Record-setting cyanobacterial bloom in the largest freshwater lake in northern China caused by joint effects of hydrological variations and nutrient enrichment

Yulong Tao; Yiran Zhang; Xiangzhen Kong; Sheng Zhang; Yufei Xue; Wen Ao; Bo Pang; Huashan Dou; Bin Xue

doi:10.1016/j.envres.2025.120813

Record-setting cyanobacterial bloom in the largest freshwater lake in northern China caused by joint effects of hydrological variations and nutrient enrichment

Environ Res. 2025 Jan 9:120813. doi: 10.1016/j.envres.2025.120813. Online ahead of print.

Authors

Yulong Tao¹, Yiran Zhang², Xiangzhen Kong³, Sheng Zhang⁴, Yufei Xue⁵, Wen Ao⁶, Bo Pang⁷, Huashan Dou⁷, Bin Xue²

Affiliations

¹ Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China; Hulunbuir Academy of Inland Lakes in Northern Cold and Arid Areas, Hulunbuir 021008, China; State Gauge and Research Station of Wetland Ecosystem, Hulun Lake, Inner Mongolia, China.
² Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China.
³ Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; Department of Lake Research, Helmholtz Centre for Environmental Research - UFZ, 39114 Magdeburg, Germany. Electronic address: xzkong@niglas.ac.cn.
⁴ Water Conservancy and Civil Engineering College, Inner Mongolia Agricultural University, Hohhot 010018, China. Electronic address: shengzhang@imau.edu.cn.
⁵ Key Laboratory of Lake and Watershed Science for Water Security, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; University of Chinese Academy of Sciences, Beijing 100049, China.
⁶ Hulunbuir Academy of Inland Lakes in Northern Cold and Arid Areas, Hulunbuir 021008, China; State Gauge and Research Station of Wetland Ecosystem, Hulun Lake, Inner Mongolia, China.
⁷ State Gauge and Research Station of Wetland Ecosystem, Hulun Lake, Inner Mongolia, China; Hulun Lake National Nature Reserve Administration.

PMID: 39798652
DOI: 10.1016/j.envres.2025.120813

Abstract

Cyanobacterial blooms represent a significant environmental issue posing widespread threats to global aquatic ecological health. Climate and nutrient enrichment were the most studied factors modulating cyanobacterial blooms in eutrophic lakes. However, in many floodplain lakes, the importance of hydrological variation in driving and predicting cyanobacterial blooms is often overlooked and largely underestimated, which has hampered the effectiveness of lake management. Here, we use a process-based lake ecosystem model (GOTM-WET) to evaluate the potential drivers of the record-setting cyanobacterial bloom during summer 2022 (>70% of lake area) in the largest shallow lake in Northern China (Hulun Lake). The model was calibrated based on a comprehensive field dataset including both remote sensing (surface water temperature) and in-lake observations (water quality). We performed a scenario analysis with various combinations of nutrient loading, hydrological variations and climate change. Our modeling results unravel that the profound water level rise through 2021 to 2022 serves as the main trigger of the severe cyanobacterial bloom in summer 2022, whereas climate factors demonstrate marginal impacts. Our model predicted a decrease of 60.5% in the annual average of cyanobacterial biomass when water level remained stable. In addition, both water level change and nutrient concentration explains 72.5% of the variance in long-term maximum area of cyanobacterial blooms. Our model further reveals that the water level rise drives the cyanobacterial bloom via bringring in excessive nutrient to lake water column from the lake basin. Thus, our results suggest that continuous increase in water level across two years could serve as an early warning signal to cyanobacterial blooms in the consecutive summer. Our findings may be applicable to similar temperate shallow lakes in floodplain areas, especially for those located in agricultural and pasture regions with abundant nutrient legacy, thus may provide a new indicator for cyanobacterial blooms prediction.

Keywords: GOTM-WET; Hulun Lake; cyanobacterial blooms; early warning signal; water level fluctuations.