Identification of driving factors for chlorophyll‐a in multi‐stable shallow lakes of China employing machine learning methods

Due to the rapid increase in urbanization and anthropogenic activity in the lake catchment, nutrients like phosphorus and nitrogen are abundant in urban sewage, leading to lake eutrophication and promoting algal blooms. Chlorophyll‐a (Chl‐a) is an important indicator of algal blooms; thus, predictin...

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Veröffentlicht in:	Ecohydrology 2023-12, Vol.16 (8), p.n/a
Hauptverfasser:	Qu, Shan, Wang, Jian‐jian, Kumar, Amit, Yu, Zhi‐Guo, Zhao, Wan‐Qi
Format:	Artikel
Sprache:	eng
Schlagworte:	Additives Algae Algal blooms Anthropogenic factors Aquatic ecosystems Catchment area Chlorophyll Chlorophyll a Chl‐a Computation Concentration gradient Decision making Decision trees Environmental management Eutrophication factor analysis Lake catchments Lake restoration Lakes Learning algorithms Machine learning Nutrients Phosphorus Predictions Redundancy Root-mean-square errors Sewage Support vector machines Taihu Lake Urbanization Water quality XGBoost model
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