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Forecasting Turbidity during Streamflow Events for Two Mid-Atlantic U.S. Streams

Author

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  • Amanda L. Mather

    (Oregon Health & Science University)

  • Richard L. Johnson

    (Oregon Health & Science University
    Oregon Health & Science University)

Abstract

Short-term streamflow forecasting is a widely used and important aspect of modern water management. In contrast, routine operational forecasting of stream water quality remains relatively limited. Turbidity is a commonly-monitored, key water-quality parameter. It can often be used to estimate other water-quality parameters and can serve as an overall indicator of stream environmental health. In this study, short-term (3-day) turbidity forecasts during streamflow events for two Mid-Atlantic U.S. streams were produced using a combination of forecast discharge, precipitation and air temperature, together with observations leading up to the issue time of the forecast. The turbidity forecast error was found to be relatively constant with lead time and significantly less than the persistence reference error for nearly all lead times. The turbidity forecast uncertainty due to streamflow forecast uncertainty was also evaluated. Potential future improvements for the example turbidity forecasts presented here are discussed. This study demonstrates for the first time that currently-available inputs (i.e., forecast discharge, precipitation and air temperature) can yield useful stream turbidity forecasts.

Suggested Citation

  • Amanda L. Mather & Richard L. Johnson, 2016. "Forecasting Turbidity during Streamflow Events for Two Mid-Atlantic U.S. Streams," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4899-4912, October.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:13:d:10.1007_s11269-016-1460-1
    DOI: 10.1007/s11269-016-1460-1
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    References listed on IDEAS

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    1. C. Iglesias & J. Martínez Torres & P. García Nieto & J. Alonso Fernández & C. Díaz Muñiz & J. Piñeiro & J. Taboada, 2014. "Turbidity Prediction in a River Basin by Using Artificial Neural Networks: A Case Study in Northern Spain," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 319-331, January.
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