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Using MODIS remote sensing data for mapping the spatio-temporal variability of water quality and river turbid plume

Journal of Coastal Conservation volume 21, pages 939–950 (2017)Cite this article

Abstract

Fox River is the main source of land-based pollutants that flows into the southern Green Bay of Lake Michigan. Evaluation of water quality is normally based on time consuming and expensive in situ measurements. Remotely sensed data is an efficient alternative for field monitoring because of its spatial and temporal coverage. In this study, remote sensing imagery combined with in situ measurements of water quality were used to estimate an empirical relationship between water surface reflectance and water quality parameters including water turbidity and Total Suspended Sediment (TSS). Surface reflectance values is obtained from MODerate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite. The empirical equations were derived from data over summers 2011–13 and show high correlation coefficients of equal to 0.83 and 0.87 for TSS and turbidity respectively. The validity of the proposed equations was tested for summer 2014 data. The NRMSE for prediction of measured data by the proposed equations are 0.36 and 0.3 for TSS and turbidity. Remotely sensed data was also used to produce water quality maps to improve our understanding of the spatiotemporal variations of Fox River turbid plume. The proposed approach can be extended to other coastal regions of Great Lakes and provide a framework to study pollution transportation in coastal areas.

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Acknowledgements

The authors gratefully acknowledge the assistance of Erin Wilcox at NEW Water GBMSD for providing in situ water quality data.

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Authors and Affiliations

  1. Department of Physics, College of Natural Sciences and Mathematics, Indiana University of Pennsylvania, Indiana, PA, USA

    Sajad Ahmad Hamidi

  2. Department of Civil and Environmental Engineering, Villanova University, Villanova, PA, USA

    Hossein Hosseiny

  3. National Center for Airborne Laser Mapping, University of Houston, Houston, TX, USA

    Nima Ekhtari

  4. Department of Civil and Environmental Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, USA

    Bahram Khazaei

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  1. Sajad Ahmad Hamidi
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  2. Hossein Hosseiny
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Correspondence to Sajad Ahmad Hamidi.

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Hamidi, S.A., Hosseiny, H., Ekhtari, N. et al. Using MODIS remote sensing data for mapping the spatio-temporal variability of water quality and river turbid plume. J Coast Conserv 21, 939–950 (2017). https://doi.org/10.1007/s11852-017-0564-y

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  • DOI: https://doi.org/10.1007/s11852-017-0564-y

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