Abstract
The silty soils of the intensively used agricultural landscape of the Saxon loess province, eastern Germany, are very prone to soil erosion, mainly caused by water erosion. Rainfall simulations, and also increasingly structure-from-motion (SfM) photogrammetry, are used as methods in soil erosion research not only to assess soil erosion by water, but also to quantify soil loss. This study aims to validate SfM photogrammetry determined soil loss estimations with rainfall simulations measurements. Rainfall simulations were performed at three agricultural sites in central Saxony. Besides the measured data runoff and soil loss by sampling (in mm), terrestrial images were taken from the plots with digital cameras before and after the rainfall simulation. Subsequently, SfM photogrammetry was used to reconstruct soil surface changes due to soil erosion in terms of high resolution digital elevation models (DEMs) for the pre- and post-event (resolution 1 × 1 mm). By multi-temporal change detection, the digital elevation model of difference (DoD) and an averaged soil loss (in mm) is received, which was compared to the soil loss by sampling. Soil loss by DoD was higher than soil loss by sampling. The method of SfM photogrammetry-determined soil loss estimations also include a comparison of three different ground control point (GCP) approaches, revealing that the most complex one delivers the most reliable soil loss by DoD. Additionally, soil bulk density changes and splash erosion beyond the plot were measured during the rainfall simulation experiments in order to separate these processes and associated surface changes from the soil loss by DoD. Furthermore, splash was negligibly small, whereas higher soil densities after the rainfall simulations indicated soil compaction. By means of calculated soil surface changes due to soil compaction, the soil loss by DoD achieved approximately the same value as the soil loss by rainfall simulation.
Highlights
Due to widespread silty soils of the European loess belt, the Saxon loess province, easternGermany, is very prone to soil erosion, mainly caused by water erosion
The method of SfM photogrammetry-determined soil loss estimations include a comparison of three different ground control point (GCP) approaches, revealing that the most complex one delivers the most reliable soil loss by digital elevation model of difference (DoD)
The results from this study offer crucial evidence for the inclusion of soil compaction for the interpretation of soil loss estimations using DoDs calculated with SfM photogrammetry in agricultural landscapes
Summary
Due to widespread silty soils of the European loess belt, the Saxon loess province, easternGermany, is very prone to soil erosion, mainly caused by water erosion. Soil erosion in agricultural landscapes occurs primarily due to interrill and rill erosion [3,4,5]. Higher detachment rates on plot scale can be achieved by large- scale rainfall simulators [15,16], which require more manpower and logistics than small-scale simulators. In this regard, Schindewolf and Schmidt [17] developed a small-scale rainfall simulator with a runoff feeding device to ensure higher runoff and sediment detachment rates, which are able to produce interrill and rill erosion on a 3 × 1 m plot size
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