UM research models water movement in L. Minnetonka

 

 

A doctoral student is working
on an ambitious computer modeling
project aimed at showing how
water moves through the lake and
is affected by climate conditions.
The modeling – so far applied to
only four of 26 bays – has the
potential to extrapolate from
water quality tests conducted
at a  relatively few spots in the lake
what the quality is likely to be at any
point in the lake, both now and into
the future.

Lake Minnetonka is a big, complex water body with 26 bays and water quality that varies significantly across the lake’s 22 square miles.

Several creeks wash soil from farm fields and suburban developments into the lake. Phosphorus bound to that soil causes summertime algal blooms that turn the water green in parts of the lake, choking out native plants and making the water unattractive for swimming, boating or fishing.

The algae also are fed by phosphorus from bottom sediment that holds a legacy of past runoff of soil and fertilizers, as well as the decades-ago discharge of treated sewage into the lake by lakeside communities.

 

In general, water quality improves, and the algae problem diminishes, as water moves from west to east through the connected bays, flowing toward Minnehaha Creek and then the Mississippi River.
Rainfall and the volume of water flowing into the lake from the creeks influence the water quality, making the algae problem better in some summers, worse in others. Other climate conditions, such as temperature and the speed and directions of winds that stir up the lake’s surface, also are factors.

missaghi400
Shahram Missaghi at the university’s Stream Lab, where
where he is investigating climate change and its possible
impact on near-shore lake plants
.

Scientists know a lot about Lake Minnetonka, but not enough to understand  why the water quality varies as it does, why some areas offer good support  for fish and native plants, and others do not.
Nor can the scientists predict with precision how a change in some factors – say, a reduction in the phosphorus  inflow from one of the bay’s watersheds, or the increased temperatures expected with global warming – would affect water quality throughout the big lake over time.

Now a University of Minnesota doctoral student is working on an ambitious computer modeling project aimed at showing how water moves through the lake and is affected by climate conditions. The modeling – so far applied to only four of 26 bays – has the potential to extrapolate from water quality tests conducted at a  relatively few spots in the lake what the quality is likely to be at any point in the lake, both now and into the future.

Over the last three years, Sharam Missaghi, working under the direction of civil engineering professor Miki Hondzo at the University of Minnesota’s St. Anthony Falls Laboratory, has been testing the applicability of two Australian water quality models to Lake Minnetonka.

The results from testing on four of the lake’s bays have been promising.

Missaghi is still tweaking and testing the models, but he has used them to map good and bad fish habitat in the four bays, and he now is preparing to use the models to try to predict how water quality in the bays might be affected by rising temperatures anticipated by 2050 due to climate change.

He also has a decidedly non-computerized project that involves growing near-shore plants common to Lake Minnetonka in separate tanks, each filled with water to a depth associated with the lake’s water level in years of high, low and average rainfall. The goal is to understand how a changing climate might affect  the plant life.

Missaghi, who earned a bachelor’s degree in biology and a master’s in environmental science at Bemidji State University, was the water resources engineer for the City of Plymouth from 1995 to 2007. In addition to pursuing a doctorate in water resources science, he now works as a University of Minnesota Extension educator, advising cities on storm water management.

The Lake Minnetonka modeling that is the subject of this PhD research was suggested by Lorin Hatch, a senior water quality specialist for HDR Engineering who is an adjunct professor in the university’s Department of Fisheries, Wildlife and Conservation Biology.

Hatch formerly was water quality specialist at the Minnehaha Creek Watershed District, which manages Lake Minnetonka. While he was at the watershed district, Hatch began an intensive water monitoring program that measures a number of parameters in the lake:  temperature; clarity; phosphorus and nitrogen content; dissolved oxygen; and chlorophyll, a measure of algae concentration.

The testing is conducted about every two weeks during the summer at a single spot in each of the lake’s bays.

Hatch said the complexity of the way water moves between the many bays defied conventional thinking about treating each bay’s water quality as an isolated problem to be solved primarily within the bay and on the adjacent land.  What lake managers needed, he said, was a sophisticated computer model that would predict water flow within the lake and show how water quality in each bay is influenced by the water passing through it.

Hatch urged Hondzo to find a graduate student to pursue the modeling.

Missaghi took up the challenge of applying and adapting two computer models, developed at the Centre for Water Research at the University of Western Australia, to four bays in the southwest corner of Lake Minnetonka.  The bays are: Halsted, Priest, Cooks and West Upper Bay.

Before he could begin testing the models, Missaghi spent parts of two summers working with Minnehaha Creek Watershed District staff in a district project to map the depth of the entire lake with a sonar-like device attached to a pontoon boat. The team also collected samples of the lake bottom sediment.

The map they produced offered a far more accurate, far more complete, picture of the lake bottom than the the 1950s-era chart it replaced.

Then Missaghi began to apply the models.

One of the models divides the four bays into about 3,000 cells, each 200 meters square by a half-meter deep. The model estimates how water flows into and out of each cell, both horizontally and vertically.
The second model factors in the known results of the water sampling and known climate data and estimates how nutrients in the water – nitrogen and phosphorus, but especially phosphorus – interact and move about. The model predicts whether phosphorus coming into the bays from creeks stays in the water, gets taken up by algae or attaches itself to sediment on the lake bottom.

And it predicts whether the phosphorus already in the sediment at the bottom of a bay stays there, gets re-circulated within the bay or flows on to the next bay.

“One figures out how the water moves, and one figures out the fate,” Missaghi said of the models. “The difficulty was to learn how they work together.”

To assess whether the two models worked for Lake Minnetonka, Missaghi  took the water quality results from the first round of testing conducted in 2000, applied the known weather conditions from that summer and asked the models to predict the water quality results for each subsequent sampling, about two weeks apart, that year. Then he did the same thing for 2005.

In effect, he was checking the accuracy of the modeling by asking it to answer questions whose answers he already knew.

The comparison between the modeled results and the actual data showed the models worked as such computer simulations often do:  Not perfectly, but acceptably.

In a paper that Missaghi and Hondzo published in 2010 in the journal “Ecological Modelling,” they said the correlation between the models’ predictions and the recorded data – the extent to which the models provided the answers they knew to be true – ranged from remarkable to reasonably good.

The modeling, performed on computers at the University of Minnesota Supercomputer Institute, did a very good  job of predicting how weather and flow affected the lake water’s dissolved oxygen content,  a key water quality indicator. The models did a reasonable job of predicting phosphorus content and algae concentrations.

“His model predicts in time and three dimensions the variability of lake water quality,” said, Hondzo, Missaghi’s dissertation adviser. And, Honzo said, the modeling done so far has yielded new insights about when and how lake sediment gives up, or retains, phosphorus.

Missaghi now is working to improve the models’ ability to accurately predict when and where algal blooms, especially toxic blue-green algae, will occur on the lake. 

Although most of the modeling work so far has been theoretical, it has practical lake-management implications, especially if it is extended to the entire lake.

Kelley Dooley, a water quality technician for Minnehaha Creek Watershed District, said Missaghi’s water-quality modeling can inform lake managers’ decisions, for example, on where they should concentrate efforts to restore lake shorelines.

“We should be able to choose a site, not just because it looks good, but we would be able to know from his modeling whether the plants had a better chance to survive there,” Dooley said.