Abstract
Abstract. The polar regions experience widespread transformations, such that efficient methods are needed to monitor and understand Arctic landscape changes in response to climate warming and low-frequency, high-magnitude hydrological and geomorphological events. One example of such events, capable of causing serious landscape changes, is glacier lake outburst floods. On 6 August 2017, a flood event related to glacial lake outburst affected the Zackenberg River (NE Greenland). Here, we provided a very-high-resolution dataset representing unique time series of data captured immediately before (5 August 2017), during (6 August 2017), and after (8 August 2017) the flood. Our dataset covers a 2.1 km long distal section of the Zackenberg River. The available files comprise (1) unprocessed images captured using an unmanned aerial vehicle (UAV; https://doi.org/10.5281/zenodo.4495282, Tomczyk and Ewertowski, 2021a) and (2) results of structure-from-motion (SfM) processing (orthomosaics, digital elevation models, and hillshade models in a raster format), uncertainty assessments (precision maps), and effects of geomorphological mapping in vector formats (https://doi.org/10.5281/zenodo.4498296, Tomczyk and Ewertowski, 2021b). Potential applications of the presented dataset include (1) assessment and quantification of landscape changes as an immediate result of a glacier lake outburst flood; (2) long-term monitoring of high-Arctic river valley development (in conjunction with other datasets); (3) establishing a baseline for quantification of geomorphological impacts of future glacier lake outburst floods; (4) assessment of geohazards related to bank erosion and debris flow development (hazards for research station infrastructure – station buildings and bridge); (5) monitoring of permafrost degradation; and (6) modelling flood impacts on river ecosystem, transport capacity, and channel stability.
Highlights
Long-term evolution of river system is the effect of an interplay between “normal” processes and “extreme” processes
One of the critical issues in fluvial geomorphology is the quantification of geomorphological effects caused by both groups of processes that affect river channel morphology and functioning
Among the most severe flood-related extreme events are glacier lake outburst floods (GLOFs), usually related to a sudden release of water stored in ice-dammed or morainedammed lakes and frequent in modern glacierised mountain areas (Russell et al, 2007; Moore et al, 2009; Iribarren et al, 2015; Harrison et al, 2018; Nie et al, 2018; Carrivick and Tweed, 2019)
Summary
Long-term evolution of river system is the effect of an interplay between “normal” processes (i.e. low-magnitude, highfrequency geomorphological work) and “extreme” processes (i.e. high-magnitude, low-frequency events) (see Death et al, 2015; Garcia-Castellanos and O’Connor, 2018). The frequency of GLOFs in Greenland varies from annual to decadal (e.g. Zackenberg River, Russell Glacier, Lake Tininnilik) to one-time events (e.g. Kuannersuit Glacier) (Furuya and Wahr, 2005; Russell et al, 2011; Carrivick and Tweed, 2019; Yde et al, 2019). On 6 August 2017, a flood event related to a glacier lake outburst affected the Zackenberg River (NE Greenland), leaving behind substantial geomorphological impacts on the riverbanks and channel morphology (see Tomczyk et al, 2020). Potential applications of the presented dataset include (1) assessment and quantification of landscape changes as an immediate result of glacier lake outburst flood (Tomczyk and Ewertowski, 2020; Tomczyk et al, 2020); (2) long-term monitoring of high-Arctic river valley development (in conjunction with other datasets); (3) establishing a baseline for quantification of geomorphological impacts of future glacier lake outburst floods; (4) assessment of geohazards related to bank erosion and debris flow development (hazards for research station infrastructure – station buildings and bridge); (5) monitoring of permafrost degradation; and (6) modelling flood impacts on river ecosystem, transport capacity, and channel stability
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