Search

Abstract Dissolved organic carbon (DOC) plays a critical role in climate-related biogeochemical cycles. The absorption spectrum slope of chromophoric dissolved organic matter (CDOM) in the 275–295 nm spectral range (S 275–295) have been previously used as indicators of the source, molecular weight, photobleaching, and fate of DOC in estuarine and coastal environments. Here, we developed a multiple regression algorithm using field measurements and near-concurrent satellite observations in estimating S 275–295 from satellites in the West Florida Shelf (WFS). The algorithm had a reliable performance in estimating S 275–295 in terms of mean relative error and root mean square error < 10%. The algorithm was applied to available daily satellite images to establish long-term time series of S 275–295 dynamics and to investigate its driving factors. S 275–295 exhibited substantial spatiotemporal variability on the WFS. Correlation analyses revealed that river discharge regulated the temporal and spatial variation of S 275–295 on the inner shelf, however, only wind had significant influence on the spatial and temporal distribution of S 275–295 on the outer shelf. Climate variations and weather conditions had significant influences on the temporal and spatial distribution of S 275–295 on the shelf by influencing the river discharge and wind at short time-scale. Highlights • An empirical algorithm has been developed to derive S 275–295. • Long-term S 275– 295 time series was established for the West Florida Shelf. • Environmental factors forcing S 275– 295 dynamics were analyzed. [ABSTRACT FROM AUTHOR]

Observed bio-optical water quality data collected from 2009 to 2011 in Pensacola Bay, Florida were used to develop empirical remote sensing retrieval algorithms for chlorophyll a (Chla), colored dissolved organic matter (CDOM), and suspended particulate matter (SPM). Time-series of the three bio-optical water quality variables were generated from MEdium Resolution Imaging Spectrometer (MERIS) observations from 2003 to 2011. Bio-optical water quality in this estuary exhibited spatial and temporal variations that were correlated to river discharge and wind. Both annual mean and monthly mean bio-optical water quality variables were positively correlated to river discharge. Monthly mean bio-optical water quality variables were also positively correlated to wind speed and wind density (defined by the number of days with daily mean wind speed > 3 m s −1 in a month) over this estuary. These results indicate that bio-optical water quality dynamics in this estuary are vulnerable to changes in river discharge and river constituent loads and local weather conditions such as winter storms and hurricanes. [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]

To overcome the retrieval problems in complex water, dual working wavelengths are required instead of a single wavelength in oceanic lidar. The wavelength optimization method of detecting chlorophyll a and Colored Dissolved Organic Matter (CDOM) absorption coefficient with a dual-wavelength lidar is studied in this paper. The inversion methods of chlorophyll a and CDOM absorption are developed based on the water absorption characteristics, which then lead to the inversion error equations. The effects of the wavelength on the inversion errors are studied. For the case in which λ1 and λ2 are both random, the errors are relatively small when λ1 is chosen between 420 and 560 nm and λ2 is selected under 420 nm. For the case in which λ1 is fixed at 532 nm, the errors generally decrease with decreasing λ2, with minimums around 300 and 356–360 nm under different water conditions. The wavelength optimization method discussed in this paper and the penetration depth criterion will be beneficial to the design of the dual-wavelength lidar. [ABSTRACT FROM AUTHOR]