Misconception of coastal morphological resilience caused by inconsistent resolution in bathymetry mapping

Miao, B., Arlinghaus, P., Ho-Hagemann, H.T.M., Schrum, C., & Zhang, W. (2025): Misconception of coastal morphological resilience caused by inconsistent resolution in bathymetry mapping. Commun Earth Environ 6, 904. https://doi.org/10.1038/s43247-025-02974-y

We identified inconsistency in the long-term time series (1998-2022) of bathymetric data of the German Wadden Sea which produces a significant but false trend in the mean elevation change. After correcting these previously overlooked errors, we found that a majority of tidal basins (15 out of 24) in the German Wadden Sea are struggling to keep pace with sea level rise. The situation deteriorates further in the most recent decade (2010–2022), during which only 4 basins maintained sufficient elevation gain. We propose that contemporary and future coastal protection and climate adaptation measures need to be far more ambitious and extensive than previously assumed.

The analytical methods can be broadly applied to geospatial data to detect and correct errors caused by inconsistent spatial resolution between different time periods, e.g. variation of mean temperature over the past decades inferred from observation and modeling using different spatial resolutions.

Long-term time series of coastal bathymetric data are indispensable for analysing morphological resilience to climate change. Despite the increasing popularity of utilizing high-resolution digital elevation models for coastal management, potential errors in analysing the long-term trend of bed elevation change from historical datasets have attracted little attention. Here, we demonstrate that inconsistency in the spatial resolution of small-scale topographic features characterized by sharp bathymetric gradients could produce errors in the mean elevation that in individual years could exceed the sea level change rate and result in a statistically significant bias in the trend of the mean elevation. Neglecting this inconsistency may lead to a misconception of coastal resilience to sea level rise. We provide an analytical method to identify such inconsistency in bathymetric datasets and a homogenization method to minimise the errors. Our methods are broadly applicable for analysing time series of geospatial data and quantitative assessment of data consistency.