Abstract

Abstract. The effect of the spatial resolution of digital terrain models (DTMs) on topography and soil erosion modelling is well documented for low resolutions. Nowadays, the availability of high spatial resolution DTMs from unmanned aerial vehicles (UAVs) opens new horizons for detailed assessment of soil erosion with hydrological models, but the effects of DTM resolution on model outputs at this scale have not been systematically tested. This study combines plot-scale soil erosion measurements, UAV-derived DTMs, and spatially explicit soil erosion modelling to select an appropriate spatial resolution based on allowable loss of information. During 39 precipitation events, sediment and soil samples were collected on five bounded and unbounded plots and four land covers (forest, fallow, maize, and eroded bare land). Additional soil samples were collected across a 220 ha watershed to generate soil maps. Precipitation was collected by two rain gauges and vegetation was mapped. A total of two UAV campaigns over the watershed resulted in a 0.60 m spatial-resolution DTM used for resampling to 1, 2, 4, 8, and 15 m and a multispectral orthomosaic to generate a land cover map. The OpenLISEM model was calibrated at plot level at 1 m resolution and then extended to the watershed level at the different DTM resolutions. Resampling the 1 m DTM to lower resolutions resulted in an overall reduction in slope. This reduction was driven by migration of pixels from higher to lower slope values; its magnitude was proportional to resolution. At the watershed outlet, 1 and 2 m resolution models exhibited the largest hydrograph and sedigraph peaks, total runoff, and soil loss; they proportionally decreased with resolution. Sedigraphs were more sensitive than hydrographs to spatial resolution, particularly at the highest resolutions. The highest-resolution models exhibited a wider range of predicted soil loss due to their larger number of pixels and steeper slopes. The proposed evaluation method was shown to be appropriate and transferable for soil erosion modelling studies, indicating that 4 m resolution (<5 % loss of slope information) was sufficient for describing soil erosion variability at the study site.

Highlights

  • The expansion of the agricultural frontier has been identified as being one of the factors driving the increase in global agricultural production (FAO, 2013), but this increase has a cost

  • Naranjo et al.: Effects of spatial resolution of terrain models on modelled discharge and soil loss in Oaxaca (UNCCD, 2017), mainly due to soil erosion costing more than USD 40 billion in lost productivity (UNEP, 2012)

  • The Cuauhtemoc watershed lies within Santa Catarina Tayata (SC Tayata) municipality in the Mixteca Alta region, Oaxaca, Mexico (Fig. 1), where serious soil erosion has been described as an “ecological disaster” (Guerrero-Arenas et al, 2010)

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Summary

Introduction

The expansion of the agricultural frontier has been identified as being one of the factors driving the increase in global agricultural production (FAO, 2013), but this increase has a cost. Naranjo et al.: Effects of spatial resolution of terrain models on modelled discharge and soil loss in Oaxaca (UNCCD, 2017), mainly due to soil erosion costing more than USD 40 billion in lost productivity (UNEP, 2012). Two types of simulation models, empirical and physically based, are distinguished (Batista et al, 2019; Pandey et al, 2016). Based models such as OpenLISEM (Jetten, 2018) or LUCIA (Lippe et al, 2014) aim at capturing relevant processes from twodimensional plots to three-dimensional landscapes and from minutes to days in temporal resolution

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