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Long-Term Water Quality Modeling of a Shallow Eutrophic Lagoon with Limited Forcing Data

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Abstract

Water quality modeling can be an important tool for lake management. However, if the simulation period is small and the forcing data is limited, the result uncertainty may diminish its usefulness. This study was conceived with the aim of implementing a long-term water quality simulation of a shallow eutrophic lagoon, with limited forcing data, to evaluate result uncertainty and the advantages of such an approach for the water management process. The lagoon water quality was simulated, over a period of 19 years (2000 to 2019), with the CE-QUAL-W2 model, and the watershed with the SWAT model. Two different scenarios regarding the lagoon inflow water quality characterization were considered and evaluated. The CE-QUAL-W2 model was used to simulate the lagoon water column and sediment biogeochemical fluxes using the following seventeen constituents as a calibration reference: water temperature; dissolved oxygen; orthophosphates; total phosphorus; ammonia; nitrate plus nitrite; total nitrogen; carbonaceous biochemical oxygen demand; total dissolved solids; pH; six algae biomass groups, and chlorophyll-a. The results show that despite the high level of uncertainty in the lagoon’s daily constituents’ variation, the long-term perspective on the biogeochemical fluxes, as described by the interannual constituent’s evolution, enabled the identification of ecological thresholds, the convergence and divergence of the system, and constituent trajectories. These results can represent a step forward into the establishment of cause-and-effect relationships between pressures and water body status, thus allowing an effectiveness improvement on the integrated water resource planning and management under the European Water Framework Directive.

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Availability of Data and Material

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Code Availability

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Acknowledgements

The authors wish to thank the Regional Secretariat for Environment for providing the hydrological and water quality data which supported this study and other colleagues for their inputs and insights (namely, Carla Melo, Cristina Padilha, Daniel Silva, and Vanessa Ramos, from Simbiente Azores – Environmental Engineering and Management).

Funding

This study had the support of national funds through Fundação para a Ciência e Tecnologia (FCT), under the project LA/P/0069/2020 granted to the Associate Laboratory ARNET, and the strategic project UDIB/04292/2020 granted to MARE.

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Authors and Affiliations

  1. Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Lisbon, Portugal

    Manuel Almeida, Ricardo Rebelo, António Rodrigues & Pedro Coelho

  2. Mare – Centro de Ciências do Mar e do Ambiente, Lisbon, Portugal

    Manuel Almeida, Ricardo Rebelo, António Rodrigues & Pedro Coelho

  3. Simbiente Açores – Engenharia e Gestão Ambiental, Cabouco – Lagoa, 9560-350, São Miguel – Açores, Portugal

    Sérgio Costa

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  4. António Rodrigues
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  5. Pedro Coelho
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Contributions

MA conceived the study, performed the simulations, and wrote de manuscript. RR, SC, AR, and PC contributed to the study design and to the results analysis. All authors contributed to the discussion and manuscript revision. All authors read and approved the final manuscript.

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Correspondence to Manuel Almeida.

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Appendix

Appendix

Initial values of hydrodynamic and water quality parameters were considered in the CE-QUAL-W2 and in the SWAT model. The remaining parameters were set to default values specified in the CE-QUAL-W2 [32] and in the SWAT user manual [41].

1.1 Listing of CE-QUAL-W2 Model Parameters

Table 8 Hydraulic coefficients
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Table 9 Extinction coefficients
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Table 10 Rates and constants: phytoplankton
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Table 11 Rates and constants: organic matter
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1.2 Listing of SWAT Model Parameters

Table 12 SWAT model parameters: streamflow, mineral nitrogen, and soluble phosphorus calibration
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Almeida, M., Rebelo, R., Costa, S. et al. Long-Term Water Quality Modeling of a Shallow Eutrophic Lagoon with Limited Forcing Data. Environ Model Assess 28, 201–225 (2023). https://doi.org/10.1007/s10666-022-09844-3

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