GeoLog

Earth Surface Dynamics

Imaggeo on Mondays: how short-term storms can impact our landscapes

Imaggeo on Mondays: how short-term storms can impact our landscapes

In the Sierra de Aconquija, a mountain range in the southern Central Andes of Argentina, strong storms often come and go at a moment’s notice, but they can have a long-lasting impact on the Earth’s surface.

The thunderstorm cell featured in this photo formed in less than half an hour, giving all those nearby only a few minutes to take cover. Mitch D’Arcy, a geomorphologist and postdoctoral researcher at the University of Potsdam and the GFZ German Research Centre for Geosciences, had the opportunity to witness this storm (and snap this picture!) while carrying out field work in the area.

“It was a spectacular experience, pouring heavy rain onto a very localised part of the mountain range, but it was also a hazard because the storm was quickly moving towards us with a lot of lightning. Without any trees around, we were likely targets for lightning strikes!” said D’Arcy. Luckily, he and his colleagues were able to find shelter in their truck while the huge downpour passed over them.

These kinds of thunderstorms are short-lived, but have intense precipitation rates. In this case, the temperature dropped by 14 degrees Celsius, and the storm was accompanied by heavy hail and lightning. And while these natural hazards are transient, they can have a long-term impact on the region’s landscape. Severe storms are capable of triggering landslides and floods and can relocate large amounts of sediment and debris in a short period of time.

D’Arcy is part of an international research programme called StRATEGy (Surface processes, Tectonics and Georesources: The Andean foreland basin of Argentina), which looks into how past and present climate change makes a mark on the terrain of the Argentine Andes, among other topics.

This research is essential for understanding and predicting how human-caused climate change will alter weather patterns and impact surface processes (such as how quickly sediments are eroded and transported across landscapes), according to D’Arcy. Having a better understanding of these surface processes and their sensitivity to the climate could help scientists better inform the public about how to prepare for natural hazards, such as flooding, erosion and landslides.

D’Arcy notes that it’s also important to assess how climate and weather trends will impact the sedimentary record, since it is one of the only physical records that scientists can use to examine how the Earth’s surface has change through time.

“North-western Argentina is a fascinating place to study how climate change affects surface processes, because it has experienced pronounced and abrupt changes in hydroclimate through time,” said D’Arcy. Their research has found that even subtle changes in the region’s climate have produced large changes to the surface environment, impacting how rivers take shape and how sediments move.

For example, while the Sierra de Aconquija is a semi-arid environment today, more than 12,000 years ago it used to be much wetter as a result of global climate changes. In fact, back then the mountain range was covered in glaciers and many of the basins were filled with lakes.

“It’s really important that we understand how different landscapes function and how they react to changes in climate. When we look at places like the southern Central Andes in Argentina, we find that the landscape records interesting signatures of ancient climate changes in Earth’s past. However, one of the big questions we still don’t have a good answer to, is how important are these very intense but rare storms for shaping landscapes and creating the sedimentary record from the geological past,” said D’Arcy.

By Olivia Trani, EGU Communications Officer

Imaggeo is the EGU’s online open access geosciences image repository. All geoscientists (and others) can submit their photographs and videos to this repository and, since it is open access, these images can be used for free by scientists for their presentations or publications, by educators and the general public, and some images can even be used freely for commercial purposes. Photographers also retain full rights of use, as Imaggeo images are licensed and distributed by the EGU under a Creative Commons licence. Submit your photos at http://imaggeo.egu.eu/upload/.

Back for the first time: measuring change at Narrabeen–Collaroy Beach

Back for the first time: measuring change at Narrabeen–Collaroy Beach

Narrabeen–Collaroy Beach in New South Wales, Australia, just north of Sydney, is home to one of the longest-running shoreline-measurement programmes in the world. With colleagues at the University of New South Wales (UNSW) Sydney, Eli Lazarus, an associate professor in geomorphology at the University of Southampton, UK, has been analysing over 40 years of data from Narrabeen–Collaroy to better understand how shorelines recover from major storm events.

In this blog post, Lazarus shares a glimpse of the programme’s history and describes his experience of visiting a field site that for him is both familiar and brand new.

“Want to see what an old GPS unit looks like after it’s been up and down the beach a thousand times?”

Mitchell Harley, a Scientia Fellow and coastal researcher at the UNSW Sydney Water Research Laboratory (WRL), in Manly Vale, Australia, handed me a battered, corroded, steel-cased receiver the size of a grapefruit. “It’s also seen a lot of Duct Tape.”

He loaded a carbon-fibre survey staff and a yellow Pelican case containing a new, a top-of-the-line Trimble GPS handset into the back of a WRL vehicle. With two visiting masters students – Tim van Dam from TU Delft, and Yann Larré from École Polytechnique – we set off on our afternoon excursion, to Narrabeen.

View of Narrabeen Beach, looking south from Narrabeen Headland. Credit: Eli Lazarus

Facing the open South Pacific, Narrabeen and Collaroy are the northern and southern halves of an embayed beach, a reach of sand framed at either end by rocky promontories, that extends approximately three-and-a-half kilometres between Narrabeen Headland and Long Reef Point. Narrabeen is the keystone of the Northern Beaches, a chain of sandy pockets defining the coastal peninsula north of Sydney. The beaches darken in colour with each embayment, from dun in the south to a reddish ochre in the north, representative of the ancient sandstone bedrock units in which they sit.

Narrabeen is a legendary surf break and home turf to a roll of world champions, where, to date, the locals have successfully prevented the installation of anything that resembles a surf cam. But the beach is also home to one of the longest-running and most complete beach-survey programmes in the world (Turner et al., Sci Data 2016).

In 1976, the renowned coastal scientist Andy Short, who used to live in Narrabeen, began the programme from the beach across the street from his house. He and family members, colleagues, friends, and volunteers diligently measured a set of cross-shore profiles along the full Narrabeen–Collaroy embayment every month for 30 years.

All long-term monitoring endeavours are labours of love. But frequent, detailed measurements of beach morphology, maintained consistently over long time scales, are exceptionally rare, and they offer essential quantitative insight into coastal events, changes, and cycles that occur more rapidly than most records tend to capture.

Harley took over the measurement programme in 2006, along with Ian Turner, who now directs the Water Research Lab, and recorded more than 120 monthly surveys of the full beach with a quad-bike Harley would trailer back and forth from Manly Vale.

Harley’s quad-bike – and shoreline-survey workhorse – at the UNSW Sydney Water Research Lab. Credit: Eli Lazarus

The Water Research Laboratory team has continued to experiment with different measurement methods for the Narrabeen–Collaroy system. Mounted on the top floor of the Flight Deck, a beachfront hotel where Narrabeen blends into Collaroy, is an array of five cameras, known as an Argus station, that takes time-averaged photos of the shoreline and surf zone. Tucked in among the cameras is a smoked-glass dome that looks like a space helmet: a lidar unit that uses a laser to measure wave swash and a cross-shore profile of beach elevation five times every second.

On our outing, Harley first drove us up Narrabeen Headland, to get an unobstructed southerly view of the bay. At the overlook was a stainless-steel post with a frame to hold a smartphone. This was the Narrabeen CoastSnap station.

In 2017, Harley, along with collaborators from the New South Wales State Government, launched the CoastSnap programme to collect crowd-sourced observations of beach dynamics (Harley et al., 2019). The process is simple: take a photo, post the image on social media with the station hashtag (#CoastSnapNarra, for example), and if you don’t post it right away, then write in the date and time of the image. With some clever analytical tricks, an algorithm finds the shoreline in your photo. Harley installed the first CoastSnap station at Manly Beach, above the Manly Surf Life Saving Club. There are now more than 35 CoastSnap stations in nine countries around the world.

Harley pointed out the various permanent features the algorithm uses to identify the shoreline position in every #CoastSnapNarra photo: an inlet hazard sign, the corners of prominent buildings in the foreground and distance. “We get about an image a day from people up here,” he said. Watching a sparse line-up of surfers work a peeling break at Narrabeen Inlet, we stood eating steak pies from The Upper Crust – like the surfers, another local institution.

Pies finished, we looped back down to the north end of the beach and assembled the GPS. The four of us would take turns walking the GPS receiver down the five main cross-shore transects still sampled at Narrabeen and Collaroy every month, and the three visitors would get our names added to the dataset’s long list of contributors.

Harley, Larré (holding GPS) and van Dam working through a beach profile. Credit: Eli Lazarus

In a reversal of cart and horse, I had written a scientific article about Narrabeen but never seen it. In fact, I was there in Sydney to visit people I had co-authored with but never met in person.

Earlier this year, Harley, Chris Blenkinsopp (of Bath University in the UK, and a former postdoc at WRL), Turner, and I published a paper in the EGU journal Earth Surface Dynamics about the information that shoreline records retain or destroy regarding the environmental conditions that shape them (Lazarus et al., 2019).

Extreme storm events, for example, can inscribe dramatic changes in the shape of a coastline. A detailed, high-frequency record of shoreline position presumably should reflect something about the magnitude of those events. But sedimentary systems can be very effective at obscuring or erasing their own histories, and not all evidence of conditions that impact a shoreline gets preserved. This phenomenon is known as ‘signal shredding’. The exceptional data catalogue for Narrabeen–Collaroy enabled us to pursue the first empirical test of signal shredding at a sandy beach, an idea I’d puzzled over since geomorphic signal-shredding was first described for other sediment-transport systems almost ten years ago (Jerolmack & Paola, 2010).

Among our survey crew, I asked to take Profile 4, near the middle of the embayment, because that was the record I had used the most when working through the signal-shredding analysis. To me, Profile 4 seemed to best capture, in a single line, the spatially variable character of the beach overall.

As we leapfrogged our way south, the beach profile became steeper and narrower. Harley mentioned an article that he had published with Turner and Short (Harley et al., 2015) that described, among other patterns at Narrabeen, a spatial pattern in the beach slope. If one end of the beach was steeply sloping toward the water, then the other end would be flat. The steep stretches of the beach tended to be narrow, and the flat stretches tended to be wide. Under certain wave conditions, the narrow, steep end of the would switch to being wide and flat, and vice versa – a pattern typical of embayed beaches called ‘rotation’.

As Harley described the slope pattern, the observation struck me as the kind that comes from investing time at a field site: the intuition internalised by surveying the beach over and over again in the seat of a quad-bike, from tipping sideways in the steeps and tracing the long meanders of the shoreline across the flats.

Standing astride the sharp break in beach slope at Collaroy, looking south toward Long Reef. Credit: Eli Lazarus

We finished the day with a walk around Long Reef, at Collaroy, looking back into the embayment we’d spent the afternoon traversing. Hang-gliders drifted in slow figure-eights above us. I was headed back to the UK the next day. There is more work to be done at Narrabeen, for sure, and we talked about what’s coming next: algorithms for predicting shoreline position (Davidson et al., 2017), fresh insights into beach recovery after major storms (Phillips et al., 2019), identifying shorelines from catalogues of satellite imagery (Vos et al., 2019). We talked about possible funding avenues to keep fuelling our collaboration.

The wind picked up, and the waves set to work rearranging the shoreline we had just measured.

Day’s end and hang-gliders at Long Reef, looking northwest toward Collaroy and Narrabeen. Credit: Eli Lazarus

By Eli Lazarus, University of Southampton, UK

Dr Eli Lazarus (@envidynxlab) is an Associate Professor in Geomorphology in the School of Geography & Environmental Science at the University of Southampton, UK.

 

GeoSciences Column: Can seismic signals help understand landslides and rockfalls?

GeoSciences Column: Can seismic signals help understand landslides and rockfalls?

From the top of a small gully in the French Alps, a 472 kg block is launched into the chasm. Every detail of it’s trajectory down the slope is scrutinised by two cameras and a network of seismometers. They zealously record every bounce, scrape and tumble – precious data in the quest to better understand landslides.

What makes landslides tick?

In 2016, fatalities caused by landslides tipped 2,250 people. The United States Geological Survey (USGS) estimates that between 25 and 50 people are killed, annually, by landslides in the United States alone. Quantifying the economic losses caused by landslides is no easy task, but the costs are known to be of economic significance.

It is paramount that the mechanisms which govern landslides are better understood in hopes that the knowledge will lead to improved risk management in the future.

But landslides and rockfalls are rarely observed in real-time. Deciphering an event, when all you have left behind is a pile of debris, is no easy task. The next best thing (if not better than!) to witnessing a landslide (from a safe distance) is having a permanent record of its movement as it travels down a slope.

Although traditionally used to study earthquakes, seismometers have now become so sophisticated they are able to detect the slightest ground movements; whether they come from deep within the bowels of the planet or are triggered by events at the surface. For some year’s now they have been an invaluable tool in detecting mass movements (an all-encompassing term for the movement of bed rock, rock debris, soil, or mud down a slope) across the globe.

More recently, processing recorded seismic signals triggered by large catastrophic events has not only allowed to identify when and where they occurred, but also their force, how quickly they travel, gain speed and their direction of movement.

This approach gives only a limited amount of data for scientists to work with. After all, large, catastrophic, mass movements represent only a fraction of the landslide and rockfall events that occur worldwide. To gain a fuller understanding of landslide processes, information about the smaller events is needed too.

So, what if scientists could use a seismic signal which is generated by all mass movements, independent of their size?

The high-frequency seismic signal

A high-frequency seismic signal is generated as the individual particles, which combined make up a landslide or rockfall, bounce and tumble against the underlying layer of rock. Would it be possible to, retrospectively, find out information about the size and speed at which individual particles traveled from this seismic signal alone?

This very question is what took a team of scientists up into the valleys of the French Alps.

At a place where erosion carves gullies into lime-rich muds, the researchers set-up two video cameras and network of seismometers. They then launched a total of 28 blocks, of weights ranging from 76 to 472 kg, down a 200 m long gully and used the data acquired to reconstruct the precise trajectory of each block.

The impacts of each block on the underlying geology, as seen on camera, were plotted on a 3D representation of the terrain’s surface. From the time of impact, block flight time and trajectory, the team were able to find out the velocity at which the blocks travelled and the energy they carried.

View from (a) the first and (b) the second video cameras deployed at the bottom of the slope. The ground control points are indicated by blue points. (c) Trajectory reconstruction for block 4 on the DEM, built from lidar acquisition, superimposed on an orthophoto
of the Rioux-Bourdoux slopes. Each point indicates the position of an impact and the colour gradient represents the chronology of these impacts (blue for the first impact and red for the last one). K2 is a three-component short-period seismometer and K1, K3 and K3 are vertical-only seismometers. CMG1 is a broad-band seismometer. From Hibert, C. et al., 2017. (Click to enlarge)

As each block impacted the ground, it generated a high-frequency seismic signal, which was recorded by the seismometers. The signals were processed to see if information about the (now known) properties of the blocks could be recovered.

Following a detailed analysis, the team of scientists, who recently published their results in the EGU’s open access journal Earth Surface Dynamics, found a correlation between the amplitude (the height of the wave from it’s resting position), as well as the energy of the seismic signals and the mass and velocities of the blocks before impact. This suggests that indeed, these high-frequency seismic signal can be used to find out details about rockfall and landslide dynamics.

But much work is left to be done.

There is no doubt that the type of substrate on which the particles/blocks bounce upon play a large part in governing the dynamics of mass movements. In the case of the French Alps experiment, the underlying geology of lime-rich muds was very soft and absorbed some of the energy of the impacts. Other experiments (which didn’t use single blocks), performed in hard volcanic and metamorphic rocks, found energy absorption was lessened. To really get to the bottom of how much of a role the substrate plays, single-block, controlled release experiments, like the one described in the paper, should be performed on a variety of rock types.

At the same time, while this experiment certainly highlights a link between seismic signals and individual blocks, rockfalls and landslides are made up of hundreds of thousands of particles, all of which interact with one another as they cascade down a slope. How do these complex interactions influence the seismic signals?

By Laura Roberts Artal, EGU Communications Officer

References and resources:

Hibert, C., Malet, J.-P., Bourrier, F., Provost, F., Berger, F., Bornemann, P., Tardif, P., and Mermin, E.: Single-block rockfall dynamics inferred from seismic signal analysis, Earth Surf. Dynam., 5, 283-292, doi:10.5194/esurf-5-283-2017, 2017.

USGS FAQs: How many deaths result from landslides each year?

The human cost of landslides in 2016 by David Petley, published, 30 January 2017 in The Landslide Blog, AGU Blogosphere.

[Paywalled] Klose M., Highland L., Damm B., Terhorst B.: Industrialized Countries: Challenges, Concepts, and Case Study. In: Sassa K., Canuti P., Yin Y. (eds) Landslide Science for a Safer Geoenvironment. Springer, Cham, (2014)