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Real‐time Permafrost Monitoring in Matter ValleyReal‐time Permafrost Monitoring in Matter ValleyJan Beutel, ETH ZurichJan Beutel, ETH Zurich
PermaSense
• Interdisciplinary geo‐science and engineering collaboration• Consortium of several projects, start in 2006• Fundamental as well as applied research
– Long‐term, high‐quality sensing in harsh environments– Better quality data, obtained online– Measurements that have previously been impossible– Enabling new science, answering fundamental questions related to
decision making, natural hazard early‐warning
• More than 35 people, 17 PhD students
Our Field Sites: Precision Scientific Instruments
Miniature Low‐Power Wireless Sensors
• Static, low‐rate sensing (120 sec)• Simple scalar values: voltages, resistivity, digital sensors• 4‐5 years operation (~200 μA avg. power)• ~0.1 Mbyte/node/day• 6+ years experience, ~946,838,342 data points
4
Our patient does not fit into a laboratory
So the laboratory has to go on the
mountain
A base station collects and relays
the data to the valley
[B. Buchli, F. Sutton, J. Beutel and L. Thiele: Dynamic Power Management for Long‐Term Energy Neutral Operation of Solar Energy Harvesting Systems. Proc. SenSys 2014.B. Buchli, F. Sutton, J. Beutel and L. Thiele: Towards Enabling Uninterrupted Long‐Term Operation of Solar Energy Harvesting Embedded Systems. Proc. EWSN 2014M. Keller, J. Beutel and L. Thiele: The Problem Bit. Proc. DCOSS 2013 ★ Best Paper Award ★B. Buchli, D. Aschwanden and J. Beutel: Battery State‐of‐Charge Approximation for Energy Harvesting Embedded Systems. Proc. EWSN 2013.M. Keller, J. Beutel and L. Thiele: How Was Your Journey? Uncovering Routing Dynamics in Deployed Sensor Networks with Multi‐hop Network Tomography. Proc. SenSys 2012.]
Online Data Management & Access• Global Sensor Network (GSN)
– Data streaming framework from EPFL (K. Aberer)– Organized in “virtual sensors”, i.e. data types/semantics– Hierarchies and concatenation of virtual sensors enable on‐line processing– Dual architecture translates data from machine representation to SI values,
adds metadata
Data from field site is received by the private GSN server “as is” and storedin a primary database.
Data is passed on to a public GSN server where it is mapped to metadata (positions, sensor types, calibration) and converted to convenient data formats.
Data is available for download and analysis using external tools.
firewall
WLAN Long‐haul Communication
• WLAN (802.11a) backbone using directional links• Leased fiber/DSL from Zermatt Bergbahnen AG to mountaintop
Randa Grossgufer Relay Station
Shallow Rock/ice Temperature Profiles
Aim: Understand temperatures in heterogeneous rock and ice• Measurements at several depths• Two‐minute interval, autonomous for several years• Survive, buffer and flush periods without connectivity
[A. Hasler, S. Gruber & W: Haeberli: Temperature variability and thermal offset in steep alpine rock and ice faces. The Cryosphere, 5, 977‐988.]
Assessment of Kinematic Behavior
• 1 and 2‐dimensional crackmeter instrumentation in the 2003 rockfall detachment zone
C2
C20 C1
The clefts at Hörnliridge move in distinct patterns
•[A. Hasler, S. Gruber and J. Beutel: Kinematics of steep bedrock permafrost.J. Geophys. Res., 117, F01016.]
2009 2010 2011 201420132012
62mm
Strong Stepwise Opening in SummertimeC2
C2 C2 C2
Reinforcementby snowmelt
•[A. Hasler, S. Gruber and J. Beutel: Kinematics of steep bedrock permafrost.J. Geophys. Res., 117, F01016.]
C2C2
2003 2009-2015
[B. Jelk]
High‐resolution Timelapse Photography
2009
C2
2010
C2
2011
C2
2012
C2
2013
C2
2014
C2
18.05.2015
C2
19.05.2015
C2
29.05.2015
C2
Why did C2 fail on
18.05.2015?
Cleft opening
Rock temperature
x [
mm
]T
[°C
]
zero curtain =
local snowmelt
>10 mm fluid precipitation in 30
min
Matterhorn Cleft Kinematic
How did C2 behave
since then?
Cleft opening
Rock temperature
x [
mm
]T
[°C
]
Matterhorn Cleft Kinematic
Recent Avenues: Micro‐seismic profiling
10 1
10 3
10 5
MS/
AE
rate
(/da
y)
Seismometer (1-100 Hz)Accelerometer (10-10 4 Hz)AE CH1: Piezo R.45 (5-30 kHz)AE CH2: Piezo R6a (35-80 kHz
Dec/17 Dec/22 Dec/27 Jan/01 Jan/06 Jan/11 Jan/16
-10
0
10
20
Roc
k te
mpe
ratu
re (°
C)
5 cm20 cm50 cm
10 1
10 3
10 5
MS/
AE
rate
(/da
y)
Seismometer (1-100 Hz)Accelerometer (10-10 4 Hz)AE CH1: Piezo R.45 (5-30 kHz)AE CH2: Piezo R6a (35-80 kHz
Jul/15 Jul/20 Jul/25 Jul/30 Aug/04 Aug/09 Aug/14
-10
0
10
20
Roc
k te
mpe
ratu
re (°
C)
5 cm20 cm50 cm
GeophonesAccelerometersPiezo Acoustics
[J. Beutel et al: X‐Sense: Sensing in Extreme Environments. Proc. Design, Automation and Test in Europe (DATE 2011)
V. Wirz et al: Temporal characteristics of different cryosphere‐related slope movements in high mountains. Proc. Second World Landslide Forum, 2011.
B. Buchli, F. Sutton and J. Beutel: GPS‐equipped Wireless Sensor Network Node for High‐accuracy Positioning Applications. Proc. EWSN 2012.]
Matter Valley: Detecting Large‐Scale Mass Movements
Wireless L1‐DGPS sensors detect millimeter‐scale
process dynamics
[Wirz, V. et al: Estimating velocity from noisy GPS data for investigating the temporal variability of slope movements, Nat. Hazards Earth Syst. Sci., 14, 2503‐2520, 2014.V. Wirzet al: Short‐term velocity variations at three rock glaciers and their relationship with meteorological conditions. Earth Surface Dynamics, 4, 1, p. 103‐123, 2016.]
Real‐time Experimentation at Valley‐Scale
Access to Real‐time Data for Early Warning Decision‐making
Bielzug Debris Flow, June 2013• Critical natural hazard event• Herbriggen partial village evacuation• Closure of road and railway to
Zermatt
Längschnee, Fall 2014• Constructive measures securing rock
boulders above Herbriggen• Extension of sensor coverage in
collaboration with authorities
Technology TransferPERMOS Continuous GPS Pilot
• Pilot program to make L1‐DGPS sensors available on PERMOS partner field sites
• First sensor installation in summer 2013, extensions in 2014, 2015(Valais: Herbriggen Bielzug, Breithorn + Längschnee, Grächen Distelhorn + Ritigraben, Saas‐Balen Gruben + Jäggihorn, Wysse Schije, Randa Grossgufer)
Hanging glacier break-off, Weissmies, Sept. 2014
PERMOS site Largario rock glacier, Sept. 2014 Avalanche protection, Randa, Nov. 2014
L1‐GPS Data Inventory
Monitoring of Weissmies Hanging Glacier
• Multi‐modal Monitoring of Hanging Glaciers – Ground‐based radar (Geopraevent)– High‐resolution imaging– In‐situ wireless GPS
installed from long‐line
‐10
‐5
0
5
10
15
20
25
30
35
40
26.05.2015 15.07.2015 03.09.2015 23.10.2015 12.12.2015 31.01.2016 21.03.2016
Triftgletscher 3D Velocity [cm/d]
Position 2 v_3d
Position 3 v_3d
10 per. Mov. Avg. (Position 2 v_3d)
10 per. Mov. Avg. (Position 3 v_3d)
• ETH Zurich– Computer Engineering and Networks Lab– Geodesy and Geodynamics Lab– Micro and Nanosystems
• University of Zurich– Department of Geography
• EPFL– Distributed Information Systems Laboratory
• University of Basel– Department Computer Science
Interested in more?
http://www.permasense.ch
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