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Past decades have seen rapid advancements … Past decades have seen rapid advancements in the field of soil erosion modelling, with a shift away from lumped empirical models and towards fully-distributed physically-based erosion models. The benefits of this shift is that distributed erosion models facilitate the spatial predictions of erosion and deposition across the landscapes by computing runoff and modelling the subsequent detachment, transport, and deposition of sediments. Despite the ability to represent the physical process of erosion spatially, distributed erosion models are validated to discharge and sediment yield at catchment outlets. Spatial information on erosion and deposition rates are seldom used to validate distributed models; this is because both plot and field-scale data on erosion rates are rare. Structure-from-motion (SfM) and multi-view stereo (MVS) algorithms coupled with the use of unmanned aerial vehicles (UAVs) have become a popular tool in geomorphology for modelling topographic change-detection on complex landscapes. We demonstrate the viability of using these techniques to generate spatial validation data; repeat UAV surveys of an agricultural field are used to identify dominant sediment flow paths, depositional zones, and rill/gully erosion processes. This unique spatial dataset allows us to tackle issues of spatial equifinality, model parameterization, and the accurate discretization of the landscape. accurate discretization of the landscape. +
Mapping Erosion and Deposition in an Agricultural Landscape: A Spatial Validation of Erosion Models +
Waterloo +
Canada +
dtrobinson@uwaterloo.ca +
University of Waterloo +
waterloo +
benjmeinen@hotmail.com +
Benjamin +
University of Waterloo +
Meinen +
2267489287 +
Benjamin_Meinen_CSDMS_Conference_Poster_final.pdf +
Image:Benjamin_Meinen_CSDMS_Conference_Poster_final.png +
4) Developing and Teaching Interactive Sedimentology +
4) Model Calibration with Dakota +
3) SALib - Model Sensitivity Analysis +
Canada +
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18:03:24, 28 March 2019 +
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20:04:24, 28 May 2019 +
