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Volume 1, issue 2
SOIL, 1, 613–620, 2015
https://doi.org/10.5194/soil-1-613-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Advancements in data acquisition for soil erosion studies

SOIL, 1, 613–620, 2015
https://doi.org/10.5194/soil-1-613-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Original research article 14 Sep 2015

Original research article | 14 Sep 2015

Determination of hydrological roughness by means of close range remote sensing

A. Kaiser1, F. Neugirg2, F. Haas2, J. Schmidt1, M. Becht2, and M. Schindewolf1 A. Kaiser et al.
  • 1Technical University Bergakademie Freiberg, Germany
  • 2Catholic University Eichstätt-Ingolstadt, Germany

Abstract. The objective of the presented work was to develop a method to acquire Manning's n by creating very high-resolution surface models with structure-from-motion methods. As hydraulic roughness is an essential parameter for physically based erosion models, a practical measuring technique is valuable during field work. Data acquisition took place during several field experiments in the Lainbach valley, southern Germany, and on agricultural sites in Saxony, eastern Germany, and in central Brazil. Rill and interrill conditions were simulated by flow experiments. In order to validate our findings stream velocity was measured with colour tracers. Grain sizes were derived by measuring distances from a best fit line to the reconstructed soil surface. Several diameters from D50 to D90 were tested with D90 showing best correlation between tracer experiments and photogrammetrically acquired data. Several roughness parameters were tested (standard deviation, random roughness, Garbrecht's n and D90). Best agreement in between the grain size and the hydraulic roughness was achieved with a non-linear sigmoid function and D90 rather than with the Garbrecht equation or statistical parameters.

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