Abstract

AbstractMany lakes in China suffer from algal bloom problems. However, the spatial and temporal distribution of lacustrine algal blooms at the national scale has not been well characterized. Here, we developed an automated algal bloom surface scums (hereafter referred to as algal bloom) detection algorithm for Moderate‐Resolution Imaging Spectroradiometer (MODIS) images based on a normalized floating algal index and the Commission on Illumination colorimetry system. This algorithm was then applied to 35,556 daily MODIS images acquired between 2003 and 2020 to hindcast the spatial and temporal dynamics of lacustrine algal blooms in 171 lakes in China. The results show that 103 (60.2%) of the examined lakes have been affected by algal blooms over the past two decades, and the bloom occurrence in 95 lakes showed an increasing trend. The prevailing increasing trends of algal blooms in Chinese lakes were also manifested by an earlier onset time and prolonged potential occurrence period. We found that approximately 80% of the historical algal blooms occurred under calm water surfaces (wind speed <3 m/s) and high temperatures (>16°C), and we revealed positive correlations between bloom occurrence and fertilizer use. We further demonstrated that the increasing trends in algal blooms were highly linked to recent increases in air temperature. The results here not only highlight the severe lacustrine algal bloom problems in China but also provide important baseline information for lake management and restoration efforts for the government.

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