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Coupling Hydrological and Hydrodynamic Models for Assessing the Impact of Water Pollution on Lake Evaporation

Author

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  • Janine Brandão de Farias Mesquita

    (Campus Crateús, Federal University of Ceará—UFC, Crateús 63708-825, Brazil)

  • Iran Eduardo Lima Neto

    (Department of Hydraulic and Environmental Engineering, Federal University of Ceará—UFC, Fortaleza 60020-181, Brazil)

Abstract

The present study evaluated the impact of hydrological variability on the hydrodynamics of an urban lake in Brazil, considering water quality dynamics and its effects on evaporation. The Storm Water Management Model (SWMM) was applied to the lake basin, and the two-dimensional model CE-QUAL-W2 was used to simulate the hydrodynamics and lake evaporation. The two models were coupled to carry out the integrated basin-lake modeling. Then, two water quality models were applied: a transient complete mixing model and an empirical model based on wind speed. Time series of total phosphorus (TP) were generated, and empirical correlations between TP and hydrological variables were proposed. Modeled TP and measured biochemical oxygen demand (BOD) were correlated with monthly Class A pan coefficients (K) adjusted for the lake. The K-values were negatively correlated with TP modeled by the complete mixing model (R 2 = 0.76) and the empirical model (R 2 = 0.52), as well as by BOD measurements (R 2 = 0.85). This indicates that water pollution attenuates evaporation rates. Scenarios of lake pollution and level reduction due to evaporation were also analyzed. The results from this study are important to improve the management of lakes and reservoirs by including the impact of pollution on the water balance.

Suggested Citation

  • Janine Brandão de Farias Mesquita & Iran Eduardo Lima Neto, 2022. "Coupling Hydrological and Hydrodynamic Models for Assessing the Impact of Water Pollution on Lake Evaporation," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13465-:d:946522
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    References listed on IDEAS

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    1. Yuanyuan Yang & Wenhui Zhang & Zhe Liu & Dengfeng Liu & Qiang Huang & Jun Xia, 2023. "Coupling a Distributed Time Variant Gain Model into a Storm Water Management Model to Simulate Runoffs in a Sponge City," Sustainability, MDPI, vol. 15(4), pages 1-13, February.

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