Threshold behavior of stormflow response is an emergent pattern observed in several studies demonstrating subsurface storage controls on catchment rainfall-runoff dynamics. These studies demonstrate a distinct transition from negligible stormflow discharge response to rapid, linearly increasing stormflow identified by a single, uniquely defined threshold as a basic catchment attribute that relates to geophysical properties. Utilizing precipitation, streamflow, and soil moisture data spanning 15 years from three catchments at the Coweeta Hydrologic Laboratory (CHL), we analyze how threshold behavior forms and varies at several timescales. We pose three hypotheses: (1) stormflow thresholds form at CHL as a function of antecedent soil moisture and gross precipitation, (2) thresholds vary seasonally and interannually, and (3) threshold variation through time implies greater long-term complexity of runoff controls beyond catchment geophysical properties, including forest canopy ecohydrologic feedbacks. We isolate threshold behavior of stormflow using piecewise regression analysis in short to long-term data sets with respect to antecedent soil moisture index and gross precipitation. We use this to investigate threshold variation over seasonal, interannual, and decadal timescales that encompass hydroclimatic extremes. Seasonal analysis reveals that thresholds are more variable between growing seasons than between dormant seasons. In growing seasons with greater water stress, stormflow thresholds are lower after controlling for soil moisture storage suggesting more complex, long-term rainfall-runoff relationships as a result of forest canopy response to water stress. We present a conceptual model of how vegetation-climate interactions influence long-term rainfall-runoff relationships creating interannual variability of stormflow thresholds and linear stormflow response.
CITATION STYLE
Scaife, C. I., & Band, L. E. (2017). Nonstationarity in threshold response of stormflow in southern Appalachian headwater catchments. Water Resources Research, 53(8), 6579–6596. https://doi.org/10.1002/2017WR020376
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