Evaluation of Ability to Determine Transpiration Fraction from Stable Water Isotopes in a Bayesian Calibration Framework

Abstract:

The partitioning of total evapotranspiration between contributions from surface evaporation and plant transpiration offers acute insight into the hydrological and biogeochemical behaviors of an ecosystem, but is notoriously difficult to establish directly. Furthermore, evapotranspiration partitioning relies heavily on knowledge of the relative pathways by which water moves from the soil column to the atmosphere. These pathways are parameterized by ecosystem resistances, which may not be known with great certainty in practical situations. By leveraging the unique signatures of evaporation and transpiration on the ratios of stable water isotopes, additional constraint on the evapotranspiration partitioning may be obtained. We present evapotranspiration partitioning results for a site in central Colorado, USA, for which sufficient meteorological, hydrological and water isotopic measurements are available to run and validate an isotopically-enabled land surface model. Field observational data are coupled with a Markov chain Monte Carlo parameter calibration framework to constrain the ecosystem resistances and provide model realizations which accurately match observations. Experiments are conducted to determine the degree to which uncertainty in the evapotranspiration partitioning may be reduced by incorporating stable water isotopic information, a Bayesian model calibration approach, or both. We find that stable water isotopic information offers unique insight into ecosystem flux partitioning, and accurate partitioning relies on accurate modeling of the isotopic kinetic fractionation factor, and therefore proper accounting for the ecosystem resistances.