Remote estimation of chlorophyll-a in turbid and productive estuaries is difficult due to the optical complexity of Case 2 waters. Although recent advances have been obtained with the use of empirical approaches for estimating chlorophyll-a in these environments, the understanding of the relationship between spectral reflectance and chlorophyll-a is based mainly on temperate and subtropical estuarine systems. The potential to apply standard NIR-Red models to productive tropical estuaries remains underexplored. Therefore, the purpose of this study is to evaluate the performance of several approaches based on multispectral data to estimate chlorophyll-a in a productive tropical estuarine-lagoon system, using in situ measurements of remote sensing reflectance, R rs . The possibility of applying algorithms using simulated satellite bands of modern and recent launched sensors was also evaluated. More accurate retrievals of chlorophyll-a (r 2 > 0.80) based on field datasets were found using NIR-Red three-band models. In addition, enhanced chlorophyll-a retrievals were found using the two-band algorithm based on bands of recently launched satellites such as Sentinel-2/MSI and Sentinel-3/OLCI, indicating a promising application of these sensors to remotely estimate chlorophyll-a for coming decades in turbid inland waters. Our findings suggest that empirical models based on optical properties involving water constituents have strong potential to estimate chlorophyll-a using multispectral data from satellite, airborne or handheld sensors in productive tropical estuaries.
Here, we demonstrate how a combination of three multivariate statistic techniques can identify key environmental factors affecting the seasonal and spatial variability of chlorophyll-a (Chl-a) in a productive tropical estuarine-lagoon system. Remote estimation of Chl-a was carried out using a NIR-Red model based on MODIS bands, which is highly consistent with the in situ measurement of Chl-a with root mean square error (RMSE) of 15.24 mg m −3 and 13.43 mg m −3 for two independent datasets used for the model's calibration and validation, respectively. Our findings suggest that the river discharges and hydraulic residence time of the lagoons promote a stronger effect on the spatial variability of Chl-a in the coastal lagoons, while wind, solar radiation and temperature have a secondary importance. The results also indicate a slight seasonal variability of Chl-a in Mundaú lagoon, which are different the from Manguaba lagoon. The multivariate approach was able to fully understand the relative importance of key environmental factors on the spatiotemporal variability of Chl-a of the aquatic ecosystem, providing a powerful tool for reducing dimensionality and analyzing large amounts of satellite-derived Chl-a data.
A crescente produção de carga orgânica e de nutrientes em bacias hidrográficas tem levado, historicamente, rios a significativas mudanças nos padrões de qualidade da água, na diversidade e riqueza biológica e nos usos nobres de suas águas. Neste trabalho avaliamos a qualidade da água na bacia do rio Doce através de um modelo hidrológico integrado a um SIG, denominado SGAG. O sistema foi capaz de analisar o efeito de lançamentos múltiplos de efluentes na qualidade da água do rio Doce no período de estiagem. O modelo foi calibrado satisfatoriamente utilizando os dados de monitoramento ao longo do curso do rio Doce. Cenários de planejamento também foram estabelecidos, simulados e avaliados. As simulações mostraram que as medidas propostas para os cenários de planejamento promovem uma significativa redução das concentrações dos poluentes em comparação com o cenário atual, principalmente o cenário de tratamento universal. O modelo hidrológico em ambiente SIG proposto mostrou ser uma ferramenta promissora e simples para investigação da qualidade da água de bacias hidrográficas sujeita a lançamentos pontuais de efluentes.
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