Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 505414
Title Using a new conceptual framework to assess sediment conncetivity
Author(s) Masselink, R.J.H.; Keesstra, S.D.; Temme, A.J.A.M.; Giménez, R.; Casali, J.; Seeger, K.M.
Source Geophysical Research Abstracts 17 (2015). - ISSN 1029-7006 - 1 p.
Event EGU General Assembly 2015, Vienna, 2015-04-12/2015-04-17
Department(s) Soil Physics and Land Management
Soil Geography and Landscape
Publication type Abstract in scientific journal or proceedings
Publication year 2015
Abstract During recent years many conceptual frameworks for hydrological and sediment connectivity have been developed.
Most of these studies however, did not take the measuring or inferring of connectivity into account in the
development of their frameworks, which is why studies on measuring connectivity have stayed behind. In this
paper a new framework is proposed which promotes measurements of connectivity. The basis of the framework
are three subcomponents of connectivity: Geomorphological, Biological and Soil. These can be combined into a
single connectivity metric and combined with measurements of sediment transport distances and/or yield. The new
framework is applied and tested in three catchments in N-Spain, where a simple model for catchment sediment
yield was developed and tested. Results for sediment yield predictions were relatively poor with R2 between 0.24-
0.41, although for water discharge better results were obtained with R2 varying between 0.53-0.77. The next step is
to apply the framework at smaller scales to include spatial variability of e.g. landforms and vegetation and achieve
better results, not only for predicting yields but also for an assessment of sources and pathways.
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