Water quality

This study compared models that used remote sensing to assess salinity in Whitewater Bay. The quantitative techniques in this research allow for a less costly and quicker assessment of salinity values. Field observations and Landsat 5 TM imagery from 2003-2006 were separated into wet and dry seasons and temporally matched. Interpolation models of Inverse Distance Weighting and Kriging were compared to empirical regression models (Ordinary Least Squares and Geographically Weighted Regression - GWR) via their Root Mean Square Error. The results showed that salinity analysis is more accurate in the dry season compared with the wet season. Univariate and multivariate analysis of the Landsat bands revealed the best band combination for salinity analysis in this local area. GWR is the most conducive model for estimating salinity because field observations are not required for future predictions once the local formula is established with available satellite imagery.

Little Lake Worth (LLW) (800 m x 200 m x 8« m) is an artificially deep, monomictic marine basin. Pigments and other water quality parameters (O2, pH, T, S, NO3 -. etc.) were utilized to characterize phototrophic communities and water quality. The water column is dominated by diatoms except in the hypolimnon during stratification events (late Summer) when strong anoxia and H2S favors abundant Chlorobium sulfur bacteria. Results indicate nitrate-enriched freshwater baseflow indicative of septic tank seepage during the wet season. This also appears to lead to the accumulation of concentrated organic matter in the sediment. LLW is a potential threat to the health of the ecosystem and the humans using it recreationally. More research is required to verify the effectiveness of restoration options. The spatial and temporal distribution of Chlorobium (phaeovibiroides tent.) and their Bacteriochlorophyll-e homologues is described and compared to similar studies.