Measuring river planform changes from remotely-sensed data: A Monte-Carlo approach to assess the impact of spatially-variable geometric error.

A majority of European rivers have been extensively affected by diverse anthropogenic activities, including e.g. channelization, regulation and sediment mining. Against this background, the planimetric analysis based on remotely-sensed data is frequently used to evaluate historical planform changes, eventually leading to quantification of migration rates. However, geometric spatially-variable (SV) error inherently associated with these data can result in poor or even misleading interpretation of measured changes, especially on mid-sized rivers. We therefore address the following issue: What is the impact of spatially-variable error on the quantification of surfacic river planform changes?

Our test river corresponds to a 20 m wide meandering sub-tributary of the Upper Rhine, the Lower Bruche. Within four, geomorphologically-diverse sub-reaches, the active channel is digitised using diachronic orthophotos (1950; 1964) and the SV-error affecting the data is interpolated with an Inverse Distance Weighting technique based on an independent set of ground control points. As a second step, the main novelty of our approach consists in running Monte-Carlo (MC) simulations to randomly translate active channels according to the interpolated SV-error. This eventually allows to display the relative margin of error (RME) associated with measured eroded and/or deposited surfaces for each sub-reach through MC simulations, illustrating the confidence level in the respective measurements of our river planform changes.

Our results suggest that (i) SV-error strongly affects the significance of measured changes and (ii) the confidence level might be dependent not only on magnitude of changes but also on their shapes. Taking SV-error into account is strongly recommended, regardless of the remotely-sensed data used. This is particularly true for mid-sized rivers and/or low amplitude river planform changes, especially in the aim of their sustainable management and/or restoration. Finally, our methodology is transferrable to different fluvial styles.

How to cite: Jautzy, T., Herrault, P.-A., Chardon, V., Schmitt, L., and Rixhon, G.: Measuring river planform changes from remotely-sensed data: A Monte-Carlo approach to assess the impact of spatially-variable geometric error., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11470, https://doi.org/10.5194/egusphere-egu2020-11470, 2020