<p>High mountain environments have shown substantial geomorphological changes forced by rising temperatures in recent decades. As such, paraglacial transition zones in catchments with rapidly retreating glaciers and abundant sediments are key elements in high alpine river systems and promise to be revealing, yet challenging, areas of investigation for the quantification of current and future sediment transport. In this study, we explore the potential of semi-automatic image analysis to detect the extent of the inundation area and corresponding inundation frequency in a proglacial outwash plain (Jamtal valley, Austria) from terrestrial time-lapse imagery. We cumulated all available records of the inundated area from 2018-2020 and analysed the spatial and temporal patterns of flood flows. The approach presented here allows semi-automated monitoring of fundamental hydrological/hydraulic processes in an environment of scarce data. The pixel classification based on greyscale values from oblique hourly recordings returned plausible results of the spatial and temporal variability of surface runoff in the investigated glacier forefield. The image sets, processed in ImageJ, allowed geo-rectification to produce inundation frequency maps. Meteorological and discharge data from downstream measuring stations was consulted to interpret our findings. Runoff events and their intensity were quantified and attributed to either pronounced ablation, heavy precipitation, or a combination of both. We also detected an increasing degree of channel concentration within the observation period. The maximum inundation from one event alone took up 35% of the analysed area. About 10% of the observed area presented inundation in 60-70% of the analysed images. In contrast, 60-70% of the observed area was inundated in fewer than 10% of the analysed period. Despite some limitations in terms of image classification, prevailing weather conditions and illumination, the derived inundation frequency maps provide novel insights into the evolution of the proglacial channel network.</p>
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