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Paper title Mapping flood extent and frequency from Sentinel-1 imagery during the extremely warm winter of 2020 in Boreal floodplains and forests
Authors
  1. Liis Sipelgas Tallinn University of Technology Speaker
  2. Age Aavaste Tallinn University of Technology
  3. Rivo Uiboupin Tallinn University of Technology
  4. Rivo Uiboupin Tallinn University of Technology
Form of presentation Poster
Topics
  • A7. Hydrology and Water Cycle
    • A7.01 Inland Water Storage and Runoff: Modeling, In Situ Data and Remote Sensing
Abstract text Estonia is known for its large riverside areas that are seasonally (in spring) flooded over. However, extremely warm winters in Estonia during the last five years have also caused large floodings during the winter. Changes in inundation extent, depth, and duration can change the phonological patterns, animal migration routes and affect the forest management, resulting in economic losses. Therefore, a need to assess the inter-annual variability of inundation along riverside areas has become interest from both public and private sectors.
At the European scale, two flood-monitoring services are provided: The (1) Copernicus Emergency Management Service provides a free-of-charge mapping service in cases of natural disasters, man-made emergencies, and humanitarian crises throughout the world. This service can be triggered by request in the case of an emergency. The (2) Copernicus Land Monitoring Service provides a pan-European high-resolution product, Water and Wetness. This product shows the occurrence of water and wet surfaces over the 2015-2018 period.
However, these services cannot be used for the inter-annual identification of flooded areas. Therefore, an automatic processing scheme of Sentinel-1 data was set up for the mapping of open-water flood (OWF) and flood under vegetation (FUV). The methodology was applied for water mapping from Sentinel-1 (S1) and a flood extent analysis of the three largest floodplains in Estonia in 2019/2020. The extremely mild winter of 2019/2020 resulted in several large floods at floodplains that were detected from S1 imagery with the maximal OWF extent up to 5000 ha and maximal FUV extent up to 4500 ha. A significant correlation (r2 > 0.6) between OWF extent and closest gauge data was obtained for inland riverbank floodplains. The outcome enabled us to define the critical water level at which water exceeds the shoreline and flooding starts. However, for a coastal river delta floodplain, a lower correlation (r2 < 0.34) with gauge data was obtained and the excess of river coastline could not be related to a certain water level. At inland riverbank floodplains, the extent of FUV was three times larger compared to that of OWF. The correlation between the water level and FUV was < 0.51, indicating that the river water level at these test sites can be used as a proxy for forest floods.
The analysis of the extent and frequency of wintertime floods can form the basis for various economic analyses as well as evaluations of revenue being conducted in the forest industry due to mild winters and evaluations of stress to Northern boreal alluvial meadows. Relating conventional gauge data to S1 time series contributes to the implementation of flood risk assessment and management directives in Estonia