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Shopping for hydrologically representative connectivity metrics in a humid temperate forested catchment
Author(s) -
Ali Geneviève A.,
Roy André G.
Publication year - 2010
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 - 10.1029/2010wr009442
Subject(s) - environmental science , temperate climate , surface runoff , drainage basin , hydrology (agriculture) , streamflow , temperate forest , antecedent moisture , fluvial , rangeland , structural basin , ecology , geology , runoff curve number , geography , geomorphology , cartography , agroforestry , geotechnical engineering , biology
In order for connectivity to serve as an effective diagnostic classification tool of hydrological behavior, it clearly matters (1) how it is measured and (2) whether the chosen measures are correlated not only to catchment‐scale antecedent moisture conditions but also to streamflow discharges. Previous studies have advocated that connectivity in shallow soil moisture patterns induces threshold‐like changes in runoff in temperate rangeland catchments but not in temperate humid forested catchments. We argue that in the latter environments, capturing critical spatial organization in soil moisture patterns depends on the way the chosen connectivity metric is built. We therefore tested a large selection of 2‐D and 3‐D connectivity measures in a temperate humid forested catchment (Laurentians, Canada). Computations were based on continuous soil moisture patterns collected on 16 occasions at four soil depths and then transformed into indicator patterns using either time‐variable or time‐invariant thresholds. Assessments of connectivity were variable depending on the computed metric, as just a few measures were significantly correlated with both antecedent moisture conditions and catchment discharges. In particular, topography‐based connectivity metrics reflected changes in catchment macrostate and stormflow response better than omnidirectional methods. Also, source‐to‐stream connectivity metrics were more hydrologically sensitive than metrics that did not consider the spatial linkage to the stream channel. These conclusions stress the importance of searching for the right connectivity metric for hydrologic prediction, especially in humid forested environments that exhibit much larger variability in soil hydrologic properties than temperate rangeland catchments.