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2015 August



In Water quality

By Eric Compas

Additional analysis of Milwaukee water quality data

On 04, Aug 2015 | In Water quality | By Eric Compas

We’ve conducted some initial analysis of our data from last Friday (more here). Our goal was to be able to better visualize our sample data along the stream corridor. As a geographer, I turn to a map as my first impulse, but in this case, it’s certainly not the only way of viewing our data. In particular, we were interested in comparing the values from each of our units and better visualizing trends on our metrics along the stream corridor.

So, from our magic GIS hat, we pulled out some dynamic segmentation tools to “linearize” the data we’ve collected. Put simply, we moved each data point to a stream center line as defined by USGS’s National Hydrography Dataset (NHD) yielding a distance along the stream. We could then plot our metrics, e.g. dissolved oxygen, versus distance along the stream in a conventional scatterplot allowing us to compare our two sample units and samples through time.

Here’s a visualization of the “linearization” of our data:

Linearization of stream sample data

Linearization of stream sample data

In ArcGIS, each data point (in red) was moved to the NHD stream center line (points in blue) if it was within 100 meters of the center line. In addition, each new blue point was given a distance along the stream stretch.

As of yet, these data are unfiltered. We haven’t removed known extraneous and/or invalid readings.

First, data from the Kinnickinnic

(which can be compared to the map here)

Note that the blip in temperature is due to Unit #2’s temperature element being removed from the water for a time. Temperature is almost the same for both units.

Kinnickinnic dissolved oxygen

Dissolved oxygen is also very similar (thankfully, after quite a struggle) between the two units. The mess to the left in the graph is explained below.

Kinnickinnic conductivity
Electrical conductivity also shows close correspondence between the two units except with fairly high values. We use a two point calibration at 84 uS and 1,413 uS, so this divergence outside the calibration range is not all that surprising.

Kinnickinnic pH - July 31

Our pH values, while still exhibiting similar trends, show the greatest discrepancy between the two units that, disconcertingly, varies throughout the sample. We’ll be revisiting our calibration procedure for the pH probe to make sure we’re consistent with each unit.

For the Menomonee River




Menomonee pH - July 31

For the Menomonee, our units again performed similarly, with all but pH matching fairly closely.

Why the jagged or seemingly noisy segments? This is due to including both the paddle out and back along each segment on the same graph. So, for dissolved oxygen on the Menomonee for example, Unit #3 (in orange) returned significantly different values on the way out as compared to the way back in the 6,200 to 6,700 meter range. Mike, paddling Unit #3, took a different path on the way back in this segment and there appears to have been a significant cross-sectional change in the DO across the stream profile. Since we’re linearizing and combining both in- and out-paddles, our line graph bounces back and forth across these values.

Obviously, we still have a lot of explaining to do for each of these trends. We’ll leave that for another post for now.



In Water quality

By Eric Compas

Testing our water quality arrays in Milwaukee

On 02, Aug 2015 | In Water quality | By Eric Compas

Mike, Karl, and I had our first big day with the water quality arrays. With everything working fairly smoothly, we headed to Milwaukee for a long day of kayaking. Our goal was to paddle up and down the Kinnickinnic, the Menominee, and Milwaukee Rivers starting from the Milwaukee County boat ramp at River Front (at the east side of the Kinnickinnic and Milwaukee confluence). We were hoping to see differences between the freshwater estuary areas of the lower river reaches to the more stream-dominated upper sections.

Sampling in Milwaukee

Sampling in Milwaukee

Starting around 10am, we paddled all day (mostly into a stiff wind) to cover almost all the ground we were hoping to. We stopped around 6pm after one of Mike’s arms fell off (well, nearly) and around 14 miles of paddling. Both Mike and Karl had units on their boats running all the time, so any stretch of water was sampled four times — a good opportunity to see how our units compared with themselves and each other.

Here’s a look at the raw data from our units starting with dissolved oxygen (DO). Click on the Legend and Layers icons in the upper right to view the legend and to switch between temperature, pH, dissolved oxygen, and electrical conductivity (I’d suggest using the link to full screen map to explore the data in detail). Also, once you’re zoomed in, you can click on any point for detailed sample information.

(Note that the map refreshes itself every minute — this is for when we’re collecting data in real time.)

The map shows considerable variability for most of the metrics we measured. The most significant changes — seen best in the temperature layer — is from the lake-influenced section of each “river” (colder water) to the stream-influenced section of each (warmer water). We were somewhat surprised, though, in how smooth this transition was, particularly in the greater surface flow from the Milwaukee and Menominee Rivers.

The second noticeable change was the increase in electrical conductivity (EC) as we moved upstream. Both the Kinnickinnic and Menominee Rivers showed increases in EC as we moved into surface-dominated waters (particularly when the river current was noticeable) indicating high amounts of dissolved solids in this largely urban watershed (more info at Milwaukee Riverkeepers and SEWRPC) (likely salts from roadways, runoff from Mitchell Field, nutrients from urban yards, and industrial waste water). The Kinnickinnic, in particular, had a region of very poor water quality with high EC values and very low DO (lowest reading of 0.97 mg/L!).

We also were very pleased with the consistency of the measurements we were getting from each unit. They both matched fairly well at initial glance with a couple of discrepancies along a couple stream reaches. We also encountered problems with our server as we paddled the Kinnickinnic, so there are a few gaps in this sample stretch (which is recorded on backup files on the phones that we haven’t retrieved yet).

Stay tuned — we have additional analysis planned to explorer values from both units and other ways of visualizing trends.