Optimizing Water Quality Sampling Through Application Of Real Time Ionic Concentration Regression Models

Authors

  • Shibly Rahman Water Resources Management Division, Department of Environment and Conservation, A1B4J6, St. John’s, Canada
  • Renee Paterson Water Resources Management Division, Department of Environment and Conservation, A1B4J6, St. John’s, Canada

Abstract

The Water Resources Management Division of the Department of Environment and Conservation performs routine water sampling to measure the physical and chemical parameters of select water bodies in Newfoundland and Labrador. Ionic concentration parameter measurement is performed during routine water sampling to complement some of the key indicator parameters measured in real time at these select water bodies. The collection, laboratory analysis and measurement of water samples are a time consuming process. Some of the common conducting ions measured during routine sampling are sodium, calcium, chloride and sulphate. These conducting ions can be estimated using continuously measured specific conductance after observing the effect of flow. The estimated measurement will help identify the quality of water at a given point in time and hence save time and resources in performing routine sampling. It will also help estimate the quality of water in remote locations where routine sampling is not feasible. This paper compares four water bodies on the island part of Newfoundland and Labrador and estimates the ionic concentration using continuously measured specific conductance.

Author Biography

Shibly Rahman, Water Resources Management Division, Department of Environment and Conservation, A1B4J6, St. John’s, Canada

I have been working with the Water Resources Management Division, Department of Environment and Conservation for the last 7 years. My current position is Environmental Scientist. Some of the major tasks I perform with the division are statistical analysis, environmental modeling, developing Water Quality Index Calculator, data analysis  report review as well as field work.

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Published

2014-08-04

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Section

Environmental Modeling, Risk Assessment and Decision Making (EMR)