Machine learning revealed monthly change characteristics of lakes on the Tibet Plateau over the past two decades

IF 5 2区地球科学 Q1 WATER RESOURCES

Journal of Hydrology-Regional Studies Pub Date : 2025-10-09 DOI:10.1016/j.ejrh.2025.102839

Juan Wu , Chang-Qing Ke , Yu Cai , Hai-Yong Wei , Jin-Peng Tang , He-Ping Xiao , Zhe Liu

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引用次数: 0

Abstract

Study region

The Tibetan Plateau (TP) hosts the highest concentration of plateau lakes on Earth, which are undergoing significant climate-induced changes. However, the lack of high-temporal-resolution data has posed challenges for capturing these dynamics at the monthly scale.

Study focus

This study integrates optical imagery from the Google Earth Engine (GEE) platform and altimetry data from 11 satellite missions, combined with four machine learning models, to investigate the monthly change characteristics of 253 lakes on the TP from 2000 to 2022.

New hydrological insights for the region

Lake area, level, and volume have expanded, risen, and increased, respectively, during the study period. Lake volume increased by 5.62 % per year, with the growth mainly concentrated in the Inner Plateau and in lakes larger than 100 km². A decreasing trend in lake volume was observed in the Brahmaputra, Ganges, and Yangtze basins. Monthly lake area, level and volume changes mainly peaked in August, September and October. The lake water volume in the Indus, Ganges, and Amu Darya basins peaks earlier. The monthly peak water volume of lakes larger than 50 km² shows a delayed trend, while lakes smaller than 50 km² show an earlier peak trend. Lake volume changes were closely linked to the El Niño-Southern Oscillation (ENSO), while regional precipitation and runoff were likely the primary drivers of monthly variability.

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然而，缺乏高时间分辨率的数据为在月尺度上捕捉这些动态带来了挑战。本研究结合谷歌地球引擎（GEE）平台的光学图像和11个卫星任务的测高数据，结合4种机器学习模型，研究了2000 - 2022年青藏高原253个湖泊的月变化特征。在研究期间，湖泊面积、水位和体积分别扩大、上升和增加。湖泊容量以每年5.62 %的速度增长，增长主要集中在内高原和面积大于100 km²的湖泊。雅鲁藏布江流域、恒河流域和长江流域湖泊容量呈减少趋势。月湖泊面积、水位和体积变化主要在8月、9月和10月达到高峰。印度河、恒河和阿姆河流域的湖泊水量较早达到峰值。大于50 km²的湖泊月峰值水量呈现延迟趋势，小于50 km²的湖泊月峰值水量呈现提前趋势。湖泊体积变化与厄尔尼诺Niño-Southern涛动（ENSO）密切相关，而区域降水和径流可能是月变率的主要驱动因素。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Hydrology-Regional Studies Earth and Planetary Sciences-Earth and Planetary Sciences (miscellaneous)

CiteScore

6.70

自引率

8.50%

发文量

284

审稿时长

60 days

期刊介绍： Journal of Hydrology: Regional Studies publishes original research papers enhancing the science of hydrology and aiming at region-specific problems, past and future conditions, analysis, review and solutions. The journal particularly welcomes research papers that deliver new insights into region-specific hydrological processes and responses to changing conditions, as well as contributions that incorporate interdisciplinarity and translational science.