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A network theory approach for a better understanding of overland flow connectivity
Authors:Rens J H Masselink  Tobias Heckmann  Arnaud J A M Temme  Niels S Anders  Harm P A Gooren  Saskia D Keesstra
Institution:1. Soil Physics and Land Management, Environmental Sciences Group, Wageningen University, Wageningen, The Netherlands;2. Physical Geography, Catholic University of Eichst?tt‐Ingolstadt, Eichst?tt, Germany;3. Soil Geography and Landscape Group, Environmental Sciences Group, Wageningen University, Wageningen, The Netherlands;4. Institute for Biodiversity and Ecosystem Dynamics (IBED), Computational Geo‐Ecology, University of Amsterdam, Amsterdam, The Netherlands
Abstract:Hydrological connectivity describes the physical coupling (linkages) of different elements within a landscape regarding (sub‐) surface flows. A firm understanding of hydrological connectivity is important for catchment management applications, for example, habitat and species protection, and for flood resistance and resilience improvement. Thinking about (geomorphological) systems as networks can lead to new insights, which has also been recognized within the scientific community, seeing the recent increase in the use of network (graph) theory within the geosciences. Network theory supports the analysis and understanding of complex systems by providing data structures for modelling objects and their linkages, and a versatile toolbox to quantitatively appraise network structure and properties. The objective of this study was to characterize and quantify overland flow connectivity dynamics on hillslopes in a humid sub‐Mediterranean environment by using a combination of high‐resolution digital‐terrain models, overland flow sensors and a network approach. Results showed that there are significant differences between overland flow connectivity on agricultural areas and semi‐natural shrubs areas. Significant positive correlations between connectivity and precipitation characteristics were found. Significant negative correlations between connectivity and soil moisture were found, most likely because of soil water repellency and/or soil surface crusting. The combination of structural networks and dynamic networks for determining potential connectivity and actual connectivity proved a powerful tool for analysing overland flow connectivity. Copyright © 2016 John Wiley & Sons, Ltd.
Keywords:connectivity  overland flow  graph theory  networks  Spain
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