The Journal of Environmental Management, a top SCI journal, has published innovative research from Professor Ai Songtao’s team at the China Antarctic Surveying and Mapping Research Center Wuhan University, in collaboration with the University of Canterbury. This study presents a fresh perspective on the hydrological behaviour of glacier-fed lakes, focusing on Blue Moon Lake, a high-altitude lake in China. It explores how air temperature, water temperature, and water levels interact over time in response to climate change. Glacier-fed lakes are highly sensitive to atmospheric changes, yet predicting their responses remains a challenge. The research team found that while both air and water temperatures are rising, the lake’s water level has remained stable during the study period. This stability is attributed to a delicate balance of inflow and outflow, maintained by hydrological factors such as precipitation, glacier melt, and a regulating hydraulic structure. This raises important questions about how these lakes buffer against climate-driven fluctuations.
To sort out these interactions, the study applied statistical techniques, including the Granger causality test and wavelet analysis, alongside machine learning models designed to capture complex, non-linear relationships. A key innovation of the study was the development of the Quad-Meta (QM) model, a hybrid machine learning approach that combines the outputs of four models—extreme gradient boosting (XGB), random forest (RF), gradient boosting machine (GBM), and decision tree (DT). By combining the strengths of each, the QM model significantly outperformed individual models in predicting lake water-air temperature, and water levels, under complex environmental conditions. Unlike standard ensemble methods, which struggled with the complexities of glacier-fed lakes, the QM model successfully captured extreme conditions and non-linear dependencies.
The findings demonstrate an important balance between atmospheric warming and hydrological stability in the basin. While rising air temperatures influence both water temperature and water levels, the role of precipitation, glacier runoff, and local hydrological structures in maintaining this balance is essential. The study draws attention to the importance of closely monitoring air temperature trends, as they have a stronger influence on water levels compared to direct water temperature fluctuations. Recognizing these dynamics is key for long-term water resource management, particularly in high-altitude regions where climate change is accelerating. This research not only boosts climate modelling for glacier-fed lakes but also provides effective insights for representatives working to manage freshwater resources in sensitive environments.
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