Geomorphological Analysis of the Koppl catchment, Austria · 5 IP: Integrated Project 2016/17 Fig....

Geomorphological

Analysis of the Koppl

catchment, Austria

Lukas Götzlich, Harald Rehard [email protected], [email protected]

Z_GIS - University of Salzburg, Austria

WS 2016/17

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IP: Integrated Project 2016/17

Table of Contents Abstract ................................................................................................................................................... 2

1 Introduction ..................................................................................................................................... 3

2 Study Area ....................................................................................................................................... 5

3 Methods ........................................................................................................................................... 7

3.1 Manual Mapping ..................................................................................................................... 7

3.1.1 Shape ............................................................................................................................... 8

3.1.2 Substrate .......................................................................................................................... 8

3.1.3 Process ............................................................................................................................. 9

3.2 Landform Extraction from DEM ........................................................................................... 10

3.2.1 Curvature ....................................................................................................................... 10

3.2.2 Residual/Regional Relief Separation ............................................................................. 12

3.2.3 Object-Based Image Analysis ....................................................................................... 13

4 Results ........................................................................................................................................... 13

4.1 Manual mapping results ........................................................................................................ 14

4.1.1 Shape ............................................................................................................................. 14

4.1.2 Substrate ........................................................................................................................ 16

4.1.3 Process ........................................................................................................................... 19

4.2 Landform extraction results ................................................................................................... 20

4.2.1 Curvature ....................................................................................................................... 20

4.2.2 Residual/Regional Relief Separation ............................................................................. 21

4.2.3 Object-Based Image Analysis ....................................................................................... 22

5 Discussion ..................................................................................................................................... 23

6 Project Management ...................................................................................................................... 26

7 Conclusion & Outlook ................................................................................................................... 28

References ............................................................................................................................................. 28

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Table of Figures

Fig. 1: Maximum Extent of the Salzach glacier at LGM during the Würm ice age (Egger &

van Husen 2009) ............................................................................................................. 5

Fig. 2: Study Area and it’s extent in an overview map with some relevant villages ................. 6

Fig. 3: Degree of Roundness classes (GeoDZ 2010) ................................................................. 9

Fig. 4: Sphericity in four classes (Freie Universität Berlin 2017) ............................................. 9

Fig. 5: Profile Curvature in a systematic form (ESRI 2017) .................................................... 11

Fig. 6: Plan Curvature in a systematic form (ESRI 2017) ....................................................... 11

Fig. 7: Landform classification according to curvature classes (Dikau 1996) ......................... 11

Fig. 8: Principal of the Regional Relief Separation (Hiller & Smith 2008) ............................. 12

Fig. 9: Cell-based vs. Object-based landform analysis (Dragut & Eisank 2011) .................... 13

Fig. 10: Geomorphological Map of the Koppl region with shapes, substrate and processes ... 14

Fig. 11: Photographs of visually detected landforms in the study area .................................... 16

Fig. 12: Overview sketch of the outcrop in cross section ........................................................ 17

Fig. 13: Profile and grain-size distribution along the profile ................................................... 17

Fig. 14: Descriptive statistics of the 74 samples; a) shows the grain size frequency within a

boxplot, b) shows the frequency of lithology types, c) illustrates the variations in the

roundness degree, d) sphericity types ........................................................................ 18

Fig. 15: Extraction of theoretical flow paths ............................................................................ 19

Fig. 16: Landform enhancement via curvature analysis........................................................... 20

Fig. 17: Landform enhancement via Regional Relief Separation ............................................ 21

Fig. 18: Landform extraction with object-based image analysis.............................................. 22

Fig. 19: Limits of landform extraction via OBIA .................................................................... 23

Fig. 20: Scratched till from the endmoraine of Willischwand ................................................. 24

Fig. 21: PERT diagram from the present project ..................................................................... 26

Fig. 22: Gantt-chart from the present project ........................................................................... 27

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Abstract This case study has an important applied aspect as the investigation takes place in a region

which is vulnerable to regularly occurring floodwaters, landslides and extreme precipitation

events. A possible explanation for these events is the glacial past of the catchment of Koppl.

The recent landscape was formed by the glacial advance of the Salzach glacier during the

Würm ice age. Surprisingly, the run-off from the catchment flows into the region of Thalgau,

which belongs to the lower areas of the former Traun glacier. To find out if this fact correlates

with the relatively high number of water induced natural events, an overview of the landscape

configuration and the near-surface material was needed. Therefore, we performed a

geomorphological analysis including a geomorphological mapping campaign collecting data

about the three landscape components shape, substrate and processes. To map the shapes GPS

was a helpful tool. Different field methods and LiDAR data as well as available geological,

soil and hydrological maps were used to complete this analysis. With LiDAR data one can

extract Digital Elevation Models (DEM’s) and based upon that different spatial analysis steps

were performed, modelled and visualized. We calculated a curvature raster, performed a

regional relief analysis and we used OBIA method to figure out glacial shapes automatically.

The main result is an overview of the whole catchment and the morphogenesis of this

catchment over time. This is delivered by a digital map, a story map in ArcGIS online and

webmap configurated with leaflet. The overall aim of this study (together with others) is to

understand the environment within the catchment and to create opportunities for the local

community and people to take action and to cope with the natural events in future.

1 Introduction

Heavy rainfall as well as intense snowmelting are causing frequently occuring floods and/or

high surface runoff within the catchment of Koppl. For the parcel owners this means a

damage of their land, especially for farmers who have to struggle with crop failures and soil

erosion. The Koppl catchment is – compared to other basins in similar location – particularly

prone to these processes. The reason therefore is complex and not yet fully clarified. One

major issue for high surface runoff over some hilly meadows are layered clays under the soil

which have the function of retaining percolating water and thus, water will be squeezed out

onto the surface where it flows down slopes and erodes the upper soil cover to a certain

degree. It seems to be sure that the main reason for this critical runoff regime within this

catchment is the glacial formation of the overburden sediments. These accumulations and

resulting landforms are subject to geomorphological research.

Hence, the authors of this report performed a geomorphological analysis within which the

main part is a geomorphological mapping of the study area (not yet available) and some

approaches of detecting and extracting landforms by remotely sensed data (especially

DEM’s). Scientific effort on the research in the Koppl catchment is limited to some works

from Klug!!!. An important study suitable for this small basin originates from MENEWEGER

(1993), who describes the landscape development in the quaternary. Some geological works

mentioning the Koppl region are from EGGER & VAN HUSEN (2009) and DEL-NEGRO (1963).

For performing the geomorphological mapping the literal guidelines from LESER & STÄBLEIN

(1975) is useful.

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Conducting a geomorphological analysis of a catchment like that in Koppl one needs to gain

fundamental knowledge on the glacial history of the alps in general and about the foreland in

particular. So, the following statements give an understanding of how this glacial landscape

has emerged and developed over the last about 100,000 years.

Four major ice ages during the last 900.000 years have been verified (with 2-3 further cool

eras depending on the literature). These ice ages are called Günz (900.000 – 600.000 years

b.p.), Mindel (460.000 – 400.000 b.p), Riß (300.000 – 130.000 b.p.) and Würm (100.000 –

10.000 b.p.) in the alpine region and are named according to rivers in the foreland where

endmoraine artefacts have been found. In the alpine region especially Riß and Würm ice age

influenced today’s landscape decisively, as massive glaciers merging to glacial stream

networks covered the alps and only the highest peaks (nunataks) overtopped the ice. From the

source areas at the main alpine crest numerous smaller glaciers emerged to fewer but larger

ones until only a handful of these foreland glaciers flew out of the alps and their tongues

reached areas some kilometres away from the alpine front. One of these main glaciers was the

Salzach glacier which flew over today’s Pongau and the Pass Lueg and the Salzburg basin

into the Flachgau and the near Bavaria. While the Riß extent of the glacier was larger than the

extent of the Würm glacier, the later one had a direct influence on today’s landscape which

will be formed approximately as follows: During the advance phase and the movement down

the valleys the glacier(s) have a high erosional potential and they transport all valley floor

sediments deposited by the rivers before. These sediments will be transported within, on and

under the glacier until it reaches its maximum extent where it’s stagnant phase leads to the

accumulation of end (or terminal) moraines which are elongated walls in front of the glacier

tongue. During the melting phase and some smaller re-advances the glacier accumulates

forms like drumlins (elongated hills made of loose sediment where the steep side is aligned

towards the glacier front), kames (dammed sediments, e.g. before endmoraines), eskers

(accumulations of fluvioglacial sediments from the glacier stream). Other prominent

landforms are kettleholes which emerge when ice bodies will be isolated for a longer period

than the glacier and sediments will be accumulated around this ice body. After ice melting

this process leaves a hole in the landscape. The whole melting phase of a glacier in general is

dominated by sediment accumulation. The Salzach glacier shows all of these landforms (e.g.

drumlin field of Eberfing) and reached its maximum advance stage in the Last Glacial

Maximum (LGM, approx. 21.000 years b.p.) when it accumulated large endmoraine wall

complexes in the region of today’s Neumarkt, Straßwalchen and Mattsee. Another important

relict of these glaciations are the lakes resulting from the melting phase which are supplied

with water until today (e.g. lake Obertrum, lake Mattsee, lake Wallersee). At the Eastern part

of the Salzach glacier one tongue flew into the catchment of Mondsee (into eastern direction)

where it collided with another huge glacier tongue sourcing from the Traun glacier which

flewed into western direction. The dimension of the Salzach glacier during the Würm ice age

is visualized in Fig. 1, while a more detailed explanation about the local situation in Koppl is

given in section 2.

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Fig. 1: Maximum Extent of the Salzach glacier at LGM during the Würm ice age (EGGER & VAN HUSEN 2009)

2 Study Area

The community of Koppl is located – separated by the prominent Gaisberg – about 8,5 km in

the East of Salzburg city. It can be reached from Salzburg via the valley “Guggenthal”, which

is located between the “Nockstein” and the “Heuberg”. Both Guggenthal and Nockstein play

also a significant role in the development of Koppl’s landscape. While Salzburg is situated on

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about 450 m, Koppl although only being 8 km away is situated on about 750 m. This huge

difference can be explained by the glacial past of the region. Although traveling from

Salzburg to Koppl means a major ascent in topography, but water from Koppl isn’t

discharging via the Guggenthal but into the basin of Thalgau. Both, the Koppl catchment

(approx. 6 km²) as well as the Thalgau basin belongs to the major Mondsee catchment. On the

other hand one glacier branch of the main Salzach glacier was able to flow during the Würm

ice age into the region of Koppl by overcoming this step in topography. The highest point on

this relief obstacle is called a transfluence pass, which means that a glacier flows from one

hydrological catchment into another one. This glacier was the Guggenthal branch in this case.

After overcoming this obstacle, the glacier flew into the Koppl subcatchment southwards on

the one hand and into the direction of Hof, Plainfeld and Thalgau on the other hand, where it

collided with the above mentioned Traun glacier branch. Some kilometres in the South of

Salzburg city near Hallein a second branch broke away from Salzach glacier and flew through

the “Wiestal” into the basin of Ebenau and during its maximum extent up to the edge of

today’s Koppl catchment. The tongue was located near Hinter- and Vorderschroffenau

(Southeast of Koppl). During melting this branch accumulated kames terraces next to the

usually occurring landforms (endmoraines etc.). Fig. 2 shows the study area from an

orthophoto with the venue of Koppl and some smaller villages which are important in the

discussion section (section 5) as well.

Fig. 2: Study Area and its extent in an overview map with some relevant villages

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3 Methods

To analyse the landscape of Koppl from a geomorphological point of view we use two distinct

approaches. The first method is a geomorphological mapping campaign which was performed

on two full days in December 2016, where most of the terrain within the study area has been

inspected. The result from this mapping campaign is a geomorphological map which can be

delivered as an analogous product or within a story map and a “leaflet” web map.

The second part of the project is the application of different methods to extract landforms

from digital elevation models. These methods are: 1. A Curvature analysis were an important

geomorphologic concept will be used for visualization of different curvature classes which

emphasize hilly landforms in combination with a hillshade visualization of the DEM. 2. The

residual/regional relief separation enables the enhancement of the DEM with a raster

calculation. 3. Object-based image analysis steps were executed to extract homogeneous

landforms based on their shapes. But also other landform parameters are used as input data.

3.1 Manual Mapping

The first method, the manual mapping campaign was performed according to the guidelines

of LESER & STÄBLEIN (1975). The geomorphologic mapping of the landscape type as it is in

Koppl is different to mapping actually glaciated valleys in high-alpine regions. In the mature

landscape of Koppl natural dynamics are much lower, while shapes are smoother and

processes occur in a weaker form due to smoothed shapes and missing relief. Although

mapping this region is important as it is an accumulation area of the Salzach glacier tongues

and these accumulations and the change of topography in the ice ages influenced the nature of

recent processes.

Nevertheless, some adaptions and compromises have to be undertaken for the

geomorphologic mapping as described in the following subchapters. LESER & STÄBLEIN

(1975) suggest to use a tripartition of the geomorphological mapping to describe the three

main elements: shapes, substrate and actually occurring processes. The first mapping step was

an overview inspection throughout major areas of the region to get an understanding of the

rough landscape configuration. Afterwards a more detailed mapping procedure was performed

where all important elements were mapped on a transparent paper (which is on top of an

orthophoto). As many areas as possible were mapped in this manner within the study area.

Due to the large size of approx. 6 km² only for the hydrological catchment, not every part

could be mapped, but we were able to map all important parts. To support the manual

mapping the most prominent shape elements were additionally measured with GNSS

technology.

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3.1.1 Shape

As the study area is a former glacier forefield the difference in mapping shapes compared to

high-alpine regions is not as large as mapping substrate or processes. On the contrary, many

shapes are not or hardly visible in high-alpine regions which can be detected in the region of

Koppl. The first step in our manual mapping campaign was the overview mapping containing

a first walk and excursion through the main parts of the study area. We started in the center of

Koppl underneath the church and walked over the landscape around this center, have past the

village Willischwand and returned via Schnurnn to Koppl center. Afterwards, we to the

highest parts above the center and to the Rettenbach creek before inspecting the region south

of Koppl via Gaisbergau to Aschau. At the end of the first day we came to see the landscape

near the villages Hinterschroffenau and Haberbichl and we ended with the Eggerhäuser and

Ladau. During this overview campaign we mapped all prominent and clearly distinguishable

landforms by drawing them as polygon, line or point shapes on a transparency paper which

was underlained by a DEM hillshade and an orthophoto. The second day on the one hand was

used to measure the positions of the most prominent landforms via GPS with a receiver from

Trimble (7 Series) having a spatial resolution of approximately 30 cm. In the highly-forested

areas the satellite signal was to poor as the initialisation process often failed. In the processing

step we therefore used the uncorrected positions to have a higher quantity while losing spatial

accuracy. On the other hand further manual mapping walks have been executed, which led us

mainly to the forested areas between Willischwand and Eggerhäuser and the slopes of the

Gitzenberg. Only the relatively flat area in the North of the main road to Hof

(Weilmannschwand) and the upper part of Winkl had to be skipped. This mapping campaign

was feasible by the detailed informations of HAMMER (1930), DEL-NEGRO (1963) and

MENEWEGER (1993).

3.1.2 Substrate

As Koppl’s landscape has been deglaciated already about 20.000 years ago, a thick soil cover

could be developed since then. Mapping the substrate of actual glacier forefields means to

map the grain size distribution in the area (e.g. areas dominated by boulders or sand etc.). This

is hardly possible in the study area due to the soil coverage. Furthermore, vertical outcrops

which excavate glacial sediments are scarce or in poor conditions. To get an acceptable result

for the geomorphological map we used the soil map as the substrate layer (alternatively with

an existing geology layer in the story map) in combination with the information from one

outcrop we found next to the Rettenbach some hundred metres southeast of Koppl center. The

Rettenbach there flows in an approx. 10 m deep canyon and erodes the slopes on its sides at

some positions. One of these positions is an undercut slope of the Northern slope where whole

vertical extent has been eroded. This erosion bank has been used as an outcrop to collect

geologic informations. 1. An overview sketch with orientation and scale has been produced. 2.

A two-metre-long profile along the slope has been measured and marked with a folding rule.

Beginning at the upper end of the profile the dominant grain-sizes have been measured and

the distribution along the profile has been recorded in a respective plot. 3. Along the profile

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overall 74 particle samples (one after the other) have been collected. The following

parameters of the particles have been determined: The grain size of the mean axis (b-axis), the

lithology, the roundness and the sphericity. The roundness of a particle will be determined on

a scale with 6 classes between “very angular” and “very rounded” (see Fig. 3). The

assignment to any class has been estimated for each particle. The sphericity describes the

shape of the particle and gets classified into 4 classes (A, B, C and D), while each class differs

from another regarding the relations of the three particle axes (see Fig. 4). After determining

all parameters photographs of the outcrop has been taken to have visual evidence for the

collected informations. To summarize the informations from the samples, descriptive statistics

have been used.

Fig. 3: Degree of Roundness classes (GEODZ 2010)

Fig. 4: Sphericity in four classes (FREIE UNIVERSITÄT BERLIN 2017)

3.1.3 Process

Current processes are much versatile in high-alpine regions than in old, mature glacier

forefields like that in Koppl. Whereas the first landscape type is often prone to processes like

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avalanches, debris flows, rockfalls or eventually periglacial processes, they can’t be found in

Koppl. Here, this mapping element is limited to fluvial/hydrological processes like erosion

(different types), discharge and wash-out through streamlets and channels. Thus, as many

streamlets as possible have been mapped manually within the study area. While not all of

them are possible to map (some of them are not even visible), we performed an intermediate

step to extract the theoretical distribution of these streamlets based on the digital elevation

model. This step is a part of the runoff analysis, where – based on the sink-filled DEM – the

flow directions are determined and based on that, flow accumulation is calculated. This means

that cells which are located at the lower areas of a catchment within a channel have high

accumulation flow values and vice versa. With a suitable visualization and especially with a

suitable choice of the lowermost class threshold one can illustrate the theoretical distribution

of the streamlets. By summarizing these classes into two classes (e.g. streamlet and non-

streamlet) and by converting the raster result into a polyline shapefile one can extract these

streamlets as line features. Additionally, the areas where different kinds of erosional processes

occur, have been manually mapped as point features.

For hydrological studies, we also compared the extent of the catchment which is defined in

the available layer with a calculated catchment based on the DEM. This has been calculated

based on the Watershed tool in ArcGIS. Therefore, the flow direction as input and a pour

point at the lowermost part of the subcatchment is needed.

3.2 Landform Extraction from DEM

Next to the manual mapping (GPS and field trip), an image analysis section for delineating

glacial forms was applied. This was done with GIS methods and Remote Sensing. In GIS, a

curvature calculation was carried out next to a Regional Relief Analysis. As a Remote

Sensing method, Object Based Image Analysis (OBIA) was chosen. Further explanations and

the results are provided in the next three chapters.

3.2.1 Curvature

The first type of automated landform extraction is curvature analysis. This means that the

landscape is investigated in matters of convex and concave shapes. To make this distinction

more accurate for a surface analysis we had to distinguish at first in profile and plan

curvature. Profile curvature is aligned parallel to the slope and shows the direction of the

maximum slope. Is the area more like a convex shape it is called also a negative profile

curvature. In contrast to a concave shape, here we speak about a positive profile curvature. A

flat surface would go with the value of zero, see Fig. 5 (ESRI 2017).

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Fig. 5: Profile Curvature in a systematic form (ESRI 2017)

Next to this plan or horizontal curvature is defined normal to the maximum slope. A positive

plan curvature indicates that the surface is lateral convex, while a negative horizontal

curvature means that the area is lateral concave. A value of zero again represents a linear

surface, see Fig. 6 (ESRI 2017).

Fig. 6: Plan Curvature in a systematic form (ESRI 2017)

To perform these calculations the execution of the tool “curvature” is necessary. The output

will be a raster for the overall, profile and plan curvature. To make the calculation more

accurate the concept of curvature of DIKAU (1996) is added. He introduced nine curvature

classes by combining profile and plan curvature. The following graph shows the nine classes:

Fig. 7: Landform classification according to curvature classes (DIKAU 1996)

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For example, in the first row we consider convex plan curvature and combine it with very

type of profile curvature. In the upper left corner, we can see the resulting shape if both

curvature types are convex (1). In the middle straight profile curvature was added to convex

plan curvature shapes (2). Thirdly concave profile curvature was combined with convex plan

curvature (3). This procedure is applied for plan straight and concave curvature as well. As a

result, we have nine classes (see Fig. 7). Additionally, we have considered flat terrain as a

tenth class. To perform this analysis in ArcMap we have to classify profile and plan curvature

into convex, concave and straight terrain. Secondly, we have to calculate the combinations

within the raster calculator. For our calculation we used a 10m DEM of the study area.

3.2.2 Residual/Regional Relief Separation

Residual or regional relief separation is another possibility of processing a DEM. By this

analysis, a regional DEM is created that is more an enhancement of the source data than an

extraction. Basically, the surface gets smoother. This is done by calculating the mean value

out of a certain number of cells. For example, this could be a 1km x 1km moving window. For

the new grid, every cell is attached with the mean value of all the cells within the 1km x 1km

sliding window. So, no cells are deleted or combined, just new values are added. Afterwards

the regional DEM is subtracted from the original one. Finally, all prominent positive and

negative relief forms are highlighted. As optional second part another moving window can be

processed on the regional DEM, to eliminate spatial inconsistencies and mitigate saturation

problems (HILLER & SMITH 2008). In our analysis, a moving window of 100m x 100m on

10m DEM was used. For a better visualisation we used a hillshade.

Fig. 8: Principal of the Regional Relief Separation (HILLER & SMITH 2008)

Figure 8 shows an exemplary regional relief from the study of HILLER & SMITH (2008). Here

we can see the smoother relief, with reduced local maxima and minima.

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3.2.3 Object-Based Image Analysis

The third automated method is based on Object-Based Image Analysis (OBIA). The challenge

was to perform an OBIA analysis with a DEM to extract landforms Usually OBIA is done

with aerial images. An object based approach is more suitable because with grid cells it is not

possible to cover entire objects (see Fig. 9). Next to this a suitable scale has to be found,

where objects are not delineated too rough or too detailed (DRAGUT & EISANK 2011).

Fig. 9: Cell-based vs. Object-based landform analysis (DRAGUT & EISANK 2011)

Generally, three steps have to be executed to extract landforms. First of all, a multi resolution

segmentation has to be done (see Fig. 9). Within a multiresolution segmentation pixels are

summarized to growing regions until they fall below a certain degree of homogeneity. With

the scale parameter the size of the objects can be controlled. Shape and Compactness are

additional parameters for designing the objects (STRASSER 2011). Secondly, a knowledge-

based classification is undertaken and as last step accuracy assessment has to be conducted

(D'OLEIRE-OLTMANNS et al.). For comprising our analysis, we used the workflow STRASSER

(2011) used in his master thesis. The object delineation is not done by the factors shape and

compactness. Rather the information of terrain parameters is preferred. Therefore, a curvature

and a slope raster were calculated out of DEM and important into eCognition (STRASSER

2011). Another possibility for extracting landforms goes with the estimation of scale

parameter tool (ESP-tool). It helps to calculate multiple segmentation levels. This is

necessary, because of the different sizes of landforms, one level is not always sufficient

(D'OLEIRE-OLTMANNS et al.). For our analysis we followed the three steps declared above. As

parameters we used a value of 0.1 for shape and compactness and a scale parameter of ten. In

addition, we wanted to test an algorithm with the ESP tool. Due to the big extent of our study

area it has not worked.

4 Results

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In this section all outcomes will be presented according to the same structure. The results can

also be viewed in the story map in ArcGIS Online where the geomorphological map is

embedded as an interactive map where the user can zoom in and out and where it is also

possible to click onto certain features while a pop-up appears for more information and

eventually including a photograph. In the subchapters some words are spent to describe the

final results and which observations have been made.

4.1 Manual mapping results

The main output from the manual mapping campaign was the geomorphological map

including all three elements, the shapes, the substrate (soil in this case) and the processes.

Regarding the shapes, all manually mapped landforms are presented within the map (in black)

and all landforms measured with GPS as well (in red). The digital version of the final

geomorphological map can be seen in Fig. 10. While the description of mapped shapes can be

seen in section 4.1.1, results regarding the substrate are written in section 4.1.2 and those of

the processes in 4.1.3.

Fig. 10: Geomorphological Map of the Koppl region with shapes, substrate and processes

4.1.1 Shape

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The most prominent geomorphological element are the shapes and especially the long and

clearly comprehensible endmoraine walls are central in the map. It is visible that one major

wall takes course from the east side of the Nockstein via Eggerl to Koppl and creates then an

arc-shaped landform via the Northern parts of Haberbichl to the Gitzenberg and further in

direction to Ladau. On the ridge of this wall in vicinity of Haberbichl numerous kettleholes

are located on the edge of the forests. Further prominent endmoraine walls can be found just a

few metres in southern direction. In the western part of the study area an s-shaped endmoraine

wall is located between Koppl and Gaisbergau. Next to this wall a kettlehole with a small

sedimenting lake was found. A few metres northeast of these landforms another row of

endmoraine walls can be detected which take course – with some interruptions – to Koppl

where it nearly touches the northern endmoraine wall. From here on the walls go side by side

until Haberbichl where the southern wall has been penetrated by the Rettenbach creek which

is canalized between the two endmoraine walls above Haberbichl. From Haberbichl eastwards

the endmoraine walls are only slightly visible at some locations, whereas the distance to the

northern endmoraine wall is increasing. It was clear and exciting to see different rows and

levels of walls regarding this southern part. Another smaller endmoraine wall was found on

the eastern side of Willischwand where it curls throughout the landscape. Further shapes

which have been identified are drumlins. One of them is located in the east of Aschau, another

one some metres in the west of Eggerhäuser. One landform shows clear evidences to be a

drumlin between Willischwand, Schnurnn and Koppl. Three eskers could be found in the

study area: Two very large and prominent ones in the southern, forested areas of Aschau, a

third one might also be a kame but due to its elongated shape we suggest the definition of an

esker. It is located next to the northern endmoraine wall between Koppl and Haberbichl. One

very large and distinct kame has been found north of Willischwand where a small moraine

wall joins the kame eastwards.

Some examples of these have been reported by photographs during the mapping campaign. A

collage of some photos is illustrated in Fig. 11.

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Fig. 11: Photographs of visually detected landforms in the study area

4.1.2 Substrate

The map contains also the substrate which relates to the soils covering the glacial sediments in

this case. It shows that dominant soil types are brown soils and gleys of different

compositions and properties. These properties are mainly relating to the content of limestone

within the soil. The final result of the outcrop next to Rettenbach which cut into the slope of

the northern endmoraine wall are illustrated in the upcoming figures. While Fig. 12 shows the

location and the environment of outcrop in sketch drawed in cross section, Fig. 13 shows the

grain-size distribution of the dominant particles along the profile. The sample statistics are

summarized in the graphics in Fig. 14.

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Fig. 12: Overview sketch of the outcrop in cross section

Fig. 13: Profile and grain-size distribution along the profile

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The grain-size distribution along the profile shows that there are no real patterns or clusters

which means that the material is very unsorted and no stratigraphy can be determined. The

particles are embedded in a very fine-grained (silt to sand) matrix which appears sticky and

muddy.

Fig. 14: Descriptive statistics of the 74 samples; a) shows the grain size frequency within a boxplot, b) shows the frequency

of lithology types, c) illustrates the variations in the roundness degree, d) sphericity types

Over the 74 collected sediment particles the median grain size is approx. 20 mm, but ranging

from less than 10 mm up to about 115 mm. Two lithology types are dominated the samples

namely limestone and dolomite with more than 80% of all particles. A special view on the

roundness of the samples show that the particles are quite angular or maximum slightly

rounded, only few of them are really rounded. Looking on sphericity type C is the dominating

class which means that all axes have different lengths, thus the particle is elongated but not

restiform.

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4.1.3 Process

As mentioned in section 3.1.3 the mapped processes are limited to erosional processes and

flow paths of streamlets. The first ones are mapped manually as point features (see Fig. 10).

The result from runoff analysis for detecting the theoretically occurring flow paths of

streamlets is shown in Fig. 15. Classification has been tried with several thresholds regarding

the lowermost value class. The final visualization was fixed with a threshold of 200. The flow

paths of the streamlets with this threshold seemed to be suitable when comparing them with

the manually mapped streamlets.

Fig. 15: Extraction of theoretical flow paths

The comparison of the catchments (layer catchment vs hydrological catchment via watershed

tool) can be found in Fig. 10. It shows that it matches quite well but some two areas show

significant differences. One is located on the Northeastern slopes of the Gitzenberg and the

second area is located around the houses of Schroffenau.

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4.2 Landform extraction results

Chapter 4.2 presents the result of the automated landform extraction. There will be one

section for each methodology.

4.2.1 Curvature

The next map (Fig. 16) shows the result of the curvature calculation according to Dikau. The

legend was covered in those colours that figure out best the shapes. To underline them a

hillshade was added below the curvature layer and it was set to a transparency of 50%.

Fig. 16: Landform enhancement via curvature analysis

With the explained settings the map helps to emphasis prominent landforms. On the one hand,

it shows valleys (blue colour) on the other tops of the surface (white colour). The reason for

that is that mostly valleys have a concave and tops a convex shape. Next to this general

remark the coloured circles and ellipses can help to figure out glacial features. We can pretty

well distinguish compact forms like the esker in the south-western in Aschau. Next to this the

Drumlin at Willischwandt is identifiable. The very prominent moraine of the

Guggenthalbranch that designed the catchment of Koppl is observable as well. By starting in

the blue ellipse, it is easy to follow it in the western direction to the village of Koppl and

finally to the foothills of the Nockstein in the west. Unfortunately, not all features could be

delineated satisfactorily. This is valid for the area in the orange ellipse in the eastern part of

Willischwandt. Here it is hard to see shapes like the endmoraine of later position of the

21


glaciertongue and the kame. A reason for this might be that the surface is modified through

agriculture. We can only see the shapes roughly. For the yellow ellipse, the situation is the

other way round. Many shapes could be detected, so a bit of uncertainty stays how to define

the shapes. It is possible to figure out the “S-shaped” moraine in the left part of the ellipse, but

hard to distinguish between the endmoraine of the Wiestalast and the kame terraces. As the

resolution of a 10m DEM is too rough, it is not possible to see kettleholes. By trying the

curvature calculation with a 1m DEM, it was neither feasible to figure out kettleholes, nor any

shapes, because the resolution was to fine. This indicates that there might by an optimal

resolution that has to be approached by an iterative process.

4.2.2 Residual/Regional Relief Separation

The next figure (Fig. 17) shows the hillshade of the regional relief separation. Valleys are

coloured in black and tops of the surface are given to a white colour.

Fig. 17: Landform enhancement via Regional Relief Separation

Similar to the curvature calculation the esker in the south-western part in Aschau can be

figured out properly (black circle). By looking at the area of Willischwandt (red circle) we

can distinguish between the landforms really well. We can see the drumlin, the kame, the

moraine next to the kame and the other moraine of a later position of the glaciertongue around

the eastern side of Willischwandt. By focusing on the endmoraine of the Guggenthalbranch,

we see that it is perfectly visible until the village of Koppl by starting in the blue ellipse. From

22


Koppl to the foothills of the Nockstein it is harder to see the moraine, but still possible. A

reason might be the flat terrain in the west of the moraine. In the part from Koppl to the blue

ellipse the moraine is steep on both sides. The fine black dots in the blue ellipse may be

kettleholes, but generally the detection of all kettleholes was not possible. Concerning

resolution, we have the same situation like in the curvature chapter. The yellow ellipse shows

the glacial shapes of the Wiestalbranch. We can roughly distinguish between the “S-shaped”

moraine, the kame terrace in the middle of the ellipse and the endmoraine that nearly touches

the endmoraine of the other branch in the upper part of the ellipse.

4.2.3 Object-Based Image Analysis

The result of the landform delineation with OBIA is displayed in the next image. Grey

polygons show shaped features according to the input layer (Slope and Curvature raster).

Green areas thus show flat terrain.

Fig. 18: Landform extraction with object-based image analysis

Figure 18 shows a clipping of the OBIA result. It contains a good visualisation of the two

endmoraines from the Guggenthal- and the Wiestalbranch. The features at Willischwandt are

distinguishable too. We can see the drumlin, the kame with the moraine on the right side and

the two parts of the endmoraine of a later position of the glaciertongue. The reason for the

23


interruption might be the agricultural background of the area. Next to this we can delineate

the “S-shaped” moraine in the south-western and the kame terrace in the southern part (long

grey area below the moraine).

Fig. 19: Limits of landform extraction via OBIA

Unfortunately, we were not able to distinguish the esker. Our algorithm is only able to

distinguish between forms and flat terrain. As the esker is part of the foothills of the Gaisberg,

the terrain around it is shaped too, so it could not be delineated. We only could exclude too

elevated features with the information of the DEM (see Fig. 19).

5 Discussion

With the help of these results one can better reconstruct the situation at the LGM during the

Würm ice age and thus it is possible the get informations about the landscape configuration in

the study area. The northern endmoraine wall between Eggerl and Ladau (via Koppl and

Haberbichl) was accumulated by the Guggenthal branch which flew on the north side of the

Nockstein and southwards into the Koppl subcatchment. From the south the Wiestal branch

advanced up to Koppl and accumulated the southern endmoraine walls. Between Koppl and

Haberbichl these endmoraine walls were dammed by the other one, the glacier tongues nearly

touched each other. While the Guggenthal branch melted, it accumulated the esker between

Koppl and Haberbichl and many kettleholes along the endmoraine wall emerged. At a later

stage the glacier re-advanced and built the moraine of Willischwand. The kame north of

Willischwand as a dammed sediment has been accumulated in one of the melting phases. The

other shapes in the north (drumlins, groundmoraine) of the large endmoraine are built

subglacial and could be accumulated either during the advance or the melting stage. All in all,

the whole area north of the endmoraine wall but belonging to the catchment is made of

groundmoraine or special accumulations. The groundmoraine sediments are also called till

24


and will be accumulated in an unsorted way with grain sizes from clay up to boulders

(erratics). Many stones in moraine material show scratches which came from the interaction

between the particles and the glacier ice. One example of these scratched till could be found

in the smaller endmoraine of Willischwand (see Fig. 20). Comparing the soil map with the

fact that most of the catchment is covered by till results in a high significance due to the fact

that mainly brown soil will be developed from glacial till. This matches well with the results

from the outcrop analysis, although no scratched till was found there. First, a high variation of

grain size has been determined which matches with the fact that till is usually unsorted. From

the samples, mainly limestones and dolomites were identified which means that most particles

source from the Northern Calcareous Alps only some kilometres in the south of the study

area. The degree of roundness shows that most particles are hardly rounded with more angular

texture. This means that the sediment was mainly transported within the glacier, while fluvial

transport would result in rounded shapes. Also, the fine grained matrix of the outcrop’s

material attests to a typical glacial accumulation.

Fig. 20: Scratched till from the endmoraine of Willischwand

The region south of the two great endmoraine walls is more complex while the landforms are

not as clearly visible as in the northern section. The three rows of endmoraine walls are still

comprehensible, which means that the glacier has shown three advance phases. In the area

between Koppl and the steep slope down to Pertill (next to Ebenau) some levels of terraces

can be detected, these are those kame terraces mentioned in MENEWEGER (1993).

Interpretations regarding the area between Haberbichl and Schlag are more difficult, although

one is able to recognize two rows of endmoraine walls. According to MENEWEGER (1993)

these endmoraine walls are intensively incorporated into the kame terraces and thus, their

shapes are smoother than in the western part of the study area. A special situation can be

25


found in Winkl, which is the area between the Gaisberg, the Nockstein, the Klausberg and the

catchment of Koppl. The main part of this area wasn’t covered by glaciers during the Würm

ice age but the whole Winkl was covered by ice during the Riß ice age. Large portions of

Winkl’s area is made up of a prominent peat bog which developed during the Würm ice age

as a lake was retained by the glaciers. Before and during the Würm ice age Winkl was

discharged via a small channel southeast of Gaisbergau down to the Ebenau basin (via Pertill).

Since the LGM the situation changed: Glaciers melted and the discharge of Winkl

(represented by the Rettenbach) flew into the direction of Koppl and canalized between the

freshly accumulated endmoraine walls. Here, intense erosion processes occur while the creek

meanders down to Haberbichl where Rettenbach penetrates through the southern endmoraine

wall and flows than over the Plötz fall to the Ebenau basin. Near Aschau which is located in

Winkl two large eskers can be cound. MENEWEGER (1993) found out that these forms were

accumulated during the Riß ice age although DEL-NEGRO (1963) identified them as

endmoraine walls of a small glacier tongue during the Würm ice age.

Concerning the automated extraction there was no algorithm or tool that managed to delineate

every single glacial form in the catchment. While the curvature extraction has its strength on

compact forms like drumlins and long clear moraines, the residual relief analysis points out

better the forms around Willischwand and less good the Guggenthalendmoraine from Koppl

to the foothills of the Nockstein. OBIA can focus on forms only when they have clear outline

and flat terrain next to them. For this reason, the esker in the south-western is no more visible

because there is mountainous area next to it. Hard to delineate for all the three methods was

the part of the endmoraine of the Wiestalbranch. The reasons are the big amount of forms in

this area like kame terraces and moraines with excrescences. Distortions in the analysis may

also occur due to the agriculture on the area and disformations of the original landscape. This

happens especially at Willischwand, where the kame and the endmoraine was hard to detect

for the curvature analysis. OBIA could at least figure out the kame with its moraine. Both

shapes were distinguished in the residual relief analysis, because the terrain got smoother and

so the distortions of the agriculture are eliminated.

26


6 Project Management

To design our project management, we created an abstract, an extended abstract, a Gantt-

chart, a PERT diagram and a risk management matrix. The abstracts were only about the

basic idea of our project and did not contain any plans how to manage it. This was done by

the Gantt-chart (Fig 22) and the PERT diagram (Fig 21). While the PERT diagram only

includes our work packages, the Gantt chart also donates information about the timing during

the project. They are: 1 project coordination and management, 2 geodata acquisition, 3 data

processing, 4 representation and visualisation, 5 interpretation of mapping, GIS analysis and 6

modelling and documentation. While coordination and management tasks took place in the

whole project, all other duties were executed after each other. Principally the time plan went

well until January. In January parts of phase 4 and tasks 5, 6 had to be completed. This is too

much effort for one month. In another project, we would start earlier with the GIS analysis

and modelling steps. A reason for this might be that I took a while to take off with the project,

because we had to clarify what exactly we want to do. Detailed information about the Gantt

chart can be found in the belonging Figure 22. Here different steps within the section

explained above are visible. The transparent dots indicate milestones during the project, the

solid one’s assignments and submission dates.

Fig. 21: PERT diagram from the present project

27


Fig. 22: Gantt-chart from the present project

28


7 Conclusion & Outlook

Finally, our result s give a good overview of the landscape configuration in Koppl. It should

be a good basis for further investigations. This could be an improvement of our methods

especially the automated ones, because there are weaknesses for each one concerning the

results. For example, one could look for the perfect resolution concerning a curvature

analysis for a hilly terrain. Concerning regional relief analysis there is also an ideal value to

find. In this case this has not to do with resolution, but with the optimal grid cell size. Will

there be more accurate results for a 50m x 50m grid than for a 100m x 100m. Thirdly de

OBIA algorithm could be expanded in order to exclude non-glacial features that are only part

of foothills. More extensive analysis can be found in the paper of Dragut & Eisank and Dragut

et al. concerning the utilisation of the ESP-tool. Next to these technical items the result can be

used for applications. As we announced in our abstract our analysis should be the basis for

actions and application to prevent the regions of Koppl from natural hazards. Therefore, a

closer look at the soil would be necessary. Our geomorphologic map would be basis for that.

By talking about floodwater events, it will also be necessary to talk about the extended

catchment that was calculated with a watershed. This indicates that the amount of the runoff is

larger. For flood prevention, it is also necessary to know the inverted drain in the

Wiestalbranch, where the water flows back into the direction where the glacier came from.

Finally, we can state that the complex glacial environment has many impacts on the

hydrology that have to be considered.

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Nr. 14, Salzburg.

DIKAU, R. (1996): Geomorphologische Reliefklassifikation und -analyse. In: Heidelberger

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D'OLEIRE-OLTMANNS, S. et al.: An Object-Based Workflow to Extract Landforms at Multiple

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HAMMER, W. (1930): Jahresbericht der Geologischen Bundesanstalt für das Jahr 1929. In:

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HILLER, J. K. & SMITH, M. (2008): Residual relief separation: digital elevation model

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LESER, H. & STÄBLEIN, G. (1975): Geomorphologische Kartierung - Richtlinien zur

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OBIA, basierend auf Laserscan DHMs - Eine Studie im alpinen Untersuchungsgebiet

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