Inventory maps and modelling of slope

Inventory maps and modelling of slope movements using
ArcView software
Mgr. Jan Klimeš
[email protected]
Katedra geografie a geoekologie, Přírodovědecká fakulta Univerzity Karlovy,
Albertov 6, Praha 2, 120 00, Česká republika
The SINMAP ArcView extension was used to help explain spatial distribution of shallow
landslides induced by the snow malting event in 1997, in the Confini-Aquasparta study area
which covers the east part of the Tiber Náia river basin, Umbria, Italy. This basin belongs to
the post-orogenic sediments complex (Guzzetti et al., 1996), which is characterised by marine
and lake deposits made up of clay, silty clay, fine and coarse gravel and cobbles, which vary
in age from Pliocene to Pleistocene (Guzzetti et al., 1994). The maximum elevation of the
study area is 420 m above see level and the mean value of slope is 8,8°.
For this study the mapping of shallow slope failures at the 1:10 000 scale over an 47 km2
large Confini-Aquasparta study area was completed. The main objective of the mapping was
to prepare a GIS based data-base which could be used as an input layer for the SINMAP slope
stability model. Only shallow landslides, which developed in a loosen bedrock and soil
mantle, were identified on black and white aerial photographs at the 1:20 000 scale.
The SINMAP is an ArcView extension which was designated for preliminary slope stability
assessment of areas endangered by shallow translational landslides controlled by shallow
ground water convergence (Pack et al., 1998). The SINMAP computes a slope stability index
(factor of safety respectively) using primarily digital elevation model (DEM) data. The
SINMAP model solution of slope stability is based on the infinite plane slope stability model
with wetness (thus pore pressures) derived from a topographically based steady state
hydrologic model. Delineation of areas with low stability index, where most of the mapped
landslides were observed is controlled also by geotechnical parameters obtained from soil,
vegetation and geologic data. The necessary input information derived from DEM are slope
and specific catchment area, which is used by the steady state hydrologic model. The
geotechnical parameters used by the infinite plane slope stability model are angle of internal
friction (), soil density (kg/m3) and cohesion (N/ m2) (Pack et al., 1998).
Fig. 1. Definition of the stability classes using the stability index (SI), factor of safety
respectively, according to Pack et al., 1998.
Condition
Class
SI > 1,5
stable
1,5 > SI < 1,25
moderately stable
1,25 > SI > 1
quasi-stable
1 > SI < 0,5
lower threshold
0,5 > SI < 0
upper threshold
0 > SI
defended
Description
Stability conditions
should not fail
external factors
required for instabiliy
probabilty of instabilty is
less than or greater than 50
%
external factors are not
required for instabiliy
unstable for any
parameters within the
parameter range
specified
external factors are
required for stabiliy
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The DEM used for the SINMAP model was derived by digitising contour lines from
topographic maps at the 1:10 000 scale with vertical interval of 10 m. The DEM prepared in
the ArcView software was refined by adding about 270 elevation points extracted manually
from the topographic maps and converted into the grid with 10 m resolution. Ranges of values
of geotechnical parameters which are required for the SINMAP model were determined using
the Table 2. in Guzzetti et al. (1996) and adjusted through interactive visual calibration done
in the SINMAP model. The shallow landslides inventory map of the Confini-Aquasparta
study area was transformed into point shapefile, representing the starting points of each
landslide and then used as one of the input layers for the SINMAP calculations.Performed
models showed that average of 43,5 % of landslides were placed in three least stable
categories while average of 29,4 % of landslides fall to the stable category. The rest (average
of 27,1 %) of landslides were modelled in quasi-stable category where the conditions were
between stable and unstable (see also Fig. 2). All these results were achieved with
geotechnical parameters set to values which could be encountered in the nature and which
characterise the geotechnical conditions at the time of failure. These values were: soil density
ρs = 1950 kg/m3, dimensionless cohesion C = 0 – 0,33, angle of internal friction ø = 17° - 19°
and T/R ratio. The hydrological parameters (T/R ratio) were set to the saturated conditions,
which implies that the water reached the soil surface at the time of failure. Calculations
showed that the maximum value of recharge R (under the range of transmissivity T = 2 . 10-5
– 10-9 m2/s suggested for the studied rock type), which would lead to the unsaturated
conditions is 0,06 mm/hr, which is unrealistic low. Therefore the parameters for all SINMAP
models were set to saturation conditions. The value of dimensionless cohesion for upper
bound is equal to 0,33, which gets cohesion of 9,6 kPa. This value is acceptable event though
in paper of Morrissey et al. (2001) is given range for soil cohesion of similar soil type
between 1 and 48 kPa. The value of 0 for lower bound of dimensionless cohesion is
suspicious and is in contrast with high suggested values of undrained cohesion in Guzzetti et
al. (1996) (2,69 kPa – 7,9 kPa). This may be explained by the fact that the conditions during
the failure of the landslides were closer to the drained conditions and therefore the value of C
was more closer to the drained cohesion which is according to the Guzzetti et al. (1996) equal
0 kPa. Another explanation could be that the values of undrained cohesion given in the
Guzzetti et al. (1996) are those for overconsolidated (bedrock) clay which has much higher
cohesion than weathered soil mantle.
Modelling showed high sensitivity of calculated factor of safety to a cohesion, which
according to the Hammond et al. (1992) increases with decreasing soil depth. On the other
hand, results showed that changing values of angle of internal friction within the range of 18°
– 20,5° does only minor changes in the model’s results. The similar results gained
calculations in Morrissey et al. (2001).
Fig. 2. Results of the SINMAP model summarised into three stability index categories.
Results were received with following values of geotechnical parameters: ρs = 1950 kg/m3, C =
0 kPa – 7,7 kPa and ø = 17° - 19° and water saturation conditions defined by T/R=1000 m 1000 m.
% of study
area
% of
landslides
Stable
Moderately Stable
QuasiStable
Lower Threshold
Upper Threshold
Defended
65,2
14,7
20
27,9
29,5
44,5
Results suggested that distribution of a portion of the studied landslides in the stability classes
was controlled by other factors which were not included in the SINMAP model. Among the
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other factors, which were not included in the model, were local geological conditions,
different local conditions of modelled geotechnical properties, different actual topography and
different hydrological conditions as well as effect of agricultural practices. Results of the
model were also heavily influenced by inaccuracies of the DEM. Due to insufficient elevation
information the DEM calculated slope of 0 – 6,7° close to the tops of the ridges and valley
bottoms and 0 contributing areas where the contourlines were widely spread apart. The
comparison of three different DEMs of the study area showed that the best results were
gained with the DEM prepared from contour lines with vertical interval of 25 m with 25 m
grid cell size, which is in contrast to all other which had 10 m grid cell size. As a measure of
quality of the DEM was considered lower percentage of grid cells in stable category, since
visual inspection of the grids showed that large areas of stable category are due to insufficient
elevation information. Difference in distribution of landslides among stability classes for the
commonly used 10 m grids and 25 m grid were 15,5 %. The model is also very sensitive to
location of the starting points of the landslides.
References
GUZZETTI, F., CARDINALI, M., REICHENBACH, P. (1994): The AVI Project: A Bibliographical
and Archive Inventory of Landslides and Floods in Italy. Environmental Management, Vol.
18, No. 4, Springer-Verlag, New York, p. 623-633.
GUZZETTI, F., CARDINALI, M., REICHENBACH, P. (1996): The Influence of Structural Settings
and Lithology on Landslide Type and Pattern. Environmental and Engineering Geoscience,
Vol. 2, No. 4, New York, p. 531-555.
HAMMOND, C., HALL, D., MILLER, S., SWETIK, P. (1992): Level I Stability Analysis (LISA)
documentation for version 2.0. Gen. Tech. Rep. INT-285. U. S. Department of Agriculture,
Forest Service, Intermountain Research Station. Ogden, UT, p. 190.
MORRISSEY, M., WIECZOREK, G., MORGAN, B. (2001): A Comparative Analysis of Hazard
Models for Predicting Debris Flows in Madison County, Viriginia. Open-File Report 010067, 2001, USGS, p. 9.
PACK, R.T., TARBOTON, D.G., GOODWIN, C.N. (1998): Terrain Stability Mapping with
SINMAP, Technical Description and Users Guide for version 1.00. Report No. 4114-0,
Terratech Consulting Ltd., Salmon Arm, B.C., Canada, p. 76.
Souhrn
Tvorba inventarizačních map a modelování svahových pohybů
s využitím programu ArcView
Studie prokázala, že extense SINMAP je užitečným nástrojem pro studium prostorového
rozmístění a podmínek vzniku mělkých svahových deformací. SINMAP počítá stupeň
stability (factor of safety) na základě topografie, geotechnických parametrů (úhel vnitřního
tření, soudržnost, transmisivita, mocnost zvětralin) a modelových hydrologických podmínek.
Model je použitelný pro mělké, translační sesuvy, které vznikly ve zvětralinovém plášti v
důsledku změny hydrologických podmínek. Model vytvořený extensí SINMAP pro
studovanou oblast Confini-Aquasparta, Umbrie, Itálie, předpověděl výskyt 44,5% mělkých
sesuvů ve třech nejnáchylnějších kategoriích modelu. Pouze 2,5% plochy těchto kategorií
bylo skutečně postiženo sesuvy během náhlého tání sněhu v roce 1997. Toto nízké postižení
nejnáchylnějších částí území, může být vysvětleno nedostatečným měřítkem, kvalitou
vstupních dat (především digitálního modelu terénu) nebo empirickým zjištěním, že během
jedné spoušťové události zpravidla nedojde k postižení všech částí svahů se stejnou
náchylností k porušení. Výsledky modelu SINMAP lze použít k tvorbě mapy náchylnosti
území k sesouvání, kde jednotlivé třídy náchylnosti jsou definovány na základě hodnot stupně
stability.
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