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Toward capturing hydrologically significant connectivity in spatial patterns
Author(s) -
Western Andrew W.,
Blöschl Günter,
Grayson Rodger B.
Publication year - 2001
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2000wr900241
Subject(s) - geostatistics , spatial ecology , spatial variability , hydrological modelling , scale (ratio) , surface runoff , hydraulic conductivity , aquifer , hydrology (agriculture) , environmental science , computer science , groundwater , soil science , geology , mathematics , cartography , geography , statistics , ecology , soil water , geotechnical engineering , climatology , biology
Many spatial fields exhibit connectivity features that have an important influence on hydrologic behavior. Examples include high‐conductivity preferred flow paths in aquifers and saturated source areas in drainage lines. Connected features can be considered as arbitrarily shaped bands or pathways of connected pixels having similar (e.g., high) values. Connectivity is a property that is not captured by standard geostatistical approaches, which assume that spatial variation occurs in the most random possible way that is consistent with the spatial correlation, nor is it captured by indicator geostatistics. An alternative approach is to use connectivity functions. In this paper we apply connectivity functions to 13 observed soil moisture patterns from the Tarrawarra catchment and two synthetic aquifer conductivity patterns. It is shown that the connectivity functions are able to distinguish between connected and disconnected patterns. The importance of the connectivity in determining hydrologic behavior is explored using rainfall‐runoff simulations and groundwater transport simulations. We propose the integral connectivity scale as a measure of the presence of hydrologic connectivity. Links between the connectivity functions and integral connectivity scale and simulated hydrologic behavior are demonstrated and explained from a hydrologic process perspective. Connectivity functions and the integral connectivity scale provide promising means for characterizing features that exist in observed spatial fields and that have an important influence on hydrologic behavior. Previously, this has not been possible within a statistical framework.