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

Chapter 2 - Lakes

How to Report and Analyze Lake Water Quality Data

Data analysis and interpretation can be as simple as comparing measurements to State standards, or be very complex involving advanced statistics and a thorough understanding of lake dynamics. The following section describes some simple, straightforward approaches to looking at the data you have collected and even making some preliminary determinations on what it all might mean. The first step in assimilating and reporting data is to create a summary table of your data, showing the average and range for each parameter measured. This will make it easy to compare the data to water quality standards or from other lakes.

You can learn the most about your lake by looking at how a measurement changes over time (like over a growing season) and how one measurement changes with respect to another. It’s easiest to see these changes by plotting the numerical values on graph paper.

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, which 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 concentrations, Secchi depths, and temperature. Choose the scale of each axis to match the range of numbers you have measured.

Any of the parameters measured can be plotted to compare changes over time or between stations. The data for the sample plots shown were collected from Lake Sammamish during the summer of 1989. The first plot is a simple depiction of the change in one parameter – chlorophyll a – through the year. Although not discussed in this guide, the high early spring peak in chlorophyll a is fairly typical. The available nutrient supply is very high at this time because of the low winter productivity. Consequently, as soon as sunlight increases in the spring, conditions are just right for a large bloom such as the one shown. In this lake, chlorophyll a levels remained low until late summer, when another smaller peak in concentrations was measured.

The second graph compares TP and SRP concentrations measured in the top meter of the lake. Notice that the TP concentration increased through most of the summer (until August), while SRP decreased. This corresponds to the process described earlier where increased growth and productivity during summer result in higher total nutrient (TP) concentrations but lower amounts of available nutrients (SRP) because available nutrients are being utilized almost immediately for continued growth.

If you have sampled at more than one station or depth, the next level of comparison is to plot the results on the same graph. Use different symbols for each station or depth – circles for one and a square for the other. When connecting the points, use different styles of line for each station or depth – like a solid line for one and a dotted line for the other. Different colors serve the same purpose as different shapes and line styles. The third plot compares DO measured in the top meter of Lake Sammamish to that measured at 20 meters depth. This provides a good example of the effects of stratification in a lake. As shown, sometime in late May the concentration of DO began to differ at the two depths – a sign the lake was stratifying. As the summer progressed, the difference became more acute, as photosynthesis and aeration near the surface created oxygen while chemical and biological processes near the bottom used it up. By July and August, DO near the bottom of the lake was too low to support many fish and other aquatic life.

You may even want to compare different parameters to each other. If the reporting units and expected range of values are the same, you can use the regular y-axis for both parameters. If the units and expected range 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. The parameters that are commonly compared for lake data are total phosphorus and total nitrogen, total phosphorus and available phosphorus, and total phosphorus and Secchi depth. It also is interesting to compare the change in temperature, DO, and pH with depth in a lake.

After you have made the plots, go back to the beginning of the lake chapter and review each of the parameters and their reasons for variation. Try to explain the variations in your plots by what you now know about how each of the parameters functions.

An additional and relatively easy data analysis technique is to calculate your lake’s trophic state index (TSI). TSI provides a simple means of determining and comparing lake productivity.

Determining a Lake’s Trophic Status

Since lake water quality has so much natural variation, it is difficult to set water quality standards for lakes. It can be much more valuable to compare changes in one lake’s quality over the years or to compare between lakes, than to have simple limits for "good" and "bad" lakes. A method has been devised for "rating" lakes. This method is called the trophic state index (TSI) or the Carlson index (after the scientist who devised it).

Calculating TSI

TSI can be calculated by using the Secchi disk depth, the total phosphorus concentration at the surface of the lake, or the chlorophyll a concentration at the surface. Either one day’s values or, preferably, average values over the summer can be used. The equations used to calculate TSI are:

Using Secchi disk depth:

TSI = 60 – 14.41 (In SD)

Where SD is the Secchi depth in meters, and In stands for the natural log of a number.

Using total phosphorus:

TSI = 14.42 (In TP) + 4.15

Where TP is the total phosphorus concentration measured in the surface water in ug/L, and In stands for the natural log of a number.

Using chlorophyll a:

TSI = 9.81 (In Chl a) + 30.6

Where chl a is the chlorophyll a concentration, in ug/L, and In stands for the natural log of a number.

Once you have calculated the TSI, you can compare the results to other lakes or recalculate the value each year to see whether there appears to be any upward or downward trend in your lake. Again, because of the large natural variation for these parameters, it would take a number of years of data to determine whether any trend existed.

You should be aware that you will not calculate the same TSI value with each of the parameters. In other words, if TSI is calculated using Secchi disk depth, the same result may not be obtained when calculating it with TP. According to the scientist who developed this index, chlorophyll a is the best indicator to use if using data from the summer months, while TP is the best during the rest of the year. Of course, if Secchi disk data is all you have – that’s what you will use.

The table above provides a comparison of each of the parameters and the resultant TSI. The higher the TSI value, the "older" or more productive the lake is. Roughly speaking, lakes with TSI values between 0 and 40 are considered to be oligotrophic, those between 40 and 60 are mesotrophic, and those between 60 and 100 are eutrophic.

A great deal of information was covered in the lake chapter. If you’ve read it from end to end you are probably feeling a little overwhelmed by now. Take a break and let your mind assimilate some of the information. Unless you are also interested in stream monitoring, you should read Chapter Four next. Chapter Four explains how to go about collecting the samples and different analysis methods for the different water quality parameters. You may want to return to this chapter now and again to refresh your memory – with luck you’ll find that each time you read it you will understand some concept a little better.

If you are interested in stream monitoring continue on to Chapter Three - Streams. 

Return to Table of Contents | Lakes | Streams | From the Field to the Lab | Hydrology