Determination of the downwelling diffuse attenuation coefficient of lakewater with the sentinel-3A OLCI

The Ocean and Land Color Imager (OLCI) on the Sentinel-3A satellite, which was launched by the European Space Agency in 2016, is a new-generation water color sensor with a spatial resolution of 300 m and 21 bands in the range of 400-1020 nm. The OLCI is important to the expansion of remote sensing monitoring of inland waters using water color satellite data. In this study, we developed a dual band ratio algorithm for the downwelling diffuse attenuation coefficient at 490 nm (Kd(490)) for the waters of Lake Taihu, a large shallow lake in China, based on data measured during seven surveys conducted between 2008 and 2017 in combination with Sentinel-3A-OLCI data. The results show that: (1) Compared to the available Kd(490) estimation algorithms, the dual band ratio (681 nm/560 nm and 754 nm/560 nm) algorithm developed in this study had a higher estimation accuracy (N = 26, coefficient of determination (R2) = 0.81, root-mean-square error (RMSE) = 0.99m-1and mean absolute percentage error (MAPE) = 19.55%) and validation accuracy (N = 14, R2= 0.83, RMSE = 1.06 m-1and MAPE = 27.30%), making it more suitable for turbid inland waters; (2) A comparison of the OLCI Kd(490) product and a similar Moderate Resolution Imaging Spectroradiometer (MODIS) product reveals a high consistency between the OLCI and MODIS products in terms of the spatial distribution of Kd(490). However, the OLCI product has a smoother spatial distribution and finer textural characteristics than the MODIS product and contains notably higher-quality data; (3) The Kd(490) values for Lake Taihu exhibit notable spatial and temporal variations. Kd(490) is higher in seasons with relatively high wind speeds and in open waters that are prone to wind- and wave-induced sediment resuspension. Finally, the Sentinel-3A-OLCI has a higher spatial resolution and is equipped with a relatively wide dynamic range of spectral bands suitable for inland waters. The Sentinel-3B satellite will be launched soon and, together with the Sentinel-3A satellite, will form a two-satellite network with the ability to make observations twice every three days. This satellite network will have a wider range of application and play an important role in the monitoring of inland waters with complex optical properties

Time-series MODIS Image-based Retrieval and Distribution Analysis of Total Suspended Matter Concentrations in Lake Taihu (China)

Although there has been considerable effort to use remotely sensed images to provide synoptic maps of total suspended matter (TSM), there are limited studies on universal TSM retrieval models. In this paper, we have developed a TSM retrieval model for Lake Taihu using TSM concentrations measured in situ and a time series of quasi-synchronous MODIS 250 m images from 2005. After simple geometric and atmospheric correction, we found a significant relationship (R = 0.8736, N = 166) between in situ measured TSM concentrations and MODIS band normalization difference of band 3 and band 1. From this, we retrieved TSM concentrations in eight regions of Lake Taihu in 2007 and analyzed the characteristic distribution and variation of TSM. Synoptic maps of model-estimated TSM of 2007 showed clear geographical and seasonal variations. TSM in Central Lake and Southern Lakeshore were consistently higher than in other regions, while TSM in East Taihu was generally the lowest among the regions throughout the year. Furthermore, a wide range of TSM concentrations appeared from winter to summer. TSM in winter could be several times that in summer

A semi-analytical model for estimating total suspended matter in highly turbid waters

Total suspended matter (TSM) is related to water quality. High TSM concentrations limit underwater light availability, thus affecting the primary productivity of aquatic ecosystems. Accurate estimation of TSM concentrations in various waters with remote sensing technology is particularly challenging, as the concentrations and optical properties vary greatly among different waters. In this research, a semi-analytical model was established for Hangzhou Bay and Lake Taihu for estimating TSM concentration. The model construction proceeded in two steps. 1) Two indices of the model were calculated by deriving absorption and backscattering coefficients of suspended matter (ap(λ) and bbp(λ)) from the reflectance signal using a semi-analytical method. 2) The two indices were then weighted to derive TSM. The performance of the proposed model was tested using in situ reflectance and Geostationary Ocean Color Imager (GOCI) data. The derived TSM based on in situ reflectance and GOCI images both corresponded well with the in situ TSM with low mean relative error (32%, 41%), root mean square error (20.1 mg/L, 43.1 mg/L), and normalized root mean square error (33%, 55%). The model was further used for the slightly turbid Xin’anjiang Reservoir to demonstrate its applicability to derive ap(λ) and bbp(λ) in other water types. The results indicated that the form Rrs −1(λ1) − Rrs −1(λ2) could minimize the effect of CDOM absorption in deriving ap(λ) from the total absorption. The model exploited the different relationships between TSM concentration and multiband reflectance, thus improving the performance and application range in deriving TSM

Evaluation of the Influence of Aquatic Plants and Lake Bottom on the Remote-Sensing Reflectance of Optically Shallow Waters

Aquatic plants and lake bottoms in optically shallow waters (OSWs) wield great influence on reflectance spectra, resulting in the inapplicability of most existing bio-optical models for water colour remote sensing in lakes. Based on radiative transfer theory and measured spectra from a campaign for Lake Taihu in October 2008, absorption and backscattering coefficients were used to simulate the remote-sensing reflectance, which are considered to be reliable if matched to their measured counterparts. Several cases of measured spectra at different depths, Secchi disk depth transparency, and aquatic plant height and coverage were analyzed thoroughly for spectral properties. The contribution of aquatic plants was evaluated and compared with the measured and simulated remote-sensing reflectance values. This is helpful for removing the influence of aquatic plants and lake bottoms from the spectra and for constructing an improved chlorophyll a retrieval model for OSWs, such as that for Lake Taihu, China

Changes of water clarity in large lakes and reservoirs across China observed from long-term MODIS

Water clarity is a well-established first-order indicator of water quality and has been used globally by water regulators in their monitoring and management programs. Assessments of water clarity in lakes over large temporal and spatial scales, however, are rare, limiting our understanding of its variability and the driven forces. In this study, we developed and validated a robust Secchi disk depth (ZSD) algorithm for lakes across China based on two water color parameters, namely Forel-Ule Index (FUI) and hue angle α, retrieved from MODIS data. The MODIS ZSD model shows good results when compared with in-situ measurements from 17 lakes, with a 27.4% mean relative difference (MRD) in the validation dataset. Compared with other empirical ZSD models, our FUI and α-based model demonstrates improved performance and adaptability over a wide range of water clarity and trophic states. This algorithm was subsequently applied to MODIS measurements to provide a comprehensive assessment of water clarity in large lakes (N = 153) across China for the first time. The mean summer ZSD of the studied lakes between 2000 and 2017 demonstrated marked spatial and temporal variations. Spatially, the ZSD of large lakes presented a distinct spatial pattern of “high west and low east” over China. This spatial pattern was found to be associated with the significant differences in lake depth and altitude between west and east China while China's population, GDP, temperature, and precipitation distribution have also contributed to a certain extent. Temporally, the ZSD of most lakes increased during this period, with an overall mean rate of 3.3 cm/yr for all lakes. Here, 38.6% (N = 59) of the lakes experienced a significant increase in their ZSD value during the past 18 years while only 8.5% (N = 13) showed a significant decreasing trend. Significant increases in lake ZSD were observed in west China, which were found to correlate with the increase of air temperature and lake surface area. This is possibly a response of the lakes in west China to climate change. In the lake systems of east China, which are predominately used as a drinking water source, the increase in lake ZSD was found to be strongly correlated with changes in local GDP (gross domestic production), NDVI (normalized difference vegetation index) and lake surface area, suggesting a combined effect of the implemented management practices and climatic variability. The results of this study provide important information for water quality conservation and management in China, and also highlight the value of satellite remote sensing in monitoring water quality over lakes at a large scale and long-term

Inversion of inherent optical properties in optically complex waters using sentinel-3A/OLCI images: A case study using China\u27s three largest freshwater lakes

Inherent optical properties (IOPs) play an important role in underwater light field, and are difficult to estimate accurately using satellite data in optically complex waters. To study water quality in appropriate temporal and spatial scales, it is necessary to develop methods to obtain IOPs form space-based observation with quantified uncertainties. Field-measured IOP data (N = 405) were collected from 17 surveys between 2011 and 2017 in the three major largest freshwater lakes of China (Lake Chaohu, Lake Taihu, and Lake Hongze) in the lower reaches of the Yangtze River and Huai River (LYHR). Here we provide a case-study on how to use in-situ observation of IOPs to devise an improved algorithm for retrieval of IOPs. We then apply this algorithm to observation with Sentinel-3A OLCI (Ocean and Land Colour Instrument, corrected with our improved AC scheme), and use in-situ data to show that the algorithm performs better than the standard OLCI IOP product. We use the satellite derived products to study the spatial and seasonal distributions of IOPs and concentrations of optically active constituents in these three lakes, including chlorophyll-a (Chla) and suspended particulate matter (SPM), using all cloud-free OLCI images (115 scenes) over the lakes in the LYHR basin in 2017. Our study provides a strategy for using local and remote observations to obtain important water quality parameters necessary to manage resources such as reservoirs, lakes and coastal waters

Evaluating Landsat-8 and Sentinel-2 Data Consistency for High Spatiotemporal Inland and Coastal Water Quality Monitoring

The synergy of fine-to-moderate-resolutin (i.e., 10–60 m) satellite data of the Landsat-8 Operational Land Imager (OLI) and the Sentinel-2 Multispectral Instrument (MSI) provides a possibility to monitor the dynamics of sensitive aquatic systems. However, it is imperative to assess the spectral consistency of both sensors before developing new algorithms for their combined use. This study evaluates spectral consistency between OLI and MSI-A/B, mainly in terms of the topof-atmosphere reflectance (ρt), Rayleigh-corrected reflectance (ρrc), and remote-sensing reflectance (Rrs). To check the spectral consistency under various atmospheric and aquatic conditions, nearsimultaneous same-day overpass images of OLI and MSI-A/B were selected over diverse coastal and inland areas across Mainland China and Hong Kong. The results showed that spectral data obtained from OLI and MSI-A/B were consistent. The difference in the mean absolute percentage error (MAPE) of the OLI and MSI-A products was ~8% in ρt and ~10% in both ρrc and Rrs for all the matching bands, whereas the MAPE for OLI and MSI-B was ~3.7% in ρt , ~5.7% in ρrc, and ~7.5% in Rrs for all visible bands except the ultra-blue band. Overall, the green band was the most consistent, with the lowest MAPE of ≤ 4.6% in all the products. The linear regression model suggested that product difference decreased significantly after band adjustment with the highest reduction rate in Rrs (NIR band) and Rrs (red band) for the OLI–MSI-A and OLI–MSI-B comparison, respectively. Further, this study discussed the combined use of OLI and MSI-A/B data for (i) time series of the total suspended solid concentrations (TSS) over coastal and inland waters; (ii) floating algae area comparison; and (iii) tracking changes in coastal floating algae (FA). Time series analysis of the TSS showed that seasonal variation was well-captured by the combined use of sensors. The analysis of the floating algae bloom area revealed that the algae area was consistent, however, the difference increases as the time difference between the same-day overpasses increases. Furthermore, tracking changes in coastal FA over two months showed that thin algal slicks (width < 500 m) can be detected with an adequate spatial resolution of the OLI and the MSI

Remote sensing and bio-geo-optical properties of turbid, productive inland waters: a case study of Lake Balaton

Algal blooms plague freshwaters across the globe, as increased nutrient loads lead to eutrophication of inland waters and the presence of potentially harmful cyanobacteria. In this context, remote sensing is a valuable approach to monitor water quality over broad temporal and spatial scales. However, there remain several challenges to the accurate retrieval of water quality parameters, and the research in this thesis investigates these in an optically complex lake (Lake Balaton, Hungary). This study found that bulk and specific inherent optical properties [(S)IOPs] showed significant spatial variability over the trophic gradient in Lake Balaton. The relationships between (S)IOPs and biogeochemical parameters differed from those reported in ocean and coastal waters due to the high proportion of particulate inorganic matter (PIM). Furthermore, wind-driven resuspension of mineral sediments attributed a high proportion of total attenuation to particulate scattering and increased the mean refractive index (n̅p) of the particle assemblage. Phytoplankton pigment concentrations [chlorophyll-a (Chl-a) and phycocyanin (PC)] were also accurately retrieved from a times series of satellite data over Lake Balaton using semi-analytical algorithms. Conincident (S)IOP data allowed for investigation of the errors within these algorithms, indicating overestimation of phytoplankton absorption [aph(665)] and underestimation of the Chl-a specific absorption coefficient [a*ph(665)]. Finally, Chl-a concentrations were accurately retrieved in a multiscale remote sensing study using the Normalized Difference Chlorophyll Index (NDCI), indicating hyperspectral data is not necessary to retrieve accurate pigment concentrations but does capture the subtle heterogeneity of phytoplankton spatial distribution. The results of this thesis provide a positive outlook for the future of inland water remote sensing, particularly in light of contemporary satellite instruments with continued or improved radiometric, spectral, spatial and temporal coverage. Furthermore, the value of coincident (S)IOP data is highlighted and contributes towards the improvement of remote sensing pigment retrieval in optically complex waters