DEVINE -  Landslide Risk


La Clapiere Landslide

Abstract

The site of the landslide at La Clapière, in the Maritime Alps, France is used to demonstrate the utility of Global Positioning System measurements for monitoring landslide motion. This study estimates the displacement rates at the base of the landslide during April 1998 to be 5 mm/year.  Several GPS data processing strategies are investigated to determine the tradeoff between the reliability of the displacement estimates and the recording duration to evaluate the near-real time potential of the system. A 12 hour measurement session yields the optimal results with the precision necessary to resolve the motion..
 

Introduction

The landslide at La Clapière, in south-eastern France, is located on the east side of the steep La Tinée river valley upstream of the village of Saint Etienne de Tinée.  Motion was first observed on the slope more than a century ago, but the first quantitative study took place in 1948 using aerial imagery to map the extent of the landslide (RRR).  Since then, the slow moving mass estimated at 50 million cubic kilometers has been the obect of detailed study using an extensive range of measurement techniques including tiltmeters, photogrammetry, two-color laser ranging, Synthetic Aperture Radar Interferometry (INSAR), and DORIS (Détermination d’Orbite et Radio-Positionnement Intégrés par Satellite; Valette, 1992), as well as classical morphological, geological, and hydrological studies.

The volume of approximately 50 million cubic meters has been in motion for at least a century, but the first quantitative study in 1948 using correlated aerial images

GPS Measurement Campaign

One GPS receiver was installed as a reference site on the opposite slope facing the landslide (CLPR, figure 1). This slope is geologically different and geotechnical studies carried out for the displacement of the access road to this slope confirm that the site is stable.

 Three GPS receivers were installed equally spaced along the base of the landslide within the limits of the obviously mobile blocks, CLP3 being the farthest north, CLP2 in the center, and CLP1 the farthest south. Site CLP1 was located in a slide block with no vegetation. CLP2 and CLP3 were located in clearings in a series of deformed terraces with surrounding low vegetation. The choice of sites was limited by accessibility. The satellite mask caused by the slope reached up to 50 degrees for almost the entire north-eastern quadrant, but was an unavoidable characteristic of the topography. CLP1 was also located near laser target 24. Site CLP2 was located 16.7 meters from laser target 23 and 7.7 meters from a radar reflector.

The four Ashtech dual frequency Z-12 receivers recorded continuously at a sample interval of 15 seconds from 7th to 12th of April, 1999 (doy 097-102). Each site had Ashtech choke ring antennas and the reference site was also equipped with a conical radome. The antennas were mounted on wooden tripods and optically centered over the metal pins embedded in concrete which served as geodetic markers. Cumulative snowfall of 50 cm during the experiment had a small but detectable effect on the measurements.

GPS Data Processing Strategy

The data was processed using the GAMIT software (REF$$). The position of the reference station CLPR was first calculated in the ITRF94 reference frame using L1 and L2 phase data from CLPR and the IGS stations Kootwijk (NL), Wettzell (D), Zimmerwald (CH), Graz (A), Noto (I), and Matera (I) with the positions of these constrained to their ITRF coordinates. We used precise IGS orbits. The coordinates of CLPR, the weighted mean of 6 sessions of 24 hours, are given in Table 1. The repeatability of the estimate is of the absolute horizontal position is the order of ?1 cm. Here the repeatability of each component of the baseline length is defined as the weighted root mean square error where the weights are the formal errors of the individual daily estimates (Genrich and Bock, 1992).

ECEF ITRF94 WGS-84
X 4544006.843 ? 44o 14’38.19575’’
Y 552760.550 ? 6o 56’ 08.62430’’
Z 4428424.477 H 1253.843

Table 1 Coordinates of CLPR reference site

The positions of the mobile stations (CLP1, CLP2, and CLP3 located on the landslide) were calculated relative to the reference site CLPR also using GAMIT. We used precise IGS orbits. CLPR was constrained to the above coordinates ?1 cm. Because of the short baseline lengths (700 meters maximum) we did not solve for tropospheric parameters. We modeled antenna phase center variations (Mader, ref$$). We used L1 frequency observations only (f1=1575.42 MHz) since the ionosphere-free dual frequency combination is actually noisier on short baselines (Genrich and Bock, 1992).  Dual frequency observables were used, however, for cycle slip editing and to check the resolution of ambiguities.

The session length was varied with the objective being to determine the optimal duration for confidently detecting motion of the mobile stations. We calculated baselines between the stations for sessions of decreasing length of 24 hours, 12 hours, 6 hours, and 1 hour. 24 hour long sessions were clearly long enough to average out multi-path noise and  varations due to the geometry of the satellite constellation represented by GDOP (Geometric Dilution of Precision). The sessions of 12, 6, and 1 hours demonstrate the increasing influence of biases with the decrease in measurement time.

Displacement Rates

24 hour sessions:
The calculations made with sessions of 24 hour provide the highest precision possible for static positioning. The short term horizontal accuracy of the measurements is estimated at 2mm for such short baselines (REF$$)  Table 2 shows the baseline lengths for each daily solution with the repeatibility.  i$$Was a solution made with globk for a constant velocity over 4 days?$$
 

Baseline Day 098 099 100 101 102
 Shortening by 12 mm Extension by 2 mm
CLPR-CLP1
 Shortening of 11 mm No change
CLPR-CLP2
 No change Shortening by 6 mm
CLPR-CLP3

Table 2 Change in baseline length for the three baselines over 5 days

Over the  5 day period, all of the baselines have shortened, which is the general trend expected from the geometry with the mobile sites approaching the reference site in the horizontal plane as the landslide moves down the slope (Figure 2). The size of the signal is well above the estimated short term accuracy of the measurements of 2 mm.  The evolution of the positions of the three mobile sites shows that the three sites are moving independently, with the minimum and maximum occurring at different times, as well as the simultaneous extension of the CLPR-CLP1 baseline with shortening of the CLPR-CLP3 baseline.

The evolution in time of the vertical component of the baseline length for the three mobile stations is shown in Figure 3. An increase in the vertical component of the baseline length implies a decrease in the altitude of the mobile sites since they are located at an altitude lower than the reference site. All three sites show an elevation increase followed by an elevation decrease. We do not have an independent estimate of the vertical repeatability of the measurements, but based on similar work ($$REF$$) we can expect an accuracy of approximately a centimeter. The variations in altitude of station CLP1 and CLP2 are twice this error level. The altitude of CLP1 initially increases by 2.5 cm then  descends by 3.5 cm. Station CLP2 initially increases in altitude by 1.5 cm then descends by 1 cm. CLP2 remains at approximately the same altitude with the variations not exceeding the expected error level.

A map view of the evolution in time of the three positions is shown in Figure 4. The movement of CLP1 is first towards the west and then towards the south. Based on the topography of the slope, this would predict first that the site descends and then remains at the same altitude, whereas the vertical measurements show that the site moves up then down abruptly. The movement of CLP2 is predicted by the topography to be first downslope and then remaining at the same altitude, whereas the motion is first up then followed by a descent. This apparent inconsistency may be explained by soil expansion, as depicted in Figure 5. Under this hypothesis, the largest motion is vertical motion upwards as the soil expands and then vertical motion downwards as the groundwater profile reaches the slip interface for the block and the whole block descends gravitationally with both these signals producing horizontal motion towards the facing slope. $$??!!whattaya think of that?.

Time series of temperature from the village of St.Etienne de Tinée and precipitation (snow)  and mean temperature from the ski station at Auron on the summits just above St. Etienne were collected from the Meteofrance archives. They are shown in figure Figure 9. Heavy precipitation on the order of 50 mm of snowfall preceded the experiment. The two following days (days 98-100) positive temperatures led to melting of the snow. Lower temperatures and continued snowfall put an end to the melting and the soil stabilized hydrologically $$$ is this right$$$ until the final day of the experiment.

There is some suggestion of diurnal periodicity in the time series of both the horizontal and vertical components of motion in the time series where 12 hour solution sessions are used. This may also be an artifact of the sampling in 12 hour sessions. However, if it is significant it may provide additional support for the argument of melting snow providing the triggering mechanism for slip. The daily rise in temperature and afternoon snow melt may cause an increase in the soil expansion corresponding to the upwards motion during the second session of 12 hours in Figure 7.

GPS Data Processing Optimization

The noise in the solutions, quantified by the repeatability of the solution, increases as a function of decreasing length of the raw data time series. This is because of the simple increase in the number of data, but also because of longer term sources of noise being averaged out such as multipath signals with periods of the order of the GPS satellite orbit time of 11 minutes 50 seconds. We investigate the potential for monitoring the landslide in near real time by examining this tradeoff between session length and solution noise. It is desirable to use the shortest session length possible to decrease the delay for early warning of an event, but it is necessary that the variations be detected with a high level of confidence.

We have calculated time series for the baseline length and its horizontal components for sessions of 12 hours, 6 hours, and 1 hour for comparison with the 24 hour session solution. Each 24 hour session was broken into 2 consecutive sessions of 12 hours with no overlap and no sliding window. Similarly for the 6 and 1 hour sessions, each day was broken into 4 sessions of 6 hours and 24 sessions of 1 hour respectively. These results are shown in Figure 7, Figure 8, and Figure 9.

The calculations for sessions of 12 and 6 hours show the same tendencies as the 24 hour session. The 24 hour solution appears to be a smooth version of the 6 or 12 hour series. However, as expected, the shorter the session length, the greater the noise that is superimposed on the landslide signal. For sessions less than 6 hours the discrimination of the true signal, i.e. the signal visible in the 24 hour session time series, is impossible. In addition the amplitude of the deviation from the true signal increases with shorter sessions. For sessions of 1 hour it is clear that the sign and amplitude of this noise is consistent for all three sites. These observations are also true for the vertical component of baseline length.

We investigate the correlation between multipath and the noise in the position estimates.

Discussion

Snowfall during the week of the measurements is expected to affect the experiment in several ways. First, the melting of snow cover permeates into the surface sediments causing soil expansion. Second, we expect an increase in the multipath noise in the measurements.  Third, the accumulation of snow on the antenna, which reached 25 cm over one 24 hour period, affects the propagation of  the GPS signal locally.  The vertical component is the the most sensitive to the snow accumulation (Kenneth et al., 1996), since the horizontal effects will be averaged out with good azimuthal coverage.  No attempt was made to remove this unknown bias from the vertical time series. The fact that CLP1 has the greatest variation in the vertical direction from hours 48 to 118 of the experiment, while the accumulated snow on the antenna was relatively constant over this time implies that snow accumulation had only a small signal in the recovered time series relative to soil expansion and real vertical motion (Figure 8).
 

Figure 1 La Clapière landslide, St. Etienne de Tinée, France. The aerial photograph taken in 1995 shows freshly exposed white rock surrounding the sliding mass on the northeast side of the valley. The locations of the GPS stations are shown as black triangles. Station CLPR on the southwest side of the valley is the stable reference station.
Figure 2 Variation in meters of the baseline length for each 24 hour session relative to initial value. Hour 0 corresponds to day 098 00:00 GMT. The time series are spline interpolated in between the 5 individual point measurements which are plotted at the middle of each session.
Figure 3 Variations in meters of the vertical components of the three baselines for 24 hour sessions. Since the mobile sites CLP1, CLP2, and CLP3 are all located at a lower elevation than the reference site, an increase in the vertical component of the baseline length implies a decrease in the altitude of the mobile site.

Figure 4 Evolution of the position of points CLP1, CLP2, and CLP3 as a function of time.

Figure 5 Hypothesis of soil expansion to explain apparent increase in elevation of station CLP1 and CLP2.

Figure 6 Variation in meters of the baseline length for each 12 hour session relative to initial value. Hour 0 corresponds to day 098 00:00 GMT. The time series are spline interpolated between successive 12 hour samples.

Figure 7 Variation in meters of the vertical component baseline length for each 12 hour session relative to initial value. Hour 0 corresponds to day 098 00:00 GMT. The time series are spline interpolated between successive 12 hour samples.

Figure 7 Comparison of the baseline length variations retrieved using several different session lengths for station CLP1. The $$ line corresponds to a session length of 24 hours, $$ corresponds to a session length of 12 hours, $$ corresponds to a session length of 6 hours, $$ corresponds to a session length of 1 hour. For session lengths of 6 hours and less, the uncertainty in the baseline length estimates obscures the trend.

Figure 8 Comparison of the baseline length variations retrieved using several different session lengths for station CLP2.

Figure 9 Comparison of the baseline length variations retrieved using several different session lengths for station CLP3.

Figure 10 Meteorological conditions during the experiment. Anomalous snowfall during the measurement period accumulated on the GPS antennas and caused an additional source of error. Melting snow on the $$last$$ day of the experiment may have caused soil expansion as water soaked into the permeable surface sediments.
 

 

[ Earthquakes | Landslides | Carto | GPS Tools 
 
| Email | Search  | DEVINE Home ACRI Home ]


Last update 20-Dec-1999
Email: jh@acri.fr