Water clarity(Secchi disk depth, Z_(SD)) and Forel-Ule Index(FUI) are critical ecological indicators for assessing water quality. Although satellite remote sensing serves as a vital tool for large-scale and long-term ...Water clarity(Secchi disk depth, Z_(SD)) and Forel-Ule Index(FUI) are critical ecological indicators for assessing water quality. Although satellite remote sensing serves as a vital tool for large-scale and long-term water quality monitoring,low accuracy, coarse resolution, and incomplete spatial coverage of existing satellite Z_(SD) and FUI products hindered the reliable ecological assessment of water quality. Here, a long-term(2003-2023) satellite dataset of monthly Z_(SD) and FUI was developed by applying the advanced high-accuracy retrieval algorithms and reconstruction method to 35 546Moderate-resolution Imaging Spectroradiometer(MODIS) images over China coastal waters. The new dataset exhibited superior performance compared to the existing one, in terms of higher accuracy(Mean Absolute Percentage Error,MAPE = 28.89% for Z_(SD) and MAPE = 34.46% for FUI), spatio-temporal resolution(monthly, 1 km), and spatial coverage(99.53%), with the most significant improvement found in the nearshore turbid waters. By leveraging this dataset, the ecological impact of human activities on water quality was accurately revealed, as indicated by the significant Z_(SD) improvements during terrestrial pollution control, which was misinterpreted by previous satellite products.Besides, natural factor-induced water quality variability was also successfully captured, particularly the seasonal dynamics of suspended sediment plumes in the East China Sea. The new dataset and adopted methods may provide essential support for the accurate monitoring, ecological assessment, and sustainable management of marine ecosystems.展开更多
Rivers provide key ecosystem services that are inherently engineered and optimized to meet the strategic and economic needs of countries around the world.However,limited water quality records of a full river continuum...Rivers provide key ecosystem services that are inherently engineered and optimized to meet the strategic and economic needs of countries around the world.However,limited water quality records of a full river continuum hindered the understanding of how river systems response to the multiple stressors acting on them.This study highlights the use of Sentinel-2 Multi-Spectral Imager(MSI)data to monitor changes in water color in two optically complex river systems:the Yangtze and Danube using the Forel-Ule Index(FUI).FUI divides water color into 21 classes from dark blue to yellowish brown stemming from the historical Forel-Ule water color scale and has been promoted as a useful indicator showing water turbidity variations in water bodies.The results revealed contrasting water color patterns in the two rivers on both spatial and seasonal scales.Spatially,the FUI of the Yangtze River gradually increased from the upper reaches to the lower reaches,while the FUI of the Danube River declined in the lower reaches,which is possibly due to the sediment sink effect of the Iron Gate Dams.The regional FUI peaks and valleys observed in the two river systems have also been shown to be related to the dams and hydropower stations along them.Seasonally,the variations of FUI in both systems can be attributed to climate seasonality,especially precipitation in the basin and the water level.Moreover,land cover within the river basin was possibly a significant determinant of water color,as higher levels of vegetation in the Danube basin were associated with lower FUI values,whereas higher FUI values and lower levels of vegetation were observed in the Yangtze system.This study furthers our knowledge of using Sentinel-2 MSI to monitor and understand the spatial-temporal variations of river systems and highlights the capabilities of the FUI in an optically complex environment.展开更多
基金The National Key Research and Development Program of China under contract No.2023YFB3905305。
文摘Water clarity(Secchi disk depth, Z_(SD)) and Forel-Ule Index(FUI) are critical ecological indicators for assessing water quality. Although satellite remote sensing serves as a vital tool for large-scale and long-term water quality monitoring,low accuracy, coarse resolution, and incomplete spatial coverage of existing satellite Z_(SD) and FUI products hindered the reliable ecological assessment of water quality. Here, a long-term(2003-2023) satellite dataset of monthly Z_(SD) and FUI was developed by applying the advanced high-accuracy retrieval algorithms and reconstruction method to 35 546Moderate-resolution Imaging Spectroradiometer(MODIS) images over China coastal waters. The new dataset exhibited superior performance compared to the existing one, in terms of higher accuracy(Mean Absolute Percentage Error,MAPE = 28.89% for Z_(SD) and MAPE = 34.46% for FUI), spatio-temporal resolution(monthly, 1 km), and spatial coverage(99.53%), with the most significant improvement found in the nearshore turbid waters. By leveraging this dataset, the ecological impact of human activities on water quality was accurately revealed, as indicated by the significant Z_(SD) improvements during terrestrial pollution control, which was misinterpreted by previous satellite products.Besides, natural factor-induced water quality variability was also successfully captured, particularly the seasonal dynamics of suspended sediment plumes in the East China Sea. The new dataset and adopted methods may provide essential support for the accurate monitoring, ecological assessment, and sustainable management of marine ecosystems.
基金sponsored by the Dragon 5 Cooperation(grant number 59193)the International Partnership Program of Chinese Academy of Sciences(grant number 313GJHZ2022085FN)+1 种基金the European Union’s Horizon Europe research and innovation programme project DANUBE4all(grant number 101093985)Fund of the International Research Center of Big Data for Sustainable Development Goals(Grant No.CBAS2022DF004).
文摘Rivers provide key ecosystem services that are inherently engineered and optimized to meet the strategic and economic needs of countries around the world.However,limited water quality records of a full river continuum hindered the understanding of how river systems response to the multiple stressors acting on them.This study highlights the use of Sentinel-2 Multi-Spectral Imager(MSI)data to monitor changes in water color in two optically complex river systems:the Yangtze and Danube using the Forel-Ule Index(FUI).FUI divides water color into 21 classes from dark blue to yellowish brown stemming from the historical Forel-Ule water color scale and has been promoted as a useful indicator showing water turbidity variations in water bodies.The results revealed contrasting water color patterns in the two rivers on both spatial and seasonal scales.Spatially,the FUI of the Yangtze River gradually increased from the upper reaches to the lower reaches,while the FUI of the Danube River declined in the lower reaches,which is possibly due to the sediment sink effect of the Iron Gate Dams.The regional FUI peaks and valleys observed in the two river systems have also been shown to be related to the dams and hydropower stations along them.Seasonally,the variations of FUI in both systems can be attributed to climate seasonality,especially precipitation in the basin and the water level.Moreover,land cover within the river basin was possibly a significant determinant of water color,as higher levels of vegetation in the Danube basin were associated with lower FUI values,whereas higher FUI values and lower levels of vegetation were observed in the Yangtze system.This study furthers our knowledge of using Sentinel-2 MSI to monitor and understand the spatial-temporal variations of river systems and highlights the capabilities of the FUI in an optically complex environment.
