Mr. Michael Maerker, University of Pavia, Italy. Global Symposium on Soil Erosion (GSER19), 15 - 17 May 2019 at FAO HQ.

1. Badland and gully erosion assessment
using remotely sensed data, non-
invasive field techniques and stochastic
modelling approaches
Michael Maerker1, Alberto Bosino1, & Ulrike Hardenbicker2
1University of Pavia, Italy; 2University of Regina, Canada
1

3. splash
Spatio-temporal scales of soil erosion processes
interrill
rill
gully
fluvial
after Renschler & Harbor (2002): Geomorphology 47, 189-209.
badlands

4.  Models often only address single processes and therefore
are scale dependent (USLE, WEPP, Erosion 2D/3D, USPED)
 Models often are focussing only on laminar soil erosion
(sheet/rill-interrill erosion)
 Integrated modelling is very complex
- Different soil erosion processes
- Parameter request
- Scale dependency (spatial/temporal)
 Spatio-temporal distribution
Research Question: How to assess and quantify different soil
erosion processes?
4
Challenges for soil erosion modeling:
Märker et al. (2011): Geomorphology, 125(4), 530-540; Zakerinejad & Märker (2015): Natural Hazards, 79 (1), 25-50
Sidorchuk et al. (2003): Catena, 50, 507-525. Märker et al. (2001): Geografia Fisica e Dinamica Quaternaria, 24, 71-83

5. How to get Information about processes and forms?
GSSI EMP 400 EM
Conductivity Meter
FieldspectrometerNon invasive
Field methods
Local Information about substrates and soils

6. Multi & Hyperspectral
Remotely Sensed Information
and Derivatives
TanDEM-X 90m, 30m, 12m
Terrain Analysis &
Topographic Indices
High resolution DEM by
Structure from Motion
Spatial continuous information about forms, features
and surface characteristics
How to get Information about processes and forms?

7. 7
Badland & Gully Inventory
Forms & Features
Identification &
Mapping
Identification &
Mapping

8. 8
Maerker, M., Pelacani, S. & B. Schröder (2011): A functional entity approach to
predict soil erosion processes in a small Plio-Pleistocene Mediterranean catchment in
Northern Chianti, Italy . GEOMORPHOLOGY, vol. 125 (4), pp. 530-540

9. Susceptibility map
MaxEnt stochastic approach to assess
the driving factors for gully formation
Variable importance
Internal validation via ROC curves

10. 10
Initial phase
(5%)
Static phase
(95%)
Sidorchuk (1999): Catena 37, 401-414
Sidorchuk, Maerker, Moretti & Rodolfi (2003) Catena 50, 507-525
Zakerinejad & Maerker (2015) Natural Hazards 79(1), 25-50
Quantitative Assessment
Maerker, M., Pelacani, S. & B. Schröder (2011): A functional entity approach to
predict soil erosion processes in a small Plio-Pleistocene Mediterranean catchment in
Northern Chianti, Italy . GEOMORPHOLOGY, vol. 125 (4), pp. 530-540
Gully Modelling

11. Conclusion
• Integrated method to assess gully and badland erosion
susceptibilities over large areas using RS, fieldwork
and stochastic modelling approaches.
• Spatial resolution of environmental data (DEM; RS-
data) is increasing, however data need field validation
• Basis for process quantification and connectivity
analysis on basin scale.
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