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Journal of Arid Land  2022, Vol. 14 Issue (3): 297-309    DOI: 10.1007/s40333-022-0090-0
Research article     
Identifying water vapor sources of precipitation in forest and grassland in the north slope of the Tianshan Mountains, Central Asia
CHEN Haiyan1,2,*(), CHEN Yaning3, LI Dalong1,2, LI Weihong3, YANG Yuhui4
1College of Geography and Environmental Science, Hainan Normal University, Haikou 571158, China
2Key Laboratory of Earth Surface Processes and Environmental Change of Tropical Islands, Hainan Province, Haikou 571158, China
3State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
4Xinjiang Normal University, Urumqi 830013, China
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Identifying water vapor sources in the natural vegetation of the Tianshan Mountains is of significant importance for obtaining greater knowledge about the water cycle, forecasting water resource changes, and dealing with the adverse effects of climate change. In this study, we identified water vapor sources of precipitation and evaluated their effects on precipitation stable isotopes in the north slope of the Tianshan Mountains, China. By utilizing the temporal and spatial distributions of precipitation stable isotopes in the forest and grassland regions, Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, and isotope mass balance model, we obtained the following results. (1) The Eurasia, Black Sea, and Caspian Sea are the major sources of water vapor. (2) The contribution of surface evaporation to precipitation in forests is lower than that in the grasslands (except in spring), while the contribution of plant transpiration to precipitation in forests (5.35%) is higher than that in grasslands (3.79%) in summer. (3) The underlying surface and temperature are the main factors that affect the contribution of recycled water vapor to precipitation; meanwhile, the effects of water vapor sources of precipitation on precipitation stable isotopes are counteracted by other environmental factors. Overall, this work will prove beneficial in quantifying the effect of climate change on local water cycles.

Key wordsTianshan Mountains      Manas River Basin      water vapor sources of precipitation      land cover      precipitation stable isotopes      Hybrid Single-Particle Lagrangian Integrated Trajectory     
Received: 09 October 2021      Published: 31 March 2022
Corresponding Authors: CHEN Haiyan     E-mail:
Cite this article:

CHEN Haiyan, CHEN Yaning, LI Dalong, LI Weihong, YANG Yuhui. Identifying water vapor sources of precipitation in forest and grassland in the north slope of the Tianshan Mountains, Central Asia. Journal of Arid Land, 2022, 14(3): 297-309.

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Fig. 1 (a) Schematic of the study area and hydrological stations used in the study and (b) land cover of the Manas River Basin. Land cover data are from MODIS Land Cover Products (MCD12Q1) (https://lpdaac.
Fig. 2 Spatial and temporal distributions of raw and adjust trajectories of Honggou station for each precipitation event in August 2015 to July 2016 in (a) spring, (b) summer, (c) autumn, and (d) winter. The satellite-derived land cover is downloaded from Natural Earth (
Fig. 3 Distribution of water vapor sources from different directions at Honggou station during August 2015 to July 2016. Here, the summer half year occurs from April to September, while the winter half year ranges from October to March in the next year.
Table 1 Meteorological parameters, isotopic composition of different components in the forest and grassland regions in different seasons
Study area Station Time Latitude Longitude Altitude (m) Proportion (%) Landcover Reference
fev ftr
Urumqi River Basin Urumqi April 2003-July 2004 (summer) 43°47′N 86°37′E 918 6.8-12.0 Oasis Kong et al. (2013)
Houxia 43°17′N 87°11′E 2100 0.9-1.8 Forest
Gaoshan 43°06′N 86°50′E 3545 0.0-1.0 Grassland
Northwest Tibet Plateau Chongce 1979-2012 35°14′N 81°07′E 6010 15.0-2.6 Glacier/
An et al. (2017)
Zangser Kangri 1979-2008 34°18′N 85°51′E 6226 24.7-81.6
Qinghai Lake Basin July 2009-June 2010 36°32′-
3193 23.4 Water Cui and Li (2015)
Tianshan Moutains Shehezi August 2012-September 2013 (summer) 44°59′N 86°03′E 443 0.6±1.7 2.8±3.6 Oasis Wang et al. (2016)
Caijiahu 44°12′N 87°32′E 441 1.2±1.6 6.8±3.0
Urumqi 43°47′N 87°39′E 935 6.2±1.4 12.0±2.1
Shiyang River Basin Xidahe July 2013-June 2014
(growing season)
38°06′N 101°24′E 2900 9.0 15.0 Forest Li et al. (2016)
Anyuan 37°18′N 102°54′E 2700 12.0 19.0 Bare land
Jiutiaoling 37°54′N 102°06′E 2225 10.0 16.0 Bare land
Yongchang 38°12′N 102°00′E 1976 9.0 12.0 Oasis
Wuwei 37°54′N 102°42′E 1531 8.0 13.0 Oasis
Minqin 38°36′N 103°06′E 1367 5.0 9.0 Oasis
Manas River Basin Honggou 2015-2016 (spring) 43°43′N 85°44′E 1472 3.7 0.4 Forest This study
Honggou 2015-2016 (summer) 43°43′N 85°44′E 1472 1.2 5.4 Forest This study
Honggou 2015-2016 (autumn) 43°43′N 85°44′E 1472 2.7 1.1 Forest This study
Honggou 2015-2016 (winter) 43°43′N 85°44′E 1472 0.4 0.0 Forest This study
Kensiwate 2015-2016 (spring) 43°58′N 85°57′E 860 2.5 1.7 Grassland This study
Kensiwate 2015-2016 (summer) 43°58′N 85°57′E 860 1.3 3.8 Grassland This study
Kensiwate 2015-2016 (autumn) 43°58′N 85°57′E 860 4.4 1.0 Grassland This study
Kensiwate 2015-2016 (winter) 43°58′N 85°57′E 860 0.5 0.0 Grassland This study
Table 2 Comparison of studies on recycled water vapor estimated based on stable water isotopes in Northwest China
Fig. 4 Relationship between δ18O and back tracking time of precipitation vapor (a and b) and the relationship between d-excess and back tracking time of precipitation vapor (c and d) at Honggou station from August 2015 to July 2016. (a) and (c) denote the summer half year; (b) and (d) denote the winter half year. The boxes represent the 25%-75% percentiles, and the line through the box represents the median (50th percentile). The whiskers indicate the 90th and 10th percentiles, and points above and below the whiskers indicate the 95th and 5th percentiles. Different lowercase letters in the figure indicate the significant differences among the five back tracking times (P<0.05).
Fig. 5 Relationship of moisture transport distance with δ18O (a) and d-excess (b) in precipitation
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