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For optically complex turbid productive waters, the optical behavior of suspended particles is the keynote of characterizing the unordered variations of inherent optical properties (IOPs). Multiple bio-optical measurements and sampling of optically active substances were performed in Lake Taihu, Lake Chaohu, and Lake Dianchi, and Three Gorges reservoir of China, in 2008, 2009, and 2010. On the basis of obtaining adequate observation data, we developed an improved and robust water classification approach, by which complex water conditions were divided into three types, i.e., Type 1 (Normalized Trough Depth at 675 nm, hereafter NTD675, ≥0.092), Type 2 (0 ＜ NTD675 ＜ 0.092), and Type 3 (NTD675 ≤ 0). Furthermore, the specific inherent optical quantities for suspended particles, including the specific absorption coefficient of non-algal particles (a*nap), the specific absorption coefficient of phytoplankton (a*ph), and the specific scattering coefficient of the suspended particles (b*p), were determined for the three classified types of waters. The validation results showed that our proposed values for these specific inherent optical quantities presented relatively high predictive accuracies, with most mean absolute percentage errors (MAPE) near 30%, and more importantly, performed much better than that of non-classified waters. Additionally, relative contributions of phytoplankton and non-algal particles to the total particulate absorption and scattering, as well as the spectra, were also analyzed, and the differences among the three classified types of waters were clarified. Overall, the results obtained in this study provide us with new knowledge for understanding complex varied inherent optical properties of highly turbid productive waters. [ABSTRACT FROM AUTHOR]

This study develops a novel support vector regression (SVR) model for retrieving the specific cyanobacterial pigment C-phycocyanin (C-PC) concentrations in cyanobacteria-dominated large turbid lakes of China. Lake Taihu, Lake Chaohu, and Lake Dianchi in China were our study areas. Five field cruises were carried out to collect data sets of optical and water quality parameters. To retrieve the C-PC, three types of reflectance forms, including single band, band ratio, and three-band-combination, were compared. The band ratio was the best candidate to serve for algorithm development. On this basis, two types of models, including linear models and a SVR model, were originally established. The previous typical algorithms were also examined. The obtained results showed that the best-performing model was the SVR model. By our validation data set, the proposed SVR model also presented accurate prediction results, with the lowest errors among all methods. The novelty of the SVR model compared to the previous ones lies in the inclusion of band ratios that are located outside of the main pigment absorption peaks but hold information on inflection points, curvature, etc., into empirical optimization. The implications of these findings indicates the potential applicability of the SVR models in lakes of the similar type. [ABSTRACT FROM AUTHOR]

Cyanobacterial blooms are an environmental issue that can cause health hazards by toxins and malodorous compounds. The pigment phycocyanin is indicative of cyanobacterial presence. In eutrophic inland waters in which nitrogen is not a limiting nutrient, the phycocyanin concentration (PC) is closely related to cyanobacterial biomass. This study proposes a simple semi-analytical four-band algorithm for PC estimation to overcome the deficiency of existing algorithms. This algorithm was calibrated using a data set collected from Lake Taihu in 2007. Optimal reference wavelengths for the algorithm were located through model tuning and accuracy optimization. The algorithm was evaluated for its accuracy against an independent data set collected in 2008. The performance of the algorithm was also compared with that of the nested band-ratio algorithm, which was developed for PC estimation in turbid waters. Although both algorithms enabled the establishment of a linear relationship between measured and predicted PC, the nested band-ratio algorithm did not have a satisfactory performance with either data set, having a high level of uncertainty. Its mean relative error stands at 51.07% and 51% for the 2007 and 2008 data sets, respectively. It accounted for 68% and 74% of the variation in PC in the 2007 and 2008 data sets, respectively. The four-band algorithm worked well in PC estimation. It accounted for 87% of the variation in PC for the 2007 data set and 86% of the variation in the 2008 data set. Furthermore, it decreased estimation uncertainty, compared with the nested band-ratio algorithm, by more than 20%. The values of mean relative error for the correspondence data sets are 29.1% and 30%. Therefore, the proposed four-band algorithm holds great potential in estimating PC in highly turbid waters. [ABSTRACT FROM AUTHOR]

Water spectral absorption characteristics of eutrophic lakes are largely different from those of ocean and coastal waters. We therefore studied them with the aim of establishing an analytical model for inland water colour, to be used in remote sensing. Field measurements were carried out on 16 and 17 August 2006 (summer), 5 and 6 November 2006 (winter), and 29 and 30 March 2007 (spring) at 15 stations in northern Lake Taihu (China). Chromophoric dissolved organic matter (CDOM) absorption coefficients (a CDOM) are higher in summer than in spring and winter, with the ratios of a CDOM in spring, summer and winter being approximately 1 : 4.0 : 1.2 at both UV-C and UV-B. The spectral slope S CDOM values change with wavelength and season, and covary with CDOM concentration, as shown by regression analysis. For the CDOM absorption spectrum in the wavelength region 500-700 nm (important for water colour remote sensing), a linear method simulates better than an exponential method. Seasonal variations in non-algal particulate (NAP) absorption (a NAP) at blue, green and red wavelengths show better consistency, in the order winter>spring>summer. The average S NAP is 0.0065±0.0009 nm-1, which is lower than that in other types of waters. Phytoplankton absorption (a ph) peak height changes with the season, with the pattern summer>winter>spring, and phytoplankton absorption spectra can be expressed with high accuracy by a quadratic model. CDOM absorption contributions in the three seasons are low compared to phytoplankton and NAP. [ABSTRACT FROM AUTHOR]

Accurate estimation of phytoplankton chlorophyll a (Chla) concentration from remotely sensed data is particularly challenging in turbid, productive waters. The objectives of this study are to validate the applicability of a semi-analytical three-band algorithm in estimating Chla concentration in the highly turbid, widely variable waters of Taihu Lake, China, and to improve the algorithm using a proposed four-band algorithm. The improved algorithm is expressed as [Rrs(λ 1)−1 −Rrs(λ 2)−1][Rrs(λ 4)−1 −Rrs(λ 3)−1]−1. The two semi-analytical algorithms are calibrated and evaluated against two independent datasets collected from 2007 and 2005 in Taihu Lake. Strong linear relationships were established between measured Chla concentration and that derived from the three-band algorithm of [Rrs−1(660)−Rrs−1(692)]Rrs(740) and the four-band algorithm of [Rrs−1(662)−Rrs−1(693)][Rrs−1(740)−Rrs−1(705)]−1. The first algorithm accounts for 87% and 80% variation in Chla concentration in the 2007 and 2005 datasets, respectively. The second algorithm accounts for 97% of variability in Chla concentration for the 2007 dataset and 87% of variation in the 2005 dataset. The three-band algorithm has a mean relative error (MRE) of 43.9% and 34.7% for the 2007 and 2005 datasets. The corresponding figures for the four-band algorithm are 26.7% and 28.4%. This study demonstrates the potential of the four-band model in estimating Chla even in highly turbid case 2 waters. [Copyright &y& Elsevier]

In order to investigate variations of absorption and total chlorophyll- a (TChl- a)-specific absorption coefficient of phytoplankton in Lake Taihu, 57 water samples obtained from Lake Taihu during November 8–22, 2007 were used in this study. Package effect and accessory pigments’ influences on the absorption spectra were also examined. Phytoplankton absorption was measured by quality filter technical, and TChl- a concentration was measured by “hot ethanol” method. Results yielded significant variations in phytoplankton absorption and TChl- a-specific absorption coefficient. Phytoplankton absorption coefficient at 675 nm is highly correlated to TChl- a concentration, while absorption at 440 nm is less correlated to TChl- a concentration because of great package effect and accessory pigments’ influence. There was an inverse relationship between a ph*(λ) and TChl- a concentration. Four types of absorption spectra are identified by normalizing a ph*(λ) to a ph*(440). The a ph*(λ) variation is mainly due to accessory pigments and package effect, whose influence at 675 nm ranges from 83.2% to 28%, with an average of 65.3%. Meanwhile, the wide varying ratio of a ph*(440) to a ph*(675) indicates a large variation range in the ratio of accessory pigment to TChl- a concentration. Those findings are significant to estimate Chl- a concentration based on bio-optical model, estimate primary production from remote sensing, and plan further ecological restoration measures for Lake Taihu. [ABSTRACT FROM AUTHOR]

Light scattering properties in such a highly turbid productive lake as Lake Taihu in China were examined through 118 samples collected during three cruises in November 2006, March 2007, and November 2007. The particulate scattering and backscattering coefficients were observed using WETLabs AC-S and ECO-BB9. A power model with a spectral exponent of -0.729 was used to simulate the particulate scattering coefficient (b(p)) spectra. It has a better performance than the linear model. Scattering parameters are more closely related to inorganic suspended matter (ISM) concentration than to other water components, such as total suspended matter (TSM), organic suspended matter (OSM), and chlorophyll a (Chla). This indicates that ISM dominates the scattering signal in the lake. Three discrepancies with oceanic/coastal waters are observed: (a) the backscattering ratio (b (bp)) decreases with an increase in the ISM concentration because of a highly strong contribution by ISM to b(p); (b) the mass-specific scattering coefficient (b(p) (m)) exhibits a wider range of variability than that reported in previous studies, which can be attributed to considerable variation in the OSM and ISM distributions; (c) the particle size distribution slope (xi) is mostly larger than 4.0 in Lake Taihu, whereas it is usually within 3.5-4.0 for marine particles. In addition, the bulk refractive index (n (p)) calculated according to the Twardowski et al. model [J. Geophys. Res. 106, 14129 (2001)JGREA20148-0227] indicates that some stations (n (p)<1.07) can be regarded as organic-particle dominant. Other stations with high ISM concentrations have a very small n (p) value mostly within 1.10-1.17. Overall, the knowledge on the scattering properties gained in this study broadens our understanding of water optics in highly turbid productive water columns.