Details

Autor(en) / Beteiligte

• Wang, Quan
• Wang, Tao
• Zhao, Shengping
• Yang, Kun
• Wen, Xinyu
• Zhao, Minhui
• Luo, Fen
• Jiang, Baoli
• Jin, Yang
• Zhang, Baoying

Titel

Comprehensive meteorological factors analysis and lag correlation study for cyanobacterial blooms in shallow plateau lake

Ist Teil von

• Ecological indicators, 2023-09, Vol.153, p.110394, Article 110394

Ort / Verlag

Elsevier Ltd

Erscheinungsjahr

2023

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• [Display omitted] •The lag effect of comprehensive meteorological factors on CBs was analyzed.•Sunshine duration has a negative relationship with CBs in plateau lakes on the whole.•Sunshine duration has a positive relationship with CBs when it is below 6 h.•Daytime precipitation has a greater influence on CBs than nighttime precipitation.•The atmospheric pressure was positively correlated with CBs. Cyanobacterial blooms (CBs) are a growing concern for shallow plateau lakes, and numerous studies have investigated the relationship between CBs and meteorological factors. However, these studies have typically lacked comprehensive analyses and neglected the impact of lag effects. This study employed Landsat satellite imagery to extract CBs information from Xingyun Lake from 1990 to 2019 and conducted a lag correlation analysis between meteorological factors ranging from 1 to 30 days with a 1-day step and CBs. The result show that the Sunshine Duration displayed a negative correlation with CBs at an 8-day lag, but when Sunshine Duration was <6 h, it exhibited a positive relationship with CBs at a 1-day lag. And daytime precipitation had a more substantial positive link with CBs than nighttime precipitation at a lag of 13 days. The aforementioned conclusions deepen our comprehension of the meteorological forces that drive cyanobacterial blooms in plateau lakes. Moreover, the maximum and minimum wind velocities were negatively and positively associated with CBs with lags of 20 and 29 days, respectively. In addition, relative humidity and atmospheric pressure were positively associated with cyanobacterial blooms 13–19 days and 3 days after their onset, respectively. The relationship between air temperature and cyanobacterial blooms in Xingyun Lake was weak. Our research emphasizes the significance of incorporating delayed effects and refined meteorological factors for accurate cyanobacterial bloom forecasting.