The quantitative estimation of changes in terrain surfaces caused by water erosion can be carried out from precise descriptions of surfaces given by means of digital elevation models (DEMs). Some stages of water erosion research efforts are conducted in the laboratory using rainfall simulators and soil boxes with areas less than 1m2. Under these conditions, erosive processes can lead to very small surface variations and high precision DEMs are needed to account for differences measured in millimetres. In this paper, we used a photogrammetric Structure from Motion (SfM) technique to build DEMs of a 0.5m2 soil box to monitor several simulated rainfall episodes in the laboratory. The technique of DEM of difference (DoD) was then applied using GIS tools to compute estimates of volumetric changes between each pair of rainfall episodes. The aim was to classify the soil surface into three classes: erosion areas, deposition areas, and unchanged or neutral areas, and quantify the volume of soil that was eroded and deposited. We used a thresholding criterion of changes based on the estimated error of the difference of DEMs, which in turn was obtained from the root mean square error of the individual DEMs. Experimental tests showed that the choice of different threshold values in the DoD can lead to volume differences as large as 60% when compared to the direct volumetric difference. It turns out that the choice of that threshold was a key point in this method. In parallel to photogrammetric work, we collected sediments from each rain episode and obtained a series of corresponding measured sediment yields. The comparison between computed and measured sediment yields was significantly correlated, especially when considering the accumulated value of the five simulations. The computed sediment yield was 13% greater than the measured sediment yield. The procedure presented in this paper proved to be suitable for the determination of sediment yields in rainfall-driven soil erosion experiments conducted in the laboratory.
Geomorphology – Elsevier
Published: Oct 15, 2017
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