@article{01K3RKB8TWD75YHB86N1169Y3B,
  abstract     = {{The flood-drought severity in arid regions such as Xinjiang is increasingly influenced by climate extremes. While prior studies have explored the relationship between climate extremes and flood-drought dynamics, few have analyzed these interactions at different time and spatial scales using different method combinations. This study addresses that gap by utilizing a gridded dataset (CN05.1) during 1961-2020, examining the China Z index (flood-drought index) and climate extremes. The analysis reveals significant increases in precipitation and heat extremes, while cold extremes have decreased. In addition to overall periodic changes with 2.5 and 8 years in the flood-drought severity, our results demonstrate a significant spatial shift between 1981 and 2000 and between 2001 and 2020. Previously flood-dominant regions, including portions of the Junggar Basin, Eastern Tianshan Mountains, and Tarim River Basin, transitioned to drought-dominant in 2001-2020. Conversely, drought-dominant regions became flood-dominant. Strong positive correlations (0.65-0.84) were found between the Z index and precipitation extremes, while temperature extremes showed weaker correlations. Furthermore, we applied six variable selection regression methods, with Random Forest variable selection + Random Forest regression (RF+RF) performing the best (mean R2 = 0.71), highlighting their ability to manage non-linear relationships and multicollinearity between climate indices. RF+RF proved more effective at handling correlated variables, which were crucial in capturing the region's flood-drought dynamics. The quantified spatial reversals and non-linear climate-flood/drought relationships provide actionable metrics for early warning systems, enabling targeted infrastructure upgrades and water allocation policies in arid regions. These findings establish a transferable framework linking climate extremes to hydrological risks, directly informing adaptive land management and disaster preparedness strategies for Xinjiang and analogous regions under intensifying climate variability.}},
  articleno    = {{1746}},
  author       = {{Sulei, Naibi and Bao, Anming and Yuan, Ye and Bao, Jiayu and Hamdi, Rafiq and Yu, Tao and Huang, Xiaoran and Wang, Ting and Li, Tao and Jin, Jingyu and Long, Gang and Termonia, Piet}},
  issn         = {{2072-4292}},
  journal      = {{REMOTE SENSING}},
  keywords     = {{climate extremes,flood-drought index,warming-wetting trend,Xinjiang,risk management,SUPPORT VECTOR MACHINE,EXTREME CLIMATE EVENTS,CENTRAL-ASIA,PREDICTION,REGRESSION,TREND,INDEX}},
  language     = {{eng}},
  number       = {{10}},
  pages        = {{29}},
  title        = {{A spatial shift in flood–drought severity in the decades surrounding 2000 in Xinjiang, China}},
  url          = {{http://doi.org/10.3390/rs17101746}},
  volume       = {{17}},
  year         = {{2025}},
}

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