PhotoMOB: a GIS tool to monitor spatial and temporal bed mobility at the patch scale

The stability or, conversely, the mobilisation of riverbeds varies in time and space, making it a complex phenomenon to study. The size and intensity of mobile grains can lead to disturbance of the substrate that supports physical habitats and can therefore control the presence of aquatic organisms. The degree of mobility of a given grain size fraction (GSF) can be approximated by assessing the proportion of its grains that are mobile. On the other hand, the relative degree of mobility can be expressed as the ratio between the proportion p_i of this fraction among all mobilised grains compared to its initial proportion at the surface of the bed F_i. A condition of full mobility is reached when the fraction's proportion among the mobilised grains is equal to or greater than its initial proportion at the surface (p_i /F_i≥ 1). An underrepresented fraction is said to be partially mobile (p_i /F_i<1).

We present PhotoMOB, a GIS-based tool to characterise (i) grain shape (i.e. axis size, orientation, roundness, compactness, elongation), (ii) patch organisation (i.e. proportion of fine material cover, proportion of overlapping grains) and (iii) mobility magnitude of gravel river beds from repeated digital photographs taken before and after targeted hydrological events. It is based on the detection and the comparison of the shape of grains identified at the same coordinates (location). PhotoMOB allows identification of coincident grains (immobile) and new grains (mobile). Several variables can be extracted from this categorisation, such as: the overall proportion of mobile or immobile grains (in number or surface area), the maximum mobile or immobile diameters, the proportion per individual GSF of grains that remain immobile (stable) and newly identified grains. In addition, changes in fine material cover, grain overlap can be assessed and the percentiles of the surface grain shape distribution before and after a targeted hydrological event, as well as the distribution of exclusively immobile and/or mobilised grains, can be calculated.

Automatic classification applied to perfect (manual) digitisation of grains gives mean absolute errors for fractional mobility estimation of less than 3%, while automatic classification applied to automated digitisation with 10 minutes of manual grain boundary revision gives errors of around 8%. This approach has been developed, tested and applied in gravel-bed mountain rivers affected by hydropeaking, which induces partial mobility.

 

Ackowledgements: This work is carried out in the background of the projects MorphHab PID2019-104979RB-I00 / AEI / 10.13039/501100011033) and Undammed TED2021-130815B-C31 / MCIN/AEI/10.13039/501100011033, funded by the Spanish Ministry of Science, Innovation and Universities and the EU “NextGenerationEU”/PRTR. All authors are part of the Fluvial Dynamics Research Group –RIUS, a consolidated group recognized by the Generalitat de Catalunya (2021 SGR 01114).