Long-term monitoring particulate composition change in the Great Lakes using MODIS data
作者：Xu, Jiafeng; Liu, Huaiqing; Lin, Jie; 等
Particulate composition provides important information for understanding the changes in underwater light fields and primary productivity. In this study, a semianalytical algorithm, based on Rayleigh-corrected reflectance at 678 nm and 748 nm on Moderate Resolution Imaging Spectroradiometer (MODIS) images was used to estimate the ratio of chlorophyll a to total suspended solids (Chla/TSS), which characterizes the particulate composition of the Great Lakes. The long-term spatial and temporal characteristics of Chla/TSS in the Great Lakes from 2000 to 2020 were obtained. The results demonstrated that Lake Superior had the highest average Chla/TSS values (5.79 & PLUSMN;0.76 mu g/mg), while Lake Erie had the lowest average Chla/TSS values (2.93 & PLUSMN;0.76 mu g/mg). The Mann -Kendall test showed that the Chla/TSS of the Great Lakes all showed an increasing trend, notably in Lake Michigan, with 88.23% pixels showing significant increasing trend. Climatic and hydrological factors dominated the intra-annual variation of Chla/TSS, with contribution rates ranging from 71.47% to 92.54%. Through the annual Chla/TSS change pattern analysis, it was found that the contribution of wind speed to the annual vari-ation in Chla/TSS was slight. Changes in temperature played a major role in the interannual variability of Chla/ TSS in Lake Superior and Ontario; runoff and settlement were the major contributors in Lake Huron and Michigan, while cropland dominated the Chla/TSS interannual variability in Lake Erie. Furthermore, the significantly low values of Chla/TSS in spring had the potential to predict the occurrence of blooms in western Lake Erie, and the spatial distribution of Chla/TSS could help predict the location of blooms in the next few days.
（来源：Water Research 出版年：2022 DOI：10.1016/j.watres.2022.118932）