Abstract

The design of alternative strategies for water and ecological quality protection at the Lake Verde of Sete Cidades should be coupled with the assessment of future trophic states. Therefore, a mathematical model was developed to make prospective scenarios to reduce the risk of environmental degradation of the lake, and a modified Psenner scheme was used to characterize P distribution in the sediments. The model was able to describe thermal stratification, nutrient cycling (P, NH4 and NO3), dissolved O2, and phytoplankton dynamics in the water column and adjacent sediment layers. Internal P recycling, resulting from thermal stratification and sediment anoxia, was identified as the main cause for the increase of P concentration in the hypolimnion followed by slow transfer to the epilimnion (about 20 μg/L annual average). Cyanobacteria blooms during spring were explained by the availability of P and increased water temperature verified during this season. The most sensitive model parameter was sediment porosity. This parameter has a direct effect in dissolved O2 and P profiles and also in phytoplankton biomass. Finally, different water quality restoration scenarios were identified and their effectiveness assessed. Without the adoption of remediation measures (scenario control), Lake Verde water quality would deteriorate with annual average concentrations of total P and phytoplankton biomass (dry matter) reaching 34 μg/L and 2 mg/L, respectively, after 10 years of simulation. The reduction of P loads (scenario PORAL) into the lake would improve water quality comparatively to the scenario control, reducing the annual average concentrations of total P from 34 μg/L to 26 μg/L and of phytoplankton from 2 mg/L down to 1.4 mg/L after 10 years of simulation. In scenario sediments, corresponding to a decrease in the organic content of the sediments, a reduction in the concentrations of total P and phytoplankton is expected in the first two years of simulation, but this effect, would be attenuated throughout the years due to organic matter sedimentation. The best strategy is obtained by combining external and internal measures for P remediation. Finally, it is recommended that the model be used to integrate the results of water quality monitoring and watershed management plans.

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