Understanding the Frequency and Magnitude of Debris Flows on Alpine Talus Slopes Hérens Valley and Col Du Sanetsch (Switzerland)

Understanding the frequency and magnitude of debris flows on Alpine talus slopes Hérens Valley and Col du Sanetsch (Switzerland)

Word count: 18 729

Annelies De Bruyne Student number: 01307441

Supervisor: Dr. Amaury Frankl1 Advisor: MSc. Hanne Hendrickx1, Local supervisor: Prof. dr. Reynald Delaloye2 1Department of Geography, Faculty of Science, Ghent University 2Department of Geosciences, Faculty of Science, University of Fribourg

A dissertation submitted to Ghent University in partial fulfilment of the requirements for the degree of Master of Science in Geography.

Academic year: 2017 - 2018

PREFACE

Writing and working on the dissertation has been a very enriching experience to me. The fulfilment of the dissertation could not have been possible without the support of many people. First of all, I would like to thank my supervisor, Dr. Amaury Frankl, my advisor, MSc. Hanne Hendrickx and the local supervisor Prof. Dr. Reynald Delaloye for the opportunity to carry out the dissertation in the Swiss Alps. They played an important role in the setup of the whole dissertation. Their feedback and instructions were crucial to accomplish this document.

Secondly, I would also like to express my gratitude to Bart De Wit and Britt Lonneville for their technical support during the drone campaign. I would also like to thank my family, mountaineering friends and fellow geography students for encouraging me during the five weeks of field work in Switzerland and afterwards when starting to write the thesis.

Hopefully, more future students will also see the potential of working and studying in the geomorphological rich environment that is offered by the Alps.

TABLE OF CONTENTS POPULARIZED TEXT ...... 5

SUMMARY ...... 6

SAMENVATTING ...... 7

1. INTRODUCTION ...... 8

1.1 General introduction ...... 8

1.2 Geomorphological characterization of debris flows and related phenomena ...... 8

1.3 Triggers and factors influencing magnitude and frequency ...... 9

1.3.1 Climatic factors and triggers ...... 10

1.3.1.1 Intense rainfall and antecedent rainfall ...... 10

1.3.1.2 Rapid snowmelt and antecedent snowmelt ...... 10

1.3.1.2 Temperature ...... 11

1.3.1.3 The response of ice and snow bodies ...... 11

1.3.2 Geomorphic factors ...... 11

1.3.3 The impact of catastrophic events ...... 12

1.4 Temporal pattern of debris flows: the return period and debris flow season ...... 13

1.5 The sediment budget ...... 14

1.6 Magnitude-frequency relation and representation ...... 16

1.7 Impact of climate change on debris flow activity ...... 16

1.8 Objectives and research questions ...... 17

1.9 About the upcoming dissertation ...... 18

2. STUDY AREA ...... 19

3. METHODOLOGY AND DATA ...... 23

3.1 3D modelling using aerial and terrestrial images ...... 23

3.1.1 Preparation of the field surveys ...... 23

3.1.2 Acquisition of UAS images ...... 26

3.1.3 Assembling of terrestrial images...... 27

3.1.4 Producing DEM and orthophotomosaics ...... 27

3.2 Estimating the magnitude of debris flows ...... 28

3.2.1 Volume based on the volume – inundated area relation ...... 28

3.2.2 Grain size analysis ...... 32

3.2.3 Volume measurement based on morphometric properties ...... 33

3.2.4 Magnitude estimation based on descriptive properties ...... 34

3.2.5 Volume measurement based on a DEM ...... 36

3.3 Determining the frequency...... 36

3.4 Map creation ...... 37

3.5 Tracing the possible lime content of debris flow deposits ...... 38

4. RESULTS ...... 39

4.1 Frequency ...... 39

4.2 Magnitude ...... 45

4.2.1 Case study: comparison of different volume measurements and geomorphology ...... 46

4.2.1.1 Hérens Valley research sites ...... 49

4.2.1.2 Col du Sanetsch research site ...... 58

4.2.2 Volume-area relations in Val d’Hérens ...... 63

4.3 Magnitude-frequency relation in Val d’Hérens...... 65

5. DISCUSSION ...... 66

5.1 The use of a UAS in Alpine mountain environment ...... 66

5.2 The applicability of volume measurements for debris flow deposits in the field ...... 66

5.3 Frequency via aerial pictures towards other methods ...... 68

5.4 Possible explanations for the observed magnitude-frequency pattern ...... 68

5.2.1 Climatic factors ...... 68

5.2.2 Geomorphic factors ...... 71

5.2.3 Catastrophic events ...... 72

6. CONCLUSION ...... 73

7. REFERENCES ...... 74

7.1 Scientific Articles ...... 74

7.2 Internet sources and other ...... 77

7.3 Software ...... 78

8. ANNEXES ...... 80

8.1 Annex 1: GPS measurements ...... 80

8.2 Annex 2: Agisoft Photoscan workflow and final data ...... 80

8.3 Annex 3: ArcMap and QGIS workflow to calculate the deposited volume ...... 80

8.4 Annex 4: Map data and creation ...... 81

8.5 Annex : Temporal changes in number of debris flow events...... 82

8.6 Annex 6: Field measurements and derived charts ...... 82

8.7 Annex 7: Weather data ...... 82

POPULARIZED TEXT

A debris flow is a landform that typically occurs on steep slopes in mountain areas. They are generated due to a mass movement of loose debris mixed with a huge amount of water. This water can originate from a severe rainstorm, dam breaks or other sources causing a sudden and rapid release of a lot of water. Debris flows can be recognized in the field by their incised channels which are terminated by a lobate shaped deposit. In this dissertation, the frequency and magnitude of debris flows are studied. The frequency points to how often a debris flow is produced on the same place. The magnitude refers to how much material is being moved and is expressed in volume m³. For this research, 64 debris flows were examined in the canton of Valais, Switzerland. Six of these were visited and studied in detail, while 58 others were analysed using aerial photographs. Debris flows can be dangerous, because they tend to damage buildings, roads and other infrastructure, and even endanger human lives.

SUMMARY

Debris flows are a landslide type that occur in regions with a steep relief and that move lots of sediment at a very high velocity due to a sudden release of huge amounts of water. Debris flows are very dangerous geomorphological phenomena as they have already caused severe damage to infrastructure and threatened human lives. On the field, they can be recognized by incised channels, gullies or cascades, flanked by levées and a deposition fan with a lobe structure. Their occurrence is influenced by climatic factors, geomorphic factors and catastrophic events. Furthermore, climate change has an impact on debris flow activity. In this dissertation, debris flows in the Hérens Valley and Col du Sanetsch, in the canton of Valais, Switzerland, are studied from the perspective of frequency and magnitude. The frequency is a measure for how often a new debris flow event is produced, while the magnitude determines the amount of debris being deposited in m³. Six debris flows were visited in the field, while 58 others were analysed remotely. To determine the frequency, a dataset of historical aerial pictures was examined in detail to detect changes in the debris flow geomorphology. For the magnitude, five methodologies were applied: (1) the volume-inundated area relation, (2) grain size analysis, (3) morphometric properties method, (4) descriptive properties method and (5) volume measurement based on a Digital Elevation Model (DEM). The first method was applied on all the debris flows. (2), (3) and (4) were applied on the visited debris flows and (5) was only carried for the debris flow at Col du Sanetsch. For (5) a Unmanned Aerial System (UAS) was used to map the debris flow and obtain a DEM. For the visited sites, time-depth maps were created as well. When looking at the frequency, it seems that most debris flow produced one to two events since the start of the monitoring on aerial pictures. The monitoring time and the detection of the first occurrence of a debris flow highly depend on the availability of aerial pictures for each individual flow. A trend in overall debris flow activity over time, has been discovered. Some striking rises in activity were linked to severe precipitation in whole of Switzerland and locally. The field measurements of the magnitude showed a significant variation for each of the individual visited debris flows. This is due to different assumptions and interpretations of the extent of the debris flow deposit. Also not all methods could be applied in the field. From the magnitude measurements of all the debris flows, can be concluded that most flows belong to a size class 2 or 3 in Jakob’s classification.

SAMENVATTING

Debris flows behoren in de geomorfologie tot de grondverschuivingen. Ze kunnen grote hoeveelheden puinmateriaal aan een hoge snelheid verplaatsen ten gevolge van een plotse instroom van zeer veel water. Debris flows kunnen een gevaar vormen voor de maatschappij omdat ze schade kunnen aanrichten aan infrastructuur en mensenlevens bedreigen. Op het terrein, kunnen ze herkend worden aan een ingesneden kanaal, gullies of cascade met aan weerszijden opeenstapelingen van puin, genaamd levées. Op het einde van het kanaal is er een afzetting van het puinmateriaal met een typische lobstructuur. Het voorkomen van debris flows wordt beïnvloed door klimatologische factoren, geomorfologische factoren en catastrofes. Bovendien heeft ook klimaatverandering een impact op de activiteit van debris flows. In deze masterproef worden debris flows in het Val d’Hérens en Col du Sanetsch, beide gelegen in het kanton Wallis in Zwitserland, onderzocht vanuit hun frequentie en magnitude. De frequentie is een maat voor hoe vaak een nieuwe debris flow wordt geproduceerd, terwijl de magnitude verwijst naar hoeveel puinmateriaal wordt afgezet in m³. Voor zes debris flows werd veldwerk uitgevoerd, terwijl 58 andere werden bestudeerd aan de hand van luchtfoto’s. Om de frequentie te bepalen, werd historisch luchtfotomateriaal bestudeerd op mogelijk veranderingen in de geomorfologie van de flow. Om de magnitude te bepalen, werden vijf methodes toegepast: (1) de volume-inundated area relatie, (2) korrelgrootte-analyse, (3) een methode op basis van morfometrische eigenschappen, (4) methode op basis van beschrijvende eigenschappen en (5) volume berekening op basis van een Digitaal Hoogtemodel (DHM). De eerste methode kon worden toegepast op alle debris flows. (2), (3) en (4) werden toegepast op de bezochte sites en (5) werd enkel uitgevoerd voor de debris flow bij Col du Sanetsch. Voor (5) werd gebruik gemaakt van een drone om de debris flow in kaart te brengen en een DHM te berekenen. Voor de bezochte sites werden ook tijdsdieptekaarten ontwikkeld. Als we de frequentie in acht nemen, blijkt dat de meeste debris flows één of twee nieuwe afzettingen produceerden sinds het moment dat ze werden opgevolgd in de tijd. De periode dat een flow kon worden gevolgd en de eerste observatie van een flow hangen sterk af van de beschikbaarheid van luchtfotomateriaal voor elke individuele flow. In de activiteit van alle debris flows over de tijd heen, zit een bepaalde trendlijn. Sterke stijgingen in activiteit kunnen gelinkt worden aan zowel zware neerslagspieken in heel Zwitserland, als lokale neerslagspieken. De resultaten van de magnitude op het terrein vertonen enige variatie die waarschijnlijk te wijten is aan verschillende assumpties en interpretaties over de omvang van de afzetting. Lang niet alle veldmethodes konden worden toegepast. Voor de magnitudeberekeningen van alle debris flows kan worden afgeleid dat de meeste flows tot grootteklasse 2 of 3 behoren in de debris flow classificatie van Jakob.

1. INTRODUCTION

1.1 General introduction

Debris flow studies have become an integral part of geomorphological and climatological research (Bovis & Jakob, 1999; Glade, 2005). Due to its hazardous character in mountainous areas all over the world, the research plays an important role in risk-management (Bovis & Jakob, 1999; Glade, 2005; (Marchi, L., Chiarle, M., Mortara, 2009; Santi et al., 2011). A debris flow can be defined as follows: a debris flow is a landslide type that occurs in regions with a steep relief, and that moves lots of sediment at a very high velocity due to a sudden release of huge amounts of water (Bardou & Delaloye, 2004; Jakob & Hungr, 2005; van den Heuvel et al., 2016). In this definition, one can recognize the geomorphological and climatological aspects: on the one hand debris flows change the geomorphology by moving extensive amounts of material, on the other hand a good knowledge of precipitation patterns is necessary as precipitation is a major trigger causing debris flows (Jakob, 2005; Stoffel et al., 2014; Adams et al., 2016). This means that large amounts of water and a large volume of debris are the two major triggers causing debris flows. Regarding the risk-management, debris flows can be a menace to society because they cause damage to infrastructure and threaten human lives (Jakob & Hungr, 2005; Tang et al., 2009; Santi et al., 2011). Debris flows are able to transport huge amounts of sediment at a very high velocity (Theule et al., 2012). Hence, many studies have been dedicated to the debris flow’s occurence, magnitude, velocity, damage, prediction, research methodology and more (Iverson, 1997; Glade, 2005; Theule et al., 2012). Furthermore, the current climate change also influences rainfall intensities making the monitoring and predicting of debris flows a challenge for future investigations (Jomelli et al., 2009; Stoffel et al., 2014).

1.2 Geomorphological characterization of debris flows and related phenomena

Describing the geomorphological characteristics of a debris flow can be seen from two different perspectives: (1) the characteristics of the debris flow during the debris flow event and (2) the geomorphology after the debris flow passed by. The first perspective refers to the path and process of the debris flow and the second refers to how a debris flow passage can be recognized afterwards (for example in the field and/or on aerial images). Firstly, a general flow path of a debris flow can be divided into three zones: the initiation zone, the transportation zone and the deposition zone (Jakob & Hungr, 2005). A slope failure in the initiation zone sets the beginning of one or more debris flows (Jakob & Hungr, 2005; Brayshaw & Hassan, 2009). The area of debris flow initiation has a slope between 20° and 45° (Jakob & Hungr, 2005). Along the transportation zone, debris flows start their movement downslope. The movement of a debris flow can be described as one or multiple surges (Jakob & Hungr,

2005; Theule et al., 2012). Furthermore, this zone consists of channels, gullies and/or cascades (Jakob & Hungr, 2005; Theule et al., 2012). In this zone more loose material from the bed and bank of the channels, gullies and/or cascades can be carried away by the debris flow. This is also called debris flow bulking (Theule et al., 2012). Finally, the debris flow enters the deposition zone as the slope decreases and a loss of confinement is established (Jakob & Hungr, 2005). This deposition zone can be recognized as a deposition fan (Jakob & Hungr, 2005). Secondly, the geomorphology of antecedent debris flow be recognized by the characteristics of the transportation zone and the deposition zone. The initiation zone will not be taken into account as this zone is sometimes hard to determine (Jakob & Hungr, 2005; Griswold & Iverson, 2008). The transportation zone is defined by channels, gullies and/or cascades. Moreover, these phenomena can be flanked by levées (Glade, 2005; Theule et al., 2012). Levées are accumulations of debris along the channels. Also scour marks, mudlines and scars on trees can be recognized after debris flow activity (Stoffel, 2010; Stoffel et al., 2014). Moreover, large boulders can be noticed in the transportation zone (Jakob & Hungr, 2005; Theule et al., 2012). Furthermore, the deposition fan also has several typical geomorphological characteristics. The depositions have a lobe structure (Stoffel, 2010). On top of the fan apex more coarse and thick deposits can be discovered. The more downslope, the more fine debris will be deposited (Jakob & Hungr, 2005). A debris flow is sometimes hard to distinguish from other related phenomena, such as a debris avalanche or a debris flood (Jakob & Hungr, 2005). These three related phenomena, for instance, tend to have the same velocity. But a debris flood has a lower peak discharge than a debris flow and a debris flood includes a very high saturation and floating debris, which is not the case for debris flows (Jakob & Hungr, 2005). In the case of a debris avalanche, there are no channels along its path. A debris avalanche is also less saturated than a debris flow (Jakob & Hungr, 2005).

1.3 Triggers and factors influencing magnitude and frequency

When looking at the influencing factors and triggers, three categories can be determined: climatic factors and triggers, geomorphic factors and catastrophic events (Glade, 2005; Jakob & Hungr, 2005; Tang et al., 2009; Stoffel et al., 2014). Climatic factors include intense (antecedent) rainfall, rapid snowmelt, changing temperature and the response of snow and ice bodies (Bardou & Delaloye, 2004; Jakob & Hungr, 2005; Marchi et al., 2009; Stoffel et al., 2014; van den Heuvel et al., 2016). The geomorphic factors comprise in situ characteristics of the study area. The impact of catastrophic events such as earthquakes, vulcanic eruption, glacial lake outburst, typhoons, dam breaks, etc are described (van Steijn, 1996; Jakob & Hungr, 2005; Marchi et al., 2009; Tang et al., 2009). Climate change sensu latu is also an important factor as it has an impact on many influencing factors and triggers causing debris flows (Jomelli et al., 2009; Stoffel et al., 2014; van den Heuvel et al., 2016). Finally, it is also important to make a distinction between factors and triggers. Factors point to an indirect influence, meaning that they create favorable circumstances for a debris flow to happen (Jakob & Hungr, 2005; Jomelli et al.,

2009; van den Heuvel et al., 2016). While triggers point to two direct causes of debris flows: a sudden release of huge amounts of water and lots of debris (Jakob & Hungr, 2005; Jomelli et al., 2009; van den Heuvel et al., 2016).

1.3.1 Climatic factors and triggers

In the following sections climatic factors and triggers are explained. First, rainfall is to be considered followed by snowmelt. The last part explains the influence of temperature and the response of ice and snow bodies. These three sections altogether explain two debris flow triggers, namely intense rainfall and rapid snowmelt. Other influences are classified as debris flow factors: antecedent rainfall, antecedent snowmelt, temperature and the response of snow and ice bodies.

1.3.1.1 Intense rainfall and antecedent rainfall

Intense rainfall is interpreted as primary climatic factors by Jakob & Hungr (2005), but in this context it is a trigger. The intense rainfall can lead to high saturation of the soil (high pore water pressure) that starts flowing downslope in response to gravity (Iverson, 1997; Jakob & Hungr, 2005). It is the combination of excessive rainfall and duration of the rainfall event that can exceed the thresholds for triggering a debris flow (Jakob & Hungr, 2005; Stoffel et al., 2014). Rainfall thresholds are an important measure for a critical amount of rainfall needed to trigger a debris flow (Jakob & Hungr, 2005; Stoffel et al., 2014). However, the rainfall thresholds, the specific duration and intensity of rainfall generating debris flows vary from region to region (Jakob & Hungr, 2005). While intense rainfall is seen as a primary climatic trigger (direct impact on triggering debris flows), antecedent rainfall is interpreted as a secondary climatic factor by Jakob & Hungr (2005). Antecedent rainfall can temporarily by stored in the soil and regolith (Glade, 2005; Stoffel et al., 2014). In this way, antecedent rain serves as an extra source of water for debris flow triggering (Jakob & Hungr, 2005). Although, the significance of antecedent precipitation is highly variable among different regions (Jakob & Hungr, 2005). In the Zermatt region, for instance, antecedent rain does not have a significant impact on debris flow activity (Stoffel et al., 2014). On the other hand, Tang et al. (2009) confirm the relevance of antecedent rainfall for triggering debris flows in their study area in the Beichuan County of the Sichuan Province (China).

1.3.1.2 Rapid snowmelt and antecedent snowmelt

Rapid snowmelt is also a trigger for generating debris flows. Moreover, the rate at which snow melts, depends on the temperature. Certainly, a sudden increase in temperature can cause rapid snowmelt as

10 well as a huge rainstorm (Jakob & Hungr, 2005; Beniston & Stoffel, 2016). The effect of rapid snowmelt is more spatially and temporally limited compared to rain. Besides antecedent rainfall, antecedent snowmelt can also be an influence as a secondary climatic factor (Jakob & Hungr, 2005; Adams et al., 2016).

1.3.1.2 Temperature

The temperature influences whether precipitation will descent as either rain or snow (Marchi et al., 2009; Stoffel et al., 2014; van den Heuvel et al., 2016). Other effects of temperature include the possible growth of vegetation, permafrost, glacier retreat, etc (Stoffel et al., 2014). Temperature itself is highly influenced by climate change and more specifically by global warming (Stoffel et al., 2014; van den Heuvel et al., 2016).

1.3.1.3 The response of ice and snow bodies

Apart from precipitation and temperature another climatic factor is examined: snow and ice bodies in mountainous areas. Snow and ice bodies comprise ground freezing, snow avalanche deposits, permafrost and buried ice. The effect of the snow and ice bodies is highly variable due to temperature changes: they can either favour or resist debris flows (Bardou & Delaloye, 2004; Glade, 2005; Marchi et al., 2009). Ground freezing annihilates soil aggregates due to water expansion. As a consequence, more loose debris is created and the infiltration of the soil is reduced (E. Bardou & Delaloye, 2004). A snow avalanche can act as a slide plane for debris flows. It also become a reservoir of water when the snow starts melting (E. Bardou & Delaloye, 2004). Conversely, a snow avalanche can also act as a shield protecting the underlying ground from rainfall (E. Bardou & Delaloye, 2004). If permafrost degradation is present due to warming up, there will be more sediment weathering leading to more sediment production (Glade, 2005; Marchi et al., 2009). Conversely, the presence of a permafrost layer leads to a lower permeability of the layer on top which lowers the climatic threshold for triggering debris flows (Stoffel et al., 2014). Buried ice can also behave as a slide surface for debris flows and the melting of it provides additional amounts of water (Chiarle et al., 2007; Marchi et al., 2009).

1.3.2 Geomorphic factors

The geomorphic factors include a wide range of in situ characteristics of the study area: (1) slope and altitude of the initiation zone, (2) ruggedness of the basin, (3) soil and regolith characteristics, (4) bedrock type (geology), (5) presence of vegetation, (6) whether the area is recently glaciated or not and

(7) the size of the catchment (Bovis & Jakob, 1999; Bardou & Delaloye, 2004; Glade, 2005; Jakob & Hungr, 2005; Chiarle et al., 2007; Tang et al., 2009; Stoffel et al., 2014). The geomorphic factors will be discussed in the form of an enumeration:

(1) The debris flow initiation zone has a slope between 20° and 45° (Jakob & Hungr, 2005). Apart from the slope, the altitude of debris flows defines the sediment availability because the altitude can be constrained by vegetation growth or the presence snow and ice bodies (Bardou & Delaloye, 2004).

(2) The ruggedness serves a measure for how dissected basins are. Highly dissected basins are more favourable for generating debris flows (Bovis & Jakob, 1999).

(3) In what extent extreme rainfall can cause debris flows, also depends on the characteristics of the soil and regolith. Permeability, thickness and porosity influence the degree of instability of the regolith and soil (Jakob & Hungr, 2005). Moreover, these characteristics also determine the storage capacity of antecedent precipitation (Glade, 2005; Stoffel et al., 2014). Higher porosity, for example, leads to a higher infiltration and less water to be stored in the soil layer (Glade, 2005).

(4) Also the local lithology matters as some bedrock types are more prone to degradation than other types. Tang et al. (2009), for instance, calculated a debris flow gully density in areas with different rock types (phyllite and slate, limestone and sandstone). It appears that phyllite and slate had a higher density than limestone and sandstone because phyllite and slate are more prone to weathering and thus provide more loose material.

(5) More vegetation leads to more stability when slopes are not too steep (Bovis & Jakob, 1999; Glade, 2005; Stoffel et al., 2014). Moreover, the presence of vegetation depends on the altitude and temperature and precipitation, but also on the human impact as humans have converted large areas of forest into agricultural land (Jakob & Hungr, 2005; E. Reynard, Lambiel, & Lane, 2012; Stoffel et al., 2014). Also the type of vegetation defines the slope stability (E. Reynard et al., 2012). Shrubs and trees, for instance, have a critical impact on the slope stability (Reynard et al. , 2012).

(6) There is a high frequency of debris flows in the forefield of glaciers (Chiarle et al., 2007). Recently glaciated zones provide lots of loose material which is advantageous for debris flows (Chiarle et al., 2007). Furthermore, due to glacial retreat moraine-dammed lake are formed that can break causing a high supply of lots of water (Chiarle et al., 2007). The impact of a glacial lake outburst will also be discussed in the section on catastrophic events.

(7) The size of the catchment defines the supply of loose material (Glade, 2005). The larger the catchment, the more material is to be stored (Glade, 2005). Furthermore, more water can be intercepted in larger catchment (Glade, 2005).

1.3.3 The impact of catastrophic events

Catastrophic events such as glacial lake outbursts, earthquakes and volcanic eruptions, typhoons, dam breaks can lead to debris flows (van Steijn, 1996; Jakob & Hungr, 2005; Tang et al., 2009). A glacial lake outbursts, for instance, provides a sudden release of huge amounts of water, which can possibly trigger debris flows (Haerberli et al., 2001; Bardou & Delaloye, 2004; Huggel et al., 2004; Chiarle et al., 2007; Marchi et al., 2009). In 2008, Tang et al. (2009) discovered a decrease in the rainfall threshold for triggering debris flow after the passing of an earthquake. The trembling of the investigated Wenchuan earthquake resulted in a higher amount of loose material. The side-effects of an earthquake – landslides, avalanches and rockfall - , provide more source material for a debris flow ( Fritsche & Fäh, 2009; Tang et al., 2009; Pedrazzini et al., 2016; www.seismo.ethz.ch, 10/05/2018).

1.4 Temporal pattern of debris flows: the return period and debris flow season

Apart from intense precipitation events or sudden catastrophic incidents and geomorphic characteristics, a debris flow can only occur when enough debris is available (Glade, 2005). The return period points to the frequency at which debris flows occur and is expressed in years. Based on the availability of debris, two types of basins can be discerned: supply-unlimited or transport-limited basins and supply-limited or weathering limited basins (Bovis & Jakob, 1999; Jakob & Hungr, 2005). The difference between the two types is based on the sediment recharge rate (Theule et al., 2012). The first type is characterized by enough debris production. Thus, every time a certain hydroclimatic treshold is exceeded, a debris flow occurs (Jakob & Hungr, 2005). The other basin type lacks this frequent sediment recharge and thus more time has to pass by before another debris flow occurs (Bovis & Jakob, 1999; Jakob & Hungr, 2005). Hence, the supply-limited basins tend to have a lower debris flow frequency than their supply- unlimited counterpart (Bovis & Jakob, 1999). Most debris flows in the Alps belong the supply-unlimited basins as constant weathering produces enough debris (van Steijn, 1996; van den Heuvel et al., 2016). Two debris flow types can be discerned based on the origin of material: slope debris flows and gully debris flows (Glade, 2005). The latter has its main sediment source from loose material in drainage lines, channels and gullies, and material from previous debris flows (Glade, 2005). Slope debris flow are nourished by loose material from a steep slope, a debris slide or the border between (Glade, 2005).

Furthermore, a seasonality in debris flows has been discovered. In the Alps, for instance, debris flows mostly occur from May till September in the Zermatt region (Theule et al., 2012; Stoffel et al., 2014). Chiarle et al. (2007) discovered similar seasonality on multiple research site covering the Alps: between late June and July for debris flows triggered by brief local rainstorms and glacial lake outburst, and between late July and September for debris flows triggered by heavy and prolonged rainfall. Stoffel (2010) assigns the seasonality to a high elevation of the source area and the presence of a rock glacier in the Ritigraben torrent (Switzerland). Bovis & Jakob (1999) presented debris flow season from October till December in the Coastal Mountains (British Columbia, Canada). Other forms of seasonality include the effect of the El Niño-Southern Oscillation (ENSO) in North and South America (Jakob & Hungr, 2005). El Niño events are associated with an increase in debris flows (Jakob & Hungr, 2005).

1.5 The sediment budget

The sediment budget comprises the magnitude of the debris flow and is a measure for the volume of transported material (van Steijn, 1996). Debris flow volume is defined as follows by (Jakob & Hungr, 2005): “[...] the total amount of inorganic sediment, organic material, and water transported past a specific point of reference (usually the fan apex)”. According to Jakob & Hungr (2005) debris flow volume consists of three elements: the volume of the initiating failure(s), the volumes entrained along the transport reach and the volumes deposited along the transport reach. Jakob (2005) set up a classification for the magnitude for debris flows. The volume of debris flows also depends on the amount of water and the size of the catchment (Glade, 2005). Table 1 represents the size classification set up by Jakob (2005) as an evaluation of debris flows regarding risk-assessment. For each class Jakob (2005) wrote a description of possible consequences of the debris flow. Other measures of debris flow size, such as peak discharge and area inundated and a description of the possbile consequences are left out. As a consequence class 5 and 6 are added together as they represent debris flow with the same volume.

Table 1: Size classification by Jakob (2005) complemented with data from other consulted literature

Size V, range Size of the investigated Location Reference class (m³) debris flow

1 <10²

2 10²-10³

3 10³-104 3000 to 5000 m³ Ritigraben torrent Stoffel (2010) (Switzerland)

4 104-105 10 000 to 60 000 m³ Manival Torrent (France) Theule et al. (2012)

15 000 m³ Ritigraben (Switzerland) Bardou & Delaloye (2004)

5 & 6 105-106 150 000 m³ Chiarle et al. (2007)

265 000 m³ (± 42 000 Sellrain Valley (Austria) Adams et al. (2016) m³)

200 000 m³ Pelm glacier (Pelmo Chiarle et al. (2007) Massif, Italy)

300 000 m³ Ormeleura glacier (Rutor Chiarle et al. (2007) Massief, Italy)

800 000 m³ Mulinet glacier (Levanne Chiarle et al. (2007) Massif, Italy)

7 106-107 1 800 000 m³ Casita debris flow Jakob (2005) (Nicaragua)

8 107-108

9 108-109

10 >109 3 000 000 000 m³ Mount Rainier, vulcanic Jakob (2005) debris (United States of America)

1.6 Magnitude-frequency relation and representation

Magnitude and frequency are often studied together as an input for hazard analysis and are represented in a magnitude-frequency diagram (van Steijn, 1996; Jakob & Hungr, 2005; Hungr et al., 2008; Stoffel, 2010). Figure 1 is an example of such a diagram. Other variants with non-logarithmic scales, or categorical data exist (Stoffel, 2010). Typically, magnitude is presented on the y-axis and frequency or return period on the x-axis (van Steijn, 1996; Jakob & Hungr, 2005).

Figure 1: Magnitude-frequency diagram of debris flows in the Alpine chain (source: van Steijn, 1996)

1.7 Impact of climate change on debris flow activity

Many studies confirm the impact of climate change on the occurrence of debris flows and how it influences the triggers and factors of debris flows (Stoffel et al., 2014; van den Heuvel et al., 2016). Debris flow is predicted by modelling changes in precipitation and temperature (Stoffel et al., 2014; van den Heuvel et al., 2016). Predicting future debris flows is crucial for risk management, as debris flows have already caused enormous damage to infrastructure and endangered human lives (Jakob, 2005; Tang et al., 2009). Moreover, it is important how the frequency and magnitude will evolve in the future

(Stoffel et al., 2014). Generally, a rise in temperature is expected, which will lead to a higher frequency and magnitude of debris flow occurrence (Jakob & Hungr, 2005; Jomelli et al., 2009; Stoffel et al., 2014). The effect of rising temperature on debris flow occurrence has already been mentioned in the section of climatic factors: more precipitation will fall as rain instead of snow for which Stoffel et al. (2014) fixed a temperature threshold of 5°C. Also permafrost degradation and glacial retreat lead to a higher sediment supply (Jakob & Hungr, 2005; Chiarle et al., 2007; Stoffel et al., 2014; van den Heuvel et al., 2016). Conversely, a higher temperature leads to more vegetation which will stabilize loose sediment (Jomelli et al., 2009; Stoffel et al., 2014). The shifting of the tree line limits the altitude of debris flow activity (Jomelli et al., 2009). Also a change in seasonality of debris flows has been discovered in the Swiss Alps due to an increasing temperature. The research by Stoffel et al. (2014) and van den Heuvel et al. (2016) shows that debris flow activity is highest from June to September in the Zermatt region, but increasing air temperatures make the season starting earlier (May) and lasting longer (October). Furthermore, van den Heuvel et al. (2016) mentions a different response of supply-limited (or weathering limited) basins and supply-unlimited (or transport-limited) basins to climate change. On one hand there will be less weathering due to higher 0 °C isotherm, on the other hand there will be more weathering at higher elevations due to more freeze-thaw cycles for supply-limited basins (van den Heuvel et al., 2016). Conversely, debris flow activity is not constrained in supply-unlimited basins by debris availability but by climatic variables.

The effect of changes in precipitation are more difficult to estimate. An increase in precipitation intensity has been investigated, having different effects on magnitude and frequency (Stoffel et al., 2014). Drier summers and wetter springs and fall are expected in the Swiss Alps (Stoffel et al., 2014; van den Heuvel et al., 2016). Jomelli et al. (2009) and van den Heuvel et al. (2016) pointed out that the geomorphic characteristics of the research sites are responsible for the different outcomes of studies concerning the impact of climate change as these in situ characteristics respond differently to climate change itself.

1.8 Objectives and research questions

In this dissertation, the debris flows of Val d’Hérens and Col du Sanetsch are examined in terms of frequency and magnitude. Considering the frequency, the number of debris flow events over a certain period in time are analyzed. By analyzing the frequency, questions about the activity of the debris flows rise: are their any changes in the number of debris flows in the study area, is there an overall change in activity, are there more or less events over time, how many new flows were formed and which have not changed since the start of the monitoring. When looking at the magnitude, the scope of the debris flows is considered: how large, in term of volume m³, are the debris flows, which methods can be applied to track down the volume, what is the highest/lowest observed volume. Finally, the magnitude and frequency are studied together. This can be done by representing them in a magnitude-frequency diagram: how are they related to each other, what are the underlying causes of the observed magnitude- frequency relation.

1.9 About the upcoming dissertation

The forthcoming dissertation is started with an introduction to the study area and its main characteristics followed by the methodology. The methodology part describes the UAS (Unmanned Aerial System) employment and terrestrial survey, the different approaches towards the magnitude calculation, the examination of the frequency of the debris flows, the tracing for possible lime content and information and data about the map creation. Thereafter, the results of the dissertation are presented accompanied with an explanation for the outcome of the results. In the discussion part, a general reflection of the dissertation towards existing literature is given. The dissertation is terminated with a conclusion summing up the main findings of the thesis. Lastly, the references are listed up and additional material is presented in the annex.

2. STUDY AREA

The study area is situated in the canton of Valais, Switzerland (figure 2). In Valais two larger study areas can be discerned, namely Col du Sanetsch and the Hérens Valley. At Col du Sanetsch, one debris flow was examined in detail and mapped by a drone. In the Hérens Valley, five flows were visited and investigated. 58 other debris flows were mapped based on aerial images. The debris flows are represented as clusters on the overview map (figure 2).The Hérens Valley has been and still is an important site for various scientific research and recreational possibilities (Wilhelm et al., 1999; Dängeli et al., 2009; Stoffel, 2009; Hegg & Rhyner, 2011; Reynard et al., 2012; Lambiel et al., 2016; www.evolene-region.ch, 22/03/2018). The climate of the canton of Valais is mainly influenced by the Mediterranean Sea (www.meteoswiss.admin.ch, 19/05/2018). The region is characterized by so called ‘dry inner Alpine valleys’ (Lambiel et al., 2016; www.meteoswiss.admin.ch, 19/05/2018). The average precipitation ranges between 500 and 600 mm per year of which the major part falls during the summer months (www.meteoswiss.admin.ch, 19/05/2018). In the summer, severe rainstorms are not an exception (www.meteoswiss.admin.ch, 19/05/2018). During winter, precipitation tends to fall as snow for altitudes above 1200 m (www.meteoswiss.admin.ch, 19/05/2018). Furthermore, the region is represented by a high geomorphological and geological diversity. First of all, a rich tectonic variability is present in the area (Lambiel et al. , 2016; Pedrazzini et al., 2016). In figure 3, from north to south different tectonic domains are crossed (Pedrazzini et al., 2016). Also, some dominant lithological groups can be discerned in the Hérens Valley: (1) clay, silts, sabbie, (2) marly shales, calcareous phyllites, (3) mica shists, gneiss and (4) basic rocks. The lithology of Col du Sanetsch is mainly dominated by limestones, partly marls. In figure 4, a lithological map of the study area can be consulted. Overall, Col du Sanetsch is situated at an average height of 2252 m and the altitude of the Hérens Valley ranges between 493 m and 4357 m (Reynard et al., 2012; www.map.geo.admin.ch, 19/05/2018). Many geomorphological landforms are visible at Col du Sanetsch. In general, these include glacial landforms, periglacial landforms, fluvial landforms, gravitational landforms and karst (Reynard et al., 2003; www.map.geo.admin.ch, 19/05/2018). The most important of these landforms comprise: the Tsanfleuron glacier, limestone pavement (lapiaz), roches moutonnées, moraines, a sandur, the Sénin Lake, badlands, permafrost and cryoturbation (Reynard et al., 2003; www.map.geo.admin.ch, 19/05/2018). The Hérens valley is mainly dominated by glacial, periglacial, fluvial and gravitational landforms (www.map.geo.admin.ch, 19/05/2018). First, some large glaciers are visible in the southern part of the valley: the Mont-Miné Glacier, the Mont-Collon Glacier and the Ferpècle Glacier (www.unige.ch, 10/05/2018). The retreat of these glaciers resulted in several glacial landforms such as large morainic complexes, roche moutonnées and fairy chimneys (Euseigne Pyramids) (Lambiel et al., 2016). The periglacial landforms in the valley are dominated by permafrost, rock glaciers and solifluction (Lambiel et al., 2016). Gravitational processes comprise landslides and talus slope due to active rockfall (Lambiel et al., 2016). Lastly, fluvial landforms involve torrent activity and the fluvial deposits of the Borgne river (Lambiel et al., 2016).

Figure 2: Situating map of Valais and the visited sites

Figure 3: Simplified tectonic domains (source: Steck et al., 1999; Pedrazzini et al., 2016)

Figure 4: Lithological map of the study area

3. METHODOLOGY AND DATA

In the following sections, the used methods and data of the thesis are described. First, the employment of the UAS and the terrestrial survey are pointed out. Secondly, five approaches towards magnitude calculation are clarified. Thereafter, the determination of the frequency is explained followed by the representation of magnitude and frequency together.

3.1 3D modelling using aerial and terrestrial images

The construction of 3D models can be separated into three steps. In the first section, the first step, the preparation of the field survey is explained. In the second step, the acquisition of images, is illustrated. The second step is separated in two sections: one handles the acquisition of images with an UAS, the other handles the terrestrial acquisition. In the third and final step, the images are used to produce a DEM (Digital Elevation Model) and orthophotomosaics.

3.1.1 Preparation of the field surveys

Before conducting the drone flights and terrestrial survey, targets were distributed along the debris flow study area. The targets were made from square shaped canvases of 40 cm by 40 cm approximately and have a two by two check pattern and a central cross, so that they easily can be recognized on images. Whenever a target was placed, the GPS location of the central cross was measured. On figure 5 an example of a target can be seen.

Figure 5: Target near the debris flow of Col du Sanetsch

Two approaches are used to relate the placement of the targets to the later modelling. For the field survey with the drone, the absolute coordinates of the targets were measured using a base and rover configuration. The GPS locations of the targets are measured with the rover for 7 minutes. The base is positioned at a fixed location and measures its GPS location during the whole survey. For the terrestrial acquisition of images, targets were placed as pairs with a distance of 5m in between the two targets (figure 6). Additionally, the GPS location was measured with a handheld GPS (table 2).

Figure 6: Targets pairs at a debris flow near Glacier de Vouasson

Table 2: GPS purposes and functions

Type Purpose Function

Trimble R10 Base and rover configuration Base

Trimble R8s Base and rover configuration Rover

Garmin Etrex 30 Additional information /

Finally, the GPS positions obtained by the rover were adjusted by taking into account the more detailed GPS measurements of the base by using Leica Geo Office 8.3. GPS measurements from both the base and rover configuration and the handheld GPS can be consulted in annex 1.

3.1.2 Acquisition of UAS images

At Col du Sanetsch, a drone was used to map the debris flow. The equipment for the drone flight consists of six components: the drone itself, the batteries, the charger of the batteries, the camera, the controller and software to prepare the flight plan. Table 3 gives an overview of the used equipment.

Table 3: Drone flight equipment

Component Type

Drone Drone Hexacopter GAUI 540H frame

Energy source Two 4000 mAh, 16 V batteries

Charger G.T. Power 4 in 1 Charger

Camera Panasonic DMC-GM5

Controller NAZA v2

Software Mission Planner 1.3.48

First, a flight plan is designed taking into account the geomorphological setting of the debris flow: the slope of the debris flow is about 300 m long with a height difference of 170 m. As a consequence, multiple flights were conducted to map the whole debris flow to prevent the drone’s batteries from running out of energy. Each flight plan consists of multiple GPS points that form a track parallel to the local altitude lines. Additional to the flight plan, the flight height had to be determined. During the flight, the drone has to maintain an average flight height of about 60 m relative to the study area’s surface by changing the absolute height of the drone. Via a small USB antenna, the flight plan is sent to a receiver on the drone. First, the drone is taken into the air manually by using the controller and as soon the drone is high enough, the manual mode is switched off and the drone starts navigating the flight plan. Meanwhile, the camera takes an image once every second. The settings of the camera are listed in table 4.

Table 4: Camera settings of the UAS

Model ISO F-stop Shutter

Panasonic DMC-GM5 400 F/5.6 1/500

The shutter is kept as low as possible to avoid motion blur during the flying (De Wulf, 2015).

3.1.3 Assembling of terrestrial images

On three research sites in Val d’Hérens, terrestrial photographing was used for the 3D modelling. Two cameras were used. The settings of both cameras are summed up in table 5.

Table 5: Camera settings of the terrestrial photographing

Model ISO F-stop Shutter

Panasonic DMC-GM5 400 F/8 1/400

Panasonic DMC-FZ50 100 F/4 1/200

For both devices, shutter is kept as low as possible to avoid motion blur (De Wulf, 2015). The Panasonic DMC-GM5 was only used at the debris flow at Glacier de Vouasson and the Panasonic DMC-FZ50 was used at all sites. To conduct terrestrial photographing, a steep slope close to the debris flow deposit was necessary. From the slope pictures can be taken from different angles from a high position. Pictures are taken starting uphill and descending gradually, while walking back and forth at the same elevation. In this way, a zigzag movement is made along the slope during photographing. The camera is held above the head to take pictures straight down.

3.1.4 Producing DEM and orthophotomosaics

Agisoft Photoscan was used to process the images obtained from the drone flight and terrestrial survey. First, a general workflow with different steps was used to produce a 3D model of each site: (1) uploading and selecting images, (2) aligning the chosen images, (3) indicating the targets, (4) optimizing the alignment with the indicated targets, (5) building a dense point cloud, (6) building a mesh and (7) building a texture (Agisoft, 2013). A detailed workflow with all settings can be consulted in annex 2. The model obtained from the images taken by the drone, is georeferenced due to the detailed GPS measurement. From this model, a DEM is built and exported to a TIFF. Later on the DEM will be used for the volume measurement of the debris flow deposit. The other models obtained by the terrestrial survey, are used to build and export orthophotos which are georeferenced in QGIS later on. The orthophotos can be used as a background to make time-depth maps of the debris flows. The original DEM and orthophotomosaics can also be consulted in annex 2.

3.2 Estimating the magnitude of debris flows

The magnitude of the debris flow is a measure for the volume of transported material (van Steijn, 1996). Debris flow volume is defined as followed by (Jakob & Hungr, 2005): “[...] the total amount of inorganic sediment, organic material, and water transported past a specific point of reference (usually the fan apex)”. According to Jakob & Hungr (2005) debris flow volume consists of three elements: the volume of the initiating failure(s), the volumes entrained along the transport reach and the volumes deposited along the transport reach.

Jakob & Hungr (2005) state that debris flow magnitude can be expressed in three different ways: debris-flow volume, peak discharge and the area inundated. Each of which is intended for a different purpose concerning hazard analysis (Jakob & Hungr, 2005). Still, the main objective of each magnitude approach is to obtain the deposited volume expressed in m³ (van Steijn, 1996; Jakob & Hungr, 2005). The purpose of the magnitude measurement is to integrate it into a magnitude-frequency relation and to make a comparative study of different methods concerning the true value of the magnitude. Also, not all volume measurements can be applied in the field. To determine the magnitude five methodologies were used: (1) volume-inundated area relation, (2) grain size analysis, (3) morphometric properties, (4) descriptive properties and (5) calculation from a DEM (Berti & Simoni, 2007; Griswold & Iverson, 2008; Hungr et al. , 2008; Stoffel, 2010). All five of them, calculate or estimate the actual volume in m³ in a different way. (1) and (5) use aerial images, while (2), (3) and (4) need measurements on the spot (Berti & Simoni, 2007; Griswold & Iverson, 2008; Hungr et al. , 2008; Stoffel, 2010). (1) uses the area inundated by the debris flow to determine the volume, while (5) calculates the volume directly from a DEM (Berti & Simoni, 2007; Griswold & Iverson, 2008). (2) matches the grain sizes of the deposited rocks with certain volume classes (Jakob, 2005; Stoffel, 2010). (3) compares the debris flow deposit to a geometric volume, called a truncated triangular prism, and (4) measures several properties of the whole debris flow, deposit and channel, from which the deposited volume can be calculated (Hungr et al., 2008; Stoffel, 2010).

3.2.1 Volume based on the volume – inundated area relation

A remote way to measure debris flow volume can be done based on the empirically determined volume inundated area relation (Crosta et al., 2003; Berti & Simoni, 2007; Griswold & Iverson, 2008; Scheidl & Rickenmann, 2010). The general relation between volume and inundated area is represented in the following formula, where A represents area, V is the volume, and k and d, respectively, are the factor and power to be determined (Griswold & Iverson, 2008).

1 A d A = k ∗ Vd ⇔ ( ) = V (1) k

In literature, there is a general agreement that the d equals 2/3, but the k factor is more difficult to establish as it depends on the type of flow (Berti & Simoni, 2007; Crosta et al., 2003; Griswold & Iverson, 2008; Scheidl & Rickenmann, 2010). First of all, the formula can be applied in two ways in terms of the area: the cross-sectional area and the planimetric area (figure 7 and figure 8) (Berti & Simoni, 2007; Griswold & Iverson, 2008). For the two types of inundated area different k values exist (Berti & Simoni, 2007; Griswold & Iverson, 2008).

Figure 7: Inundated area representation. The yellow A1 to A4 represent the cross-sectional areas and the red dashed line shows the planimetric area (source: Griswold & Iverson, 2008).

Figure 8: Inundated area representation (source: Berti & Simoni, 2007).

As the planimetric area can be measured on aerial pictures in GIS, it is used for the calculation of the volume of the debris flows. A second choice to be made is the exact interpretation of the planimetric area. Crosta et al. (2003) and Griswold & Iverson (2008) include the debris flow deposit and levée structures, while Berti & Simoni (2007) only take into account the deposit on the deposition fan (figure 7 and 8). Berti & Simoni (2007) assume a theoretical representation of a debris flow with a clear distinction between channel and deposit. The main reason to adopt a more strict definition of the inundated area, is because they want to map older deposits as well as deposits along the channel that are hard to measure. Lastly, the best k factor had to be chosen. Table 6 lists up the values of k for non-volcanic debris flows ordered from low to high. For each value, the R² is mentioned of the statistical test performed by the authors. Crosta et al. (2003), Berti & Simoni (2007) and Griswold & Iverson (2008) have a high R² for their k value. Finally, the k of Griswold & Iverson (2008) is applied in the study area. The value obtained by Berti & Simoni (2007) is not implemented due to their different approach concerning the planimetric inundated area. Crosta et al. (2003) also have a high R², but this value is very site specific. As such, the final formula is presented in the following equation.

3 2 A 2 A = 20 ∗ V3 ⇔ ( ) = V (2) 20

Table 6: K factors for debris flow inundated area relation (source: Crosta et al. (2003), Berti & Simoni (2007), Griswold & Iverson (2008), Scheidl & Rickenmann (2010))

K value Study Area/Description R² Reference

6.2 Alps, northern Italy (Val Alpisella and Val 0.97 Crosta et al. (2003) Zebru)

17 Overall regression combining Berti & Simoni / Berti & Simoni (2007) (2007), Crosta et al., (2003) and Griswold & Iverson (2008): values 20, 6.2 and 33.

17.3 Alps, northern Italy (South Tyrol) 0.59 Scheidl & Rickenmann (2010)

20 Worldwide 0.91 Griswold & Iverson (2008)

28.1 Alps, Switzerland (events from 1987) 0.70 Scheidl & Rickenmann (2010)

32.0 Alps, Switzerland (events from 2005) 0.42 Scheidl & Rickenmann (2010)

33 Alps, northern Italy (multiple sites along the 0.80 Berti & Simoni (2007) Swiss-Italian border)

44.7 Alps, western Austria 0.67 Scheidl & Rickenmann (2010)

Lastly, the area measurement is done by using a measuring tool in GIS. First, the measuring tool of QGIS in combination with satellite images from Google, provided by the OpenLayers plugin, was used. But compared to the online measuring tool of SwissTopo, there seemed to be an overestimation of distances and areas by the QGIS tool. An explanation for the miscalculations in QGIS might be the combination of the plugin and the measuring tool that are not adjusted to each other. Also, the pictures of Google Satellite are less zoomable than the ones provided by SwissTopo. The latter has better resolution and appear brighter. Even though the measuring on the online map gives better results, the national projection system, CH1903+ / LV95 (EPSG: 2056), itself is, from a cartographical perspective, not suitable for area measurements as it is a conformal cylinder projection based on WGS84 and not an equal area projection (https://www.swisstopo.admin.ch, 19/03/2018).

Another reason to choose formula 2, is because Jakob & Hungr (2005) use it to set up a classification of debris flows magnitude. Table 7 represents the size classification set up by Jakob (2005) as an evaluation of debris flows regarding risk-assessment. For each class Jakob (2005) wrote a description of possible consequences of the debris flow. The classification consists of ten classes, but only the first six are represented. Non-volcanic debris flow larger than size class six have not been observed yet.

Table 7: Size classification of debris flows based on volume-inundated area relation (source: Jakob, 2005)

Size class Volume (m³) Area (m²) Consequences

1 <10 m² < 4 x 10² Very localized damage, known to have killed forestry workers in small gullies, damage small buildings

2 [10² - 10³[ [4 x 10² - 2 x 10³[ Could bury cars, destroy a small wooden building, break trees, block culverts, derail trains

3 [10³ - 104[ [2 x 10³ - 9 x 10³[ Could destroy larger buildings, damage concrete bridge piers, block or damage highways and pipelines

4 [104 – 105[ [9 x 10 ³ - 4 x 104[ Could destroy parts of villages, destroy sections of infrastructure corridors, bridges, could block creeks

5 [105 – 106[ [4 x 104 – 2 x 105[ Could destroy parts of towns, destroy forests of 2 km2 in area, block creeks and small rivers

6 ≥ 106 ≥ 2 x 105 Could destroy towns, obliterate valleys or fans up to several tens of km2 in size, dam rivers

3.2.2 Grain size analysis

A first estimation is based on the grain size and is a methodology proposed by Stoffel (2010). Fifty rocks were measured from each debris flow deposit and associated channel (Stoffel, 2010). Rocks were collected evenly distributed over the debris flow: on levées, within the channel, near the edges of the deposit, on the deposit, et cetera (Stoffel, 2010). In this way, the grain size is a measure that represents the debris flow as a whole. Each rock was measured in centimetre along three axes, length, width and depth, with a yardstick and/or a tape measure. With the following formula the nominal diameter of the rock sample can be calculated:

1⁄ Dn = (a ∗ b ∗ c) 3 (3)

With Dn, the nominal diameter, a the longest diameter, b the intermediate diameter and c the shortest diameter (Bunte & Abt, 2001). This measure is chosen for further calculations as it is recommended for

32 volume calculations (Bunte & Abt, 2001). Hereafter, the maximum and mean grain size can be defined for each deposit. According to the mean and maximum grain size, the debris flow can be associated to a certain size class (Jakob, 2005; Stoffel, 2010). Table 8 show the relation between the size magnitude classes and grain size. The grain size is not completely determined by the volume (Stoffel, 2010). The grain size is more of a reflection of the power of the event (Stoffel, 2010). As a consequence, there is some overlap between the classes and the proportion grain sizes represented. Generally, the larger the boulder, the larger the flow.

Table 8: Size class and grain size (source: Jakob, 2005; Stoffel, 2010)

Stoffel’s Associated Jakob’s Mean grain size (%) Maximum grain size (%) classification volume (m³) classification (<0,5m ; 0,5 m – 1 (0,1 m; <1 m; <1,5 m; <2 m; 1 m – 2 m) m; <3 m)

Small 10² - 10³ 1 - 2 60/40/0 43/7/7/40/3

Medium 10³ - 5 x 10³ 3 44/54/2 15/15/11/37/22

Large 5 x 10³ - 104 3 36/51/14 17/16/10/24/23

Extra Large 104 - 5 x104 4 24/51/24 14/14/8/8/35/30

3.2.3 Volume measurement based on morphometric properties

Another method to define the volume of the debris flow deposit, is proposed by Stoffel (2010). The volume is compared to a truncated triangular prism of which the morphometric properties can be measured in the field. These properties are captured in the following equations:

1 푉 = ⁄3 ∗ ( 푤푓 + 푤푡 + 푤푐) ∗ 퐴 (4)

1 퐴 = ⁄2 ∗ 푎 ∗ 푏 ∗ sin 훾 (5)

A representation of these properties can be seen on figure 9.

Figure 9: Morphometric properties of the truncated triangular prism (source: Stoffel, 2010)

For the widths, measurement ‘a’ and measurement ‘b’ a tape measure and a yardstick were used. W f stands for the width at the front of the deposit, which is measured exactly in front of the deposit. W c stands for width at the crest of the deposit and was measured where the lob deposit was at its widest.

Wt is the width at the tail, which was measured at end of the deposit where the transition to the debris flow channel began. ‘a’ represents the total distance between wt and wf, while b represents the distance between wc and wf. γ was measured in degrees by using a clinometer. A walking stick was held against the front of the deposit creating a steady surface. In this way the angle could be measured unambiguously. In case of uncertainty, the angle was measured multiple times. For further calculations, the average value of these measured angles was used. The final calculations of the volume were carried out in Excel 2016. Crosta et al. (2003) use a similar approach to measure debris flow volume by comparing it to “[…] pipes with semi-elliptical cross sections and rectangular bases”. No further explanation is given on how the dimensions were measured (Crosta et al., 2003).

3.2.4 Magnitude estimation based on descriptive properties

A third method to estimate debris flow volumes is described by Hungr et al. (2008). In their study, the Queen Charlotte Islands database of debris avalanches and debris flows is used to define magnitude-frequency relations. This database contains a large collection of descriptive properties that have been measured in the field for every debris flow (Hungr et al., 2008). From the values of these

34 properties, it is possible to calculate the volume of a debris flow (Hungr et al., 2008). The descriptive properties and their abbreviations are listed in table 9.

Table 9: Descriptive properties and abbreviations (source: Hungr et al., 2008)

Abbreviation Description

LEN Slope length of the reach

MSA Mean slope angle

EWID Mean width of erosion

DWID Mean width of deposition

EDEP Mean erosion depth (measured perpendicular to slope)

DDEP Mean deposition depth

The length of the reach can be measured in GIS using a measuring tool. MSA was measured similar to the angle measurement of the morphometric properties. A walking stick was held against the slope on which a clinometer was placed to read the value of the angle in degrees. Based on these properties the following parameters can be calculated (table 10).

Table 10: Derived parameters (source: Hungr et al., 2008)

Abbreviation Description

WID = EWID + DWID Total channel top width

Y = EDEP x EWID – DDEP x DWID Channel yield rate in m³/m length, negative if net deposition

E = Y / WID Mean erosion depth

Vi = Y x LEN Volume increment per reach

Vi can either be positive or negative. Negative values signify more net deposition than erosion and positive values signify more net erosion (Hungr et al., 2008).

3.2.5 Volume measurement based on a DEM

In the last method, a DEM is used to calculate the volume. As input, the DEM obtained from the aerial mapping of the drone is used. A general method to determine the deposited volume is by calculating the difference of the DEM relative to a reference plane (Theule et al., 2012; Adams et al., 2016; www.desktop.arcgis.com, 27/03/2018; www.pro.arcgis.com, 27/03/2018). This reference plan can be a DEM that has been measured and calculated before an event or it can be an estimation of the underlying surface (Theule et al., 2012; Adams et al., 2016; www.desktop.arcgis.com, 27/03/2018; www.pro.arcgis.com, 27/03/2018). In the first case, a DEM of difference can be calculated visualizing deposition and erosion by an event (Theule et al., 2012; Adams et al., 2016). As there is no DEM available of the situation before the event (apart from a general DEM for Switzerland with a 2 m resolution), the second approach will be used. Overall, three steps are needed to calculate the volume: (1) creating an interpolated reference surface, (2) clipping the desired surface – the deposit – from the DEM obtained from aerial mapping and (3) calculating the difference between the surfaces from (1) and (2). The full workflow in GIS can be consulted in annex 3 along with intermediate results.

3.3 Determining the frequency

The frequency defines the rate at which a debris flow is produced (van Steijn, 1996; Jakob & Hungr, 2005). Frequency is the inverse of the return period (Jakob & Hungr, 2005). Therefore a time sequence of aerial images of the same location will be analysed to discover possible changes in the debris flow deposit, channel, source area and wider environment. First, aerial pictures from SwissTopo were examined. Black and white pictures from 1927 to 2003 and coloured pictures from 1998 to 2010 can be viewed online at a high quality (https://www.swisstopo.admin.ch, 14/03/2017). The time series is not continuous in the study area, but there are approximately two to three pictures per decade for each debris flow site. Apart from the aerial pictures, the orthophotomosaic, SWISSIMAGE, can be viewed as a background image in the online viewer (www.map.geo.admin.ch, 14/03/2017). For the study area, SWISSIMAGE dates back to 2016 (www.map.geo.admin.ch, 14/03/2017; www.shop.swisstopo.admin.ch, 22/03/2018). Additional historical images are provided by Google Earth (www.googleblog.blogspot.be, 22/03/2018; www.support.google.com, 22/03/2018). Table 11 gives an overview of the available time series. Consecutive time series are put together when having the same source and range of colours. For some years, both coloured, and black and white images were available.

Table 11: Times series of aerial pictures

Years Black/white or Coloured Source

1946, 1958, 1959, 1961, 1964, Black/white Federal Office of Topography 1965, 1967, 1969, 1971, 1974, Swisstopo 1976, 1980, 1983, 1986, 1988, 1992, 1994, 1995, 1997

1998, 1999 Black/white and coloured Federal Office of Topography Swisstopo

2000, 2001 Black/white Federal Office of Topography Swisstopo

2004 Coloured Federal Office of Topography Swisstopo

2005 Black/white and coloured Federal Office of Topography Swisstopo

2009 Black/white Federal Office of Topography Swisstopo

2009 Coloured Google Earth

2010 Black/white Federal Office of Topography Swisstopo

2012, 2013 Coloured Google Earth

2016 Coloured Federal Office of Topography Swisstopo (SWISSIMAGE)

2016 Coloured Google Earth

3.4 Map creation

Throughout the dissertation, several maps will be presented accompanied with background data. For example, for the visited sites, time-depth maps were created showing all of the geomorphological features of the debris flows and their age. Table 12 sums up the source data and a description.

Table 12: Source map data

Name Description

Swiss Map Vector 500 Data from the national road map.

OpenStreetMap Switzerland Topography

Swiss Boundaries 3D Borders of countries, cantons and districts

Lithological groups Lithology

DHM 200 DEM with 200 m cell size

Swiss Alti 3D DEM with 2m cell size

The map data can be consulted in the annex 4.

3.5 Tracing the possible lime content of debris flow deposits

As the lithology of the Hérens Valley shows dominant lime content, a small chemical test with HCl was performed along with the grain size measurement. Little HCl was poured on a rock with a pipette to trace for possible lime content of the rock (www.geology.com, 22/02/2018). The test was performed for ten rocks out of the fifty that were collected for the grain size measurement. For each rock sample a binary code (Yes/No) was used to indicate whether the rock reacted with the liquid or not. Afterwards, the results were compared with a lithological map to get an idea of the origin of the rock. This can be interesting when a debris flow crosses different lithological units.

4. RESULTS

In the following sections, the results will be introduced. First, the frequency of the debris flows is explained. The part visualizes both frequency and return period and discusses the changes of the debris flows in the Hérens Valley. Second, the magnitude of the debris flows are clarified over two sections. In the first section, the results of the different magnitude measurements of the visited sites are presented. In the second section, the magnitude, based on the volume inundated area relation, of all the debris flows in the Hérens Valley are discussed. Lastly, frequency and magnitude are analysed together. The underlying causes, the contributing triggers and factors, of the pattern they show are examined. The mapping of the debris flows along with original measurements are presented in the annex 4.

4.1 Frequency

In total 63 distinct debris flows were mapped over time. Figure 10 represents all the debris flows and the time the monitoring was started with the first occurrence of the flow. The map connects data availability – the aerial photographs – with the first time the debris flow was detected on the aerial photographs. As some symbols tend to overlap, eight inset maps were created for clusters of debris flows on the main map. The start of monitoring indicates the date of the earliest available aerial picture for the area where a debris flow is currently situated. For 29 out of 63 flows, there was no flow visible on the earliest available picture. Some flows could be followed through time since 1946 at earliest, in some cases the monitoring could only start in 1967. After the 1967, all the locations of the debris flows were at least detected once. On figure 10, each year has a different colour. The left half of the circle indicates the start of monitoring for a certain flow, while the right half shows the first occurrence. Clustered debris flows tend to have the same start of monitoring as they can be detected together on one and the same aerial picture. Table 13 shows a cross table indicating the distribution of the number of flows for a certain start of monitoring and first occurrence.

Figure 10: Start of monitoring and first occurrence of debris flows

Table 13: Distribution of number of debris flows depending on start of monitoring and first occurrence

First occurrence Grand /Start of monitoring 1946 1958 1959 1961 1965 1967 1977 1986 1988 1994 1998 1999 2005 2009 2016 Total 1946 7 1 1 9 1958 3 2 1 6 1959 18 1 1 2 1 1 2 1 1 2 30 1961 1 1 1965 5 1 4 1 1 12 1967 1 4 5 Grand Total 7 3 20 1 5 3 5 1 6 2 1 2 2 2 3 63

Figure 11 shows the activity of the flows in terms of number of produced events since the start of their monitoring. As the chart indicates, most of the flows only produced one or two events. For larger numbers of events, there is a decrease in debris flows. This chart does not take into account the monitoring time. The end of the monitoring is 2016 for not visited flows and 2017 for the five visited flows in the Hérens Valley, but the start of monitoring is more miscellaneous. As a consequence, flows that could be followed for a longer period therefore have a higher chance of producing an extra event. Chart 12, on the contrary, shows the return period of the flows. Still, this representation can be misleading due to the debris flows with a low amount of events and their possible different starting years of the monitoring.

35 31 30

20 20

Number of debris flows debris of Number 10 7

5 3 1 1 0 1 2 3 4 5 6 Number of events

Figure 11: Number of events of debris flows

30 28

15 14

10 6

Number of debris flows debris of Number 5 5 3 3 2 1 0 10-15 15-20 20-25 25-30 35-40 50-55 55-60 70-75 Return period (years)

Figure 12: Return period of the debris flows

Figure 13 show the spatial distribution of the debris flows and the amount of produced events. Debris flows with a high amount events (larger than two) are distributed along the valley and do not form a cluster. Sometimes they are surrounded by less active flows. This indicates that their activity might be caused by site specific characteristics.

Figure 13: Debris flows and their number of produced events

Finally, the activity of the debris flows of the whole valley are analysed. The chart in figure 14 shows the cumulative rise of the number of events for all debris flows over time. Changes before 1967 should not be considered as not all debris flows could already be monitored. The rise before 1960 is due to the fact that in 1959 there were a lot of aerial pictures available that were the start of the monitoring for many debris flows. As such, changes in number of flows before 1969 are faded. The red circles indicate five apparent rises in number of flows. The chart without the indications can be consulted in annex 5.In the beginning of the 70’s, there is an increase. In the middle of 80’s, there is a striking rise in the number of events. This rise is situated between 1983 and 1988, two series of aerial pictures that cover the whole study area. Also the beginning of the nineties and in the middle between 2000 and 2010. The most prominent rise can be seen after 2010. The rise is situated between the time series 2009 and 2016.

Figure 14: Cumulative amount of events over time with indications

4.2 Magnitude

The magnitude will be discussed into two parts. The first part deals with the field measurements and observations of five debris flows in the Hérens Valley and one at Col du Sanetsch. In the second part, the volume of all debris flows in the Hérens valley are presented for which the volume-inundated area

45 relation is used. The volumes can be associated with a certain volume class. Each size class represents a possible impact on the environment (Jakob, 2005).

4.2.1 Case study: comparison of different volume measurements and geomorphology

Figure 15 and 16 give an overview of the visited sites in the Hérens Valley and Col du Sanetsch with an aerial view. Each site is named after the nearest toponym in the area. In the Hérens Valley, three sites were visited and number on the map in figure 15. At two sites, two debris flows were present – indicated with A and B. Figure 16 shows both the debris flow of Col du Sanetsch and one general overview map showing the location of Col du Sanetsch and the extent of the overview map of figure 16. For each flow – six in total – the corresponding outcome of the measurements will be presented. Also a detailed time-depth map of each debris flow will be displayed. The inset maps and main maps of all the time- depth representations have the same scale. Throughout the explanation, the measurements and the maps will be linked to each other.

Figure 15: Overview of the five visited sites

Figure 16: Satellite image of debris flow at Col du Sanetsch with overview map

4.2.1.1 Hérens Valley research sites

The first site to be discussed is Plan de Levri. At Plan de Levri, two sites – named A and B – were investigated (number 1 of figure 15). According to the frequency, both flows produced two events. For both debris flows, their latest event was created between 2009 and 2016. Remnants of older deposits were no longer visible as they were overburden. As such, the measurements were carried out on recent deposits as can be seen on time-depth maps on figure 17. The deposit of debris flow A splits up into four channels. Two smaller channels with no clear deposit, but levées consisting of lined up rocks. It is the other two deposits which have the largest share in volume. In total, six grain size analyses were carried out: 300 rocks were measured. The complete measurements can be found in annex 6. A large part of the measured rocks content lime. The mean and maximum grain sizes are presented in table 14.

Table 14: Grain size analysis of Plan de Levri A

Maximum grain size Mean grain size Lime Stoffel’s Jakob’s Associated (cm) (cm) content classification classification volume (m³) 13,87188389 7,568371253 10/10 Small 1 - 2 10² - 10³ 16,34660405 8,483745364 9/10 16,90204333 6,491105572 10/10 14,36883693 8,331726097 9/10 11,36525793 5,750843449 10/10 28,39326032 7,041541529 10/10 15,62464874 8,183808933 10/10

To calculate the deposit based on the morphometric properties, four measurements (four times a truncated triangular prism) were needed. The total measured volume was 133,7764 m³. The volume based on the descriptive properties amounts -1033,192125 m³. Finally, the volume was also defined from aerial pictures by using the inundated area relation. For this, the two interpretations of the deposit as mentioned in the method are used. When taking into account the whole deposit, the area equals 8554,23 m² corresponding to a volume of 8845,581558 m³. For the deposit measured in the field methods, the area is 2333,72 m² corresponding to a volume of 1260,457273 m³. Both volumes are associated with size class 3 in Jakob’s classification. An overview of these measurements can be seen in table 20.

For site B at Plan de Levri, one grain size analysis was necessary as there is only one large deposit and channel. Table 15 shows the results. The mean and max grain size appear to have larger values compared to the other site. Still, this debris flow is also small sized and belongs to size classes 1 and 2. Also, a significant lime content was found in the rocks: 8 out of 10 measured rocks.

Table 15: Grain size analysis of Plan de Levri B

Maximum grain size Mean grain size Lime Stoffel’s Jakob’s Associated (cm) (cm) content classification classification volume (m³) 32,24005663 11,91581807 8/10 Small 1 – 2 10² - 10³

To calculate the morphometric properties of the deposit, two surveys were required. The total measured volume was 670,0147 m³. Descriptive properties method estimated a volume equal to -3071,59889 m³. The inundated area of the whole flow was 4287,40 m³ with a volume of 3138,67257 m³. In the other case, the area equals 967,78 m² corresponding to a volume of 336,6045411 m³.

Figure 17: Time-depth maps of sites near Plan de Levri

The second visited site near Col du Torrent has a higher activity and produced four events over time. The site showed major difficulties to put the volume measurements into practice. The site is located on an old alluvial plain (figure 18). The deposit is embedded in a predefined channel, while the morphometric properties method and the descriptive properties method require deposits that reach out of the local topography. As such, the thickness of the deposits could not be defined. Apart from the thickness, the deposit does not have a lobate shape at all, but a more trail like deposit showing the extent of the channel. Two time events are visible in the field. There is a deposit created between 2001 and 2005, and one between 2009 and 2016 as can be seen on the map (figure 18). At the height of the deposit from 2005, the overall debris flow was disturbed severely. As a consequence the channel could not be recognized nor on the field, nor on aerial pictures. The disturbance is probably caused by the grazing and trampling of cattle (black bulls) that could be seen on aerial pictures – the animals were standing on both sides of the deposit – and in the field. For both events, the grain size analysis was carried out. For each event three analyses were needed (table 16). The rocks showed significant lime content.

Table 16: Grain size analysis of Col du Torrent site

Maximum Mean grain Lime Stoffel’s Jakob’s Associated Period grain size (cm) size (cm) content classification classification volume (m³) 2009 - Small 1 - 2 10² - 10³ 2016 32,13203777 11,48719564 9/10 2009 - 2016 51,16593396 12,29756832 9/10 2009 - 2016 43,14821756 11,66097293 9/10 2001 - Small 1 – 2 10² - 10³ 2005 19,1081551 7,854493432 10/10 2001 - 2005 30,17349472 8,145967537 10/10 2001 - 2005 51,54672104 12,48625969 9/10

The rocks appear to be larger compared to the other two research sites. The whole deposit covers an area of 9110,15 m³ with an associated volume of 9721,724 m³. The end deposit of the most recent events corresponds to an area of 1619,13 m² with a volume of 728,4128 m³. The end deposit of the 2005 event has an area of 1057,84 m³ with a corresponding volume of 384,667 m³.

Figure 18: Time-depth map of site near Col du Torrent

In the third research site near the Vouasson glacier, two debris flows could be measured. The sites are distinguished with indications A and B and number 3 as can be seen on figure 15. Within the source area of these debris flows is a rock glacier (figure 20). The acceleration of the rock glacier is of major importance for the supply of debris. Debris flow A seems affected the most by the frequent supply of source material. Six events have been produced over time making it the most active flow of the whole Hérens valley. Debris flow B, on the contrary, has produced two events over time. For debris flow A, three time events are visible in the field. The shape of a small part of the 1977 event is still visible, but is completely overburden and overgrown by vegetation. As such, no volume measurements of any kind could be carried out. The 2005 event, on the contrary, still has a clear channel and some deposits. From 2009 to 2016, probably two events happened at this site. Figure 19 illustrates this finding. Even though a debris flow can consist of multiple surges, it is very unlikely that a channel gets blocked so severely within one event. Because there is an uncertainty for when both flows happened exactly, they have the same time colour in the time-depth maps in the annex. In fact, four time event are visible in the field instead of three.

Figure 19: Two events at debris flow A between 2009 and 2016

Five grain size analyses were carried out for the deposit of 2005. For the two events between 2009 and 2016, two analyses were performed. Table 17 gives an overview of the calculations and classifications.

For the northern channel (main channel) created between 2009 and 2016, less lime was detected compared to other deposits.

Table 17: Grain size analyses at Glacier de Vouasson A

Maximum Associated grain size Mean grain size Lime Stoffel’s Jakob’s volume Period (cm) (cm) content classification classification (m³) 2001 - 2005 26,78066475 9,006266653 9/10 Small 1 - 2 10² - 10³ 2001 - 2005 73,727133 23,97495286 8/10 Small/Medium 1 - 2 (- 3) 10² - 10³ (- 104) 2001 - 2005 15,2272753 7,324152587 8/10 Small 1 - 2 10² - 10³

2001 - 2005 31,43132937 11,82954984 9/10 Small 1 – 2 10² - 10³

2001 - 2005 22,19737003 9,372102147 9/10 Small 1 – 2 10² - 10³

2009 – 2016 44,3716725 14,93973932 5/10 Small 1 – 2 10² - 10³ (northern main channel

2009 – 2016 15,79851506 7,623656517 8/10 Small 1 – 2 10² - 10³ (thin

southern channel)

Because the deposit of the small southern debris flow branch only consist of a channel with lined up levées, it was not possible to carry out the morphometric properties method and the descriptive properties method. For the other two events, it was possible to carry out the measurements. The 2005 deposit gave a volume of 97,4581466 m³ based on the morphometric properties method and the 2016 deposit a volume of 21,8785803 m³. On the other hand, the descriptive properties method gave volumes of -153,9986554 m³ and 1466,86732 m³ for the 2005 and 2016 deposit respectively. The total inundated area for the whole debris flow A equals 5921,17 m² with a corresponding volume of 5094,09 m³. The 2005 and 2016 deposit event has an inundated area of 1362,91 m² and 433,22 m² with a volume of 562,54306 m³ and 100,813282 m³, respectively. The small southern branch of 2016 has an area of 236,81 m² corresponding to a volume of 40,74319319 m³.

At debris flow B, one major event is still visible in the field. An older deposit used to have a slightly different trajectory, which is still visible. This flow also went through a predefined channel, but in contrast to the flow near Col du Torrent, the end deposit is beyond of the predefined channel. One grain size analysis was carried out for the most recent event. As for the other event, the end deposit is topped by the newer event. As a consequence, the grain size analysis was not carried out for that event. Table 18 gives an overview of the analysis and the classification.

Table 18: Grain size analysis of Glacier de Vouasson B

Maximum grain Lime Stoffel’s Jakob’s Associated size (cm) Mean grain size (cm) content classification classification volume (m³) 27,41433352 10,46652634 10/10 Small 1 -2 10² - 10³

The morphometric properties method gave a deposited volume of 33,42449 m³. The descriptive properties method gave 170,0379934 m³ as volume. The inundated area equals 3266,56 m² with a corresponding volume of 2087,329284 m³ for the whole flow. For the end deposit, the area amounts 236,03 m² with a volume of 40,54206038 m³.

Figure 20: Time-depth map of sites near Glacier de Vouasson

4.2.1.2 Col du Sanetsch research site

The debris flow at Col du Sanetsch differs from the other sites as only one debris flow event has been produced so far. Between 2012 and 2016, a flow with one channel and deposit was created (figure 22). Before 2012, there was no sight of any debris flow deposit. This means that the deposit and channel could not have been influenced by previous deposits and channels. Furthermore, a drone was used to map the flow with the view to create a DEM to calculate the volume. First, the grain size analysis was carried out at the research site. One analysis was necessary because the deposit consist of one lobe. The result is visible in table 19.

Table 19: Grain size analysis at Col du Sanetsch

Mean grain size Lime Stoffel’s Jakob’s Associated Maximum grain size (cm) (cm) content classification classification volume 10² - 10³ - (5 61,51718074 13,40625 10/10 Small 1 – 2 ( - 3) x 10³)

The interpretation of the grain size analysis is more ambiguous. Due to the maximum grain size, the flow could also reach to a size of 5000 m³. The morphometric properties method estimated the volume to be equal to 3020,973 m³. The descriptive properties method showed a volume of 32 423,4024 m³. The total inundated area of the flow equals 10 581,69 m² with a volume of 12 169,91537 m³. When only the lobe deposit is taken into account the area is 2942,22 m², which corresponds to a volume of 1784,299367 m³. The lobe deposit is also used to calculate the volume from the DEM. Figure 21 visualizes the extent of the deposit with erosion and deposition visualized.

Figure 21: Calculations of the volume from the DEM

Figure 22: Time-depth map of Col du Sanetsch

4.1.2.3 Overview of the measurements

Table 20 sums up all the measurements of the visited sites. The original measurements can be consulted in the annex 6.

Table 20: Summary of the measurements in m³ (*VIAR = Volume Inundated Area Relation)

Morphometric VIAR* Descriptive VIAR* (whole Location Grain size DEM properties (deposit) properties flow) Plan de Levri A 10² - 10³ 133,7764 1260,457273 1033,192125 8845,581558 NA Plan de Levri B 10² - 10³ 670,0147 967,78 3071,59889 3138,67257 NA

Col du Torrent (2001 – 2005) 10² - 10³ NA 384,667 NA NA 9721,724 Col du Torrent (2009 – 2016) 10² - 10³ NA 728,4128 NA NA

Glacier de Vouasson A (2001 – 10² - 10³ (- 5 x 103) 97,4581466 562,54306 153,9986554 NA 2005) Glacier de Vouasson A (2009 – 10² - 10³ 21,8785803 100,813282 1466,86732 5094,09 NA 2016), northern branch Glacier de Vouasson A (2009 – 10² - 10³ NA 40,74319319 NA NA 2016), southern branch Glacier de Vouasson B 10² - 10³ 33,42449 40,54206038 170,0379934 NA

Col du Sanetsch 10² - 10³ (- 5 x 103) 3020,973 1784,299367 32 423,4024 12169,91537 1807,92826

4.2.2 Volume-area relations in Val d’Hérens

The magnitude of all the debris flows in the Hérens Valley is based on the volume inundated area relation. Based on the area the flow occupies, the debris flows can be assigned to a size class (Jakob, 2005). Figure 23 represents the distribution of the Hérens debris flows in size classes. The size classes higher than six are not included, as there have never been debris flows discovered in these classes before. Most of the flows belong to size class three.

Figure 23: Number of debris flows and associated size class

Figure 24 shows the spatial distribution of the flows. The large flows are spread over the study area and are not clustered. Some appear isolated, while others are surrounded by smaller flows.

Figure 24: Magnitude distribution of the Hérens debris flows

4.3 Magnitude-frequency relation in Val d’Hérens

4.3.1 Magnitude-frequency representation

Figure 25 represents magnitude and frequency together. On the x-axis the size class of the flows are used. The categorical data facilitate the visualization of the magnitude-frequency relation. Most of the flows have a low frequency with one to two events and belong to size class 2 and 3. The largest group of flows belong to size class three and produced two events over time.

Figure 25 : Magnitude and frequency represented in a bubble chart

5. DISCUSSION

5.1 The use of a UAS in Alpine mountain environment

When using a drone in an Alpine mountain environment, some remarks can be made. First, one should reckon with the weather. Whenever there is heavy precipitation such as rain, it is not possible to conduct drone flights as this can damage the equipment of the drone. Fog causes disturbances and ambiguities on the pictures and makes it more difficult to see the drone. Also terrestrial recording of images is disadvantaged by fog. Furthermore, heavy wind withholds drone flying and was experienced the most during the drone campaign. The drone starts flying skewed and is deviating from the flight plan causing distortions on the photographs. The batteries also waste a lot of energy when flying against the wind. Heavy wind might even blow the drone against the rock wall.

Furthermore, Papa et al. (2016) stated that using a drone can be safer than an actual field survey because of the instability of the research site of interest. Even when using a drone, it is necessary to enter the research site as it is better to be close the flight zone of the drone to keep an eye on it. This applies mostly to the take-off and landing of the drone since this action is performed in manual mode by the controller (and not automated mode when the flight plan is conducted).

Moreover, the battery pairs of the used UAS - Drone Hexacopter GAUI 540H frame - only maintain for maximum 15 minutes. As a consequence, each separate flight took approximately 10 minutes to prevent the batteries from running out of energy. The charging of the batteries ranges from half an hour to an hour. Due to the short flight time, the substituting of the batteries and the recharging of the batteries is a time consuming activity during field work. A part of this problem was overcome because eight pairs of batteries were used plus two charging devices that each can handle four separate batteries. The placing of the targets can also lead to problems. A few targets were placed near a walking track and grassland and were taken away later on. If the targets are moved before the drone flight, the GPS measurements cannot be used and this could lead to inaccuracies when further processing the photographs.

Nevertheless, the use of UAS has received wide attention and shows many advantages for geosciences. (Carrivick et al., 2013; Adams et al., 2016; Custers, 2016). Compared to blimps, kites and laser scanners, drones offer a good balance between cost, survey speed and spatial coverage (Carrivick et al., 2013). The Drone Hexacopter GAUI 540H frame could easily be carried around on the field due to its light weight. Also, the parts of the drone be detached to facilitate transport.

5.2 The applicability of volume measurements for debris flow deposits in the field

The methodologies according to the volume measurements can be biased by deposition-area constraints and reworking. Both of them make a debris flow deposit deviate from its theoretical logical form and structure, which is assumed to have a straight channel and a lobate shaped deposit (Jakob & Hungr, 2005). Deposition area constraints points to how the existing environment influences the form and structure of a new debris flow. This includes for example previous debris flow deposits and present geomorphology (Stoffel, 2010). Reworking of debris flows exists due to, for instance, older deposits getting buried by more recent debris flow deposits, the regrowth of vegetation, animal trampling, anthropogenic reworking, rockfall, rock avalanches and snow avalanches and more (Rapp & Nyberg, 1981; van Steijn, 1996; Jomelli et al., 2009; Stoffel, 2010; Reynard et al., 2012). In some cases, severe debris flow events can completely wipe away any evidence of previous debris flow activity (Stoffel, 2010). This was for example visible for debris flow A near Glacier de Vouasson: only a small remnant of the 1977 event was visible because it got overburden by newer deposits.

The grain size analysis is biased by rockfall. One cannot always be sure that the measured rocks actually were transported by a debris flow. Some of the rocks were transported by rockfall and avalanches. This is certainly the case when a debris flow is deposited near a debris fan or on a talus slope. Big boulders that stick out of a matrix of finer material, are also considered not to be a part of the debris flow deposit. Finer sediment of the deposit is also lost due to the reworking of wind and rain (Stoffel, 2010). In some cases, an outwash of this finer material lies in front of the snout of the debris flow deposit. In some case, the lobate shape of the deposit is still visible in the field, but the rocks are too much covered by reformed soil and vegetation (Lambiel et al., 2016). Furthermore, the classification of Stoffel (2010) needs extension with data from other debris flows to get more delineated size classes.

The morphometric properties and descriptive properties method suffer the most as a theoretical structure of a debris flow is assumed. Older debris flows are buried by more recent ones. As a consequence, a part of their original shape is lost and as a consequence the volume of older deposits gets underestimated (Stoffel, 2010). Big boulders that lie within the path of the debris flow cause major disturbances to the shape. The debris mass is pressed against the boulder and is flushed around it causing the deposit to deviate from a lobate structure.

It seems that field measurements have different outcomes due to different interpretations of the deposit: the whole flow or the lobate deposit at the end of the debris flow channel (Berti & Simoni, 2007; Hungr et al., 2008; Scheidl & Rickenmann, 2010; Stoffel, 2010). For some researchers, the amount of field methods is rather scant (Jakob & Hungr, 2005; Papa et al., 2016). Papa et al., (2016) see more potential in remote methods such as terrestrial laser scanning (TLS) and UAS photogrammetry. Also the volume inundated area relation has received wide attention (Crosta et al., 2003; Berti & Simoni, 2007; Griswold & Iverson, 2008; Scheidl & Rickenmann, 2010). Apart from measuring on aerial pictures, delineation of the debris flow deposit using GPS measurements can generate more accurate data for the inundated area (Berti & Simoni, 2007). Overall, the applied method poses two difficulties. One when separate flows collide with one another: it is hard to distinct the flows from each other. Another difficulty is caused by vegetation cover. Debris flows that cross forested areas cannot be measured.

5.3 Frequency via aerial pictures towards other methods

In contrast to the magnitude, defining the frequency is more clear in literature. There are several clearly defined methods of which the interpretation of a time series of aerial pictures, lichenometry and dendrochronology are practiced the most (Rapp & Nyberg, 1981; van Steijn, 1996; Jakob & Hungr, 2005; Bollschweiler et al., 2007; Scheidl & Rickenmann, 2010; Stoffel, 2010). Lichenometry could not be applied as there was no lichen cover of the deposits. Dendrochronology can be can be carried out for debris flows crossing the tree line. Only a small part of the study area – five flows visible on inset map 3 on figure 16 – map In the Hérens Valley, dendrochronological data has already been collected during the ‘99 severe avalanche which could be of use for correlations (Wilhelm et al., 1999; Dängeli et al., 2009). To define the frequency via aerial pictures, mostly two to three pictures per decade were available. As such, maximum amount of events for a single debris flows depends on the amount of pictures. Two or more events are hard to determine between two consecutive time series of aerial pictures. To avoid inaccuracies, one event is assumed between two successive aerial pictures whenever change was noticed. Even then not every picture is useful. Pictures taken during the winter months, especially the ’99 series in February, cannot be used to recognize any geomorphological structures due to snow cover. Furthermore, aerial pictures can be disturbed due to shadows and cloudiness. Unlike dendrochronology, vegetation is rather disturbing for detection on aerial pictures. This can be overcome when using LiDAR images (Jakob & Hungr, 2005).

5.4 Possible explanations for the observed magnitude-frequency pattern

5.2.1 Climatic factors

The rise of debris flows between 1983 and 1988 is in all probability caused by a huge rainstorm event in 1987 that affected throughout Switzerland (Landeshydrologie und -geologie, 1988; Rickenmann & Zimmermann, 1993; van Steijn, 1996; Hegg et al., 2000). Also in 2005 and 2007, severe rainstorms affected Switzerland causing several debris flow events (Schmid et al., 2004; Scheidl & Rickenmann, 2010; Umbricht et al., 2013; Andres & Badoux, 2018). Figure 26 shows the correspondence of the debris flow activity in the Hérens Valley and the Swiss flood and damage database. Changes before 1970 are left out for the Hérens Valley.

Figure 26: Correspondence between cumulative debris flow activity in the Hérens Valley and cumulative cost damage in the Swiss flood and landslide damage database (source: Hilker et al. (2009))

Three apparent rises are visible in both charts, but not all trends from the database were observed in the Hérens Valley. Peaks of flooding and flows in 1978, 1999 and 2000 are not visible in the debris flow activity of the Hérens Valley. The most recent rise in flows, between 2009 and 2016, is more difficult to explain. About one third of the debris flows in the Hérens Valley produced a new event in that period. First of all, there is not many literature and/or reports available showing any evidence of a possible flooding and extreme rainfall after 2007 (Umbricht et al., 2013; Andres & Badoux, 2018). When taking a look at information from nearby weather stations - Les Diablerets, Sion, Evolène/Villa and Hérémence – some other hypotheses present themselves. Data from Les Diablerets could only be consulted since 2015 and is operational since 2013, which is too short to explain the rise between 2009 and 2016 (www.meteoswiss.admin.ch, 25/05/2018). Still, this station will be imported to correlate future changes of the Col du Sanetsch debris flow. For Sion monthly precipitation data since 1864 was consulted (www.meteoswiss.admin.ch, 26/10/2017). Figure 27 shows the maximum summer – June, July and August – precipitation since 1970 in Sion with indications towards the debris flow activity.

Figure 27: Maximum monthly summer precipitation at Sion and debris flow activity (source: MeteoSwiss, 2018)

The Sion precipitation data reflects general trends and specific trends. For example the rise of debris flows in the early ’70, can be linked with Sion maximum precipitation. After 2009, the peak in 2014 might explain the apparent debris flow activity. Still, the data from Sion might not be completely representative due to the lower elevation (482 m) of the station in the Rhône Valley. The snout elevation of the Hérens Valley debris flows is approximately 1500 m higher. The difference in local climate will play a role. From more nearby weather stations, Hérémence and Evolène/Villa, only the extreme value analysis of precipitation could be consulted (www.meteoswiss.admin.ch, 25/05/2018). At Hérémence, the 1-day peak precipitation, 2-day peak precipitation, 3-day peak precipitation, 4-day peak precipitation and 5- day peak precipitation only showed winter precipitation (www.meteoswiss.admin.ch, 25/05/2018). For Villa the 10-minute peak precipitation, one hour peak precipitation, two hour peak precipitation, three hour peak precipitation, four hour peak precipitation, five hour peak precipitation, six hour peak precipitation, eight hour peak precipitation, twelve hour peak precipitation and sixteen hour peak precipitation were available (www.meteoswiss.admin.ch, 25/05/2018). These data did show summer precipitation peaks in the following years: 1988, 1993, 1994, 1997, 2001, 2004, 2006, 2007 and 2011 (www.meteoswiss.admin.ch, 25/05/2018). These data also reflect general trends. For example, severe precipitation in 1993 and 2007. After 2009, a peak in 2011 was discovered. It must be said that the major part of the data at these two weather stations was classified as ‘doubtful’. Furthermore, Beniston & Stoffel (2016) mention both 2011 and 2014 as recent flood episodes. In the future, more accurate weather data will be available. In the Hérens Valley, another three weather stations – Barrage Grande Dixence, Arolla and Bricola – with focus on precipitation monitoring are operational since 2011 of which data could not be consulted (www.meteoswiss.admin.ch, 25/05/2018). The original weather data can be consulted in the annex 7. Apart from extreme rainfall, other climatic influences can contribute to the debris flow activity. For instance, an increase in rock glacier velocity in the Hérens Valley has been observed, as well as a complex discontinuous permafrost distribution (Reynard et al., 2012). Also, rain- on-snow events complement the described precipitation patterns (Beniston & Stoffel, 2016). Moreover, Bollschweiler & Stoffel (2010) confirm the dependency of debris flow activity on rainfall. Their study comprises the monitoring of debris flows since 1850 in nearby parallel valleys in the canton of Valais.

5.2.2 Geomorphic factors

The lithology in the Hérens Valley shows a high variability of rock types. The contribution of the lithology to debris flow activity depends on the erodibility (D’Agostino & Marchi, 2001; Tang et al., 2009). D’Agostino & Marchi (2001) set up a classification of the rock types with a geological index for debris flow predictions. The geological index is a score that represents the erodibility of the rock (D’Agostino & Marchi, 2001). The higher the score, the higher the erodibility (D’Agostino & Marchi, 2001). Table 21 shows their classification.

Table 21: Lithological classification with a geological index (source: D’Agostino & Marchi, 2001)

Lithology Geological Index

Quaternary deposits 5

Schists and phyllites 4

Marls, marly-limestone, siltstone, etc. 3

Volcaniclastic rocks 2

Dolomite and limestone rock 1

Massive igneous and metamorphic rocks 0

Several of these values apply to the Hérens Valley.

5.2.3 Catastrophic events

Several catastrophic incidents can occur in the canton of Valais and may effect debris flow activity. First of all, the Valais canton is the most active seismic region of Switzerland (Fritsche & Fäh, 2009; www.seismo.ethz.ch, 10/05/2018; www.earthquaketrack.com; 10/05/2018). The latest severe event dates from 1946, which caused up to 252 930 CHF total loss due to damage in the Hérens Valley (Fritsche & Fäh, 2009). The 1946 event had a magnitude of 6 on the Richter scale and, once every century, an event of that kind is expected (Fritsche & Fäh, 2009; www.seismo.ethz.ch, 10/05/2018). Apart from direct damage to buildings, the event produced secondary effects like rockfall, avalanches and landslides (Fritsche & Fäh, 2009). Even though a high seismic activity is observed, only few eartquakes are experienced by humans: out of the 270 recorded seismic activities in ten years, two to three per year were felt by people (www.seismo.ethz.ch, 10/05/2018). Also, debris flows themselves can provoke trembling, which can be detected by seismic equipment (Walter et al., 2017). Lake outburst are also important evokers of debris flows (Haerberli et al., 2001; Bardou & Delaloye, 2004; Huggel et al., 2004; Chiarle et al., 2007; Marchi et al., 2009). Mostly lakes at higher elevations – often glacial lakes – are important for debris flow activity. A last possible catastrophic event could induce debris flows, are dam breaks (Jakob & Hungr, 2005). There is the large Grande Dixence dam and a storage basin in Ferpècle (www.grande-dixence.ch, 19/02/2018; www.unige.ch, 10/05/2018). The latter is part of the Grande Dixence hydroelectric plant (www.unige.ch, 10/05/2018). The Grande Dixence dam is the largest gravity dam in the world and provides 20% of Switzerland energy (www.grande-dixence.ch, 19/02/2018). Measures against earthquakes have already been drawn up (Darbre, 2004). A possible outbreak will lead to more than the provoking of debris flow, but will probably cause a national disaster.

6. CONCLUSION

Like many other valleys in the Alps, the Hérens Valley and Col du Sanetsch are affected by debris flows. The majority of these flows produced one or two events since the start of their monitoring. The monitoring time of each separate flow and their first occurrence, highly depends on the availability of aerial pictures. Still, it was possible to have a good overview of debris flow activity over time in the whole Hérens Valley. When taking a look at this activity, several apparent rises could be observed, which were linked to severe rainstorms and damage cost in Switzerland. The debris flow activity reflects both general trends in severe precipitation, as well as local variation in precipitation. Other factors might as well have an influence on the activity: rock glacier acceleration, permafrost distribution, rain-on-snow events, the lithology and several catastrophic events. The field measurements of the magnitude of the visited sites show some variability. These measurements are biased by reworking, the present topography, older deposits, rockfall and more. Two out of three methods to measure debris flow magnitude, could not be applied at a research site due to a lack of deposition thickness. The remote methods, volume inundated area relation and volume calculation from DEM showed less difficulties, but multiple interpretations are possible. The volume inundated area relation applied for all debris flows in the Hérens Valley, showed that most flows belonged to size class 2 and 3. Debris flows up to size class 3 can damage larger buildings, highways, bridge piers and pipelines. The currently observed flows do not show any immediate threat. There is almost no infrastructure in the vicinity of a debris flow.

7. REFERENCES

7.1 Scientific Articles

Adams, M. S., Fromm, R., Lechner, V. (2016). High-resolution debris flow volume mapping with unmanned aerial systems (UAS) and photogrammetric techniques. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 2016– Janua(July), 749–755. https://doi.org/10.5194/isprsarchives-XLI-B1-749-2016 Agisoft. (2013). Agisoft PhotoScan User Manual : Professional Edition, Version 1.0.0. User Manuals, 70. Retrieved from http://www.agisoft.com/downloads/user-manuals/ Andres, N., Badoux, A. (2018). Unwetterschäden in der Schweiz im Jahre 2017. Wasser Energie Luft, 110(1), 67–74. Bardou, E., Boivin, P., & Pfeifer, H. R. (2007). Properties of debris flow deposits and source materials compared: Implications for debris flow characterization. Sedimentology, 54(2), 469–480. https://doi.org/10.1111/j.1365-3091.2007.00855.x Bardou, E., & Delaloye, R. (2004). Effects of ground freezing and snow avalanche deposits on debris flows in alpine environments. Natural Hazards and Earth System Science, 4(4), 519–530. https://doi.org/10.5194/nhess-4-519-2004 Beniston, M., & Stoffel, M. (2016). Rain-on-snow events, floods and climate change in the Alps: Events may increase with warming up to 4 °C and decrease thereafter. Science of the Total Environment, 571(January), 228–236. https://doi.org/10.1016/j.scitotenv.2016.07.146 Berti, M., & Simoni, A. (2007). Prediction of debris flow inundation areas using empirical mobility relationships. Geomorphology, 90(1–2), 144–161. https://doi.org/10.1016/j.geomorph.2007.01.014 Bollschweiler, M., & Stoffel, M. (2010). Changes and trends in debris-flow frequency since ad 1850: Results from the Swiss Alps. Holocene, 20(6), 907–916. https://doi.org/10.1177/0959683610365942 Bollschweiler, M., Stoffel, M., Ehmisch, M., & Monbaron, M. (2007). Reconstructing spatio-temporal patterns of debris-flow activity using dendrogeomorphological methods. Geomorphology, 87(4), 337–351. https://doi.org/10.1016/j.geomorph.2006.10.002 Bovis, M. J., & Jakob, M. (1999). the Role of Debris Supply Conditions in Predicting Debris Flow Activity. Earth Surface Processes and Landforms, 1054, 1039–1054. Bunte, K., & Abt, S. R. (2001). 2. Particle analysis. In Sampling Surface and Subsurface Particle-Size Distributions in Wadable Gravel- and Cobble-Bed Streams for Analyses in Sediment Transport , Hydraulics , and Streambed Monitoring (Vol. 0, pp. 14–106). Gen. Tech. Rep. RMRS-GTR-74. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. Retrieved from http://doi.wiley.com/10.1111/j.1530-9290.2011.00429.x Carrivick, J. L., Smith, M. W., Quincey, D. J., & Carver, S. J. (2013). Developments in budget remote sensing for the geosciences. Geology Today, 29(4), 138–143. https://doi.org/10.1111/gto.12015 Chiarle, M., Iannotti, S., Mortara, G., & Deline, P. (2007). Recent debris flow occurrences associated with glaciers in the Alps, 56, 123–136. https://doi.org/10.1016/j.gloplacha.2006.07.003 Crosta, G. B., Cucchiaro, S., & Frattini, P. (2003). Validation of semi-empirical relationships for the definition of debris-flow behavior in granular materials. International Conference on Debris-Flow Hazards Mitigation: Mechanics, Prediction, and Assessment, Proceedings, 2(1).

Custers, B. (2016). Drones Here, There and Everywhere Introduction and Overview. The Future of Drone Use (Vol. 27). https://doi.org/10.1007/978-94-6265-132-6 D’Agostino, V., & Marchi, L. (2001). Debris flow magnitude in the Eastern Italian Alps: Data collection and analysis. Physics and Chemistry of the Earth, Part C: Solar, Terrestrial and Planetary Science, 26(9), 657–663. https://doi.org/10.1016/S1464-1917(01)00064-2 Dängeli, S., Bollschweiler, M., & Stoffel, M. (2009). Jahrringe, Lawinen und eine zerstörte Alphütte. Schweiz Z Forstwes, 160(4), 87–92. https://doi.org/10.3188/szf.2009.0087 Darbre, G. R. (2004). Swiss guidelines for the eartquake safety of dams (pp. 1–12). Vancouver, B. C., Canada: 13th World Conference on Earthquake Engineering. Fritsche, S., & Fäh, D. (2009). The 1946 magnitude 6.1 earthquake in the Valais: Site-effects as contributor to the damage. Swiss Journal of Geosciences, 102(3), 423–439. https://doi.org/10.1007/s00015-009-1340-2 Glade, T. (2005). Linking debris-flow hazard assessments with geomorphology. Geomorphology, 66(1– 4 SPEC. ISS.), 189–213. https://doi.org/10.1016/j.geomorph.2004.09.023 Griswold, J. P., & Iverson, R. M. (2008). Mobility Statistics and Automated Hazard Mapping for Debris Flows and Rock Avalanches Scientific Investigations Report 2007 – 5276. USGS Scientific Investigations Report, 62. Haerberli, W., Kääb, A., Vonder Mühll, D., & Teysseire, P. (2001). Prevention of outburst floods from periglacial lakes at Grubengletscher, Valais, Swiss Alps. Journal of Glaciology, 47(156), 111–122. https://doi.org/doi:10.3189/172756501781832575 Hegg, C., Gerber, D., & Röthlisberger, G. (2001). Unwetterschaden-Datenbank der Schweiz. Interpraevent 2000 - Villach/Österreich, Tagungspublikation, 1, 37–48. Hegg, C., & Rhyner, J. (2011). for floods and debris flows, 509–527. https://doi.org/10.1007/s11069- 010-9507-8 Hilker, N., Badoux, A., & Hegg, C. (2009). The swiss flood and landslide damage database 1972-2007. Natural Hazards and Earth System Science, 9(3), 913–925. https://doi.org/10.1002/asl.183 Huggel, C., Haeberli, W., Kääb, A., Bieri, D., & Richardson, S. (2004). An assessment procedure for glacial hazards in the Swiss Alps. Canadian Geotechnical Journal, 41(6), 1068–1083. https://doi.org/10.1139/t04-053 Hungr, O., McDougall, S., Wise, M., & Cullen, M. (2008). Magnitude-frequency relationships of debris flows and debris avalanches in relation to slope relief. Geomorphology, 96(3–4), 355–365. https://doi.org/10.1016/j.geomorph.2007.03.020 Iverson, R. M. (1997). The physics of debris flows. Reviews of Geophysics, 35(3), 245–296. https://doi.org/10.1029/97RG00426 Jakob, M. (2005). A size classification for debris flows. Engineering Geology, 79(3–4), 151–161. https://doi.org/10.1016/j.enggeo.2005.01.006 Jakob, M., & Hungr, O. (2005). Debris-flow hazards and related phenomena. Canadian Geotechnical Journal (Vol. 42). https://doi.org/10.1139/t05-075 Jomelli, V., Brunstein, D., Déqué, M., Vrac, M., & Grancher, D. (2009). Impacts of future climatic change (2070-2099) on the potential occurrence of debris flows: A case study in the Massif des Ecrins (French Alps). Climatic Change, 97(1), 171–191. https://doi.org/10.1007/s10584-009-9616-0 Lambiel, C., Maillard, B., Kummert, M., & Reynard, E. (2016). Geomorphology of the Hérens valley (Swiss Alps). Journal of Maps, 12(1), 160–172. https://doi.org/10.1080/17445647.2014.999135 Landeshydrologie und -geologie, L. und. (1988). Hochwasserereignisse im Jahre 1987 in der Schweiz. Bundesamt Für Umweltschutz, (10), 1–144. Marchi, L., Chiarle, M., Mortara, G. (2009). Climate changes and debris flows in periglacial areas in the Italian alps. In Y. Taniguchi, M., Burnett, W.C., Fukushima, Y., Haigh, M., Umezawa (Ed.), From

Headwaters to the Ocean: Hydrological Changes and Watershed Management (pp. 111–115). Boca Raton: CRC Press. Retrieved from https://books.google.be/books?hl=nl&lr=&id=wMTLBQAAQBAJ&oi=fnd&pg=PA111&dq=Climate +changes+and+debris+flows+in+periglacial+areas+in+the+Italian+Alps&ots=9piw5VLDBl&sig=2f wKsiDNrXwRRpBZd3DCznVFT4g#v=onepage&q=Climate changes and debris flows in periglacial

Papa, M. N., Sarno, L., Ciervo, F., Barba, S., Fiorolla, F., & Limongiello, M. (2016). Field Surveys and Numerical Modeling of Pumiceous Debris Flows in Amalfi Coast (Italy). International Journal of Erosion Control Engineering, 9(4), 179–187. https://doi.org/10.13101/ijece.9.179 Pedrazzini, A., Humair, F., Jaboyedoff, M., & Tonini, M. (2016). Characterisation and spatial distribution of gravitational slope deformation in the Upper Rhone catchment (Western Swiss Alps). Landslides, 13(2), 259–277. https://doi.org/10.1007/s10346-015-0562-9 Rapp, A., & Nyberg, R. (1981). Alpine Debris Flows in Northern Scandinavia: Morphology and Dating by Lichenometry http://www.jstor.org/stable/520. Geographiska Annaler, 63(3-), 183–196. Reynard, E., Holzmann, C., Guex, D., & Summermatter, N. (2003). Géomorphologie et Tourisme, 21– 23. Reynard, E., Lambiel, C., & Lane, S. N. (2012). Climate change and integrated analysis of mountain geomorphological systems. Geographica Helvetica, 67(1/2), 5–14. https://doi.org/10.5194/gh-67- 5-2012 Rickenmann, D., & Zimmermann, M. (1993). The 1987 debris flows in Switzerland: documentation and analysis. Geomorphology, 8(2–3), 175–189. https://doi.org/10.1016/0169-555X(93)90036-2 Santi, P. M., Hewitt, K., VanDine, D. F., & Cruz, E. B. (2011). Debris-flow impact, vulnerability, and response. Natural Hazards, 56(1), 371–402. https://doi.org/10.1007/s11069-010-9576-8 Scheidl, C., & Rickenmann, D. (2010). Empirical prediction of debris-flow mobility and deposition on fans. Earth Surface Processes and Landforms, 35(2), 157–173. https://doi.org/10.1002/esp.1897 Schmid, F., Fraefel, M., & Hegg, C. (2004). Unwetterschäden in der Schweiz 1972 - 2002: Verteilung, Ursachen, Entwicklung. Wasser Energie Luft, 96(1–2), 21–28. Steck, A., Bigioggero, B., Dal Piaz, G. V, Escher, A., Martinotti, G., & Masson, H. (1999). Carte tectonique des Alpes de Suisse occidentales et des régions avoisinantes, 1:100000. Service Géologique National, Bern. Stoffel, M. (2010). Magnitude-frequency relationships of debris flows - A case study based on field surveys and tree-ring records. Geomorphology, 116(1–2), 67–76. https://doi.org/10.1016/j.geomorph.2009.10.009 Stoffel, M., Mendlik, T., Schneuwly-Bollschweiler, M., & Gobiet, A. (2014). “Possible impacts of climate change on debris-flow activity in the Swiss Alps.” Climatic Change, 122(1–2), 141–155. https://doi.org/10.1007/s10584-013-0993-z Tang, C., Zhu, J., Li, W. L., & Liang, J. T. (2009). Rainfall-triggered debris flows following the Wenchuan earthquake. Bulletin of Engineering Geology and the Environment, 68(2), 187–194. https://doi.org/10.1007/s10064-009-0201-6 Theule, J. I., Liébault, F., Loye, A., Laigle, D., & Jaboyedoff, M. (2012). Sediment budget monitoring of debris-flow and bedload transport in the Manival Torrent, SE France. Natural Hazards and Earth System Science, 12(3), 731–749. https://doi.org/10.5194/nhess-12-731-2012 Umbricht, A., Fukutome, S., Liniger, M. a, Frei, C., & Appenzeller, C. (2013). Seasonal Variation of Daily Extreme Precipitation in Switzerland. Scientific Report MeteoSwiss, (97), 122. van den Heuvel, F., Goyette, S., Rahman, K., & Stoffel, M. (2016). Circulation patterns related to debris- flow triggering in the Zermatt valley in current and future climates. Geomorphology, 272, 127–136. https://doi.org/10.1016/j.geomorph.2015.12.010 van Steijn, H. (1996). Debris-flow magnitude—frequency relationships for mountainous regions of

Central and Northwest Europe. Geomorphology, 15(3–4), 259–273. https://doi.org/10.1016/0169- 555X(95)00074-F Walter, F., Burtin, A., McArdell, B. W., Hovius, N., Weder, B., & Turowski, J. M. (2017). Testing seismic amplitude source location for fast debris-flow detection at Illgraben, Switzerland. Natural Hazards and Earth System Sciences, 17(6), 939–955. https://doi.org/10.5194/nhess-17-939-2017 Wilhelm, C., Wiesinger, T., Brundl, M., & Ammann, W. (1999). The Avalanche Winter 1999 in Switzerland - An Overview. Swiss Federal Institute for Snow and Avalanche Research SLF, Davos Switzerland, (February), 487–494.

7.2 Internet sources and other

De Wulf, A. (2015) Course of Photogrammetry. Unpublished. Ghent University. Earthquake Tracker (2018) Recent Eartquakes Near Valais, Switzerland. https://www.earthquaketrack.com/p/switzerland/valais/recent. 10/05/2018. ESRI (2017) Surface volume. http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/surface- volume.htm. 27/03/2018. ESRI (2017) Polygon volume. http://desktop.arcgis.com/en/arcmap/10.3/tools/3d-analyst- toolbox/polygon-volume.htm. 27/03/2018. Evolène-Région Tourisme (s.d.) Leisure & activities – Climbing & Mountaineering. https://www.evolene- region.ch/tourism/climbing-mountaineering.html. 22/03/2018. Federal Office of Topography swisstopo (s.d.) Lubis viewer . https://map.geo.admin.ch/?topic=swisstopo&layers=ch.swisstopo.lubis- luftbilder_schwarzweiss,ch.swisstopo.lubis- luftbilder_farbe&lang=de&bgLayer=ch.swisstopo.pixelkarte- farbe&layers_timestamp=99991231,99991231&catalogNodes=1430&E=2599761.31&N=1107576.31& zoom=4. 14/03/2017. Federal Office of Topography swisstopo (s.d.) Lubis viewer. https://map.geo.admin.ch/?topic=swisstopo&layers=ch.swisstopo.lubis- luftbilder_schwarzweiss,ch.swisstopo.lubis-luftbilder_farbe,ch.swisstopo.images-swissimage- dop10.metadata,ch.swisstopo.swissimage-product,ch.swisstopo.swissimage- product.metadata&lang=de&bgLayer=ch.swisstopo.swissimage&layers_timestamp=99991231,999912 31,,current,2016&E=2580857.46&N=1164833.45&zoom=1&layers_opacity=1,1,1,1,0.7&layers_visibilit y=false,false,false,false,true&catalogNodes=1430. 14/03/2017. Federal Office of Topography swisstopo (s.d.) Aerial photos. https://www.swisstopo.admin.ch/en/knowledge-facts/historical-images/aerial-photo.html. 14/03/2017. Federal Office of Topography swisstopo (s.d.) Swiss map projections. https://www.swisstopo.admin.ch/en/knowledge-facts/surveying-geodesy/reference-systems/map- projections.html. 19/03/2018. Federal Office of Topography swisstopo (s.d.) SWISSIMAGE 25 cm. https://shop.swisstopo.admin.ch/en/products/images/ortho_images/SWISSIMAGE. 22/03/2018.

Federal Office of Topography swisstopo (2014) National Map. https://map.geo.admin.ch/?topic=swisstopo&bgLayer=voidLayer&catalogNodes=1392,1430,1538,139 6,1397&lang=en&E=2588517.50&N=1133287.50&zoom=8&layers=ch.swisstopo.pixelkarte-farbe- pk25.noscale. 19/05/2018.

Federal Office of Topography swisstopo (1975) Atlas of Switzerland - Overview of geomorphology. https://map.geo.admin.ch/?topic=swisstopo&layers=ch.swisstopo.geologie- 77 geomorphologie,ch.swisstopo.swissboundaries3d-gemeinde-flaeche.fill,ch.swisstopo- vd.ortschaftenverzeichnis_plz&lang=en&bgLayer=ch.swisstopo.pixelkarte- farbe&E=2590264.16&N=1128529.54&zoom=5&layers_opacity=0.6,1,0.75&catalogNodes=1476&laye rs_visibility=true,false,false. 19/05/2018.

Federal Office of Meteorology and Climatology MeteoSwiss (2016) Automatic monitoring network. http://www.meteoswiss.admin.ch/home/measurement-and-forecasting-systems/land-based- stations/automatisches-messnetz.html?station=dia. 25/05/2018.

Federal Office of Meteorology and Climatology MeteoSwiss (2018) Homogeneous data series since 1864. http://www.meteoswiss.admin.ch/home/climate/swiss-climate-in-detail/homogeneous-data- series-since-1864.html?station=sio. 26/10/2017.

Federal Office of Meteorology and Climatology MeteoSwiss (2016) Standard period 1966 – 2015. http://www.meteoswiss.admin.ch/home/climate/swiss-climate-in-detail/extreme-value- analyses/standard-period.html?. 25/05/2018.

Google (2018) Een kaart in de loop van de tijd bekijken. https://support.google.com/earth/answer/148094?hl=nl. 22/03/2018.

Hanke, J. (2009) Dive into the new Google Earth. https://googleblog.blogspot.be/2009/02/dive-into-new- google-earth.html. 22/03/2018. Hobart, M. K. (2005) The “Acid Test” for Carbonate Minerals and Carbonate Rocks. https://geology.com/minerals/acid-test.shtml. 22/02/2018.

MeteoSwiss (2018) The Climate of Switzerland. http://www.meteoswiss.admin.ch/home/climate/the- climate-of-switzerland.html. 19/05/2018.

MeteoSwiss (2017) Gewitterregen. http://www.meteoswiss.admin.ch/home/climate/the-climate-of- switzerland/specialties-of-the-swiss-climate/gewitterregen.html. 19/05/2018.

N. N. (s.d.) Grande Dixence. http://www.grande-dixence.ch/. 19/02/2018. Swiss Seismological Service (2016) Earthquake Country Switzerland. http://www.seismo.ethz.ch/en/knowledge/earthquake-country-switzerland/. 10/05/2018. Swiss Seismological Service (2016) Seismic Hazard Switzerland. http://www.seismo.ethz.ch/en/knowledge/seismic-hazard-switzerland/. 10/05/2018. Swiss Seismological Service (2016) Earthquakes in the Valais. http://www.seismo.ethz.ch/knowledge/earthquake-country-switzerland/regional- earthquakes/valais/index.html. 10/05/2018. Wildi, W., Gurny-Masset, P., Sartori, M. (2015) Glacial landscapes of the Val d’Hérens (Valais, Switzerland) http://www.unige.ch/forel/fr/services/guide/valdherens/. 10/05/2018.

7.3 Software

Agisoft Photoscan Professional ArcMap ESRI 10.1 Google Earth Pro

Leica Geo Office 8.3 Mission Planner OpenLayers plugin Quick Map services plugin Point sampling tool Quantum GIS 3

8. ANNEXES

8.1 Annex 1: GPS measurements

GPS measurements can be consulted in the digital annex file. For the base and rover measurements, original data from the GPS devices are presented as well as CSV exports from Leica Geo Office. An extra Excel with decimal coordinates was created as input for the Agisoft project. From the field measurements, the GPX files were saved. Two handheld GPS’s (named ‘3’ and ‘K3’) were used. For each GPS a separate folder is created.

8.2 Annex 2: Agisoft Photoscan workflow and final data

First, all photos are added to a new chunk. Thereafter, the quality of the data can be estimated. Images with a low quality are disabled. Apart from the quality, a general selection has to be made. The more pictures involved in the project, the longer the calculation of the modelling. For all of the four different sites around 100 images were used for the modelling, which is already a lot. Secondly, the images are aligned at highest accuracy. Thirdly, the targets are indicated on all enabled images. For the detailed GPS measurements near Col du Sanetsch, the decimal coordinates are added. The coordinate system in the settings had to be changed from ‘Local’ to ‘WGS84’. For the terrestrial measurements, scale bars are created in the reference tab. Fourthly, alignment optimization is applied with ‘Fit f’, ‘Fit p1’ and ‘Fit p2’ enabled. From there on, the different steps can be combined in a batch file: building a dense point cloud, building a mesh and building a texture. Ultra-high density and high face count are used for the dense cloud and the mesh, respectively. For the UAS modelling, ‘build DEM’ is applied to create the final DEM. For the sites with terrestrial survey, ‘build orthophotos’ is applied. Because the orthophotomosaics are not georeferenced, one has to make sure the plane is right. The view from ‘above’ has to be exported. For these two final steps, standard settings were used. The outcome can be found in the digital annex.

8.3 Annex 3: ArcMap and QGIS workflow to calculate the deposited volume

Throughout intermediate results/layers will be mentioned that are presented in the digital annex.

(1) Create point layer and polygon layer with the points presenting the contours of the surface of interest. A Google Satellite image via the QuickMapServices plugin was used in QGIS to draw both layers.

(2) Assigning height values to the points based on the produced DEM. For this, another plugin, the point sampling tool is used. From the DEM height values have to be abstracted.

(3) Converting the DEM and point layer from WGS84 to WebMercator to continue in a metric system. The shapefiles from the previous to steps are already converted. It is necessary to work in the metric system to obtain values in m³. In the ArcToolbox > Data Management Tools > Projections and Transformations > Feature > Project.

(4) Creating a TIN surface from the converted point layer. This is the reference plane. For this 3D analyst needs to be enabled. In the ArcToolbox > 3D Analyst Tools > Data Management > TIN > Create TIN.

(5) Converting the TIN surface to a raster surface. In the settings, the raster needs to have the same cell size as the DEM obtained from Agisoft (which can be found in annex 1). In the ArcToolbox > 3D Analyst Tools > Conversion > From TIN > TIN to raster.

(6) Clipping the DEM and raster surface with the polygon layer from step 1. In this way, the data from the exact surface is obtained. In the ArcToolbox > Data Management Tools > Raster > Raster Processing > Clip.

(7) Substract the interpolated raster surface from the DEM. For this Spatial Analyst needs to be enabled. In the ArcToolbox > Spatial Analyst Tools > Map Algebra > Raster Calculator. Final volume can be consulted in the following tab: click right on the layer and go to properties > symbology > classified > classify > classification statistics. The ‘Sum’ has to multiplied with the cell size to obtain the volume in m³.

8.4 Annex 4: Map data and creation

8.4.1 Maps of the study area

All the data are presented in the digital annex. A distinction is made between newly created data and background data.

8.4.2 Maps showing magnitude and frequency of all the flows

The data presented on these maps can be found in the digital annex. New layers and source layers can be discerned.

8.4.3 Data of the time-depth maps 81

The data can be consulted in the digital annex.

8.5 Annex : Temporal changes in number of debris flow events

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60 Cumulative number number eventsofCumulative 40

0 1940 1950 1960 1970 1980 1990 2000 2010 2020 Years

Figure 28: Cumulative number of events for the Hérens Valley debris flows

8.6 Annex 6: Field measurements and derived charts

All the original data are presented in the digital annex. A distinction is made between measurements concerning all the debris flows and measurements of the visited sites. For all the flows, an Excel contains the data and derived charts. Polygons on which the measurements of the volume inundated area relation were based, were exported from Swisstopo in kml files. These files are also in the digital annex.

8.7 Annex 7: Weather data

The original weather data are summed up in the digital annex.