Accessing the Potential of Satellite and Telemetric Data to Evaluate the Influence of the Heat Flux Exchange in the Water Column Mixing and Stratification

Alcântara, Enner

doi:10.4236/ijg.2012.325092

Cited by 2 publications

(3 citation statements)

References 20 publications

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“…These differences could be explained by the stratification and mixing processes in the reservoir. Alcâ ntara [30] showed that for May 2009, the water column of the Itumbiara Reservoir was in the beginning of the mixed period. In September, however, it was in the beginning of the stratified period.…”

Section: Environmental Characteristicsmentioning

confidence: 99%

“…Therefore, the low frequency of chl-a peaks during the winter period was also related to external forces, because there were a high number of cold front entrances. Alcâ ntara [30] showed that during the spring and summer when the heat balance was positive (heat gain), the water column stratifies. However, when the heat balance was negative, the water column exhibits mixing.…”

Section: Time Seriesmentioning

confidence: 99%

“…Thus, a heat balance analysis proposed by Alcâ ntara [30] to identify the mixing and stratification periods was used to evaluate the estimated chl-a time-series. This analysis ascribed a positive heat balance (heat gain) to the stratification of the water column and a negative heat balance to a mixing in the water column.…”

Section: Time Seriesmentioning

confidence: 99%

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Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo- to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil

et al. 2014

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Monitoring chlorophyll-a (chl-a) concentrations is important for the management of water quality, because it is a good indicator of the eutrophication level in an aquatic system. Thus, our main purpose was to develop an alternative technique to monitor chl-a in time and space through remote sensing techniques. However, one of the limitations of remote sensing is the resolution. To achieve a high temporal resolution and medium space resolution, we used the Moderate Resolution Imaging Spectroradiometer (MODIS) 500-m reflectance product, MOD09GA, and limnological parameters from the Itumbiara Reservoir. With these data, an empirical (O14a) and semi-empirical (O14b) algorithm were developed. Algorithms were cross-calibrated and validated using three datasets: one for each campaign and a third consisting of a combination of the two individual campaigns. OPEN ACCESSRemote Sens. 2014, 6 1635 Algorithm O14a produced the best validation with a root mean square error (RMSE) of 30.4%, whereas O14b produced an RMSE of 32.41% using the mixed dataset calibration. O14a was applied to MOD09GA to build a time series for the reservoir for the year of 2009. The time-series analysis revealed that there were occurrences of algal blooms in the summer that were likely related to the additional input of nutrients caused by rainfall runoff. During the winter, however, the few observed algal blooms events were related to periods of atmospheric meteorological variations that represented an enhanced external influence on the processes of mixing and stratification of the water column. Finally, the use of remote sensing techniques can be an important tool for policy makers, environmental managers and the scientific community with which to monitor water quality.

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Section: Environmental Characteristicsmentioning

confidence: 99%

Section: Time Seriesmentioning

confidence: 99%