Historical and Future Variation of Lacustrine Chlorophyll-a and Driving Factors on the Qinghai–Tibet Plateau
The temperature of the Qinghai–Tibet Plateau (QTP) has rapidly increased under global change, accelerating the process of lacustrine eutrophication. Chlorophyll-a (Chla) has always been a key indicator of lacustrine phytoplankton biomass and eutrophication. Satellite images have incomparable advanta...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
American Association for the Advancement of Science (AAAS)
2025-01-01
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| Series: | Journal of Remote Sensing |
| Online Access: | https://spj.science.org/doi/10.34133/remotesensing.0689 |
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| Summary: | The temperature of the Qinghai–Tibet Plateau (QTP) has rapidly increased under global change, accelerating the process of lacustrine eutrophication. Chlorophyll-a (Chla) has always been a key indicator of lacustrine phytoplankton biomass and eutrophication. Satellite images have incomparable advantages in estimating the long-term and large-scale variation of Chla under extremely harsh climate conditions. In order to effectively manage lakes and work toward Sustainable Development Goals, this research made use of Landsat surface reflectance data from 1986 to 2023, which were collected and processed on the Google Earth Engine platform, to remotely estimate Chla in lakes on the QTP. Among the 1,069 lakes studied in the QTP, 281 and 166 lakes showed significant increases and decreases in Chla (P < 0.05), respectively. Correlations between Chla and multiple environmental factors were analyzed (analyzed in particular nitrogen deposition, large livestock, and sheep factors, besides conventional factors), aiming to bring new inspiration to water environment management. Utilizing variance decomposition and multiple general linear model regression, we quantitatively analyzed the contribution of various environmental factors. This study creatively set up the 3 change scenarios of large livestock, sheep, and fertilizer into general-linear-model-based equations to forecast yearly variations in Chla in 10 typical lakes from 2024 to 2100. The concentration of Chla in most lakes exhibited a marked rise due to the yearly increase in large livestock, sheep, and fertilizer. We suggest reducing human activities in lakes facing high environmental pressures and redirecting some environmental pollution pressure to lake basins with more space for self-ecological system regulation in the future. |
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| ISSN: | 2694-1589 |