Remote sensing estimation of water volume changes of typical lakes in Xinjiang, China from 1990 to 2021.

Inland lakes are important surface water resources in arid Central Asia. Due to the superimposed influence of natural factors and human factors, the hydrological characteristics of arid lakes show significant temporal and spatial variations. However, data shortage in this area makes it difficult to carry out detailed and long-term quantitative monitoring of hydrological regimes for different lakes. Based on the Google Earth Engine Platform (GEE), we firstly selected the Landsat 5/7/8 remote sensing image data that completely covered the Saram Lake and Ebinur Lake during 1990-2021, and used the multi-remote sensing index decision tree method to extract the continuous long time series of lake area. Combined with lake water level extracted by CryoSat-2 and ICESat-2 alti-meter satellites, we constructed the storage capacity curve based on the relationship between lake area and water level, and estimated the water volume change information of the lakes. Finally, combined with the hydrological, climate and population factors data of the basin, the correlation analysis and random forest method were used to quantitatively compare and analyze the factors of water quantity variation between the two lakes. The results showed that both Saram Lake and Ebinur Lake had expanded during 1990-2021, though with quite different water conditions. The area of Saram Lake increased by only 1.3%, with little interannual variation. The water volume increased by 1.12 km<sup>3</sup> at a growth rate of around 0.04 km<sup>3</sup>·a<sup>-1</sup>. Conversely, the area of Ebinur Lake experienced a 30.1% expansion and exhibited significant annual fluctuation, averaging approximately 0.01 km<sup>3</sup>·a<sup>-1</sup>. Annual precipitation and glacial meltwater were the main factors affecting the water content of the Saram Lake, with contribution rates of 33% and 27%, respectively. However, temperature and precipitation were the main factors affecting the water quantity change of Ebinur Lake, and their contribution rates in the process of water quantity change were both 28%. The aim of this study was to use remote sensing technology to reveal the characteristics of lakes' dynamic change and the difference of its response to their external environment in arid areas with the shortage of measured data, which would provide scientific reference for lake ecological environment and water resources protection in arid areas.

Authors

Institutions

Publication Details

Journal
PubMed
Published
2024-11-01
DOI
https://doi.org/10.13287/j.1001-9332.202411.026
Citations
1
Primary Topic
Environmental Changes in China
Type
article
Field-Weighted Citation Impact
0.28
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Remote sensing estimation of water volume changes of typical lakes in Xinjiang, China from 1990 to 2021.

Dapeng Zhang, Tan Chen, Shuang Zhao
1 citations
PubMed
Environmental Changes in China
0.28
article

Remote sensing estimation of water volume changes of typical lakes in Xinjiang, China from 1990 to 2021.

Dapeng Zhang, Tan Chen, Shuang Zhao
article en
1 citations

Abstract

Inland lakes are important surface water resources in arid Central Asia. Due to the superimposed influence of natural factors and human factors, the hydrological characteristics of arid lakes show significant temporal and spatial variations. However, data shortage in this area makes it difficult to carry out detailed and long-term quantitative monitoring of hydrological regimes for different lakes. Based on the Google Earth Engine Platform (GEE), we firstly selected the Landsat 5/7/8 remote sensing image data that completely covered the Saram Lake and Ebinur Lake during 1990-2021, and used the multi-remote sensing index decision tree method to extract the continuous long time series of lake area. Combined with lake water level extracted by CryoSat-2 and ICESat-2 alti-meter satellites, we constructed the storage capacity curve based on the relationship between lake area and water level, and estimated the water volume change information of the lakes. Finally, combined with the hydrological, climate and population factors data of the basin, the correlation analysis and random forest method were used to quantitatively compare and analyze the factors of water quantity variation between the two lakes. The results showed that both Saram Lake and Ebinur Lake had expanded during 1990-2021, though with quite different water conditions. The area of Saram Lake increased by only 1.3%, with little interannual variation. The water volume increased by 1.12 km<sup>3</sup> at a growth rate of around 0.04 km<sup>3</sup>·a<sup>-1</sup>. Conversely, the area of Ebinur Lake experienced a 30.1% expansion and exhibited significant annual fluctuation, averaging approximately 0.01 km<sup>3</sup>·a<sup>-1</sup>. Annual precipitation and glacial meltwater were the main factors affecting the water content of the Saram Lake, with contribution rates of 33% and 27%, respectively. However, temperature and precipitation were the main factors affecting the water quantity change of Ebinur Lake, and their contribution rates in the process of water quantity change were both 28%. The aim of this study was to use remote sensing technology to reveal the characteristics of lakes' dynamic change and the difference of its response to their external environment in arid areas with the shortage of measured data, which would provide scientific reference for lake ecological environment and water resources protection in arid areas.

PubMedVol. 35(11)
Chinese Academy of Sciences (CN), Chuzhou University (CN), Nanjing Institute of Geography and Limnology (CN)
Openalex Percentile: Top 39%
Environmental Changes in China
0.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.