Zou et al. (2025) Quantifying drivers of lake dynamics in Xinjiang: Evaluation of water storage and climatic sensitivity from 1990 to 2022

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2025
• Date: 2025-11-27
• Authors: Bin Zou, Yanfeng Di, Shan Zou, Yaning Chen, Wenjing Huang, Z. Zhu, Ying Li, Yuhui Yang
• DOI: 10.1016/j.ejrh.2025.102966

Research Groups

• College of Geographic Science and Tourism, Xinjiang Normal University, Urumqi, China
• State Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology & Geography, Chinese Academy of Sciences, Urumqi, China
• College of Resources and Environment, University of China Academy of Sciences, Beijing, China
• Akesu National Station of Observation and Research for Oasis Agro-ecosystem, Akesu, Xinjiang, China
• North China University of Water Resources and Electric Power, Zhengzhou, China

Short Summary

This study quantified lake surface area (LSA) and water storage changes (LWSC) for 324 lakes larger than 1 km² in Xinjiang from 1990 to 2022 using remote sensing and a lake water balance model. It revealed a significant expansion in both LSA and LWSC, primarily driven by groundwater recharge and surface runoff, with lake surface evaporation acting as the main water loss.

Objective

• To extract and investigate changes in all lakes in Xinjiang with an area greater than 1 km² from 1990 to 2022.
• To apply a lake water balance model to quantitatively assess the contributions of various factors to changes in lake water storage.

Study Configuration

• Spatial Scale: Xinjiang Uygur Autonomous Region, China (approximately 1.6649 million km²), including South and North Xinjiang, and nine elevation zones. The study focused on 324 lakes larger than 1 km².
• Temporal Scale: 1990 to 2022. Specific data sources had slightly different temporal coverages (e.g., GRACE 2003-2022, CNRD 1990-2018).

Methodology and Data

• Models used:
  • Empirical equation for area-water storage changes (ΔV = 1/3(H2 − H2) × (A1 + A2 + √(A1 + A2))).
  • Lake water balance model (ΔV = A × (P − E) + R + ΔG).
  • Hybrid index method for Lake Surface Area (LSA) extraction using rules (mNDWI > EVI or mNDWI > NDVI) and (EVI < 0.1).
  • Sen’s slope for trend analysis.
• Data sources:
  • Satellite Imagery: Landsat 5 TM, Landsat 7 ETM, Landsat 8 OLI, Landsat 9 OLI (1990–2022, from Google Earth Engine - GEE). Sentinel-2A images (for accuracy assessment).
  • Topographic Data: Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) (1 arc-second, v1, 2000, from NASA).
  • Climate Data: Daily meteorological data from 105 meteorological stations (1990–2022, from China Meteorological Administration - CMA). ERA5-Land reanalysis dataset (0.1° spatial resolution, 1990–2022, from GEE).
  • Runoff Data: Natural Runoff Dataset (CNRD v1.0, 0.25° spatial resolution, 1990–2018, from National Tibetan Plateau Data Center). Water transfer data (2000–2018, from Xinjiang Tarim River Basin Authority).
  • Terrestrial Water Storage: GRACE RL06_mascons dataset (0.25° spatial resolution, 2003–2022, from Center for Space Research at the University of Texas - CSR).
  • Other: CRD dam database (to exclude reservoirs). In-situ observational data for Bosten Lake (1990–2022, from Xinjiang Tarim River Basin Authority). Satellite altimetry data for Sayram Lake, Ulungar Lake, Aqqikkol Lake, and Aksayquin Lake (for validation).

Main Results

• Lake Number: The number of lakes increased by 59 (approximately 25%) from 1990 to 2022, reaching a maximum of 315 in 2018. South Xinjiang saw an increase of 45 lakes, while North Xinjiang gained 14.
• Lake Surface Area (LSA): Max LSA expanded by 1943.51 km² at an average rate of 84.99 km²/a, and min LSA expanded by 1858.51 km² at 75.65 km²/a. South Xinjiang accounted for approximately 92% of the total LSA increase. Lakes with increased LSA were primarily located in the northern foothills of the Kunlun Mountains, while reductions were observed in piedmont plains affected by human activities.
• Lake Water Storage Change (LWSC): Max LWSC increased by 40.98 Gt (1.75 Gt/a), and min LWSC increased by 38.37 Gt (1.52 Gt/a) from 1990 to 2022. Lakes in South Xinjiang contributed approximately 95% of this growth, effectively doubling their LWSC.
• Spatial Distribution of LWSC: The greatest LWSC increases were observed in the 1500–4500 m elevation zone (maxLWSC: 21.06 Gt; minLWSC: 22.64 Gt). Lakes below 1000 m showed significant fluctuations due to human activities and ecological water transfers.
• Drivers of LWSC: For the five major expanding lakes, the overall change in water volume was primarily controlled by groundwater (84.31% contribution) and surface runoff (69.85% contribution), with lake surface evaporation being the main loss factor (-78.83% contribution) and lake surface precipitation contributing 24.67%. High-altitude lakes (e.g., Aksayqin, Whale Lakes) were directly replenished by glacial meltwater. Taitema Lake's recovery was mainly due to ecological water transfer and groundwater recharge.
• Terrestrial Water Storage (TWS) Relationship: LWSC generally aligned with TWS changes from 2003 to 2022, showing declines in the central Tianshan Mountains and increases in southeastern Xinjiang, though discrepancies existed due to other TWS components.

Contributions

• This study is the first to systematically calculate and analyze the Lake Surface Area (LSA) and Lake Water Storage Change (LWSC) for all lakes larger than 1 km² in Xinjiang over a long-term period (1990–2022).
• It provides a quantitative, process-based assessment of the contributions of various hydrological factors (runoff, precipitation, evaporation, groundwater) to lake water storage changes using a lake water balance model, addressing previous research gaps that often focused on larger lakes or employed statistical methods without in-depth process understanding.
• The research offers important scientific evidence for a deeper understanding of the lake water cycle processes in Xinjiang, supporting sustainable water resource management and ecological protection policies in the region.

Funding

This study was jointly supported by the Third Xinjiang Scientific Expedition Program (Grant No. 2023xjkk0101).

Citation

@article{Zou2025Quantifying,
  author = {Zou, Bin and Di, Yanfeng and Zou, Shan and Chen, Yaning and Huang, Wenjing and Zhu, Z. and Li, Ying and Yang, Yuhui},
  title = {Quantifying drivers of lake dynamics in Xinjiang: Evaluation of water storage and climatic sensitivity from 1990 to 2022},
  journal = {Journal of Hydrology Regional Studies},
  year = {2025},
  doi = {10.1016/j.ejrh.2025.102966},
  url = {https://doi.org/10.1016/j.ejrh.2025.102966}
}