R
Rens Masselink
Researcher at Wageningen University and Research Centre
Publications - 21
Citations - 912
Rens Masselink is an academic researcher from Wageningen University and Research Centre. The author has contributed to research in topics: Sediment & Surface runoff. The author has an hindex of 13, co-authored 21 publications receiving 739 citations.
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Journal ArticleDOI
The way forward: Can connectivity be useful to design better measuring and modelling schemes for water and sediment dynamics?
Saskia Keesstra,Saskia Keesstra,João Osvaldo Rodrigues Nunes,João Osvaldo Rodrigues Nunes,Patricia M. Saco,Tony Parsons,Ronald E. Poeppl,Rens Masselink,Artemi Cerdà +8 more
TL;DR: A short review of the State-of-the-Art of the connectivity concept is provided, from which it is concluded that scientists have been struggling to find a way to quantify connectivity so far.
Journal ArticleDOI
Linking landscape morphological complexity and sediment connectivity
TL;DR: In this paper, the authors explored sediment connectivity in response to sequences of rainfall events and found that feedback between erosion and deposition are more important for certain landscape morphologies than for others: rolling or V-shaped catchments than from dissected or stepped landscapes.
Journal ArticleDOI
Connectivity and complex systems: learning from a multi-disciplinary perspective
Laura Turnbull,Marc-Thorsten Hütt,Andreas A. Ioannides,Stuart Kininmonth,Ronald E. Poeppl,Klement Tockner,Klement Tockner,Louise J. Bracken,Saskia Keesstra,Lichan Liu,Rens Masselink,Anthony J. Parsons +11 more
TL;DR: This review evaluates how a connectivity-based approach has generated new understanding of structural-functional relationships that characterise complex systems and proposes a ‘common toolbox’ underpinned by network-based approaches that can advance connectivity studies by overcoming existing constraints.
Journal ArticleDOI
Modelling Discharge and Sediment Yield at Catchment Scale Using Connectivity Components
TL;DR: In this article, the authors used existing data to assess governing factors of connectivity, and how these change over time, using a linear model for discharge and suspended-sediment yield.
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Assessing hillslope-channel connectivity in an agricultural catchment using rare-earth oxide tracers and random forests models
TL;DR: In this paper, two contrasting conceptual models for sediment connectivity were assessed using a Random Forest (RF) machine learning method using a 15-year period of measured sediment output at the catchment scale, and the results showed that low intensity events do not contribute any sediment from the hillslopes to the channel in the Latxaga catchment.