Investigating the Effect of Climate Change on Drought Propagation in the Tarim River Basin Using Multi-Model Ensemble Projections

被引:2
|
作者
Ding, Xiaoyun [1 ,2 ]
Yu, Yang [1 ,2 ]
Yang, Meilin [1 ]
Wang, Qian [1 ]
Zhang, Lingyun [1 ,2 ]
Guo, Zengkun [1 ,2 ]
Zhang, Jing [1 ,2 ]
Mailik, Ireneusz [1 ,3 ]
Malgorzata, Wistuba [1 ,3 ]
Yu, Ruide [1 ,2 ]
Bonacci, Ognjen
机构
[1] Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Key Lab Ecol Safety & Sustainable Dev Arid Lands, Urumqi 830011, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Univ Silesia Katowice, Fac Earth Sci, PL-41200 Sosnowiec, Poland
关键词
drought propagation; SPEI; SRI; STI; CMIP6; conditional probability; WATER-RESOURCES; IMPACT; INDEX; ASIA;
D O I
10.3390/atmos15010050
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Recent studies on China's arid and semi-arid regions, particularly the Tarim River Basin (TRB), have shown an increase in the intensity and frequency of extreme weather events. This research examines the link between meteorological droughts, as measured by the Standardized Precipitation Evapotranspiration Index (SPEI), and hydrological droughts, as indicated by the Standardized Runoff Index (SRI) and the Standardized Terrestrial Water Storage Index (STI), over various time scales. Historical data indicate that SPEI drought frequency (DF) was 14.3-21.9%, with prevalent events in the northern oases. SRI DF ranged from 9.0% to 35.8%, concentrated around the Taklamakan and Kumtag Deserts, while STI DF varied between 4.4% and 32.7%, averaging 15% basin-wide. Future projections show an increased DF of SPEI in deserts and a decrease in oases; SRI DF decreased in deserts but increased in oases. STI changes were more moderate. The study also found a higher risk of drought progression from SPEI to SRI in the southwestern and northeastern oases, exceeding 50% probability, while central and eastern TRB had lower risks. The western TRB and inner Taklamakan Desert faced higher risks of SPEI to STI progression, with probabilities over 45%, in contrast to the lower risks in the eastern and central oases. The concurrence of SRI/STI with moderate to extreme SPEI droughts led to a higher probability and area of SRI/STI droughts, whereas consistent SPEI types showed a reduced induced probability and extent of SRI/STI droughts. This study enhances the understanding of drought propagation from meteorological to hydrological droughts in the TRB and contributes to the prevention of hydrological drought to a certain extent.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] Quantifying climate change impacts on hydropower production under CMIP6 multi-model ensemble projections using SWAT model
    Yalcin, Emrah
    HYDROLOGICAL SCIENCES JOURNAL, 2023, 68 (13) : 1915 - 1936
  • [32] Estimating the consequences for projections of river discharges resulting from uncertainties in climate-change modelling - Analysis of an application of a multi-model ensemble in the catchment of the River Rhine
    Krahe, Peter
    Nilson, Enno
    Carambia, Maria
    Maurer, Thomas
    Tomassini, Lorenzo
    Buelow, Katharina
    Jacob, Daniela
    Moser, Hans
    HYDROLOGIE UND WASSERBEWIRTSCHAFTUNG, 2009, 53 (05): : 316 - 331
  • [33] CMIP6 multi-model prediction of future climate change in the Hotan River Basin
    He C.
    Luo C.
    Chen F.
    Long A.
    Tang H.
    Earth Science Frontiers, 2023, 30 (03) : 515 - 528
  • [34] Multi-Model Grand Ensemble Hydrologic Forecasting in the Fu River Basin Using Bayesian Model Averaging
    Qu, Bo
    Zhang, Xingnan
    Pappenberger, Florian
    Zhang, Tao
    Fang, Yuanhao
    WATER, 2017, 9 (02)
  • [35] Climate change projections for Switzerland based on a Bayesian multi-model approach
    Fischer, A. M.
    Weigel, A. P.
    Buser, C. M.
    Knutti, R.
    Kuensch, H. R.
    Liniger, M. A.
    Schaer, C.
    Appenzeller, C.
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2012, 32 (15) : 2348 - 2371
  • [36] Impacts of Climate Change on Peanut Yield in China Simulated by CMIP5 Multi-Model Ensemble Projections
    Xu, Hanqing
    Tian, Zhan
    Zhong, Honglin
    Fan, Dongli
    Shi, Runhe
    Niu, Yilong
    He, Xiaogang
    Chen, Maosi
    REMOTE SENSING AND MODELING OF ECOSYSTEMS FOR SUSTAINABILITY XIV, 2017, 10405
  • [37] Statistically downscaled probabilistic multi-model ensemble projections of precipitation change in a watershed
    Hashmi, Muhammad Z.
    Shamseldin, Asaad Y.
    Melville, Bruce W.
    HYDROLOGICAL PROCESSES, 2013, 27 (07) : 1021 - 1032
  • [38] Uncertainty Analysis of Climate Change Impact on River Flow Extremes Based on a Large Multi-Model Ensemble
    Jan De Niel
    E. Van Uytven
    P. Willems
    Water Resources Management, 2019, 33 : 4319 - 4333
  • [39] Uncertainty Analysis of Climate Change Impact on River Flow Extremes Based on a Large Multi-Model Ensemble
    De Niel, Jan
    Van Uytven, E.
    Willems, P.
    WATER RESOURCES MANAGEMENT, 2019, 33 (12) : 4319 - 4333
  • [40] Statistical downscaling of CMIP5 multi-model ensemble for projected changes of climate in the Indus River Basin
    Su, Buda
    Huang, Jinlong
    Gemmer, Marco
    Jian, Dongnan
    Tao, Hui
    Jiang, Tong
    Zhao, Chengyi
    ATMOSPHERIC RESEARCH, 2016, 178 : 138 - 149