenomenons. The P consists of the definition of the probability of a subject to landslides phenomenon of determined characteristics, but it has also to consider a prevision of the future evolution of the phenomenon. The complete evaluation of P would request a prevision: spatial (where in a given area and in a given time period T a landslide can be verified); temporal (when it will happen); typologic (type of landslide); the intensity (prevision of the speed, dimensions or energy of the landslide); the evolution (distance of propagation, limits of retrogression). The spatial prevision can be achieved resorting to the statistic analysis that is one of the methods more used to weigh the varied classes employed in the realization of the risk maps and which considers the frequency of the landslides on the varied litologies, in the different slope, etc. To evaluate the hazard P it will be used the Statistic analysis Multivariate [14] that results one of the fittest ones for the use with tools GIS on raster basic. The analysis consists of assigning a “weight” to every signalled parameter as cause of the disorder, making possible, through statistical formulas, the interaction between the parameters with the “weights” so that to point out the potential instability of a slope on probabilistic basic. The technique is based on the Theorem of Bayes [20], according to which “frequency” can be used to calculate probabilities of a future event to verify. For “frequency” it intends the relationship among, for example, the areas really in landslide for a thematic date (es. 5°-10° of slope), and the area of the same thematic. It is fundamental to divide the territory in the zones with unique-condition units UCU, for example classes of slope, areas with the same lithology or slopes with the same aspect. For the Theorem of Bayes the landslides frequency is equal to the probability of landslide that is assigned to the examined characteristic for every class of the same UCU. Then, the probabilities of landslide in the studied area are given by the relationship among the area in landslide and the total studied area. The “weight” W, eqn (3), for a class of parameters as the lithology or the slopes, is defined by Van Westen [21], from the natural logarithm of the



relationship among the density of the landslides in the examined class and that of all the landslides in the whole studied area.

W = ln [DensClas/Densmap] = ln [(NpixSi/NpixNi)/(ΣNpixSi/ΣNpixNi)] (3)

dove, Densclas is the landslides density within the class of examined parameters, Densmap represents the density of landslides in the whole area. Npix(Si) is the number of pixels in landslide within the examined class, while Npix(Ni) is the total number of pixels in the map. All necessary values are achieved through a function of the GIS that allows to superimpose (OVERLAY) and to cross (CROSSTAB) the landslides map with the map of other parameters. The natural logarithm is used to assign the negative values where the density of landslides is low and positive values where the density is high. Adding the different “weights”(W) of two or more maps relative to the varied thematic in examination, a map of the potential instability of the slopes can be created, in this map high values represent high probabilities of slope movement. The map so obtained will have a range of continuous values from a negative number to a positive one: afterwards a grouping in classes, imposed by the necessities of the use and by the experience of the operator, will come. Finally, it is necessary to appraise the results and hence to set the model. The Elements to risk E in comparison to a potential event subject to landslides are represented from the human life, from the structures and public or private infrastructures, from the background of the economic activities and from the environmental goods. The exposed value of the Elements to risk, that corresponds to the quantity of the good exposed to the potential harmful phenomenons, can be expressed [22] from the number of exposed unity or from the exposed area. The value is linked to inhabitants’ age and number, to the income, to the buildings cost in terms of the infrastructures and of the morphological modifications. With the purpose to individualize a map of the elements to risk, the methodology is followed, modified, adopted from the GNDCI U.O.2.9 [23] for risk zonation. The partner-economic value of the E is valued in base to a relative scale, assigning a different weight to according to of the risk that E is subject (equal to 1 for the inhabited centers, the streets of primary communication, etc..), as shown in table 1. The Vulnerability V expresses the degree of loss produced on an element to risk and it depends on the type of E and from the intensity of the phenomenon subject to landslides. In practice it expresses the relation between the intensity of the phenomenon and the possible consequences. In the present methodology V will be assumed equal to the exposed value [24], qualitatively described under form of the classes of territory use, digitized on the base cartography. The scale of V, table 2, goes from a higher value, 5, in correspondence of the inhabited centers to value correspondent to void vulnerability equal to 1. A threshold of acceptable risk to define, is useful within the activities of prevention and planning of the development of the territory; in fact, it allows to individualize the priorities of intervention and to decide the criterions of risk management. In the case of landslides in natural slopes, a specific risk



acceptable Rs can be defined; according to Whitman [25] it is equal to 10-2 events/years. Fell [26] estimates an acceptable annual Rs equal to 10-2 for damages to the ownerships and 10-3 for the human life. In the case of artificial slope the tolerate risk is equal to 10-5 for year.

Table 1: Social economic cost of the E in the area.

Weight 1 0,7 0,3 0 Buildings Civil house.

graveyards. Rural funds.

Civil house: second houses. Summer houses. Farms.

Main roads Primary road: nationals roads.

Secondary road: provincial and communal roads.

Minor road: local and country roads.

Waterworks Works of plug. Principal collectors

Varied infrastructures

Isolated goods and architectural emergencies.

Agricultural and mountain zone

Any element to

risk.

Table 2: Classes of use territory.

Vulnerability. Classes of use of the territory

Description

5 Urban areas Connected areas to the town and separate or with structure clearly more road, suburbs.

4 Areas with scattered houses and isolated goods

Areas of pertinence of farms-house, ranchs, shed houses with short. Buildings of particular importance (hospitals, barrackses, town hall), farms, drinking trough, fountains..

3 Areas with infrastructure

Areas of pertinence of purification and purifying plant, refuse disposal site, springs, wells, equipped parks, camping, equip archaeological areas, etc.

2 Roads infrastructures

Areas of pertinence of the motorway net, national road and provincial, meaningful considered for the intrinsic value and of the local road and country net

1 Areas with non significant vulnerability

Uninhabited and deprived of exposed goods areas

The risk zonation in a given territory constitutes the basis of the risk management that provides for the interpretation of the information and for the background of the operational decisions for the risk mitigation. A concrete example of risk management are the Plans of the Risk Exposure PER [27] that in France are integral part of Urbanistic Planning. In areas with high values of risk two strategies of management are possible: increase of the thresholds of acceptable risk, prosecutable with the information with installation of system of signs of alarm, use of mass-media and not structural intervention; and mitigation



of the risk made possible through an activity of prevention and structural intervention.

4 Valuation of the risk landslide in the Platani’s basin.

We bring the results achieved by following the methodology previously exposed in the preceding paragraph, in correspondence to the under basin of the Platani river containing the Fanaco lake, as shown in fig.1. The Platani is one of the most important river in the southern Sicily. It originates approximately from S. Stefano Q. (Ag) near Cozzo Confessionario and it develops for around 103 km. The basin’s morphology is essentially hilly except for the West zone of Casteltermini where there is Mountain Cammarata (1580 m). It has an extension of 1784.9 km2, and it flows in the Mediterranean sea with a front of around 4 km. The waters currently filled in the lake Fanaco are used to drinking purposes, alleged to a purifying plant denominated Fanaco. As for the description of the nature in the studied area, the following maps have been produced, fig.2: hydrography, geology, geomorphology, pedology; fig.3: vegetation landscape, use of the soil, slope, aspect. The maps-that will be used for the evaluation of the potential hazard of the slopes-are: the geology, the use of the soil and the slope. The map of the Elements to risk is represented in fig. 4 (a). The Vulnerability map is represented in fig. 4 (b). The potential instability of the slopes map (Hazard), achieved by the Statistic Multivariate analysis, is represented in fig. 4 (c). From the combination of the three maps of the Hazard, of the Vulnerability and of the Elements to risk, the Risk Map is obtained, fig. 4 (d). Finally to valid the model, the risk map is superposed with the map of censussed phenomenon subject to landslides, fig. 5. In the map the landslides revert in the zones with high risk. In this way the reliability of the adopted methodology is verified.

Figure 1: Studied area.



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Figure 4: Map of the Risk components: a) Elements to risk; b) Vulnerability; c) Hazard; d) Risk.

Figure 5: Confrontation between risk areas and real landslides.

5 Conclusion

The produced risk map foresees the areas to risk where the landslides will happen, but no their frequency. This limit is also tied up to the methods used for calculating the risk factors. The efficacy of the method used for the hazard evaluation depends from the factors that weigh on the slope stability and from

a) b)

c) d)



the values of the relative weights that indirectly describe the relationships among the physical quantities that are mechanically combined determining the slope stability. Comparing the produced risk map with the map of the finded and mapped landslides, the validity of the methodology has been shown: almost completely the real landslides actually revert in the zones with elevated risk. The risk map represents an useful tool for the realization of non structural interventions (normative and planners) to defense of the hydrogeologic risk. In fact it furnishes useful indications for additional investigations in the areas, that insist on inhabited centers, road infrastructures, to high risk. The risk map constitutes therefore a useful tool during the planning of basin; it allows to direct the planning in sure areas, in the conviction that the best defence from the landslide risk always is the prevention.

Research funded from CNR-GNDCI, research line 2, U.O.2.30., Contract n.18, and from the MIUR ex 60% 2003.

References

[1] Turner A.T. & Schuster R.L, Landslides - Investigation and Mitigation. Transportation Research Board Special Report No. 247, National Academy Press, Washington DC, 1996.

[2] Autorità di bacino Regione Calabria. Piano stralcio per l’assetto idrogeologico (PAI). Studi relativi alla valutazione e alla zonazione della pericolosità e del rischio frana, 2002.

[3] Varnes D. J., Landslides hazards zonation: a review of principles and practice. UNESCO, 1984.

[4] Tropeano D. & Turconi L., Geomorphic classification of alpine catchment for debris-flow hazard reduction. Davos, Switzerland, 10-12 September, 2003. In Debris-flow Hazards mitigation: mechanics, prediction and assessment, eds. Ricklnmann D., Cheng-hung C., Rotterdam, Netherlands, 2003.

[5] Autorità di bacino Regione Marche. Piano stralcio per l’assetto idrogeologico (PAI), 2003.

[6] Autorità di bacino del Fiume Magra. Progetto di Piano stralcio per l’assetto idrogeologico (PAI) del bacino del fiume Magra, 1999.

[7] Autorità di bacino Regione Campania. Piano stralcio per l’assetto idrogeologico (PAI), 2000.

[8] Regione Lombardia, Procedure per la valutazione e la zonazione della pericolosità e del rischio da frana. Milano, Dicembre 2000.

[9] Cascini L. & Sorbino G., Opere di protezione per i fenomeni di colata. In Atti delle Conferenze di Geotecnica di Torino, XIX Ciclo, Stabilità e consolidamento dei pendii. 4-5-6 Novembre, 2003.

[10] Cruden D.M. & Varnes D.J., Landslide types and process. In Landslides- Investigation and Mitigation, Trasportation Research Board Special



Acknowledgements

Report No. 247, eds. Turner A.T., Schuster R.L., National Academy Press, Washington DC, 1996.

[11] Picarelli L., Deangeli C. & Olivares L., Analisi dei fenomeni di colata. In Atti delle Conferenze di Geotecnica di Torino, XIX Ciclo, Stabilità e consolidamento dei pendii. 4-5-6 Novembre, 2003.

[12] Sitar N. & MacLaughlin M.M., Kinematics and Discontinous Analysis of Landslide Movement. Proceed. Int. II Panamerican Symposium on Landslides. Rio de Janeiro, 10-14 Novembre, 1997.

[13] Autorità di bacino del Fiume Tevere. Piano stralcio per l’assetto idrogeologico (PAI) del bacino del fiume Tevere, 2003.

[14] Carrara A. e Guzzetti F., Geographical Information Systems in Assessing Natural Hazards, pp. 21-34, pp. 57-77, pp. 107-133, pp. 135-175, 1995.

[15] Carrara A., Multivariate Models for landslide hazard evaluation. Mathematical Geology, 1983

[16] Carrara A., Cardinali M., Detti R., Guzzetti F., Pasqui V. & Reichenbach P.. GIS techniques and statistical models in evaluating landslide hazard. Earth Surface Process. and Landforms, 16, pp. 427-445, 1991.

[17] Guzzetti F., Landslide hazard and risk by GIS-Based multivariate models. Proceed. Int. Workshop GIS in Assessment Natural Hazards, eds. Reichenbach P., Guzzetti F., Carrara A., Perugia, pp. 83-91, 1993.

[18] Prestininzi A., La valutazione del rischio di frana: metodologie ed applicazioni al territorio della Regione Lazio, 2000.

[19] Natoli S., Prestininzi A. & Romagnoli C., Determinazione della pericolosità da frana: un esempio di applicazione di una nuova metodologia. Geologica Romana, 30, pp. 381-394, 1994.

[20] Morgan B.W., An introduction to Bayesian statistical decision process. Prentice-Hall, New York, pp. 116, 1968.

[21] Van Westen C.J., Application of Geographic Information Systems to landslide hazard zonation. ITC Publication No. 15. International Institute for Aerospace Survey and Earth sciences (ITC), Enschede, Netherlands, pp. 245, 1993.

[22] Canuti P. & Casagli R., Considerazioni sulla valutazione del rischio di frana. In Fenomeni Franosi e centri abitati. Regione Emilia Romagna. CNR- GNDC, 1996.

[23] GNDCI U.O.2.9, Proposta di una carta del rischio da frana per il centro abitato di Sestola (Appennino modenese). CNR-GNDCI - Linea 2 “Previsione e prevenzione di eventi franosi a grande rischio”, Programma speciale SCAI, 1994.

[24] Autorità di bacino Regione Lazio. Piano stralcio per l’assetto idrogeologico (PAI), 1999.

[25] Whitmann R.V., Evaluating calculated risk in Geotechnical engineering. ASCEE Journal of Geotechnical engineering, 110, pp. 145-188, 1984.

[26] Fell R., Landslide risk assessment and acceptable risk. Canadian Geotechnical Journal, 31, pp. 261-272, 1994.

[27] PER - Plan d'Exposition aux Risques, Francia, creato con la legge del 2 febbraio 1995, articolo L562-1 del codice dell’ambiente.



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