Abstract
Algal blooms in eutrophic lakes have been a global issue to environmental ecology. Although great progress on prevention and control of algae have been made in many lakes, systematic research on long-term temporal-spatial dynamics and drivers of algal blooms in a plateau Lake Dianchi is so far insufficient. Therefore, the algae pixel-growing algorithm (APA) was used to accurately identify algal bloom areas at the sub-pixel level on the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 2000 to 2018. The results showed that algal blooms were observed all year round, with a reduced frequency in winter–spring and an increased frequency in summer–autumn, which lasted a long time for about 310–350 days. The outbreak areas were concentrated in 20–80 km2 and the top three largest areas were observed in 2002, 2008, and 2017, reaching 168.80 km2, 126.51 km2, and 156.34 km2, respectively. After deriving the temporal-spatial distribution of algal blooms, principal component analysis (PCA) and redundancy analysis (RDA) were applied to explore the effects of meteorological, water quality and human activities. Of the variables analyzed, mean temperature (Tmean) and wind speed (WS) were the main drivers of daily algal bloom areas and spatial distribution. The precipitation (P), pH, and water temperature (WT) had a strong positive correlation, while WS and sunshine hours (SH) had a negative correlation with monthly maximum algal bloom areas and frequency. Total nitrogen (TN) and dissolved oxygen (DO) were the main influencing factors of annual frequency, initiation, and duration of algal blooms. Also, the discharge of wastewater and the southwest and southeast monsoons may contribute to the distribution of algal blooms mainly in the north of the lake. However, different regions of the lake show substantial variations, so further zoning and quantitative joint studies of influencing factors are required to more accurately understand the true mechanisms of algae in Lake Dianchi.
Highlights
Since ancient times, human civilization has depended on water
We assumed that there were only pure-algae and none-algae pixels existing in Landsat images, we use floating algae index (FAI), which has been widely used with high precision [13,41,43], to extract algal bloom areas
The spatial distributions of these six comparison images were roughly the same (Figure 3), there was a little inconsistent distribution of algal bloom area in the north of the lake in 08/04/2005, which may be related to the difference of transit time on Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua and Landsat
Summary
Human civilization has depended on water. Lake Dianchi Basin is an area with a high population density and the highest degree of industrialization and urbanization [1], most developed economy, and most dynamic social development in Yunnan Province of China [2]. Based on the above-recognized information, studies on algal blooms in Lake Dianchi have gradually increased in recent years [5,17,18,21,22,23,24,25,26]. Compared with other nonlinear identification methods such as the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), floating algae index (FAI) is not affected by the aerosol thickness and observation angle, which can penetrate thin clouds more effectively This index has been widely applied to monitor algal blooms [32,35,39,40,41,42,43]. These images were processed by the same atmospheric correction to get Rrc, which followed the calculation requirements and steps strictly of the floating algae index (FAI) by Hu et al [40,49]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
