Study On The Monitoring Of Cyanobacterial Blooms In Taihu By Remote Sensing And How Surface Wind Influence Its Distribution

In recent years, frequent outbreaks of cyanobacteria blooms in Taihu have posed a great threat to the economic development of Wuxi and Suzhou and the safety of drinking water for residents, which have attracted wide attention of all levels of management departments and the social from all walks of life. This study is based on HJ-l satellite multispectral (CCD) data, the objective is to explore the establishment of a fast, simple and practical technology for cyanobacteria bloom information recognition and extraction in Taihu, then to realize the spatial and temporal characteristics of the outbreak and the dynamic monitoring of cyanobacteria bloom on this basis. In addition, we use the WRF3.5.1model to study how instantaneous wind field on the near surface can affect the cyanobacteria bloom. The main results are as follows:(1) Getting reflectivity information of Taihu through preprocessing for HJ-l CCD data. On the reflectance image of Taihu, due to the remarkable differences between cyanobacteria bloom and background water’s spectrum and the lake’s surface type is single, we can use a single band of gray scale display, single band color transform and multiband color transform to realize the visual interpretation for cyanobacteria bloom. An empirical inversion model for chlorophyll-a is built, the threshold of0.075mg/L of chlorophyll-a can accurately extract the cyanobacteria bloom information, but the empirical model’s generality and portability are not conducive to the fast, accurate and operational monitoring of cyanobacterial blooms; and then, by comparing the effect of ratio vegetation index (RVI), normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) for the extraction of cyanobacteria bloom, we found that as for HJ-1CCD data, NDVI has the best effect and it is a powerful way for cyanobacteria bloom monitoring by remote sensing.(2) Using changing information detection technology can realize the dynamic monitoring for cyanobacteria bloom, which provides scientific basis for determining its distribution range and future trends. By analyzing the images of cyanobacteria bloom of Taihu from2012to2013, we found that in spring and winter the outbreak times are less, only accounted for25%of the total outbreak times in recent two years, then summer and autumn is the peak of the outbreak, of which autumn is also the most serious outbreak season; most of the cyanobacteria blooms in recent two years are sporadic and local outbreak, the outbreak frequency gradually increased from the southeast to the northwest area.(3) The area and distribution of cyanobacteria bloom show rapid response to the changes of near surface wind, the smaller wind speed (less than3m/s) in favor of cyanobacteria particles agglomeration and floating forward the windward coast then accumulate to form bloom, if the wind speed exceeds a certain critical value (about4m/s), cyanobacteria particles are not easy to float and under the control of wave and the mean circulation, they will be homogeneously mixed throughout the water column and not easy to cause bloom.