Determination of the Damage Potential: a Contribution to the Analysis of Avalanche Risk

Determination of the damage potential: a contribution to the analysis of avalanche risk

M. Keiler, G. Meißl & J. Stötter Institute of Geography, University of Innsbruck, Austria

Abstract

Risk assessment involves analysing and evaluating both hazard and damage potential. While studies on natural hazard processes and the hazard potential are numerous, research on human aspects and the damage potential is rare. However, more attention needs to be drawn to the latter, as most parts of the Alps have undergone significant socio-economic changes since the mid-twentieth century. Methods and approaches which determine and assess the damage potential for risk analyses are still missing. This study presents a concept for an investigation and monetary assessment of buildings and mobile values as well as the estimation of the number of persons endangered by avalanches. The method is mainly based on digital data as well as statistical information. The results are presented corresponding to the existing hazard zones on a municipal level. Thus, buildings and mobile values as well as the number of persons of a region or district can be determined in a cost- and time-efficient way. Moreover the whole approach is incorporated in a Geographical Information System (GIS). The study is conducted and tested in the Paznaun Valley (Tyrol, Austria) and will be standardised for alpine regions. Keywords: natural hazards, avalanches, damage potential, risk assessment. 1 Introduction

The United Nations declared the 1990s the International Decade for Natural Disasters Reduction (IDNDR). Its program focus was giving attention on increasing losses caused by natural hazards and promoting actions to reduce their impact. From a global perspective, alpine natural hazards like avalanches, debris flows, rock fall and landslides, cause only a small proportion of the total losses [1]. In the Alps, however, natural hazard processes affects society significantly, as economic and tourist activities as well as settlements share a spatially limited and intensively used area. The direct and indirect losses of the

Risk Analysis IV, C. A. Brebbia (Editor) © 2004 WIT Press, www.witpress.com, ISBN 1-85312-736-1 188 Risk Analysis IV avalanche winter 1999 represent an extreme example [2, 3]. In order to reduce the impact of natural hazards, the UNO called for two basic approaches, which are mitigation planning (coordinated with land-use planning) and response (event coping and recovery) [4]. Comprehensive mitigation planning includes a) determining the location and nature of the potential hazards, b) characterising the population and structures that are vulnerable to specific hazards (risk results from a) and b)), c) establishing standards for acceptable levels of risk, and d) adopting mitigation strategies based on an analysis of realistic costs and benefits [4]. In general, society is far from reaching these objectives at present. Austria belongs to the few countries which have had hazard zone maps for a few decades. The hazard zone maps are incorporated with building bans and codes in land-use planning [5]. An improvement of risk assessment is necessary, because the hazard zones are only identified by assessing the hazard potential. For the subsequent steps of risk calculation, definition of the acceptable risk and cost/benefit analysis few approaches and conceptual proposals [6, 7, 8] exist, yet standardised methods are still missing. There are hardly any approaches for determining the damage potential for the risk calculation. Data of persons and tangible assets (like buildings) is due to protection of data privacy not available, or needs to be collected in a time- and cost-intensive way. In this study, an approach to determine the damage potential in a cost- and time-efficient way is presented. The newly developed approach was built up on a detailed investigation in the municipality of Galtür [9]. Available digital data and statistical information, the monetary assessment of buildings and mobile values as well as the estimation of the number of persons endangered by avalanches served as a basis for the investigation. Moreover, the whole approach is incorporated in a Geographical Information System (GIS). The study is conducted in the Paznaun Valley (Tyrol, Austria). The valley is divided into the four administrative municipalities of Galtür, Ischgl, Kappl and See. These municipalities have undergone significant socio-economic changes from farming villages to tourist resorts since the mid-twentieth century [10]. Due to location, topography and political interests, winter tourism influences the structures of the municipalities more or less intensively. Seasonal fluctuation of damage potential (persons, mobile values) is pointed out by most of the approaches [7, 8], but only residents and immobile values are considered. Regarding increasing losses of tangible assets, the proportion of mobile values like passenger cars is rising. In this study, the fluctuation of damage potential caused by tourism is determined. The results of this generalised approach in the Paznaun Valley are outlined, followed by a critical comparison of the presented results with those of the detailed investigation in the municipality of Galtür [9]. 2 Methods

2.1 Buildings Digital data for the evaluation of buildings was provided by the Tyrolean state government, division spatial planning and statistics (TIRIS). Following data

Risk Analysis IV, C. A. Brebbia (Editor) © 2004 WIT Press, www.witpress.com, ISBN 1-85312-736-1 Risk Analysis IV 189 were available for the study: coloured orthophotos, as well as information on location of buildings and addresses. The digital data was incorporated in a GIS, updated by interpretation of orthophotos and intersected with the addresses. By means of analysing additional information, such as accommodation statistics and attributes of addresses, the functionality of buildings (inter alia residential building, hotel, guesthouses, public buildings, business) and the building height were derived. If no data was available, buildings were classified as residential buildings. The height of buildings was estimated using the average value according to the building function, which was recorded by the detailed investigation in the municipality of Galtür [9]. Based on the data attained and the calculated area of buildings by using GIS, the volume of each building was determined. In a subsequent step, the value of buildings was estimated with respect to the average prices of insurance companies for new buildings and the corresponding functionality of buildings. Buildings with special functions, like churches, petrol stations, ski lifts or sewage plants were not evaluated due to missing or not clearly definable assessing criteria. For this purpose, detailed analyses are necessary for each building.

2.2 Persons

When determining the number of persons in the avalanche-prone areas, permanent (residents) and temporary (tourist) population were distinguished. The number of residents is derived from statistical data of households [11] and the average number of residents at the end of year (31.12.) from 2000 – 2002 [12] in each municipality. At the end of the year, the number of residents is higher than at the reference date of the census (15.05.). The manpower increases in the winter season due to intense winter tourism in the region and has to be considered in the statistic. The number of residents for each building was determined by using the number of flats in the building and the average size of a household. The potential number of tourists in the endangered buildings was calculated by using the official number of beds specified by local tourist board. The data represent values with maximum occupancy rate of beds assumed.

2.3 Passenger cars

Collecting data on passenger cars is closely attached to the investigations of potentially present persons. For estimating the number of passenger cars per residents, the ratio between registered motor vehicle [13] and the number of residents in the district of Landeck in 2002 were statistically analysed [12]. The number of tourist passenger cars was calculated by employing information on the chosen means of transport and the number of passengers per tourist car. A questionnaire-based survey conducted in the municipality of Galtür and the results of a study on arrivals and departures of tourists [14] show that 95% of the tourists arrive by car. In addition, 3-4% uses private bus companies and 1-2% public transport in winter. Bed & breakfast businesses or small guesthouses register solely arrivals by private cars. Therefore, the number of beds is reduced

Risk Analysis IV, C. A. Brebbia (Editor) © 2004 WIT Press, www.witpress.com, ISBN 1-85312-736-1 190 Risk Analysis IV by 5% for hotels; in all other businesses the total number of beds is considered for the calculations. In a next step, the number of the potential tourist passenger cars was calculated applying the average number of passenger per car in leisure- time (2.34 persons) [15]. The value of the passenger cars was determined using the price of the most popular brand (Volkswagen) and the most sold type of car in Austria in 2002 [13]. 2.4 Spatial analysis All information on the damage potential was intersected with the hazard zones for avalanches via GIS in order to point out the spatial variations. The basis of hazard zone mapping in Austria is the forestry law of 1975 and the respective decree of 1976. The zones are identified by taking the intensity of a design event with a recurrence probability of 150 years as a basis [18]. In the red zone it has to be anticipated that buildings are destroyed and persons in buildings are at the risk of their lives; any building activity is forbidden. In the yellow zone, avalanches have an impact on the economic and individual use of the area and can damage buildings. When observing building codes, it is, however, unlikely that those buildings are destroyed and people in buildings endangered [5]. The official hazard zone map was provided by the Federal Service for Torrent, Erosion and Avalanche Control, District Office Imst and Landeck. 3 Results

The results of the study are presented in following categories with respect to the official hazard zones: In the classes ‘red zone’ and ‘yellow zone’, buildings (and the related persons and passenger cars) are completely located in the respective zone. Buildings that are located in both the red and yellow hazard zone are assigned to the category ‘red/yellow zone’. The same classification is applied to buildings located in the fringe of the yellow zone and non-classified areas (yellow/no zone). 3.1 Buildings In the Paznaun Valley 481 buildings are located in avalanche-prone areas. 16% (75 buildings) are found in the municipality of Galtür, 43% (200 buildings) in the municipality of Ischgl, 39% (190 buildings) in the municipality of Kappl and 2% (10 buildings) in the municipality of See. In the municipality of See, buildings are only located in the yellow hazard zone and in the fringe of the yellow zone and non-classified area. The total value of buildings in all the endangered areas is higher than € 600 mill. The building values show a different distribution as the number of buildings, due to the unequal average building value in the four municipalities (Ischgl € 1.7 mill., Galtür € 1.5 mill., See € 0.8 mill. and Kappl € 0.7 mill.) (See fig. 1a). Nearly 60% of the values concerned are located in the municipality of Ischgl, about 20% in Galtür as well as in Kappl, and a small proportion in See. In Kappl, more than a third of the total value of endangered buildings is located in the red and the red/yellow zone. In the other communities, this proportion is very

Risk Analysis IV, C. A. Brebbia (Editor) © 2004 WIT Press, www.witpress.com, ISBN 1-85312-736-1 Risk Analysis IV 191 low or zero. The highest amount of values accumulates in the yellow zones of the municipalities.

a) b) c)

Figure 1: a) Building values, b) Number of persons, c) Value of passenger cars. 3.2 Persons In the Paznaun valley, nearly 8000 persons live or stay in avalanche-prone areas (calculated with a 100% occupancy rate of guest beds). The persons are distributed as the following: A majority of 65% (about 5200 persons) is located in the municipality of Ischgl, Galtür and Kappl follow with a proportion of 16% respective 17%, and only 2% are found in See (see fig. 1b). 66% of the 350 persons living or staying in the red zones of the Paznaun, are registered in Ischgl, 21% in Galtür and 11% in Kappl. In all communities, more tourists stay in the endangered areas than residents. However, major differences exist between the municipalities under investigation. In the municipality of Kappl has an almost balanced ratio of 48% residents to 52% tourists. In See, the proportions shift to 37% and 63%, and in Galtür and Ischgl, both strongly characterised by winter tourism, a ratio of 21% residents to 79% tourists, respective 13% to 87% exists. In the municipalities of Ischgl and Kappl, the proportion of permanent population in the red zone is highest. The ratio of permanent to temporary population in the red zone shows in Ischgl and Galtür a minor deviation to the ratio of the population in all endangered areas of the respective municipality. In the municipality of Kappl, however, the ratio of permanent population to tourists is 89% to 11%. 3.3 Passenger cars In the four municipalities, the value of passenger cars in endangered areas amounts to about € 62 mill. Most of these mobile values are located in the

Risk Analysis IV, C. A. Brebbia (Editor) © 2004 WIT Press, www.witpress.com, ISBN 1-85312-736-1 192 Risk Analysis IV municipality of Ischgl with a total sum of € 40 mill. (64%). The total value in Galtür is € 10.2 mill. (16%) and in Kappl € 10.9 mill. (18%); in See the value of passenger cars adds up to € 1 mill. (2%) (See fig. 1c). Estimating the number of passenger cars depends on the number of persons. Thus, the distributions and ratios are similar to those of the persons (see fig. 1b and 1c).

3.4 Uncertainties

In order to point out errors and uncertainties of the presented method, the results of the municipalitiy of Galtür are compared with the detailed investigations [10], and determining factors for errors are analysed.

3.4.1 Buildings In each of the municipalities of Kappl and Ischgl four addresses located in the endangered area could not be assigned to any building. In comparison to the detailed investigation in the municipality of Galtür, the total values of buildings in avalanche-prone areas are 32% higher. The largest differences are noted in the red zone (see table 1). Following factors are decisive for deviation of the building valuation: • Building volume (base area, height of buildings) • Different assignment of functionality and consequently a too high or low value in the calculation The largest deviation of building volume occurs with farm buildings that dispose of a connected agricultural and residential part. This information can be derived neither from orthophotos nor from the attributes of the addresses. If all buildings with a large agricultural part are neglected, the deviation is reduced to 12%. In the red hazard zone the low number of buildings and the predominant number of large farm buildings leads to this high deviation. In addition, errors can occur when digitizing the size of the building base using orthophotos, be cause the area of the roof may differ from the base of the building. Using the average building height is also errors-prone. The assignments of the building functionality in the detailed investigation and the presented approach vary due to little or missing information in the address database. In particular, unoccupied buildings are assigned a residential function, which does not exist in reality. Thus, the value of these buildings is calculated too high. Regarding unoccupied farm buildings, the combination of the factors may result in a quintuple deviation of the actual value.

Table 1: Deviation of building values between the detailed investigation (=100) and the presented approach.

Categories Deviation in % Red Zone 176 Red/Yellow Zone 117 Yellow Zone 135 Yellow/No Zone 122 Total 132

3.4.2 Persons The presented approach of determining persons in endangered areas shows just a slight positive deviation of nine percent compared with the detailed investigation in the municipality of Galtür. On the one hand, the number of residents and tourists in the red zone deviate strongly. On the other hand, the number of residents in the red/yellow zone is underestimated (see table 2). The high number of residents is due to incorrect information on the number of flats in the address database. After the correction of this data, deviation is slightly negative compared with the detailed investigation. In the red/yellow zone hotels with staff-housing lead to higher-than-average household sizes. The high number of residents in this zone cannot be compensated in an approach applying average values because of the low number of buildings. The total number of persons in the red/yellow zone is accurately reproduced when adding the number of tourists, as the latter is slightly overestimated. The number of beds respective tourists deviates in Galtür because the number of beds in holiday flats is given in margins (e.g. 3 holiday flats with 2-6 beds). In the other the communities, the listings are more accurate and the deviations are negligible.

Table 2: Deviation of the number of persons between the detailed investigation (= 100) and the presented approach.

Deviation in % Categories Residents Tourists Total Persons Red Zone 134 151 147 Red/Yellow Zone 53 108 100 Yellow Zone 100 116 112 Yellow Zone 96 99 98 Total 99 112 109

3.4.3 Passenger cars The generalised approach is the same as the detailed one, but neglects underground parking and public parking area. In the detailed investigation, the number of parking spaces in underground parking was subtracted from the number of passenger cars in avalanche-prone areas only. The number of parking spaces of public or ski lift parking areas was added to the number of passenger cars. Questionnaires are necessary to gather this information, because documents on accommodation contain only data on garages without detailed information on the type of garage (underground parking or not) and the number of available parking spaces. Orthophotos could be only partially used to extract a potential capacity for passenger cars on a parking area, because agriculturally used areas are turned into parking areas in winter. Therefore, additional mapping in winter is essential for determining the number of parking spaces. In the municipality of Ischgl, 80% of the hotels in the endangered areas have garages (without information on the number of parking spaces). Every one in four guesthouses and bed & breakfast businesses disposes of a garage. The volume of traffic as well as parking caused by tourism produces extensive problems in

Risk Analysis IV, C. A. Brebbia (Editor) © 2004 WIT Press, www.witpress.com, ISBN 1-85312-736-1 194 Risk Analysis IV this municipality. For the whole village, traffic restrictions as well as no parking zones exist in winter. Parking spaces outside or in the public underground parking (which is located in red/yellow zone) can be rented from the municipality. Determining the actual number of passenger cars is not possible without detailed investigations, as pointed out in the example of Ischgl. Hence, the results in fig. 1c display a maximum value.

4 Conclusion and discussion

This approach calculates immobile and mobile values as well as the number of persons of a region in avalanche-prone areas. Thus, the avalanche related damage potential can be determined efficiently and with sufficient accuracy. The method aims to contribute to the improvement of the risk assessment in the field of natural hazards. In the following the most important aspects concerning the type of damage potential are summarized and assessed with regard to a standardised application. Up to now, building values were estimated using basic approaches with average values or with time-consuming expertise. The method described above allows for a plausible and advanced estimation of the damage potential of buildings. The specified high positive deviation for farm buildings can be reduced by applying accurate and detailed information in the address database. In the state of Tyrol the municipalities are responsible for the gathering of information on the address database. The municipalities carry out the recording of the data by them selves, or pass it on to a third party. In the municipalities under investigation, the accuracy of the recordings varies. Slightly overestimating single building values is an advantage, as fully detached farm buildings of agricultural businesses and garages are not recorded in the address database and not considered in the estimation. Thus, these buildings are indirectly incorporated in the assessment of building values. The applicability of the used method displays a strong dependency on the quality of the available original data, in particular on the information in the address database. Unlike other approaches, tourists are taken into consideration when determining the number of persons. The result represents the maximum number of endangered persons. Deviation occurs in categories with a very low number of building respective households due to the average values applied. Moreover, insufficient information in the address database affects the results negatively, yet to a lower extent as when evaluating the buildings. The applied approach is a efficient way of determining the permanent and temporary population. The results obtained when calculating the values of the passenger cars presents a maximum value without considering cars of day-trippers. The results of the detailed investigation cannot be generalised and transferred to other municipalities. This is not possible because of the completely different structures of parking facilities in other communities. However, the presented method provides a good base for assessing the damage potential of passenger cars realistically when adding some more information on the municipalities.

The vulnerability of the objects (persons as well as immobile and mobile assets) based on the intensity of avalanches should be included in a comprehensive analysis of the damage potential. In this case, detailed information can only be attained by individual expertise of buildings [17]. Owing to the lack of knowledge on the relation between pressure and vulnerability, existing avalanche risk studies use simple relations for both persons [18, 6] and buildings [6, 19]. Models for assessing the vulnerability like in earthquake [20] or flood research [21] are still missing [22]. Numerous studies concerning alpine natural hazards [6, 7, 8, 23, 24] in all disciplines provide an improvement of risk management and mitigation planning, as postulated by the IDNDR. It is acknowledged that accurate hazard assessment is an essential starting point and needs to be combined with comprehensive studies on damage potential [4]. The presented study contributes to this goal by means of simplifying the determination of the damage potential. Smith [1] summarises: ”At the end of the Decade, there was an acceptance that 10 years is a rather short period for real progress to be attained. The IDNDR was only a signpost near the start of a very long journey.”

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