Universität zu Köln

van der Meij, W. Marijn ORCID: 0000-0001-8724-5120 (2025). Translating deposition ages into erosion rates: inverse landscape evolution modelling and uncertainty analysis. Earth Surface Dynamics, 13 (5). pp. 845-860. Copernicus Publications. ISSN 2196-632X

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Abstract

Soil erosion is a significant threat to agricultural food production. Determination of erosion rates is essential for quantifying land degradation, but it is challenging to determine temporally dynamic erosion rates over long time scales. Optically Stimulated Luminescence (OSL) dating can provide temporally-resolved deposition rates by determining the last moment of daylight exposure of buried colluvial deposits. However, these deposition rates may differ substantially from the actual hillslope erosion rates. In this study, hillslope erosion rates were derived from OSL-based deposition ages through inverse modelling with soil-landscape evolution model ChronoLorica. This model incorporates geochronological tracers into simu- lations of soil mixing and redistribution. The model was applied to a closed catchment in north-eastern Germany, which has experienced tillage erosion over the last 5000 years. Previously reconstructed pre-erosion topography and land-use history, with known uncertainties, allowed for an uncertainty analysis to quantify the impacts of various sources of uncertainty on the model output. The inverse modelling provided local tillage parameters for different land-use phases that aligned well with a global compilation from comparable studies. The simulated erosion and deposition rates, which increased by two order of magnitude over time, correspond well with independent age controls at both the catchment and point scales. On average, deposition rates were 1.5 times higher than the erosion rates, with recent increases up to five times, indicating that deposition rates cannot be used as direct proxies for erosion rates. The uncertainty analysis showed that the initial topography was the dominant source of variance in the model output, followed by land-use history and model parameters. Reconstruction of these initial and boundary conditions with their uncertainty is essential for representing uncertainty in model output and avoiding overconfidence in the model. This study demonstrates the suitability of ChronoLorica for upscaling experimental geochronological data to better understand landscape evolution in agricultural settings.

Item Type:	Article
Creators:	Creators Email ORCID ORCID Put Code van der Meij, W. Marijn UNSPECIFIED https://orcid.org/0000-0001-8724-5120 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-798399
Identification Number:	10.5194/esurf-13-845-2025
Journal or Publication Title:	Earth Surface Dynamics
Volume:	13
Number:	5
Page Range:	pp. 845-860
Number of Pages:	16
Date:	11 September 2025
Publisher:	Copernicus Publications
ISSN:	2196-632X
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Geosciences > Geographisches Institut
Subjects:	Earth sciences
['eprint_fieldname_oa_funders' not defined]:	Publikationsfonds UzK
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/79839