首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Plant source water apportionment using stable isotopes: A comparison of simple linear,two‐compartment mixing model approaches
Authors:Jaivime Evaristo  Jeffrey J McDonnell  John Clemens
Institution:1. Department of Natural Resources and Environmental Science, University of Nevada, Reno, NV, USA;2. Global Institute for Water Security;3. School of Environment and Sustainability, University of Saskatchewan, Saskatoon, Canada;4. School of Geoscience, University of Aberdeen, Aberdeen, UK;5. Christchurch Botanic Gardens, Christchurch, New Zealand
Abstract:Plant source water identification using stable isotopes is now a common practice in ecohydrological process investigations. Notwithstanding, little critical evaluation of the approaches for source apportionment have been conducted. Here, we present a critical evaluation of the main methods used for source apportionment between vadose and saturated zone water: simple mass balance and Bayesian mixing models. We leverage new isotope stem water samples from a diverse set of tree species in a strikingly uniform terrain and soil conditions at the Christchurch Botanic Garden, New Zealand. Our results show that using δ2H alone in a simple, two‐source mass balance approach leads to erroneous results, particularly an apparent overestimation of groundwater contribution to xylem. Alternatively, using both δ2H and δ18O in a Bayesian inference framework improves the source water estimates and is more useful than the simple mass balance approach, particularly when soil and groundwater contributions are relatively disproportionate. We suggest that plant source water quantification methods should take into consideration the possible effects of 2H/1H fractionation. The Bayesian inference approach used here may be less sensitive to 2H/1H fractionation effects than simple mass balance methods.
Keywords:Bayesian inference  hydrogen isotope fractionation  mixing model  plant source water  water stable isotopes
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号