干旱区研究

Arid Zone Research >

2024 , Vol. 41 >Issue 11: 1808 - 1818

DOI: https://doi.org/10.13866/j.azr.2024.11.02

Weather and Climate

Changes in atmospheric vapor pressure deficit in the Kaidu-Kongque River Basin and its influencing factors

  • LI Xiaoqi ,
  • LI Moyan ,
  • LI Jiahui ,
  • YAO Junqiang ,
  • XU Xingbin
Expand
  • 1. School of Geographic Science and Tourism, Xinjiang Normal University, Urumqi 830054, Xinjiang, China
    2. Xinjiang Key Laboratory of Lakes Environment and Resources in Arid Zone, Urumqi 830054, Xinjiang, China
    3. Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, Xinjiang, China

Received date: 2024-06-20

  Revised date: 2024-08-01

  Online published: 2024-11-29

Fold

Abstract

In this study, we analyzed meteorological observation data from the Kaidu-Kongque River basin in Xinjiang between 1961 and 2021 to investigate trends of vapor pressure deficit (VPD), as well as saturated (es) and actual (ea) water vapor pressure. We explored VPD changes across mountainous, oasis, and desert environments along with the factors influencing these changes. The results revealed the following: (1) Annual and seasonal VPD showed an upward trend from 1961 to 2021, characterized by distinct phases in which a sudden change occurred in 1997, shifting from a downward trend from 1961 to 1996 to an upward trend from 1997 to 2021, highlighting an intensification of atmospheric drought post 1997, particularly in spring. (2) VPD trends align with those of temperature and ea, showing the most significant increase in desert environments, followed by oasis and mountainous environments. (3) VPD changes are primarily affected by ea and es, positively correlated with temperature changes and negatively correlated with Relative Humidity changes. The rapid rise in temperature and decline in RH since 1997 are the primary causes of accelerated VPD, with the growth rate of ea being lower than that of es. These findings enhance our understanding of atmospheric drought and its response to climate change.

Key words： VPD; actual water vapor pressure; variation characteristics; influencing factors; Kaidu-Kongque River

Cite this article

LI Xiaoqi , LI Moyan , LI Jiahui , YAO Junqiang , XU Xingbin . Changes in atmospheric vapor pressure deficit in the Kaidu-Kongque River Basin and its influencing factors[J]. Arid Zone Research, 2024 , 41(11) : 1808 -1818 . DOI: 10.13866/j.azr.2024.11.02

References

[1] Balliu A, Zheng Y, Sallaku G, et al. Environmental and cultivation factors affect the morphology, architecture and performance of root systems in soilless grown plants[J]. Horticulturae, 2021, 7(8): 243.
[2] Zhong Z, He B, Wang Y P, et al. Disentangling the effects of vapor pressure deficit on northern terrestrial vegetation productivity[J]. Science Advances, 2023, 9(32): eadf3166.
[3] 赵卉忱, 贾根锁, 王鹤松, 等. 中国半干旱区草甸草原和典型草原碳通量日变化特征[J]. 气候与环境研究, 2020, 25(2): 172-184.
  [Zhao Huichen, Jia Gensuo, Wang Hesong, et al. Diurnal variations of the carbon fluxes of semiarid meadow steppe and typical steppe in China[J]. Climatic and Environmental Research, 2020, 25(2): 172-184. ]
[4] Yuan W, Zheng Y, Piao S, et al. Increased atmospheric vapor pressure deficit reduces global vegetation growth[J]. Science Advances, 2019, 5(8): eaax1396.
[5] Lobell D B, Hammer G L, McLean G, et al. The critical role of extreme heat for maize production in the United States[J]. Nature Climate Change, 2013, 3(5): 497-501.
[6] Novick K A, Ficklin D L, Stoy P C, et al. The increasing importance of atmospheric demand for ecosystem water and carbon fluxes[J]. Nature Climate Change, 2016, 6(11): 1023-1027.
[7] 李晓菲, 徐长春, 李路, 等. 21世纪开都-孔雀河流域未来气候变化情景预估[J]. 干旱区研究, 2019, 36(3): 556-566.
  [Li Xiaofei, Xu Changchun, Li Lu, et al. Projection of future climate change in the Kaidu-Kongqi River Basin in the 21st Century[J]. Arid Zone Research, 2019, 36(3): 556-566. ]
[8] IPCC. Climate Change 2022: Impacts, Adaptation and Vulnerability[M]. Cambridge: Cambridge University Press, 2022: 3056.
[9] IPCC. Climate Change 2023: Synthesis Report[M]. Cambridge: Cambridge University Press, 2023: 1-36.
[10] Zhang H, Wu B, Yan N, et al. An improved satellite-based approach for estimating vapor pressure deficit from MODIS data[J]. Journal of Geophysical Research: Atmospheres, 2014, 119(21): 212-256.
[11] Dai A. Increasing drought under global warming in observations and models[J]. Nature Climate Change, 2013, 3(1): 52-58.
[12] 李旭谱, 张福平, 胡猛, 等. 基于SPOT NDVI的植被覆盖时空演变规律分析——以西北五省为例[J]. 干旱地区农业研究, 2012, 35(5): 180-184, 199.
  [Li Xupu, Zhang Fuping, Hu Meng, et al. Analysis of the regulation of spatial-temporal variation of the vegetation coverage based on SPOT NDVI data—A case study in Northwest China[J]. Agricultural Research in the Arid Areas, 2012, 35(5): 180-184, 199. ]
[13] 董翰林, 王文婷, 谢云, 等. 新疆气候干湿变化特征及其影响因素[J]. 干旱区研究, 2023, 40(12): 1875-1884.
  [Dong Hanlin, Wang Wenting, Xie Yun, et al. Climate dry-wet conditions,changes, and their driving factors in Xinjiang[J]. Arid Zone Research, 2023, 40(12): 1875-1884. ]
[14] 虞佳陆, 张景, 张敏, 等. 基于标准化前期降水蒸散指数的新疆干旱时空演变特征[J]. 干旱地区农业研究, 2023, 41(4): 275-288.
  [Yu Jialu, Zhang Jing, Zhang Min, et al. SAPEI—Based spatial and temporal variation characteristics of drought in Xinjiang[J]. Agricultural Research in the Arid Areas, 2023, 41(4): 275-288. ]
[15] 潘银妹, 戴雪荣, 毛东雷. 新疆开都河-孔雀河流域近59年极端气候事件时空变化特征[J]. 湖北农业科学, 2022, 61(15): 42-49,74.
  [Pan Yinmei, Dai Xuerong, Mao Donglei. Characteristics of spatial and temporal changes of extreme climate events in the Kaidou River-Kongque River Basin in Xinjiang in recent 59 years[J]. Hubei Agricultural Sciences, 2022, 61(15): 42-49, 74. ]
[16] 石光義. 基于SWAT模型的新疆开都-孔雀河流域径流时空变化研究[D]. 长春: 长春工程学院, 2020.
  [Shi Guangyi. Study on Runoff Spatiotemporal Variation of Xinjiang Kaidu-Kongqi River Basin Based on SWAT Model[D]. Changchun: Changchun Institute of Technology, 2020. ]
[17] Allen R G, Pereira L S, Raes D, et al. FAO Irrigation and drainage paper No. 56[J]. Rome: Food and Agriculture Organization of the United Nations, 1998, 56(97): e156.
[18] Aguilar E, Peterson T, Obando P R, et al. Changes in precipitation and temperature extremes in Central America and northern South America, 1961-2003[J]. Journal of Geophysical Research: Atmospheres, 2005, 110(D23): 1-15.
[19] Jaeckel L A. Estimating regression coefficients by minimizing the dispersion of the residuals[J]. The Annals of Mathematical Statistics, 1972, 43(5): 1449-1458.
[20] Wang H, Chen Y, Chen Z. Spatial distribution and temporal trends of mean precipitation and extremes in the arid region, Northwest of China, during 1960-2010[J]. Hydrological Processes, 2013, 27(2): 1807-1818.
[21] Dodge Y. The Concise Encyclopedia of Statistics[M]. New York: Springer, 2008.
[22] Fang S, Yan J, Che M, et al. Climate change and the ecological responses in Xinjiang, China: Model simulations and data analyses[J]. Quaternary International, 2013, 311: 108-116.
[23] Li B, Chen Y, Shi X, et al. Temperature and precipitation changes in different environments in the arid region of Northwest China[J]. Theoretical and Applied Climatology, 2013, 112(3-4): 589-596.
[24] Yao J, Chen Y, Yang Q. Spatial and temporal variability of water vapor pressure in the arid region of Northwest China, during 1961-2011[J]. Theoretical and Applied Climatology, 2016, 123: 683-691.
[25] Li M, Yao J, Guan J, et al. Observed changes in vapor pressure deficit suggest a systematic drying of the atmosphere in Xinjiang of China[J]. Atmospheric Research, 2021, 248: 105199.
[26] 韩永贵, 韩磊, 黄晓宇, 等. 基于指数平滑和ARIMA模型的西北地区饱和水汽压差预测[J]. 干旱区研究, 2021, 38(2): 303-313.
  [Han Yongui, Han Lei, Huang Xiaoyu, et al. Prediction of vapor pressure deficit in Northwest China based on exponential and ARIMA models[J]. Arid Zone Research, 2021, 38(2): 303-313. ]
[27] 李素雲, 祁栋林, 温婷婷, 等. 1961—2020年青海省饱和水汽压差变化特征及影响因子分析[J]. 干旱区研究, 2023, 40(2): 173-181.
  [Li Suyun, Qi Donglin, Wen Tingting, et al. The variation characteristics and influencing factors of vapor pressure deficit in Qinghai Province from 1961 to 2020[J]. Arid Zone Research, 2023, 40(2): 173-181. ]
[28] Simmons A, Willett K, Jones P, et al. Low-frequency variations in surface atmospheric humidity, temperature, and precipitation: Inferences from reanalyses and monthly gridded observational data sets[J]. Journal of Geophysical Research: Atmospheres, 2010, 115(D1): 1-21.
[29] Willett K, Dunn R, Thorne P, et al. HadISDH land surface multi-variable humidity and temperature record for climate monitoring[J]. Climate of the Past, 2014, 10(6): 1983-2006.
[30] Rawson H, Begg J, Woodward R. The effect of atmospheric humidity on photosynthesis, transpiration and water use efficiency of leaves of several plant species[J]. Planta, 1977, 134: 5-10.
[31] 於嘉禾, 王卫光, 陈泽峰. 全球旱地饱和水汽压差和根区土壤水分变化对植被生产力的影响及其成因[J]. 生态学报, 2024, 44(11): 4808-4819.
  [Yu Jiahe, Wang Weiguang, Chen Zefeng. Influences of vapor pressure deficit and root-zone soil moisture changes on vegetation productivity and its causes across global drylands[J]. Acta Ecologica Sinica, 2024, 44(11): 4808-4819. ]
[32] Yao J, Zhao Y, Chen Y, et al. Multi-scale assessments of droughts: A case study in Xinjiang, China[J]. Science of the Total Environment, 2018, 630: 444-452.
[33] Chen Y, Li Z, Fan Y, et al. Progress and prospects of climate change impacts on hydrology in the arid region of Northwest China[J]. Environmental Research, 2015, 139: 11-19.
Options
Outlines

/

〈 〉