Documentation of forest and other woody land along trajectories of non-destructive rockfall

V2 2018-04 Frank Perzl, Andreas Kofler, Elisabeth Lauss, Hanna Krismer, Monika Rössel, Christian Scheidl and Karl Kleemayr

1 Introduction

In this guideline, an approach to consider forest structure and characteristics along a rockfall trajectory guideline is presented to determine key parameters, which help to evaluate the protective role of forests stands against rock-fall events. Therefore, this work should be seen as extension to “Guidelines for collecting data about past rockfall events” (ASP 462 – RockTheAlps; WP1 – Activity A. T1.2) proposed by Žabota & Kobal (2017). In this concept, the approach and the survey setup for a comprehensive rockfall hazard event documentation, focusing on woody vegetation, are illustrated. The main forest parameters are explained and in a “best practice example”, the general workflow and some exceptional cases are discussed.

2 General concept

The spatial distribution of (woody) land cover units like forest stands with relative uniformity and the internal structure of woody vegetation of these units of homogeneity (U) is documented along rockfall trajectories (real rockfall paths) from the farthest block deposit (FBD) identifiable to the starting point of the rockfall hazard (the center of the scar – CS). Methods and work steps: 1) Preliminary orthophoto-mapping of the rockfall trajectory. 2) Preliminary segmentation of the rockfall trajectory into units of homogeneity (not stocked areas and stands of woody vegetation) by means of aerial image interpretation. 3) Preliminary determination of sample plot positions (plot centers) within the unity of homogeneity along the trajectory. 4) On-site inspection of the trajectory uphill: correction of the direction of the trajectory and of the U-borders, classification and description of U, log sampling along the segments, correction of sample point positions and plot sampling within Us.

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2.1 Parameters TORRID explicit

Depending on the classification of land cover unit the amount of collected data varies. Clearing areas and non-forested areas are registerd by their length and position. For the forested sections, the required parameters for the TORRID toolbox (explicit) are determined. The necessary parameters for TORRID explicit cannot all be determined directly in the field, but can be calculated using the following measurable parameters, which are collected following the work steps of the general concept stated above. The key parameters of TORRID explicit are:

Basal area [m²/ha]: The angle count sampling method (ACS) (Bitterlich, 1984) and, in case of young wood and shrubs below callipering limit of ACS, tree diameters at breast height (DBH) from stem surveys on fixed area plots are used to calculate the basal area.

Stand density [N/ha]: The method is set up for determination of the number of wood plants per ha regardless of plant size.

Species composition: Stand composition can be specified as proportions of basal area or canopy cover on base of the proposed survey.

Ratio high forest/shrub forest: The method enables the calculation of the percentage of different types of land cover of the total length of the rockfall path.

Top height [m]: Different indications of the height of the woody vegetation like the top height may be calculated on base of the surveys.

3 Pre-investigation

First step of pre-investigation is the collection of all information about the rockfall hazard from initial hazard reports like photos and witness statements if available. These reports will help to identify the rockfall sources and paths. Registration of the hazard and of all suitable reports in the hazard database prior to terrestrial survey enables clear allocation to data sources by identity numbers. Next step is mapping of the rockfall trajectory or determination of the most probable direction from FBD to CS on a current aerial orthophoto (mapping scale ~ 1:2,000) with contour lines. If available, relief images from high resolution digital elevation models should also be used. Relief images provide the identification of the downhill direction, terrain features and possible rockfall sources. The rockfall trajectory is drawn as a polyline. The edges of the polyline are recommended to not be smaller than about 20 m in length on a mapping scale of 1:2,000. Information about vegetation and other surface cover provided by the orthophoto and relief imagery is used for segmentation of the trajectory into units of homogeneity of slope and surface cover with special consideration of the density and structure of woody vegetation. On-site views from points on the opposite slope may be particularly suitable for mapping and segmentation of trajectories on base of topographic maps, optical and relief imagery.

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Pre-investigation of trajectory may be done in office or on-site or both, depending on the situation. Especially prior information provided by hazard reports and remote sensing sources are key factors. In some situations, above all in case of rockfall deposits under dense forest cover, mapping and segmentation of the trajectory as well as positioning of sample plot centers is a consecutive task of on-site investigation of hillslope.

Figure 1: Mapping and segmentation of the rockfall trajectory. Figure 1 is a sketch of mapping and segmenting of the rockfall trajectory taking into account the spatial distribution of units of woody vegetation. The units 2 and 3 portray forested areas, whereas the units 1 and 4-6 represent non-forested areas, which are registered solely by length and GPS position. A more detailed description of the trajectory recording, as well as a detailed description of examples considering special forest conditions can be found in chapter 5. We recommend a minimum length of a unit of 20 m in downslope direction (regarding canopy cover on woody land, CC).

Planning of on-site surveys requires an assessment of the number of samplings. The number of sampling plots in each unit is a crucial question regarding validity and explanatory power of the data. The number of plot samples required to give a defined degree of accuracy is difficult to be predicted in advance. Therefore, we suggest to define a fixed number of samplings per length of unit instead of statistical calculation of the required number of samples on base of assumptions. The respective sampling plot set up is illustrated in chapter 4.2.

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We suggest 1 plot per 60 m length of the segment (LS) of the trajectory within a unit, at least one plot per unit. The ratio R is rounded mathematically (R ≈ LS/60). The distance of samples along the segment of the unit is simply DS = LS / (R + 1). The general concept for measuring the structure of woody land (forest stands) is a plot survey along the trajectory within units of homogeneity. We suggest a combination of angle count sampling (Bitterlich, 1984) of the "tree layer" and several small fixed area plots in order to survey shrubs and regeneration.

4 On-site inspection of trajectory

4.1 Description of the course of the trajectory and of units

The description of the course of the trajectory may follow the structure of template C. EVENTID: Identifier of the hazard event record in the database. PATHID: Identifier of the rockfall path (trajectory) in the database (or sequential number). EPSG-Code: Code of the coordinate reference system used. Description of trajectory and units starts at FBD with GPS measurement of position (Figure 1). Inspection of the situation of the surrounding and uphill area may show appropriate conditions for a sampling at FBD. No positional shift is required. The next point of the course will be the uphill border of unit 1 (Figure 1). At FBD the first sampling is positioned. The FBD is the starting point of the first segment of the traverse. Hence, attributes of the first row of the table are:

PATHID: Identifier of the rockfall path. UNITID: Consecutive number of the unit of homogeneity (Figure 1). PLOTID: In case of a sample plot, consecutive number or identifier of the sample plot. No: Number of the segment of the traverse (Figure 1). GPS-X (Easting): Coordinate (Easting) of the starting point of the first segment (GPS). GPS-Y (Easting): Coordinate (Northing) of the starting point of the first segment (GPS). Altitude: Altitude of the point (GPS or barometric measurement). Ideally, a team of 2 groups will conduct the recordings, considering time management and work flow. One part of the staff (group 1) stays at FBD for sampling. The other part (group 2) may explore the terrain uphill to define and mark further sample points. Group 2 measures:

Azimuth: The Azimuth of the next segment of the course to the borderline of unit 2 (e.g. L1.1, Figure 1).

Inclination: The Inclination of the segment.

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Distance: The planar length of the segment. Logs: Additionally, group 2 counts the number of woody logs with a diameter ≥ 20 cm, which intersect the segment of the trajectory on the way to the next point. This enables the calculation of a log density.

4.2 Plot sampling of woody vegetation

Figure 2 shows the design of tree and stand structure measurements. Sampling method may be:

1) Angle count sampling (ACS) of woody vegetation (DBH ≥ 12 cm) in combination with four crosswise arranged fixed area subplots (4 m x 5 m) for survey of bushes, coppices and regeneration (h ≥ 1.3 cm). 2) Alternatively: Survey of woody vegetation (DBH ≥ 12 cm) on fixed area plots (20 x 20 m or 15 x 15 m) in combination with crosswise-arranged subplots for plants (h < 1.3 m). 3) Optionally: survey of woody regeneration ("single-stem trees", 0.1 m ≤ h < 1.3 m) on half of the area of the subplots. As general sampling procedure, we propose method 1 (ACS in combination with fixed area subplots). Alternatively, a combination of one larger und several smaller fixed area plots will be more appropriate for some situations of forest structure and technical equipment. Method number 3 will be optional, if there is an interest in collecting data on woody regeneration.

Figure 2: Plot design

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We classify the numerous phenotypes of woody vegetation into three simple types:

1) Single-stem trees including woody plants, which show no branching or branching of the main axis at 1.3 m in height or over (dead or alive). 2) Forked woody plants: woody plants, which show branching of the main axis into two or more shoots and stems (bushes, coppices – stumps with sprouts, candelabra trees) below 1.3 m in height (dead or alive). 3) Stumps: basal axes of woody plants cut or broken below 1.3 m in height with or without own living sprouts with a maximum DBH smaller than 12 cm (DBH < 12 cm). Forked woody plants with a maximum DBH of all shoots or stems smaller than 12 cm (DBH < 12 cm) are counted as one plant (e.g. a bush or stump with small stump sprouts). So we do not count the other shoots on subplots. We consider that forked woody plants with a DBH of the thickest shoot or stem (max DBH) of at least 12 cm (DBH ≥ 12 cm) may differentiate into single-stems or coppices similar to single-stems trees growing close together. Therefore, each shoot or stem (h > 1.3 m) is counted as one plant:

• Stems of such woody plants with DBH ≥ 12 cm and h > 1.3 m: they count at ACS and within the alternative main fixed area plots (20 m x 20 m or 15 m X 15 m). • Stems of such woody plants with DBH < 12 cm and h > 1.3 m: they do not count at angle count sampling and also not within main fixed area plots, but in subplots (4 m x 5 m) of the regeneration survey.

Note that a stump may be counted doubly: a stump and a forked woody plant (with sprouts with a max DBH smaller than 12 cm).

Template A is a proposal for angle count sampling of trees (DBH ≥ 12 cm): No.: Consecutive number of the stem. Species: Species or species group of woody vegetation. Use your one abbreviations or numeric codes. However, codes should be delivered with metadata.

DBH: Diameter at breast height. DBH-Age: Optionally. h: Top height – in case of forked woody plants with a common crown the maximum height of the plant. We measure the height of stems with maximum, medium and minimum BHD of each species.

Status: Status of the tree according to Figure 3. Habit: Growth habit of the woody plant. S = single-stem tree. F = part of a forked woody plant. We also not the number of stems (DBH ≥ 12 cm) of a woody plant in the sample. For example, see template A: tree No. 1 and tree No. 2 are both part of a forked woody plant and in the sample; so we note F and 2 for both stems.

Canopy: Optionally: Diameter of the canopy/crown. In case of common canopies of forked woody plants, we note the diameter of the common crown for the thickest stem.

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Figure 3: Status of woody plants. Modified from Maser et al. (1979) and Backhouse & Lousier (1991) Template B may be used for survey of woody vegetation (DBH < 12 cm) and stumps on regeneration subplots (4 m x 5 m). Alternatively, it may also be used for counting stems with a DBH of 12 cm or thicker on fixed area plots (20 m x 20 m, 15 m x 15 m).

We recommend to measure DBH, h and the diameter of the canopy of one of ten plants per h- DBH-class and species (reference plants). Data of diameters of the canopies provide calculations of canopy cover of the shrub layer. In case of common canopies of forked woody plants, we note the diameter of the common crown for the thickest stem.

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5 Example cases for special conditions

In this section, an advanced example for special cases which may arise in the field is presented.

Figure 4: Mapping and segmentation of the rockfall trajectory. Figure 4 is a sketch of mapping and segmenting of the rockfall trajectory taking into account the spatial distribution of units of woody vegetation.

Unit 1 (Figure 4) may be dense area of shrubs or coppices like hazel (Corylus avellana) at the outer unit of the forested terrain. The FBD stopped in this shrubland and is the starting point of the polyline representing the rockfall trajectory. The coordinates of the starting point of the polyline should be registered as exactly as possible. We recommend to compare GPS coordinates and the position on the aerial imagery according to distances from control points. In case of a FBD at the outer borderline of the unit, the polyline also starts with the FBD. Hence, a shift of the first sample plot into the (woody) unit or a reduction of the plot size is necessary. Borders of sample plots should be completely within units. We suggest first to try a spatial shift 8

along the trajectory, secondary (in case of fixed plot sampling) to reduce plot size. In case of angle count sampling, selected trees may be outside of the unit because of a wide variable radius depending on a large tree diameter. We do not count such woody vegetation (omission of not representative woody vegetation outside of units). However, in some situations a spatial shift of sample plots into units, partition of the sample or omission of sample trees is not appropriate. The example (Figure 4) shows two special cases. First, we assume a downfall of the boulder along the borderline between a dense thicket of Norway spruce (Picea abies) mainly and a plenter forest of beech (Fagus sylvatica) and fir (Abies alba) (Unit 2, Figure 4). The two different types of forest adjoin each other closely along the trajectory. In some cases, different forest types of forest structure may flowingly merge into each other in downslope or other directions. The margins of the units (stands) form transitional structures of woody vegetation which may offer immanent response to impacts of rockfall or avalanches. Hence, despite of two different types of forest stands along the trajectory, consider boundary or transition zones as units (of forest effects rather than of homogeneity). However, we suggest to document this special situation (description of unit). Borderline situations may constitute own classes of structure of woody land. Analysis of effects of woody land on natural hazards and biosphere require definition of borderline and transit units.

The next example and section of the trajectory (Unit 3, Figure 4) is a typical situation in forested terrain affected or prone to gravitational natural hazards. There may be an elongated gap or blank between different stands of woody vegetation or within one stand. Since different research questions require adaptions, there is no commonly applied definition of a gap and a blank. We suggest to use gap and blank definition of the BFW geohazard database (BFW-GeoNDB) (Perzl et al., 2017):

Gaps and blanks: The total canopy cover on a gap or a blank is smaller than 15 %. The length is the dimension in downslope direction. The width is the dimension along the contour line of the terrain.

A gap (small blank or lane) is a clearly separable and small crown canopy opening within a matrix of woody vegetation. Not clearly delimitable canopy openings are not considered as gaps. The minimum planar width of a gap is 10 m (from canopy segment to canopy segment in bird's- eye-view - CC, on-site from stem to stem about 15 m) and the minimum area is 100 m² (CC). In case of the planar width is more than 50 m (CC), the planar area is smaller than 2,000 m² (CC). If the planar width does not exceed 50 m (CC), there is no limitation of the area (e.g. small cutting stripes).

A blank is a sparse stocked area (of forest use) which does not match the gap criteria of maximum size. Hence, the planar width of a blank is more than 50 m (CC) and the planar area is 2,000 m² (CC) or more. We suggest to consider gaps and blanks of 20 m (CC) in length and over as units. However, regarding gaps, differentiation of two situations may be appropriate.

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A gap may be a discrete feature showing clear borderlines (e.g. cutting stripes) or a feature with a fuzzy margin. Although, the definition of a gap claims clear borderlines, transitional forms of appearance occur frequently. In case of discrete gaps, dimensions of fixed plots should be adapted to gap size by shift of the plot along the trajectory systematically or by reduction of the width of the plot (e.g. to 15 m). Borderlines of fixed plots should be within the gap (Figure 4). In case of ACP, woody vegetation outside of the gap or on the borderline does not count. In case of fuzzy margins and similar dimensions of adjacent woody vegetation, shifting of plot position, a reduction of the plot size or omission of stems included in the angle count sample is not necessary. Canopy openings smaller than 10 m in width (CC) are also a part of the adjacent woody unit. We suggest to document width and length of gaps and blanks as well as to document discrete and fuzzy situations. Units 5 to 7 (Figure 4) are free of woody vegetation visible in remote sensing sources. However, some woody vegetation may only be visible on-site and plots may provide in-depth survey of site conditions. The last segment of the example of a trajectory (Unit 7, Figure 4) is too steep and dangerous for walking. However, such segments are also a part of a complete trajectory description. Boundaries of fixed plots may be laid out using barrier tapes or thin ropes (Figure 5). However, another efficient method for small subplots (4 m x 5 m) is to lay out a center baseline with a measuring tape. In order to count woody plants (h ≥ 1.3 m, BHD < 12 cm), follow the line with a horizontally aligned measuring stick of 2 m in length on both sides.

Figure 5: Example of 2 fixed area subplots with the dimensions of 4 m x 5 m

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6 List of abbreviations

ACS Angle count sampling Winkelzählprobe CC Canopy cover, regarding canopy cover Kronenüberschirmung, in Bezug auf den Kronenschirm CS Center of the scar Zentrum der Anbruchs-/Ausbruchsstelle DBH Diameter [cm] at breast height (1.3 m) Brusthöhendurchmesser (BHD) max DBH DBH [cm] of the thickest shoot or Maximaler Brusthöhendurchmesser: BHD des stem of a forked woody plant at stärksten Triebs eines Strauchs oder Ausschlags. breast height d Diameter Durchmesser DS Distance of samples along a segment Abstand der Probeflächen entlang eines Einheits- of the trajectory [m] abschnittes der Trajektorie FBD Farthest block deposit Block- (Stein-)-Endablagerung GPS Positioning with devices of a Global Positionsmessung mit einem globalen Positioning System Positionsbestimmungssystem h top height [m] of a woody plant Höhe eines Baumes oder Gehölzes bis zur höchsten Stelle eines Haupttriebes oder bis zur Bruchstelle. L Length of polyline segment of the Länge einer Strecke der Trajektorie. trajectory LU Length of a unit of the trajectory Länge eines Einheitsabschnittes der Trajektorie; aggregating the polyline segments L Summe der Strecken L der Trajektorie innerhalb within a unit of homogeneity [m] einer Homogenitätseinheit U Unit of homogeneity Homogenitätseinheit (Bestand)

7 References

Backhouse, F.; Lousier, J.D. (1991): Silvicultural Systems Research: Wildlife Tree Problem Analysis. Min. For., Min. Environ., Lands and Parks, Wildlife Tree Committee, Victoria, B.C.

Bitterlich, W. (1984): The Relascope Idea: Relative Measurements in Forestry. Commonwealth Agricultural Bureaux, London.

Maser, C.; Anderson, R.G.; Cromack, J.; Williams, J.T.; Martin, R.E. (1979): Dead and Down Woody Material. In Wildlife habitats in managed forests: The Blue Mountains of Oregon and Washington. Edited by Jack Ward Thomas. US Department of Agriculture Forest Service, Washington, D.C. pp. 78-95.

Perzl, F.; M. Rössel; Th. Zieher (2017): C3S-ISLS. Climate induced system status changes at slopes and their impact on shallow landslide susceptibility. WP 2. Landslide Data Acquisition and Geodata Management: Description of the C3S-ISLS Landslide Inventory and of the landslide hazard database BFW-GeoNDB. V9 2017. Deliverables of the ACRP Project C3S-ISLS funded by the Climate and Energy Fund. University of Innsbruck, Austrian Research Centre for Forests (BFW).

Žabota, B.; Kobal, M. (2017): Collecting historical rockfall events. Guidelines for collecting data about past rockfall events. Deliverables of ASP – RockTheAlps. WP1 – Activity A. T1.2. University of Ljubljana, Biotechnical Faculty, Department of Forestry and Renewable Forest Resources.

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8 Templates

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A TREE AND FOREST STAND MEASUREMENT

EVENTID PATHID PLOTID YEAR MONTH DAY 595 157 2 2018 05 19

VARIABLE RADIUS PLOT SAMPLING k = 4 (upstanding single-stem trees and shoots or stems of forked woody plants alive or dead with DBH ≥ 12 cm) No. Species DBH [0.1 cm] DBH-Age h [0.1 m] Status Habit Ø of canopy [0.1 m] 1 Fagus syl. 12.1 14.7 1 F 2 optionally 7.8

2 Fagus syl. 20.8 1 F 2 7.8

3 Abies alb. 58.0 4 S

4 Abies alb. 45.9 1 S

5 Picea ab. 37.2 28.2 1 S 4.5

6 Abies alb. 45.1 33.4 2 S 5.1

7 Picea ab. 28.3 24.4 1 S 4.2

8 Abies alb. 61.0 39.1 1 S 8.6

9 Fagus syl. 46.0 37.1 1 S 10.1

10 Abies alb. 51.2 1 S

11 Abies alb. 56.8 38.3 1 S 8.0

12 Fagus syl. 31.7 29.5 1 S 9.5

13 Fagus syl. 44.4 4 S

BFW 2018, I6, F. Perzl B TREE AND FOREST STAND MEASUREMENT – FIXED SUBPLOT FOR SHRUBS/COPPICES AND YOUNG GROWTH (DBH < 12 cm) OR CLUSTERED FOREST

EVENTID PLOTID SUBPLOTID SUBPLOT AREA [m²] 595 2 4 B1 B2 B3 B4 20 Number of single-stem-trees (DBH < 12 cm), forked plants with max DBH of shoots < 12 cm, shoots (DBH < 12 cm) of forked plants with max DBH ≥ 12 cm h [m] DBH [cm] Snags Picea ab. Abies alb. Fagus syl. Fagus syl. 0.1 – 0.49 --- optionally optionally optionally optionally optionally optionally optionally optionally optionally

0.5 – 1.29 --- optionally optionally optionally optionally optionally optionally optionally optionally optionally II IIII IIII II II IIII IIII IIII IIII IIII IIII IIII II ≥ 1.3 < 3 IIII IIII IIII IIII IIII 3 – 6.9 IIII IIII I IIII IIII I

7 – 11.9 I II In case of (fixed) plot sampling without angle count sampling: Number of single-stem-trees (DBH ≥ 12 cm) and shoots of forked woody plants (DBH ≥ 12 cm) alternative 12 – 19.9 alternative 20 – 29.9 alternative 30 – 39.9 alternative 40 – 49.9 alternative ≥ 50 Number of stumps (d ≥ 20 cm & 0.2 m ≤ h < 1.3 m) → 0.2 m ≤ h < 0.5 m IIII IIII I 0.5 m ≤ h < 1.3 m II Measurement of 1 of 10 reference single-stem trees alive or forked woody plants alive per tree species and h-DBH-class Species h [0.01 m] Age Species DBH [0.1 cm] h [0.1 m] Ø of canopy [0.1 m] Species DBH [0.1 cm] h [0.1 m] Ø of canopy [0.1 m] Picea ab. 2.1 2.5 Picea ab. 5.1 5.2 Fagus syl. 1.5 3.1 Abies alb. 6.0 5.6 Fagus syl. 2.4 3.1 Fagus syl. 5.1 4.8 Fagus syl. 1.0 1.3 Picea ab. 7.1 8.5 Fagus syl. 2.9 3.7 Fagus syl. 1.0 1.5 Fagus syl. 1.0 1.7 Abies alb. 2.1 2.2

BFW 2018, I6, F. Perzl C COURSE OF TRAJECTORY, LOG SAMPLING ALONG TRAJECTORY AND DESCRIPTION OF UNITS

EVENTID PATHID EPSG-Code DATE (yyyy-mm-dd) 595 157 31287

STARTING POINT OF EDGE EDGE TO NEXT POINT PATHID UNIT PLOTID No GPS X (Easting) GPS Y (Northing) Altitude[m] Azimuth[0.5 gon] Inclination[0.5 deg] Distance[0.01 m] LogsØ ≥ 20 cm 157 1 1 L1.1 260,725.8 348,945.8 1238.0 192.5 28.0 20.15 no logs

157 2 --- L2.1 260,728.2 348,925.8 1248.7 201.1 32.0 41.20 IIII I

157 2 2 L2.2 260,727.5 348,884.6 1274.5 199.0 32.0 40.32 no logs

157 3 --- L3.1 … … … … … … …

…

BFW 2018, I6, F. Perzl C COURSE OF TRAJECTORY, LOG SAMPLING ALONG TRAJECTORY AND DESCRIPTION OF UNITS

EVENTID PATHID 595 157

Unit Description

BFW 2018, I6, F. Perzl Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

Addendum to „Compilation of data about rock falls and rockslides in form WLV and BWF natural hazard event databases” (Perzl, Rössel, 2017) Elisabeth Lauss, Christian Scheidl, Frank Perzl, Karl Kleemayr Innsbruck, 2019-02-19

Introduction

This report is an addendum to „Compilation of data about rock falls and rockslides in Austria form WLV and BWF natural hazard event databases” by Frank Perzl and Monika Rössel in 2017 and contains a description of the provided data on historic rockfall events for the RockTheAlps project by Austrian Research Center for Forests (BFW). Two separate databases were created, due to the nature of different data requirements for TORRID_explicit and TORRID_light.

Data compilation characterized in this report was composed to develop the TORRID toolbox, which is a risk reduction model. The objective of this model is to state the percentage of risk reduction for each predefined forest type individually.

Database TORRID_explicit

The database for TORRID_explicit is a collection of empirical data of historic rockfall events and forest parameter. The field work was conducted in summer 2018.

Information on historic rockfall events were extracted from the WLV.EKM database of the WLV, an agency of the Austrian Federal Ministry of Sustainability and Tourism (BMNT), which is described in detail in the previous report. In addition to the rockfall events found in den WLV.EKM, there was first-hand information collected from practitioners and foresters working in affected regions.

Using this information, it was paramount to connect the deposition zone to the source area of the rockfall event, to enable the application of the energy line concept (Heim, 1932). Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

The data collection of the hazard event followed the guideline, provided in WP 1 by Ẑabota and Kobal in 2017

- “Collecting historical rockfall events – guidelines for collecting data about past rockfall events”.

The required forest parameters were gathered, based on the guideline

- “Documentation of forest and other woody land along trajectories of non- destructive rockfall” supplied by Frank Perzl in 2018 in course of WP2.

The data collection process followed a transect from the farthest deposition point of a known rockfall event to the source area. Demonstrated in Figure 1 are sampling plots along a transect. The distances between the sampling plots were predefined during the preprocessing.

Fig. 1: Exemplary illustration of a transect from the deposition zone to the source area on an orthophoto (left) and a hillshade (right)

Field work activities:

The field work was carried out in nine communities in and Upper Austria. During August 2018, several rock-fall events have been documented in the Western part of Austria. Recording took place within the following municipalities of Tyrol (AUT): Galtür, Mathon, , Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

Kappl, , Gris im Sellrain, Gries am Brenner, St. Jodok am Brenner, Vals und Zirl.

Galtür Galtür Number of transects: Number of rocks Spruce forest 4 7 Larch-Spruce forest 2 14 Larch forest 3 2 Mountain Pine Green-Alder Birch Hardwood 1 Brushwood

Example Jamtal, release area is the central rock face located over the forest

Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

Ischgl Ischgl Number of transects: Number of rocks Spruce forest 4 10

Example Ischgl

Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

Kappl Kappl Number of transects: Number of rocks Spruce forest 1 2

Example Kappl

Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

Gries im Sellrain Gries im Sellrain Number of transects: Number of rocks Spruce forest 7 12

Example Narötz, Gries i.S.

Ried im Oberinntal Number of transects: Number of rocks Spruce forest 1 2

Gries am Brenner Number of transects: Number of rocks Spruce forest 1 8

Vals Number of transects: Number of rocks Larch-Spruce forest 1 1 Spruce forest 1 1

Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

St. Jodok am Brenner Number of transects: Number of rocks Spruce forest 3 5

Zirl Number of transects: Number of rocks Pine-Oak-Ash-Linden forest 1 8

In Figure 2 the distribution of the communes Vals, Gries am Brenner, Zirl, Galtür, Ischgl, Ried im Oberinntal, Gries im Sellrain, Haibach ob der Donau, Grünau im Almtal and Micheldorf are illustrated.

Fig. 2: Location of the communes where field work was conducted.

In the course of the field work in summer 2018, 164 individual rocks were recorded on 18 different rockfall locations. With the weighted and homogenized data, the database was complied. In table 1 all attributes of the TORRID_explicit database is listed and described.

Tab. 1: Description of attributes of TORRID_explicit

Attribute Unit Description

Event ID [-] Identifier of the rockfall event recorded in the database, using a character. Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

Rock ID [-] Identifier for an individual rock recorded in the database, combining the character of the Event ID and a consecutive number for the individual rocks.

Total Length [m] Total length of the energy line

Total Δ Height [m] Total vertical height difference from the source area to the deposition point of the individual rock.

Angle [°] Energy line angle

Basal_area [m²/ha] Basal area of the recorded forest section

Stand density [N/ha] Stand density of the recorded forest section

Species [%] Tree species composition or species of woody composition vegetation, containing various subdivisions, for instance “Picea”and “Larix”, in percent

High_forest [%] Percentage of high forest of the recorded forest section

Shrub_forest [%] Percentage of shrub forest of the recorded forest section

Top_height [m] Top height of the recorded forest section

Logs [-] Number of woody logs with a diameter bigger or equal to 20 centimeters.

Database TORRID_light

The goal of TORRID_light database was to provide a catalogue of historic rockfall data regarding areas where no detailed information on the vegetation is available, enabling a quick evaluation using existing information like land cover maps, orthophotos and digital elevation models Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

The database TORRID_light consists of preexisting information on rockfall events as well as data, gained via remote sensing. The main source for the database was the first data compilation of Frank Perzl (2017) and the rockfall events of the TORRID_explicit database.

The rockfall events selected from the first Austrian data compilation had to fulfil the restriction criteria of at least partial coverage with forest or woody vegetation of the path of the rockfall event.

The required forest parameters were determined with preexisting forest maps of the Austrian Research Center for Forests (BFW). This forest map allowed a division in coniferous forests, broadleaved forests, mixed forests with either predominant coniferous or broadleaved composition.

The TORRID_light database contains information on 215 individual rocks.

Tab. 2: Description of attributes of TORRID_light

Attribute Unit Description

Event ID [-] Identifier of the rockfall event recorded in the database, using a character

Rock_ID [-] Identifier for an individual rock recorded in the database, combining the character of the Event ID and a consecutive number for the individual rocks

Total_Length [m] Total length of the energy line

Length_forested [m] Total forested length of the energy line

Height [m] Total vertical height difference from the source area to the deposition point of the individual rock

Coniferous [%] Percentage of coniferous forest or coniferous woody vegetation of the transect Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

Broadleaved [%] Percentage of broadleaved forest or broadleaved woody vegetation of the transect

Mixed C [%] Percentage of mixed forest or woody vegetation with predominant coniferous vegetation of the transect

Mixed B [%] Percentage of mixed forest or woody vegetation with predominant broadleaved vegetation of the transect

Non-forested [%] Percentage of the non-forested part of the transect

Data format

The data delivery of both databases consists of a Microsoft Excel file including all attributes illustrated in tables 1 and 2. Following the same methodology as described above, additionally rockfall data from Bavaria, Italy and Slovenia could be compiled.

Metadata of the TORRID database (per February 2019)

Austria Institution: Austrian Research Center for Forests (BFW), Department of Natural Hazards Contact information: DI Dr. Karl Kleemayr Rennweg 1 6020 Innsbruck Phone: +43 (0) 512-573 933-5101 E-Mail: [email protected]

Area of fieldwork Tyrol (Vals, Gries am Brenner, Zirl, Galtür, Ischgl, Ried im Oberinntal, Gries im Sellrain)

Upper Austria (Haibach ob der Donau, Grünau im Almtal and Micheldorf) Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

Data foundation Field work Begin of field work: 18-05-2018 End of field work 08-06-2018 Number of datapoints 164 Language English

Bavaria Institution: Bavarian State Research Center for Forests (LFW) Department 3: Silviculture and Mountain Forest Contact information: DI Dr. Daniel Trappmann Hans-Carl-von-Carlowitz-Platz1 85354 Freising Phone: +49 8161 71-4641 E-Mail: [email protected] Area of fieldwork Data foundation Field work Begin of field work: End of field work Number of datapoints 253 Language English

Italy Institution: University of Padova, Italy Department of Land, Environment, Agriculture and Forestry Contact information: Dr. Francesco Bettela Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

Viale dell'Università, 16Legnaro 35020 (PD) Phone: +39 049 8272700 E-Mail: [email protected] Area of fieldwork North Italy Data foundation Field work Begin of field work: End of field work Number of datapoints 234 Language English

Slovenia

Institution: Slovenian Forestry Institute Department of Forest and Landscape Planning and Monitoring Contact information: Mitja Skudnik PhD Vecna pot 2, SI – 1000 Ljubljana, Slovenia GSM/Mobile: +386 (0)31 327 432 E-Mail: [email protected] Area of fieldwork Data foundation Field work Begin of field work: End of field work Number of datapoints 15 Language English

References

Heim, A. (1932): Bergsturz und Menschenleben. In: Geologische Nachlese Nr. 30. Beiblatt zur Vierteljahrsschrift der Naturforschenden Gesellschaft in Zürich No. 20, Jahrgang 77. Description of the RTA database on historic rockfall events taking the example of the Austrian data collection campaign

Perzl, F., Rössel, M. (2017) Compilation of data about rock falls and rockslides in Austria form WLV and BWF natural hazard event databases (unpublished) Perzl, F. et al (2018): Documentation of forest and other woody land along trajectories of non-destructive rockfall (unpublished) Ẑabota, B., Kobal, M. (2017): Collecting historical rockfall events – guidelines for collecting data about past rockfall events (unpublished)