Monitoring the particulate phosphorus concentration of inland waters on the Yangtze Plain and understanding its relationship with driving factors based on OLCI data.

Tracking the spatiotemporal dynamics of particulate phosphorus concentration (CPP) and understanding its regulating factors is essential to improve our understanding of its impact on inland water eutrophication. However, few studies have assessed this in eutrophic inland lakes, owing to a lack of suitable bio-optical algorithms allowing the use of remote sensing data. Herein, a novel semi-analytical algorithm of CPP was developed to estimate CPP in lakes on the Yangtze Plain, China. The independent validations of the proposed algorithm showed a satisfying performance with the mean absolute percentage error and root mean square error less than 27% and 27 µg/L, respectively. The Ocean and Land Color Instrument observations revealed a remarkable spatiotemporal heterogeneity of CPP in 23 lakes on the Yangtze Plain from 2016 to 2020, with the lowest value in December (62.91 ± 34.59 µg/L) and the highest CPP in August (114.9 ± 51.69 µg/L). Among the 23 examined lakes, the highest mean CPP was found in Lake Poyang (124.58 ± 44.71 µg/L), while the lowest value was found in Lake Qiandao (33.51 ± 4.71 µg/L). Additionally, 13 lakes demonstrated significant decreasing or increasing trends (P < 0.05) of annual mean CPP during the observation period. The driving factor analysis revealed that four natural factors (wind speed, air temperature, precipitation, and sunshine duration) and two anthropogenic factors (the normalized difference vegetation index and nighttime light) combined explained more than 91% of the variation in CPP, while the impacts of these factors on CPP showed considerable differences among lakes. This study offered a novel and scalable algorithm for the study of the spatiotemporal variation of CPP in inland waters and provided new insights into the regulating factors in water eutrophication.

Tempo-spatial dynamics of water quality and its response to river flow in estuary of Taihu Lake based on GOCI imagery.

Knowledge of tempo-spatial dynamics of water quality and its response to river flow is important for the management of lake water quality because river discharge associated with rainstorms can be an important source of pollutants to the estuary. Total phosphorus (TP), chlorophyll a (Chl-a), and total suspended matter (TSM) are important indexes of water quality and important factors influencing eutrophication and algal blooms. In this study, remote sensing was used to monitor these indexes to investigate the effects of river discharge on the estuary of Taihu Lake by the largest inflow river which is Chendong River using a total of 136 Geostationary Ocean Color Images (GOCI). In situ datasets collected during the four cruise experiments on Taihu Lake between 2011 and 2015 were used to develop the TP, Chl-a, and TSM inversion models based on simple empirical algorithms: 154 points for TP (mg/L), 114 for Chl-a (µg/L), and 181 for TSM (mg/L). The spatial and temporal changes of the concentration of the three parameters in the Chendong River estuary were analyzed by combining the GOCI data, the flow of the Chendong River, and meteorological data throughout the year in 2014. The several key findings are as follows: (1) In summer and autumn, TP, Chl-a, and TSM contents were significantly higher than in winter and spring. TP and Chl-a have a few similar distribution characteristics. And organic suspended matter in summer was the main reason for the increase of the TSM concentration. (2) The severe surface erosion in the rivers cannot be ignored; the high erodibility is an important factor in the increase of TP and TSM concentrations in the estuary. The concentration of the water quality parameter showed exponential decay with distance from the shore. The concentration decreased slowly after 12 km and then remained essentially constant. (3) TP content in the Chendong River estuary decreased under steady flow inputs and dramatically increased when the flow became large. The increase in Chl-a content was linked to higher levels of TP and good weather conditions after the rain event. Higher flow rates mainly play a dilution role for the Chl-a concentration. Erosion of the surface soil via rainfall is a major source of TSM to the estuary. This paper firstly analyzes tempo-spatial dynamics of water quality and its response to river flow in estuary of Taihu Lake, helps to further understand the impact of river input on lake water quality, and is important for lake eutrophication.

[Inversion Model and Daily Variation of Total Phosphorus Concentrations in Taihu Lake Based on GOCI Data].

The TP concentration is an important index of water quality and an important influencing factor of eutrophication and algae blooms. Remote sensing technology has advantages of wide scope and high time limited efficacy. Monitoring the concentration of TP by satellite remote sensing is important for the study of water quality and eutrophication. In situ datasets collected during the three times of experiments in Taihu Lake between 2013 and 2014 were used to develop the TP inversion model based on GOCI data. The GOCI data in spring, summer, autumn and winter in 2014 were selected to analyze the time and space changes of TP concentration in Taihu Lake. The results showed that the TP algorithm was built up based on the variables, which was to use the eight band combination of GOCI data as variable, and build model using Multi factor linear regression method. The algorithm achieved more accurate TP estimation with R² = 0.898, MAPE = 14.296%, RMSE = 0.026 mg · L⁻¹. Meantime, a analysis on the precision of the model by using the measured sample points and the synchronous satellite images with MAPE = 33.642%, 22.551%, RMSE = 0.076 mg · L⁻¹, 0.028 mg · L⁻¹ on August 5, 2014 and October 24, 2014. Through the analysis of the 30 images on the four days of the four seasons, it showed that the absolute concentration of total phosphorus was different in different seasons. But temporal and spatial distribution of total phosphorus concentration was similar in the morning and afternoon. In spatial distribution, the TP concentration in Meiliang Bay, Zhushan Bay, Gonghu Bay, Xiaomei Port and Changdou Port in the southwest coast was at a continuously high position. The TP concentration change in different regions was influenced by wind direction, wind speed and other factors. The TP concentration highest in the morning, and then gradually decreased, this phenomenon reflected that the TP concentration was affected by temperature and light.