Using High-Frequency Water Vapor Isotopic Measurements as a Novel Method to Partition Daily Evapotranspiration in an Oak Woodland

• Main Authors: Christopher Adkison, Caitlyn Cooper-Norris, Rajit Patankar, Georgianne W. Moore
• Format: Article
• Language: English
• Published: MDPI AG 2020-10-01
• Series: Water
• Subjects: water stable isotopes; ecohydrology; evapotranspiration; eddy covariance; forest hydrology; National Ecological Observatory Network (NEON)
• Online Access: https://www.mdpi.com/2073-4441/12/11/2967

Partitioning evapotranspiration (<i>ET</i>) into its constituent fluxes (transpiration (<i>T</i>) and evaporation (<i>E</i>)) is important for understanding water use efficiency in forests and other ecosystems. Recent advancements in cavity ringdown spectrometers (CRDS) have made collecting high-resolution water isotope data possible in remote locations, but this technology has rarely been utilized for partitioning <i>ET</i> in forests and other natural systems. To understand how the CRDS can be integrated with more traditional techniques, we combined stable isotope, eddy covariance, and sap flux techniques to partition <i>ET</i> in an oak woodland using continuous water vapor CRDS measurements and monthly soil and twig samples processed using isotope ratio mass spectrometry (IRMS). Furthermore, we wanted to compare the efficacy of <i>δ²</i>H versus <i>δ¹⁸</i>O within the stable isotope method for partitioning <i>ET.</i> We determined that average daytime vapor pressure deficit and soil moisture could successfully predict the relative isotopic compositions of soil (<i>δ</i>_e) and xylem (<i>δ</i>_t) water, respectively. Contrary to past studies, <i>δ²</i>H and <i>δ¹⁸</i>O performed similarly, indicating CRDS can increase the utility of <i>δ¹⁸</i>O in stable isotope studies. However, we found a 41–49% overestimation of the contribution of <i>T </i>to <i>ET</i> (<i>f_T</i>) when utilizing the stable isotope technique compared to traditional techniques (reduced to 4–12% when corrected for bias), suggesting there may be a systematic bias to the Craig-Gordon Model in natural systems.