Quantifying the dynamics of microtopography during a snowmelt event. Issue 13 (22nd August 2019) - Barneveld, Robert J.; van der Zee, Sjoerd E. A. T. M.; Stolte, Jannes
Abstract: Knowledge of soil microtopography and its changes in space and over time is important to the understanding of how tillage influences infiltration, runoff generation and erosion. In this study, the use of a terrestrial laser scanner (TLS) is assessed for its ability to quantify small changes in the soil surface at high spatial resolutions for a relatively large surface area (100 m 2 ). Changes in soil surface morphology during snow cover and melt are driven by frost heave, slaking, pressure exertion by the snowpack and overland flow (erosion and deposition). An attempt is undertaken to link these processes to observed changes at the soil surface. A new algorithm for soil surface roughness is introduced to make optimal use of the raw point cloud. This algorithm is less scale dependent than several commonly used roughness calculations. The results of this study show that TLSs can be used for multitemporal scanning of large surfaces and that small changes in surface elevation and roughness can be detected. Statistical analysis of the observed changes against terrain indices did not yield significant evidence for process differentiation. © 2019 The Authors. Earth Surface Processes and Landforms Published by John Wiley & Sons Ltd. © 2019 The Authors. Earth Surface Processes and Landforms Published by John Wiley & Sons Ltd. Abstract : Terrestrial Laser Scanning can be used to detect minute changes in soil surface elevation and roughness that resulted from snow cover and melt. Some of these changes can be linked to specific processes. A new soil roughness algorithm is tested and found to be comparatively scale‐independent.