Chlorophyll-a plays an essential biochemical role in the eutrophication process, and is widely considered an important water quality indicator for assessing human activity’s effects on aquatic ecosystems. Herein, 20 years of moderate resolution imaging spectroradiometer (MODIS) data were applied to investigate the spatiotemporal patterns and trends of chlorophyll-a concentration (Chla) in the eutrophic Lake Taihu, based on a new empirical model. The validated results suggested that our developed model presented appreciable performance in estimating Chla, with a root mean square error (MAPE) of 12.95 μg/L and mean absolute percentage error (RMSE) of 29.98%. Long-term MODIS observations suggested that the Chla of Lake Taihu experienced an overall increasing trend and significant spatiotemporal heterogeneity during 2002–2021. A driving factor analysis indicated that precipitation and air temperature had a significant impact on the monthly dynamics of Chla, while chemical fertilizer consumption, municipal wastewater, industrial sewage, precipitation, and air temperature were important driving factors and together explained more than 81% of the long-term dynamics of Chla. This study provides a 20 year recorded dataset of Chla for inland waters, offering new insights for future precise eutrophication control and efficient water resource management.

In order to expand the network capacity and reduce the blocking rate of services, this paper uses the signal overlapping technology to double the number of available frequency slots in the Elastic Optical Networks (EONs). On this basis, the Routing and Spectrum Allocation (RSA) problem is studied. Considering the time loss caused by signal overlapping technology, this paper designs an RSA algorithm for time-frequency allocation on EONs based on signal overlapping. This algorithm will select the route with the smallest lost time slot. In this paper, the feasibility and low blocking rate of the algorithm are verified by simulation.