Long-term dynamics and drivers of particulate phosphorus concentration in eutrophic lake Chaohu, China.

Particulate phosphorus (PP) plays an important biological role in the eutrophication process, and is thus an important water quality parameter for assessing climatic change and anthropogenic activity factors that affect aquatic ecosystems. Here, we used 20-year Moderate Resolution Imaging Spectroradiometer (MODIS) data to explore the patterns and trends of PP concentration (CPP) in eutrophic Lake Chaohu based on a new empirical model. The validation results indicated that the developed model performed satisfactorily in estimating CPP, with a mean absolute percentage error of 31.89% and root mean square error of 0.022 mg/L. Long-term MODIS observations (2000-2019) revealed that the CPP of Lake Chaohu has experienced an overall increasing trend and distinct spatiotemporal heterogeneity. The driving factor analysis revealed that the chemical fertilizer consumption, municipal wastewater, industrial sewage, precipitation, and air temperature were the five potential driving factors and collectively explained more than 81% of the long-term variation in CPP. This study provides the long-term datasets of CPP in inland waters and new insights for future water eutrophication control and restoration efforts.

An improved algorithm for estimating the Secchi disk depth of inland waters across China based on Sentinel-2 MSI data.

Accurate remote sensing of the Secchi disk depth (ZSD) in waters is beneficial for large-scale monitoring of the aquatic ecology of inland lakes. Herein, an improved algorithm (termed as ZSD20 in this work) for retrieving ZSD was developed from field measured remote sensing data and is available for various waters including clear waters, slightly turbid waters, and highly turbid waters. The results show that ZSD20 is robust in estimating ZSD in various inland waters. After further validation with an independent in situ dataset from 12 inland waters (0.1 m < ZSD < 18 m), the developed algorithm outperformed the native algorithm, with the mean absolute square percentage error (MAPE) reduced from 32.8 to 19.4%, and root mean square error (RMSE) from 0.87 to 0.67 m. At the same time, the new algorithm demonstrates its generality in various mainstreaming image data, including Ocean and Land Color Instrument (OLCI), Geostationary Ocean Color Imager (GOCI), and Moderate Resolution Imaging Spectroradiometer (MODIS). Finally, the algorithm's application was implemented in 410 waters of China based on Sentinel-2 MSI imagery to elucidate the spatiotemporal variation of water clarity during 2015 and 2021. The new algorithm reveals great potential for estimating water clarity in various inland waters, offering important support for protection and restoration of aquatic environments.

Long-term remote observations of particulate organic phosphorus concentration in eutrophic Lake Taihu based on a novel algorithm.

Monitoring the long-term spatiotemporal variations in particulate organic phosphorus concentration (CPOP) is imperative for clarifying the phosphorus cycle and its biogeochemical behavior in waters. However, little attention has been devoted to this owing to a lack of suitable bio-optical algorithms that allow the application of remote sensing data. In this study, based on Moderate Resolution Imaging Spectroradiometer (MODIS) data, a novel absorption-based algorithm of CPOP was developed for eutrophic Lake Taihu, China. The algorithm yielded a promising performance with a mean absolute percentage error of 27.75% and root mean square error of 21.09 µg/L. The long-term MODIS-derived CPOP demonstrated an overall increasing pattern over the past 19 years (2003-2021) and a significant temporal heterogeneity in Lake Taihu, with higher value in summer (81.97 ± 3.81 µg/L) and autumn (82.07 ± 3.8 µg/L), and lower CPOP in spring (79.52 ± 3.81 µg/L) and winter (78.74 ± 3.8 µg/L). Spatially, relatively higher CPOP was observed in the Zhushan Bay (85.87 ± 7.5 µg/L), whereas the lower value was observed in the Xukou Bay (78.95 ± 3.48 µg/L). In addition, significant correlations (r > 0.6, P < 0.05) were observed between CPOP and air temperature, chlorophyll-a concentration and cyanobacterial blooms areas, demonstrating that CPOP was greatly influenced by air temperature and algal metabolism. This study provides the first record of the spatial-temporal characteristics of CPOP in Lake Taihu over the past 19 years, and the CPOP results and regulatory factors analyses could provide valuable insights for aquatic ecosystem conservation.