Estimating Components Of Forest Evapotranspiration: A Footprint Approach For Scaling Sap Flux Measurements

  • Sites: US-Dk3
  • Oishi, A. C., Oren, R., Stoy, P. C. (2008) Estimating Components Of Forest Evapotranspiration: A Footprint Approach For Scaling Sap Flux Measurements, Agricultural And Forest Meteorology, 148(11), 1719-1732.
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  • Forest evapotranspiration (ET) estimates that include scaled sap flux measurements often underestimate eddy covariance (EC)-measured latent heat flux (LE). We investigated potential causes for this bias using 4 years of coupled sap flux and LE measurements from a mature oak-hickory forest in North Carolina, USA. We focused on accuracy in sap flux estimates from heat dissipation probes by investigating nocturnal water uptake, radial pattern in flux rates, and sensor-to-stand scaling. We also produced empirical functions describing canopy interception losses (measured as the difference between precipitation and throughfall) and soil evaporation (based on wintertime eddy covariance fluxes minus wintertime water losses through bark), and added these components to the scaled sap flux to estimate stand evapotranspiration (ETS). We show that scaling based on areas in which the leaf area index of predominant species deviates from that of the EC footprint can lead to either higher or lower estimate of ETS than LE (i.e. there is no bias). We found that accounting for nocturnal water uptake increased the estimate of growing season transpiration by an average of 22%, with inter-annual standard deviation of 4%. Annual ETS estimate that included sap flux corrected for nocturnal flux and scaled to the EC footprint were similar to LE estimates (633 ± 26 versus 604 ± 19 mm, respectively). At monthly or shorter time scales, ETS was higher than LE at periods of low flux, similar at periods of moderate flux, and lower at periods of high flux, indicating potential shortcomings of both methods. Nevertheless, this study demonstrates that accounting for the effects of nocturnal flux on the baseline signal was essential for eliminating much of the bias between EC-based and component-based estimates of ET, but the agreement between these estimates is greatly affected by the scaling procedure.