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Long-term monitoring particulate composition change in the Great Lakes using MODIS data
Water Research ( IF 11.4 ) Pub Date : 2022-08-01 , DOI: 10.1016/j.watres.2022.118932
Jiafeng Xu 1 , Huaiqing Liu 1 , Jie Lin 2 , Heng Lyu 3 , Xianzhang Dong 1 , Yunmei Li 3 , Honglei Guo 1 , Huaijing Wang 1
Affiliation  

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±0.76 µg/mg), while Lake Erie had the lowest average Chla/TSS values (2.93±0.76 µg/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 variation 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.



中文翻译:

使用 MODIS 数据长期监测五大湖的颗粒成分变化

颗粒成分为了解水下光场和初级生产力的变化提供了重要信息。在这项研究中,基于中分辨率成像光谱仪 (MODIS) 图像上 678 nm 和 748 nm 处的瑞利校正反射率的半解析算法用于估计叶绿素 a 与总悬浮固体 (Chla/TSS) 的比率,其表征五大湖的颗粒成分。获得了2000-2020年五大湖区Chla/TSS的长期时空特征。结果表明,苏必利尔湖的 Chla/TSS 平均值最高(5.79±0.76 µg/mg),而伊利湖的 Chla/TSS 平均值最低(2.93±0.76 µg/mg)。Mann-Kendall 检验表明五大湖区 Chla/TSS 均呈上升趋势,尤其是在密歇根湖,88.23% 的像素呈现出明显的增长趋势。气候和水文因素主导Chla/TSS的年内变化,贡献率在71.47%~92.54%之间。通过对 Chla/TSS 年变化规律的分析发现,风速对 Chla/TSS 年变化的贡献很小。温度变化在苏必利尔湖和安大略省 Chla/TSS 的年际变化中起主要作用;径流和沉降是休伦湖和密歇根州的主要贡献者,而农田主导了伊利湖的 Chla/TSS 年际变率。此外,春季 Chla/TSS 的显着低值有可能预测伊利湖西部水华的发生,

更新日期:2022-08-01
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