Fu et al. (2026) Climate change enhances the propagation from meteorological to lake drought

Identification

• Journal: Weather and Climate Extremes
• Year: 2026
• Date: 2026-03-01
• Authors: Xinxin Fu, Meiling Gao, Chuang Song, Zhenhong Li, Jiahao Ma, Meiling Zhou, Lili Chen, Jianbing Peng
• DOI: 10.1016/j.wace.2026.100887

Research Groups

• State Key Laboratory of Loess Science, Chang’an University, Xi’an, China
• College of Geological Engineering and Geomatics, Chang’an University, Xi’an, China
• Big Data Center for Geosciences and Satellites, Chang’an University, Xi’an, China
• Key Laboratory of Western China's Mineral Resources and Geological Engineering, Ministry of Education, Xi’an, China

Short Summary

This study quantified the propagation time and probability from meteorological to lake droughts for 153,643 global lakes from 1985 to 2018, revealing that climate change is enhancing this propagation, particularly in arid regions and North America due to rising temperatures and vapor pressure deficit.

Objective

• To investigate the spatiotemporal characteristics of drought propagation from meteorological to lake droughts at the global scale.
• To identify which lakes are at higher risk of drought propagation and determine the main driving factors behind these changes.

Study Configuration

• Spatial Scale: Global, covering 153,643 lakes worldwide. Lakes smaller than 1 km² and the Caspian Sea were excluded.
• Temporal Scale: 1985–2018 (34 years). Trend analysis used a 10-year sliding window with a 1-year step.

Methodology and Data

• Models used:
  • Standardized Waterbody Index (SWI) for lake drought (based on Gamma, Generalized Extreme Value, and Pearson Type III distributions, selected by Bayesian Information Criterion and Kolmogorov–Smirnov test).
  • Standardized Precipitation Evapotranspiration Index (SPEI) for meteorological drought.
  • Maximum correlation method (Spearman’s rank correlation) for Drought Propagation Time (DPT).
  • Copula-based approaches (Clayton, Frank, Gumbel, Gaussian, and t Copula, selected by Bayesian Information Criterion) for Drought Propagation Probability (DPP).
  • Sen’s slope estimator and Mann-Kendall (MK) test for trend analysis.
  • Principal Component Regression (PCR) for attributing driving factors.
• Data sources:
  • Global Lake Evaporation Volume (GLEV) dataset (Zhao et al., 2022) for monthly ice-free lake surface area.
  • Global SPEI dataset (Vicente-Serrano et al., 2010) for meteorological drought (1–48 months, 5 km spatial resolution).
  • HydroSHEDS global multi-level watershed dataset (level-12 sub-basins) for upstream catchment boundaries.
  • Global land-use dataset (Song et al., 2018).
  • TerraClimate for climate variables (temperature, precipitation, vapor pressure deficit, solar radiation, soil moisture).

Main Results

• Spatial Heterogeneity: Drought propagation time (DPT) and probability (DPP) showed strong spatial heterogeneity. DPT was longer (40–48 months) in high-latitude/high-elevation regions and shorter (1–10 months) in tropical humid regions. DPP exhibited stronger spatial aggregation, with high values (>50%) in southwestern North America, eastern South America, southern Africa, and northeastern Asia.
• Influence of Lake Morphology, Climate, and Land Surface: Large, shallow lakes (>100 km², 0–5 m) generally had longer DPT and higher DPP. DPP decreased markedly along the aridity gradient, from 31% in arid regions to 10% in humid regions. Catchments with high tree cover exhibited longer DPT and lower DPP, while those dominated by non-woody vegetation showed the opposite.
• Temporal Variations (1985–2018): 14% of lakes (21,510) experienced significantly faster drought propagation (decreased DPT), mainly in North America and northern Europe. 26% of lakes (39,947) exhibited a significantly higher probability of propagation (increased DPP), particularly in arid regions (61% of lakes in arid regions showed increased DPP). The most prevalent joint pattern (35% of lakes) was decreased DPT alongside increased DPP, concentrated in northern North America.
• Dominant Driving Factors: Temperature was the dominant driver for changes in DPT (16.07% of lakes) and DPP (16.53% of lakes), especially in high-latitude and high-elevation areas. Moisture-related factors (precipitation, soil moisture) dominated in humid/semi-humid regions. Vapor pressure deficit (VPD) and solar radiation were influential in climatic transition zones and high-latitude/high-elevation plateaus. Land-use factors (tree cover, non-tree vegetation) were significant in arid/semi-arid regions.
• High-Risk Lakes: Lakes with both shorter DPT and higher DPP were mainly concentrated in North America, primarily influenced by rising air temperatures (90.9% of catchments showed significant warming) and increased vapor pressure deficit (48.4% showed significant increases).

Contributions

• Provides the first global assessment of the propagation characteristics (time and probability) from meteorological to lake droughts for a large dataset of 153,643 lakes.
• Quantifies the spatiotemporal patterns of drought propagation and identifies the key climatic and land-surface drivers, including the role of lake morphology and aridity.
• Highlights the accelerating exposure of global lakes to drought under climate change, particularly in North America, driven by increasing temperatures and vapor pressure deficit.
• Offers crucial insights for developing robust early warning systems and adaptive water management strategies for lake ecosystems globally.

Funding

• National Natural Science Foundation of China (42341101)
• Shaanxi Province Science and Technology Innovation Team (2021TD-51)
• Shaanxi Province Geoscience Big Data and Geohazard Prevention Innovation Team (2022)
• Fundamental Research Funds for the Central Universities, Chang’an University (300102260301, 300102262902, and 300102262712)

Citation

@article{Fu2026Climate,
  author = {Fu, Xinxin and Gao, Meiling and Song, Chuang and Li, Zhenhong and Ma, Jiahao and Zhou, Meiling and Chen, Lili and Peng, Jianbing},
  title = {Climate change enhances the propagation from meteorological to lake drought},
  journal = {Weather and Climate Extremes},
  year = {2026},
  doi = {10.1016/j.wace.2026.100887},
  url = {https://doi.org/10.1016/j.wace.2026.100887}
}