Qichun Liang

Aquatic macrophytes in lakes and rivers are highly sensitive to changes in water quality and ecological conditions. Satellite remote sensing of aquatic macrophyte distributions can map changes in freshwater ecosystem dynamics. However, macrophyte mapping by remote sensing is challenging in lakes dominated by algal blooms or with high turbidity. In this study, we mapped the composition and distribution of emergent/floating and submerged macrophytes in the large turbid and eutrophic Lake Taihu, China. We used a novel classification method and 16 y of MODIS images to map these data. The inter-annual trends in macrophyte distribution and cover show complex dynamics in this heavily-managed lake. The area occupied by emergent/floating macrophytes increased from 39.3 km² in 2000 to 90.3 km² in 2015 (a 230% increase), whereas the area dominated by submerged macrophytes decreased from 404.6 km² in 2001 to 167.5 km² in 2015 (a 59% decrease). We also used the annual date of initial macrophyte occurrence and growth period to examine temporal variation in species composition and biodiversity of macrophytes. Aquatic macrophytes in different parts of the lake responded differently to temporal trends in water quality (Secchi disk and nutrient concentrations), hydrology (water level), and meteorological data (daily temperature, precipitation, and h of sunlight). Changes in lake transparency occurred over the study period, reducing the availability of underwater solar irradiance. Light availability was the most influential local environmental factor for macrophyte dynamics. We also found that eutrophication control projects indirectly reduced lake ecosystem quality in some bays. These control projects included water transfers from the Yangtze River (dilution), aquaculture management actions, macrophyte removal, and dredging. Our findings suggest the species composition and area covered by aquatic macrophytes in this shallow lake are driven by multiple mechanisms. These results highlight that efforts to manage the increase in algal-dominated lake areas require a more complete understanding of the direct and indirect impacts of management activities. We also show that satellite-based remote sensing measurements of macrophyte spatial and temporal dynamics provide a useful indicator to evaluate the impacts of these activities.

Satellite remote sensing can be an effective alternative for mapping cyanobacterial scums and aquatic macrophyte distribution over large areas compared with traditional ship’s site-specific samplings. However, similar optical spectra characteristics between aquatic macrophytes and cyanobacterial scums in red and near infrared (NIR) wavebands create a barrier to their discrimination when they co-occur. We developed a new cyanobacteria and macrophytes index (CMI) based on a blue, a green, and a shortwave infrared band to separate waters with cyanobacterial scums from those dominated by aquatic macrophytes, and a turbid water index (TWI) to avoid interference from high turbid waters typical of shallow lakes. Combining CMI, TWI, and the floating algae index (FAI), we used a novel classification approach to discriminate lake water, cyanobacteria blooms, submerged macrophytes, and emergent/floating macrophytes using MODIS imagery in the large shallow and eutrophic Lake Taihu (China). Thresholds for CMI, TWI, and FAI were determined by statistical analysis for a 2010–2016 MODIS Aqua time series. We validated the accuracy of our approach by in situ reflectance spectra, field investigations and high spatial resolution HJ-CCD data. The overall classification accuracy was 86% in total, and the user’s accuracy was 88%, 79%, 85%, and 93% for submerged macrophytes, emergent/floating macrophytes, cyanobacterial scums and lake water, respectively. The estimated aquatic macrophyte distributions gave consistent results with that based on HJ-CCD data. This new approach allows for the coincident determination of the distributions of cyanobacteria blooms and aquatic macrophytes in eutrophic shallow lakes. We also discuss the utility of the approach with respect to masking clouds, black waters, and atmospheric effects, and its mixed-pixel effects.