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Estimates of light availability in the water column require accurate quantification at different depths of the diffuse attenuation coefficient ( K ). This study examines spatial and seasonal variability of K derived variables [euphotic zone depth ( Z ), attenuation depth ( Z )], their relationship with optically active constituents (OACs), and their impact on the underwater light field at Ibitinga Reservoir (São Paulo, Brazil). Radiometric data were acquired using profiling spectroradiometers operating from 320 to 950 nm in four campaigns (February-July 2014) concurrently with OAC water samplings. Minimum and maximum values of K PAR were, respectively, 0.99 and 3.45 m for average ranges of OACs varying from 14.4 to 16.2 mg/l for dissolved total carbon, 11.5-100.5 μg/l for chlorophyll- a, 1.8-14.5 mg/l for total suspended solid, and from 0.73 to 1.71 m for absorption coefficient of colored dissolved organic matter (CDOM) in 440 nm ( a ). CDOM removed blue wavelengths in the first meter of the water column throughout seasons, while green wavelengths were predominant with increasing depth. Furthermore, this study demonstrated that K variability is mainly influenced by the presence of phytoplankton and CDOM in the reservoir, and reveals that the seasonal variability of K was much larger than spatial variability. [ABSTRACT FROM AUTHOR]

Relationships between water clarity, light attenuation, and concentration of suspended particulates are important in water optics and remote sensing, but are not well described yet, especially for optically complex turbid inland waters. In this study, based on 3-year data from Chinese lakes (Lake Taihu, Lake Chaohu, and Three Gorges reservoir), we propose a new approach to describe the inter-relationships of these bio-optical variables. This approach includes a pre-classification step of the waters into three types based on a semi-analytical parameter C before establishing the relationships. Our results showed that the pre-classification of waters increased model accuracies both for Z (Secchi depth) versus K (diffuse attenuation coefficient) and K versus TSM (total suspended matter concentration). The quasi-theoretical model described better the relationship between Z and K than the empirical model. For the K versus TSM relationship, linear models proved suitable for the Type 2 and Type 3 waters, whereas the power function model gave a better fit for the Type 1 water. Testing of the proposed relations with an independent dataset showed mean absolute percentage errors (MAPE) mostly below 30%. The findings of this study clarify the relationships between Z, K, and TSM, and improve our bio-optical understanding of complex turbid inland waters. [ABSTRACT FROM AUTHOR]

The diffuse attenuation coefficient of photosynthetically active radiation (PAR) (400-700 nm) ( K(PAR)) is one of the most important optical properties of water. Our purpose was to create K(PAR) prediction models from the Secchi disk depth (SDD) and beam attenuation coefficient of particulate and dissolved organic matter ( C(PAR), excluding pure water) in the PAR range. We compare their performance and prediction precision by using the determination coefficient ( r), relative root mean square error (RRMSE), and mean relative error (MRE). Our dataset comprised 1,067 measurements, including K(PAR), SDD, and C(PAR) taken in shallow, eutrophic, Lake Taihu, China, from 2005 to 2010. The prediction models of K(PAR) were based on the linear model with an intercept of zero, using the inverse SDD, and the nonlinear model using SDD. The linear model generated a slope of 1.369, which was not significantly different from 1.7, the index used worldwide, but significantly lower than the value of 2.26. The nonlinear model gave a slightly more reliable prediction of K(PAR) with a r of 0.804. Compared to the SDD, C(PAR) was more significantly correlated to K(PAR) based on the linear model, with a significantly higher r and lower RMSE and RE. Considering the measurement simplicity of C(PAR) and data acquisition feasibility from high-frequency autonomous buoys and satellites, our results demonstrated that this prediction model reliably estimates K(PAR), and could be used to significantly expand optical observations in an environment where the conditions for underwater PAR measurement are limited. [ABSTRACT FROM AUTHOR]