Synchronized high-resolution bed-level change and biophysical data from 10 marsh-mudflat sites in northwestern Europe

Zhan Hu, Pim W.J.M. Willemsen, Bas W. Borsje, Chen Wang, Heng Wang*, Daphne Van Der Wal, Zhenchang Zhu, Vincent Vuik, Tjeerd J. Bouma, More Authors

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)
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Abstract

Tidal flats provide valuable ecosystem services such as flood protection and carbon sequestration. Erosion and accretion processes govern the ecogeomorphic evolution of intertidal ecosystems (marshes and bare flats) and, hence, substantially affect their valuable ecosystem services. To understand the intertidal ecosystem development, high-frequency bed-level change data are thus needed. However, such datasets are scarce due to the lack of suitable methods that do not involve excessive labour and/or costly instruments. By applying newly developed surface elevation dynamics (SED) sensors, we obtained unique high-resolution daily bed-level change datasets in the period 2013-2017 from 10 marsh-mudflat sites situated in the Netherlands, Belgium, and the United Kingdom in contrasting physical and biological settings. At each site, multiple sensors were deployed for 9-20 months to ensure sufficient spatial and temporal coverage of highly variable bed-level change processes. The bed-level change data are provided with synchronized hydrodynamic data, i.e. water level, wave height, tidal current velocity, medium sediment grain size (D50), and chlorophyll a level at four sites. This dataset has revealed diverse spatial morphodynamics patterns over daily to seasonal scales, which are valuable to theoretical and model development. On the daily scale, this dataset is particularly instructive, as it includes a number of storm events, the response to which can be detected in the bed-level change observations. Such data are rare but useful to study tidal flat response to highly energetic conditions. The dataset is available from 4TU.ResearchData (https://doi.org/10.4121/12693254.v4; Hu et al., 2020), which is expected to expand with additional SED sensor data from ongoing and planned surveys.

Original languageEnglish
Article number22
Pages (from-to)405-416
Number of pages12
JournalEarth System Science Data
Volume13
Issue number2
DOIs
Publication statusPublished - 2021

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