Assessment of ground-based monitoring techniques applied to
landslide investigations
S. Uhlemann a,b,
⁎, A. Smith c
, J. Chambers a
, N. Dixon c
, T. Dijkstra a
, E. Haslam a
, P. Meldrum a
, A. Merritt d
,
D. Gunn a
, J. Mackay a
a
British Geological Survey, Natural Environment Research Council, Kingsley Dunham Centre, Keyworth, Nottingham NG12 5GG, United Kingdom
b
ETH Zurich, Institute of Geophysics, Sonneggstrasse 5, CH-8092, Zurich, Switzerland
c
Loughborough University, School of Civil and Building Engineering, Loughborough LE11 3TU, United Kingdom
d
Plymouth University, School of Geography, Earth & Environmental Sciences, Drake Circus, Plymouth PL4 8AA, United Kingdom
a b s t r a c ta r t i c l e i n f o
Article history:
Received 7 May 2015
Received in revised form 27 October 2015
Accepted 28 October 2015
Available online 31 October 2015
A landslide complex in the Whitby Mudstone Formation at Hollin Hill, North Yorkshire, UK is periodically reactivated
in response to rainfall-induced pore-water pressure fluctuations. This paper compares long-term measurements
(i.e., 2009–2014) obtained from a combination of monitoring techniques that have been employed together
for the first time on an active landslide. The results highlight the relative performance of the different
techniques, and can provide guidance for researchers and practitioners for selecting and installing appropriate
monitoring techniques to assess unstable slopes. Particular attention is given to the spatial and temporal resolutions
offered by the different approaches that include: Real Time Kinematic-GPS (RTK-GPS) monitoring of a
ground surface marker array, conventional inclinometers, Shape Acceleration Arrays (SAA), tilt meters, active
waveguides with Acoustic Emission (AE) monitoring, and piezometers. High spatial resolution information has
allowed locating areas of stability and instability across a large slope. This has enabled identification of areas
where further monitoring efforts should be focused. High temporal resolution information allowed the capture
of ‘S’-shaped slope displacement-time behaviour (i.e. phases of slope acceleration, deceleration and stability)
in response to elevations in pore-water pressures. This study shows that a well-balanced suite of monitoring
techniques that provides high temporal and spatial resolutions on both measurement and slope scale is necessary
to fully understand failure and movement mechanisms of slopes. In the case of the Hollin Hill landslide it enabled
detailed interpretation of the geomorphological processes governing landslide activity. It highlights the benefit of
regularly surveying a network of GPS markers to determine areas for installation of movement monitoring techniques
that offer higher resolution both temporally and spatially. The small sensitivity of tilt meter measurements
to translational movements limited the ability to record characteristic ‘S’-shaped landslide movements
at Hollin Hill, which were identified using SAA and AE measurements. This high sensitivity to landslide movements
indicates the applicability of SAA and AE monitoring to be used in early warning systems, through detecting
and quantifying accelerations of slope movement.
© 2015 The British Geological Survey (NERC). Published by Elsevier B.V. This is an open access article under the
CC BY license (http://creativecommons.org/licenses/by/4.0/).
1. Introduction
Landslides form one of the major natural hazards causing loss of life
and damaging of infrastructure worldwide. In the seven year period between
2004 and 2010, 2620 fatal, non-seismically triggered landslides
were recorded worldwide, causing 32,322 fatalities (Petley, 2012). Although
the landslide frequency in the UK is comparably low (e.g.
some 754 reported events between 2006 and August 2015), the economic
impact is high. Failure of engineered earthworks (embankments
and cuttings) or adjacent natural slopes causes interruptions to transportation
and utilities networks — a process that is affected by ongoing
climate change and ageing of slope materials (Dijkstra and Dixon, 2010;
Foster et al., 2011; Dijkstra et al., 2014; Glendinning et al., 2015;
Pennington et al., 2015).
Since one of the primary triggering mechanism for landslides is intense
or prolonged precipitation (Highland and Bobrowsky, 2008), the
frequency and severity of landslides are expected to fluctuate with
changes in precipitation patterns (spatial and temporal variations of duration
and intensity). In a context of climate change, precipitation cannot
be regarded as a steady state input and it is essential to develop
robust models of adequate complexity that allow evaluation of possible
future changes in slope instability due to forecasted changes in
Geomorphology 253 (2016) 438–451
⁎ Corresponding author at: British Geological Survey, Natural Environment Research
Council, Kingsley Dunham Centre, Keyworth, Nottingham NG12 5GG, United Kingdom
E-mail address: suhl@bgs.ac.uk (S. Uhlemann).
http://dx.doi.org/10.1016/j.geomorph.2015.10.027
0169-555X/© 2015 The British Geological Survey (NERC). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Contents lists available at ScienceDirect
Geomorphology
journal homepage: www.elsevier.com/locate/geomorph
precipitation (Dijkstra and Dixon, 2010). Mid- to high-latitude regions
are likely to face an increase in precipitation of up to 20%, including increased
flash floods due to more frequently appearing high-intensity
rainfall events (Defra, 2012; Füssel et al., 2012). This increase in precipitation
is likely to occur during the winter season, while summers will
become drier (Defra, 2012). Wetter winters and drier summers will
lead to an increased and deeper weathering of the topsoil, due to larger
amplitudes in the wetting and drying cycles. This is likely to reduce the
strength of the material and cause more frequent shallow slope instabilities.
Understanding triggering mechanisms and failure potentials, to
improve landslide forecasting, is therefore a major focus of research
internationally.
Monitoring of kinematic, hydrological, and climatic parameters
plays a significant role in supporting the development of slope stability
models (e.g. Buchli et al., 2013; Springman et al., 2013), since without
understanding movement patterns and responses to climate events,
forecasting is not possible (Angeli et al., 2000). This requires not just
monitoring of actual movements, but also environmental factors including
rainfall, temperature, soil moisture content and relative (air) humidity,
as well as geotechnical parameters, such as, pore water pressure.
This enables the correlation of movement events with their triggering
mechanisms and helps to inform the underlying causalities in the process–response
models.
Previous studies have related deformation measurements by GPS/
GNSS, inclinometer, extensometer or tilt meter readings to rainfall
events (e.g. Malet et al., 2002; Corsini et al., 2005; García et al., 2010;
Brückl et al., 2013) to study the deformation behaviour of rainfall triggered
landslides. Additionally, Malet et al. (2002), Corsini et al. (2005),
and Brückl et al. (2013) compare measurements of two or three of the
mentioned conventional deformation monitoring techniques, showing
good correlation between surface (e.g. GPS) and subsurface (e.g. inclinometer)
deformations in terms of movement occurrences.
In this paper we introduce and compare conventional techniques,
such as GPS, inclinometer and tilt meter, and recently emerging deformation
monitoring techniques, such as acoustic emission (AE) monitoring
using active waveguides (AEWG), and Shape Acceleration Array
(SAA). To our knowledge, this is the first time that these monitoring
techniques have been combined on an active landslide, providing
long-term (2009–2014) measurements. This paper highlights the relative
performance of these techniques focusing on different movement
periods, and it provides detailed, integrated interpretations of movement,
environmental, and geotechnical data of the Hollin Hill landslide.
The paper reports how these long-term monitoring results have enabled
a step-change in the understanding of slope dynamics, building
upon previously published work.
The study site, where a Lias mudstone formation is failing, is typical
for many inland landslides in lowland settings. Thus, the conclusions
drawn from this study can provide guidance for researchers and practitioners
for selecting and installing appropriate monitoring techniques
to assess unstable slopes.
1.1. Slope monitoring instruments and techniques
There is a clear need to monitor landslides and marginally stable
slopes to provide early warning of instability. This will allow for timely
evacuation of vulnerable people, as well as timely repair and maintenance
of critical infrastructure. The cost of remediation subsequent to
landslide failure is several times higher than the cost of corrective measures
and repairs if conducted prior to collapse (Glendinning et al.,
2009); this highlights the importance of early warning through monitoring.
Monitoring also provides: (1) the information necessary for
slope stability analysis and remediation design, (2) knowledge of stability
to and through construction, and subsequent to remediation, as well
as (3) understanding of the condition (both serviceability and ultimate
limit states) of adjacent infrastructure that has the potential to be
impacted upon by slope instability (Dunnicliff, 1988; Machan and
Beckstrand, 2012).
There are many different techniques and types of instrumentation
typically used in slope monitoring, and numerous emerging technologies.
No single technique or instrument can provide complete information
about a landslide and therefore various combinations are usually
employed. The primary parameters of interest are deformation and
pore-water pressure. Information on these is necessary to assess the
rate and magnitude of movement, as well as changes to effective stress
and hence stability. Performance of monitoring techniques and instruments
is usually assessed in terms of accuracy and precision, spatial
and temporal resolutions, sensitivity, and reliability (Dixon et al.,
2015). However, on most projects the predominant factor driving the
choice of instrumentation and techniques is their cost. For this reason
the majority of slope monitoring programmes comprise installation of
inclinometer casings and standpipes, which are usually read at discrete
and infrequent intervals of the order of months. Inclinometers allow the
depth to any shear surface(s) to be identified and standpipes provide information
on the ground water conditions; information that is necessary
for stability assessment and remediation design. However, this
mode of monitoring provides relatively low spatial and temporal resolutions,
which is usually insufficient to provide early warning of
instability.
Detailed in Table 1 are the monitoring instruments and techniques
employed in this study, together with an indication of their spatial
and temporal resolutions. The resolution of the methods is a function
of the nature of the installation and the extent of the sensor network.
Note that the classification shown in Table 1 specifically refers to the installation
at the Hollin Hill study site. This combination of monitoring
approaches was selected in order to: (1) provide relatively high spatial
resolution of ground surface movements, (2) determine the depth to
shear surfaces, (3) monitor subsurface deformation at localised areas
with high temporal resolution, and (4) to monitor pore-water pressures
at shear surface depths with high temporal resolution. This significant
level of information provides the basis for a thorough assessment of
each of the approaches in order to make recommendations for other
landslide investigations.
2. Study site
The landslide observatory is set on a south-facing hillslope, Hollin
Hill, with a mean slope angle of 12°, located south of the village of
Terrington, North Yorkshire, UK (54°06′38″ N, 0°57′30″W; Fig. 1). It is
set in the Howardian Hills, an undulating landscape running approximately
NW–SE shaped in four bedrock formations of Lower to Middle
Jurassic age and covered by superficial deposits of variable thickness
(Fig. 1b). Hollin Hill is a flat-topped hill capped by calcareous sandstone
and ferruginous limestone belonging to the Dogger Formation (DF).
There is a sharp boundary to the underlying Whitby Mudstone Formation
(WMF), the failing formation at this site (Gunn et al., 2013). The
WMF, showing a thickness of about 25 m (Chambers et al., 2011), is
composed of grey to dark grey mudstone and siltstone with scattered
bands of calcareous and sideritic concretions (Chambers et al., 2011).
It overlies the Staithes Sandstone Formation (SSF). The boundary between
these two formations is represented by an upward transition
from sandstone or siltstone to shaley mudstone. This change in depositional
facies is marginally episodic and, although a fining upward trend
persists, the boundary between the SSF and WMF is manifested by sequences
of ferruginous, micaceous siltstone, with fine-grained sandstone
and thin mudstone partings. The SSF is heavily bioturbated and
shows local occurrences of siderite and pyrite (Gaunt et al., 1980). The
formation underlying the SSF is the Redcar Mudstone Formation
(RMF) that comprises grey, silty, calcareous, and sideritic mudstone
with thin shelly limestones (Powell, 1984, 2010). The DF represents a
potential aquifer above the WMF. Hydrogeological characterisation of
the WMF and SSF is very complex as a result of variations in particle
439S. Uhlemann et al. / Geomorphology 253 (2016) 438–451
size in sedimentary sequences that, in turn, may be disturbed by bioturbation
and inter-connected joint systems.
On top of much of the lower slopes in the SSF, a thin (up to 2 m thick)
fine sand deposit is found, preserving the old slope and head deposits. It
is likely that this sequence represents a periglacial slope with associated
coversand (e.g. Catt, 1977; Ballantyne and Harris, 1994; Bateman,
1995). The persistence of a thin head deposit on top of the SSF suggests
that the old (periglacial) slope profile has been largely preserved by the
subsequent cover of the aeolian sands.
The Hollin Hill landslide is in many ways representative of inland
landslides in stiff clays and is acting as a field laboratory to provide,
amongst others, a test site for a range of monitoring techniques, including
the ALARMS (e.g., Dixon et al., 2010, 2014; Smith et al., 2014) and
ALERT systems (e.g. Kuras et al., 2009). So far, the geological and geomorphological
characterisation was mainly informed by geophysical
data, borehole logs and inclinometer readings during periods of veryslow
movement (~0.5 m year−1
; Chambers et al., 2011; Merritt et al.,
2013). This paper utilises previously unavailable data to focus on periods
of landslide reactivation with movements of up to 3.5 m year−1
,
leading to a better informed interpretation of landslide processes and
characterisation of the site.
Merritt et al. (2013) provide a preliminary geomorphological characterisation
of the slope together with an initial assessment of a ground
model. An updated and more detailed ground model is presented
here based on the interpretation of borehole and geotechnical data.
Characterisation of the morphogenesis of this slope is supported by a
section constructed on the basis of a series of shallow (up to 4 m
depth), hand-augered boreholes (Fig. 2).
In summary, Hollin Hill comprises a largely linear slope that is affected
by different types of slope instability that can be sub-divided into
three domains (with fuzzy boundaries; Fig. 2).
• In the central section translational landsliding in the WMF dominates.
Multiple translational components can be distinguished and discrete
Table 1
Monitoring devices installed at the Hollin Hill landslide field laboratory. For each system a brief description as well as an indication of its spatial and temporal resolutions is given. Spatial
resolution is given on a local, i.e. measurement, and global, i.e. slope, scale.
Instrument/technique Description Spatial resolution Temporal
resolution
Local Global
Surface deformation monitoring
Global positioning system (GPS) • Repeated survey of permanently installed markers using RTK/GNSS GPS with
centimetric accuracy providing time-series of 3D topographical data. Allows for
measurement of surface movements and deformations
• Permanent GNSS stations allow for high temporal resolution
Moderate Moderate Low
Tilt meter • Installed near the ground surface providing an indication of landslide
activity and an indirect measurement of deformation
High Low High
• Most suitable for monitoring of landslides with a large rotational
component of movement; translational movements are unlikely to be detected
Subsurface deformation monitoring
Conventional inclinometer • Installed in a borehole penetrating stable stratum below any shear surface
(or potential shear surface). The annulus around the casing is backfilled with
material having similar properties as the surrounding soil (e.g. bentonite-grout)
High Low Low
• A torpedo probe measures the inclination of the casing with depth, providing a
horizontal deformation vs. depth profile
• Time-series data can be used to determine magnitude and rate of displacements,
and depth to shear surfaces (Mikkelsen, 2003; Simeoni and Mongiovì, 2007;
Wan and Standing, 2014)
• If an in-place probe or probe-string is installed and deformation is logged
continuously then high temporal resolution can be acquired
Shape Acceleration Array (SAA) • Comprises a string of MEMS (micro-electrical–mechanical systems) sensors
installed at regular intervals along the depth of a borehole, which penetrates any
shear surface or potential shear surface
High Low High
• Each sensor monitors displacement in x-, y- and z-directions with high accuracy and
temporal resolution (Abdoun et al., 2012)
Active waveguide and Slope
ALARMS sensor
(i.e. AE monitoring)
• Installed in a borehole penetrating any shear surface or potential shear surface.
Comprises a steel waveguide (i.e. to transport AE signals generated at the shear surface to
the ground surface with low attenuation) and granular backfill (i.e. to generate
high energy AE as the slope deforms)
High Low High
• AE is generated when the granular backfill is deformed by deformation of the host slope
• AE is measured at the ground surface with a Slope ALARMS system (Dixon and Spriggs, 2011)
• Recorded are AE rates or ring-down counts (RDC) per unit time, which are the number of
times the signal amplitude crosses a pre-defined voltage threshold per pre-defined time period
• AE rates (e.g. RDC/h) are proportional to slope displacement rates, enabling detection of
accelerations and decelerations of slope movement (Dixon et al., 2003, 2014, 2015;
Smith et al., 2014; Smith and Dixon, 2015)
Ground water monitoring
Piezometer • Piezometer tip is installed to depth(s) of interest (e.g. a shear surface) inside a borehole to
monitor pore-water pressures of a certain depth range
Moderate Low Low to High
• The annulus around the tip is backfilled with either sand or grout (dependent on the
permeability characteristics of the host slope material)
• The remainder of the hole is backfilled with low permeability grout to form a closed/sealed
system (Wan and Standing, 2014)
• Water levels in the piezometer can either be logged manually (low temporal resolution) or
automatically (high temporal resolution) and can be used to calculate pore-water pressures
within the screened interval of the piezometer tip
440 S. Uhlemann et al. / Geomorphology 253 (2016) 438–451
shear zones have been observed in boreholes in this central part of the
slope complex.
• With progressive displacement of the translational slides, disintegration
of the slide mass occurs, leading to slope deformation that is increasingly
characteristic of flow-like behaviour further down the
slope.
• The slopes above the central section display recent, rotational deformation.
Progressive translational deformation in the central domain
leads to unloading and oversteepening of the toe of the upper slopes,
resulting in landsliding that is dominated by sliding along curved slip
surfaces.
Note that the instrumentation clusters described in this study are
installed in the translation/flow-dominant zone. The translation/flowdominant
lobes located in this zone are simply referred to as lobes
hereafter.
Instability in the WMF involved sequences of thin translational slide
or flow events. Multiple slip surfaces and stretched out, thin bands of aeolian
sands provide some evidence that phases of deformation have occurred
subsequent to the aeolian deposition.
The steepest slope angles are found where the slope is developed in
the SSF. As the translational-flow slide deformation in the WMF reaches
this steeper section, it would be logical to expect the development of
further runout, but instead a series of ridges are observed. Progressive
deformation of the translational-flow slides appears to be impeded by
base draining as the landslide moves over the fine sands further down
the slope.
A substantial thickness of fine sand is found between boreholes El04
and El08 (hand-augered boreholes, Fig. 2). This local accumulation may
reflect uneven aeolian deposition, but it is also plausible that landslide
activity in the WMF incorporated some sand in the slope deformation
process, driving this surface veneer onto the sand further down the
slope and thus creating a local accumulation. This latter scenario is supported
by the inclinometer data of Fig. 3. It shows borehole logs and the
results of cumulative inclinometer measurements conducted over a period
of 2.5 to 3 years. It is evident that the lowest active shear surfaces
occur in the fine sandy deposits at a depth of approximately 1.5 m at
the western lobe (BH 1 and 7). The profiles also suggest the existence
of further slip surfaces or flow-like deformation in more shallow
deposits.
The profile representing the eastern lobe (BH 5) is more complex.
This borehole is set in an accumulation ridge where ongoing deformation
in the upper WMF is inhibited by toe draining through the underlying
fine sands. This is clearly illustrated by the relatively thick silty clays
overlying the fine sands. In these silty clay landside deposits shear surfaces
are observed at about 2.0 m depth, i.e. about 0.5 m above the
boundary with the fine sands, and these observations are supported
by the inclinometer data. At approximately 4 m depth there appears
to be a second shear surface resulting in very slight deformation of up
to 10 mm over a period of 3 years.
The aeolian sands within and below the landslide deposits have a
complex relationship with the deformation behaviour of this slope.
When incorporated in the slide body, it is possible that these sand lenses
act as interceptors for diffuse inflow of water, and are potentially capable
of generating artesian pore pressures at critical depths.
3. Instrumentation installation
As already mentioned and shown, this landslide is equipped with a
range of monitoring systems to serve as a research landslide observatory
to improve our understanding of triggering mechanisms for first time
failure and landslide reactivation. The following monitoring systems are
deployed on the slope and were actively monitoring as indicated:
Fig. 1. Overview maps of the study site. a) Geomorphological map of the landslide indicating different landslide bodies and features (after Merritt et al., 2013). Also shown are the locations
of the monitoring equipment that are deployed at the site and discussed in this paper. b) Geological setting of the study site; inlet shows location within the UK. c) A section of Fig. 1a at a
larger scale showing the locations of sensor clusters comprising inclinometer, AEWG, SAA, piezometer, and tiltmeter deployed on the two lobes, as well as the location of the weather
station. Note that cluster 1 comprised AEWG logging during February 2010 to December 2010; the locations of the SAAs at clusters 2 and 3 are adjacent to the locations of inclinometers
2 and 3.
441S. Uhlemann et al. / Geomorphology 253 (2016) 438–451
• Three clusters of active waveguides monitoring acoustic emission
(2009–ongoing)
• Three inclinometers (2008–2012)
• Two shape acceleration arrays (2013–ongoing)
• Two tilt meters (2008–ongoing)
• GPS tracking of 45 marker points (2008–ongoing)
Fig. 2. Representative section of the stratigraphy and slope instability domains for Hollin Hill. a) Diagram modified after Gunn et al. (2013). b) Profile A–A* through the eastern lobe informed
by hand augered holes down to depth of 4 m (profile location indicated in Fig. 1).
Fig. 3. Borehole logs and corresponding inclinometer data highlighting slip surfaces. Boreholes 1 and 7 (BH1 and BH7) are located on the western lobe (Inclinometer 1 and adjacent to SAA2
in Fig. 1c), Borehole 5 (BH5) on the eastern lobe (adjacent to AEWG 3 in Fig. 1c).
442 S. Uhlemann et al. / Geomorphology 253 (2016) 438–451
• Weather station (2008–ongoing)
• Two piezometers (2009–ongoing)
Additionally, soil moisture content, bulk conductivity and temperature
are monitored at three different locations, covering the backscarp,
active lobes, and an area outside of the landslide, with sensors deployed
at different depths below ground level (bgl) ranging from 0.1 to 6.5 m.
The location of the different monitoring systems can be found in
Fig. 1a, c. This range of different monitoring systems, each characterized
by different accuracy, sensitivity, and spatial and temporal resolutions
provides the basis for a thorough assessment of techniques used for
slope monitoring.
In the following a brief description is provided for each monitoring
system.
3.1. Active waveguides (AEWG)
The active waveguides were installed in 130 mm diameter boreholes
to depths of 5.7 m bgl; each comprises 6 m long, hollow steel tubing of
50 mm diameter and 3 mm thickness. The annulus around the steel tubing
was backfilled with angular 5 to 10 mm gravel compacted in nominally
0.25 m high lifts. The top 0.3 m of the boreholes were backfilled
with a bentonite grout plug to seal against the ingress of surface water
(Fig. 4). The gravel backfill, which is acoustically noisy, generates
high-amplitude AE signals. This overcomes the limitation of detecting
low-amplitude AE signals caused by slope movement of the finegrained,
acoustically quiet, host material (Dixon et al., 2003). Transducers
were coupled to each of the waveguides at the ground surface and
were connected to Slope ALARMS (Dixon and Spriggs, 2011) sensors
which were powered by batteries and recharged by solar panels; logging
was at 30-min intervals. These AE monitoring systems, which inform
only about the behaviour of the installation borehole, provide
globally a low spatial resolution, but deliver information on rates of subsurface
deformation (i.e. accelerations and decelerations) with high
temporal resolution.
3.2. Inclinometers
Inclinometer casings were installed at the three cluster locations and
approximately 1 m east from the active waveguides with keyways orientated
along the slope dip- and strike-directions. The inclinometers
penetrated to depths of 6 to 7 m bgl. They ceased to be usable after
3 years of monitoring in November 2012 due to significant shear surface
displacement inducing localised bends within the casing sufficient to no
longer allow the torpedo probe to pass.
Inclinometers provide relatively low global spatial resolution as a
survey of the casing only informs of deformation in the soil surrounding
the borehole. If casings are surveyed manually using a torpedo probe,
relatively low temporal resolution with intervals of the order of months
can be obtained (NB — higher temporal resolutions can be achieved by
using in-place probes).
3.3. Shape Acceleration Array (SAA)
SAAs were installed approximately 1 m west of AEWG2 in May 2013
and AEWG3 in December 2013 to provide continuous subsurface deformation
measurements; their installation was instigated subsequent to
the inclinometer casings no longer being usable. They were installed
to depths of 2.5 m bgl. Each of the MEMS sensors that comprise the
SAA log deformation at 1-hour intervals. The SAA operates in a similar
manner to an in-place inclinometer in that it provides deformation vs.
depth measurements with high temporal resolution (Fig. 4).
3.4. Tilt meter
Tilt meters were installed to monitor small changes in surface inclination,
related to rotational downslope movement of mass that is evident
at several trees on site. Each tilt meter consists of a dual axis
inclinometer sensor with an accuracy of 0.1° mounted on a 0.5 m long
coated iron stake (Fig. 4). The two tilt meters were connected to a
data logger recording tilt angles hourly.
Tilt meters provide point measurements only that are representative
for a small area within the landslide (and thus low global spatial resolution)
and monitor tilt as opposed to actual deformation; however, they
log data with high temporal resolution enabling correlation of movement
with rainfall-induced instability.
3.5. Tracking of GPS markers
GPS markers were distributed regularly as five parallel lines of nine
markers each, and made of wooden pegs. Inline marker separation
was about 20 m, while line spacing was about 10 m. Their initial positions
were surveyed using a real-time kinematic GPS equipment, providing
centimetric accuracy. Every 1–2 months these markers were
re-surveyed using the same equipment, building a time-series of landslide
movements at those locations.
This approach provides a moderate spatial resolution, both, on local
(i.e. marker) and global (i.e. slope) scales. It allows for identification and
mapping of areas of activity across the slope, forming the basis for deciding
where more sensitive instrumentation is to be installed (NB — depending
on the available resources fine grids and permanent GNSS
logging stations can be employed, delivering high spatial and temporal
resolutions).
3.6. Weather station
The weather station was an all-in-one system measuring barometric
pressure, humidity, precipitation, temperature, and wind speed and direction,
with an hourly frequency. To minimize the effects upon the system
from vegetation and other installations at the site, especially on the
measurement of wind speed and direction, the weather station was
placed on top of a pole at a height of 3 m. The data were recorded and
Fig. 4. Schematic illustration of permanently installed subsurface movement monitoring techniques; a) AEWG monitoring, b) SAA, and c) tilt meter. Note, employing a longer stake for the
tilt meter and fixing it below the shear surface (dashed installation) will induce a larger proportion of rotational movement..
443S. Uhlemann et al. / Geomorphology 253 (2016) 438–451
stored using the same data logger as for recording the tilt meter
readings.
3.7. Piezometers
Piezometers were installed in boreholes hand augered to 2.85 and
2.8 m on the western and eastern lobes, respectively. These depths
were chosen in order to place the active zone of the piezometers in
the vicinity of the depth to predicted shear surfaces, which were determined
using CPT measurements (Gunn et al., 2013). We installed a
19 mm uPVC pipe, fitted with a 0.9 m slotted, porous piezometer tip
in the borehole. The hole was backfilled with clean sand to 1.95 and
1.75 m below ground for the western and eastern piezometers, respectively,
forming an active zone that allows for monitoring of the pore
water pressure in the region of the slip surface located at about 1.6
and 1.9 m depth, respectively. The remainder was backfilled using
bentonite granules to ensure sealing. The piezometric head measured
in these standpipes is referred to the top level of the sand
pocket forming the active zone, thus positive heads present conditions
of positive pore water pressure. Since the active zones of the piezometers
are in close proximity to the shear surface (b 0.35 m), the
measured pore water pressures are indicative for the conditions at
the shear surface. The water levels in these piezometers were logged
with a 30 min interval. Note that the eastern piezometer experienced
severe bending and became unusable in January 2013. It was
reinstalled in December 2013, although slightly deeper (now 0.5 m
below the shear surface).
It is important to highlight that the monitoring clusters are distributed
over the two lobes, rather than installed adjacent to each other. Thus,
times of activation may vary depending on their location on the lobe.
4. Interpretation of slope deformation
4.1. Delineation of regions of slope instability
Table 1 shows that the different monitoring techniques deployed
have different spatial and temporal resolutions. To indicate their ability
to differentiate movements at the system and over a typical slope scale,
their spatial resolution has to be divided into two scales, local and global.
While the tilt meter, AEWG, and SAA are sensitive to very small
movements and thus have high local spatial resolution, their global spatial
resolution is rather poor, since their recordings are determined by
movements in their vicinity only. However, they can record movements
with a high temporal resolution, allowing for a correlation of movement
events with climatic circumstances, such as specific rainfall events. GPS
marker and inclinometer measurements on the other hand have low
temporal resolution, but can easily be used to determine areas of instability
(GPS markers) and shear surfaces (inclinometer) on a slope scale.
Fig. 5 highlights this ability of GPS marker measurements to determine
regions of slope instability and active movements. These measurements
can be used to (1) show the direction and amplitude of surface deformations
at monitoring points (Fig. 5a) and (2) to provide a map of the 5year
average landslide movement rates covering the entire slope
(Fig. 5b) by interpolation of the monitoring points (Uhlemann et al.,
2015). Between 2009 and 2014 the lobes experience significant surface
deformations, with the eastern lobe showing significantly higher activity
than the western, while the remaining areas show little or no
deformation.
Fig. 5 shows that the rotational movements in the backscarp are directly
connected with translational movements of the lobes. Such investigation
is only possible with a distributed network of deformation
measurements offering reasonable spatial resolution on both scales.
Fig. 5. Displacements determined from GPS marker surveys between 2009 and 2014 superimposed on the geomorphological map after Merritt et al. (2013). a) Displacement vectors (i.e.
direction and amplitude); arrows show absolute surface deformation over the 5-year monitoring period. The colour of the arrows corresponds to the standard classification for landslide
movement rates after Cruden and Varnes (1996). b) Map of average landslide movement rate (after Uhlemann et al., 2015) highlighting the activity of the eastern lobe and the connection
between rotational failure of the backscarp and translational movements of the lobe.
444 S. Uhlemann et al. / Geomorphology 253 (2016) 438–451
Fig. 6. Data overview showing rainfall, water level, cumulative tilt movements (i.e. absolute change in tilt meter reading), and cumulative GPS marker movements. Note the interruption in
seasonality in rainfall pattern and the correlation between peaks in piezometric heads and reactivation of the landslide movements. Note that the reason for the drop of the head of the
eastern piezometer below the active zone is its reinstallation to a slightly deeper level.
445S. Uhlemann et al. / Geomorphology 253 (2016) 438–451
Hence, studies of movement patterns are only possible either with distributed
subsurface monitoring devices or limited to surface deformation
monitoring. In its current application the data suffer from low
temporal resolution due to the need to survey positions manually.
Therefore, the timings of periods of activity can only be approximately
determined. The approach introduced by Buchli et al. (2012) would
overcome this limitation by employing wireless GPS sensor networks
that could log deformations nearly continuously. Recent studies on
tracking electrode movements by employing electrical resistivity monitoring
data (Wilkinson et al., 2010, 2015) introduce another technique
to obtain surface movement information on a global scale with high
temporal and spatial resolutions.
4.2. Characteristics of the 5-year monitoring period
Fig. 6 shows rainfall, water level, cumulative tilt, and GPS marker
movements for the monitoring period from the beginning of 2009 to
2014 (five years). Note that the GPS movement data shown in Fig. 6 correspond
to markers adjacent to Cluster 2 on the western lobe and close
to the southernmost boundary of the eastern lobe, respectively. Rainfall
data are shown in terms of absolute rainfall (black line) and effective
rainfall (green bars, potential evotranspiration calculated using
Hydrus1D; Šimůnek et al., 2008). Cumulating the effective rainfall
over the summer (red bars) and the winter (blue bars) shows a clear
seasonality in the first two years, with dry summers and wet winters.
It also indicates a negative water balance (i.e. potential evotranspiration
larger than the amount of rainfall), which got expressed as an 18months
drought between 2010 and 2012. This seasonality is interrupted
in the years 2011 and 2012 (Fig. 6). This can be attributed to a cooler and
wetter than average summer in 2011 resulting in enhanced effective
rainfall (absolute rainfall 10–20% higher than 30 year average; Belcher
et al., 2014) followed by a drier than average winter. The following summer
of 2012 was characterised by prolonged and intense rainfall of up to
65 mm day−1
. It has been recorded as the wettest summer since 1912
(Belcher et al., 2014).
The seasonality of the years 2009 to 2011 can also be seen in the piezometric
heads. During the winters of 2009–10 and 2010–11 the effective
rainfall percolates downwards to recharge the water table resulting
in elevation of piezometric heads. Conversely, in the summer, recharge
diminishes and groundwater flow and discharge causes the piezometric
heads to fall. The difference between summer and winter piezometric
heads is about 1.8 and 1.0 m for the western and eastern lobes, respectively.
Not only is the difference between summer and winter heads
larger on the western lobe, it also shows more fluctuation and faster response
times to rainfall events in comparison to the eastern lobe, which
shows a much smoother response. This indicates that the two lobes are
set within different hydrological environments. These can be
characterised by (1) stronger bypass flow on the western lobe due to
a higher degree of fissuring as indicated by recent infiltration experiments,
and (2) the existence of sand lenses within the WMF of the western
lobe providing preferential pathways for moisture drainage due to
the higher permeability of those sand lenses. These two effects are less
pronounced on the eastern lobe.
The surface movement indicators shown in Fig. 6 (i.e. cumulative
GPS marker and tilt movement) indicate three periods of significant
movement within the five year monitoring period. The first movements
were recorded in October 2009, with a total of approximately 0.25 m.
This movement period was brief, lasting for no longer than 2 months.
After this, an 18-month period of persistent drier than average conditions
caused the slope to remain in a stable condition with no movements
until July 2012 when movement commenced due to the wet
summer. First indication of movement during this period (Fig. 6) is
given by the GPS measurements located at the front of the eastern
lobe. The tilt meter of the eastern lobe shows the movements commencing
in November 2012, during a period when significant movements
were also recorded on the GPS markers of the eastern lobe
(1.4 m between November 2012 and January 2013). This offset in the
start of movement recordings may be caused by the different sensor locations
(the tilt meter is located about 20 m upslope from the marker)
or by the insensitivity of the tilt meter to record pure translational
movements. Movements on the western lobe commenced about 2
months after the eastern lobe, in January 2013, and lasted until April
2013. Although the tilt meter of the western lobe shows a response
comparable to that on the eastern lobe, the GPS marker measurements
reveal a smaller degree of movement of only about 0.25 m between November
2012 and January 2013. This period of landslide reactivation
and acceleration lasted until February 2013, after which the landslide
entered a period of deceleration due to a reduction of rainfall, which
allowed dissipation of pore-water pressures in the slope. GPS marker
measurements show that between February and October 2013 the eastern
lobe moved about 0.3 m, while the western lobe reached a stable
state. In the same period, the tilt meter recorded movements on both
lobes. This may be explained by (1) localised surface disaggregation at
or near the tilt meter, or (2) small magnitude movement that was not
captured using RTK-GPS measurements (i.e. sub-mm scale). Another
acceleration of movements occurred in the winter of 2013–2014,
where the eastern lobe moved another 0.3 m in just one month.
The dashed horizontal lines in the piezometric head section of Fig. 6
indicate the active zone of the piezometer; the upper dashed line shows
the location of the upper level of the sand pocket, which was used as reference
for the piezometric head. Thus, positive heads indicate positive
pore water pressure close to the slip surface. Extended periods of positive
pore water pressure correlate clearly with reactivation and acceleration
of the landslide on the western lobe (i.e., movement between
December 2009–March 2010, and November 2012–March 2013). The
piezometer on the eastern lobe shows positive pore water pressures
throughout the years 2011 and 2012, with an average piezometric
head of +0.6 m above the slip surface. A global peak showing a piezometric
head of +1.5 m was recorded in November 2012 when the
fastest movements commenced on this lobe. The positive piezometric
head level sufficient to induce instability and movement at this location
is therefore between 0.6 and 1.5 m. These movements led to a severe
bending of the piezometer pipe, causing the loss of the logger. Another
piezometer was installed in November 2013. This new piezometer
showed positive pore water pressures immediately after its installation,
correlating well with another acceleration of this lobe.
Two periods of winters 2012–13 and 2013–14 are considered in detail
below. These two periods represent times at which the landslide
reactivated or movement accelerated, respectively, as indicated by the
GPS marker measurements. To understand the actual kinematic behaviour
of the deformations, higher temporal resolution than available for
the GPS marker data is required. This is provided by the continuous or
near-continuous recordings of the AEWG, SAA, and tilt meter.
4.3. Period 1 — winter 2012/2013
Fig. 7 shows period 1, which presents a time at which the landslide
reactivated subsequent to more than 2 years of stability. This period,
set between November 2012 and April 2013, follows a very wet summer,
with rainfall exceeding 50% more than the 30-year average
(Belcher et al., 2014). This intense rainfall caused the highest piezometric
heads measured at the site during the 5-year monitoring period
(Fig. 6). Although the high piezometric heads and thus positive pore
water pressures are likely to be one of the main reasons for the reactivation
and acceleration of the landslide, their highest peak has not been
the ultimate trigger for the reactivation of the lobe movements. For
this period the reasons for reactivation were: (1) intense rainfall leading
to increased total stress due to increased moisture content; (2) loading
from a rotational failure up-slope; and (3) reduction of material
strength caused by elevations in pore water pressure. Fig. 7 shows
that rainfall of up to 30 mm day−1
on 25th November 2012 caused
the stable slope to move. These movements have been recorded by
446 S. Uhlemann et al. / Geomorphology 253 (2016) 438–451
the AEWG on the western lobe and the tilt meter on the eastern lobe.
The two techniques recorded the onset of instabilities at the same
time, despite being located on different lobes. At this time, no AEWG
was operational on the eastern lobe. Inclinometer readings (Fig. 3)
show very slow subsurface deformation from the beginning of the monitoring
period in 2009 (b 50 mm year−1
) with a significant acceleration
between May and October 2012 (when they eventually ceased being
useable). The tilt meter and GPS markers are installed at different locations
to the AEWG and inclinometer. Hence, the difference between
their recordings may be an indication that the lobes move as separate
blocks. Tilt meter recordings from the western and eastern lobes (and
also GPS marker measurements, but with limited temporal resolution)
reveal that major movements on the western lobe commenced on
16th January 2013, 51 days after movement began on the eastern
lobe. At the time of slope movement initiation no intense rainfall has
been recorded. Snow build-up during the several days of low temperature
prior to this reactivation event resulted in 5 to 10 cm of snow cover.
This snow melted as temperatures increased on 16th January 2013,
which provided additional moisture to a nearly saturated subsurface
(Uhlemann et al., 2014) leading to elevated pore water pressures.
While smaller rainfall events (27th and 29th January with 4 and
9 mm day−1
, respectively) succeeding the snowmelt period caused further
movement acceleration, a heavy rainfall event on 5th February
2013 (39 mm day−1
) did not increase the rate of movement. This
could be due to already fully saturated conditions of the lobe and thus
surface runoff rather than infiltration of moisture. This heavy rainfall
event was followed by a dry period leading to drainage of moisture,
thus a reduction of pore water pressures, and movement decelerated.
All movement indicators exhibit characteristic ‘S’-shaped slope
displacement-time behaviour (e.g. Allison and Brunsden, 1990; Petley
et al., 2005; Smith et al., 2014); periods of acceleration followed by
deceleration and stability, due to oscillations in pore water pressures
in the vicinity of the shear surface. The GPS marker information did exhibit
this behaviour; however, it had low temporal resolution and numerous
‘S’-shaped events were not captured. The tilt meter and AEWG
both captured all of the phases of reactivated movement and with a sufficient
temporal resolution. This demonstrates the significance of temporal
resolution in capturing landslide deformation behaviour. The
time series measurements show that these periods of reactivated movement
were detected at different times on the different instruments; this
is because the instruments are installed at different locations on the
lobes. For this five-month period of winter 2012–2013 the GPS marker
measurements showed surface movements on the eastern lobe of up
to 1.7 m.
4.4. Period 2 — winter 2013/2014
The second period of landslide reactivation investigated in this paper
occurred between 9th January 2014 and 4th February 2014. Period 2 has
a different prehistory compared to Period 1. While Period 1 followed
one of the wettest summers of recent records, Period 2 follows an average
summer that led to drainage of the moisture accumulated in the
slope during the winter before. Note that the weeks prior to this period
were characterized by strong rainfall events, resulting in approximately
220 mm cumulative 90-day antecedent rainfall. For this period, also SAA
data for the two lobes is available.
Fig. 8 shows continuous cumulative RDC- and deformation-time series
measurements from active waveguides (AEWG2 and AEWG3),
SAAs (SAA2 and SAA3), GPS marker, and tilt meter measurements recorded
from the two lobes. The shape of the cumulative time series at
both lobes are characteristic of ‘S’-shaped slope movements (e.g.
Allison and Brunsden, 1990; Petley et al., 2005; Smith et al., 2014).
The series of slide movement events are preceded by periods of rainfall
that induced transient elevations in pore water pressures along the
shallow shear surface and induced movement. The slide mass accelerated
towards a peak velocity and subsequently decelerated as pore-water
pressures dissipated. Shear resistance was mobilised internally within
the slide mass and through remoulding of the landslide toe (Dixon
et al., 2014, Dixon et al., 2015). This process was repeated subsequent
to each rainfall trigger as shown in Fig. 9. Fig. 9 shows the AE rates,
which are the first derivative of cumulative AE and are proportional to
slope velocity (Smith et al., 2014; Smith and Dixon, 2015), and SAA
measured velocity at Clusters 2 and 3 for the same period of movements
as in Fig. 8. Although movement appears to trigger on both lobes simultaneously,
the eastern lobe clearly experienced greater magnitudes of
movement as shown by GPS measurements.
Monitoring GPS markers did not provide sufficient temporal
resolution to capture the ‘S‘-shaped phases of reactivated slope
movement. The tilt meter did not capture the reactivation phases because
the movements had a predominantly translational component.
It is only possible to capture this slope deformation behaviour using
deformation monitoring techniques that provide continuous information
with high temporal resolution (e.g. AEWG and SAA), and
can capture the appropriate behaviour (i.e. tilt meters are inappropriate
for measuring translational movements). For a system to be
capable of providing an early warning of slope instability, it must
provide this level of information, to detect accelerations of movement
as early as possible and communicate them in real-time using
appropriate communication systems.
The information gained from the evaluation of the movement monitoring
techniques in conjunction with the accompanying rainfall and
pore water pressure data led to an improved understanding of the
movement pattern forming the Hollin Hill landslide in recent years.
Fig. 10 shows a simplified representation of the geomorphological features
and example cyclic processes underpinning the movements. Rainfall
induced instabilities in the WMF of the back scarp and subsequent
downslope movement of material (1 in Fig. 10) lead to an accumulation
Fig. 7. Comparison of movement measurements for period 1. Shown are GPS marker, cumulative
AE (RDC), and tilt meter measurements. Also shown are effective rainfall and
temperature.
447S. Uhlemann et al. / Geomorphology 253 (2016) 438–451
of slipped material at the WMF–SSF boundary (2). These processes, as
they are rainfall dependent, show varying movement rates. Once a
threshold of accumulated material and pore water pressure has been
exceeded, a breakthrough occurs, transporting slipped WMF further
downslope with high movement rates (3), which decrease as pore
water pressures dissipate. Consequently, this material moves in a
flow-like behaviour on top of the aeolian sands and the SSF, where
changes in the pore water pressure levels determine the movement
rates. Pore water pressures are elevated by rainfall-induced moisture
input and reduced by toe-drainage through the aeolian sands and SSF.
To maintain this flow-dominated process that forms the lobes of slipped
WMF on top of the SSF material, input from upslope is required. The
flow material is supplied episodically, following a cyclic pattern of rainfall
induced deformation in the WMF, and accumulated at the WMF–SSF
boundary until a stress/pore water pressure threshold is exceeded that
triggers a breakthrough of a flow lobe. This cyclic behaviour is characteristic
of the slopes movement during winter months when it is at its
wettest and the pore water pressures in the slope are at their greatest
magnitude. The slope remains predominantly stable for the remainder
of the year, unless rainfall with high intensity and duration occurs.
5. Discussion of technique applicability and conclusions
This paper has detailed the application of various monitoring instruments
and techniques to a reactivated landslide that moves in response
to rainfall-induced pore water pressure elevations. The case study has
served as a comparison of the various monitoring approaches and particular
attention has been given to the spatial and temporal resolution
offered by the approaches.
Monitoring an array of markers installed across the slope using GPS
during site visits has allowed the quantification of surface movement
vectors at each marker location and therefore the identification of
areas of stability/instability. This high spatial resolution information is
particularly important where a large slope area is of suspected instability.
The information obtained from monitoring the GPS markers can be
utilised in identifying areas across the slope where further monitoring
effort should be focused.
The centimetric accuracy offered by the GPS surveys is sufficient in
identifying areas of relative stability across the slope and periods of
movement; however, for most monitoring applications, but especially
when a slope threatens infrastructure, greater accuracy in time and
space is necessary. While GPS measurements are sensitive to surface deformation,
acquisition of subsurface deformation information is often
critical. The conventional inclinometer allows the depth to shear
surface(s) to be identified. Movements over a localised depth, such as
the shear surface, can be determined with an accuracy of the order of
±0.2 mm (Mikkelsen, 2003). The inclinometer casings at Hollin Hill became
unusable (i.e. would no longer allow the torpedo probe to pass the
shear surface) after localised shear surface deformations of approximately
60 mm, as evidenced by the incremental readings (note Fig. 3
shows cumulative readings). Consideration should therefore be given
to the life-span of such instrumentation, keeping in mind the anticipated
magnitudes of movement.
Monitoring markers using GPS and inclinometer casings using torpedo
probes during site visits offer low temporal resolution. This
mode of monitoring informs the user whether movement occurred
since the last reading but does not provide information on how and
when the slope moved during this interval. It cannot provide realFig.
8. Comparison of movement measurements for period 2. Shown are GPS marker, cumulative AE (RDC), SAA horizontal displacement measurements, and tilt meter measurements,
together with effective rainfall and temperature. Note that axis for the movement measurements differ for the western and eastern lobes.
448 S. Uhlemann et al. / Geomorphology 253 (2016) 438–451
time information for use in early warning. This can be overcome by
using in-place probes and probe-strings installed within boreholes, providing
high temporal resolution information as deformation is logged
near-continuously at user-defined intervals. This study at Hollin Hill
utilised SAA and AEWG to perform this function. The SAA logged deformation
at 1-hour intervals using a series of MEMS installed along the
depth of the borehole with accuracy of the order of ±1.5 mm per
30 m (Abdoun et al., 2012). Additionally, AEWG monitoring provided
continuous information on rates of subsurface movement, accelerations
and decelerations in particular, sampled with a high temporal resolution
of 30 min intervals. This high temporal resolution information provided
by SAA and AEWG monitoring, was paramount in understanding
the deformation behaviour of the slope in response to rainfall-induced
instability. It allowed the identification of the ‘S’-shaped deformation
time cycles. This was not captured using the other deformation
monitoring approaches. SAA and AEWG have therefore demonstrated
the potential to provide early warning of movement by detecting accelerations
of movement in real-time if connected to an appropriate communication
system. Note that the selection of appropriate measurement
intervals for these approaches is very important. An understanding of
the way in which the slope will behave should inform this decision.
For example, the slope at Hollin Hill is reactivated and moves in
response to rainfall-induced pore water pressure elevations; these
episodes of movement occur over a period of 2–3 days (Fig. 8). A monitoring
frequency of the order of hours is therefore sufficient to capture
this behaviour. However, when monitoring a slope that has the potential
to undergo progressive first-time failure, i.e., collapse as a result of
brittle strength loss (Chandler, 1984), which may experience rapid accelerations
of movement over minutes or hours, a monitoring frequency
of the order of minutes would be necessary to capture this behaviour
and provide early warning.
Tilt meters also provide continuous information with high temporal
resolution. However, as evidenced by the study at Hollin Hill, they do
not successfully detect movements with predominantly translational
components. This is because the instrument monitors rotation at the
near-surface. Anchoring the base of the tilt meter below the slip surface
offers an approach to capturing translational movements. Movement
would induce bending within the tilt meter conduit, which would be
measured as rotation by the tilt meter (dashed installation in Fig. 4c).
Consideration should therefore be given to the use of tilt meters for
slopes that are expected to have a significant rotational component of
movement. For slopes with predominantly translational deformation
their installation should be adapted accordingly.
Rainfall-induced elevations in pore water pressure are the main trigger
for slope instability in the UK and the majority of the world. Thus,
monitoring both rainfall and pore water pressures continuously with
high temporal resolution provides significant opportunities in identifying
critical conditions for instability. Resistance to movement is dictated
primarily by the stability along shear surface(s) and therefore knowledge
of pore water pressures at shear surface depth(s) is critical in understanding
the stability of the slope. Piezometer tips were installed at
predicted shear surface depths, which were inferred from CPT measurements
at the same time as the installation of inclinometer casings. This
resulted in the active zone of the piezometers being installed below the
depth of the shear surfaces, as identified from subsequent inclinometer
measurements. More accurate measurements of pore water
pressures at the shear surface would be required for stability assessment.
Therefore, it would be advisable to install piezometers at shear
surfaces after their depths have been determined from inclinometer
Fig. 9. First derivative of data presented in Fig. 8 showing AE rates and SAA measured velocity.
Note that periods of acceleration correlate well with rainfall events. A subset of the
SAA and AE measurements from the eastern lobe are also analysed in Smith et al. (2014).
Fig. 10. Conceptual diagram of processes defining the landslide behaviour at Hollin Hill. a) Simplified plan view and cross section of Hollin Hill showing the geomorphological processes
forming the landslide. b) Characteristic, cyclic movement pattern of the Hollin Hill landslide.
449S. Uhlemann et al. / Geomorphology 253 (2016) 438–451
measurements. The piezometers were logged with high temporal
resolution and this, in conjunction with continuous rainfall data,
allowed the identification of periods of potential instability (e.g.
Fig. 6 and Section 4.2). This level of information can be taken to develop
rainfall intensity–duration relationships (e.g. Caine, 1980)
and critical pore water pressures to allow prediction/forecasting of
instability for the slope.
Stability assessment of slopes requires information that inclinometers
and standpipes can provide such as shear surface depths and
ground water levels. However, in order to inform ongoing risk assessments
and numerical modelling of slope stability, and to provide early
warning of instability, greater knowledge of the slopes behaviour
must be acquired. This can be achieved by using combinations of instruments
and techniques. This combination should cover instrumentation
that provides high temporal and spatial resolutions, both at the measurement
and slope scale. While high spatial resolution at the slope
scale usually omits high spatial resolution at the measurement scale
and high temporal resolution, it provides the necessary information
for targeted installation of sensors that can subsequently provide the
necessary high resolution data at those scales. For high temporal resolution
data that inform early warning systems, a telemetric link between
the field site and a database is required. Methods to deliver those data
in real-time to web-platforms informing not only engineers and scientists
but the wider public about potential hazards are becoming more
frequently implemented in recent years (Reid et al., 2012; Huang
et al., 2015), but still require more research on how to manage the available
data and present it in an informative fashion.
Although it is a significant constraint on the majority of projects, the
cost of monitoring and of each instrument and technique has not been
discussed in this paper. However, with rapidly developing technologies
and greater awareness of the value that monitoring can bring to projects,
such instruments and techniques are expected to become more
widely used in the future. This case study provides an example of various
techniques and instruments applied to a landslide over a 5-year period.
It has demonstrated the level of information attainable from the
combination of instruments and techniques, in order to capture both
spatial and temporal behaviour. It showed that only a well-balanced
choice of monitoring devices covering all scales of spatial and temporal
resolutions delivers information that can be used to understand triggering
mechanisms and deformation behaviour of a slope in great detail.
Acknowledgements
We thank the editor, Takashi Oguchi, Federica Bardi, and two anonymous
reviewers for their constructive comments and suggestions that
helped to improve this paper. We would like to extend our sincerest
gratitude to Steve and Josie Gibson (the Hollin Hill landowners) for
their support and cooperation in the research. The Engineering and
Physical Sciences Research Council (EPSRC), UK, funded much of the
Slope ALARMS research and development. This paper is published
with the permission of the Executive Director of the British Geological
Survey (NERC).
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