Decline of suspended particulate matter concentrations in Lake Taihu from 1984 to 2020: observations from Landsat TM and OLI.

Suspended particulate matter (SPM) affects the optical properties of water, which can be used as a marker of water quality. The water quality of Lake Taihu has changed immensely since the 1980's. However, despite the link between water quality and SPM, long-term systematic studies on SPM have not been conducted in this lake. Here, we used Landsat-5 TM and Landsat-8 OLI data to model changes in the SPM concentration of Lake Taihu from 1984 to 2020. Various models were generated, calibrated, and finally validated using in situ SPM, remote sensing reflectance (Rrs) data, and synchronous satellite data. After comparing various commonly used models, it was found that the exponential model based on band combination [Rrs(red) + Rrs(NIR)/Rrs(green)] had the highest accuracy, with an average unbiased relative error greater than 35%. Subsequently, the SPM products of Lake Taihu during 1984-2020 were generated. Overall, the SPM concentration showed a downward trend over the study period, which might be primarily attributable to a decline in wind speed. These findings may assist in the conservation of Lake Taihu and its associated water resources.

Measurement of Water Leaving Reflectance Using a Digital Camera Based on Multiple Reflectance Reference Cards.

With the development of citizen science, digital cameras and smartphones are increasingly utilized in water quality monitoring. The smartphone application HydroColor quantitatively retrieves water quality parameters from digital images. HydroColor assumes a linear relationship between the digital pixel number (DN) and incident radiance and applies a grey reference card to derive water leaving reflectance. However, image DNs change with incident light brightness non-linearly, according to a power function. We developed an improved method for observing and calculating water leaving reflectance from digital images based on multiple reflectance reference cards. The method was applied to acquire water, sky, and reflectance reference card images using a Cannon 50D digital camera at 31 sampling stations; the results were validated using synchronously measured water leaving reflectance using a field spectrometer. The R2 for the red, green, and blue color bands were 0.94, 0.95, 0.94, and the mean relative errors were 27.6%, 29.8%, 31.8%, respectively. The validation results confirm that this method can derive accurate water leaving reflectance, especially when compared with the results derived by HydroColor, which systematically overestimates water leaving reflectance. Our results provide a more accurate theoretical foundation for quantitative water quality monitoring using digital and smartphone cameras.

Increase in chlorophyll-a concentration in Lake Taihu from 1984 to 2021 based on Landsat observations.

Lake Taihu, located in a densely populated and highly industrialized area in eastern China, has experienced dramatic changes in water quality since the reform and opening-up in the 1980s. Landsat data can be used to trace water quality changes over approximately 40 years. However, chlorophyll-a (Chla) estimation, which characterizes the trophic status, has not been thoroughly explored (especially in turbid water using wide bandwidth Landsat) due to the interference of suspended particulate matter (SPM) to Chla. In this study, we used Landsat TM/OLI for turbid water Chla inversion and to analyze the spatiotemporal variation of Chla in Lake Taihu for 38 years and its influencing factors. An optical classification algorithm based on Rrs(green)/Rrs(red) was used to exclude highly turbid waters dominated by SPM; Chla was estimated only in waters with low SPM. We constructed an exponential estimation model based on Rrs(NIR)/Rrs(red), and verified the accuracy of the model using the measured Chla synchronized with satellite data. The model was applied to Landsat images to calculate the Chla concentration in Lake Taihu during 1984-2021, and its spatiotemporal distribution patterns were further analyzed. Spatially, the Chla concentrations in the western and northern regions of Lake Taihu were higher than those in other regions, probably because these areas are estuaries with large exogenous pollutant discharge and more nutrients are imported from exogenous sources. Chla showed an overall significant upward trend from 1984 to 2021 probably because of temperature rise, wind speed reduction, and nutrient increase. The results of the spatial and temporal variation of Chla and the influencing factors in this study provide supporting data for eutrophication monitoring and management in Lake Taihu. The proposed Chla estimation method can be extended to assess the spatial and temporal distribution of eutrophication in other inland waters with similar optical properties.