Quantifying moisture recycling of a leeward oasis in arid central Asia using a Bayesian isotopic mixing model

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dc.contributor.authorWang, Sen_AU
dc.contributor.authorWang, Len_AU
dc.contributor.authorZhang, MJen_AU
dc.contributor.authorShi, Yen_AU
dc.contributor.authorHughes, CEen_AU
dc.contributor.authorCrawford, Jen_AU
dc.contributor.authorZhou, Jen_AU
dc.contributor.authorQu, Den_AU
dc.date.accessioned2024-02-23T04:10:43Zen_AU
dc.date.available2024-02-23T04:10:43Zen_AU
dc.date.issued2022-10en_AU
dc.date.statistics2024-02-23en_AU
dc.description.abstractLocally 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.en_AU
dc.description.sponsorshipThe authors greatly thank all the staff in Kashi Prefecture Meteorological Bureau and Kizilsu Kirgiz Autonomous Prefecture Meteorological Bureau, especially Qin Zhang and Ying Lin, for helping in sampling. Thank the colleagues in Northwest Normal University for sample collection and lab analyzing, including Mengyu Shi, Rong Jiao, Yufeng Li, Yijie Xia, Lihong Duan and Shijun Lei. Thank Yanyan Zeng for compiling the stable isotope data of groundwater. The research is supported by the National Natural Science Foundation of China (No. 41971034 and 41701028), the Foundation for Distinguished Young Scholars of Gansu Province (20JR10RA112) and the Northwest Normal University (NWNU-LKZD2021-04).en_AU
dc.identifier.articlenumber128459en_AU
dc.identifier.citationWang, 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.2022.128459en_AU
dc.identifier.issn0022-1694en_AU
dc.identifier.journaltitleJournal of Hydrologyen_AU
dc.identifier.pagination128459-en_AU
dc.identifier.urihttp://dx.doi.org/10.1016/j.jhydrol.2022.128459en_AU
dc.identifier.urihttps://apo.ansto.gov.au/handle/10238/15424en_AU
dc.identifier.volume613en_AU
dc.languageEnglishen_AU
dc.language.isoenen_AU
dc.publisherElsevieren_AU
dc.subjectMoistureen_AU
dc.subjectArid Landsen_AU
dc.subjectAsiaen_AU
dc.subjectBayesian statisticsen_AU
dc.subjectEvaporationen_AU
dc.subjectPrecipitationen_AU
dc.subjectDataen_AU
dc.titleQuantifying moisture recycling of a leeward oasis in arid central Asia using a Bayesian isotopic mixing modelen_AU
dc.typeJournal Articleen_AU
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