## 5 Conclusions  
This study employed the AQUATOX lake ecological model to simulate the ecological variations in a typical alpine lake, Namco, on the TP, using the available lake observation data. Through uncertainty and sensitivity modules, the key parameters affecting the ecological indicator simulations were tested and calibrated. The model demonstrated acceptable performance in modeling the concentrations of water nutrients, specifically WTP and WTN, within the lake. Long-term simulations revealed an upward trend in the concentrations of water nutrients, WGPP, WNPP, and Chl-a over the period from 1980 to 2020, even though this lake was in an oligotrophic state. The WTN and WTP concentrations increased to 0.0369 mg L\({}^{-1}\) and 0.00245 mg L\({}^{-1}\) per decade, respectively. The regression coefficients \(R^{2}\) for WTN and WTP of lake ecology were found to be 0.99 and 0.97, respectively. Moreover, the WGPP, WNPP, and Chl-a concentrations increased at 0.0651 g O\({}_{2}\) m\({}^{-2}\) d\({}^{-1}\), 0.0509 g O\({}_{2}\) m\({}^{-2}\) d\({}^{-1}\), and 0.2 ug L\({}^{-1}\) per decade, respectively. For WGPP, WNPP, and Chl-a, the regression coefficients \(R^{2}\) were 0.97, 0.97, and 0.96, respectively. Furthermore, utilizing multiple regression analysis, it was determined that WGPP, WNPP, and Chl-a were largely influenced by the local climate and hydrology. The lake's thermodynamic status, including lake water temperature and volume, was found to be an important factor. In addition, water nutrients, i.e., WTP and WTN, exhibited insensitivity to local environmental changes. With continuous lake warming in the future, water primary productivity would maintain an increasing trend, especially under high-emission scenarios. Future research should focus on integrating datasets for lake water ecology and enhancing the accuracy of lake ecological simulations, particularly for lakes situated in high-altitude and high-latitude regions.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/w16141982/s1](https://www.mdpi.com/article/10.3390/w16141982/s1)]([https://www.mdpi.com/article/10.3390/w16141982/s1](https://www.mdpi.com/article/10.3390/w16141982/s1)), Table S1: Data used for initialization and modeling the ecological indicators in the AQUATOX model.  
Conceptualization--Q.Z.; formal analysis--Q.Z, L.C. and X.G.; methodology--Q.Z., L.C., X.G., R.D. and M.M.; writing--original draft, Q.Z.; review and editing--Q.Z., L.C., X.G., R.D. and M.M. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This study was supported by Geological Survey Project of China (grant no. DD202030301), the Technology project of Qinghai Bureau of Environmental Geology Exploration of China (grant no. 2023-ZK-01), and the Natural Science Basic Research Program of Shaanxi (2022)Q-238). [PERSON] was also supported by the foundation of Director of the Xi'an Center of Geological Survey, CGS (Grant XACGS-2023-05).  
**Data Availability Statement:** Data are contained within the article and Supplementary Material.  
**Acknowledgments:** The data used in this study were provided by the National Tibetan Plateau/Third Pole Environment Data Center at [[http://data.tpdc.ac.cn](http://data.tpdc.ac.cn)]([http://data.tpdc.ac.cn](http://data.tpdc.ac.cn)) (last accessed on 5 June 2024). Lake temperature projections are available at [[https://data.isimip.org/](https://data.isimip.org/)]([https://data.isimip.org/](https://data.isimip.org/)) (last accessed on 5 June 2024).  
**Conflicts of Interest:** The authors declare no conflicts of interest.