Geomorphological development of aquatic mesohabitats in shore channels along longitudinal training dams

DOI

Dataset for the article 'Geomorphological development of aquatic mesohabitats in shore channels along longitudinal training dams' published in Remote Sensing in Ecology and Conservation.AbstractLongitudinal training dams (LTDs) are novel hydraulic engineering structures in the river Waal intended to facilitate intensive navigation and safe discharges in the main channel while providing sheltered habitats for aquatic biota in shore channels. Monitoring data collected using light detection and ranging (LiDAR), multibeam echosounder (MBES) and aerial photography for the years during and after to construction of the LTDs were analyzed in order to determine patterns of erosion and deposition, the retreat rate of steep eroding banks and shoreline length change through time. The LTD shore channels and two traditional groyne fields (references) were divided into nine mesohabitats based on physical attributes. Net erosion was estimated for eight out of the nine mesohabitats for the 2015-2020 period. Generally, there is a pattern of riverbed aggradation towards the LTDs and degradation or bank erosion towards the littoral zones of the LTD shore channels. This kind of continuous behavior could be indicative of current or eminent channel and thus habitat stability. The bankline erosion in shore channels had mean retreat rates of 1.4-1.6 m/yr. The shorelines were longer in sand-dominated mesohabitats, which could be key for habitat heterogeneity. The LTD shore channels offered more complex relatively natural continuous littoral zones than the traditional groyne fields while maintaining the multifunctionality of the river. Thus, the development of sandy shorelines in the LTD shore channels should be encouraged through management in order to enhance biodiversity. Geomorphological monitoring of the shore channels should continue in the future in order to detect any long-term changes in the sedimentary processes and ecological functions.For detailed methods see the Readme.txt file.

Identifier
DOI https://doi.org/10.17026/dans-xaj-ysx8
Metadata Access https://lifesciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-xaj-ysx8
Provenance
Creator N.Y. Flores; F.P.L. Collas; ROB S.E.W. Leuven
Publisher DANS Data Station Life Sciences
Contributor RU Radboud University
Publication Year 2022
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact RU Radboud University
Representation
Resource Type Dataset
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Version 2.0
Discipline Earth and Environmental Science; Environmental Research; Geosciences; Life Sciences; Medicine; Natural Sciences