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    Author(s): Scott T. Allen; Richard F. Keim; Jeffrey J. McDonnell
    Date: 2015
    Source: Journal of Hydrology
    Publication Series: Scientific Journal (JRNL)
    Station: Pacific Northwest Research Station
    PDF: Download Publication  (790.0 KB)


    Spatial variability of throughfall isotopic composition in forests is indicative of complex processes occurring in the canopy and remains insufficiently understood to properly characterize precipitation inputs to the catchment water balance. Here we investigate variability of throughfall isotopic composition with the objectives: (1) to quantify the spatial variability in event-scale samples, (2) to determine if there are persistent controls over the variability and how these affect variability of seasonally accumulated throughfall, and (3) to analyze the distribution of measured throughfall isotopic composition associated with varying sampling regimes. We measured throughfall over two, three-month periods in western Oregon, USA under a Douglas-fir canopy. The mean spatial range of d18O for each event was 1.6‰ and 1.2‰ through Fall 2009 (11 events) and Spring 2010 (7 events), respectively. However, the spatial pattern of isotopic composition was not temporally stable causing season-total throughfall to be less variable than event throughfall (1.0‰; range of cumulative d18O for Fall 2009). Isotopic composition was not spatially autocorrelated and not explained by location relative to tree stems. Sampling error analysis for both field measurements and Monte-Carlo simulated datasets representing different sampling schemes revealed the standard deviation of differences from the true mean as high as 0.45‰ (d18O) and 1.29‰ (d-excess). The magnitude of this isotopic variation suggests that small sample sizes are a source of substantial experimental error.

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    Allen, Scott T.; Keim, Richard F.; McDonnell, Jeffrey J. 2015. Spatial patterns of throughfall isotopic composition at the event and seasonal timescales. Journal of Hydrology: 58-66.


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    Stable isotopes, Spatiotemporal variability, Sampling error, Net precipitation, Canopy interception

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