Determination of hydrological roughness by means of close range remote sensing

Abstract

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 D 50 to D 90 were tested with D 90 showing best correlation between tracer experiments and photogrammetrically acquired data. Several roughness parameters were tested (standard deviation, random roughness, Garbrecht's n and D 90 ). Best agreement in between the grain size and the hydraulic roughness was achieved with a non-linear sigmoid function and D 90 rather than with the Garbrecht equation or statistical parameters.

sUAS and their application in observing geomorphological processes

“…There is a need for research that will contribute to sustainable soil management (Bisantino et al, 2015;Mekonnen et al, 2015;Ndah et al, 2015;Wildemeersch et al, 2015) and that will assist policy makers in finding a way to apply the findings and achieve the sustainability . The use of remote sensing is today a key strategy to research the soil and the soil processes (Aucelli et al, 2016;Holleran et al, 2015;Kaiser et al, 2015;Van Eck et al, 2016). Throughout remote sensing we can observe the "behaviour" of the environment we live in -changes of soil, vegetation, landforms, land uses, and land management; what is the cause for these changes; and mainly what effects these changes have on the environment (De Mûelenaere et al, 2011;Gong et al, 2015;Islam et al, 2015;Zucca et al, 2014).…”

Image-based surface reconstruction in geomorphometry – merits, limits and developments

“…These data further serve to assess pros and cons of SfM photogrammetry, e.g. detection of small-scale erosion features (Nouwakpo et al, 2014), with regard to the doming effect (Eltner and Schneider, 2015) or as input parameter for erosion modelling (Kaiser et al, 2015).…”

Modelling Discharge and Sediment Yield at Catchment Scale Using Connectivity Components

“…Topographical connectivity can be inferred from digital terrain models (DTMs), aerial photography or (traditional) geomorphological mapping. Currently, techniques exist to create DTMs with resolutions of up to a few centimetres or even millimetres (Westoby et al ., ; Kaiser et al ., ; Nadal‐Romero et al ., ). With such DTMs the structure of the landscape can be captured from small scale features like soil roughness up to large scale landforms like floodplains and alluvial fans.…”