Susceptibility models for pipe collapse in loess-derived soils in a temperate humid climate*
Els Verachtert (1), Miet Van Den Eeckhaut (2,1), Jean Poesen (1), Gerard Govers (1) and Jozef Deckers (3)
(1) Division of Geography, Department of Earth and Environmental Sciences, K.U.Leuven, Belgium; (2) Land Management and Natural Hazards Unit Institute for Environment and Sustainability, Joint Research Centre (JRC) - European Commission, Ispra, Italy;
(3) Division of Soil and Water Management, Department of Earth and Environmental Sciences, K.U.Leuven. E-mail address: els.verachtert@ees.kuleuven.be
Problem statement
A. Logistic regression
B. Topographic thresholds (SA-relation)
Soil piping (tunnel erosion) has been recognized as an important erosion
process in collapsible loess-derived soils in a temperate humid climate,
which can cause collapse of the topsoil and formation of discontinuous
gullies. Still, information on the spatial patterns of collapsed pipes and
regional models describing these patterns is limited.
Therefore, this study aims at predicting pipe collapses and a better
understanding the factors controlling their spatial distribution.
(a)
(b)
(c)
The use of the SA-thresholds
allowed producing a map with
reasonable predictions of
susceptibility to pipe collapse
with
a
minimum
of
information…
for this environment!
Figure 1. Pictures of (a) collapsed pipes (n=3; diameter ca. 0.6 m; depth ca. 0.7 m) in a pasture (Kluisbergen,
April 2009), (b) a collapsed pipe (Maarkedal, February 2008) and (c) a typical pipe cross-section (Kluisbergen,
March 2010)
Methods
Fig. 5. Topographical thresholds for pipe collapse used for classification of the
SA derived piping susceptibility map (1 very low, 2 low, 3 moderate, 4 high, 5
very high).
A dataset with parcels suffering from piping (560 collapsed pipes) and
parcels without collapsed pipes was compiled through a detailed survey
in a 236 km² study area in the Flemish Ardennes (Belgium; Fig. 2).
This is in contrast to findings
from the UK (Jones, 1986,
1997; Holden, 2005) where
other
factors
(e.g.
land
management)
are
more
important
than
surface
topography.
Fig. 3. Methodology used for modelling piping susceptibility using logistic regression.
In the Flemish Ardennes, the
SA
relation
seems
to
represent
the
spatial
distribution of other factors
such as lithology as well.
Fig. 6. Classified map indicating susceptibility to pipe collapse produced with
logistic regression.
Conclusions
For logistic regression, locations in NCP-parcels that were similar to locations of
collapsed pipes were selected to allow for correct comparison. Pipe collapse is
more likely to occur when a topographical threshold depending on both slope
gradient and upslope area is exceeded in zones where subsurface flow occurs,
due to topographical convergence and/or the presence of a clay-rich lithology.
Fig. 2. Location of the study area in Belgium and inventory of the collapsed pipes (n=560) projected on a map
with indication of the clay-rich Aalbeke Member (Tertiary lithology).
Logistic regression was carried out to find the best model describing the
relationship between the presence/absence of a collapsed pipe and a set
of independent explanatory variables (slope gradient, drainage area,
distance-to-thalweg, curvature, aspect, soil type and lithology).
Special attention was paid to the selection procedure of the grid cells
without piping erosion.  Part A
A second piping susceptibility map was made based on topographical
thresholds of slope gradient (S) and upslope drainage area (A).  Part B
Fig. 4. Classified map indicating susceptibility to pipe collapse produced
with logistic regression.
The logistic regression model allowed identifying the most
important factors controlling pipe collapse: i.e. S, distance-tothalweg, A, wet and silty clay loam soil, west-facing slopes, (silty) clay
lithology and concave plan curvature.
References
Holden J. 2005. Controls of soil pipe frequency in upland blanket peat. J. Geophys. Res. Earth Surf. 110, F01002.
Jones JAA. 1986. Some limitations to the a/s index for predicting basin-wide patterns of soil water drainage.Z. Geomorph.
N.F., Suppl.-Bd 60, 7-20.
Jones JAA. 1997. Pipeflow contributing areas and runoff response. Hydrol. Process.11, 35-41.
Verachtert E, Van Den Eeckhaut M, Poesen, J, Deckers J. 2010. Factors controlling the spatial distribution of soil piping
erosion on loess-derived soils: a case study from central Belgium. Geomorphology 118 (3-4), 339-348.
* Verachtert E, Van Den Eeckhaut M, Poesen J, Govers G, Deckers J. 2011. Prediction of spatial patterns of collapsed
pipes in loess-derived soils in a temperate humid climate using logistic regression. Geomorphology,
10.1016/j.geomorph.2011.03.015