| Popis: |
The occurrence of water blooms in reservoirs poses a serious threat to water safety, so the assessment of water bloom risk is crucial. In this study, we constructed a reservoir water bloom risk index (RWBRI) using the trophic state index (TSI), floating algae index (FAI), temperature, precipitation, and wind speed datasets, and estimated and validated the water bloom risk levels of three large-scale eutrophication reservoirs in Fujian Province, China, from 2019 to 2023 based on the Sentinel-2 MSI dataset at the pixel scale. The results showed that there is no positive correlation between the TSI and FAI parameters of the three reservoirs (the significance test coefficients for Shanzai Reservoir, Dongzhen Reservoir, and Shanmei Reservoir were −0.455**, −0.371**, and −0.049, respectively, and ** indicates that the reservoir passed the statistical significance test at the 0.01 significance level). The TSI of Shanmei Reservoir was less fluctuating and more stable than that of Shanzai Reservoir and Dongzhen Reservoir, but the average value of FAI was higher. The average value of water bloom risk in Shanzai Reservoir and Dongzhen Reservoirs is higher than Shanmei Reservoir (0.47, 0.46, and 0.41, respectively), but the trend of annual average changes indicates that the overall risk of Dongzhen Reservoir is decreasing, while the risk of Shanzai Reservoir and Shanmei Reservoir is increasing. Due to the influence of weather, the water bloom risk in spring and summer is higher than that in fall and winter in the three reservoirs, and the highest risk value usually occurs in summer. The high values in Shanzai Reservoir were mainly distributed in the two inlet channels in the northern and southwestern parts of the reservoir, the bank risk was higher than in the other areas of Dongzhen Reservoir, and the high value of the risk in Shanmei Reservoir was mainly distributed in the center of the reservoir. The RWBRI method can be used for water bloom risk identification in reservoirs with eutrophication trends by comparing it with four-hourly and monthly water quality level data. |
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