Shen et al. (2026) A four-decade satellite record of coupled lake area and water quality responses to climate changes and human activities in Northwest China

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-07-09
• Authors: Ming Shen, Yuan Liu, Tianci Qi, Changjiang Liu, Zhigang Cao, Zhenyu Tan, Juhua Luo, Hongtao Duan
• DOI: 10.1016/j.jhydrol.2026.136001

Research Groups

• State Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences
• University of Chinese Academy of Sciences
• Shanghai LandFun Information Technology Co., Ltd
• School of Geographic Sciences and Tourism, Xinjiang Normal University
• College of Urban and Environmental Sciences, Northwest University

Short Summary

This study establishes a novel remote sensing–based framework to assess coupled lake quantity–quality dynamics in Xinjiang, China. The framework links water quantity (lake area) and quality (Secchi disk depth) and provides a scalable baseline for comprehensive lake assessments and sustainable water-resource management under climate change.

Objective

• Investigate the long-term changes in lake area and Secchi disk depth (SDD) in Xinjiang, China, using a four-decade Landsat archive.
• Develop remote sensing algorithms tailored to the optical characteristics and hydrological conditions of arid-region lakes for obtaining water quantity and quality metrics.
• Reconstruct spatiotemporally continuous lake area and SDD records for all major lakes across Xinjiang from 1986 to 2023.

Study Configuration

• Spatial Scale: Regional scale, covering the entire Xinjiang Uygur Autonomous Region in northwestern China.
• Temporal Scale: Long-term, spanning four decades (1986-2023) with a temporal resolution of three years per period.

Methodology and Data

• Models used: Dual-index algorithm for water extraction, random forest regression for SDD estimation.
• Data sources: Landsat imagery, field measurement datasets (Xinjiang Lake SDD Dataset and GLORIA), auxiliary data (temperature, precipitation, Palmer Drought Severity Index, cropland area).

Main Results

• The dual-index algorithm achieved an overall accuracy of 97.42% and a Kappa coefficient of 0.86 for water extraction.
• Random forest regression showed good performance for SDD estimation, with R2 ≥ 0.80 and sMAPE ≤ 30.0%.
• Long-term trends in lake area and SDD were identified, with significant increases in both metrics observed in northern and southern Xinjiang.
• Lakes were classified into four categories based on coupled change patterns: Type I (+SDD, +Area), Type II (+SDD, −Area), Type III (−SDD, +Area), and Type IV (−SDD, −Area).

Contributions

• This study provides a novel framework for assessing coupled lake quantity–quality dynamics in arid regions.
• The results highlight the importance of considering both water quantity and quality when evaluating lake ecological and hydrological status.

Funding

• This research was supported by the National Natural Science Foundation of China (Grant No. 42122015) and the Chinese Academy of Sciences (CAS) Strategic Priority Research Program (Grant No. XDA23000000).

Citation

@article{Shen2026fourdecade,
  author = {Shen, Ming and Liu, Yuan and Qi, Tianci and Liu, Changjiang and Cao, Zhigang and Tan, Zhenyu and Luo, Juhua and Duan, Hongtao},
  title = {A four-decade satellite record of coupled lake area and water quality responses to climate changes and human activities in Northwest China},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.136001},
  url = {https://doi.org/10.1016/j.jhydrol.2026.136001}
}