Geostatistical mapping and spatial variability of surficial sediment types on the Beaufort Shelf based on grain size data.

The paper describes an approach for a quality controlled mapping of grain sizes and sediment textures for the Beaufort Shelf in the Canadian Arctic. The approach is based on grain size data collected during The Nahidik Program (2005-2009) and earlier. A replenishment of grain size data since the 198...

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Bibliographic Details
Published in:Journal of Marine Systems
Main Author: Jerosch, Kerstin
Format: Article in Journal/Newspaper
Language:unknown
Published: ELSEVIER SCIENCE BV 2013
Subjects:
Online Access:https://epic.awi.de/id/eprint/25880/
https://epic.awi.de/id/eprint/25880/1/Jerosch2013_Journal_of_Marine_Systems_Sediments_BeaufortSea.pdf
https://hdl.handle.net/10013/epic.39573
https://hdl.handle.net/10013/epic.39573.d001
Description
Summary:The paper describes an approach for a quality controlled mapping of grain sizes and sediment textures for the Beaufort Shelf in the Canadian Arctic. The approach is based on grain size data collected during The Nahidik Program (2005-2009) and earlier. A replenishment of grain size data since the 1980’s, as well as the consideration of correlating parameters (bathymetry, slope and sediment input) to a cokriging algorithm, amends the former way of mapping the surficial sediments of the Beaufort Shelf. The cokriging analysis showed that the simulation of a sediment input by the Mackenzie River, modeled as a cost-distance function, was the key variable in reducing the errors of the output estimate. Furthermore, the approach compares the geostatistical interpolation methods of ordinary kriging and cokriging and recommends the use of a combination of both. The predicted mean standard errors showed that in this study cokriging was the superior interpolation method for clay, silt and sand while ordinary kriging was more suitable for gravel. A new sediment texture map, based on the grain size maps, is provided according to commonly used grain size and sediment type classification systems