Predicting water level fluctuations in glacier-fed lakes by ensembling individual models into a quad-meta model

Engineering Applications of Computational Fluid Mechanics, Journal Year: 2025, Volume and Issue: 19(1)

Published: Jan. 8, 2025

Predicting water levels in glacier-fed lakes is vital for resource management, flood forecasting, and ecological balance. This study examines the predictive capacity of multiple climate factors affecting Blue Moon Lake Valley, fed by Baishui River glacier on Yulong Snow Mountain. The introduces a novel quad-meta (QM) ensemble model that integrates outputs from four machine learning models – extreme gradient boosting (XGB), random forest (RF), (GBM), decision tree (DT) through meta-learning to improve prediction accuracy under complex environmental conditions. High-frequency depth data, recorded every five minutes using an RBR logger, alongside variables such as temperature, wind speed, humidity, evaporation, solar radiation, rainfall, were analyzed. Temperature was identified most significant factor influencing levels, with importance score 15.69, followed atmospheric pressure (14.08) radiation (12.89), which impacted surface conditions evaporation. Relative humidity (10.24) speed (8.71) influenced lake stability mixing. QM outperformed individual models, achieved RMSE values 0.003 m (climate data) 0.001 (water data), R2 0.994 0.999, respectively. In comparison, XGB GBM exhibited higher lower scores. RF struggled 0.008 0.962, while DT performed better (RMSE: 0.006 but remained inferior proposed model. These findings demonstrate robustness approach handling particularly where fall short. highlights potential enhanced systems, recommending future research directions incorporate deep long-term forecasting expand capabilities global scale.

Language: Английский

Ferrochrome Pollution and Its Consequences on Groundwater Ecosystems and Public Health

Limnological Review, Journal Year: 2025, Volume and Issue: 25(2), P. 23 - 23

Published: June 2, 2025

Ferrochrome pollution, a by-product of the ferroalloy industry, is emerging as significant environmental concern due to its potential contaminate groundwater resources. This contamination occurs primarily through leaching heavy metals, such chromium, into soil and water systems. review article presents strategic framework for assessing health risks associated with ferrochrome industry pollution rather than focusing on case study. The suggested methodology designed guide future field investigations in areas impacted by industrial activities. presence chromium poses serious both ecosystems human health. In aquatic ecosystems, elevated levels can disrupt balance microbial communities, affect biodiversity, harm organisms. For humans, long-term exposure chromium-contaminated range issues, including carcinogenic effects, skin rashes, respiratory problems, damage vital organs. widespread use drinking, irrigation, purposes exacerbates public paper explores sources, pathways, mechanisms contamination, examines impact highlights consequences affected populations. Strategies mitigating treatment technologies policy interventions, are also discussed help safeguard

Language: Английский