| The algal blooms problem caused by eutrophication of lakes has seriously affected the utilization and protection of freshwater resources,hence the rapid,comprehensive and accurate monitoring of algal blooms information is of great significance for the governance of water environment.Chaohu Lake,located in the Yangtze River Delta Economic Zone,is an important channel for the cross-basin water diversion project of "River Diving from Yangtze-Huaihe River",which has great significance for economic and social development and far-reaching ecological value.In recent years,with the rapid development of aquaculture,tourism,shipping and other industries in the Chaohu Lake Basin,as well as the rapid increase of urban construction and human activities,cyanobacteria blooms frequently break out,seriously affecting the ecological environment of the water area,damaging the ecological landscape of the water area,and affecting human production and life.Therefore,it is of great significance for the scientific prevention and control of algal blooms in Chaohu Lake to realize the monitoring of cyanobacteria blooms in Chaohu Lake in a long time sequence,to reveal the temporal and spatial variation rules of cyanobacteria blooms in Chaohu Lake,it is of great significance for scientific prevention and control of algal blooms in Chaohu Lake to analyze the meteorological conditions of cyanobacteria blooms in Chaohu Lake outbreak and explore the early warning mechanism of cyanobacteria blooms in Chaohu Lake outbreak risk.Taking Lake Chaohu as the research area,this article uses multi-source optical remote sensing images and spatio-temporal fusion technology to reveal the spatio-temporal change trends of algal blooms during the year of 2009 to 2018,by employing band fusion method and supervised classification-based blooms extraction method,furthermore,use of binary Logistic nonlinear regression probability model,combining the meteorological conditions during the blooms occurrence period and the remote sensing monitoring information of the blooms,a probability prediction model for the outbreak risk of cyanobacteria blooms in Chaohu Lake was constructed to realize the prediction of the occurrence probability of algal blooms in Chaohu Lake through meteorological data,the above research aims to provide data and method support for remote sensing monitoring of inland water bodies in China,provide technical support for early warning and control of water blooms,and provide theoretical basis and reference value for the management of eutrophic lakes in China in the future.The main conclusions are as follows:(1)Temporal and spatial characteristics of cyanobacteria blooms in Chaohu Lake with long time series(2009-2018):(1)Degree of algal blooms: The cyanobacteria blooms in Chaohu Lake were mainly sporadic and partial blooms,and the algal blooms in the whole lake remained at zero state,in many years,the proportion of local blooms was higher than that of sporadic blooms,and the change trend of local blooms was the most significant.(2)The algal blooms outbreak first time and duration: From 2009 to 2013,the onset time cyanobacteria blooms in Chaohu Lake was delayed year by year,in addition,the year 2015 was the earliest year of algal blooms in Chaohu Lake outbreak in the past decade,the duration of blooms was prolonged year by year from 2009 to 2012,and the duration of blooms in 2014 was the longest,on the whole,the duration of algal blooms in Chaohu Lake basically increased at first and then decreased.(3)Seasonal characteristics of algal blooms: Chaohu Lake has strong seasonal changes of algal blooms,with severe blooms in summer and autumn,relatively low blooms in winter and spring,and great differences in blooms in summer and winter half year,among which the difference is most significant in 2018.(4)Interannual outbreak frequency of algal blooms: According to ten years algal blooms outbreak whole frequency,west high frequency in Chaohu Lake,algal blooms outbreaks and main west high frequency outbreaks in Chaohu Lake area is located in the northwest,five years after blooms outbreak frequency higher than the previous five years,from the perspective of the frequency of algal blooms in each of the outbreak,the water off the coast of China,2011,in the higher frequency,frequency of the outbreak in 2014,the water of the southwest China,2016 new blooms high-risk areas in eastern and central regions,2017 and2018,compared with previous years,high frequency area of the outbreak.(5)Spatial distribution characteristics of algal blooms and their causes: Cyanobacteria blooms in Chaohu Lake are mainly distributed in the half,and half distribution the biggest lake in northwest,one of the reasons is that the land types along the northwest coast of Chaohu Lake are mainly urban construction land and cultivated land,secondly,southeast wind is prevailing in Chaohu Lake region,in addition,the algal blooms in Chaohu Lake showed a trend of zonal distribution,which was related to the runoff around the lake.(2)Results of risk prediction model for algal blooms in Chaohu Lake outbreak:The model was tested,and it was found that the independent variables of the four meteorological factors,daily average temperature,sunshine duration,average daily precipitation in the previous five days and average daily wind speed,were relatively appropriate,and the correlation between meteorological factors and the occurrence of algal blooms was statistically significant.Moreover,all the indicators of the model met the requirements of the model,and the prediction accuracy was as high as 87.52%.Further analysis of the model prediction results shows that after rainy days and long sunshine hours,the probability of algal blooms in Chaohu Lake is the highest.In addition,low wind speed and suitable temperature are also important conditions affecting the probability of algal blooms,in which sunshine hours are the dominant meteorological factors affecting the probability of algal blooms. |
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