shawano lake watershed assessment final report

Watershed Assessment of Shawano Lake, Shawano County, Wisconsin

Final Report

February 2008

University of Wisconsin – Stevens Point

Center for Watershed Science and Education N. Turyk, K. Foster, D. Hoverson, P. McGinley

Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point

Acknowledgements

The Shawano Lake study and report reflects the efforts of many groups and individuals from the Wisconsin Department of Natural Resources, the University of Wisconsin Stevens Point, the Shawano County Government, and Shawano’s citizens. Thank you all for the direction provided. Special thanks to:

• Phil Zhuse, Gary DeFere, Bob Hynek, Greg and Diane Rick, and David Fisher for their participation in meetings, planning, and use of boats, and volunteer monitoring.

• Wisconsin Department of Natural Resources, Shawano Area Waterways Management Inc., Shawano County, and the University of Wisconsin Stevens Point Center for Watershed Science and Education whose funding allowed for the Shawano Lake Study.

• Nancy Turyk, whose expertise on data examination, report writing and editing, and lake sample scheduling were integral for the completion of the study.

• Dr. Paul McGinley, University of Wisconsin Stevens Point, for direction with data analysis and computer modeling.

• Ron Ostrowski, Shawano County Conservationist, for helpful insights into agricultural management practices in the watershed.

• Mary Gansberg, Jay Moynihan, and Bob Korth for their roles as organizational leader in lake meetings, and for providing insight for public relations and local regulations.

• To the residents of Shawano Lake for their willful and involved participation and use of the Lake Study.

• Dick Stephens, Bill DeVita, Kandace Waldmann, Deb Sisk, and all the members of Water and Environmental Analysis Lab for their excellent work processing water samples.

• Bill James for assistance with sediment internal loading expertise and use of continuous DO monitoring equipment.

• Student Associates at the Center for Watershed Science and Education for assistance with sample collection and data entry, including Adam King, Kyle Homan, John Mumm, Adam Skadsen, Tiffany Short, Andy Janecki, Luke Hennigan, and Mark Breunig.

• Donna Hobscheid for covering stories about this study in the Shawano Leader.

Shawano Lake Watershed Assessment, Febraury, 2008 UW-Stevens Point ii

Executive Summary This document is the culmination of the Shawano Lake watershed assessment study initiated in

2004. The project has been a cooperative effort between Shawano County, Shawano Area Waterways Management, Inc. (SAWM), the University of Wisconsin–Stevens Point (UWSP) Center for Watershed Science and Education (CWSE), the U.S. Army Corps of Engineers (USACOE), the Wisconsin Department of Natural Resources (WDNR), and the Fox Wolf Watershed Alliance (FWWA), Northern Environmental, and the dedicated volunteers and citizens of the Shawano Lake area.

Shawano Lake is located in east central Wisconsin in Shawano County. The 6,178‐acre lake is the 3rd largest inland water body in Wisconsin. It has a 74 square mile watershed within the Wolf River Basin. This impounded drainage lake is relatively shallow for its size, with a maximum depth of 40 feet (WDNR, 2001). The City of Shawano; Village of Cecil; Towns of Wescott, Washington, and Richmond are located adjacent to the lake. The Shawano Lake watershed is located predominantly in Shawano County, but extends into Menominee and Oconto Counties.

Shawano Lake is heavily used year‐round for recreation and is economically significant to Shawano County. The concerns of local citizens and SAWM members about excessive aquatic plants, blue‐green algae blooms, and reduced water clarity led to this study. Field work was conducted throughout the duration of the study to obtain an extensive data set needed to better understand the hydrology and water quality in Shawano Lake. These data included water quality data from the lake, tributaries, and groundwater; rates of tributary and groundwater discharge into Shawano Lake, lake sediment data, and aquatic macrophyte surveys. Most of these data sets were used to calibrate models to help estimate the annual mass phosphorus contributed to Shawano Lake annually, and to make predictions about future water quality. The study also included an extensive land‐use analysis, which was used to help explain variation in water chemistry observed throughout the sub‐watersheds.

Shawano Lake and its watershed comprise a fairly complex system. In general, Shawano Lake has relatively good water quality for a shallow drainage lake. The lake tends to have enriched sediment and relatively shallow depths which results in good growing conditions and light penetration for aquatic plant growth in more than half of the lake. In addition to the natural complexity associated with a relatively shallow lake, Shawano Lake’s ecosystem appears to be in flux due to the introduction of many non‐native aquatic organisms including zebra mussels, Eurasian water milfoil, and curly‐leaf pondweed. Warmer regional temperatures are also increasing the number of days without ice and therefore increasing the period of time that productivity can occur. The results of this study help to understand the state of Shawano Lake and its watershed.

Seasonal and annual variability were observed in water chemistry and flow. Summer stratification is rare and not wide‐spread throughout the lake, so the majority of the lake remains mixed which enables aquatic plants and algae to take advantage of nutrients that are redistributed in the water column. Short term increases in nutrient concentrations occur due to inputs associated with storms or snowmelt, phosphorus release from sediment, phosphorus release from mass aquatic plant die off, and/or sediment re‐suspension due to wind and/or heavy boating activity.

Water quality in Shawano Lake is dependent upon internal and external factors. The watershed, as a whole, contributes about half of the annual phosphorus load. This includes direct runoff and loading from tributaries. Land use practices near shore and within the watershed are probably the most manageable aspect in terms of phosphorus reduction and reduction of runoff and improved infiltration. It is also important to address land management issues further out in the watershed including reducing phosphorus inputs to groundwater.

The greatest single contributor of total phosphorus to Shawano Lake is internal sediment release; this is difficult and expensive to directly manage. The invasive aquatic plant curly‐leaf pondweed (P. crispus) is abundant in Shawano Lake. A large pulse of phosphorus is released after P. crispus dies off in June, which

Shawano Lake Watershed Assessment, Febraury, 2008 UW-Stevens Point iii

then becomes available for algae to utilize. Management strategies should specifically address the reduction of this aquatic plant. Phosphorus can also be reduced from Shawano Lake by removing nuisance aquatic plants.

Lake modeling demonstrates significant benefits from total phosphorus load reduction. A reduction of phosphorus in Shawano Lake will reduce the frequency of algae blooms. Although there is no single, clear phosphorus source that stands out as problematic, a watershed‐scale management approach may bring water quality in Shawano Lake closer to the desired levels.

In addition to data collection, analysis, and synthesis, communication amongst the study’s participants was, and continues to be, an important component of the project. Quarterly planning meetings and annual progress report meetings have been integral for creating a discussion forum where research findings were communicated, questions were asked and answered, ideas were proposed, and timelines were developed and updated. Continued interaction amongst involved parties will contribute to the effective interpretation and implementation of the findings and recommendations in this document. This project will be followed by the development of a strategic plan to lead into the most critical implementation phase.


Table of Contents ACKNOWLEDGEMENTS....................................................................................................................................................... I EXECUTIVE SUMMARY...................................................................................................................................................... II TABLE OF CONTENTS........................................................................................................................................................ IV LIST OF FIGURES ...............................................................................................................................................................VI LIST OF TABLES ................................................................................................................................................................. IX LIST OF EQUATIONS ...........................................................................................................................................................X UNITS AND CONVERSIONS ..............................................................................................................................................XI 1 INTRODUCTION ........................................................................................................................................................ 1

1.1 STUDY GOALS AND OBJECTIVES ............................................................................................................................... 1 2 METHODS ................................................................................................................................................................. 3

2.1 LAKE MEASUREMENTS AND SAMPLING STRATEGY....................................................................................................... 3 2.2 WATERSHED MEASUREMENTS AND SAMPLING STRATEGY ............................................................................................ 4

2.2.1 Tributary Sampling..................................................................................................................................... 4 2.2.2 Calculating Tributary Loads ...................................................................................................................... 4 2.2.3 Modeling Tributary Loads.......................................................................................................................... 5 2.2.4 SWAT Modeling of Watershed.................................................................................................................... 5 2.2.5 Landuse Assessment ................................................................................................................................... 5 2.2.6 Shoreland Studies ....................................................................................................................................... 6

2.3 GROUND WATER MEASUREMENTS AND SAMPLING STRATEGY ...................................................................................... 6 2.3.1 Study Design............................................................................................................................................... 6 2.3.2 Locations and chemistry of inflow.............................................................................................................. 6 2.3.3 Rates of inflow ............................................................................................................................................ 7 2.3.4 Comparative Estimation ............................................................................................................................. 7

2.4 NUTRIENT AND WATER BUDGETS AND SIMULATION MODELING .................................................................................... 7 2.4.1 Bathtub Model Structure............................................................................................................................. 8 2.4.2 Empirical Model Selection ......................................................................................................................... 8

2.5 INTERNAL LOADING EVALUATION............................................................................................................................. 9 2.6 AQUATIC PLANT ASSESSMENT................................................................................................................................. 9 2.7 LAKE AND WATERSHED COMMUNITY COORDINATION ................................................................................................. 9

3 RESULTS AND DISCUSSION: THE LAKE ................................................................................................................... 11 3.1 LAKE HYDROLOGY – WHERE THE WATER IS COMING FROM ......................................................................................... 11

3.1.1 Precipitation ............................................................................................................................................. 11 3.1.2 Surface Watersheds .................................................................................................................................. 11

3.2 LAKE WATER QUALITY......................................................................................................................................... 12 3.2.1 Dissolved Oxygen and Temperature......................................................................................................... 12 3.2.2 Phosphorus ............................................................................................................................................... 16 3.2.3 Soluble Reactive Phosphorus ................................................................................................................... 19 3.2.4 Total Nitrogen to Total Phosphorus Ratio................................................................................................ 19 3.2.5 Nitrogen.................................................................................................................................................... 20 3.2.6 Water Clarity and Chlorophyll a .............................................................................................................. 20 3.2.7 pH, Hardness, and Alkalinity.................................................................................................................... 23

4 RESULTS AND DISCUSSION: TRIBUTARIES AND WATERSHED............................................................................... 25 4.1 THE INFLUENCE OF LAND USE ............................................................................................................................... 25 4.2 GENERAL TRENDS, LANDUSE IN THE WATERSHED ..................................................................................................... 26 4.3 SUB‐WATERSHED EVALUATION.............................................................................................................................. 28

Shawano Lake Watershed Assessment, Febraury, 2008 UW-Stevens Point v

4.3.1 Sub-watershed 1 ....................................................................................................................................... 28 4.3.2 Sub-watershed 2 ....................................................................................................................................... 28 4.3.3 Sub-watershed Tributary of 2 ................................................................................................................... 28 4.3.4 Sub-watershed 3 ....................................................................................................................................... 29 4.3.5 Sub-watershed 4 ....................................................................................................................................... 29 4.3.6 Sub-watershed Tributary of 4 ................................................................................................................... 30 4.3.7 Sub-watershed 5 ....................................................................................................................................... 30 4.3.8 Sub-watershed East of 5 ........................................................................................................................... 31 4.3.9 Sub-watershed 6 ....................................................................................................................................... 31

4.4 NUTRIENT & POLLUTANT EVALUATION ................................................................................................................... 31 4.4.1 Chloride.................................................................................................................................................... 31 4.4.2 Total Suspended Solids ............................................................................................................................. 33 4.4.3 Total Nitrogen........................................................................................................................................... 34 4.4.4 Inorganic Nitrogen ................................................................................................................................... 36 4.4.5 Organic Nitrogen...................................................................................................................................... 38 4.4.6 Phosphorus ............................................................................................................................................... 39

4.5 SYNOPTIC STREAM SAMPLES................................................................................................................................. 43 4.6 MODELED PHOSPHORUS LOADS ............................................................................................................................ 44 4.7 SWAT MODEL OF THE WATERSHED ...................................................................................................................... 46 4.8 LAKESHORE LANDUSE AND SHORELAND LOADS......................................................................................................... 46

4.8.1 Runoff ....................................................................................................................................................... 46 4.8.2 Soils and Groundwater ............................................................................................................................. 48

5 GROUNDWATER ..................................................................................................................................................... 50 5.1 GROUNDWATER INFLOW ..................................................................................................................................... 50

6 PHOSPHORUS BUDGET .......................................................................................................................................... 51 6.1 PHOSPHORUS INPUTS.......................................................................................................................................... 51

6.1.1 Watershed Inputs ...................................................................................................................................... 51 6.1.2 Precipitation ............................................................................................................................................. 51 6.1.3 Sediment ................................................................................................................................................... 51 6.1.4 Aquatic Plant Removal ............................................................................................................................. 52 6.1.5 Biotic Addition/Removal........................................................................................................................... 52

6.2 PREDICTED PHOSPHORUS BUDGET......................................................................................................................... 54 6.2.1 Summary of Bathtub Modeling Results..................................................................................................... 55

7 NUTRIENT REDUCTION SCENARIOS ....................................................................................................................... 55 7.1 WILMS MODEL STRUCTURE AND RESULTS ............................................................................................................. 56

8 SUMMARY AND CONCLUSIONS ............................................................................................................................. 58 9 RECOMMENDATIONS............................................................................................................................................. 59 10 REFERENCES............................................................................................................................................................ 62


List of Figures Figure 1. Shawano Lake watershed, sampling points and associated sub‐watersheds. ....................2 Figure 2. Water quality sampling locations in Shawano Lake.............................................................3 Figure 3. Seasonal temperature variation causing the stratification and mixing of many Wisconsin lakes (Shaw et al, 2000)......................................................................................................................13 Figure 4 Temperature profiles measured at the West site in Shawano Lake....................................14 Figure 5 Dissolved oxygen profiles measured at the West site in Shawano Lake. ............................14 Figure 6 Temperature profiles measured at the East site in Shawano Lake. ....................................15 Figure 7 Dissolved oxygen profiles measured at the East site in Shawano Lake. ..............................15 Figure 8. Mean epilimnion TP concentrations (µg L‐1) by month in Shawano Lake. (UWSP and Self‐help data 2004‐2007), ........................................................................................................................17 Figure 9. TP concentrations (µg L‐1) depicting seasonal and annual variability in Shawano Lake. (UWSP and Self‐help data 2004‐2007)...............................................................................................18 Figure 10. 2006 hypolimnion and epilimnion TP concentrations (µg L‐1) at the East site of Shawano Lake. Hypolimnetic TP concentrations significantly increase from June to August with the onset of stratification. ........................................................................................................................18 Figure 11. TP concentrations (µg L‐1) samples collected during early morning sampling near dense aquatic plant beds. An increase in late June follows the senescence of curly leaf pondweed. .......19 Figure 12. Inorganic nitrogen concentrations (mg L‐1) representing measured concentrations on sampling dates. ..................................................................................................................................20 Figure 13. Average annual water clarity measurements in Shawano Lake 1968‐2007. ...................21 Figure 14. Water clarity measurements in Shawano Lake (2004‐2007). These measurements represent depth at which the Secchi disc was no longer visible in the water (average for May‐Oct is 9 ft). ....................................................................................................................................................22 Figure 15. Chlorophyll a concentrations (μg L‐1) in Shawano Lake. These values represent measured concentrations on sampling dates during study period. UWSP and Self‐help data 2004‐2007....................................................................................................................................................22 Figure 16. Seasonal increases of chlorophyll a correlate with the late summer peaks of phosphorus in Shawano Lake. Red line indicates nuisance concentrations of algae related to chlorophyll a and high enough concentrations of phosphorus to induce nuisance algal concentrations. ....................23 Figure 17. Increases of chlorophyll a correlate with a decrease in water clarity (secchi depth) measures in Shawano Lake. ...............................................................................................................23 Figure 18. Alkalinity (mg/L) and total hardness (mg/L) in Shawano Lake samples. .........................24 Figure 19. Landuse in the Shawano Lake watershed and sub‐watersheds. .....................................27 Figure 20. Landuse area by sub‐watershed in the Shawano Lake watershed. .................................27 Figure 21. Annual chloride load in monitored tributaries, 2005‐2007 .............................................32 Figure 22. Median chloride export rates in monitored tributaries of Shawano Lake watershed, 2005‐2007. .........................................................................................................................................32 Figure 23. Seasonal/flow components of median chloride loads in monitored tributaries of Shawano Lake, 2005‐2007. ................................................................................................................33 Figure 24. Annual total suspended solids load in monitored tributaries of Shawano Lake, 2005‐2007....................................................................................................................................................33 Figure 25. Median total suspended solids export rates in monitored tributaries, 2005‐2007 ........34

Shawano Lake Watershed Assessment, Febraury, 2008 UW-Stevens Point vii

Figure 26. Seasonal/flow components of median TSS loads in monitored tributaries in Shawano Lake watershed, 2005‐2007 ...............................................................................................................34 Figure 27. Measured TN concentrations in monitored tributaries and comparison to EPA reference concentrations (yellow box)...............................................................................................................35 Figure 28. Annual total nitrogen load in monitored tributaries of Shawano Lake, 2005‐2007........35 Figure 29. Median total nitrogen export rates in monitored tributaries in Shawano Lake watershed, 2005‐2007 ..........................................................................................................................................36 Figure 30. Seasonal/flow components of median TN loads in monitored tributaries in Shawano Lake watershed, 2005‐2007 ...............................................................................................................36 Figure 31. Comparison of monitored tributary NO2

++NO3‐ concentrations to EPA reference

concentrations (yellow box)...............................................................................................................37 Figure 32. Annual inorganic N loads in monitored tributaries of Shawano Lake, 2005‐2007 ..........37 Figure 33. Median inorganic N export rates in monitored tributaries, 2005‐2007 ..........................38 Figure 34. Seasonal/flow components of median inorganic N load in monitored tributaries of Shawano Lake, 2005‐2007 .................................................................................................................38 Figure 35. Annual organic nitrogen load in monitored tributaries of Shawano Lake, 2005‐2007 ...39 Figure 36. Median organic nitrogen export rates in monitored tributaries of Shawano Lake, 2005‐2007 ....................................................................................................................................................39 Figure 37. Seasonal/flow components of organic N load in monitored tributaries of Shawano Lake, 2005‐2007 ..........................................................................................................................................39 Figure 38. Comparison of tributary TP concentrations to EPA reference concentrations (yellow box)............................................................................................................................................................40 Figure 39. Annual TP load, averaged over 3 years in monitored tributaries of Shawano Lake, 2005‐2007 ....................................................................................................................................................41 Figure 40. Annual SRP load, averaged over 3 years in monitored tributaries of Shawano Lake, 2005‐2007 ..........................................................................................................................................41 Figure 41. Median TP export rates in monitored tributaries, 2005‐2007.........................................42 Figure 42. Median SRP export rates in monitored tributaries, 2005‐2007.......................................42 Figure 43. Seasonal/flow components of TP load in monitored tributaries of Shawano Lake, 2005‐2007 ....................................................................................................................................................42 Figure 44. Seasonal/flow components of SRP load in monitored tributaries of Shawano Lake, 2005‐2007 ....................................................................................................................................................43 Figure 45. Synoptic survey stream sampling sites, sub‐watersheds, and land use ..........................44 Figure 46. Calculated TP load, compared to FLUX TP load, averaged over 3 monitoring seasons, 2005‐2007 ..........................................................................................................................................46 Figure 47. Long‐term annual phosphorus loads from all tributaries and unmonitored regions. .....46 Figure 48. Impervious surfaces on shoreland parcels.......................................................................47 Figure 49. Annual TP load from Shawano shorelands, predicted with SLAMM and calculated with export coefficients and NRCS curve numbers....................................................................................48 Figure 50. Soil test phosphorus in shoreland parcels (undeveloped sampled parcels are green). ..49 Figure 51. Mini‐piezometer sites and groundwater flow along the Shawano Lake perimeter. .......50 Figure 52. General predicted contributions to the Shawano Lake phosphorus budget...................54 Figure 53. Specific predicted contributions to the Shawano Lake phosphorus budget. ..................55 Figure 54. Relationship between changes in the averaged 2005‐2007 external total phosphorous load and predicted TP and chlorophyll a concentrations for Shawano Lake.....................................56

Shawano Lake Watershed Assessment, Febraury, 2008 UW-Stevens Point viii

Figure 55. Predicted bloom frequencies (%) and associated chlorophyll a concentrations for four scenarios, 20% reduction, 40% reduction, and 20% increase from the averaged 2005‐2007 total phosphorous external loading. ..........................................................................................................56 Figure 56. Stream sections in sub‐watershed 3 where buffers are missing or thinner than 35 ft (red circles).................................................................................................................................................60 Figure 57. Identified stream sections in sub‐watersheds 4, trib of 4, 5, east of 5, and 6 where buffers are missing or thinner than 35 ft (red circles) .......................................................................61 Figure 58. Site 1 modeled vs. measured 2005 ................................................................................ C-I Figure 59. Site 1 modeled vs. measured 2006 ................................................................................ C-I Figure 60. Site 1 modeled vs. measured 2007 ................................................................................ C-I Figure 61. Site 2 modeled vs. measured 2005 ............................................................................... C-II Figure 62. Site 2 modeled vs. measured 2006 .............................................................................. C-II Figure 63. Site 2 modeled vs. measured 2007 ............................................................................... C-II Figure 64. Site 3 modeled vs. measured 2005 ..............................................................................C-III Figure 65. Site 3 modeled vs. measured 2006 ..............................................................................C-III Figure 66. Site 3 modeled vs. measured 2007 ..............................................................................C-III Figure 67. Site 4 modeled vs. measured 2005 ..............................................................................C-IV Figure 68. Site 4 modeled vs. measured 2006 ..............................................................................C-IV Figure 69. Site 4 modeled vs. measured 2007 ..............................................................................C-IV Figure 70. Site 5 modeled vs. measured 2005 ...............................................................................C-V Figure 71. Site 5 modeled vs. measured 2006 ...............................................................................C-V Figure 72. Site 5 modeled vs. measured 2007 ...............................................................................C-V Figure 73. Measured and SWAT simulated monthly P loads (kg) at site 1 ...................................C-VI Figure 74. Measured and SWAT simulated monthly P loads (kg) at site 2 ..................................C-VI Figure 75. Measured and SWAT simulated monthly P loads (kg) at site 3 ................................. C-VII Figure 76. Measured and SWAT simulated monthly P loads (kg) at site 4 ................................. C-VII Figure 77. Measured and SWAT simulated monthly P loads (kg) at site 5 ................................C-VIII


List of Tables Table 1. Depth increments in Shawano Lake ......................................................................................1 Table 2. Water quality data sources used for the BATHTUB models..................................................8 Table 3. Empirical total phosphorus and chlorophyll a models used for each BATHTUB model .......9 Table 4. Hypolimnion and epilimnion TP concentrations (µg L‐1) in samples collected in summer from the East site during different mixing scenarios. ........................................................................18 Table 5. Landuse breakdown in sub‐watershed 1 and stream corridor ...........................................28 Table 6. Landuse breakdown in sub‐watershed 2 and stream corridor ...........................................28 Table 7. Landuse breakdown in sub‐watershed Tributary of 2 and stream corridor .......................29 Table 8. Landuse breakdown in sub‐watershed 3 and stream corridor ...........................................29 Table 9. Landuse breakdown in sub‐watershed 4 and stream corridor ...........................................30 Table 10. Landuse breakdown in sub‐watershed Trib of 4 and stream corridor..............................30 Table 11. Landuse breakdown in sub‐watershed 5 and stream corridor .........................................30 Table 12. Landuse breakdown in sub‐watershed East of 5 and stream corridor .............................31 Table 13. Landuse breakdown in sub‐watershed 6 and stream corridor .........................................31 Table 14. Results of synoptic sampling for TP in the Shawano Lake watershed, where “total” represents the entire sub‐watershed upstream of the established monitoring site ........................44 Table 15. Seven‐month tributary outflow and phosphorus export for Shawano Lake watershed ..45 Table 16. Chemistry and SRP loads in groundwater entering Shawano Lake...................................51 Table 17 Summary of Myriophyllum spicatum harvesting records and estimated phosphorus removal from Shawano Lake, 2005‐2007. .........................................................................................52 Table 18. Summary of zebra mussels collected from sampling plates located throughout Shawano Lake. ...................................................................................................................................................53 Table 19. Summary of predicted phosphorus inputs to Shawano Lake. ..........................................54 Table 20. Summary of observed (2005‐2007) and predicted mean TP and chlorophyll a concentrations....................................................................................................................................55 Table 21. Estimated total phosphorus concentrations in Shawano Lake from hydrologic and phosphorus loading models contained in the WiLMS for scenarios specified to calibrate and what‐if scenarios.............................................................................................................................................57 Table 22. Predicted chlorophyll a concentrations secchi depths for four scenarios, 20% reduction, 40% reduction, current estimate, and 20% increase from the averaged 2005‐2007 total phosphorous external loading ...........................................................................................................57 Table 23. TP from sample sites........................................................................................................ A-I Table 24. SRP from sample sites.....................................................................................................A-II Table 25. NO2

‐ +NO3‐ from sample sites .........................................................................................A-II

Table 26. TKN from sample sites ...................................................................................................A-III Table 27. TN from sample sites .....................................................................................................A-III Table 28. NH4

+ from sample sites ................................................................................................. A-IV Table 29. Site 1 stage/flow relationship.......................................................................................... B-I Table 30. Site 1 rating curve ............................................................................................................ B-I Table 31. Site 1 hydrograph ............................................................................................................ B-I Table 32. Site 2 stage/flow relationship......................................................................................... B-II Table 33. Site 2 rating curve ........................................................................................................... B-II

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Table 34. site 2 hydrograph............................................................................................................ B-II Table 35. Site 3 stage/flow relationship........................................................................................B-III Table 36. Site 3 rating curve ..........................................................................................................B-III Table 37. Site 3 hydrograph ..........................................................................................................B-III Table 38. Site 4 stage/flow relationship........................................................................................B-IV Table 39. Site 4 rating curve ..........................................................................................................B-IV Table 40. Site 4 hydrograph ..........................................................................................................B-IV Table 41. Site 5 stage/flow relationship.........................................................................................B-V Table 42. Site 5 rating curve ...........................................................................................................B-V Table 43. Site 5 hydrograph ...........................................................................................................B-V Table 44. Site 6 stage/flow relationship........................................................................................B-VI Table 45. Site 6 rating curve ..........................................................................................................B-VI Table 46. Site 6 hydrograph ..........................................................................................................B-VI

List of Equations Equation 1. Annual baseflow load.......................................................................................................4 Equation 2. Annual event load ............................................................................................................4


Units and Conversions Several different units are used in this document, depending on the scale of the parameter being

measured. The following is a list of metric units and their equivalents, both metric and English. Volume: 1 cubic hectometer (hm3) = 1,000,000 m3 = 35,314,666.70 ft3 1 L = 0.26 gal = 0.04 ft3

1 m3 = 264.17 gal Area: 1 hectare (ha) = 2.47 acres Mass: 1 kg = 2.2 lbs Nutrient Export Rate: 1 kg/ha/yr = .89 lb/acre/yr Concentration: 1 mg/L = 1000 μg/L

Shawano Lake Watershed Assessment, Febraury, 2008 UW-Stevens Point 1

1 Introduction Shawano Lake is located in east central Wisconsin in Shawano County. The 6,178‐acre lake is the

3rd largest inland water body in Wisconsin. Shawano Lake’s watershed has an area of 74 square miles (47,454 acres) and is located within the Wolf River Basin (Figure 1). With a maximum depth of 40 feet, this impounded drainage lake is relatively shallow for its size. The depth summary in Table 1 demonstrates that a very small portion of the lake is deeper than 20 feet, and over half of the lake is between 3 and 10 feet deep.

The City of Shawano, Village of Cecil, Towns of Wescott, Washington, and Richmond are located adjacent to the lake. The Shawano Lake watershed is located predominantly in Shawano County, but extends into Menominee and Oconto Counties. Shawano Lake is heavily used year round for recreation and is economically significant to Shawano County. The concerns of local citizens and SAWM members about excessive aquatic plants, blue‐green algae blooms, and reduced water clarity led to this study.

Depth (ft) Acres% of Lake Surface

0‐3 676 10.93‐5 1648 26.55‐10 1712 27.510‐15 1146 18.415‐20 664 10.720‐25 224 3.625‐30 82 1.330‐35 45 0.735‐40 23 0.4

Table 1. Depth increments in Shawano Lake

1.1 Study Goals and Objectives The goals of this study were to better understand Shawano Lake and its watershed, inform citizens

about the lake, and establish a lake management partnership to identify scientifically based management options. Specific objectives of the UWSP study included:

• assessing the current water quality of Shawano Lake, its tributaries, and the groundwater entering the lake

• estimating in‐lake, near lake, surface, and groundwater watershed nutrient contributions • developing water and nutrient budgets using predictive models • fostering a cooperative and active community focused on Shawano Lake and its watershed • providing the community and agencies with information needed to develop science‐based

management strategies


Figure 1. Shawano Lake watershed, sampling sights and associated sub‐watersheds.


2 Methods Many processes affect water quality, algae, and aquatic plant conditions in Shawano Lake;

therefore, an array of sub‐studies were conducted to evaluate hydrologic and nutrient movement within the Shawano Lake system.

2.1 Lake Measurements and Sampling Strategy UWSP along with SAWM volunteers conducted in‐lake water quality monitoring from the spring of

2004 to the fall of 2007. Lake water quality data was collected at two of the deep points in each basin (Figure 1). Profiles of temperature, dissolved oxygen, pH, specific conductance, and water clarity were taken and water samples were acquired for lab analysis. During the summer season lake samples were analyzed for phosphorus, nitrogen, total hardness, alkalinity, and chlorophyll a (an indicator of algae). With the onset of stratification in the summer of 2006 and 2007, hypolimnion water samples were collected and analyzed for phosphorus to determine nutrient enrichment in this lower layer. Additional analyses were performed on samples collected during overturn in the spring and fall.

In 2006 water samples were collected and profiles were measured at multiple locations around the lake during periods of heavy boat traffic and in the early morning when dissolved oxygen concentrations are generally at lowest levels (Figure 2). The samples were analyzed for total phosphorus. This sampling strategy allowed evaluation of the spatial distribution of phosphorus in Shawano Lake and a snapshot of potential effects from heavy boat traffic and aquatic plant respiration contributions to overall phosphorus enrichment.

All samples were kept on ice during transport to the lab. Water chemistry analysis was performed at the state certified UWSP Water and Environmental Analysis Lab and the Wisconsin State Lab of Hygiene.

Figure 2. Water quality sampling locations in Shawano Lake.


2.2 Watershed Measurements and Sampling Strategy 2.2.1 Tributary Sampling

To understand how the watershed influences water quality in Shawano Lake, water monitoring was preformed at six tributaries (Site 1, Loon Creek; Site 2, Duchess Creek; Site 3, Pickerel Creek; Site 4, unnamed tributary; Site 5, Murray Creek; and Site 6, Resort Creek). Tributary nutrient concentrations and water flow rates were measured. A delineation of six sub‐watersheds was used to determine the area of land each tributary drains (Figure 1). All unmonitored sub‐watersheds and shorelands are represented in Figure 1 as a pale yellow color.

Stream flow was measured with pressure transducers, staff gauges, and stream flow measurements. Water samples were collected for lab analysis throughout the year and during a variety of flow conditions. Samples were collected during low flow (baseflow) using the grab method and during high flow using siphon samplers. The siphon samplers were set at varying depths in each tributary to collect samples during different points in a storm or snow melt event. The arrangement of siphon samplers was intended to explore if and how nutrient concentrations varied with stream flow intensity related to precipitation and runoff. A synoptic sampling procedure was used in 2007 to collect additional high flow samples at locations upstream of the normal monitoring sites. These samples allowed us to evaluate how landuse changes from the upper to lower reaches of sub‐watersheds affected TP concentrations in the streams. A scaling procedure was used to estimate nutrient concentrations and flow in the unmonitored tributaries. Nutrient loads and flows from adjacent watersheds with similar land use and relief characteristics were scaled by area to the unmonitored watershed of interest.

2.2.2 Calculating Tributary Loads

The estimated flow and water quality data from the unmonitored sub‐watersheds, as well as the measured data from the monitored sub‐watersheds, were used to calculate contributions from each sampling sub‐watershed and to develop nutrient and water budgets. To calculate loads, average daily flow rates were first categorized as baseflow or event flow. This permitted us to designate each water sample collected as either a baseflow or event sample, thus providing a range of water chemistry data specific to the two types of flow. A load was calculated for every observed baseflow concentration (Equation 1) to provide a range of possible loads. Because the water chemistry data varied from one sample to the next for an individual stream, we could not calculate a single, definite load. By calculating a range of loads, we were able to describe baseflow loads in terms of 25th, 50th, and 75th percentiles because a large number of observations were available. Percentiles describe the calculated load that is greater than the specified percent of all other calculations. For example, the 25th percentile is the load that is greater than 25% of all the possible loads we calculated. Event samples were described as seasonal averages. Since these samples were divided into three seasons (baseflow was assumed throughout the winter), there were not enough samples in a single season to display percentiles (Equation 2).

Equation 1. Annual baseflow load

Baseflow load (kg) = (baseflow concentration) × (total baseflow volume) Equation 2. Annual event load

Event load (kg) = ∑ (mean event concentration)season × (total event volume)season The total annual loads could be described in terms of percentiles because a single event load was

added to every calculated baseflow load. When the relative contribution of each flow type was explored, only the median baseflow load was used.


2.2.3 Modeling Tributary Loads

Annual phosphorus loading was further explored with a model. The annual yields (loads) of TP were calculated with FLUX, a model to estimate TP loads through a flow‐concentration relationship (Walker 1996). The model, which is a more sophisticated approach to TP load estimation than the averaging methods discussed in the previous section, provided a check against the accuracy of the calculated phosphorus loads. Each of the monitoring stations was modeled individually using a continuous record of mean daily flow and nutrient concentration data from sampling during the 2005 and 2006 field seasons. A daily flow record was created using flow measurements and depth measurements from pressure transducers. Nutrient concentrations were analyzed from grab samples and siphon samples. When a runoff event triggered multiple siphons at a single site, composite phosphorus concentrations were calculated by the model.

Prior to modeling, stream data was stratified by flow and/or season, depending on which strategy produced the best load/flow correlations. Phosphorus loading was calculated using several regression methods (Appendix B); the method which most closely estimated the observed concentrations (i.e. the lowest error) was selected for each stream. The best fit regression was used to generate daily cumulative flows and phosphorus loads.

2.2.4 SWAT Modeling of Watershed

Outputs from the FLUX model were used to calibrate SWAT. The SWAT model averages characteristics of the land and its management within hydrologic response units (HRUs). These HRUs are established based on combinations of land management and soils. The Shawano Lake watershed was divided into 24 different HRUs based on overlaying land use (WISCLAND) and soils (STATSGO). These included forest, wetland, agricultural and urban land with different soils.

Properties of the HRUs were based on SWAT model defaults and some modifications through a calibration process to better fit the observed measurements. To account for agricultural rotations and variations in chemical fertilizer and manure, a generalized row‐crop management system was used. Watershed‐wide runoff curve numbers for different HRUs and soil erosion parameters were adjusted during the calibration process. The urban area impervious fraction and percentage connection was also adjusted during the calibration. The calibration was through trial and error with adjustments to the model made using recommendations in the SWAT User’s Manual to improve the fit between modeled and observed flow and phosphorus loads.

2.2.5 Landuse Assessment

Model results allowed us to determine problem areas within the watershed (i.e. those sub‐watersheds that contribute disproportionately high nutrient loads per unit area). Landuse within problem areas was further explored to pinpoint the major nutrient sources within the particular sub‐watershed. Landuse was evaluated in all sub‐watersheds and the nearshore region, as well as within a seventy foot corridor of all tributaries. The evaluation was performed with GIS software using a 30m×30m grid compiled with 2001 landuse data.

Near‐shore land use and soil evaluations were performed to explore the importance of shorelands in nutrient loading. Landuse was further evaluated in the nearshore region to determine the amount of impervious surfaces that may increase the amount of runoff and pollutants delivered to the lake during storms. An orthophoto (aerial photo corrected for Earth’s curvature) with a one foot resolution was used with GIS software to obtain a precise value for the shoreland area covered by roofs, driveways, walkways, and other impervious surfaces.

Nutrient loss from urbanized pervious areas (e.g., lawns) was estimated based on previous studies and testing performed on several lawn sites near Shawano Lake. Data was mapped and utilized in the


nutrient models. Additionally, 64 riparian soil samples were collected for phosphorus analysis in 2006 and 2007. Data indicated the fertility of shoreland areas and enabled recommendations regarding the need for fertilizer additions.

2.2.6 Shoreland Studies

A landuse analysis was performed in the region of the watershed that drained directly to Shawano Lake rather than a tributary. Phosphorus from overland runoff was examined with a modeling approach. Of particular interest were the developed areas along the shoreline. An aerial photo was used with GIS software to digitize impervious surfaces (roofs, driveways, and walkways) on shoreland lots. The areas of impervious and pervious surfaces were used as inputs in the Source Loading and Management Model (WinSLAMM), an urban runoff model. Scenarios were modeled using different degrees of connection, that is, the portions of the impervious surfaces that drained either directly to the lake (connected) or onto a lawn or other pervious surface (disconnected). These scenarios were used to provide a range of phosphorus loads expected from the shoreland areas. The model was run assuming 0, 25, 50, 75, and 100 percent disconnection of all shoreland impervious surfaces.

Groundwater entering Shawano Lake also contained soluble reactive phosphorus (SRP). Potential shoreland sources of groundwater phosphorus were examined in a field study. Soil samples were collected from shoreland lawns for phosphorus testing. Groundwater samples were also collected from transects that extended down a lawn and into the lake. Samples were collected at two or three intervals along the transect, and a single sample was collected in the lake at the end of the transect. The sampling strategy was devised under the assumption that SRP concentrations would increase toward the lake as contact between groundwater and soil phosphorus increased. SRP concentrations in groundwater samples were compared to soil test phosphorus concentrations. The soil samples also allowed us to determine if lawn fertilization is recommended.

2.3 Ground Water Measurements and Sampling Strategy In August 2006, a groundwater study was conducted on the near shore region of Shawano Lake.

The objectives of this study were to determine (1) locations where groundwater enters the lake (inflow), and (2) the amount of phosphorus and nitrogen that groundwater contributes to the lake.

2.3.1 Study Design

Prior to the collection of any groundwater data on Shawano Lake, 189 shoreline study sites were selected at 152.4 meter (500 foot) intervals along the entire lake perimeter. Mini‐piezometers were installed at these sites to determine the locations of groundwater inflow and to collect groundwater samples for water quality analysis. Where groundwater inflow was documented, crews quantified the rate of groundwater inflow with seepage meters, and performed temperature and flow‐transects to determine the near‐shore extent of inflow. Temperature transects were based on the observation that areas of inflow would exhibit cooler temperatures than areas of no‐flow or outflow.

2.3.2 Locations and chemistry of inflow

Minipiezometers were constructed of a five‐foot length of polypropylene tubing. One end of the minipiezometer was sealed, above which a 3.94 in (10 cm) perforated area formed the screen of a well. The sealed, screened end of the minipiezometer was inserted 18 to 24 inches below the sediment surface, a depth deemed appropriate to avoid sampling water from the shallow sediment layer where biological activity can influence water chemistry.


Once the minipiezometer was inserted, a well was established by drawing water with a syringe. The syringe was detached from the minipiezometer and the water was allowed to fall. Groundwater inflow was occurring at locations where hydraulic head in the minipiezometer was higher than the lake surface, groundwater outflow was occurring where hydraulic head was lower than the lake surface, and no‐flow was occurring where hydraulic head and the lake surface were the same.

Where inflow was observed, a sample was usually collected for analysis of soluble reactive phosphorus, inorganic nitrogen (ammonium NH4

+, nitrite NO2‐, and nitrate NO3

‐), and chloride. Substrate and surface measurements of temperature, specific conductivity, and pH were recorded at all sites to supplement groundwater flow data.

2.3.3 Rates of inflow

To further quantify shoreline groundwater flow, seepage meters were installed at sites of inflow. Seepage meters were constructed from the cap‐ends, and the first eight inches of sidewall, of 55‐gallon high‐density polyethylene drums. The meters isolated an area of 0.24 m2 of lake bed. A valve was inserted into the drum cap, and attached via tubing and a quick‐release valve to a three‐liter enema bag sealed with a binder clip. Meters were inserted approximately four to six inches into the sediment and allowed to settle several hours to ensure that all lake water had been forced out by inflow. The bags were attached to the quick‐release valves and allowed to collect groundwater until a volume suitable for analysis was obtained.

2.3.4 Comparative Estimation

Annual groundwater inflow calculated from the seepage meters and mini‐piezometers was compared to an estimate of annual precipitation infiltration within the watershed. It is assumed that 2/3 of the annual precipitation becomes runoff and the remaining 1/3 infiltrates. The average annual rainfall for the region is 30 inches, which translates to 10 inches of infiltration annually. Groundwater contours were mapped using well data and surface water elevations within and beyond the watershed boundaries. The total groundwater shed and the tributary groundwater sheds were delineated based on the contours. Infiltration that occurs within the groundwater sheds of the tributaries contributes to baseflow, and the remaining infiltration contributes to groundwater inflow to the lake. During the summer some of the tributaries stop flowing; it is assumed that the water table has fallen to a depth where it is no longer intercepted by tributaries. During these periods the sub‐watersheds are no longer excluded from the lake groundwater contribution area because they can still contribute groundwater to the lake. Multiplying 10 inches of infiltration by the contributing area of Shawano Lake (including fluctuations in the contributing area when baseflow does not occur) provided a comparative estimate of annual groundwater inflow.

2.4 Nutrient and Water Budgets and Simulation Modeling The Wisconsin Lake Modeling Suite (WiLMS) and BATHTUB model were used to develop a

phosphorus budget for Shawano Lake and predict the response of algae bloom frequency to phosphorus reduction scenarios. WiLMS and BATHTUB can be used as both descriptive and predictive tools. By calibrating the models to observed data, predictions of how changes in the watershed may impact water quality conditions in the lake were obtained.

The WiLMS model uses watershed characteristics and lake response to predict total phosphorus (TP) concentrations in lakes. The WiLMS model structure is organized into four principal parts, which include the front‐end, phosphorus prediction, internal loading, and trophic response. The front‐end portion or model setup includes the lake characteristics, watershed loading calculation inputs, and the observed in‐lake TP. Both the phosphorus prediction and internal load estimator use the front‐end portion of the model for lake and watershed inputs. The phosphorus prediction portion contains 13 phosphorus prediction regressions


and the uncertainty analysis routines. The internal load estimation platform provides four methods to estimate a lake’s internal loading. The trophic response segment of the program develops a trophic evaluation and comparison. The models used in WiLMS are empirical methods developed via statistical analysis of lake and reservoir systems.

The BATHTUB model provides a more detailed tool for estimating lake response to TP loading. It consists of four primary parts. The first allows the user to choose the “best fit” model from a variety of empirical models that predict phosphorus, chlorophyll a, and other concentrations based on inputs to the lake. The second component involves defining “global variables”, which are applied to the entire model. These parameters include precipitation, evaporation, and atmospheric nutrient loads. The third component of BATHTUB allows the user to define the model segments. The user may define specific attributes for several different tributaries, and even divide a reservoir into different segments. Average depth, surface area, in addition to other information, is required for each segment. The fourth main component of BATHTUB involves defining water quality information for tributaries. This can be done in two ways, either by entering in actual observed data, or by using theoretical runoff coefficients based on land use. Information about how much flow the tributary has and its watershed area is also needed. The BATHTUB model was developed by William Walker Jr., USACOE.

2.4.1 Bathtub Model Structure

Four models were created in BATHTUB. One of the models was calibrated to field data collected and averaged from 2005, 2006, and 2007. The other three models were developed to predict how water quality in Shawano Lake might respond to potential changes in phosphorus from the watershed. A summary of the data sources used for the four models can be found below in Table 2.

Model Observed Water Quality Data Source

2005-2007 average CWSE & WDNRTP-40% modified from 2005-2007 average CWSE & WDNR dataTP-20% modified from 2005-2007 average CWSE & WDNR dataTP+20% modified from 2005-2007 average CWSE & WDNR data

Table 2. Water quality data sources used for the BATHTUB models The hydrologic inputs for the model were based on data collected from the six monitored

tributaries within the Shawano Lake watershed (previously described in this report). A flow calibrated model (FLUX) was used to estimate the annual contributions from the monitored tributaries; this data was then used to develop runoff coefficients for the unmonitored areas within the watershed. Inputs from groundwater were estimated using data collected by CWSE staff during the summers of 2006 and 2007. Within the lake, observed data was available from both the East and West sampling sites in Shawano Lake for 2005‐2007, which provided a comparison of observed data and the predictions made by BATHTUB. The BATHTUB model was not segmented. 2.4.2 Empirical Model Selection

A summary of the empirical models used in each BATHTUB model are found in Table 3. All versions of the model used a linear model based on phosphorous to estimate algae response represented by changes in chlorophyll a concentrations. Interestingly, it was observed that the relationship between phosphorus and chlorophyll a varied from year to year. The best fitting empirical model was selected by comparing the values of all empirical models to the observed data.


Model TP model Chlorophyll A model2005-2007 average Vollenweider P, Jones & Bach.TP-40% Vollenweider P, Jones & Bach.TP-20% Vollenweider P, Jones & Bach.TP+20% Vollenweider P, Jones & Bach.

Table 3. Empirical total phosphorus and chlorophyll a models used for each BATHTUB model Computer models are tools used to understand how and where water and nutrients are moving

into and out of Shawano Lake and how the processes within Shawano Lake affect the availability of nutrients along with algal and aquatic plant growth. Nutrient models that predict nutrient movement from the watershed to the outfall (Shawano Lake) require data specific to the watershed. Included are landuse categories, soil types, topographic information, and annual rainfall data. Models specific to urban areas may require additional information on the storm drainage systems present and the ratio of impervious to pervious surfaces. These predictive tools can be used during the lake management planning phase to test “what if” scenarios to estimate the best approaches for nutrient reduction.

2.5 Internal Loading Evaluation The two‐year USACOE internal phosphorus loading study was completed in September 2006 by

William James and Chetta Owens. The study examined the amount of phosphorus being recycled within Shawano Lake and under what conditions this cycling is occurring. The completed report, Experimental Determination of Internal Phosphorus Loading from Sediment and Curly‐Leaf Pondweed in Shawano Lake, Wisconsin, is available by contacting the U.S. Army Engineer Research and Development Center in Spring Valley, WI. Further evaluation of internal loading was preformed by UWSP graduate student Darrin Hoverson.

2.6 Aquatic Plant Assessment The USACOE completed a two‐year aquatic plant survey in September 2006. The survey provides

an estimate of aquatic plant biomass and nutrient release from decomposing plant matter. A completed report, Distribution of Eurasian Watermilfoil (Myriophyllum spicatum) and Curly Leafed Pondweed (Potamogeton crispus) in Shawano Lake, is also available through the USACOE. This work was used in water quality modeling, estimating responses in the lake from aquatic plants, and developing an aquatic plant management plan. Northern Environmental, an environmental consultant will be developing a comprehensive aquatic plant management plan with the data collected and input from the Shawano Lake steering committee and others involved.

2.7 Lake and Watershed Community Coordination A shoreline and resident survey was designed to assess the opinions and perceptions of lakeshore

and watershed citizens regarding water management issues, goals, objectives, and management options related to Shawano Lake. Survey questions were designed by FWWA, UWSP, SAWM, and Shawano County. The survey was conducted in June 2003 by the FWWA with more than 560 responses received; the compiled data can now be found on their website at www.fwwa.org/shawanolake.html .

This information will be used to identify issues that are important to Shawano area residents and will also provide guidance topic selection for workshops. Workshops will continue to be conducted throughout the study to update progress as well as provide information about Shawano Lake and its watershed, and to initiate discussions to prepare citizens for development of management options.

The next scheduled workshop will be hosted by SAWM at their 2007 annual meeting to be held Memorial Day weekend. Additional information about this meeting will be provided in the SAWM


newsletter and local papers. UWSP will provide a presentation on the lake study and results since last annual meeting in 2006. A news release about the study was printed in the Stevens Point Gazette and Waupaca Post. UWSP will provide an article for the SAWM and local municipal newsletters in March and will submit an article focusing on activities in 2007.


3 Results and Discussion: The Lake

3.1 Lake Hydrology – Where the water is coming from Understanding how water moves to and from a lake is critical to determining how to reduce inputs

to a lake. The amount of water going into and out of the lake defines the amount of time water stays in a lake, its water quality and thus, the aquatic plants and biota in an aquatic system. During snowmelt or a rainstorm, water moves across the surface of the landscape towards lower elevations such as wetlands, lakes and rivers, or internally drained areas (where water on the land’s surface recharges groundwater). The capacity of this landscape to hold water and filter particulates ultimately determines the water quality, habitat, and amount of erosion in and out of the stream. Simply put, the more the landscape can hold water during a storm, the slower the water is delivered to the wetlands and streams and the greater the ability to filter the runoff and result in better water quality for the receiving lake.

As water moves across the land surface, soluble and particulate matter is picked up and travels with the flow. Less surface runoff is generated and surface water runoff is partially filtered when water is infiltrated and plants divert and slow water movement causing sediment and associated nutrients to be deposited or absorbed. The best plant filters (buffers) consist of a combination of trees, shrubs, and deeply rooted perennial vegetation with well structured soil. Although some of the land around Shawano Lake and its tributaries has this type of vegetated buffer, one aspect or another is missing from much of the landscape.

Shawano Lake is receiving water from direct precipitation on the lake, surface runoff during rainstorms and snowmelt, and groundwater inflow. Shawano Lake is also receiving water from many tributary inflows around the lake and has one outlet in on the southwest corner of the lake. The majority of water entering the lake is through the inflow tributaries around the lake. The lake is 6,178 acres with a watershed that is 74 square miles. The retention time for the lake is approximately three years.

3.1.1 Precipitation

Precipitation feeds lakes and their tributaries directly via surface runoff and groundwater inflow. Near Shawano Lake, about one third of the precipitation that falls infiltrates into the ground to recharge groundwater. The rest of this precipitation is either lost through evapotranspiration or makes its way to wetlands, tributaries, or the lakes as surface runoff. A combination of interactions between topography, geology, soil, man‐made structures, drainages, and land use practices influence the water chemistry and both regional and local surface water flow. Historic precipitation records were acquired from the National Oceanic Atmospheric Association (NOAA); precipitation near Shawano Lake averaged approximately 30 inches per year, resulting in about 10 inches of annual groundwater recharge.

3.1.2 Surface Watersheds

A surface watershed is the land area where runoff from precipitation drains to water bodies before it can infiltrate into the ground. Surface watersheds with large amounts of steeply sloped land, stream inflows to the lake, and a large percent of impervious surface (buildings, roads, compacted soil) deliver additional surface runoff by averting infiltration into the soil and by funneling water directly to the lake. The surface watershed for Shawano Lake was determined using GIS software (ArcView) and a digital elevation map. Topographic and storm sewer maps were used to ground truth the delineation based on elevation contours and natural or man‐made inflows that feed or divert water to/from the lake (Figure 1). The surface watershed has an area of 19204 ha (47450 acres).


3.2 Lake Water Quality For the past four years UWSP and local volunteers have been collecting water quality

measurements such as temperature, dissolved oxygen, pH, water clarity, and multiple water samples for laboratory analysis of nutrients, total hardness, alkalinity, chloride, and chlorophyll a. Historic data including Self‐Help data, WDNR data, and data collected from previous studies was also included in the water quality evaluation.

3.2.1 Dissolved Oxygen and Temperature

Dissolved oxygen is the amount of oxygen contained in water and is significant to aquatic ecosystems since many aquatic organisms depend on it for survival and growth. Dissolved oxygen enters lake water by diffusion from the air and photosynthetic activity from aquatic plants. Greater wind and wave interaction with the atmosphere improves diffusion of oxygen into the water.

Increased biological activity in a lake can reduce dissolved oxygen concentrations in water. Decaying organic material in the lake reduces oxygen as it is consumed by decomposers during respiration. An increased biomass of aquatic plants and algae results in reduced oxygen concentrations during the fall and winter, when respiration rates from decomposers are highest. Nutrient additions to the lake often result in increased plant and algal growth. These nutrients come from fertilizers, soil, and vegetation carried to Shawano Lake and its tributaries during runoff events, in groundwater, and can be contained in buried wetland sediment.

Dissolved oxygen concentrations are also affected by water temperature. Cold water can contain more oxygen than warmer water. Temperature variations throughout the year affect how water mixes with the atmosphere because the density of water changes with temperature changes. Water is densest at 39°F (4°C), which causes ice to float and water to mix periodically throughout the year. For example, in a typical year in Shawano Lake, ice melts in early spring, and the temperature of the lake water is similar from top to bottom (Figure 3). The presence of wind causes the lake to uniformly mix because all the water is the same density. Mixing redistributes dissolved oxygen and other dissolved constituents evenly from top to bottom within the lake. This mixing phenomenon is called overturn.


Figure 3. Seasonal temperature variation causing the stratification and mixing of many Wisconsin lakes (Shaw et al, 2000).

As surface water warms in late spring, the density of surface water decreases, keeping this warmer

water “floating” above the cooler, denser bottom water (Figure 3). Layers of warm and cooler waters have differing densities which creates layering or stratification. The surface water remains in contact with atmospheric oxygen, while the lower layers do not. When layering exists for extended periods of time, dissolved oxygen begins to be depleted in the bottom layer as decomposers consume oxygen. If enough material decomposes, almost all the oxygen can be consumed. In Shawano Lake only the deep areas remain stratified throughout the summer. Strong winds moving across the large lake surface mix the water in shallower areas, introducing oxygen throughout the water column.

During the fall, lake temperatures become uniform as the season cools the water from the top down (Figure 3). Density becomes greater at the surface and Shawano Lake experiences fall overturn. At the deep holes in Shawano Lake, fall overturn replenishes the water column with dissolved oxygen as water circulates back to the surface where oxygen can diffuse from the air.

In winter, stratification creates colder temperatures at the ice surface than at the lake bottom. During ice cover, temperatures remain relatively stable and in Shawano Lake the temperature difference from top to bottom is about 5°C. Should this stratification last too long while ice covers the lake, oxygen in the system may become significantly reduced and fish kills may result.

Temperature and dissolved oxygen measurements in Shawano Lake show the lake water remains homogenous (mixed) from top to bottom for a large portion of the year. This is not surprising as it is a large, relatively shallow lake and wind can easily initiate mixing of the water. Shawano Lake experiences stratification during both the winter and in the summer. Stratification at deeper depths in the East basin occurs for periods of time in mid to late summer. Winter stratification also occurs under the ice in winter. Stratification can result in dissolved oxygen concentrations in the bottom layer to fall below 5 mg/L, which is considered the minimum to support most biota. However, for a majority of the season stratification is absent or confined to a deeper depths (Figure 4, Figure 5, Figure 6, Figure 7).


Figure 4. Temperature profiles measured at the West site in Shawano Lake.

Figure 5. Dissolved oxygen profiles measured at the West site in Shawano Lake.

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Figure 6. Temperature profiles measured at the East site in Shawano Lake.

Figure 7. Dissolved oxygen profiles measured at the East site in Shawano Lake.

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3.2.2 Phosphorus

In Shawano Lake, phosphorus is the most significant limiting nutrient which is similar to most Wisconsin lakes where phosphorus is the primary element that leads to the development of nuisance algae (Wetzel 2002; Cogger 1988). Phosphorus is present naturally throughout the watershed in soil, plants, and animals. It is transferred to the lake with the erosion of soil, runoff of animal waste and fertilizers, effluent from septic systems, nutrients and sediments released from wetlands and shoreland plants, groundwater, and atmospheric deposition.

The most common mechanism for the transport of phosphorus from the land to the water is via surface runoff. Phosphorus adheres to soil/sediment particles. If those particles (soil, organic material, etc.) are disturbed or if water containing phosphorus from decaying vegetation and fertilizer is conveyed directly to the lake, phosphorus is transferred from land to water. Phosphorus can also travel to Shawano Lake in a dissolved form. Once in Shawano Lake, a portion of the phosphorus becomes part of the aquatic system in the form of plant and animal tissue, sediments, and in solution in the water. The phosphorus continues to cycle within the system, and is very difficult to remove once it enters. Phosphorus can form insoluble precipitate with calcium (marl), iron, and aluminum under appropriate conditions helping to reduce phosphorus concentrations and overall algal growth (Shaw et al. 2000). It can react very differently under aerobic (oxygenated) versus anaerobic (no oxygen) conditions, as well as under changes to temperatures and pH. These reactions can either contribute to further phosphorus enrichment or make it unavailable for use by algae and plants.

Zebra mussels (Dreissena polymorpha) have been documented as removing particulate nutrients through filtration but, may in fact, be recycling and excreting soluble phosphorus back into the water (James et al. 2000; Arnott and Vanni 1996). If this is the case in Shawano Lake, zebra mussels may increase the forms of phosphorus to that which is readily available for aquatic plant and algal use.

Phosphorus can also travel to the lake in groundwater; however, in Shawano County it is not naturally abundant in groundwater. In situations where there is a continuous phosphorus source (e.g. earthen barnyards, routine spreading of manure on a field, septic drain field) it may migrate slowly from the land surface to the groundwater. Once the soil’s capacity to hold phosphorus is exceeded phosphorus movement to groundwater can readily occur. Phosphorus also moves to Shawano Lake in groundwater that flows through the wetland sediments that were submerged when the lake level was increased.

In this study, two forms of phosphorus were measured: soluble reactive phosphorus (SRP) and total phosphorus (TP). SRP is dissolved phosphorus that is readily available for use by aquatic plants and algae. It is usually present in low concentrations and where present uptake up by aquatic plants and algae occurs very rapidly (Wetzel 2002). TP is a measure of the dissolved phosphorus plus organic and inorganic particulate phosphorus in the water. Examples of organic phosphorus would be plant or animal matter or phosphorus that is bound to soil particles. TP is commonly used as a measure of lake phosphorus because its concentrations are more stable than SRP. Phosphorus availability can vary within a lake seasonally, annually, and spatially. For example, when the lake is stratified, oxygen concentrations and pH can cause reducing conditions in the bottom layer (hypolimnion) of a lake, reducing conditions result in the release of soluble phosphorus from sediments; this is referred to as internal loading.

Figure 8 shows average TP concentrations at the West, East, Deep Hole, and all sites by month for samples collected from 2004 to 2007. TP concentrations were fairly low in May and June, however in late June, senescence (maturation and die off) of the invasive aquatic plant, curly leaf pondweed (Potomageton crispus) lead to a pulse of phosphorus in the water as it is released from dead and decaying plant material. The unfortunate timing of this pulse occurs when the water is warm and can readily support the propagation of algae. Sediment release of phosphorus also becomes more significant during the summer. This increase constitutes a large amount of phosphorus that was previously unavailable to algae which now becomes available. Additional increases in TP concentrations in the shallow water (epilimnion) were


observed following the senescence of curly leaf pondweed and continued until fall overturn, in which internal phosphorus loading from littoral sediment was the likely cause of further phosphorus enrichment.

For all sites sampled, the TP that has been measured in Shawano Lake since 2004 shows an increasing trend in concentration. It frequently crosses the threshold from mesotrophic conditions to eutrophic conditions. Routine algal blooms and abundant aquatic plant growth are typical in eutrophic lakes (Figure 9). TP concentrations above 30 µg L‐1 are enough to stimulate algae blooms and excessive aquatic plant growth. In Shawano Lake, concentrations greater than 30 µg L‐1 were observed in late summer for all four years. The epilimnion in the East site had a mean TP concentration of 25 µg L‐1 with a range of 7 to 41 µg L‐1. At the West site, the mean TP concentration was 26 µg L‐1 with a range of 7 µg L‐1 to 49 µg L‐1. The concentrations of phosphorus in the July and August samples averaged 28 µg L‐1 for all years. During most sampling periods concentrations were slightly less in the East site than the West site. The highest observed epilimnion concentration (49 µg L‐1) in the lake was measured at the East site in August 2007.

Average TP concentrations in Shawano Lake during spring overturn for 2004 was 35 µg L‐1, which is high enough to support nuisance levels of algae and aquatic plants. In 2005, 2006, and 2007 spring overturn TP concentrations were 24, 21, and 22 µg L‐1, respectively.

When the lake was stratified in 2006 and 2007, the hypolimnion of the lake had higher concentrations than the epilimnion. This is normal; the higher phosphorus concentrations at the lake bottom are the result of phosphorus release from particles settling out of the water column and the re‐release of phosphorus from the sediments under an anoxic environment. The highest concentrations of TP (48‐223 µg L‐1) in 2006 were found in the hypolimnion during late summer when a strong, anoxic hypolimnion had formed during late June to late August, 2006 (Table 4 and Figure 10). Stratification in 2007 also occurred; one late season sample was collected in mid‐August with a TP concentration greater than 300 µg L‐1. These high concentrations are linked to the strong stratification that occurred in the summers of 2006 and 2007 which was previously an undocumented phenomenon in Shawano Lake. It is not clear what led to the apparently strong thermal stratification in Shawano Lake in 2006 and 2007, but it may be linked to better than average early season water clarity (~ 10 ft) and warmer air temperatures that led to deeper light penetration and increased water temperatures thereby inducing deeper and stronger stratification. This stratification resulted in approximately 7% of the lake volume to have high concentrations of phosphorus. During the summer this enriched layer was somewhat contained and likely had minimal effect on epilimnion concentrations because phosphorus was not easily transferred across stratified layers until full mixing occurred in late August.

0

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3 4 5 6 7 8 9 10 11Month

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rage

Tot

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(µg

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)

WestEastDeep Holeall sites

Figure 8. Mean epilimnion TP concentrations (µg L‐1) by month in Shawano Lake. (UWSP and Self‐help data 2004‐2007),


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Jan-04 Jul-04 Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07 Jan-08

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)

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East Site

Deep Hole

Oligiotrophic(0-10 µg L-1)

Eutrophic(30+ µg L-1)

Mesotrophic(10-30 µg L-1)

Figure 9. TP concentrations (µg L‐1) depicting seasonal and annual variability in Shawano Lake. (UWSP and Self‐help data 2004‐2007)

Date Epilimnion Hypolimnion Mixing Status 5/28/06 22 Mixed 6/09/06 14 13 Weakly stratified6/29/06 23 48 Stratified 7/2/06 85 Stratified 7/13/06 25 190 Stratified 8/10/06 29 185 Stratified 8/18/06 223 Stratified 8/25/06 41 Mixed 8/13/2007 49 358 Stratified

Table 4. Hypolimnion and epilimnion TP concentrations (µg L‐1) in samples collected in summer from the East site during different mixing scenarios.

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Apr-06 May-06 Jun-06 Jul-06 Aug-06 Sep-06

Tota

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East Site HypolimnionEast Site Epilimnion

Figure 10. 2006 hypolimnion and epilimnion TP concentrations (µg L‐1) at the East site of Shawano Lake. Hypolimnetic TP concentrations significantly increase from June to August with the onset of stratification.


Aquatic plant respiration in the dense aquatic plant beds can change water chemistry by removing oxygen and respiring carbon dioxide at night thereby reducing oxygen and decreasing the pH. These changes can mobilize phosphorus from sediment if the appropriate conditions exist. To evaluate these effects in Shawano Lake temperature, dissolved oxygen, pH, and conductivity profiles were measured at multiple locations around the lake in the early morning (~ 4 am to 7 am) and water samples were collected for TP analysis. The profiles showed changes from top to bottom with a decrease in oxygen and increase in pH but were not enough change to induce phosphorus release from the sediment. However, TP concentrations were elevated in comparison to the open water sites and a substantial increase occurred in the aquatic plant beds following the senescence of curly leaf pondweed (Figure 11).

Lillie and Mason (1983) developed a water quality index based on TP concentrations in Wisconsin lakes; Shawano Lake has the same water quality as the average natural lake in Wisconsin.

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Apr-06 May-06 Jun-06 Jul-06 Aug-06 Sep-06

Tota

l P ((

µg/L

)

Figure 11. TP concentrations (µg L‐1) samples collected during early morning sampling near dense aquatic plant beds. An increase in late June follows the senescence of curly leaf pondweed.

3.2.3 Soluble Reactive Phosphorus

Soluble reactive phosphorus (SRP) is readily available for use by algae and aquatic plants. Shaw, et al. (2000) suggests that the SRP concentrations following spring overturn should be 10 µg L‐1 or less to prevent summer algae blooms. The East site of Shawano Lake had spring overturn SRP concentrations in 2004, 2005, 2006, and 2007 of 3, 7, 6, and 9 µg L‐1 respectively, and the West site had spring overturn SRP concentrations of 6, 12, 6, and 17 µg L‐1 respectively (Appendix A2). Throughout the growing season, SRP concentrations in samples collected in from the East site remained relatively low, averaging 3, 5.5, and 6.6 µg L‐1 (ranging between 3 and 17 µg L‐1) for 2004, 2005, and 2006 respectively. The average SRP concentration in the West site samples were higher at 5.3, 8.8, and 8.4 µg L‐1 (range 3 to 31 µg L‐1) in 2004, 2005, and 2006 respectively.

3.2.4 Total Nitrogen to Total Phosphorus Ratio

The amount of aquatic plants and algae that can grow in a lake depends on the amount of nutrients that are available. The major nutrients of concern for surface waters in Wisconsin are phosphorus and nitrogen. In a given body of water, a plant community’s requirement for phosphorus is usually different than for nitrogen. The total nitrogen (TN) to total phosphorus (TP) ratio indicates whether nitrogen or phosphorus is the limiting nutrient for plant growth. When the TN:TP ratio is greater than approximately 15:1, plant growth is generally restricted by the amount of phosphorus available. The average TN:TP ratio


in Shawano Lake from April 2004 to October 2006 was 33:1, which indicates that phosphorus is the more limiting nutrient meaning that efforts to control phosphorus inputs to the lake will have the most direct impact on algae/aquatic plant growth.

3.2.5 Nitrogen

Nitrogen is an important biological element. It is second only to phosphorus as a key nutrient that influences aquatic plant and algal growth in lakes. Nitrogen is a major component of soil, all plant and animal tissue, and therefore organic matter. It is also found in precipitation and can be the primary nitrogen source in some seepage and drainage lakes. Nitrogen travels in groundwater and surface runoff therefore it can enter a lake in both soluble and particulate forms. Sources of nitrogen are often directly related to land uses including agricultural, lawn, and garden fertilizers, animal waste, nutrients in septic system effluents, sewage treatment plants.

Nitrogen enters and exits lakes in a variety of forms. The most common include ammonium (NH4+),

nitrate (NO3‐), nitrite (NO2

‐), and organic nitrogen. These forms summed yield total nitrogen. Aquatic plants and algae can use all inorganic forms of nitrogen (NH4

+, NO3‐, and NO2

‐); if these inorganic forms of nitrogen exceed 0.3 mg L‐1 in spring, there is sufficient nitrogen to support summer algae blooms (Shaw et al., 2000). Organic forms of nitrogen can also become available after biological conversion to ammonium.

In the samples collected from Shawano Lake nitrate and ammonium concentrations were low. The inorganic forms of nitrogen exceeded 0.3 mg L‐1 only once in 3 years of sampling and was not during turnover but in late August of 2006 with a concentration of 0.4 mg L‐1 (Figure 12). Throughout the course of the year, much of the nitrogen moving to the system was in the organic form (associated with particles).

0.0

0.1

0.2

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0.4


Inor

gani

c N

(mg

L-1)

West Site

East Site

Figure 12. Inorganic nitrogen concentrations (mg L‐1) representing measured concentrations on sampling dates.

3.2.6 Water Clarity and Chlorophyll a

Water clarity is a measure of light penetration which can be associated with algal growth, turbidity, and/or color. The Secchi disc is a tool used to measure water clarity by lowering this black and white (Secchi) disc into the water and measuring the depth where it is no longer visible. Secchi disc measurements give a value of water clarity at the time of reading. These measurements can vary from month to month or day to day. Variations can result from storm and wind events, sunny versus cloudy days, time of day and year, abundance of algae, and/or boat traffic.


Water clarity measurements have been taken in Shawano Lake since 1968 and are summarized in Figure 13. There is considerable variability in year‐to‐year averages; however, some of this variability may be due to inconsistency in the number and timing of measurements. The recent (2004‐2006) water clarity measurements ranged from a minimum of 6 feet in August 2004 and 20 feet in October 2005 which suggests fluctuations in the range of 14 feet (Figure 14). An average of 10 feet was calculated for the three years of this study.

Chlorophyll a, which is used as a measure of algae abundance, also varies seasonally and annually. During the summers of 2004, 2005, 2006, and 2007 concentrations ranged between 2 μg L‐1 in June 2006 and 45 μg L‐1 in August 2006 (Figure 15). Chlorophyll a concentrations greater than 30 μg L‐1 is considered a potentially nuisance level of algae. Seasonal increases of chlorophyll a correlate with late summer peaks of phosphorus (Figure 16) and nitrogen. When comparing chlorophyll a and Secchi disc measurements a decrease in water clarity (Secchi depth) is likely associated with algal abundance (Figure 17). Generally chlorophyll a concentrations remained low in spring and early summer than increased with the increase of available nutrients.

Figure 13. Average annual water clarity measurements in Shawano Lake 1968‐2007.


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25


Secc

hi d

epth

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Figure 14. Water clarity measurements in Shawano Lake (2004‐2007). These measurements represent depth at which the Secchi disc was no longer visible in the water (average for May‐Oct is 9 ft).

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chlo

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yll a

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West Site

East Site

Deep Hole

Oligiotrophic(<5 µg L-1)

Eutrophic(10+ µg L-1)

Mesotrophic(5-8 µg L-1)

Figure 15. Chlorophyll a concentrations (μg L‐1) in Shawano Lake. These values represent measured concentrations on sampling dates during study period. UWSP and Self‐help data 2004‐2007.


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0 10 20 30 40 50 60 70Total P (µg L-1)

chlo

roph

yll a

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West Site

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Deep Hole

Figure 16. Seasonal increases of chlorophyll a correlate with the late summer peaks of phosphorus in Shawano Lake. Red line indicates nuisance concentrations of algae related to chlorophyll a and high enough concentrations of phosphorus to induce nuisance algal concentrations.

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Chlorophyll a (µg L-1)

Secc

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epth

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Deep Hole

Figure 17. Increases of chlorophyll a correlate with a decrease in water clarity (secchi depth) measures in Shawano Lake.

3.2.7 pH, Hardness, and Alkalinity

Measured on a scale ranging between 1 and 14, pH references those values with lower pH to be acidic and higher pH values basic conditions. Lakes with low pH values often allow metals (aluminum, zinc, mercury), which can be located in the lake sediment, to become soluble. These metals can then make their way into the food chain and bio‐accumulate in larger organisms (Shaw et al. 2000). Conversely, lakes with a high pH can provide buffering against acidic conditions. Higher pH values are often found when limestone or dolomite (carbonate minerals) is present in the watershed geology. Groundwater dissolves these rocks and, once in the lake, neutralizes the acidity in rainfall. Such is the case in the Shawano Lake Watershed.


Dolomite bedrock to the south and east of Shawano Lake and glacial till with limestone and dolomite mineral composition is common in the watershed (Andrews and Thrienen 1968). The value of pH can change throughout the day, year, and with depth because of chemical interaction with photosynthesizing biota, which can lower the pH by releasing carbon dioxide during respiration or increase pH by using carbon dioxide during photosynthesis.

The pH in Shawano Lake is neutral to basic and the profiles with depth are quite similar. The pH levels are within the acceptable range for Wisconsin lakes. East and West site profiles were collected during the mid day; therefore, pH increases due to aquatic plant photosynthesis can be observed in the summer months. In 2006 pH followed similar patterns as the temperature and dissolved oxygen did when stratification occurred. The surface layer which was connected to the atmosphere ranged from 8.5 to 8.3 and the bottom layer ranged from a more acidic pH of 7.5 to 7.1. The change to a more acidic level is induced by respiration by microbial decomposition in which carbon dioxide is respired. Because of stratification, the water does not mix and oxygen can not reach the lower layer. On average in the summer, Shawano Lake ranged from 8.1 to 9.0 at both the East and West sites. Only when stratification occurred did pH fall below 8.0 in either the East or West site. When sampling aquatic vegetation beds pH did reach a max of 9.2 but was most often below 9.0 in all locations.

Alkalinity and hardness also impact the aquatic system by providing acid buffering which is affected by the type of soil and bedrock in the watershed. Alkalinity measures the resistance or buffering to changes in pH and lakes with higher alkalinity are less affected by acid precipitation. Hardness includes calcium, and many organisms use calcium in the development of bones, shells, and exoskeletons. A lake’s hardness and alkalinity are affected by the type of minerals in the soil and watershed bedrock, and by how much the lake water comes in contact with these minerals (Shaw et al. 2000). Lakes in watersheds that contain limestone minerals such as calcite and dolomite have water with higher hardness and alkalinity values (Shaw et al. 2000). Local geology, as previously mentioned in the Shawano Lake watershed contains limestone minerals. Due to its higher concentrations of calcium and magnesium Shawano Lake is considered a hard water lake and concentrations put it in the moderate range for alkalinity (Figure 18). Hard water lakes tend to be more productive overall and produce more fish and aquatic plants than soft water lakes (Shaw et al. 2000).

Figure 18. Alkalinity (mg/L) and total hardness (mg/L) in Shawano Lake samples.

Hardness ScalePresence of Soluble Minerals

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Very Hard> 180 mg/L

Hard 121-180 mg/L

Moderately Hard61-120 mg/L

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Shawano Average

Shawano 1970's Average

Alkalinity ScaleSensitivity to Acid Rain

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40-199 mg/LHigh

Sensitivity0-39 mg/L

Shawano Average Shawano 1970's Average 104


4 Results and Discussion: Tributaries and Watershed This portion of the document discusses the external sources of nutrients and pollutants to Shawano

Lake. The first section is a discussion on the influence that different kinds of land uses and practices have on water quality. This is followed by a Sub‐watershed Evaluation, which examines each sub‐watershed individually in detail with discussion on how the specific characteristics of each sub‐watershed affects water quality. The final section, Nutrient & Pollutant Evaluation, compares the annual nutrient and pollutant loads from the sub‐watersheds against each other, with interpretation about the differences based on the hydrologic and land use evaluation.

4.1 The Influence of Land Use A primary source of water and nutrients to Shawano Lake is its tributaries. Runoff, groundwater,

and precipitation are additional sources of water. Water coming from all of these sources can carry nutrients (nitrogen and phosphorus) and pollutants (sediment, chloride, and others) to the lake. Nutrient and pollutant loss from the land to the lake can be referred to as export. The amount of any nutrient exported to a water body over the course of a year is known as a nitrogen or phosphorus “load” and is reported in units of kilograms (kg) in this document. Different types of land uses and land use practices influence the nutrient load to the lake or tributaries.

Generally, nutrient and pollutant export is low from undeveloped and undisturbed lands. Forests and wetlands are the major types of undeveloped land in the Shawano Lake watershed. Several characteristics in forested landscapes contribute to the low nutrient and pollutant export rates. The canopy cover of a forest intercepts rainfall, which reduces runoff. The well‐structured soils (not compacted) in forest floors allow adequate infiltration of rain, and fewer nutrients are available to be transported by groundwater because of vegetation uptake.

Wetlands are a critical component in healthy watersheds. Wetlands act as pollutant filters for surface water and groundwater. Stream flow slows in wetlands, allowing sediment and other pollutants to settle out. This is especially important during storms when streams are most likely to be carrying high sediment loads. During some high flow periods, wetlands can be a source of dissolved nutrients.

Agriculture can contribute significant amounts of nutrients to groundwater and nutrient‐laden sediment to runoff, but the amount can vary considerably depending upon the specific type of agriculture, the management practices being used on a farm, and the distance to the water body. In general, some agriculture types or practices that contribute to higher nutrient export are annual rather than perennial crops, conventional rather than conservative tillage, surface‐spread manure on frozen soils or snow, or non‐roofed feed lots without runoff control rather than covered lots with controlled runoff. Under some conditions, nutrient and sediment export can be increased because of reduced infiltration rates and therefore, increased runoff.

Urban and residential areas can also deliver nutrients and pollutants. In the Shawano Lake watershed, chloride from road salt is a pollutant that originates in both urban and rural areas. Chloride readily dissolves in water, so it is easily transported to lakes and streams by runoff and groundwater. During the thaw and storms of early spring, chloride concentrations can be remarkably high in runoff and streams. Sources of chloride can include fertilizers, animal waste, septic systems, and road salt. Residential areas can contribute large nutrient loads, particularly when directly connected impervious surfaces lead to runoff from even small storms allowing nitrogen and phosphorus in soils, vegetation, and fertilizers to run off.

Exposed soil can be another large source of sediment and nutrients. During rainstorms and snow melt the nutrient‐rich soil can move with runoff to the rivers and the lake. Exposed soil can be found in any type of landuse, but is probably most prevalent in certain types of agriculture practices and expanding urban areas undergoing construction.

Reducing exposed soil and controlling runoff from farm fields, barnyards, yards, rooftops, streets, parking lots, and construction sites can all help to reduce the amount of nutrients entering Shawano Lake.


This can be accomplished by minimizing impervious surfaces, and infiltrating runoff with rain gardens or bioretention areas near impervious surfaces. Near the edge of lakes and streams (i.e. the riparian zones), “buffers” comprised of tall grasses, forbs, shrubs, and trees can help foster infiltration and filter runoff water before it enters the lake. A fully intact riparian zone is the final filtering process before runoff enters a stream. A compromised riparian zone is not only inefficient in removing nutrients and pollutants from the water, but also may be a sediment source due to increased erosion. To protect water quality and provide habitat, the state recommends 35 feet of vegetative buffer from the water’s edge inland. Eliminating/minimizing the use of fertilizers will also reduce nutrients that are potentially delivered to the lake.

4.2 General Trends, Landuse in the Watershed A land use assessment was performed in each sub‐watershed to help interpret nutrient loads in

associated tributaries. Figure 19 spatially displays landuse throughout the Shawano Lake sub‐watersheds; the same information is displayed graphically in Figure 20. A more detailed description at the sub‐watershed level is addressed in the following sections of the document. In general, the northern sub‐watersheds (1 and 2) are chiefly forested and/or wetlands. The remaining sub‐watersheds are largely agricultural (approximately half crops and half grass‐based). Sub‐watershed 5, the lowest reaches of sub‐watershed 3, and the shoreland region contain the only significant amount of developed land in the watershed. Such landuse distributions are reflected in the nutrient concentrations in the sub‐watersheds. Lower concentrations of phosphorus and nitrogen were observed in the forested sub‐watersheds 1 and 2, and higher concentrations were observed in the more agricultural and urban sub‐watersheds 3‐6. The urban influence of sub‐watersheds 5 and 3 is reflected as high chloride concentrations.

The following sections describe nutrient and pollutant export from each sub‐watershed individually, as well as the stream and watershed characteristics that influence export. Landuse was examined at the sub‐watershed scale. Land use was evaluated in greater detail in the 70‐ft stream corridor to determine the extent to which the riparian zone was functioning as a buffer against pollutants and nutrients. A 70‐ft corridor was chosen because it represents the 35‐ft shoreland buffer region specified in NR 115 (for navigable waters), extended to both sides of a stream.

Nutrient and pollutants were first examined broadly as annual loads and were then analyzed more closely to determine the relative contribution of seasonal storms and baseflow to nutrient load. TP load calculations from monitored tributaries were compared against TP loads produced by a model to check the accuracy of the model. Validating the model was important because the predicted loads for monitored sub‐watersheds were scaled to nearby unmonitored sub‐watersheds with similar characteristics, allowing us to estimate annual loads from the unmonitored regions.


Figure 19. Landuse in the Shawano Lake watershed and sub‐watersheds.

Figure 20. Landuse area by sub‐watershed in the Shawano Lake watershed.

0

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4.3 Sub‐watershed Evaluation 4.3.1 Sub‐watershed 1

Loon Creek drains sub‐watershed 1. It is the most undeveloped sub‐watershed in the Shawano Lake watershed. Over 80% of sub‐watershed 1 is forested and wetland area (Table 5). In fact, 23% of the forested regions of the Shawano Lake watershed are found in sub‐watershed 1. The landuse trends in the sub‐watershed are mirrored along the stream corridor. Table 5 indicates that the stream riparian zone is intact and functioning as a natural buffer. The high percent of “open water” in the corridor indicates that the stream passes through lakes. The high percentage of undeveloped land in the sub‐watershed and the riparian contribute to low nutrient and pollutant loads in Loon Creek. Development in the sub‐watershed is found along lake perimeters, especially Loon Lake.

Area (ha) % Area (ha) %Crops 69.3 1.4 0.2 0.1Pasture/Hay 11.9 0.2 0.0Developed 328.5 6.5 3.9 2.9Open Water 417.8 8.3 42.8 31.6Forest/Undeveloped 2987.9 59.6 32.6 24.1Wetland 1201.1 23.9 55.9 41.3

LanduseSub-watershed Stream corridor

Table 5. Landuse breakdown in sub‐watershed 1 and stream corridor

4.3.2 Sub‐watershed 2

The main branch of Duchess Creek drains sub‐watershed 2. Table 6 shows that the majority of sub‐watershed 2 is forested or undeveloped land and, similar to sub‐watershed 1, represents a significant portion (20%) of the total forested/undeveloped land in the entire Shawano Lake watershed. Moreover, 87% of the land in the riparian zones is either forested or wetlands, suggesting that the stream corridors are largely intact and functioning as buffers. It is important to point out the area of sub‐watershed and stream corridor that is used as cropland; although the percent of land devoted to crops is not particularly high, it is still capable of exporting nutrients and sediment to Duchess Creek, especially in the corridor.

Area (ha) % Area (ha) %Crops 299.2 14.2 5.4 10.1Pasture/Hay 46.6 2.2 0.0Developed 116.3 5.5 1.5 2.9Open Water 21.8 1.0 0.0Forest/Undeveloped 1309.5 62.2 24.9 46.6Wetland 312.8 14.9 21.6 40.4



4.3.3 Sub‐watershed Tributary of 2

Sub‐watershed Tributary of 2 is drained by the eastern tributary of Duchess Creek. No single landuse comprises the majority of the sub‐watershed (Table 7). This sub‐watershed represents the transition from mainly undeveloped lands to mainly agriculture observed between the northern and southern halves of the Shawano Lake watershed. The area of the corridor devoted to crops and development raises some concern; it must be pointed out that this tributary typically has an intact riparian zone, but the zone was very thin (<35 ft from water’s edge) where the stream flowed through agricultural


lands. The developed areas of the sub‐watershed and the corridor represent a golf course, which could be a potential source of nutrients from turf fertilizers. The tributary did not typically flow during the summer months, barring brief periods of discharge during and after storms. It was not regularly monitored, although several storm samples were collected.

Area (ha) % Area (ha) %Crops 103.5 24.1 2.3 10.3Pasture/Hay 52.0 12.1 0.1 0.4Developed 52.3 12.2 2.4 10.7Open Water 12.2 2.8 2.2 9.5Forest/Undeveloped 92.6 21.5 4.9 21.4Wetland 117.6 27.3 10.8 47.6


Table 7. Landuse breakdown in sub‐watershed Tributary of 2 and stream corridor


Pickerel Creek drains sub‐watershed 3, which is the largest of the sub‐watersheds. Sub‐watershed 3 is mainly agricultural; crops are the dominant landuse (Table 8). In fact, sub‐watershed 3 contains 45% of the watershed’s cropland and 47% of the pasture/hay lands. When a watershed consists of such a high percentage of agricultural lands, it is important that tributaries have intact and functional riparian zones. Adequate buffers appear to be lacking in sub‐watershed 3. Crops and pasture/hay combined from nearly half (47%) of the stream corridors. These figures are increasingly problematic when we consider that Pickerel Creek is the most dendritic (i.e. has many branches) stream in the watershed. The more dendritic a stream is, the greater chance it has of encountering nutrient and pollutant sources simply because there are more stream branches flowing through more land.

Area (ha) % Area (ha) %Crops 1524.4 43.6 71.3 34.0Pasture/Hay 891.5 25.5 26.6 12.7Developed 184.4 5.3 4.0 1.9Open Water 103.8 3.0 15.1 7.2Forest/Undeveloped 400.5 11.5 24.5 11.7Wetland 388.5 11.1 68.1 32.5

Sub-watershed Stream corridorLanduse



Sub‐watershed 4 is drained by the main branch of an unnamed tributary dubbed “Noname Creek”. The landuse distribution is similar to that of sub‐watershed 3, although with significantly fewer wetlands or open water (Table 9). There is a notable increase in the amount of agricultural area in the stream corridor of Noname Creek. The fact that the stream corridor has a greater percent of forest/undeveloped land than the sub‐watershed as a whole indicates that buffers were deliberately left in the corridor. However, cattle in the upper reaches of the sub‐watershed were observed along the banks and in the channel of the stream on a number of occasions between 2005 and 2007. Any amount of down‐stream buffers will not significantly decrease the nutrient and sediment load caused by cattle upstream. Landuse practices in sub‐watershed 4 indicate that it may be a potentially large source of nutrients and sediment to Shawano Lake. Most of the development along Noname Creek is located in the Swan Acres neighborhood, which is downstream of the sampling point and the mouth of Noname’s tributary. The influence of Swan Acres on


water quality is addressed in the synoptic sampling section of this document.

Area (ha) % Area (ha) %Crops 247.7 37.7 19.71 43.4Pasture/Hay 260.5 39.7 8.73 19.2Developed 38.3 5.8 2.43 5.3Open Water 0.0 0.0Forest/Undeveloped 98.5 15.0 12.51 27.5Wetland 11.4 1.7 2.07 4.6

Stream corridorLanduse

Sub-watershed


4.3.6 Sub‐watershed Tributary of 4

The western tributary of Noname Creek drains sub‐watershed Tributary of 4. The landuse patterns in this sub‐watershed mirror those in sub‐watershed 4 (Table 10). A notable increase in forest and wetland, as well as a decrease in agriculture, is observed in the stream corridor. The tributary was not regularly monitored, although several storm samples were collected.



Table 10. Landuse breakdown in sub‐watershed Trib of 4 and stream corridor 4.3.7 Sub‐watershed 5

Murray Creek drains sub‐watershed 5. This sub‐watershed has the highest percent of developed land (Table 11) in the watershed. It is unique because it encompasses a portion of the City of Shawano that is drained by storm sewers (approximately half of the City of Shawano is drained by storm sewers that discharge into the Wolf River rather than the Shawano Lake watershed). Although other sub‐watersheds have developed areas, these areas are nearly all residential and do not have a high amount of impervious cover. Sub‐watershed 5 is the only sub‐watershed that drains industrial and commercial areas, and therefore has significant amounts of impervious cover. Creditably, the stream corridor of Murray Creek is comprised of over 70% forest/undeveloped land and wetlands. This arrangement is critical for good water quality in urban watersheds.

Area (ha) % Area (ha) %Crops 222.2 23.8 2.4 11.9Pasture/Hay 77.2 8.3 0.0Developed 194.9 20.9 2.3 11.0Open Water 1.8 0.2 0.8 4.0Forest/Undeveloped 254.5 27.3 6.4 31.3Wetland 182.0 19.5 8.6 41.9




4.3.8 Sub‐watershed East of 5

Sub‐watershed East of 5 is drained by an unnamed stream approximately 2 miles east of Murray Creek. The majority of the sub‐watershed is agricultural. The landuse in the stream corridor is almost identical to the landuse in the sub‐watershed; this pattern is indicative of no streamside buffers or very thin buffers.



Table 12. Landuse breakdown in sub‐watershed East of 5 and stream corridor


Sub‐watershed 6 is drained by an unnamed stream that was dubbed “Resort Creek” in reference to the road used to access the monitoring point. This sub‐watershed is roughly split between crops, pasture/hay, and undeveloped/forest (Table 13). Over half of the stream corridor is forested or wetlands, suggesting that the buffers are intact.




4.4 Nutrient & Pollutant Evaluation A general summary of nutrient and pollutant loading is as follows:

• Pickerel creek contributes the highest chloride load • Pickerel and Duchess contribute the highest TSS loads • Noname Creek has the highest TN concentrations, but Pickerel creek has the highest TN

load. Similar loads are observed at Loon, Duchess, and Noname Creeks. Murray Creek has very low TN loads.

• Noname and Resort Creeks have the highest TP concentrations; Pickerel Creek has the highest TP loads. Similar loads are observed at Loon, Duchess, and Noname Creeks. Murray Creek has very low TP loads.

The following sections provide a detailed discussion on nutrient and pollutant loading in the Shawano Lake Watershed.

4.4.1 Chloride

Natural chloride concentrations are low in the Shawano Lake watershed. Chloride concentrations tend to reflect the amount of development in a watershed; it follows that the tributaries draining


watersheds with more urban landuse and impervious cover have higher chloride concentrations and loads. The highest chloride loads are exported from Pickerel and Murray Creeks, with median values of 58,810 and 19,478 kg/yr, respectively (Figure 21). Chloride from Pickerel Creek could be linked directly to residential street/swale storm runoff; samples collected from a stormwater outflow pipe had elevated concentrations (average of 282.3 mg/L) well above any in‐stream concentrations (average of 16.8 mg/L). Loon, Duchess, and Noname Creeks stand out as sites with low loads and low variability. The median chloride loads for these streams are 10,881, 9835, and 9204 kg/yr.

0

10000

20000

50000

60000

70000

80000

Chl

orid

e (k

g)

Loon Duchess Pickerel Noname Murray

Stream Figure 21. Annual chloride load in monitored tributaries, 2005‐2007 (black dots are outliers)

By examining chloride loads per unit area of sub‐watershed, we can determine which sub‐watersheds are contributing disproportionately high chloride loads. Figure 22 reveals that Noname Creek has a high chloride export rate, and may be more of a problem area than the load alone indicates in Figure 21. Pickerel and Murray Creeks have high export rates, while Loon and Duchess Creeks are low.

0

6

12

18

24


Cl (k

g/ha

/yr)

Figure 22. Median chloride export rates in monitored tributaries of Shawano Lake watershed, 2005‐2007.

The majority of the chloride exported to Shawano Lake occurred during spring events or as

baseflow (Figure 23). In the early spring, events are frequently the result of snowmelt. When melting snow enters a stream, it transports a winter’s‐worth of road salt and some fluids from land spread manure. Chloride in baseflow is usually carried to the stream in the groundwater that feeds it. The groundwater sources can be a distance from the stream and may take years between its original infiltration to the groundwater and the time it discharges into the stream or lake.


0

20000

40000

60000


CL (k

g)

summerspringfallbaseflow

Figure 23. Seasonal/flow components of median chloride loads in monitored tributaries of Shawano Lake, 2005‐2007.

4.4.2 Total Suspended Solids

The total suspended solids (TSS) load is an estimate of floating particles in the stream water. It is an important pollutant because phosphorus adheres to suspended soil and sediment, which are then conveyed to Shawano Lake. Once the suspended sediment settles, it may blanket rocky substrate that would otherwise provide important spawning habitat for fish. Sources are usually exposed soil in the landscape or stream bank erosion. The highest TSS loads were observed at Duchess and Pickerel Creeks (Figure 24). Pickerel Creek has large amounts of croplands within the sub‐watershed and the stream corridor, which contributes soils and sediments during periods of little or no vegetative cover and land spreading of manure. Pastured land also comprises a significant portion of the sub‐watershed and about 13% of the corridor. Depending upon how this land is managed it can be a minimal source of TSS or can contribute significantly, especially when grazing animals have access to the stream and its corridor. Sources to Duchess Creek were not as evident and may require more detailed exploration of land use practices within the sub‐watershed.

0

10000

20000

30000390000

400000

410000

Tota

l Sus

pend

ed S

olid

s (k

g)


Stream Figure 24. Annual total suspended solids load in monitored tributaries of Shawano Lake, 2005‐2007 (black dots are outliers)

An examination of TSS export rates reveals that Duchess, Noname, and Murray Creeks contribute

disproportionately higher TSS loads than Loon or Pickerel Creeks (Figure 25). Interpreting the very high export rates observed in Duchess Creek remains difficult and may be of site‐specific origin. The high rates


of loading in Noname Creek may very likely attributed to the agriculture in the sub‐watershed (nearly 80% of the land) and cropland and pastures that are comprise the majority of the stream corridor. Murray Creek’s high TSS export rates are probably due to a combination of croplands and developed lands, which comprise nearly half of the sub‐watershed and about one‐quarter of the corridor. Despite the high TSS loads observed in Pickerel Creek, the export rates are low because the sub‐watershed is so large and deposition can occur in lakes and wetlands within the sub‐watershed.

0

24

68

10


TSS

(kg/

ha/y

r)

Figure 25. Median total suspended solids export rates in monitored tributaries, 2005‐2007

Spring and summer events contribute the majority of the TSS. Theoretically, baseflow should not

contribute any TSS since this is not a soluble parameter. Observations of TSS in baseflow suggest a disturbance of the stream bed and streambank erosion; cattle access is a plausible explanation for the high baseflow TSS loads. Pickerel and Noname Creeks have the most area of pasture in their corridors, and cattle have frequently been observed in these streams. TSS loads in Loon Creek may be re‐suspended sediment from boating activity in Loon Lake, immediately upstream of the monitoring site.

0

5000

10000

15000

20000


TSS

(kg)


Figure 26. Seasonal/flow components of median TSS loads in monitored tributaries in Shawano Lake watershed, 2005‐2007

4.4.3 Total Nitrogen

As with lakes, nitrogen is transported to streams via runoff and groundwater, and moves through the watershed with particulates and in solution. The range of total, inorganic (nitrogen in solution), and organic (particulate nitrogen) nitrogen loads from the combined baseflow and event flow were explored for all tributaries.

The Environmental Protection Agency (EPA) references total nitrogen conditions in Wisconsin rivers and streams for this region of the state (Ecoregion VII, region 51). These conditions constitute the highest and lowest observations from stream stations in the region. Reference conditions for total nitrogen concentrations are 0.46 to 1.88 mg/L. The majority of observations from Shawano Lake’s monitored tributaries were within the bounds of the EPA reference concentrations, which are represented by the yellow box in Figure 27. Only total nitrogen concentrations at Noname Creek were consistently greater than the upper bound identified by the EPA.


0

6

12

18

Tota

l Nitr

ogen

(ppm

)

Loon Duchess Pickerel Noname Murray ResortStream

0

6

12

18

Tota

l Nitr

ogen

(ppm

)


Figure 27. Measured TN concentrations in monitored tributaries and comparison to EPA reference concentrations (yellow box, black dots are outliers)

Pickerel Creek contributes the largest TN loads to Shawano Lake, while Noname Creek delivers a TN load that is similar to Duchess and Loon Creeks (Figure 28). This may seem unexpected, given the TN concentrations of Pickerel and Noname Creeks in Figure 27; the TN loads demonstrate the influence of stream discharge. Noname Creek has a consistently lower discharge than Pickerel Creek.

0

1500

3000

4500

6000

7500

Tota

l Nitr

ogen

(kg)


Stream Figure 28. Annual total nitrogen load in monitored tributaries of Shawano Lake, 2005‐2007 (black dots are outliers)

An examination of TN export rates reveals that Noname Creek exports a disproportionately higher

load than any other monitored stream in the watershed. A plausible source for high export rates from this sub‐watershed is the croplands, both within the watershed and in the stream corridor. Between 60‐70% of croplands in the watershed receive liquid or solid dairy manure, and remaining croplands receive commercial nitrogen fertilizer (Ostrowski, personal communication 2008).


0.01.02.03.04.05.0


TN (k

g/ha

/yr)

Figure 29. Median total nitrogen export rates in monitored tributaries in Shawano Lake watershed, 2005‐2007

Baseflow and spring events are responsible for the majority of the total nitrogen loads in all

streams except Loon Creek (summer events, rather than spring events, are important). Figure 30 shows the seasonal and flow components of TN loads, but it is more meaningful to divide nitrogen into its organic and inorganic components before discussing seasonal and flow relationships. In general, inorganic nitrogen is dissolved, and so it is the only form of nitrogen that groundwater can deliver to a stream. Organic nitrogen is suspended, so sources may be carried to a stream in storm runoff, or from biologic detritus present in the stream.

0

10002000

30004000

5000


TN (k

g)


Figure 30. Seasonal/flow components of median TN loads in monitored tributaries in Shawano Lake watershed, 2005‐2007

4.4.4 Inorganic Nitrogen

The EPA references become more meaningful when NO2++NO3

‐ ‐N (nitrate) concentrations are compared. Again, this is an inorganic form of nitrogen and is immediately available for use by aquatic plants and algae. Figure 31 displays the EPA reference boundaries for nitrate that is measured in streams in this region of the state as a yellow box (.003 mg/L‐7.33 mg/L). Nitrate from the monitored tributaries generally fall well below the upper EPA bound. Based on these figures, it appears that Shawano nitrate concentrations do not generally deviate from what is expected for the region, nor does it deviate significantly from what would be considered natural concentrations (< 2 mg/L). Again, Noname Creek is an exception. It is important to note that the upper EPA bound represents the single highest observation, and is very high for nitrate in this region of Wisconsin and may impact aquatic biota in this tributary.


0

5

10

15

NO

2+N

O3 (p

pm)


0

5

10

15

NO

2+N

O3 (p

pm)


Figure 31. Comparison of monitored tributary NO2++NO3

‐ concentrations to EPA reference concentrations (yellow box, black dots are outliers)

The concentration of all inorganic nitrogen forms (NH4 and NO2

++NO3‐ ‐N) is reflected in the annual

loads (Figure 32). Noname Creek has the greatest annual loads; Loon, Duchess, and Pickerel Creeks have a similar range of loads; and Murray Creek has the lowest loads. The high loads and concentrations in Noname Creek increasingly point to sub‐watershed 4 as heavily impacted by agriculture as well as residential lawn fertilizer.

0

1500

3000

4500

Inor

gani

c N

itrog

en (k

g)

Loon Duchess Pickerel Noname MurrayStream

Figure 32. Annual inorganic N loads in monitored tributaries of Shawano Lake, 2005‐2007 The only stream that stands out as having disproportionately high inorganic nitrogen export rates is

Noname Creek (3.5 kg/ha/yr, Figure 33). The export rates of the remaining streams are all less than 0.3 kg/ha/yr.


0.0

1.0

2.0

3.0

4.0


IN (k

g/ha

/yr)

Figure 33. Median inorganic N export rates in monitored tributaries, 2005‐2007

Baseflow and spring events are the two main contributors to inorganic nitrogen load. The very high

contribution of baseflow in Noname Creek indicates high rates of nitrogen fertilizer leaching through the soil and into the groundwater.

0

500

10001500

2000

2500


IN (k

g)


Figure 34. Seasonal/flow components of median inorganic N load in monitored tributaries of Shawano Lake, 2005‐2007

4.4.5 Organic Nitrogen

The majority of the total nitrogen load is in the form of organic N for Loon, Duchess, and Pickerel Creeks (Figure 35). Organic nitrogen is the particulate component of total nitrogen; sources may include in‐stream detritus, soil or manure in runoff, and suspended particles and is closely associated with TSS. The high loads from Pickerel Creek suggest agriculture influence, considering the amount of agriculture in the sub‐watershed. The seasonal and flow distribution of load, discussed below, is more informative regarding the source of organic nitrogen in Pickerel Creek. Before it can be used for growth by aquatic plants and algae, organic nitrogen must undergo biologic conversion to ammonium. Inorganic nitrogen is of greater immediate concern because it is in a form which is readily available for use by aquatic plants and algae. As demonstrated in the previous section, the highest load of organic nitrogen is exported from Murray Creek. Organic nitrogen export rates are similar between all streams (Figure 36).


0

1300

2600

3900

5200

6500

Org

anic

Nitr

ogen

(kg)


Stream Figure 35. Annual organic nitrogen load in monitored tributaries of Shawano Lake, 2005‐2007 (black dots are outliers)

0.0

0.5

1.0

1.5

2.0


ON

(kg/

ha/y

r)

Figure 36. Median organic nitrogen export rates in monitored tributaries of Shawano Lake, 2005‐2007

The high spring organic nitrogen in Pickerel Creek suggests land‐spread manure runoff. Previously,

spring events were also demonstrated as an important source of TSS in Pickerel Creek, which further supports manure runoff.

0

1000

20003000

4000

5000


ON

(kg)


Figure 37. Seasonal/flow components of organic N load in monitored tributaries of Shawano Lake, 2005‐2007

4.4.6 Phosphorus

Total phosphorus export is a function of baseflow (which contributes soluble reactive phosphorus, SRP), as well as runoff, so it is expected that both flow components are critical in phosphorus delivery. EPA reference conditions for TP in this region of the state are 20.6 to 80.0 µg/L. All monitored tributaries within


the Shawano watershed yielded concentrations that were beyond the upper bound of 80 µg/L (Figure 38). The highest concentrations were consistently observed in Noname Creek. Resort Creek also has high concentrations, but only four water samples were collected from this tributary. High TP concentrations are expected in sub‐watersheds with significant area devoted to agriculture, such as sub‐watersheds 4 (Noname Creek) and 6 (Resort Creek). Natural concentrations during baseflow in this region of the state should be less than 20 µg/L. From the standpoint of delivery to Shawano Lake, the crux of the matter lies in phosphorus loads rather than phosphorus concentrations.

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Tota

l Pho

spho

rus

(ppb

)


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500

600

700

800

900

1000

Tota

l Pho

spho

rus

(ppb

)


Figure 38. Comparison of tributary TP concentrations to EPA reference concentrations (yellow box, black dots are outliers)

The range of total phosphorus loads from the monitored streams was explored. Pickerel Creek

contributed the greatest total phosphorus load to Shawano Lake; 75% of observations from this stream were higher than 75% (or more) of the observations from any other stream (Figure 39). Such loads are not surprising, given that nearly 70% of the sub‐watershed is devoted to agricultural landuse. 1524 ha of sub‐watershed 3 is croplands; over 1000 ha of the cropland receives solid or liquid dairy manure, according to estimates from the county conservationist, Ron Ostrowski. Although manure applications will probably influence groundwater/baseflow chemistry to some extent regardless of environmental precautions, the contribution to TP load dramatically increases when manure is spread on frozen soils or snow, if it is spread too close to a stream without adequate buffers, if it is not incorporated into the soil, and if it exceeds the soil’s capacity to retain the phosphorus. A significant portion of stream corridor in sub‐watershed 3 is cropland, which further increases the potential runoff to transfer phosphorus to the stream. Use of winter cover crops or crop residue left on fields can help retain P enriched soil particles on the field during winter and spring runoff events. Loon, Duchess, and Noname Creeks contributed similar loads (all between 50 and 150 kg or 110 and 330 lb), and Murray Creek contributed relatively little total phosphorus to the lake. As we would expect, SRP annual loads mirror TP loads (Figure 40).


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350

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450

500

550

600

650

Tota

l Pho

spho

rus

(kg)


Stream Figure 39. Annual TP load, averaged over 3 years in monitored tributaries of Shawano Lake, 2005‐2007 (black dots are outliers)

0

100

200

300

Solu

ble

Rea

ctiv

e Ph

osph

orus

(kg)


Figure 40. Annual SRP load, averaged over 3 years in monitored tributaries of Shawano Lake, 2005‐2007 (black dots are outliers)

Although Pickerel Creek contributed a high phosphorus load, the size of the tributary dwarfed the

export rate on a per‐hectare basis, indicating that the distribution of the problem is spotty rather than uniformly problematic. Higher phosphorus export rates were observed in Duchess, Noname, and Murray Creeks. It is worthwhile to point out that all observed export rates were less than 0.10 kg/ha/yr, which is lower than the range typical of other regional watersheds and sub‐watersheds. Wisconsin’s small agriculture watersheds (similar in size to the sub‐watersheds of Shawano Lake) usually export about 3.1kg/ha/yr whereas much larger river drainages export between 0.40 and 0.46 kg/ha/yr. Forested watersheds of all sizes typically export 0.1 or less kg/ha/yr (Robertson 1996); these values more closely match observations in the monitored sub‐watersheds.


0.000.020.040.060.080.10


TP (k

g/ha

/yr)

Figure 41. Median TP export rates in monitored tributaries, 2005‐2007

0.00

0.02

0.04

0.06

0.08


SRP

(kg/

ha/y

r)

Figure 42. Median SRP export rates in monitored tributaries, 2005‐2007

Fall events appear to be the only flow/seasonal component that plays a less significant role in total

phosphorus loading (Figure 43). High spring event loads indicate runoff from un‐vegetated fields and possible landspread manure, which is probably the case in Pickerel and Noname Creeks. Loon and Pickerel Creeks stand out as having unusually high TP contributions from baseflow. The high baseflow TP load is explained in Figure 44, where we see that much of the baseflow TP load can be attributed to SRP. In fact, about 60% of the baseflow TP in Loon Creek is in the form of SRP, and 40% of the baseflow TP in Pickerel Creek is in the form of SRP. These figures indicate that SRP is being released from the TP that is bound to sediment. It is possible that the lakes through which Loon and Pickerel Creeks flow (Loon Lake and White Clay Lake) may be important sources of baseflow SRP due to sediment phosphorus release.

0

65

130

195

260


TP (k

g)


Figure 43. Seasonal/flow components of TP load in monitored tributaries of Shawano Lake, 2005‐2007

Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point 43

0

40

80

120


SRP

(kg)


Figure 44. Seasonal/flow components of SRP load in monitored tributaries of Shawano Lake, 2005‐2007

4.5 Synoptic Stream Samples To determine the extent to which landuse affects nutrient concentrations within the sub‐

watersheds, synoptic sampling was performed during storms in July and October 2007. Samples were collected from 10 sites in the Shawano Lake watershed. In addition to the regular sampling sites, samples were collected upstream of the regular sampling sites where Richmond Street crossed Murray Creek, Resort Creek, and Noname Creek, at the mouth of the western tributary of Duchess Creek, and at the mouth of Loon Creek (Figure 45). The samples are snapshots during two storms; significant variability in water quality may be observed at different points in a storm and during different seasons.

The water quality at the additional sites was compared to water quality of samples collected at the regular monitoring sites on the same day. For the most part, little variability in concentrations occurred between the upstream and downstream sites (Table 14). As expected, no important concentrations changes were observed in the Loon Creek sites, as land use between these sites consist predominantly of wetland and forest. In sub‐watershed 2, insignificant changes in concentration were observed between the downstream site and the two upstream sites in Duchess Creek and its eastern tributary. Due to the high proportion of agricultural land in the eastern tributary sub‐watershed, we would expect to see higher phosphorus concentrations, however, the low concentrations observed may have been a result of the wetland area through which the stream flows prior to the collection site. This would indicate that the wetlands may be improving water quality and should be protected. At the time of sample collection, no differences in TP concentrations were measured in the headwaters and lower regions of Noname Creek in sub‐watershed 4. This sub‐watershed is largely agriculture, with similar proportions of agriculture upstream and downstream. This land use may account for some of the higher phosphorus concentrations observed during the storm event, as well as the similarities in upstream and downstream concentrations. When the tributary is included in the downstream sample, little change in TP is evident during the first storm, but a noticeable change was observed during the second storm (118 μg/L total, 141 μg/L downstream). The additional 180 ha of agriculture and 23 ha of urban area (Swan Acres subdivision) may account for the change during the later storm.

Samples collected in sub‐watershed 5 in August measured higher concentrations of phosphorus in samples collected upstream. The reduction observed downstream in August suggests that runoff entering the stream downstream may have lower concentrations of TP than upstream. A wetland exists between the headwaters and the established sampling point (Site 5) on Murray Creek and at times may also help to filter out some of the upstream phosphorus and sediment.

Phosphorus concentrations in samples collected in August from sub‐watershed 6 were similar. Elevated concentrations of phosphorus (536 ug/L) were measured in the sample collected downstream in October. Such high concentrations were often observed in this tributary. Throughout the study, this tributary was typically dry during the summer months.


!.

!.

!.

!.

!.!.

!.

!. !.

!.

!.

!.

!. UVE

UVHH

UVH

UV22

5 total

6 total

4 total

3 total

2 total1 totaltrib of 2

4 upstream6 upstream

2 downstream1 downstream

5 drains landfill5 drains industrial park

LegendAgriculture

Forest

Developed

Wetlands

Grass/Shrub

Open Watertributaries

watershed & sub-basins

!. synoptic sample sites

Synoptic Sample Locations

0 2 41 Miles

M

Figure 45. Synoptic survey stream sampling sites, sub‐watersheds, and land use

08/20/07 10/17/07 General Ag. Developed Water Wetland Foresttotal 12 28downstream 17total 36 23 346 116 22 313 1310trib of 2 27 505 169 34 430 1398downstream 29 159 52 12 118 89total 186 118 508 38 11 98upstream 113 159 5 23downstream (includes trib) 200 141 688 61 0 26 154total 23 33 307 195 2 182 247upstream, drains industrial park 76 16 120 149 1 100 163

upstream, drains landfill 101 19 133 15 41 46total 145 536 530 37 39 244upstream 140 75 425 2 27 200

81 329

Murray

Resort

2988

Stream Site

418 1201

Landuse (ha)TP (μg/L)

Loon

Noname

Duchess

Table 14. Results of synoptic sampling for TP in the Shawano Lake watershed, where “total” represents the entire sub‐watershed upstream of the established monitoring site

4.6 Modeled Phosphorus Loads The water chemistry analysis in the previous section allowed us to make general statements about

a large data set, and then dissect it to arrive at more detailed interpretation. The results were reported either as a range, or as median values. This analysis was based on data collected, however, it is desirable to use a model to extrapolate annual data between periods when data was not collected. Annual TP load from the watershed was needed for the Shawano Lake phosphorus budget, so a computer model (FLUX)


was used to generate single TP values for each sub‐watershed and monitoring season. Three TP loads were generated, representing the 2005, 2006, and 2007 monitoring season. The output from FLUX was then scaled to unmonitored sub‐watersheds. Table 15 displays the TP loads and the stream discharge from each sub‐watershed during the monitoring periods of 2005‐2007. The values generated by FLUX for the monitored tributary were used to calibrate the Soil and Water Analysis Tool (SWAT) to gain a better understanding of the long‐term phosphorus loading patterns. FLUX values were also used to calibrate a model to create the Shawano Lake phosphorus budget.

Vol (hm3) TP (kg) Vol (hm3) TP (kg) Vol (hm3) TP (kg)Loon Creek (1) 2.06 78.1 4.32 158.2 1.86 64.7Dutchess Creek (2) 1.07 105.5 1.07 48.9 2.98 109.9trib to Dutchess** 0.13 12.8 0.13 15.2 0.04 3.3Pickerel Creek (3) 2.20 123.3 2.53 181.8 1.64 206.9Noname Creek (4) 0.31 72.1 0.31 85.1 0.08 18.5trib to Noname** 0.22 4.4 0.22 2.1 0.60 4.5Murray Creek (5) 1.23 87.7 1.50 111.6 0.25 22.8"Resort Creek" (6) --- --- --- --- 0.01 2.6trib west of Resort** 0.13 13.8 0.14 16.3 0.04 3.5Total 6.86 466.7 11.04 624.5 6.82 425.4*values for April-October**unmonitored

Stream (Site)2005* 2006* 2007*

Table 15. Seven‐month tributary outflow and phosphorus export for Shawano Lake watershed

TP loads from the previous section were recalculated for only the monitoring seasons to match the

timeline used in FLUX. The calculated loads were then compared to the modeled loads (Figure 46) to check the consistency of the two methods. For each site, at least one FLUX prediction was within the calculated data spread. The annual variability observed in modeled loads at individual sites may be a function of the amount and timing of rainfall and snowmelt, changing agriculture rotations, and natural variability.

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TP (k

g)


FLUX loads

LEGENDcalculated loads

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TP (k

g)


FLUX loads


FLUX loads

LEGEND

FLUX loads



Figure 46. Calculated TP load, compared to FLUX TP load, averaged over 3 monitoring seasons, 2005‐2007 (black dots are outliers)

4.7 SWAT Model of the Watershed The SWAT model was used to simulate the variability in phosphorus export from the Shawano Lake

watershed. The SWAT model is a relatively complex simulation approach that combines characteristics of the watershed with daily precipitation and temperature to simulate plant growth and water routing. It can be used to better understand the fate of water and nutrients within watersheds and the variations that occur with different weather conditions.

The Shawano Lake watershed was divided into seven different sub‐watersheds for SWAT modeling. Five of the different sub‐watersheds terminated at the study monitoring locations and included an additional sub‐watershed upstream of White Clay Lake. A seventh sub‐watershed included the unmonitored portions of the watershed.

Appendix C shows the agreement between streamflow measurements and model simulations at all five monitoring locations. Calibration to the phosphorus export was based on sediment concentrations and the ratio of dissolved to particulate phosphorus in the runoff. The modeled and measured monthly phosphorus loads for the five monitoring locations are also shown in Appendix C.

The calibrated SWAT model was used to explore the long‐term variability in phosphorus loading to the lake. The result of a twenty‐year SWAT simulation (1987‐2006) is shown in Figure 47. The model results suggest that the last several years were likely ones of below average phosphorus export to the lake.

0

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3500

1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

April

-Sep

tem

ber P

hosp

horu

s (k

g)

Figure 47. Long‐term annual phosphorus loads from all tributaries and unmonitored regions.

4.8 Lakeshore Landuse and Shoreland Loads 4.8.1 Runoff

A land use analysis was performed in the region of the watershed that drained directly to Shawano Lake. To assist in the evaluation of this region the most detailed analysis occurred in developed areas along the shoreline. Digital aerial photos were used with GIS software to digitize impervious surfaces on shoreland parcels (Figure 48).

The areas of impervious and pervious surfaces were used as inputs in the Source Loading and Management Model (WinSLAMM), an urban runoff model. Scenarios were modeled using different degrees of connection, that is, the portions of the impervious surfaces that drained either directly to the lake (“connected”) or onto a lawn or other pervious surface (“disconnected”). These scenarios were used


to provide a range of phosphorus load estimates from the shoreland areas around the lake. The model was run assuming 0, 25, 50, 75, and 100% disconnection. Model results ranged from 0 to 168 kg of phosphorus per year (Figure 49). The range of results directed our decision for the portion of the phosphorus budget attributed to shoreland runoff. A value of 108 kg/yr was predicted for the phosphorus budget, as it provided a realistic value for the calibration of lake models. The value was verified with an ex post facto calculation of shoreland runoff and phosphorus loading using NRCS curve numbers and phosphorus export coefficients for lawns, roofs, and driveways. The verification calculation was 106 kg/yr, which closely matched the predicted TP load for the phosphorus budget (Figure 49).

Single site values were not calculated because it is not possible to determine the amount impervious surfaces that are directly connected using only aerial photos. Site characteristics such as compacted soil, sparse vegetation, and steep slopes influence how much runoff actually flows across a lawn and connects to the lake.

Figure 48. Impervious surfaces on shoreland parcels


Modeled Shoreland Phosphorus Loads

108 106

168

126

84

42

00

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SelectedValue

ExportCoef.

0% 25% 50% 75% 100%

TP(k

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r)

SLAMM % Disconnected

Modeled Shoreland Phosphorus Loads

108 106

168

126

84

42

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SelectedValue

ExportCoef.

0% 25% 50% 75% 100%

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SLAMM % Disconnected

Figure 49. Annual TP load from Shawano shorelands, predicted with SLAMM and calculated with export coefficients and NRCS curve numbers. 4.8.2 Soils and Groundwater

The shoreland groundwater study did not yield any relationship between soil test phosphorus and groundwater SRP concentrations; nor was any trend observed in groundwater SRP concentrations along the sampling transects. However, a direct relationship was observed between groundwater NH4

+ and SRP. These nutrients are components of turf fertilizers. Increasing concentrations of one nutrient accompanied by increasing concentrations of the other indicates fertilizer application. They are also common components of groundwater that moves through buried wetlands.

The study was valuable in that it revealed that property owners are applying fertilizer when it already has more phosphorus than necessary. Figure 50 shows soil phosphorus concentrations from lawns and undeveloped regions, where concentrations less than or equal to 20 ppm are the standard for comparison. 20 ppm is the concentration recommended for a healthy lawn; phosphorus additions are not necessary beyond this concentration. Thirty‐nine soil samples were collected from lawns; 36 of those samples (93%) had >20 ppm soil test phosphorus. 16 soil samples were collected from woodlots or other undeveloped areas; 4 of those samples (25%) had >20 ppm soil test phosphorus. Soils from lawns are consistently higher in phosphorus than undeveloped areas, and are almost always greater than 20 ppm.


Figure 50. Soil test phosphorus in shoreland parcels (undeveloped sampled parcels are green).


5 Groundwater

5.1 Groundwater Inflow Groundwater in Shawano Lake was measured using a combination of minipiezometers and seepage

meters. Groundwater inflow was observed at 86 of the 189 mini‐piezometer sites (47%) and groundwater outflow was not observed (Figure 51). Inflow zones were designated wherever mini‐piezometer observations yielded inflow over a distance greater than 500 feet. The distance that inflow extended from the shore ranged from 30 to 115 feet. The 26 detected inflow zones are estimated to cover an area of 48 acres (19 ha) on the 6217 acre lake (2516 ha). The volume of groundwater inflow (hm3/yr) was calculated based on precipitation infiltrating in the contributing zone, produces an annual groundwater contribution of 1.09 hm3 (38,500,000 ft3).

Water samples that were collected from mini‐piezometers were analyzed for soluble reactive phosphorus (SRP), inorganic nitrogen (NH4

+, NO2++NO3

‐), and chloride (Cl). Table 16 summarizes the groundwater chemistry. A phosphorus load was calculated by multiplying the calculated inflow volume by concentration; the range of annual SRP loads is shown in Table 16. The chosen value that most realistically contributed to the phosphorus budget was 160 kg/yr, which was within the range of observed load calculations.

Figure 51. Mini‐piezometer sites and groundwater flow along the Shawano Lake perimeter.


NO2+NO3 (mg/L)

NH4 (mg/L)

CL (mg/L)

SRP (μg/L)

SRP (kg/yr)

maximum 0.90 27.30 134.00 2130 2313475th percentile <0.2 3.06 22.13 469 5097median <0.2 0.92 12.50 142 154225th percentile <0.2 0.24 6.00 45 491minimum <0.2 <0.01 0.05 13 141

Table 16. Chemistry and SRP loads in groundwater entering Shawano Lake.

6 Phosphorus Budget The BATHTUB model was used to create a phosphorus budget for Shawano Lake. The budget

accounts for phosphorus sources entering, within, and leaving of the lake. The phosphorus sources entering the lake included contributions from inflowing tributaries (as modeled by FLUX), shoreland runoff (as modeled by SLAMM), groundwater inflow, precipitation, waterfowl, and aquatic macrophytes. Phosphorus stored in the sediment may be on the lake bottom but can be released to the water column through a variety of mechanisms and therefore is also treated as a load to the lake. Phosphorus leaving the lake included losses from the lake’s outlet, groundwater outflow, and aquatic macrophyte harvesting.

6.1 Phosphorus Inputs 6.1.1 Watershed Inputs

Phosphorus loads from the monitored tributaries (modeled with FLUX), unmonitored tributaries (scaled to FLUX data), shoreland runoff (modeled with SLAMM), and groundwater (calculated as the “comparative estimate”) were described earlier in the document.

6.1.2 Precipitation

Precipitation and dry deposition of phosphorus onto the lake surface occurs throughout the year encapsulated in rain or snow or as dry fall from dust and other particles in the air. An average annual P mass of 138 kg from precipitation was quantified using total rainfall for a given time period (month or year) and a phosphorus concentration of 7 μg/L of precipitation. This concentration was selected using data collected by the National Atmospheric Deposition Program and collaboration with other researchers in Wisconsin. Atmospheric deposition accounted for about 8% of the annual phosphorus inputs to Shawano Lake (Figure 53). Another method of estimation was tested using rain gauges that were placed throughout the watershed. Daily precipitation was measured and content was analyzed for phosphorus. Due to complications associated with debris and insect contamination these data were excluded.

6.1.3 Sediment

Sediment plays an important role in phosphorus cycling in a lake by acting as both a sink and source for phosphorus. Organic sediment is comprised of particles from dead plants and animals, sediment carried in from tributaries or eroded from shorelines, and other debris that is deposited on the lake bed. Over time, lakes tend to accumulate phosphorus in the sediment. Phosphorus retention and release from the sediment in Shawano Lake was estimated from research preformed by James and Owens in 2005 and 2006 and Hoverson in 2007. The research evaluated phosphorus release from Shawano Lake sediment to the


water under oxygenated and non‐oxygenated conditions. Sediment cores were collected at multiple depths and locations and measurements in the laboratory were made to derive phosphorus release rates.

Sediment phosphorus release rates and monitored dissolved oxygen and pH values in the lake were used to calculate an internal phosphorus load for Shawano Lake. Particularly during the summer when external load was limited, the internal phosphorus load became the greatest source of phosphorus to the water column as phosphorus became highly concentrated in the hypolimnion (> 200 g L‐1); however this phosphorus remained in the lower layer of lake water unless the lake became mixed during a heavy mid‐summer storm (Hoverson 2008). Shawano Lake appears to mix by September, when some algae growth is still taking place. The total annual internal load was estimated to be 455 kg or 24% of the average annual phosphorus budget for Shawano Lake.

6.1.4 Aquatic Plant Removal

Multiple aquatic plant control strategies are implemented in Shawano Lake including chemical treatment (focused on boating/transportation lanes), mechanical harvesting, and manual removal by individual landowners on a smaller but lake‐wide scale. Many of these activities are being organized and funded by SAWM; locations and other criteria are outlined in a permit approved by the WDNR. Following chemical treatment, phosphorus in aquatic plant tissue stays in the lake and eventually becomes sediment. Mechanical and hand harvesting aquatic plants not only removes the plants but also the phosphorus contained in the plant tissue. To determine the amount of phosphorus removed from harvesting plants, SAWM’s harvesting records of the number of truck loads and weight for years 2005 – 2007 were used. Several assumptions were required to compute the amount of phosphorus removal associated with the harvested loads; the harvested areas were assumed to be dominated by Eurasian water milfoil (Myriophyllum spicatum) and therefore biomass estimates and associated phosphorus in EWM obtained in research at nearby lakes were used. The phosphorus content of the plant tissue was not measured from the Shawano Lake harvested plants so reasonable low (15%) and high (40%) phosphorus tissue concentrations were calculated. Harvesting and phosphorus removal estimates are shown in Table 17.

Year Truck Loads Removed

Wet weight (kg)

Dry weight (kg)

Low P content .15% kg P/ kg

biomass

High P content .40% kg P/ kg

biomass

2005 144 261449 52290 78 209 2006 235 426671 85334 128 341 2007 246 446643 89329 134 357 Dry weight equivalent to 80% moisture content

Table 17 Summary of Myriophyllum spicatum harvesting records and estimated phosphorus removal from Shawano Lake, 2005‐2007. 6.1.5 Biotic Addition/Removal

Shawano Lake has a large migratory population of waterfowl using the lake in the spring and fall and a population of about 300‐400 mallards live and breed locally on the lake (personal observations – Darrin Hoverson). No direct measures of phosphorus were made in estimating the phosphorus contribution to the lake from waterfowl feces. Observations by Kay Brockman‐Mederas, Wildlife biologist, WDNR indicate there are usually more coot and diver duck species, but Canada geese (Branta canadensis) and mallards (Anas platyrhynchos) also use Shawano Lake while migrating. The local mallard population was assumed to be recycling phosphorus within the lake as most of the food it was consuming likely came from the lake. Shawano Lake has a large fall American coot (Fulica americana) population that visits the lake for upwards of a month later in the fall. Coots spend a substantial period of time on the water and so


are used to determine a fall estimate of phosphorus inputs to the lake. This seasonal population is estimated at around 10,000 birds, assuming 19 g P/coot‐day the resulting fecal matter can account for 57 kg of phosphorus. This phosphorus remains within the lake as the coots likely do not bring phosphorus from outside sources such as agricultural field as many water bodies in which migrating or local Canada geese and mallard populations may do so. Therefore, phosphorus associated with waterfowl may increase the amount of available phosphorus in the lake in the fall but because it is a recycled source of phosphorus; due to the cooling temperature and decrease in the lake’s metabolism, an algal bloom is less likely therefore this source will be mentioned but omitted from the phosphorus budget.

First identified in 2002, the zebra mussel (Dreissena polymorpha) a highly invasive and exotic mollusk became a new addition to Shawano Lake. They reproduce very quickly and have the ability to out‐compete many native mollusks. They are a nuisance and can be problematic to other aquatic life, boats, docks, and whatever else they are able to attach to. Zebra mussels have the ability to filter and remove large quantities of suspended materials (organic particles, algae, etc) from water, thereby clarifying the water and improving light transparency. Zebra mussels have been documented as changing stratification patterns in lakes (Neng and Culver 2000) and while removing nutrients through filtration are recycling and excreting soluble inorganic nitrogen and soluble phosphorus back into the water resulting in increased concentrations of nutrients that are readily available for aquatic plant and algal use (James et al. 2000, Arnott and Vanni 1996). Much is still unknown about the long‐term impacts from zebra mussels on water quality and a lake’s ecosystem.

Throughout this study, the zebra mussel population appeared to be increasing; however a lake‐ wide survey of zebra mussels was beyond the study scope; because the introduction occurred recently the population will likely fluctuate for some time. Qualitative monitoring has been conducted by a SAWM volunteer since 2000, zebra mussels were first identified on sampling plates in 2004. A summary of this data that was collected at seven locations in and around Shawano Lake is presented in Table 18. An increase in numbers at all locations was observed following 2004, with the greatest increase occurring in 2006. A maximum plate count of 18,240 individuals/sampling device was the greatest population density. In 2007 another increase occurred at all but the north sampling location where a large decrease in density was observed. It is unknown what caused the decrease in zebra mussels inhabiting this location, however, lifecycles of 3 to 4 years may have contributed to a decrease as the first generation population aged.

Test Unit Location Year

2004 2005 2006 20071 South West 0 84 440 30252 North 72 235 18240 277 3 East 0 8 14 40 4 South na 810 1064 49505 West na 0 4 61 6 Outlet to Wolf River na 1 6 17 7 Up‐river Near Dam na na na 1 Total 72 1138 19768 8371Average count per unit placed 24 190 3295 1196

Increase (Decrease) Factor (year to year) na + 8 + 17 ‐ 3 Table 18. Summary of zebra mussels collected from sampling plates located throughout Shawano Lake. Data collected and supplied by Bob Hynek, Bonduel, Wisconsin.


6.2 Predicted Phosphorus Budget Field and modeled data were used to calibrate BATHTUB to match lake phosphorus concentrations.

Data was adjusted, so the annual loads (or “predicted loads”) from the various inputs reflected the measured data. Table 19 documents the annual total phosphorus predicted by BATHTUB, and Figure 52 and Figure 53 show the percent contribution of the different sources. An estimated 1821 kg of phosphorus are introduced to Shawano Lake each year. Figure 52 demonstrates that tributaries contribute almost half of the annual phosphorus budget, and over a third of the budget is attributed to internal loading (sediment release and p. crispus). Amongst the tributaries, Loon and Pickerel Creeks appear to contribute the most phosphorus. However, predicted contribution range of the monitored tributaries is only 6%‐11%, so no single tributary stands out significantly above the others.

Source Load (kg/yr) Load (%)Loon Creek 196 10.8Dutchess Creek 126 6.9Pickerel Creek 197 10.8No Name 111 6.1Murray Creek 126 6.9Unmonitored 25 1.4Shoreland Runoff 108 5.9Internal Sediment Release 456 25.0P. crispus 178 9.8Groundwater 160 8.8Precipitation 138 7.6Total 1821 100

Table 19. Summary of predicted phosphorus inputs to Shawano Lake.

P‐Budget (kg/yr)

Internal Load63435%

Tributaries78242%

Precipitation1388% Direct Runoff

1086%

Groundwater1609%

Figure 52. Predicted contributions to the Shawano Lake phosphorus budget.


Stream Contributions (kg/yr)

Dutchess Creek6.9%

Pickerel Creek10.8%

No Name6.1%

Unmonitored1.4%

Loon Creek10.8%

Murray Creek6.9%

Figure 53. Predicted tributary contributions to the Shawano Lake phosphorus budget.

6.2.1 Summary of Bathtub Modeling Results

It is estimated that about 35% of the total phosphorus load in Shawano Lake is from internal loading and the remaining 65% is from external loads entering the lake via its tributaries and near shore runoff (48%), groundwater (9%), and atmospheric deposition (8%). Data collected in 2005, 2006, and 2007 were used in BATHTUB to determine the mean lake total phosphorous and chlorophyll a concentrations averaged for the growing season months of April through September. The estimations produced by BATHTUB are very similar to the field data (Table 20).

TP (ug/L) Chlorophyll a (ppm)

predicted observed predicted observed 29.5 29 11.4 11.3

Table 20. Summary of observed (2005‐2007) and predicted mean TP and chlorophyll a concentrations

7 Nutrient Reduction Scenarios Once the BATHTUB model was accurately calibrated to predict values that were very similar to field

data, it was than used as a predictive tool. The influences of changes in tributary phosphorus loads on Shawano Lake’s total phosphorus and chlorophyll a concentrations were explored by developing three scenarios; these scenarios involved reducing total phosphorus loads from the entire watershed by 20% and 40%, and increasing loads by 20%. The relationship between changes in the averaged 2005, 2006, and 2007 total phosphorous external loads and chlorophyll a are found in Figure 54. A very strong linear correlation exists between sets of data points. The gentle slope of the chlorophyll a regression line suggests that mean lake chlorophyll a concentrations are influenced but do not change proportionally to changes in external total phosphorous loads.

In addition to changes in chlorophyll a, the frequency that an algae bloom would occur between April and September was also predicted for the three scenarios. In general, algal blooms are considered a nuisance at chlorophyll a concentrations of about 20 μg L‐1 (ppb). Currently chlorophyll a concentrations of 20 μg L‐1 or more occur during about 11% of the growing season or 17 days. If total phosphorus from external sources were reduced by 20%, nuisance blooms would only occur about 4% of the growing season


or about 6 days, and a 20% increase in total phosphorus would result in nuisance algal blooms about 22% of the growing season or 33 days (Figure 55).

y = 29.95x + 29.57R2 = 1

y = 15.85x + 11.56R2 = 0.9976

0

10

20

30

40

-40% -30% -20% -10% 0% 10% 20% 30%

% TP External Load

Pre

dict

ed T

P an

d C

holo

rphy

ll a (μ

g L-1

)

TP Chlor a

Figure 54. Relationship between changes in the averaged 2005‐2007 external total phosphorous load and predicted TP and chlorophyll a concentrations for Shawano Lake.

2030

4050

60

-40%

-20%

0%

20%

0.0

5.0

10.0

15.0

20.0

25.0

Bloo

m F

requ

ency

(% e

xcee

danc

e)

Chlor a (μg L-1)

External TP Load (% of average 2005-2007)

Algae Bloom Frequencies Under Various Scenarios in Shawano Lake

Figure 55. Predicted bloom frequencies (%) and associated chlorophyll a concentrations for four scenarios, 20% reduction, 40% reduction, and 20% increase from the averaged 2005‐2007 total phosphorous external loading.

7.1 WiLMS Model Structure and Results Like the BATHTUB model, average phosphorus inputs from the 2005, 2006, and 2007 monitoring

years were used to calibrate the model and simulate in‐lake phosphorus concentrations. Two external phosphorus reduction scenarios of 20% and 40% and one scenario with a 20% increase in phosphorus were input into the models to predict the in lake effects of the changes. The Larsen‐Mercier predicted the Shawano Lake concentration of 29 μg L‐1. The Walker model was slightly higher than what was observed in Shawano Lake and the Vollenweider shallow lake model was about 30% lower than the observed mean concentrations. A change in lake phosphorus concentration related to each scenario’s change in phosphorus load is shown in Table 21.


Parameter Average 20% reduction 40% reduction 20% increaseTotal P loading 1820 1450 1120 2100Lake P modelWalker, 1977 (general lakes) 33 27 21 39Vollenweider, 1982 (shallow lakes) 20 16 13 23Larsen and Mercier, 1976 (general lakes) 29 23 18 34Average of models 26 22 17 32Reduction from Average 15% 35% -23% Table 21. Estimated total phosphorus concentrations in Shawano Lake from hydrologic and phosphorus loading models contained in the WiLMS for scenarios specified to calibrate and what‐if scenarios

Based on the decreases in phosphorus loading to the lake by 20 and 40%, in‐lake phosphorus

concentrations should decrease by almost the same percentage as the decrease in loading rates, whereas decreases in chlorophyll a concentrations and increases in water clarity (secchi depth) will not be as great (Table 22). With the measured average summer phosphorus concentration of 29 μg L‐1, the models simulated a chlorophyll a concentration of 11.7 μg L‐1 (compared to 11.3 μg L‐1 2005‐2007 mean) and a secchi depth of 1.3 m (compared to 3.2 m 2005‐2007 mean). The WiLMS results predict less of a response to reductions and increases in algae and water clarity than reductions predicted by BATHTUB.

Scenario TP (ug/L) Chlor a (ug/L) Secchi (ft)

TP - 20% 22 9.8 1.5TP - 40% 17 8.3 1.70% 29 11.7 1.3TP + 20% 32 12.5 1.2

Table 22. Predicted chlorophyll a concentrations secchi depths for four scenarios, 20% reduction, 40% reduction, current estimate, and 20% increase from the averaged 2005‐2007 total phosphorous external loading


8 Summary and Conclusions Shawano Lake and its watershed comprise a fairly complex system. In general, Shawano Lake has

relatively good water quality for a large shallow drainage lake. The lake tends to have enriched sediment and relatively shallow depths which results in good growing conditions and light penetration for aquatic plant growth in more than half of the lake. In addition to the natural complexity associated with a relatively shallow lake, Shawano Lake’s ecosystem appears to be in flux due to the introduction of many non‐native aquatic organisms including zebra mussels, Eurasian water milfoil, and curly‐leaf pondweed. Warmer regional temperatures are also increasing the number of days without ice and therefore increasing the period of time that productivity can occur. The results of this study help to understand the state of Shawano Lake and its watershed.

Seasonal and annual variability in water chemistry, flow, and field measurements were observed. The lake exhibited slight summer stratification in 2005, strong stratification in 2006, and a brief stratification at the East Site in 2007. Stratification was not measured prior to this study. The majority of the lake remains mixed which enables aquatic plants and algae to take advantage of nutrients that are redistributed in the water column. Short term increases in nutrient concentrations occur due to inputs associated with storms or snowmelt, phosphorus release from sediment during periods of low dissolved oxygen, phosphorus release from mass aquatic plant die off, and/or sediment re‐suspension due to wind and/or heavy boating activity. The chlorophyll a data suggests seasonal increases in productivity leading to decreased water clarity and water quality.

Water quality in Shawano Lake is dependent upon internal and external factors. The watershed, as a whole, contributes about half of the annual phosphorus load. This includes direct runoff and tributary loads. Land use practices near shore and within the watershed are probably the most manageable aspect in terms of phosphorus reduction. Each monitored stream contributes 7% to 11% of the annual phosphorus load. Lake and tributary near‐shore land management improvements would have the swiftest effect on nutrient reduction to Shawano Lake. For long‐term improvement it is also important to address land management issues further out in the watershed including reducing phosphorus inputs to groundwater which contributes about 9% of the phosphorus load to the lake.

The greatest single contributor of total phosphorus to Shawano Lake is internal sediment release; this is difficult and expensive to directly manage. The invasive aquatic plant curly‐leaf pondweed (P. crispus) is abundant in Shawano Lake. Its lifecycle results in a large pulse of phosphorus into the lake following its die‐off in June. Timing is such that algae are available to utilize phosphorus that is released from the deceased plants, contributing about 10% of the phosphorus load to the lake. Management strategies should specifically address the reduction of this aquatic plant. Phosphorus can also be reduced from Shawano Lake by harvesting/hand pulling and removing nuisance aquatic plants. The phosphorus in the precipitation that falls directly in Shawano Lake is a result of the agriculture in the region and is therefore difficult to manage.

Lake modeling demonstrates significant benefits from total phosphorus load reduction. A reduction of phosphorus in Shawano Lake will reduce the frequency of algae blooms; it is predicted that a 20% reduction in phosphorus load to Shawano Lake may result in decreasing nuisance algae blooms in the summer from 17 days to 6 days. Although there is no single, clear phosphorus source that stands out as problematic, a watershed‐scale management approach may bring water quality in Shawano Lake closer to the desired levels.


9 Recommendations • The tributaries have been identified as the major source of phosphorus to Shawano Lake. In

many of the southern sub‐watersheds, segments of all streams have partially‐intact or missing buffers. NR‐115 provides that all navigable streams have a 35 ft buffer zone. Although some sections of the tributaries had existing development that was “grandfathered in” and the southern tributaries of Shawano Lake are not navigable, the provision is a good standard for management. (1) Pickerel Creek is a very large watershed and was identified as the largest phosphorus

source among the tributaries. Restoring buffers within 35 ft of the stream banks should help reduce sediment and phosphorus transported in runoff. Excluding cattle from the stream will reduce nutrient inputs and will decrease bank erosion which contributes to total suspended solids and total phosphorus loads. Figure 56 identifies stream segments in sub‐watershed 3 where the corridors are either less than 35 ft or missing. Restoration on these segments may reduce the phosphorus load from Pickerel Creek. Upland flow and erosion reduction measures such as spreading runoff from impervious surfaces across infiltration areas and increasing residue cover will make these buffers more effective.

(2) Noname Creek and its tributary, Resort Creek, Murray Creek, and the stream east of Murray Creek were not major phosphorus contributors individually, but together contributed up to 20% of the annual phosphorus load to Shawano Lake. Figure 57 identifies those areas in the southern tributaries where buffer zones are inadequate. Upland peak flow and erosion reduction measures will reduce the likelihood of concentrated flow through these buffers.

(3) Roads and bridges over the tributaries should be designed to drain road runoff to vegetated filters or retention areas that will help to infiltrate the water. Runoff from roofs can also be drained directly to infiltration areas and thereby reduce the runoff that enters Shawano Lake immediately after storms. Infiltration/treatment devices such as bioretention systems can also be used adjacent to parking lots, driveways and streets.

(4) Agricultural lands should all be managed following a phosphorus‐based nutrient management plan.

(5) Manure should be carefully managed. Whenever possible, store it over winter and incorporate it into the soil whenever possible.

(6) Use of winter cover crops and allowing crop residuals to remain on fields over winter would help to reduce soil movement during early spring snowmelt/runoff.

(7) Mitigating drained wetlands within the problem sub‐watersheds could help to improve water quality conditions.

• Natural areas and wetlands appear to be improving water quality as water flows down tributaries like Duchess and Murray Creeks. Steps should be taken to protect these important natural filters.

• Elevated nitrate concentrations were measured during baseflow in the Noname Creek watershed. Private drinking water wells within this sub‐watershed should be tested for nitrates.

• Years of poor water quality appear to be related to years with increased spring precipitation. Consider designing best management practices for more extreme runoff conditions that could lead to large inputs of phosphorus during events.

• Shoreland runoff contributes an estimated 108 kg of phosphorus per year to Shawano Lake. Opportunities exist for decreased runoff volume and phosphorus concentrations. (1) Much of the shoreline lacks sufficient vegetative buffers to remove sediments, nutrients,

and pollutants from runoff and to provide habitat for aquatic wildlife. The state standard


for a functional buffer is thirty‐five feet from the water. Re‐establishment of buffers in these areas is strongly encouraged, and should include grasses, forbs, shrubs, and trees.

(2) Existing native shoreline vegetation around the lake should be protected and efforts should be made to establish more natural vegetation in shoreline riparian areas. This vegetation provides many benefits to the lake ecosystem. The grasses and shrubs filter out sediments which flow from adjacent areas. The vegetation maintains and increases soil infiltration rates, uses nutrients that would otherwise flow to the water, taking up some phosphorus and nitrogen and provides habitat for many species of animals that use the shoreline.

(3) Take measures to reduce runoff and increase infiltration by installing rain gardens and/or bioretention devices near impervious surfaces on new and existing structures.

• Soil test phosphorus concentrations indicate that soil below most residential lawns has adequate phosphorus concentrations and additions are not necessary to maintain a healthy lawn. Prior to adding fertilizer, homeowners should have their soil tested to determine whether phosphorus additions are necessary.

• Explore the use of lime or alum to reduce oxic internal loading from sediment in target areas of the lake.

• Aggressively harvest curly leaf pondweed in early spring, prior to the formation of turions, to remove biomass (and associated phosphorus) and reduce viable reproductive seed.

• Take aggressive action to prevent the introduction of new aquatic invasive species into Shawano Lake and its tributaries.

• Run build‐out scenarios in the Shawano Lake watershed based on existing zoning to better anticipate design standards that might be necessary to prevent additional runoff from increased impervious area.

• Continue monitoring water quality and invasive species in Shawano Lake.

Figure 56. Stream sections in sub‐watershed 3 where buffers are missing or thinner than 35 ft (red circles)


Figure 57. Identified stream sections in sub‐watersheds 4, trib of 4, 5, east of 5, and 6 where buffers are missing or thinner than 35 ft (red circles)


10 References

Andrews, L.M. and C.W. Threinen. 1968. Surface Water Resources of Shawano County. Wis. Dept. of Natural Resources Publication, Madison 1.

Arnott, D.L. and M.J. Vanni. 1996. Nitrogen and phosphorus recycling by the zebra mussel (Dreissena

polymorpha) in the western basin of Lake Erie. Can. J. Fish. Aquati. Sci. 56: 646‐659 Cogger, C.G. 1988. On‐site septic systems: The risk of groundwater contamination. Journ. Env. Health. 51 (1):

12‐16. Hoverson, D. 2008. Phosphorus release from the sediment in a hard‐water lake. Master’s thesis.

University of Wisconsin‐Stevens Point. James W.F., et al. 1997. Filtration and excretion by zebra mussels: Implications for water quality impacts in

Lake Pepin, Upper Mississippi River. J. Fresh. Eco. 15‐4: 429‐437. James, W. F., and C. S. Owens. 2006. Experimental determination of internal phosphorus loading from

sediment and curly‐leaf pondweed in Shawano Lake, Wisconsin. Letter report. Vicksburg, MS: U.S. Army Engineer Research and Development Center, 1‐21.

Lillie, R. A. and J.W. Mason. 1983. Limnological characteristics of Wisconsin lakes. Wis. Dept. of Natural

Resources Tech. Bull. 138, Madison. McCuen, R. 2004. Hydrologic analysis and design. 3rd ed. Pearson Education, Inc., Upper Saddle River, NJ Neng, Y. and D.A. Culver. 2000. Can zebra mussels change stratification patterns in a small reservoir?

Hydrobiologia. 431: 175‐184 Reckhow, K.H., M.N. Beaulac, J.T. Simpson. 1980. Modeling phosphrus loading and lake response under

uncertainty: a manual and compilation of export coefficients. Michigan State University, Department of Resource Development. East Lansing, MI.

Robertson, D.M. 1996. Sources and transport of phosphorus in the western lake Michigan drainages. US

Geological Survey Fact Shett FS‐208‐96. http://wi.water.usgs.gov/pubs/FS‐208‐96/ Shaw, B., C. Mechenich, L, Klessig. 2000. Understanding lake data. University of Wisconsin, Stevens Point.

Extension Publications, Madison, WI. US Army Corps of Engineers. 1960. Engineering and design: runoff from snowmelt. EM‐1110‐2‐1046. US Environmental Protection Agency. 2000. Ambient water quality criteria recommendations. EPA 822‐B‐

00‐018. Office of Water, Washington, DC. Walker, W. 1996. Simplified procedures for eutrophication assessment and prediction: user manual. U.S.

Army Engineer Waterways Experiment Station, Vicksburg, MS.


Walker, W. 1984. "Statistical Bases for Mean Chlorophyll‐a Criteria" Lake and Reservoir Management:

Practical Applications, North American Lake Management Society, Proceedings of Fourth Annual Conference, McAcfee, New Jersey.

Wetzel, R.G. 2002. Limnology: Lake and river ecosystems. Academic Press. 841. Wetzel, Robert G. 2001. Limnology: Lake and river ecosystems. 3rd Ed. Academic Press. 240‐288.

Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point A-I

Appendix A Lake Water Quality Data Date Deep Hole East Site West Site Average Comment

04/24/04 34 35 35 spring overturn05/24/04 26 2606/21/04 7 13 1007/12/04 19 11 1507/20/04 25 2508/04/04 10 7 908/31/04 27 30 24 2710/25/04 27 2711/05/04 25 25 25 fall overturn04/29/05 29 19 24 spring overturn05/24/05 21 2106/29/05 20 2007/19/05 40 32 3607/27/05 38 3808/17/05 34 42 3808/29/05 36 3610/05/05 25 34 30 fall overturn10/28/05 23 2303/08/06 14 28 21 winter04/27/06 16 18 17 spring overturn05/23/06 32 3206/09/06 14 17 1606/29/06 25 23 30 2607/13/06 25 27 2607/31/06 28 2808/10/06 29 29 2908/24/06 36 3608/25/06 41 29 3509/09/06 31 32 3210/18/06 31 33 32 fall overturn10/25/06 19 1902/21/07 25 11 18 winter04/25/07 21 26 24 spring overturn05/29/07 22 2206/29/07 35 3507/25/07 41 4108/13/07 49 49

Site Average 28 26 25 26 Table 23. Concentrations of TP (ug/L) in lake samples

Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point A-II

Date East Site West Site Average Comment

04/24/04 3 6 5 spring overturn06/21/04 3 5 407/12/04 3 7 508/04/04 3 8 608/31/04 3 3 311/05/04 3 3 3 fall overturn04/29/05 7 12 10 spring overturn07/19/05 3 6 508/17/05 7 3 510/05/05 5 14 10 fall overturn03/08/06 6 6 6 winter04/27/06 4 7 6 spring overturn06/09/06 4 8 606/29/06 4 4 407/13/06 8 5 708/10/06 17 7 1208/25/06 8 31 2009/09/06 3 3 310/18/06 5 5 5 fall overturn02/21/07 4 3 4 winter04/25/07 9 17 13 spring overturn

Site Average 5 8 7 Table 24. Concentrations of SRP (ug/L) in lake samples

Date East Site West Site Average Comment

04/24/04 0.04 0.02 0.03 spring overturn06/21/04 0.02 0.02 0.0207/12/04 0.02 0.02 0.0208/04/04 0.02 0.02 0.0208/31/04 0.02 0.02 0.0211/05/04 0.02 0.02 0.02 fall overturn04/29/05 0.02 0.02 0.02 spring overturn07/19/05 0.07 0.02 0.0508/17/05 0.08 0.02 0.0510/05/05 0.10 0.10 0.10 fall overturn03/08/06 0.18 0.05 0.12 winter04/27/06 0.03 0.03 0.03 spring overturn06/09/06 0.01 0.01 0.0106/29/06 0.10 0.10 0.1007/13/06 0.10 0.10 0.1008/10/06 0.10 0.10 0.1008/25/06 0.10 0.10 0.1009/09/06 0.10 0.10 0.1010/18/06 0.10 0.10 0.10 fall overturn02/21/07 0.08 0.04 0.06 winter04/25/07 0.10 0.10 0.10 spring overturn

Site Average 0.07 0.05 0.06 Table 25. Concentrations of NO2

‐ +NO3‐ (mg/L) in lake samples

Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point A-III

Date EAST WEST Average Comment


Site Average 0.81 0.85 0.83 Table 26. Concentrations of TKN (mg/L) in lake samples



Site Average 0.83 0.86 0.85 Table 27. Concentrations of TN (mg/L) in lake samples

Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point A-IV


04/24/04 0.01 0.03 0.02 spring overturn06/21/04 0.07 0.07 0.0707/12/04 0.06 0.05 0.0608/04/04 0.04 0.02 0.0308/31/04 0.04 0.02 0.0311/05/04 0.02 0.01 0.02 fall overturn04/29/05 0.05 0.02 0.04 spring overturn07/19/05 0.06 0.08 0.0708/17/05 0.09 0.09 0.0910/05/05 0.05 0.06 0.06 fall overturn03/08/06 0.02 0.07 0.05 winter04/27/06 0.02 0.03 0.03 spring overturn06/09/06 0.04 0.06 0.0506/29/06 0.01 0.11 0.0607/13/06 0.02 0.01 0.0208/10/06 0.07 0.03 0.0508/25/06 0.05 0.30 0.1809/09/06 0.01 0.01 0.0110/18/06 0.01 0.01 0.01 fall overturn02/21/07 0.04 0.02 0.03 winter04/25/07 0.18 0.18 spring overturn

Site Average 0.05 0.06 0.05 Table 28. Concentrations of NH4

+ (mg/L) in lake samples

Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point B-I

Appendix B Rating Curves and Hydrographs

Stage vs. FlowSite 1, Loon Creek, MY 05-07

y = 22.156x - 8.8823R2 = 0.7869

0

5

10

15

20

25

0.0 0.5 1.0 1.5Staffgage Stage (ft)

Flow

(cfs

)

Table 29. Site 1 stage/flow relationship

Staff Gauge Rating CurveSite 1, Loon Creek, MY 05-07

y = 18.952x - 8.7422R2 = 0.7192

0

5

10

15

20

0.0 0.5 1.0 1.5Transducer Level (ft)

Flow

(cfs

)

Table 30. Site 1 rating curve

Site 1 2005-2007 Estimated Flow

0

10

20

30

2/17/05 7/17/05 12/14/05 5/13/06 10/10/06 3/9/07 8/6/07 1/3/08

Flow

(cfs

)

observedpressure transducerstaff gauge

Table 31. Site 1 hydrograph

Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point B-II

Stage vs. FlowSite 2, Dutchess Creek, MY 05-07

y = 12.217x - 7.6626R2 = 0.8988

0

10

20

30

40

0.0 0.5 1.0 1.5 2.0 2.5 3.0

Staffgage Stage (ft)

Flow

(cfs

)


Staff Gauge Rating CurveSite 2, Dutchess Creek, MY 05-07

y = 13.101x - 6.8057R2 = 0.9788

0

10

20

30

0.00 0.50 1.00 1.50 2.00 2.50 3.00Transducer Level (ft)

Flow

(cfs

)



0

10

20

30

2/17/05 7/17/05 12/14/05 5/13/06 10/10/06 3/9/07 8/6/07 1/3/08

Flow

(cfs

)


Table 34. site 2 hydrograph

Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point B-III

Stage vs. FlowSite 3, Pickerel Creek, MY 04-07

y = 18.694x - 17.061R2 = 0.7296

0

10

20

30

0.0 0.5 1.0 1.5 2.0 2.5 3.0Staffgage Stage (ft)

Flow

(cfs

)


Staff Gauge Rating CurveSite 3, Pickerel Creek, MY 04-07

y = 20.244x - 4.708R2 = 0.8258

0

10

20

30


Flow

(cfs

)



0

10

20

30

2/7/05 7/7/05 12/4/05 5/3/06 9/30/06 2/27/07 7/27/07

Flow

(cfs

)

observedpressure transducerstaf f gauge


Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point B-IV

Stage vs. FlowSite 4, Noname Creek, MY 04-07

y = 6.9322x - 4.8639R2 = 0.9713

0

2

4

6

8

10

0.0 0.5 1.0 1.5 2.0Staffgage Stage (ft)

Flow

(cfs

)


Staff Gauge Rating CurveSite 4, Noname Creek, MY 04-07

y = 5.3643x - 2.4537R2 = 0.8668

0

1

2

3

4


Flow

(cfs

)



0

10

20

30

2/17/05 7/17/05 12/14/05 5/13/06 10/10/06 3/9/07 8/6/07 1/3/08

Flow

(cfs

)



Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point B-V

Stage vs. FlowSite 5, Murray Creek, MY 05-06

y = 9.3823x - 3.5677R2 = 0.8592

0

5

10

15

20

25

0.0 0.5 1.0 1.5 2.0 2.5Staffgage Stage (ft)

Flow

(cfs

)


Staff Gauge, Shaw ano Tributary Rating CurveSite 5, Murray Creek, MY 05-06

y = 9.3695x - 4.4651R2 = 0.9876

0

5

10

15

20

0.0 0.5 1.0 1.5 2.0 2.5Transducer Level (ft)

Flow

(cfs

)



0

10

20

30

2/7/05 7/7/05 12/4/05 5/3/06 9/30/06 2/27/07 7/27/07

Flow

(cfs

)

observedstaff gauge


Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point B-VI

Stage vs. Flow Site 6, Resort Creek, MY 07

y = 2.1795x - 0.6216R2 = 0.6044

0.0

0.2

0.4

0.6

0.8

0 0.1 0.2 0.3 0.4 0.5 0.6

Staffgage Stage (ft)

Flow

(cfs

)


Staff Gauge, Shaw ano Tributary Rating Curve Site 6, Resort Creek, MY 07

y = 1.3593x - 0.0078R2 = 0.9792

0.0

0.2

0.4

0.6

0.8

-0.1 0 0.1 0.2 0.3 0.4 0.5

Transducer Level (ft)

Flow

(cfs

)


Site 6 2007 Estimate Flow

0.0

0.5

1.0

1.5

2.0

4/8/07 5/8/07 6/7/07 7/7/07 8/6/07 9/5/07 10/5/07

Flow

(cfs

)

observedpressure transducer


Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point C-I

Appendix C SWAT Modeled vs. Measured Discharge

0.0

0.2

0.4

0.6

0.8

1.0

1.2

04/08/05 05/28/05 07/17/05 09/05/05 10/25/05 12/14/05

Flow

(cm

s)

Measured

Modeled

Figure 58. Site 1 modeled vs. measured 2005

0.0

0.2

0.4

0.6

0.8

1.0

1.2

02/02/06 03/24/06 05/13/06 07/02/06 08/21/06 10/10/06 11/29/06

Flow

(cm

s)

Measured

Modeled


0.0

0.2

0.4

0.6

0.8

1.0

01/18/07 03/09/07 04/28/07 06/17/07 08/06/07 09/25/07 11/14/07

Flow

(cm

s)

Measured

Modeled


Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point C-II

0.0

0.2

0.4

0.6

04/08/05 05/28/05 07/17/05 09/05/05 10/25/05 12/14/05

Flow

(cm

s)

Measured

Modeled


0.0

0.2

0.4

0.6

02/02/06 03/24/06 05/13/06 07/02/06 08/21/06 10/10/06 11/29/06

Flow

(cm

s)

Measured

Modeled


0.0

0.2

0.4

0.6

01/18/07 03/09/07 04/28/07 06/17/07 08/06/07 09/25/07 11/14/07

Flow

(cm

s)

Measured

Modeled


Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point C-III

0.0

0.2

0.4

0.6

0.8

1.0

04/08/05 05/28/05 07/17/05 09/05/05 10/25/05 12/14/05

Flow

(cm

s)

Measured

Modeled


0.0

0.4

0.8

1.2

1.6

2.0

02/02/06 03/24/06 05/13/06 07/02/06 08/21/06 10/10/06 11/29/06

Flow

(cm

s)

Measured

Modeled


0.0

0.2

0.4

0.6

0.8

01/18/07 03/09/07 04/28/07 06/17/07 08/06/07 09/25/07 11/14/07

Flow

(cm

s)

Measured

Modeled


Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point C-IV

0.0

0.1

0.2

0.3

0.4

0.5

4/8/05 5/28/05 7/17/05 9/5/05 10/25/05 12/14/05

Flow

(cm

s)

Measured

Modeled


0.0

0.1

0.2

0.3

0.4

0.5

2/2/06 3/24/06 5/13/06 7/2/06 8/21/06 10/10/06 11/29/06

Flow

(cm

s)

Measured

Modeled


0.0

0.1

0.2

0.3

0.4

0.5

01/18/07 03/09/07 04/28/07 06/17/07 08/06/07 09/25/07 11/14/07

Flow

(cm

s)

Measured

Modeled


Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point C-V

0.0

0.1

0.2

0.3

0.4

0.5

0.6

4/8/05 5/28/05 7/17/05 9/5/05 10/25/05 12/14/05

Flow

(cm

s)

Measured

Modeled


0.0

0.1

0.2

0.3

0.4

0.5

0.6

2/2/06 3/24/06 5/13/06 7/2/06 8/21/06 10/10/06 11/29/06

Flow

(cm

s)

Measured

Modeled


0.0

0.1

0.2

0.3

0.4

0.5

0.6

01/18/07 03/09/07 04/28/07 06/17/07 08/06/07 09/25/07 11/14/07

Flow

(cm

s)

Measured

Modeled


Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point C-VI

0

5

10

15

20

25

30

35

40

45

May 05

June

05

July

05

Augus

t 05

Sept 0

5Oct

06

April 0

6

May 06

June

06

July

06

Augus

t 06

Sept 0

6Oct

06

April 0

7

May 07

June

07

July

07

Augus

t 07

Sept 0

7

Kilo

gram

s TP

Measured

Simulated

Site 1

Figure 73. Measured and SWAT simulated monthly P loads (kg) at site 1

0

10

20

30

40

50

60

70

80

90

May 05

June

05

July

05

Augus

t 05

Sept 0

5Oct

06

April 0

6

May 06

June

06

July

06

Augus

t 06

Sept 0

6Oct

06

April 0

7

May 07

June

07

July

07

Augus

t 07

Sept 0

7

Kilo

gram

s TP

Measured

Simulated

Site 2


Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point C-VII

0

20

40

60

80

100

120

140

160

May 05

June

05

July

05

Augus

t 05

Sept 0

5Oct

06

April 0

6

May 06

June

06

July

06

Augus

t 06

Sept 0

6Oct

06

April 0

7

May 07

June

07

July

07

Augus

t 07

Sept 0

7

Kilo

gram

s TP

Measured

Simulated

Site 3


0

5

10

15

20

25

30

35

40

45

50

May 05

June

05

July

05

Augus

t 05

Sept 0

5

Oct 06

April 0

6

May 06

June

06

July

06

Augus

t 06

Sept 0

6

Oct 06

April 0

7

May 07

June

07

July

07

Augus

t 07

Sept 0

7

Kilo

gram

s TP

Measured

Simulated

Site 4


Shawano Lake Watershed Assessment, February 2008, UW-Stevens Point C-VIII

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

May 05

June

05

July

05

Augus

t 05

Sept 0

5

Oct 06

April 0

6

May 06

June

06

July

06

Augus

t 06

Sept 0

6

Oct 06

April 0

7

May 07

June

07

July

07

Augus

t 07

Sept 0

7

Kilo

gram

s TP

Measured

Simulated

Site 5


shawano lake watershed assessment final report

Documents