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Hydrological Processes
Article . 2008 . Peer-reviewed
License: Wiley Online Library User Agreement
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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Connectivity as a concept for characterising hydrological behaviour

Authors: Michaelides, K; Chappell, A.;

Connectivity as a concept for characterising hydrological behaviour

Abstract

Received 27 October 2008 Accepted 27 October 2008 Introduction In recent years, an increasing number of studies have referred to the concept of ‘connectivity’ in an attempt to explain hydrological (Western et al., 2001), geomorphological (Brierly et al., 2006) and ecological (Pringle, 2003) systems. There has been particular discussion surrounding hydrological connectivity as the key driver for many other catchment processes such as nutrient transfers (e.g., Stieglitz et al., 2003), sediment transfers (e.g., Fryirs et al., 2007) and biological processes (e.g., Amoros and Bornette, 2002) at different time and space scales. This increasing interest in understanding, representing and quantifying connectivity and its effect on processes is demonstrated by the recent sessions at International conferences where connectivity is rapidly becoming a theme that transcends different disciplines. At the 2007 European Geosciences Union alone, connectivity was the main focus of at least six different and unrelated sessions and was discussed in different contexts and across a range of scales. The term ‘connectivity’ suffers from a degree of ambiguity because it is both an everyday word and a technical term. Consequently, it can be used quite loosely and it can escape stringent definition. As a result, connectivity is referred to widely in the hydrological literature, often in wildly contrasting ways ranging from general descriptive discussions to specific quantifications of process and everything in between. No matter the use, all work involving connectivity has one thing in common—the increasing widespread acknowledgement that connectivity is important (qualitatively at least) for understanding processes and system behaviour. In its most general sense, the term intuitively implies that there can be varying states of connectedness in landscape properties and these can affect certain processes. For example, if areas of low surface infiltration rate become physically close, they will connect and may lead to enhanced surface runoff (Michaelides and Wilson, 2007). Similarly, if flow pathways on a floodplain connect over a wide area, they may affect the diversity of some species of fish. Recent publications demonstrate that connectivity means different things to workers between (e.g., Pringle, 2003; Ocampo et al., 2006; Bracken and Croke, 2007; Tetzlaff et al., 2007) and within (e.g., in hydrology: Buttle et al., 2004; Todd et al., 2006; Lehmann et al., 2007; Maneta et al., 2008) different disciplines. Despite the term being widely recognised as qualitatively important, there is a lack of an agreed, quantitative definition of the concept. There is a lack of a useful, applicable methodological framework for quantifying and using connectivity. Existing proposed frameworks are often too vague or too specific for wider hydrological and other applications (e.g., Hooke, 2003; Bracken and Croke, 2007). In this commentary, we discuss the importance and meaning of connectivity and advocate the use of geostatistical connectivity to provide a methodological framework within a hydrological context (e.g., Western et al., 2001). We propose that geostatistical connectivity be adopted as a simplified, universally applicable, quantifiable measure of hydrological behaviour that transcends individual complexities in hydrological response.

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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
87
Top 10%
Top 10%
Top 10%
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