EGU23-6524, updated on 25 Feb 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Spatio-temporally highly resolved validation of a rill-based soil erosion model with 4D data 

Oliver Grothum1, Dave Favis-Mortlock2, Petr Kavka3, Martin Neumann3, Tomáš Laburda3, and Anette Eltner1
Oliver Grothum et al.
  • 1Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, Dresden, Germany
  • 2British Geological Survey, Nottingham, UK
  • 3Faculty of Civil Engineering, Czech Technical University in Prague, Prague, Czechia

Time-lapse photogrammetry has been proven to be a valuable tool to support the understanding of earth surface processes since it can be used to create 3D models with an unprecedented temporal resolution. Overlapping images are captured simultaneously and structure from motion (SfM) photogrammetry is used to reconstruct 3D point clouds from these images automatically.

We performed one rainfall simulation on an erosion plot in the field covering about 16 square meters and having a slope of 9 degrees and another experiment in the laboratory with a plot of about 4 square meters and a slope of 20 degrees. Rainfall intensities were similar and high in both simulations to ensure rill formation. During the experiment, we measured soil surface changes with a time series of 3D point clouds derived via SfM photogrammetry. We also estimated runoff flow velocities with a tracer and observed the spatial pattern of runoff velocities with particle tracking velocimetry (PTV) applied to videos captured during the field experiment. At the plot outlet, we also measured runoff and sediment yield. These datasets were used as validation data for the soil erosion model.

Soil erosion was simulated with the physically-based model RillGrow and SMODERP, which conceptualizes the formation of erosion rills as a self-organizing dynamic system. We ran several thousand erosion simulations using a Monte Carlo approach. The aim was first to assess the sensitivity of the input parameters of the model, and secondly to automatically find the best fitting set of input parameter values for the given field site conditions and rainfall intensity. We compare the simulation results to global values, such as the sediment yield and runoff, and to local changes, measured by the photogrammetric 4D data.

Our study combines established as well as newly developed data recording and processing methods to create a spatio-temporal high-resolution dataset. This is used to test a soil erosion model with the aim of enhancing understanding of rill erosion processes.

This research was supported by the projects DFG EL926/3-1, SFZP 085320/2022, SS05010180, and SGS OHK1-086/23/11143.

How to cite: Grothum, O., Favis-Mortlock, D., Kavka, P., Neumann, M., Laburda, T., and Eltner, A.: Spatio-temporally highly resolved validation of a rill-based soil erosion model with 4D data , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6524,, 2023.