Study on the spatiotemporal distribution of algal blooms and its influencing factors in young reservoirs based on remote sensing interpretation.
Ning Liao, Zhuoyu Chen, Linglei Zhang, Min Chen, Yuliang Zhang, Jia Li, Hongwei Wang
Author Information
Ning Liao: State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource & Hydropower, Sichuan University, Chengdu, 610065, China.
Linglei Zhang: State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource & Hydropower, Sichuan University, Chengdu, 610065, China.
Min Chen: State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource & Hydropower, Sichuan University, Chengdu, 610065, China. Electronic address: mchen@scu.edu.cn.
Yuliang Zhang: Northeast Electric Power Design Institute CO., LTD. of China Power Engineering Consulting Group, Changchun, 130022, China.
Jia Li: State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource & Hydropower, Sichuan University, Chengdu, 610065, China.
Hongwei Wang: Sichuan Province Zipingpu Development Corporation Limited, Chengdu, 610091, China.
Algal blooms caused by excessive proliferation of phytoplankton in young reservoirs have been frequently reported, seriously threatening the unstable aquatic ecosystem, water quality safety and public health. Thus, there is an urgent need to investigate the dynamics of phytoplankton in these young reservoirs, and many current studies on phytoplankton in young reservoirs are based on point monitoring information. This study used remote sensing interpretation to invert the chlorophyll-a concentration in 131 images of Zipingpu Reservoir from 2013 to 2021, and analyzed the spatiotemporal characteristics of algal blooms. Partial least squares-structural equation modeling was used to identify the environmental influencing factors of algal blooms. The results showed that the average chlorophyll-a concentration in the reservoir was 4.49 mg/m, and the frequency of algal blooms was 28%. The maximum area of algal blooms shows a significant increase trend in the interannual (increase by 0.05%/yr in the proportion of water surface area), and the average blooms area shows a weaker increase trend (0.01%/yr). The prone period of algal bloom is from April to August every year. The solar duration and wind speed had significant direct positive effects on the maximum and average algal bloom area, which was the similar effects in different years and months (path coefficient exceeds 0.44). TP also has a significant direct positive effect on the average algal bloom area between different years (path coefficient of 0.30). The suitable meteorological factors level making the bloom-prone period from April to August, the prevailing westerly and southerly winds provide transport for the aggregation of phytoplankton and algal blooms outbreak in the northeastern waters. This study expand the monitoring frequency and spatial information of algal blooms, which provided a reference for young reservoir management and prevention of blooms.
