A Citizen's Guide to Understanding and Monitoring Lakes and Streams

Chapter 3 - Streams

How to Report and Analyze Stream Water Quality Data

There is a great deal of variation in just how you may want to go about interpreting the information you collect. The level of interpretation will be partially dependent upon the type and quality of the data collected. The following are examples of different approaches to looking at your stream water quality data.

The most straightforward approach is to create a summary table of your data showing the average and range for each of the parameters measured. This will make it easier to compare them to applicable water quality standards. That would be as far as your interpretation would go. Does the stream meet water quality standards? Does it meet them at all stations at all times? You may want to calculate and compare seasonal averages as well. For example, the year-round average may indicate there is no DO problem, but perhaps by calculating the summertime average you will find there is a seasonal problem with meeting this water quality standard.

In streams it is often more interesting to consider how the quality of the water changes as it moves downstream and either picks up additional pollutants or picks up cleaner water that acts to dilute pollutants already present. The easiest way to make this comparison is to plot the parameter of interest against the river mile to provide a nice visual comparison. You can create a plot for any one sampling date or you can create it using the average concentrations for many dates and showing the range in the data by adding range bars.

To plot data the horizontal axis (x-axis) is used for the independent variable. It is called independent because it is not affected by the variable shown on the vertical axis (y-axis). Typical x-axis variables include time, date, and distance. The y-axis is used for the dependent variable; this variable changes over time or date or distance. Typical y-axis variables include the parameters measured in your sampling program such as dissolved oxygen, total phosphorus, and temperature. Choose the scale of each axis to match the range of number measured.

The graphs below were created from data collected in Portage Creek, a tributary to the Stillaguamish River, during 1988 and 1989. The graphs compare the change in total phosphorus concentration with river mile. The first plat contains data from one sampling date (August 8, 1989), while the second summarizes the average total phosphorus concentration for the year at each of the sampling points and also depicts the range in concentrations measured.

The first graph shows TP concentrations rising substantially between river miles three and one. However, this situation does not appear to be a common trend in the stream when compared to the second graph. The second graph depicts the major increase in concentration occurring between stations seven and five. The variation in the data (range) also becomes most pronounced below station seven. Concentrations decrease at the stations nearest the mouth, but it is unclear from this comparison of concentrations whether the decrease represents less phosphorus or whether additional stream flow is masking an increase in the pollutant. In this case, land use activities between stations five and one appear to be those most affecting stream water quality.

Because the discharge of pollutants to streams may change with weather and flow conditions, it also is informative to consider how the quality of the water changes over the course of the year. Again, a graph provides the best means of visual comparison. This time the horizontal axis is used to show the date. Two stations, for example the mouth and the headwater station, can be plotted on the same graph to provide additional comparisons.

The graph above depicts the change in TP concentrations through the year at the station nearest the mouth and one near the headwaters. At both stations the concentrations are highest during the December through January period, which corresponds to the time of year when the most runoff enters the stream. Except for the one January date, the TP concentrations near the headwaters are consistently below those measured near the mouth. At both stations TP concentrations increase during the summer and then again during the winter.

The next level of complexity takes into account the change in the volume of the river water to assess changes in pollutant loading. This is getting into pretty detailed analysis and is limited to those stations where flow has been measured. Again the x-axis is used to represent the river mile and the y-axis is used to represent calculated pollutant loads. The graph below illustrates the change in the load of phosphorus with distance downstream. Here it is clearly shown that the major increase in pollutant loading occurs between stations seven and five. The load decreases slightly below river mile three.

You may even want to compare different parameters to each other by including them on the same plot. If the reporting units and expected range of values are the same, you can use the regular y-axis for both parameters. If the reporting units and expected range of values are different, use an y-axis on the left for one of the parameters and draw another y-axis on the right for the other parameter. For streams, common comparisons of this type are: comparing different nutrients or nutrient fractions to each other (e.g., total phosphorus to total nitrogen, or total phosphorus to available phosphorus), or comparing nutrients to dissolved oxygen or pH or TSS. After you have made the graphs return to the beginning of this chapter and review each of the parameters and their reasons for variation. Try to explain the variations in your graphs by what you now know about how each of the parameters functions.

Additional Analysis and Interpretation Hints

• As stated previously, DO can reach critical levels during late summer when streamflows are low and temperatures are high. Plotting the DO concentration in late August against river mile will provide information on where levels become critical and allow you to guess what may have caused it. NOTE: If DO appears to be a problem in a reach of the river, try a pre-dawn monitoring event in late summer to assess what is termed the worst case condition.
  
• For fecal coliform bacteria the use of seasonal averages is probably the best way to compare between stations. Calculating and comparing the "load" of bacteria is most informative and may be the best way to assess the data.
  
• There are a number of additional parameters not described in this guide that can provide interesting, informative data. Two that would be worthwhile to investigate include BOD, and conductivity. Standard Methods for the Examination of Water and Wastewater would be a good starting point for further research. A complete reference is included.

The next chapter is called from the field to the lab and discusses data collection and water analyses for stream and lake parameters.

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