Quantifying moisture recycling of a leeward oasis in arid central Asia using a Bayesian isotopic mixing model
No Thumbnail Available
Date
2022-10
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
Locally recycled moisture from transpiration and surface evaporation is of great importance in the terrestrial hydrological cycle, especially in the widely distributed oases across arid central Asia. Quantitative assessment of the proportional contribution of recycled moisture to local precipitation, i.e., the recycling ratio, is useful to understand the land-air interaction as well as the anthropogenic impact on the regional water cycle. Here we analyzed the stable hydrogen and oxygen isotopes in precipitation samples collected at six stations across the Kaxgar-Yarkant Oasis in the western Tarim Basin of central Asia from April 2018 to June 2020. Using this data, the moisture recycling ratio in this typical oasis was assessed using a Bayesian three-component isotopic mixing model. For the plain stations, the annual weighted mean δ18O value in precipitation ranged from −5.94 ‰ to −1.46 ‰, and the mountain station has a lower annual mean precipitation isotopic ratio. The average recycling ratio during the summer months ranged between 17.0 % and 63.9 % for each sampling station in the Kaxgar-Yarkant Oasis, and the proportional contribution from transpiration ranged from 15.1 % to 61.3 %. The contribution of plant transpiration to local precipitation is much larger than that of surface evaporation. The recycled portion in total precipitation amount may increase the local precipitation under an oasis expansion background but is insufficient to change the arid background. In addition, the Bayesian isotopic mixing model is promising to determine the recycling ratio in an arid setting, and provides more spatial details than the climate reanalysis-based calculation. © 2022 Elsevier B.V.
Description
Keywords
Moisture, Arid Lands, Asia, Bayesian statistics, Evaporation, Precipitation, Data
Citation
Wang, S., Wang, L., Zhang, M., Shi, Y., Hughes, C. E., Crawford, J., Zhou, J., & Qu, D. (2022). Quantifying moisture recycling of a leeward oasis in arid central Asia using a Bayesian isotopic mixing model. Journal of Hydrology, 613, 128459. doi:10.1016/j.jhydrol.2022.128459