Land-Use Effects on Nutrient and Algae in the Middle and Lower Nottawasaga River

Land-use effects on nutrient and algae in the Middle and Lower Nottawasaga River

and the Minesing Wetlands

Submitted to:

Environment Canada Lake Simcoe and Southeastern Georgian Bay Cleanup Fund

Julia Rutledge1, Massimo Narini2, Andrea Kirkwood2, Tim Duval3 and Patricia Chow-Fraser1

1McMaster University, 2U. of Ont Inst of Tech, 3University of Toronto, Department of Biology, Faculty of Science, 2000 Department of Geography, 1280 Main St. W, Simcoe St.N. 3359 Mississauga Rd N., Hamilton, ON Oshawa, ON Mississauga ON L8S 4K1 L1H 7K4 L5L 1C6

April 2015

EXECUTIVE SUMMARY

We carried out a monthly (June to September inclusive) sampling program during baseflow conditions to measure physical, chemical (including primary nutrients) and biological variables at 15 stations along the main branch of the Nottawasaga River (between Alliston and the river mouth at Wasaga Beach). This program included four stations within the Minesing Wetlands, a Ramsar site and Provincially Significant Wetland, which should be filtering out nutrients and sediment as the river runs through it. We also obtained water samples from the main branch of the Nottawasaga River and six of its tributaries (first and second order streams) draining three types of agricultural practices (corn row crops, soy bean row crops, cattle pasture) to determine the taxonomic affiliation of planktonic algae and periphytic algae respectively. In addition, from June to August we continuously monitored water levels along and around the Giffin-Walton-Downey Agricultural Drain network within the eastern downstream portion of the Minesing Wetlands to assess the physical mixing of the drain water with the wetland sediments and to determine the residence time of water through this drain. This program also included a near-weekly (June to August inclusive) sampling program during mostly baseflow conditions along and around the drain to detect variation in water solutes (including primary nutrients) to assess the wetlands’ water purification capacity of agricultural runoff.

Results from our monthly monitoring program conducted in the main branch of the Nottawasaga River indicated that nutrient and sediment loading is the most serious water- quality problem. Almost all monitoring stations exceeded the Provincial Water Quality Objective (PWQO) for Total P (TP; 30 µg/L), Total Ammonia N (TAN; 0.02 mg/L), and E. coli (100 CFU/100 mL), while Total N (TN; 1.06 mg/L), Total Suspended Solids (TSS; 3.6 mg/L), and Turbidity (TURB; 6.1 NTU) exceeded the National Agri-Environmental Standards Initiative (NAESI) performance standards for southern Ontario at every single monitoring station. Innisfil Creek (station 02) had significantly higher mean monthly TP, TSS, and TURB compared to all other stations. As the river flows through the Minesing Wetlands, TURB remained high through this section, while nutrient concentrations initially decreased; however, after Willow Creek enters the system, TP concentrations significantly increased, and the concentration of dissolved oxygen decreased significantly. As a consequence, water quality of the Nottawasaga River actually worsened as it exited the Minesing Wetlands. Willow Creek flows through Midhurst, an area of increasing urban development, before it reaches the Minesing Wetlands and flows into Nottawasaga River.

Results from the monthly planktonic algae monitoring program indicated that most areas of the Nottawasaga River are dominated by pollution-dependent or pollution-tolerant species. Both species composition and dominant species of algae varied inconsistently throughout the sampling period and through the Nottawasaga River, but were consistently dominated by one of three diatom genera: Navicula, Nitzschia or Gomphonema. Although not all species in these genera are indicative of increased nutrients or degraded water quality, many of those present in high abundance, such as N. acicularis or G. parvulum, are able to dominate in nutrient-rich waters. Planktonic algal biomass, as well as density, increased throughout the sampling season from June to September across the Nottawasaga River. The Minesing Wetlands did not appear to have an effect on algal community structure or

dominance. Results from periphytic algae monitoring indicated that agricultural practice (crop-type, livestock grazing, etc) did not have a significant effect on any of the water-quality variables, periphytic ash free dry mass (AFDM), or periphyton chlorophyll-α (CHL) content in the tributaries monitored, although it is premature to draw any conclusions due to the small sample size. It is noteworthy that site 6-LC, which drains corn row crops, consistently exceeded the Provincial Water Quality Objective (PWQO) for TAN (0.02 mg/L).

Results from the physical characterization of the Minesing Wetlands’ interaction with agricultural drains indicated an extremely slow movement of water along the drain toward the Nottawasaga River (<0.5 cm/s during baseflow conditions). This slow transfer rate to the Nottawasaga River resulted in the agricultural runoff residing in the drain for a minimum of 5 days. However, there was minimal interaction of the drainage ditch water with the surrounding wetland sediments, except during higher water levels when the wetland water discharged into the drainage ditch. As the agricultural runoff water travelled the length of the Giffin Drain, there were significant decreases in TP, SRP, TAN, and Total Nitrate Nitrogen (TNN) concentrations, but to varying degrees. SRP and TNN decreased by 90% over the length of the ditch, and dilution was not a factor (as revealed through conservative tracers); however, TAN and TP concentrations were still above PWQO levels before the drainage ditch water entered the Nottawasaga River.

We followed a standardized global reference system to classify the Nottawasaga River Watershed into six main types of land uses that included agriculture (row crop, pasture, hay), forest, wetland, barren (beaches, transitional areas, golf courses), urban (built-up pervious and impervious surfaces, golf courses), and water. The dominant land use is agricultural (47%) and it is not surprising that agricultural runoff is one of the major sources of nutrients and sediment to the Nottawasaga River. We identified five key problem areas in the Nottawasaga River. The Innisfil Creek confluence (station 02) was associated with significantly higher mean monthly concentrations of TP (48.2μg/L), TURB (41.4 NTU), and Total Suspended Solids (TSS; 29.1 mg/L) compared to all other stations. Within the Minesing wetlands, TP (42.45 μg/L) was significantly higher and pH (7.8) was significantly lower after Willow Creek (station 10) entered the river. This tributary flows through Midhurst, an area of increasing urban development. Marl Creek contributed relatively high concentrations of TP (37.3 μg/L) at station 12; similarly, Jack’s Lake (station 13), a lentic system within the Nottawasaga River, also had higher TP (42.1 μg/L) and lower DO (6.1 mg/L) compared to other stations. The warmest stretch of river occurred after Knox Road in the town of Wasaga Beach (station 14), where concentrations of Total Ammonia Nitrogen (0.08 mg/L) and E. coli (2424 CFU/100 mL) were elevated. One third of the TSS in the river is organic in nature, indicating that majority of the turbidity in the river is inorganic. Without an additional strategic sampling program, we cannot determine if the TSS is being resuspended within the river. At this point, there is no reason to believe that water in the Downey Drain is mixing with water within the Nottawasga River except during rain events. Although farmland contributes elevated levels of primary nutrients and sediments to the river, we could not find consistent differences among the three land-use practices.

Water quality in the Nottawasaga River is generally impaired and needs to be rehabilitated. In particular, the anoxic conditions at Jack's Lake and in the river within the

Minesing Wetlands during July could limit use by juvenile sturgeon. To determine where rehabilitation should be focused, it would be useful to quantify the relative contributions of nutrients and suspended solids from the various sub-watersheds. Since all of the data collected during this project correspond to base flow conditions, a project designed to monitor changes in water quality conditions during storm events should be carried out in the future. With respect to how the river mixes with bay water, monitoring Nottawasga Bay was outside the scope of this project. Based on aerial photos taken on July 8 with an unmanned aerial vehicle, however, the polluted water from Nottawasaga River entered the bay and flowed along the beach northward towards Tiny Township. In areas of Nottawasga Bay outside this river plume, nutrient and algal concentrations appeared to be very low.

ACKNOWLEDGEMENT

This project was funded in part by a research grant from Environment Canada through the Lake Simcoe Southeastern Georgian Bay Cleanup Fund. We acknowledge in- kind support from McMaster University, University of Toronto and University of Ontario Institute of Technology. We also thank the Nottawasaga Valley Conservation Authority, Sierra Club Canada and Federation of Tiny Township Shoreline Association for sharing information and providing logistical support.

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This report is being provided to partners and the funder for reporting purposes only. Data from this study should be considered and treated as preliminary, and should not be reproduced, used, published or disseminated. All of the information in this study will eventually become part of theses of graduate students from participating universities, and will be published in peer-reviewed journals. Please contact the authors directly for permission to use the information in advance of these publications.

INTRODUCTION

The Nottawasaga River Watershed (NRW) drains 3,600 km2 of the Lake Huron sub- basin into the Nottawasaga River, which eventually flows into Nottawasaga Bay in southeastern Georgian Bay. About half of the NRW is agricultural land-use, 70% of which is specialty crops (Post, 2014; Table 1), and is the probable source of sediment and nutrient enrichment in the river and in the bay. This has become an environmental concern because Nottawasaga Bay features one of the most popular stretches of beach in Ontario, with many summer resorts and cottages. The river also bisects the Minesing Wetlands, a Ramsar site and the largest contiguous inland wetland (6,000 ha) in southern Ontario (Ramsar, 1996; Frazier, 1999). The river itself is also very unique, flowing through a variety of geological landscapes (Niagara Escarpment, Simcoe Uplands, Oak Ridges and Oro Moraines) and is the only tributary of Georgian Bay with confirmed spawning populations of Lake Sturgeon, which is currently listed as a species at risk within Ontario.

The functions of the Minesing Wetlands are critical. Every year, they hold back large volumes of water from spring melt and prevent flooding in low-lying downstream areas such as the town of Wasaga Beach. The vast wetland complex provides various habitats that support diverse assemblages of plant and animal species, including species at risk (lake sturgeon, Blanding’s turtle, wood turtle, Hine’s emerald dragonfly; Bowles, Laverty, & Featherstone, 2007), all of which require good water quality in order to persist. Due to its large size and difficult terrain for field campaigns, research in the Minesing Wetlands has been scarce, but recent studies have shown that water quality on the more accessible northern portion of the wetland is impaired (Post et al., 2010; Brown et al., 2011), with significantly higher concentrations of total phosphorus (TP), turbidity (TURB), and chlorophyll-α (CHL) as the river exits the Minesing Wetlands compared with levels in upstream segments of the Nottawasga River (Chow-Fraser (2006). Given that the Nottawasaga River is the largest tributary (sixth order) that discharges into Georgian Bay, it has the potential to greatly impact the water quality of Nottawasaga Bay and Georgian Bay itself.

Study Rationale

Intensification of agricultural practises, including fertilizer application, tilling, and cattle grazing have led to significant increases in loading of nitrogen (N), phosphorus (P), and sediment in many riverine systems throughout the world (Sharpley et al., 1994, 2003; Carpenter et al., 1998; Goolsby et al., 2000; Dieleman & Chow-Fraser, 2012). This loading can be visualized as a dark plume of sediment entering bays and estuaries. Such a plume has been seen flowing out of the Nottawasaga River into Nottawasga Bay, spreading northeast along the shoreline towards Woodland Beach or southwest along the shoreline towards Wasaga Beach (see Figure 1a).

Pollutants in the plume are more pronounced after storm events. Figure 1b contains a photo that was taken by an unmanned aerial vehicle (UAV) on July 8, 2014, following a rainstorm on July 7th. The high nutrient inputs from runoff can lead to nuisance algal blooms. When the algae die, their decomposition can lead to anoxic zones near the substrate, a condition that favours proliferation of resident type E botulism bacteria (C. botulinum) (Yule et al., 2005). Biomagnification of this neurotoxin has caused substantial avian and fish kills throughout Wasaga Beach and Tiny Township, including 120 Lake Sturgeon during the fall of 2011 (Hopper, 2011). Algal blooms have yet to be observed in the bay, but have been reported in the lower section of the river due to high P concentrations and low flow velocities.

Figure 1a (Top photo): Google Earth image showing the outflow of the lower Nottawasaga River (arrow). To the north is Woodland Beach, and to the south is the town of Wasaga Beach .

Figure 1b (Bottom photo): Image acquired with UAV on July 8th, following a rainstorm on July 7th. The plume appears to have moved in all directions.

Objectives

We will document monthly changes (Jun to Sep) in nutrients and algae at 15 long- term stations in the middle and lower Nottawasaga River, and investigate the type of interactions between the Minesing Wetlands and the Nottawasaga River. Specifically, we will confirm water-quality trends and fill data gaps identified by Chow-Fraser (2006) and Brown et al. (2011). Secondly, we will identify the primary algal groups in the plankton of the main branch of the Nottawasaga River, and in the periphyton collected in representative tributaries draining 3 different types of agricultural land uses (corn row crops, soy bean row crops, cattle pasture). We will also identify areas within the Nottawasaga River where diurnal fluctuations in dissolved oxygen and temperature may become unsuitable for aquatic species including the threatened Lake Sturgeon.

METHODS

Water quality monitoring of the Nottawasaga River

Study Area

The focus of our study lies within the eight subwatersheds (Upper Nottawasaga River, Innisfil Creek, Boyne River, Pine River, Middle Nottawasaga River, Mad River, Willow Creek, Lower Nottawasaga River; Figure 2) that drain into the Nottawasaga River and its watercourses. This encompasses the majority of the watershed monitored by the Nottawasaga Valley Conservation Authority (~2,900 km2). Using ArcMap 10.2 (ESRI Inc., Redlands, California), we followed a standardized global reference system (Anderson et al, 1976; Di Gregorio, 2005) to classify the NRW into six main types of land-use (agriculture, forest, wetland, barren, urban, and water), and subsequently determined their total areas and percent cover within the entire watershed (Table 1; Figure 2). Tributaries that run through different regions and land classifications within the NRW contribute to longitudinal variation in water quality along the Middle and Lower Nottawasaga River (Table 2).

Table 1: Land-use classifications in the Nottawasaga River Watershed and their respective cover expressed as an area (km2) and as a percentage (%).

Land-use Classification Area (km2) % Cover Agriculture 1439 50 Forest 605 21 Wetland 365 13 Barren 267 9 Urban 208 7 Water 19 <1 Total Watershed: 2903 100

Site Selection

We used ArcGIS 10.3 and orthophotos of the study area (Muskoka and Simcoe County Orthophotos, 2008) to strategically select 15 monitoring stations along the main branch of the Middle and Lower Nottawasaga River (Figure 3). Stations were chosen to confirm previous trends and include new areas not previously sampled by Chow-Fraser (2006). As recommended by Brown et al. (2011), four of our stations were established within the stretch of river that bisects the Minesing Wetlands. All locations were field validated and adjusted accordingly to ensure river access was feasible prior to sampling.

Figure 2: Land-use classifications in the Nottawasaga River Watershed (NRW). Each colour represents a main type of land-use: forest (dark green), wetland (light green), barren (brown), urban (grey), agriculture (beige), water (blue). Subwatersheds are outlined in black.

Table 2: Major tributary, subwatershed, and point source inputs influencing water quality at all monitoring stations (01-15). “X” indicates inputs to a station.

Tributary Inputs

Main Branch of the

WWTP

Nottawasga River

Station Number Upper Innisfil Middle Boyne Angus Pine Mad Willow Marl Jack’s Lake Lower 01 X 02 X 03 X X X 04 X X 05 X X 06 X X 07 X 08 X 09 X X 10 X X 11 X 12 X X 13 X X 14 X 15 X

Four additional stations were implemented to monitor diurnal changes in dissolved oxygen concentrations (mg/L) and temperature (°C; Figure 4). Monitoring stations were selected in suspected problem areas, or areas that had not been previously monitored on a continuous basis. One logger was deployed in Jack’s Lake and remained there for the duration of the study period. A second logger rotated between the other three stations, two of which were located within the Minesing Wetlands.

Figure 3: Map of the NRW study area illustrating the 15 water quality monitoring stations (red circles) sampled monthly between June and September. Agricultural land use is coloured beige.

Figure 4: Map illustrating the location of continuous monitoring DO and TEMP stations in the Nottawasaga River (red circles). Agricultural land-use is coloured beige.

Sampling Procedures

Following the sampling procedures outlined by Crosbie and Chow-Fraser (1999), we designed a robust monthly sampling program (June – September) to measure physical and chemical variables, as well as primary nutrients at 15 stations in the Nottawasaga River during base flow conditions. We used a Van Dorn sampler to collect discrete samples at each station in freshly acid-washed Corning™ snap-seal containers or Nalgene® bottles to measure total phosphorus (TP; µg/L), total nitrogen (TN; mg/L), total nitrate nitrogen (TNN; mg/L), total ammonia nitrogen (TAN; mg/L), chloride (Cl-;mg/L), colour (COL), total suspended solids (TSS; mg/L), and chlorophyll-α (CHL; µg/L) (Lind, 1974; Crosbie & Chow- Fraser, 1999). Once collected, all samples were stored on icepacks in a cooler until they could be processed or placed immediately in a freezer for storage until they can be processed back at McMaster University. A YSI 6920 V2 sonde was calibrated prior to each sampling week and used to measure pH, temperature (TEMP), conductivity (COND; µS/cm), turbidity (TURB; NTU), and dissolved oxygen (DO; mg/L) at each station. TURB readings were measured in triplicate with a HACH® 2199Q turbidimeter, and a BOD bottle was filled with Hach chemicals and analyzed for DO according to the Winkler method to confirm accuracy of YSI values. All grab samples and measurements were taken from mid-depth against the current to ensure the sample is thoroughly mixed (Barton, 1977; Shelton, 1997; Poor & McDonnell, 2007).

A longitudinal survey was completed during the first week of July to observe turbidity changes from the Innisfil Creek confluence to the mouth at Wasaga Beach. A sonde (YSI 600OMS V2) with an optical turbidity and conductivity sensor was calibrated and towed down the river by canoe, and set to take simultaneous measurements and GPS coordinates at 60-second intervals. The sonde was fastened to the canoe to ensure measurements were taken at the same depth and to prevent rocks or large debris from damaging the sensor. Escherichia coli (E. coli) samples were also collected during the longitudinal survey in sterile Whirl-Pak® bags. Samples were collected at all 15 monitoring stations. We used Coliplate kits from Bluewater Biosciences to determine the most probable number of colony forming units at each sampling location.

Continuous monitoring stations were set up from June until the end of October. At each station, loggers (Onset HOBO U26) were deployed 50 cm from the sediment in protective, water penetrable encasements in the line of current. DO and TEMP measurements were recorded every hour and were left submerged in place for one month at a time. At the end of each month, the data were downloaded and the loggers were recalibrated.

Sample Processing

Unless otherwise indicated, all analyses were performed in triplicate for each variable. TP concentrations were determined with the molybdenum blue method (Murphy & Riley, 1962) following potassium persulfate digestion in an autoclave for 50 minutes (120°C, 15 psi). Absorbance values were read with a Genesys 10 UV Spectrophotometer and

final phosphorus concentrations were calculated with a standard curve. TN and TNN samples were also processed in the laboratory and read in a DR 2800 Spectrophotometer following the HACH® TNT 826 and cadmium reduction methods, respectively. Samples collected for Cl- were titrated following the mercuric nitrate method (HACH method 8206). A HACH® DR 850 colorimeter was used to read TAN and COL in the field according to HACH® methods 8155 and 8025 respectively.

Known aliquots of river water was filtered through GC filters (0.45 µm) and subsequently used to calculate concentrations of TSS and CHL. All filters used for TSS were pre-weighed before samples were filtered. Filters were then folded in half and kept in small plastic petri plates and placed in a freezer. When we were ready to process the TSS samples, filters were retrieved from the freezer and placed on a crucible of known weight to be dried in the oven for 1h at 100°C; subsequently, they were placed in a dessicator for an additional hour, and then weighed. Concentrations of total organic suspended solids (TOSS) were determined by burning the dried filter in a muffle furnace for 1 h at 550°C, placing it in a dessicator for an additional hour, and then weighed again. Filters for CHL determination were folded, then wrapped in aluminum foil and placed in a freezer until they were processed. CHL filters were extracted in 90% reagent grade acetone in a freezer over a 24 h period. Following extraction, samples were acidified with hydrochloric acid (0.1 N), and fluorescence was read with a Turners Design Trilogy Fluorometer.

Data Analysis

Statistical analyses were conducted with JMP 11 software (SAS Institute Inc., Toronto, ON, Canada). We compared station means of all water quality parameters across sampling months (June – September) to determine temporal trends (one-way ANOVA; Tukey-Kramer HSD). We also determined mean monthly trends and identified problem areas in the Nottawasaga River for all water quality variables using similar statistical analyses. A multivariate pairwise analysis was performed to determine significant correlations between all possible combinations of water quality parameters.

Phytoplankton sampling and analyses in the Nottawasga River

On a monthly basis, we used a van Dorn sampler to collect samples from the middle of the water column at a deep spot within the station (to avoid contaminating the sample with sediment). Aliquots were preserved for phytoplankton analysis (Qorpak quartz bottles) and preserved immediately with Lugol's iodine solution. We analyzed samples using standard microscopic techniques (i.e. EVOS XL inverted LCD microscope equipped with a Phycotech Nannoplankton chamber) to identify phytoplankton to the lowest practical taxonomic level.

Periphyton accrual experiments in tributaries of the NRW

We identified suitable sites for periphytic algal rod deployment using digital orthophotos of the study area (Muskoka and Simcoe County Orthophotos, 2008) in a

Geographic Information System (ArcGIS 10.3). We strategically selected 6 monitoring sites in 1st or 2nd order streams, 2 of which drained exclusively corn crop agricultural land, 2 exclusively drained soy bean crop agricultural land and 2 exclusively drained cattle pasture. We also selected two sites each that drained the upper, middle and lower sections of the Nottawasaga River. All locations were field validated to ensure that there would be sufficient base flow throughout the summer. The artificial substrate were ¼-inch diameter acrylic rods (the type used as curtain rods for venetian blinds), and we inserted them into the stream substrate in a grid pattern (3-5 evenly spaced rods with a minimum distance of 50 cm between rods to ensure periphyton colonizing them would not interact during the incubation period). To ensure that algae would be able to colonize all surfaces of each rod, we used 90% isopropanol to clean them before the installation (McNair & Chow-Fraser, 2003). We removed terrestrial and aquatic vegetation from the surrounding areas to minimize shading effects at each site. The rods were left to grow for four weeks in each of July and August.

Prior to installation of the acrylic rods, water samples were collected at the site for determination of TAN. An YSI 6920 V2 sonde was also used to take readings of DO, TURB, COND and TEMP. The same suite of parameters were measured again at the end of the incubation period before the acrylic rods were taken down. Since we carried out two consecutive sets of incubation periods, water quality was only monitored three times (i.e. before rods were installed in July and in August, and again in September, before the second incubation period was terminated)

At the end of the incubation period, a known area of periphyton growth was scraped from rods and suspended in a known volume of water. This solution was filtered through pre-weighed GC filters (0.45 mm). These filters were then desiccated for 24 hours at 60°C. Filters were then baked for 2 hours at 550 °C in a Fisher Scientific Thermolyne muffle furnace, and weighed for ash free dry mass (AFDM). Some of the samples were extracted for CHL in 90% reagent grade acetone at room temperature for 24 hours. Following extraction, samples were acidified with hydrochloric acid (1M) , and absorbance was read at 665 nm with a Genesys 10S UV-Vis spectrophotometer. Part of the sample was also preserved in Lugol's iodine and used later to for identification and enumeration of periphytic algae (see method above for phytoplankton analyses).

Interaction between Giffin Drain and the Minesing wetland/Nottawasga River

Study Area and Methodology

Serving several surrounding farms, the Giffin Drain starts at the intersection of Glengarry Landing Rd S and Ronald Rd outside the town of Minesing, Simcoe County, Ontario (Figure 5). The drain travels westward for 187 m between two more farms before entering the Minesing Wetlands, whereupon it runs another 840 m before meeting the larger Downey Drain. Together, these drains run another 800 m to the Nottawasaga River. Within the Minesing, the Giffin Drain allows agricultural runoff to travel through 225 m of mixed cedar swamp and then 615 m of perennially-wet marsh. Through the swamp, the drain averages 3 m wide with an average depth of 60 cm. The drain widens and deepens

through the marsh area to an average of 6.5 m wide to 1.1 m deep during baseflow conditions. The timing of ditch construction is unknown, but the material excavated to create the ditch was deposited on either side of the ditch, forming berms that rise 68 cm above the surrounding marsh area.

Figure 5: Illustrated aerial photograph of the study area, showing the Giffin Drain at the north end of the Minesing Wetlands and surrounding features.

We implemented a network of water monitoring wells and surface-water sampling stations to characterize the extent of physical interaction of drainage-ditch water with the surrounding wetland and to quantify any associated water-quality changes. We visited the site 11 times between mid May to end of August in 2014. On each trip, we measured water- velocity along the ditch and collected water samples at 22 locations in the ditch and wetland (Figure 6) for determination of total phosphorus, soluble reactive phosphorus, nitrate- nitrogen, and ammonia-nitrogen, and other relevant data (conductivity, temperature, and pH) (methods used have already been described above). Standard operation and QA/QC procedures for the nutrient analysis were followed throughout. Once water levels receded to the point that allowed proper installation of the wells, eight water level loggers were deployed adjacent to the drainage ditch in the marsh area of the wetland. Logger data were compared with water depths in ditches to determine lateral flow potential. The ditch and surrounding areas were then surveyed to determine elevation changes.

Figure 6: Study area map indicating locations of water sampling stations and water monitoring wells.

RESULTS

Results of the monthly variation of water quality in the Nottawasaga River

We found that water quality across the Nottawasaga River varied between sampling months (June – September), with significant monthly differences observed for TN, TP, CHL, COL, Cl-, DO, and TEMP (Table 3; ANOVA, Tukey-Kramer HSD). TN was significantly higher in June (2.28 mg/L), and significantly lower in September (1.71 mg/L; Figure 7). TP was significantly higher in July (49.6 µg/L), and significantly lower in September (18.7 µg/L; Figure 8). Following a similar trend, CHL was significantly higher in July (3.98 µg/L) and August (3.27 µg/L) and was significantly lower at the beginning of the summer in June (1.95 µg/L; Figure 9). By comparison, DO was significantly lowest in July (6.73 mg/L), and highest in June (7.87) and August (7.78; Figure 10). July was significantly warmer (21.5 °C) compared to the other three months (Figure 11). September (33.5 mg/L) and August (31.7 mg/L) yielded significantly higher Cl- concentrations, while June produced significantly lower results (21.3 mg/L; Figure 12). COL was significantly higher in September (91 Pt-Co), while no significant differences were observed in previously sampled months (Figure 13).

Month 3.0 June July August 2.5 September

2.0

1.5 TN (mg/L)

1.0

0.5

0.0 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Station Figure 7: Monthly variation (June – September) in TN concentrations at each monitoring station. The red line illustrates the suggested NAESI standard (1.06 mg/L) for southern Ontario streams. Almost all values lie within the eutrophic status range (>1.5 mg/L) for streams.

Month 70 June July August 60 September

40 g/L) µ

TP ( 30

0 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Station Figure 8: Monthly variation (June – September) in TP concentrations at each monitoring station. The red line illustrates the PWQO (30 µg/L) for Ontario streams.

Month 8 June July 7 August September

5 g/L) µ 4 CHL ( 3

0 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Station Figure 9: Monthly variation (June – September) in CHL concentrations at each monitoring station. All values lie within the oligotrophic status range (<10 µg/L) for streams.

Table 3: Mean water quality variables among stations during the summer months. Values that share the same letter are statistically homogeneous (α = 0.05; Tukey-Kramer HSD).

Variable Month Mean SE Statistically Significant Groups TN June 2.28 ±0.071 A (mg/L) July 2.08 ±0.091 A B August 1.83 ±0.069 B C September 1.71 ±0.084 C TNN July 0.15 ±0.040 A (mg/L) June 0.079 ±0.016 A August 0.070 ±0.024 A September 0.058 ±0.020 A TAN September 0.034 ±0.0074 A (mg/L) July 0.033 ±0.0067 A August 0.030 ±0.0060 A June 0.028 ±0.0072 A TP July 49.6 ±2.68 A (µg/L) August 32.4 ±2.78 B June 31.3 ±3.39 B September 18.7 ±2.98 C CHL July 3.98 ±0.40 A (µg/L) August 3.27 ±0.42 A September 3.13 ±0.28 A B June 1.95 ±0.14 B COL September 91 ±9.37 A (Pt-Co) June 60 ±10.5 B July 46 ±5.25 B August 43 ±5.80 B TSS September 15.2 ±2.21 A (mg/L) July 15.0 ±1.62 A June 14.4 ±1.69 A August 12.5 ±2.02 A TOSS September 4.93 ±0.34 A (mg/L) June 4.91 ±0.36 A August 4.69 ±0.32 A July 4.49 ±0.37 A TURB September 18.5 ±3.41 A (NTU) August 15.6 ±2.70 A July 15.1 ±1.66 A June 12.3 ±1.13 A Cl- September 33.5 ±2.21 A (mg/L) August 31.7 ±1.59 A July 29.5 ±2.51 A B June 21.3 ±3.14 B COND June 569 ±10.6 A (µS/cm) July 559 ±11.7 A September 550 ±6.23 A August 534 ±10.3 A DO August 7.87 ±0.12 A (mg/L) June 7.78 ±0.24 A September 7.42 ±0.19 A B July 6.73 ±0.34 B pH August 8.12 ±0.031 A June 8.02 ±0.041 A July 7.99 ±0.072 A September 7.99 ±0.047 A TEMP July 21.5 ±0.48 A (°C) August 19.6 ±0.30 B September 19.2 ±0.31 B June 19.1 ±0.28 B

Month 10 June July August September

6 DO (mg/L)

2 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Station Figure 10: Monthly variation (June – September) in DO concentrations at each monitoring station. The red line illustrates the suggested PWQO (>4 mg/L) for Ontario streams.

Month 25 June July August September

20 TEMP (°C)

15 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Station Figure 11: Monthly variation (June – September) in TEMP at each monitoring station.

Month 60 June July August 50 September

30 Cl- (mg/L)

0 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Station Figure 12: Monthly variation (June – September) in Cl- concentrations at each monitoring station.

Month June July August 150 September

100 COL (Pt-Co)

0 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Station Figure 13: Monthly variation (June – September) in COL measurements at each monitoring station.

Our results confirm that loading of nutrient and sediment is the most serious water- quality problem in the Nottawasaga River (Chow-Fraser, 2006; Brown et al., 2011). We calculated monthly means for each water-quality parameter to determine seasonal trends at each monitoring station (Table 4). We then compared these monthly means to published water quality targets and nutrient guidelines to evaluate the health and trophic status of the Nottawasaga River. We could not make comparisons for some variables that did not have a pre-determined provincial or federal water-quality target. Provincial Water Quality Objectives (PWQO) exist for TAN, TP, E. coli, DO and pH, while the Canadian Environmental Quality Guidelines (CEQG) exist for TNN.

Almost all monitoring stations exceeded the PWQO for TP (30 μg/L; Table 4), TAN (0.02 mg/L; Table 4), and E. coli (100 CFU/100 mL; Figure 14). PWQOs for TP was exceeded at all stations except for stations 01, 04 and 07. TAN was exceeded at every station, and E. coli was exceeded at stations 01, 02, 03, 06, 07, 13 and 14.

Table 4: Summary of mean monthly water quality parameters at all 15 monitoring stations. Numbers that are bolded indicate that values have exceeded the provincial or federal water quality target (PWQO, CEQG, or NAESI). Means with the same letter(s) are statistically homogeneous (α = 0.05; Tukey-Kramer HSD).

Statistically Significant Variable WQ Target Station Mean SE Groups TN 1.06 04 2.38 ±0.048 A (mg/L) (NAESI) 05 2.29 ±0.17 A B 07 2.22 ±0.17 A B C 08 2.20 ±0.14 A B C 06 2.17 ±0.17 A B C 10 2.04 ±0.19 A B C 15 1.91 ±0.19 A B C 01 1.90 ±0.19 A B C 11 1.90 ±0.084 A B C 09 1.89 ±0.16 A B C 02 1.88 ±0.27 A B C 14 1.78 ±0.19 B C 12 1.73 ±0.16 B C 13 1.70 ±0.17 C 03 1.63 ±0.16 C TNN 3.0 04 0.24 ±0.099 A (mg/L) (CEQG) 06 0.20 ±0.10 A 08 0.15 ±0.082 A 07 0.12 ±0.044 A 14 0.093 ±0.042 A 05 0.081 ±0.051 A 11 0.080 ±0.018 A 01 0.061 ±0.028 A 13 0.059 ±0.010 A 10 0.057 ±0.020 A 03 0.043 ±0.015 A

Statistically Significant Variable WQ Target Station Mean SE Groups 02 0.043 ±0.0056 A 12 0.042 ±0.017 A 09 0.036 ±0.019 A 15 0.028 ±0.0099 A TAN 0.02 14 0.080 ±0.0074 A (mg/L) (PWQO) 02 0.050 ±0.0089 A B 15 0.043 ±0.015 A B 12 0.040 ±0.016 A B 13 0.035 ±0.016 A B 10 0.030 ±0.014 A B 05 0.029 ±0.0083 A B 04 0.029 ±0.013 A B 06 0.029 ±0.014 A B 08 0.026 ±0.010 A B 11 0.021 ±0.0080 A B 03 0.020 ±0.012 B 07 0.016 ±0.0072 B 09 0.015 ±0.0046 B 01 0.010 ±0.0029 B TP 30, 26 02 48.2 ±6.76 A (µg/L) (PWQO, 13 42.1 ±5.47 A NAESI) 10 39.8 ±7.97 A 12 37.3 ±9.54 A 11 34.4 ±11.4 A B 06 33.9 ±7.90 A B 09 33.4 ±8.96 A B 14 32.7 ±7.51 A B 15 31.6 ±10.5 A B 03 31.1 ±4.41 A B 05 30.2 ±7.88 A B 08 30.2 ±6.64 A B 04 29.7 ±7.03 A B 07 28.0 ±7.96 A B 01 12.2 ±4.89 B CHL -- 02 4.43 ±0.42 A (µg/L) 13 3.92 ±1.02 A 05 3.73 ±1.29 A 15 3.57 ±0.87 A 14 3.39 ±0.91 A 07 3.33 ±0.73 A 08 3.09 ±0.55 A 03 2.90 ±1.01 A 09 2.85 ±0.59 A 06 2.80 ±0.57 A 04 2.75 ±0.53 A 10 2.70 ±0.29 A 11 2.63 ±0.40 A 12 2.61 ±0.31 A

Statistically Significant Variable WQ Target Station Mean SE Groups 01 1.54 ±0.65 A COL -- 11 95 ±26 A (Pt-Co) 02 84 ±15 A 03 83 ±21 A 12 74 ±28 A 07 73 ±14 A 13 66 ±14 A 15 65 ±8 A 04 62 ±19 A 01 57 ±22 A 10 52 ±12 A 14 48 ±13 A 09 47 ±8 A 08 36 ±25 A 05 31 ±5 A 06 29 ±7 A TSS 3.6 02 29.1 ±5.50 A (mg/L) (NAESI) 10 18.7 ±2.47 A B 12 17.4 ±3.79 A B 09 16.2 ±3.33 A B 06 15.9 ±1.90 A B 11 15.6 ±3.57 A B 03 15.1 ±4.80 A B 05 13.7 ±1.15 B 07 13.6 ±0.84 B 13 13.2 ±0.23 B 08 12.2 ±1.06 B 04 10.9 ±2.24 B 14 10.0 ±1.11 B 01 6.94 ±2.35 B 15 5.51 ±1.12 B TOSS -- 02 6.64 ±0.44 A (mg/L) 06 5.49 ±0.44 A B 12 5.48 ±0.24 A B 10 5.47 ±0.44 A B 07 5.31 ±0.072 A B 13 5.23 ±0.60 A B 11 4.91 ±0.44 A B 09 4.89 ±0.62 A B 03 4.88 ±1.15 A B 08 4.81 ±0.23 A B 05 4.36 ±0.42 A B 04 4.03 ±0.45 A B 14 3.75 ±0.44 B 15 3.14 ±0.29 B 01 2.96 ±0.83 B TURB 6.1 02 41.4 ±9.12 A (NTU) (NAESI) 06 19.3 ±3.38 B

Statistically Significant Variable WQ Target Station Mean SE Groups 05 16.7 ±1.70 B 03 15.9 ±4.49 B 13 15.6 ±1.20 B 12 15.5 ±1.40 B 07 15.1 ±1.04 B 11 13.8 ±1.54 B 09 13.3 ±1.22 B 08 12.5 ±1.15 B 04 12.3 ±1.81 B 10 11.6 ±0.55 B 14 11.6 ±0.71 B 01 8.28 ±2.88 B 15 7.59 ±0.98 B E. coli 100 Lower 612 ±272 A (CFU/100 mL) (PWQO) Nottawasa ga (11-15) Middle 327 ±248 A Nottawasa ga (1-6) Minesing 113 ±304 A (7-10) Cl- -- 02 53.8 ±2.20 A (mg/L) 05 39.8 ±6.95 B 04 37.6 ±1.42 B C 12 27.2 ±3.16 C D 07 27.0 ±3.54 C D 06 26.9 ±3.89 C D 08 26.6 ±3.96 C D 15 26.6 ±1.99 C D 10 26.2 ±2.46 D 11 25.5 ±3.23 D 09 25.2 ±2.57 D 03 25.0 ±4.47 D 14 25.0 ±2.87 D 13 24.3 ±2.40 D 01 18.4 ±3.17 D COND -- 02 668 ±19 A (µS/cm) 04 582 ±10 B 05 579 ±10 B C 03 563 ±16 B C D 08 547 ±5 B C D E 11 544 ±6 C D E 07 543 ±6 C D E 06 543 ±10 C D E 12 542 ±6 C D E 15 540 ±14 D E 10 538 ±6 D E 09 532 ±6 D E

Statistically Significant Variable WQ Target Station Mean SE Groups 14 531 ±11 D E 13 531 ±11 D E 01 517 ±7 E DO > 4 (PWQO) 03 8.44 ±0.29 A (mg/L) 04 8.34 ±0.38 A B 02 8.05 ±0.27 A B C 01 8.03 ±0.15 A B C 06 7.96 ±0.15 A B C 05 7.90 ±0.20 A B C 07 7.79 ±0.27 A B C 08 7.75 ±0.28 A B C 09 7.64 ±0.39 A B C D 15 7.31 ±0.55 A B C D 14 6.85 ±0.47 B C D 11 6.58 ±0.36 C D 12 6.54 ±0.39 C D 10 6.51 ±0.56 C D 13 6.11 ±0.74 D pH 04 8.24 ±0.037 A 6.5 - 8.5 01 8.23 ±0.021 A (PWQO) 08 8.18 ±0.017 A 05 8.18 ±0.036 A 07 8.18 ±0.014 A 03 8.18 ±0.028 A 06 8.14 ±0.046 A 02 8.09 ±0.029 A 09 8.04 ±0.044 A B 11 7.87 ±0.059 B C 12 7.86 ±0.045 B C 15 7.85 ±0.083 B C 10 7.80 ±0.076 C 14 7.80 ±0.082 C 13 7.78 ±0.069 C TEMP 14 21.8 ±0.87 A (°C) 15 21.6 ±0.89 A B 13 21.3 ±0.73 A B C 05 20.8 ±0.45 A B C 04 20.1 ±0.68 A B C 06 19.9 ±0.41 A B C 02 19.7 ±1.12 A B C 08 19.6 ±0.80 A B C 07 19.4 ±0.78 A B C 11 19.2 ±0.079 A B C 09 19.2 ±0.43 A B C 12 19.1 ±0.10 B C 01 18.9 ±1.31 C 03 18.7 ±1.08 C 10 18.7 ±0.27 C

July

2400

2000

1600

1200 E. coli (CFU/100 mL) 800

400

0 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 Station

Figure 14: Summary of E. coli CFU counts at each monitoring station sampled during the month of July. The red line illustrates the suggested PWQO (<100 CFU/100 mL) for recreational water and safe swimming.

Non-regulatory performance standards have been developed for the National Agri- Environmental Standards Initiative (NAESI) for TN (1.06 mg/L), TP (26 µg/L), TSS (3.6 mg/L), and TURB (6.1 NTU) in southern Ontario (Culp et al., 2009; Chambers et al., 2011). These standards indicate nutrient and sediment concentrations that protect and sustain ecological integrity and health of streams in agricultural settings. All 15 monitoring stations in the Nottawasaga River exceed the NAESI standards for TN, TP, TSS, and TURB (Table 4).

Smith et al. (1999) summarized nutrient and CHL concentrations for different trophic states in stream environments (Table 5). The Nottawasaga River is unique in that it can be classified into three different trophic states depending on the indicator variable. Consequently, TN levels indicate that the Nottawasga River is eutrophic (>1.5 mg/L) across all 15 monitoring stations, while low planktonic CHL concentrations throughout the river suggest that it is oligotrophic (<10µg/L). By comparison, TP concentrations were inconsistent, with some stations (01, 04 and 07) indicating oligotrophic conditions (<25 µg/L), while higher concentrations at the remaining 12 stations indicated a mesotrophic state (25-75µg/L).

Table 5: Trophic status for different nutrient levels in stream ecosystems. Table modified from Smith et al. (1999). Bolded values indicate the ranges that exist within the Nottawasaga River.

TN TP CHL Trophic Status (mg/L) (µg/L) (µg/L) Oligotrophic < 0.7 < 25 < 10

Mesotrophic 0.7 – 1.5 25 – 75 10 – 30

Eutrophic > 1.5 > 75 > 30

We created a correlation matrix for all parameters and found that 24 correlations were statistically significant (Table 6). The strongest correlations exist between Cl- and COND (0.961), pH and DO (0.921), as well as TOSS and TSS (0.912). Other noteworthy significant correlations exist between E. coli and TAN (0.768), TSS and TP (0.739), TN and TNN (0.737), and TP and TURB (0.633). Our results indicate that inorganic matter constitutes the majority of TSS at all stations, with the exception of station 15, most influenced by water of Nottawasga Bay (Figure 15). TSS and TURB were highly correlated (0.864), suggesting that inorganic sediments are the leading cause of high TURB in the Nottawasaga River.

35 Total Organic 30 Total Inorganic 25

TSS(mg/L) 15

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Station

Figure 15: Relative mean monthly contributions of organic (grey) and inorganic (black) constituents in TSS at each monitoring station (01-15).

Table 6: Pairwise correlations between mean monthly water quality variables (MVA). Of the 105 pairwise correlations, only statistically significant correlations (bolded) are presented.

Variable by Variable Correlation P-value TN pH 0.550 0.0335 TN TNN 0.737 0.0017 TAN pH -0.532 0.0413 TAN TEMP 0.672 0.0061 TP pH -0.519 0.0475 TP TURB 0.633 0.0114 CHL COND 0.590 0.0207 CHL TEMP 0.589 0.0209 CHL TURB 0.592 0.0202 CHL TP 0.690 0.0044 CHL Cl- 0.642 0.0099 TSS COND 0.697 0.0039 TSS TURB 0.864 <0.0001 TSS TP 0.739 0.0017 TSS Cl- 0.640 0.0101 TOSS TURB 0.745 0.0014 TOSS TP 0.764 0.0009 TOSS TSS 0.912 <0.0001 TURB COND 0.873 <0.0001 E. coli TAN 0.768 0.0008 Cl- COND 0.961 <0.0001 Cl- TURB 0.811 0.0002 Cl- TP 0.519 0.0476 pH DO 0.921 <0.0001

Further statistical analyses allowed us to identify the stations that have impaired water quality (Table 7; ANOVA, Tukey-Kramer HSD). These include stations 02, 04, 05, 10 12, 13 and 14. Overall, station 02 (Innisfil) was highest for TSS, TOSS and TURB, and confirm findings from previous studies. TN was significantly highest at station 04 while TP was significantly higher at stations 02, 10, 12 and 13. Stations where pH was significantly lower include stations 10, 13, and 14. DO was significantly lowest at station 13, and TEMP, TAN, and E. coli were all significantly higher at station 14. COND and Cl- were both significantly higher at stations 02, 04, and 05. Presented in order from areas of greatest concern, the major problem areas revealed from this study appear to be station 02 (Innisfil Creek), 14 (near Knox Rd in the town of Wasaga Beach), 13 (near Jack’s Lake), and 10 (in Minesing Wetlands after Willow Creek).

Table 7: Summary of problem stations in the Nottawasaga River. “X” indicates significantly higher (TN, TAN, TP, TSS, TOSS, TURB, E. coli, Cl-, COND, TEMP) and lower (DO, pH) monthly means compared across all 15 stations (ANOVA; Tukey- Kramer HSD).

Station Middle Reach Minesing Lower Reach WQ Variable 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 TN X TAN X TP X X X X TSS X

TOSS X TURB X

E. coli X Cl- X X X COND X X X DO X pH X X X

TEMP X

Results of longitudinal survey of water quality in the Nottawasgaa River

The longitudinal survey successfully identified stretches of the Nottawasaga River that had high turbidity, as well as local point sources and areas of high sediment inputs (Figure 16). The most turbid section of the Nottawasaga stretches from Angus, through the Minesing Wetlands, and remains high until station 14 within the town of Wasaga Beach. At the river mouth near Wasaga Beach, turbidity levels decrease because of mixing that occurs with water from Nottawasaga Bay. Notable spikes in TURB were identified in the southern portion of the Minesing Wetlands before station 07 (Mad River breaches bank), at station 10 (after Willow Creek) and at station 12 (after Marl Creek).

Figure 16: Longitudinal map depicting TURB changes in the Nottawasaga River from the Innisfil Creek confluence to the mouth at Wasaga Beach. Green circles are low values, red are high.

In addition to TURB, the longitudinal survey also recorded changes in COND along the Nottawasaga River (Figure 17). The general trend reveals that COND begins high at station 03 near the Innisfil Creek confluence, and gradually decreases downstream. There is a spike in COND near station 04 in the middle section of the Nottawasaga River. This station is located near the Essa Fishing and Trailer Park, and is also the site with significantly higher TN, COND, and Cl- compared to all other stations in the middle Nottawasaga River reach. The decrease in COND observed within the Minesing Wetlands (denoted by a change in yellow to green, where the Mad River breaches the bank and flows into the Nottawasaga River early) corresponds with the spike in TURB recorded during the longitudinal survey (Figure 16).

Diurnal trends in temperature and dissolved oxygen

Continuous monitoring confirmed diurnal fluctuations of DO and TEMP at all four stations. There appeared to be sufficient DO concentrations (>4 mg/L) to support aquatic life in the Middle Nottawasaga River at station 03 (Innisfil Creek confluence) during June (Figure 18a). In the Lower Nottawasaga River, more specifically, within the Minesing Wetlands, DO concentrations decreased to anoxic levels (<0 mg/L) at station 07 in July (Figure 18b). We also monitored the river within the Minesing Wetlands at station 10 from August to the end of October, and did not find any problems with low DO concentrations (Figure 19). Due to sediment build up following storm flows, we were unable to record DO for the entire month of June at station 03, or station 10 in August. DO and TEMP were recorded continuously in Jack’s Lake (before station 13) from June to the end of October (Figure 20); this revealed that DO concentrations declined below the PQWO (4 mg/L) in both June and July, and were at near-hypoxic conditions (2 mg/L) very early in the morning on July 26. Due to equipment malfunction, we were unable to capture continuous DO measurements in August.

Monthly changes in phytoplankton assemblages in the Nottawasaga River

The relative abundance of different taxonomic groups of phytoplankton varied throughout the four summer months. In June, most of the sites were dominated by Navicula spp, which is a species of diatom. The notable exception is Station 6, which is influenced by good quality river of the Pine River (Figure 21) In July and August, the various taxonomic groups were more evenly distributed across the stations, including green algae and cryptomonads (Figures 22 and 23). By September, another diatom species, Nitzschia spp. was dominant (Figure 24). Many Nitzschia spp. are known to be indicators of nutrient enrichment, and their dominance during this sampling period may indicate water quality degradation. There were, however, no significant relationships between site and dominant genera across any of the months (p-value>0.05). Results of this monthly monitoring indicated that the Nottawasaga River is dominated by pollution-dependent or pollution- tolerant species. Three diatom genera, Navicula, Nitzschia and Gomphonema. N. acicularis and G. parvulum, were present in high numbers and these tend to dominate in nutrient-rich waters. We point out, however, that some of the species present are not indicators of degraded water quality. The level of taxonomic detail required to make inferences about water quality conditions is difficult to obtain with such a synoptic monitoring program.

Figure 17: Longitudinal map depicting changes in COND along the Nottawasaga River from the Innisfil Creek confluence to the mouth at Wasaga Beach. Green circles are low values, red are high.

We can calculate planktonic algal biomass (fresh weight) by estimating biovolume for algae by approximating them to geometric shapes and assuming that the specific density of water is 1. Biomass increased throughout the sampling season from June to September across the Nottawasaga River (Figure 25). There was high variability in phytoplankton biomass both among sites and sampling dates. As well, there was no apparent relationship between the biomass and water quality/ nutrient variables, suggesting that there may be other factors controlling algal biomass. The Minesing Wetlands did not appear to have an effect on algal community structure or dominance.

Periphyton accrual experiments

We carried out experiments to determine the effect of agricultural runoff on the growth of periphyton on artificial substrates in 1st and 2nd order tributaries that drained three different types of land-use practices in the NRW. A large amount of variation was observed in water quality conditions across the 6 sites during the July and August sampling periods, and there were no significant differences among the three land-use practices for any of the water-quality parameters (p-values >0.05) (Table 8). Due to the very small sample size, we cannot make any conclusions regarding the effects of agricultural practices on water quality.

Periphytic algae obtained from the July and August experiments were analyzed for Chlorophyll a biomass (Figure 26). These did not differ significantly across agricultural practices or between months (p-values >0.05). Samples were also analyzed for ash free dry mass for the two sets of experiments and again, we found no significant effect of land-use practices (p-values >0.05) or significant differences between time periods (Figure 27). These results do not show that periphytic algae are affected by land-use practices, but given the small sample size, no conclusion should be made. It is noteworthy that data obtained at Site 6 (Corn row crops in the lower portion of the watershed) consistently exceeded the Provincial Water Quality Objective (PWQO) for TAN (0.02 mg/L).

25 10 24 23 22 21 9 20 19 DO (mg/L)

18 TEMP (°C) 17 8 16 15 14 13 7 12 05 07 09 11 13 15 17 19 21 23 25 27 29 01 03 06-2014 07-2014 Date (dd-mm-yyyy) Left Scale: DO TEMP Right Scale: b)

8 23

7 22 6

5 21

4 20 DO (mg/L) TEMP (°C) 3 19 2

1 18

0 17 07-03 07-07 07-11 07-15 07-19 07-23 07-27 07-31 08-04 2014 Date (mm-dd) Left Scale: DO TEMP Right Scale:

Figure 18: Diurnal fluctuations in DO (black) and TEMP (blue) at a) station 03 near the Innisfil Creek confluence throughout the month of June and b) station 07 within the Minesing Wetlands throughout the month of July. The red line indicates the PWQO (>4 mg/L) for DO concentrations.

8.5 20

19 8 DO (mg/L) 18 TEMP (°C)

7.5 17

16 7 07 09 11 13 15 17 19 21 23 25 27 29 31 02 04 06 08-2014 09-2014 Date (dd-mm-yyyy) b)

20 10

9 16

8 14 DO (mg/L) TEMP (°C)

7 12

6 10

8 5 09-06 09-12 09-18 09-24 09-30 10-06 10-12 10-18 10-24 10-30 2014 Date (mm-dd) Left Scale: DO TEMP Right Scale:

Figure 19: Diurnal fluctuations in DO (black) and TEMP (blue) at station 10 in the Minesing Wetlands throughout the months of a) August and b) September/October.

10 24 23 9 22 8 21 7 20 DO (mg/L) 19 TEMP (°C) 6 18 5 17 4 16

06-05 06-09 06-13 06-17 06-21 06-25 06-29 07-03 2014 Date (mm-dd) b) 24 9 23 8 22 7 21 6 20 DO (mg/L) 5 19 TEMP (°C) 4 18 17 3 16 07-03 07-07 07-11 07-15 07-19 07-23 07-27 07-31 08-04 2014 Date (mm-dd) c)

10 20

9 18

8 16

7 14 DO (mg/L) 12 TEMP (°C) 6 10 5 8 4 6 09-04 09-08 09-12 09-16 09-20 09-24 09-28 10-02 10-06 10-10 10-14 10-18 10-22 10-26 10-30 2014 Date (mm-dd) Left Scale: DO

Right Scale: TEMP

Figure 20: Diurnal fluctuations in DO (black) and TEMP (blue) in Jack’s Lake throughout the months of a) June b) July and c) September/October. The red line indicates the PWQO (>4 mg/L) for DO concentrations.

100.0

90.0

80.0

70.0

60.0

50.0

40.0 % abundance 30.0

20.0

10.0

0.0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Site Achnanthes Achnanthidium Amphora Biremis Brachysira Cavinula Chroococcus Cocconeis Coelastrum Cryptomonas Cymbella Desmodesmus Diatoma Didymocystis Encyonema Epithemia Eucapsis Euglenoid Fragilaria Fragilariforma Frustulia Geissleria Gleocapsa Gomphonema Gyrosigma Kirchneriella Kobayasiella Meridion Monoraphidium Navicula Nitzschia Scenedesmus Surirella Synedra Chlorophyceae

Figure 21: Relative abundance of phytoplankton genera in samples collected between June 2 to 6, 2014. Except for Station 6, the diamtom Navicula is the most dominant taxon genus at these stations.

100.0

90.0

80.0

70.0

60.0

50.0 % abundacne

40.0

30.0

20.0

10.0

0.0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Site Achnanthes Achnanthidium Amphora Biremis Brachysira

Cavinula Chroococcus Cocconeis Coelastrum Cryptomonas

Cymbella Desmodesmus Diatoma Didymocystis Encyonema

Epithemia Eucapsis Euglenoid Fragilaria Fragilariforma

Frustulia Geissleria Gleocapsa Gomphonema Gyrosigma

Kirchneriella Kobayasiella Meridion Monoraphidium Navicula

Nitzschia Scenedesmus Surirella Synedra Chlorophyceae

Figure 22: Relative abundance of phytoplankton genera in samples collected between July 1 to 5, 2014. The dominant taxa at these sites during July tended to be dominated by Cryptomonas spp.

100.0

90.0

80.0

70.0

60.0

50.0

40.0 % abundance 30.0

20.0

10.0

Figure 23: Relative abundance of phytoplankton genera in samples collected between August 4 to 8, 2014. The dominant taxa at these sites during August were green algae and Cryptomonas spp.

100.0

90.0

80.0

70.0

60.0

50.0

40.0 % Abundance 30.0

20.0

10.0

0.0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Site

Achnanthes Achnanthidium Amphora Biremis Brachysira Cavinula Chroococcus Cocconeis Coelastrum Cryptomonas Cymbella Desmodesmus Diatoma Didymocystis Encyonema Epithemia Eucapsis Euglenoid Fragilaria Fragilariforma Frustulia Geissleria Gleocapsa Gomphonema Gyrosigma Kirchneriella Kobayasiella Meridion Monoraphidium Navicula Nitzschia Scenedesmus Surirella Synedra Chlorophyceae

Figure 24: Relative abundance of phytoplankton genera in samples collected between September 2 to 5, 2014. The dominant taxa at these sites during September were the diatom Nitzschia and Cryptomonas spp.

7 June

6 July

August 5 September ) 1 - Seasonal Mean 4

3 Biomass (mg· mL 2

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Site

Figure 25: Seasonal trends (June to September) in total phytoplankton biomass (based on biovolume estimation of preserved specimens using microscopic techniques) in samples taken at monthly intervals at the 15 stations in the Nottawasga River.

Table 8. Summary of water quality parameters associated with periphyton accrual experiments (4-weeks duration) conducted during July and August in 2014. Bolded values are above the Provincial Water Quality Objective (PWQO).

Site Upper portion Middle portion Lower portion Water quality (1) (2) (3) (4) (5) (6) Sampling Notes variable Pasture Soy Corn Pasture Soy Corn DO (mg/L) 9.67 9.53 4.78 3.6 7.04 7.59 Samples collected before COND (mS/cm) 611 758 420 1064 715 462 July rod 8.17 7.65 7.14 7.12 7.55 7.66 installation pH (Jul 3-7) 17.49 15.63 17.39 15.96 19.28 17.31 TEMP (Cᵒ) TURB (NTU) 2.55 0.89 6.50 11.46 2.75 11.90

TAN (mg/L) 0 0 0.01 0.08 0.02 0.29 DO (mg/L) 9.83 9.9 1.5 5.72 3.54 8.42 Samples collected after COND (mS/cm) 620 834 407 1215 758 548 July rod pH 8.11 7.65 7.04 7.29 7.75 7.77 installation and before August TEMP (Cᵒ) 20.39 15.56 14.46 15.1 16.18 16.87 deployment (Aug 4-8) TURB (NTU) 1.6 7.8 4.3 8.7 14.5 6.0

TAN (mg/L) 0 0.01 0.005 0.005 0.01 0.145

DO (mg/L) 8.78 8.7 0.71 3.29 2.23 7.57 Samples collected after COND (mS/cm) 575 808 395 1380 700 600 August deployment pH 7.81 7.52 6.80 7.20 7.53 7.30 (Sep 1-5) TEMP (Cᵒ) 17.59 15.26 15.00 15.53 17 16.71

TURB (NTU) 2.2 20.3 4.2 5.8 12.3 141.7

TAN (mg/L) 0.005 0.04 0.01 0.045 0.495 0.31

0.03 July

0.025 2) - 0.02

0.015

0.01 Chlorophyll a (µg·cm

0.005

0 1-Upper 2-Upper Soy 3-Middle Corn 4-Middle 5-Lower Soy 6-Lower Corn Pasture Pasture Site

Figure 26: Periphytic algal biomass as Chlorophyll a averaged from 3 replicates at each rod deployment site in tributaries of the Nottawasaga River over a 4-week incubation period during July and August

1.2000 July August 1.0000

0.8000

0.6000

0.4000 Ash free dry mass (mg)

0.2000

0.0000 1-Upper 2-Upper Soy 3-Middle Corn 4-Middle 5-Lower Soy 6-Lower Corn Pasture Pasture Site

Figure 27: Periphytic algal biomass as ash-free dry mass averaged from 3 replicates at each rod deployment site in tributaries (1st and 2nd order streams) of the Nottawasaga River over a 4-week incubation period during July and August

Interaction between Giffin Drain and the Minesing wetland/Nottawasga River

With the exception of the raised berms on either side of the drainage ditch there was less than 10 cm elevation change across the 1.01 km stretch of the Giffin Drain through the Minesing Wetlands. This resulted in a very low topographic, and hydraulic, gradient of 0.000099, or less than 0.01 %. The very gentle slope of the land greatly restricted flow through the ditch; most of the attempts to quantify water velocity proved unsuccessful and during baseflow conditions velocity was never detected above 0.5 cm s-1. A nominal average baseflow velocity of 0.25 cm s-1 was determined for the rate of flow of runoff from the surrounding agricultural areas in the Giffin Drain to the Nottawasaga River through the Minesing. This calculated average velocity suggests the residence time of water in the Giffin Drain is 4.7 days. Similar velocities were determined throughout the Downey-Giffin combined drain, adding an additional 3.7 days for agricultural runoff water to reside in the Minesing.

Two of the site visits were shortly after significant rain the previous days. On these two occasions velocity increased to on average 0.65 cm s-1, reducing residence time to 1.8 and 1.4 days through the Giffin and Downey-Giffin combined drains, respectively. Thus, it takes on average 8.4 and 3.2 days for agriculturally-derived water to travel from the start of the Giffin Drain to the Nottawasaga River during baseflow and stormflow conditions, respectively. The baseflow residence time in particular is quite high and affords increased opportunity for enhanced nutrient retention due to the long contact time with wetland plants and sediments.

Water levels in the marsh area were very harmonious, but for ease of comparison the marsh surrounding the drainage ditch was separated into five sections based on the location of the water level monitoring wells (Figure 28). Overall, water levels in the marsh increased with increasing proximity to the Downey Drain and Downey-Giffin Combined Drain (Figure 29). This was because the berms of the ditches prevented further down-gradient movement of the water in the marsh. The depth of water in the Giffin Drain as measured near its confluence with the Downey Drain was for much of the growing season very near the water level in Marsh Area E (Figure 28).

In most areas of the marsh and in the ditch, water levels were highest in late spring – very early summer. During this time period, water levels in both the marsh and the ditch increased soon after a rain event and with much greater magnitude than can be accounted for by rainfall alone. For example, the 46.8 mm of rain over 24 to 25 June resulted in an increase in water level within the down-gradient section of the marsh (Marsh Area E; Figure 28) of 23 cm (Figure 29). This suggests that the wetland is in hydraulic contact with the surrounding upland landscape, with rapid delivery of hill-slope water into the wetland. As the summer progressed however, this connection deteriorated. The 33.9 mm storm of 08 July increased the water level in Areas A, B, and C of the marsh by 7, 8, and 10 cm, respectively, a decrease as compared to just a few weeks earlier (Figure 29). Throughout July and early August, this disconnection persisted, and increases in water level in the marsh were of equal magnitude to rainfall depths.

Figure 28: Detailed map of the marsh portion of the Minesing surrounding the Giffin Drain, indicating sampling locations as in Figure 2 and the separation of the marsh into distinct areas.

Figure 29: Seasonal rainfall and water-level fluctuation in the marsh and Giffin Drainage Ditch. All values are above ground surface relative to their respective areas. Marsh locations refer to water monitoring well to the southeast of the Giffin Drain in each respective area.

The connection between the marsh and surrounding swamp and upland areas was restored during heavy rains in mid-August. A total of 86.2 mm of rain fell over a five-day period beginning 12 August. Unlike earlier in the growing season, though, this large volume of rain did not translate into an immediate increase in the water level in the marsh; rather, a time delay of 9 days was required for significant increase in marsh water level, over which time an additional 12.7 mm of rain fell (Figure 29). Water level in Marsh Area C increased from pre-storm levels of 4 cm (the shallowest water level during the summer) to 38 cm. While water level in Marsh Area E also increased, the response was very muted, with just a 24 cm increase compared to the 34 cm increase in Area C. The berms on both sides of the Giffin Drain were lower around the sampling location in Marsh Area C (Figure 3), and during higher levels, water from Marsh Areas A to C bypassed the down-gradient drainage toward Areas D and E and instead entered the Giffin Drain. As rain water flowing through the swamp and upland water travelled down-slope toward the marsh, water levels in the receiving marsh increased, up to the breakage point at the downslope end of Marsh Area C. From that point on, only some water was directed toward Marsh Areas D and E, resulting in less of an increase in water level in those locations, while the remainder of that water was diverted to the ditch. At this time the water level in the ditch was higher than that in the adjacent Marsh Area E.

The interactions between the Giffin Drain and the surrounding marsh of the Minesing Wetlands can be distinguished between the three stages of water level, corresponding to different periods of the growing season. Figure 30 depicts these three stages of water level. During high water levels in late spring/early summer, the ditch water level was equivalent to that in the marsh, producing zero hydraulic gradient in either direction (Figure 30a). Thus, during these periods water in the ditch has no physical mechanism to mix with marsh water and the ditch acts as a pipe carrying agricultural water to the Nottawasaga River. Most of the growing season is characterized by this equal-water level time period. The ditch water level drops below the surrounding marsh water level during the low water level period (Figure 5b). At this time there is a slight physical hydraulic gradient from water in the marsh to the drainage ditch through the berm; however, this gradient is very low and the lack of longitudinal (downgradient) movement of water prevents any significant flux of water through the berm. Following the large mid-August storm the water level in the ditch was raised relative to the Marsh Area E water level due to the increased flux of water from the access point at Marsh Area C (Figure 5c). During this time there was the possibility of dilution from Marsh Area C and recharge of ditch water into the berm toward Marsh Area E; however, as in the moderate water level period, the flux of water between the compartments was quite minimal.

Figure 30: Cross-section of the marsh at the downstream end of the Giffin Drain just before the confluence with the Downey Drain showing representative water levels in the marsh and ditch during periods of (a) high, (b) low and (c) low water levels. All elevations are referenced to the monitoring well in Marsh Area E to the southeast of the Giffin Drain.

Overall, because of the construction of the berms on either side of the Giffin Drain, there was minimal interaction of the ditch water with the surrounding wetland sediments and vegetation. Given this situation, any improvements in the quality of the agricultural runoff entering the Giffin Drain would remain inside the ditch itself. On the other hand, the fact that water resides in this ditch for an extended period of time, it may be possible to increase nutrient uptake and turnover within the ditch as the water moves slowly toward the Nottawasaga River.

Water Quality Improvement

Results of the sampling campaign indicated that there was indeed significant improvement in water travelling along the Giffin Drain on its way to the Nottawasaga River. Total phosphorus (TP), soluble reactive phosphorus (SRP), and nitrate (NO3) concentrations decreased substantially over the 1 km drain (Table 9). Most of this reduction in concentration took place through the first 400 m in the swamp. On the other

hand, ammonium (NH4) concentrations actually increased along the drain. Electrical conductivity (EC) does not show any clear trend.

Table 9: Seasonal averages of nutrients in select locations along the Giffin Drain (means ±SE). Station IDs are in order from start of drain as shown in Figure 28.

Distance from Field - + Station ID Edge TP SRP NO3 NH4 EC -1 -1 -1 -1 -1 (m) (µg P L ) (µg P L ) (µg N L ) (µg N L ) (µS cm ) Giffin Drain Start 0 407 (+/-112) 215 (+/-186) 1199 (+/-53) 46 (+/-19) 704 (+/-65) Swamp 1 187 378 (+/-136) 178 (+/-159) 979 (+/-74) 80 (+/-35) 678 (+/-87) Swamp 2 232 321 (+/-73) 163 (+/-85) 834 (+/-66) 88 (+/-41) 680 (+/-120) Swamp 3 282 342 (+/-101) 144 (+/-98) 728 (+/-52) 94 (+/-27) 650 (+/-77) Swamp 4 324 203 (+/-32) 93 (+/-29) 543 (+/-71) 96 (+/-36) 707 (+/-60) Swamp 5 368 139 (+/-24) 51 (+/-37) 432 (+/-39) 102 (+/-21) 685 (+/-73) Swamp 6 404 56 (+/-9) 15 (+/-8) 265 (+/-32) 107 (+/-19) 711 (+/-130) Marsh 1 506 51 (+/-7) 17 (+/-9) 15 (+/-1) 122 (+/-16) 675 (+/-143) Walton Drain 558 62 (+/-13) 20 (+/-10) 36 (+/-2) 72 (+/-30) 777 (+/-81) Marsh 2 621 52 (+/-6) 16 (+/-7) 29 (+/-29) 112 (+/-16) 754 (+/-111) Marsh 3 861 56 (+/-19) 27 (+/-23) 24 (+/-16) 92 (+/-10) 717 (+/-124) Giffin Ditch End 1012 47 (+/-5) 12 (+/-4) 21 (+/-3) 71 (+/-15) 672 (+/-128)

SRP comprised 53 % of TP at the start of the Giffin Drain, probably due to the higher levels associated with inorganic fertilizer application. By the time the water reached the end of the swamp, much of the SRP in the ditch water had been taken up and/or precipitated out, with a resultant increase in the proportion of organic and particulate P, even as TP levels were decreasing; consequently, SRP in the ditch water at the end of the swamp comprised approximately 30 % of TP. SRP as a function of TP continued to fluctuate through the marsh as new water entered the Giffin Ditch from the Walton Ditch, but by the end of the 1 km reach, the SRP constituted 26 % of TP. Average SRP concentrations at the end of the Giffin Drain had decreased to just 5 % of the level found at the start, from 215 to just 12 µg L-1, a significant removal of the most labile form of phosphorus. On the other hand, while TP reductions of ~85 % were observed along the ditch, concentrations were still above the provincial water quality objective of < 30 µg L-1 (Table 1). Thus, much of the observed SRP removal was attributed to conversion of SRP to other TP forms.

Nitrate levels decreased from over 1 mg L-1 to near detection limits, an overall decrease of ~ 98 %. Again, almost all of this decrease occurred within the first 400 of the swamp community. On the other hand, some of this NO3 appeared to be taken up into organic matter and remineralized into ammonium in the ditch water throughout the swamp, as NH4 concentrations doubled across this space. NH4 levels continued to increase until there was a slight dilution from the Walton Drain. The concentration of NH4 did decrease along the final 400 m of the ditch through the marsh, presumably due to uptake in concert

with the very low NO3 concentrations along this reach. Across all sampling locations along the Giffin Drain, NH4 levels exceeded the PWQO for ammonia.

The water in the Giffin Drain continued toward the Nottawasaga River after the confluence with the Downey Drain. Along the combined drain, SRP levels doubled, though with great variability (Table 10). Unfortunately TP values for this section of the ditch network, as well as for the marsh areas were unreliable for over half of the site sampling visits. As such all TP data have been removed due to a lack of temporal characterization. SRP values from the exit of the combined drain are in line with the upstream Nottawasaga River. In contrast, NO3 levels were reduced in half along the combined drain, and were significantly lower than that in the Nottawasaga River. Likewise, NH4 levels leaving the combined drain were only 33 % of their initial values, and were roughly half the levels in the Nottawasaga. The electrical conductivity of the Downey Drain was quite a bit lower (though not significantly) than that in the Giffin Drain, suggesting either a different geologic substrate along that drain or else faster movement of water along that drain. The EC data also highlighted the dominance of the Downey Drain in the combined drain relative to the Giffin Drain.

Table 10: Seasonal averages of nutrients obtained from the Giffin and Downey Drains as they travelled through Nottawasaga River (means ± SE). Station IDs are in order from end of Giffin and Downey drains as shown in Figure 28.

SRP NO3- NH4+ EC Station ID (µg P L-1) (µg N L-1) (µg N L-1) (µS cm-1) Giffin Drain 12 (+/-4) 21 (+/-3) 71 (+/-15) 672 (+/-128) Downey Drain 12 (+/-8) 29 (+/-8) 41 (+/-16) 571 (+/-52) Giffin-Downey Confluence 14 (+/-5) 24 (+/-6) 96 (+/-14) 573 (+/-73) G-D Downstream 25 (+/-21) 12 (+/-10) 32 (+/-16) 582 (+/-85) Notty Upstream of G-D 25 (+/-22) 611 (+/-6) 59 (+/-12) 457 (+/-20) 709 (+/- Notty Downstream of G-D 15 (+/-6) 27) 66 (+/-2) 457 (+/-18)

Seasonal values of SRP, NO3, NH4 and electrical conductivity corresponding to the marsh areas adjacent the Giffin Drain varied but were all quite low, and in line with values found near the end of the Giffin Drain in the Nottawasga River (Table 11). There was, however, no clear trend in the data. The EC levels from all but Marsh Area A were much lower than those found in the drainage ditch. This provides very strong evidence for the lack of marsh-ditch interactions.

Table 11: Seasonal averages of nutrients in the marsh areas (means +/- standard deviation). Station IDs are in composite samples from each area as shown in Figure 28.

- + SRP NO3 NH4 EC Station ID (mg P L-1) (mg N L-1) (mg N L-1) (mS cm-1) Marsh Area A 13 (±6) 36 (±7) 52 (±8) 650 (±98) Marsh Area B 13 (±4) 39 (±13) 44 (±10) 569 (±57) Marsh Area C 12 (±2) 27 (±17) 38 (±21) 483 (±3) Marsh Area D 27 (±29) 12 (±2) 51 (±9) 495 (±107) Marsh Area E 24 (±3) 14 (±8) 48 (±11) 391 (±43)

Overall, the Giffin Drain is doing a fairly effective job of removing excess phosphorus from the water coming from the upslope agricultural fields. There were no significant relationships with any of the nutrients between sampling dates; however, there were significantly lower concentrations of SRP, TP, and NO3 amongst the station locations (data not shown). Table 12 demonstrates the magnitude of decrease in concentrations of SRP, TP and NO3 between the start of the ditch and downstream sites. There was a significant decrease in monthly means of SRP along the drainage ditch (Figure 31). Levels of SRP measured at around 400m to the edge of the ditch were within manageable limits. Thus, the slow transport of water down this ditch is apparently having a net positive effect on stream water quality as the agricultural runoff travels toward the Nottawasaga River.

Table 12: Holm-Sidak Pairwise Multiple Comparison Test of SRP concentrations between Giffin Ditch sampling locations (only statistically significant relationships are shown).

Diff of Unadjusted Critical Comparison Means t - score P-value Level Start Ditch vs. Marsh 1 146.587 4.256 <0.001 0.001 Start Ditch vs. Marsh 2 156.263 3.667 <0.001 0.001 Start Ditch vs. Marsh 3 136.55 3.964 <0.001 0.001 Start Ditch vs. End Ditch 155.983 4.226 <0.001 0.001

Figure 31: Box-whisker plot showing the seasonal variability of phosphate concentrations along the Giffin Drainage Ditch from the start to the end of the ditch as shown in Figure 28. The black line within each box represents the median value; the blue line represents the mean. The PWQO level is shown with the dashed line for comparison.

While this net positive effect of the ditch is better than having no ditch, based on our results, the Minesing Wetlands are not having any significant role in facilitating this effect, except for providing a very gentle slope that allows for the slow transport. The variability in Electrical Conductivity along the Giffin Drain supports the hypothesis that there is no dilution, since EC means across all sample locations are around 680 µS cm-1 (Figure 32). There was some evidence of a slight enrichment of solutes from the Walton Drain, but nutrient levels from the Walton Drain were similar to that of the Giffin Drain. If there had been mixing between the water in the drain and that in the Minesing Wetlands, we would have seen a decrease in EC values. Lack of a significant decrease therefore supports the hydrometric characterization that the wetland and ditch are not interacting.

FIgure 32: Box-whisker plot showing the seasonal variability of EC along the Giffin Drainage Ditch from the start to the end of the ditch as shown in Figure 28. Description of box and whiskers as above.

RECOMMENDATIONS FOR FUTURE

Our study reveals that nutrient and sediment loading is a serious problem in the Nottawasaga River. Water quality varies significantly between months for TN, TP, CHL, COL, Cl-, DO, and TEMP. Almost all monitoring stations exceeded suggested guidelines (PWQO, CEQG, NAESI) for mean monthly TN, TAN, TP, E. coli, TSS, and TURB. Major problem areas exist at stations 02 (Innisfil Creek), 14 (near Knox Rd in the town of Wasaga Beach), 13 (near Jack’s Lake), and 10 (in Minesing Wetlands after Willow Creek). As the river flows through the Minesing Wetlands, TURB values remain elevated. Nutrient concentrations within the Minesing Wetlands initially decrease; however, after Willow Creek enters the system, TP concentrations significantly increase, while DO concentrations decrease significantly. Consequently, the water quality in the Nottawasaga River worsens as it exits the Minesing Wetlands.

The extremely low slope of the landscape between the Giffin Drain and the Minesing Wetlands prevents interaction between these systems during baseflow conditions; migration of surface water from the agricultural field through the Giffin Drain to the Nottawasaga River was extremely slow, allowing the water to be retained in the drain for a relatively long time (8.4 and 3.2 days, during baseflow and stormflow, respectively). This relatively long retention time led to a significant decrease in TP, SRP, and NO3, but an increase in NH4. Study of the water levels combined with geochemical tracers confirmed that the ditch water has negligible interaction with the wetland sediments and vegetation. Therefore, the observed change in water quality parameters from the beginning to the end of the ditch was due almost entirely to in-ditch processing of nutrients. This suggests that the Minesing Wetlands are not being utilized to their maximum assimilative capacity, as water quality should be improved even further if the drainage ditch water could interact with the wetland sediments and plants. It is probable that lowering or removing the berms separating the ditch from the wetland would increase the contact time, leading to even greater removal of agricultural pollutants. The ditch was incapable of removing TP levels to below PWQO levels; thus, this restorative measure may be warranted. This study focussed only on baseflow conditions, and presently it is unknown what the role the ditch and wetland play in water quality improvement during higher levels of flooding, particularly in early spring and fall.

Further landscape-level analyses will be required before we can accurately assess the ability of the Nottawasga River to assimilate nutrients and sediments from different land uses in the NRW. We suggest that future research in the Nottawasaga River focus on tributary loading from various subwatersheds and point sources, as well as on analysis of nutrient and sediment inputs following storm events..

References

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APPENDIX

Table A1: Water quality variables collected each month at 15 monitoring stations (Stn) during the 2014 field season. Standard deviations are presented where samples were processed in triplicate. Values reported with no standard error were single values that had been measured once with a probe or result of a titration. E. coli was only measured once during July.

Stn Month TN TNN TAN TP CHL COL TSS TOSS TURB E. coli Cl- COND DO pH TEMP 01 June 2.18 0.13 0.005 5.94 0.84 117 3.93 2.10 5.03 9.37 528 8.11 8.24 18.5 ±0.06 ±0.02 ±0 ±0.50 ±0.15 ±9 ±0.29 ±0.1 ±1.71 July 2.19 0.08 0.015 23.6 0.98 41 4.93 1.97 5.28 388 19.0 528 8.02 8.26 22.7 ±0.01 ±0.02 ±0.005 ±0.75 ±0.06 ±2 ±0.17 ±0.17 ±0.50 Aug 1.85 0.03 0.015 16.9 0.83 12 4.93 2.33 5.89 21.2 503 8.35 8.26 17.4 ±0.08 ±0.02 ±0.015 ±0.86 ±0.15 ±8 ±0.80 ±0.41 ±0.25 Sept 1.38 0.005 0.005 2.45 3.49 49 14.0 5.43 16.93 24.0 507 7.63 8.17 16.9 ±0.04 ±0.001 ±0 ±0.50 ±0.12 ±21 ±0.38 ±0.24 ±0.33 02 June 1.83 0.035 0.04 31.4 3.44 93 22.5 7.40 23.1 57.6 695 8.74 8.1 18.6 ±0.08 ±0.005 ±0.02 ±1.0 ±0.20 ±15 ±1.34 ±0.6 ±0.73 July 2.64 0.047 0.035 53.3 5.07 69 17.2 5.47 29.8 587 52.8 699 8.01 8.1 23.1 ±0.05 ±0.007 ±0.005 ±1.32 ±0.52 ±1 ±7.94 ±0.98 ±3.47 Aug 1.66 0.057 0.05 63.3 4.04 53 36.5 7.22 49.7 48 660 7.43 8.15 18.6 ±0.09 ±0.007 ±0.01 ±3.96 ±0.13 ±4 ±13.9 ±1.44 ±1.03 Sept 1.40 0.033 0.075 44.8 5.18 122 40.2 6.46 62.9 56.8 617 8.03 8.01 18.5 ±0.15 ±0.003 ±0.015 ±1.80 ±0.28 ±11 ±2.23 ±0.18 ±1.91 03 June 1.65 0.08 0.01 18.4 1.66 115 12 4.13 12.9 13.2 608 9.29 8.13 18.0 ±0.14 ±0.01 ±0.01 ±1.73 ±0.08 ±2 ±0.81 ±0.33 ±0.36 July 2.01 0.05 0.005 31.9 1.56 55 4.72 2.21 7.47 375 23.2 557 8.16 8.23 22.0 ±0.03 ±0.015 ±0 ±4.49 ±0.08 ±8 ±1.11 ±0.37 ±0.09 Aug 1.60 0.033 0.01 36.8 2.53 39 16.1 5.56 14.5 30.4 541 7.95 8.22 17.8 ±0.03 ±0.019 ±0.01 ±1.32 ±0.09 ±6 ±2.76 ±0.40 ±0.27 Sept 1.25 0.01 0.055 37.3 5.87 122 27.7 7.64 28.6 33.2 544 8.36 8.13 17.3 ±0.06 ±0.006 ±0.005 ±1.32 ±0.30 ±16 ±1.43 ±0.84 ±1.19 04 June 2.38 0.18 0.005 15.9 1.55 53 7.73 3.20 7.51 40.8 599 9.13 8.25 20.0 ±0.09 ±0.005 ±0 ±1.0 ±0.16 ±26 ±0.74 ±0.31 ±0.32 July 2.38 0.5 0.015 46.8 3.83 23 9.53 4.20 12.3 79 35.2 599 8.73 8.29 21.6 ±0.01 ±0.015 ±0.005 ±3.96 ±0.26 ±4 ±0.58 ±0.20 ±0.54 Aug 2.27 0.027 0.03 35.3 2.19 57 8.89 3.50 13.1 35.2 559 8.08 8.28 20.4 ±0.05 ±0.003 ±0.017 ±2.64 ±0.18 ±8 ±2.54 ±0.67 ±0.28 Sept 2.50 0.28 0.065 20.9 3.42 115 17.5 5.23 16.3 39.2 571 7.42 8.13 18.3 ±0.02 ±0.06 ±0.005 ±1.32 ±0.24 ±42 ±0.76 ±0.53 ±0.44 05 June 2.40 0.05 0.015 21.4 1.99 25 11.3 3.67 11.6 19.8 590 8.48 8.12 20.8 ±0.27 ±0.01 ±0.005 ±0.86 ±0.06 ±25 ±0.52 ±0.29 ±0.27 July 2.62 0.23 0.04 49.3 7.48 19 16.4 5.53 18.7 79 50.4 602 7.65 8.28 22.0 ±0.03 ±0.02 ±0 ±3.89 ±0.50 ±2 ±1.15 ±0.35 ±0.43 Aug 2.35 0.017 0.047 36.3 2.09 41 12.4 3.89 18.3 40.8 560 7.71 8.19 20.5

Stn Month TN TNN TAN TP CHL COL TSS TOSS TURB E. coli Cl- COND DO pH TEMP ±0 ±0.017 ±0.019 ±0.86 ±0.06 ±3 ±2.81 0.64 ±0.54 Sept 1.81 0.023 0.015 13.9 3.37 38 14.7 4.36 18.1 48.0 563 7.76 8.14 19.8 ±0.05 ±0.003 ±0.005 ±1.73 ±0.17 ±4 ±0.26 ±0.26 ±0.58 06 June 2.52 0.24 0.005 22.4 1.84 15 14.2 6.27 14.0 15.7 552 8.23 8.03 20.2 ±0.20 ±0.01 ±0 ±1.0 ±0.13 ±7 ±1.22 ±1.40 ±0.20 July 2.36 0.48 0.02 51.8 4.45 26 17.2 6.0 25.7 451 28.0 560 7.61 8.25 20.9 ±0.06 ±0.097 ±0.02 ±4.08 ±0.50 ±4 ±2.88 ±0.20 ±2.50 Aug 2.09 0.093 0.07 42.3 2.47 27 20.6 5.39 24.6 33.2 516 7.83 8.16 19.3 ±0.07 ±0.058 ±0.015 ±3.96 ±0.12 ±4 ±1.91 ±0.20 ±0.26 Sept 1.73 0.005 0.02 18.9 2.42 47 11.7 4.31 13.0 30.8 542 8.17 8.12 19.2 ±0.05 ±0.002 ±0 ±3.89 ±0.25 ±7 ±0.59 ±0.41 ±0.54 07 June 2.71 0.135 0.02 19.4 2.39 68 14.3 5.47 13.1 17.4 556 7.87 8.14 17.7 ±0.25 ±0.015 ±0 ±1.32 ±0.07 ±7 ±1.51 ±0.35 ±0.06 July 2.12 0.23 0.035 48.8 5.51 38 15.5 5.20 15.0 200 28.0 534 7.02 8.19 21.4 ±0.09 ±0.11 ±0.015 ±2.49 ±0.31 ±5 ±0.47 ±0.23 ±0.69 Aug 1.95 0.023 0.005 31.4 2.85 81 11.7 5.40 14.4 28.4 533 8.21 8.2 19.7 ±0.01 ±0.003 ±0.005 ±1.80 ±0.06 ±15 ±0.35 ±1.40 ±0.57 Sept 2.11 0.09 0.005 12.4 2.55 105 12.7 5.18 18 34.4 550 8.07 8.19 19.0 ±0.03 ±0.012 ±0 ±1.73 ±0.14 ±9 ±1.83 ±0.57 ±0.67 08 June 2.61 0.027 0.015 36.8 1.99 14 11.7 4.93 9.39 15.3 556 7.82 8.16 17.8 ±0.15 ±0.012 ±0.005 ±2.64 ±0.05 ±4 ±0.35 ±1.05 ±0.31 July 1.98 0.037 0.005 43.1 4.60 19 15.3 5.33 14.8 98 27.2 535 6.96 8.22 21.6 ±0.02 ±0.007 ±0 ±2.24 ±0.32 ±3 ±0.98 ±0.18 ±0.58 Aug 2.15 0.38 0.05 28.4 2.76 2 11.3 4.67 12.6 31.2 542 8.27 8.2 19.8 ±0.01 ±0.003 ±0.03 ±1.99 ±0.18 ±2 ±2.4 ±0.24 ±0.31 Sept 2.07 0.13 0.035 12.4 3.00 110 10.6 4.26 13.4 32.8 555 7.97 8.15 19.0 ±0.08 ±0.01 ±0.015 ±0.86 ±0.03 ±4 ±0.29 ±0.10 ±0.54 09 June 2.34 0.037 0.01 46.3 1.81 39 22.1 5.73 12.9 19.2 550 8.14 8.01 18.1 ±0.15 ±0.003 ±0 ±3.03 ±0.08 ±10 ±2.37 ±0.37 ±0.84 July 1.80 0.09 0.005 48.8 4.53 34 21.5 5.87 16.4 87 22.7 527 6.53 7.97 19.1 ±0.02 ±0.05 ±0 ±3.27 ±0.12 ±5 ±1.48 ±0.33 ±0.32 Aug 1.84 0.013 0.025 27.9 2.67 45 8.56 3.18 10.4 28.4 521 8.22 8.17 20.1 ±0.03 ±0.003 ±0.005 ±1.32 ±0.23 ±7 ±1.88 ±0.05 ±0.61 Sept 1.60 0.005 0.02 10.4 2.40 69 12.7 4.77 13.4 30.4 529 7.69 8.02 19.5 ±0.19 ±0.003 ±0 ±0.50 ±0.15 ±0 ±0.37 ±0.69 ±0.80 10 June 2.35 0.035 0.005 48.3 1.86 45 24.6 6.33 11.4 19.7 554 7.27 7.88 17.9 ±0.03 ±0.005 ±0.005 ±2.28 ±0.10 ±3 ±0.64 ±0.48 ±0.17 July 2.38 0.043 0.07 57.3 3.12 76 20.6 6.0 11.3 65 26.4 535 4.91 7.6 18.9 ±0.15 ±0.009 ±0.01 ±5.39 ±0.09 ±18 ±1.33 ±0.20 ±0.34 Aug 1.62 0.033 0.015 31.9 3.06 23 13.2 4.33 13.2 31.6 528 7.26 7.95 19.1 ±0.01 ±0.003 ±0.005 ±2.28 ±0.28 ±6 ±0.70 ±0.10 ±1.42 Sept 1.80 0.12 0.03 21.9 2.75 63 16.6 5.23 10.7 27.2 536 6.6 7.77 19.0 ±0.01 ±0.016 ±0 ±1.80 ±0.41 ±8 ±0.72 ±0.67 ±0.03 11 June 2.09 0.085 0.015 44.3 1.61 141 22.5 5.67 17.1 15.9 546 6.33 7.92 19.4 ±0.01 ±0.003 ±0.005 ±1.32 ±0.09 ±15 ±1.39 ±0.98 ±0.15

Stn Month TN TNN TAN TP CHL COL TSS TOSS TURB E. coli Cl- COND DO pH TEMP July 1.98 0.097 0.045 60.8 3.59 57 21.0 4.47 15.8 69 27.2 551 5.69 7.7 19.1 ±0.31 ±0.038 ±0.005 ±6.59 ±0.14 ±3 ±2.16 ±0.07 ±1.01 Aug 1.74 0.069 0.01 23.4 2.71 44 8.72 5.61 11.5 29.2 525 7.1 7.97 19.1 ±0.08 ±0.006 ±0 ±1.80 ±0.19 ±2 ±1.39 ±1.50 ±0.38 Sept 1.78 0.027 0.015 8.93 2.6 137 10.2 3.90 11.0 29.6 553 7.2 7.87 19.4 ±0.04 ±0.007 ±0.015 ±0.50 ±0.05 ±1 ±0.67 ±0.84 ±0.78 12 June 2.21 0.043 0.075 40.8 2.02 48 19.7 5.60 12.8 17.9 545 6.38 7.87 19.4 ±0.03 ±0.003 ±0.045 ±0.86 ±0.06 ±17 ±2.56 ±0.23 ±0.50 July 1.54 0.087 0.06 62.3 3.48 59 27.0 5.8 19.4 79 29.6 549 5.5 7.73 18.9 ±0.03 ±0.035 ±0 ±6.25 ±0.38 ±7 ±1.97 ±0.42 ±2.20 Aug 1.56 0.005 0.02 28.4 2.36 33 10.3 4.78 14.3 32.0 523 7.25 7.94 19.0 ±0.03 ±0.003 ±0 ±1.32 ±0.17 ±10 ±1.23 ±1.02 ±0.38 Sept 1.64 0.033 0.005 17.9 2.56 155 12.4 5.74 15.5 29.2 550 7.04 7.89 19.1 ±0.01 ±0.012 ±0 ±2.49 ±0.11 ±20 ±0.18 ±0.10 ±0.20 13 June 2.2 0.035 0.075 44.8 2.17 33 13.7 5.27 15.1 17.9 553 6.67 7.8 19.7 ±0.09 ±0.005 ±0.005 ±0.50 ±0.14 ±29 ±0.87 ±0.18 ±0.70 July 1.57 0.08 0.005 56.3 4.54 83 13.2 3.53 13.5 451 23.4 529 4.36 7.67 23.2 ±0.01 ±0.04 ±0.005 ±6.06 ±0.11 ±6 ±1.51 ±0.53 ±0.31 Aug 1.58 0.07 0.015 35.3 6.53 56 12.6 6.13 14.6 27.6 502 7.81 7.96 21.4 ±0.01 ±0.006 ±0.015 ±1.99 ±0.39 ±4 ±1.01 ±1.16 ±0.30 Sept 1.44 0.05 0.045 31.9 2.44 94 13.1 6.0 19.0 28.4 538 5.62 7.67 20.8 ±0.03 ±0.015 ±0.005 ±6.04 ±0.18 ±13 ±1.39 ±1.69 ±0.55 14 June 2.35 0.058 0.075 33.9 2.13 18 9.93 4.4 11.4 16.7 554 7.29 7.86 20.5 ±0.26 ±0.012 ±0.025 ±1.32 ±0.08 ±18 ±0.47 ±0.20 ±0.12 July 1.65 0.2 0.065 53.3 3.61 43 12.4 3.07 11.2 2424 25.6 531 5.76 7.64 24.3 ±0.05 ±0.057 ±0.015 ±4.08 ±0.12 ±2 ±0.83 ±0.24 ±0.12 Aug 1.62 0.11 0.08 24.9 5.88 47 7.07 4.6 10.4 28.8 503 7.91 8 21.3 ±0.01 ±0.015 ±0.01 ±1.80 ±0.40 ±6 ±0.41 ±0.69 ±0.19 Sept 1.52 0.005 0.1 18.9 1.94 83 10.7 2.92 13.7 28.8 536 6.43 7.69 20.8 ±0.02 ±0 ±0.03 ±2.17 ±0.17 ±3 ±0.37 ±0.94 ±0.23 15 June 2.42 0.025 0.055 38.8 1.93 72 5.33 3.47 6.72 22.9 555 7.04 7.77 20.4 ±0.28 ±0.005 ±0.005 ±2.78 ±0.14 ±14 ±0.44 ±0.29 ±0.28 July 1.98 0.013 0.08 56.8 3.31 47 8.73 2.73 10.5 39 23.4 546 6.11 7.7 24.3 ±0 ±0.003 ±0.03 ±0.50 ±0.20 ±11 ±0.93 ±0.87 ±0.17 Aug 1.63 0.057 0.015 22.9 6.02 85 4.2 3.8 6.3 29.6 499 8.76 8.08 20.8 ±0.02 ±0.019 ±0.005 ±1.73 ±0.47 ±8 ±0.42 ±0.53 ±0.71 Sept 1.63 0.017 0.02 7.93 3.02 55 3.79 2.56 6.82 30.4 559 7.32 7.84 21.1 ±0.04 ±0.003 ±0 ±0.86 ±0.17 ±9 ±0.89 ±0.21 ±0.24

TEMP (°C) 14

06-01 06-15 06-29 07-13 07-27 08-10 08-24 09-07 09-21 10-05 10-19 2014 Date (mm-dd)

Figure 2A: Diurnal fluctuations in TEMP (black) within the Minesing Wetlands at station 07 from the beginning of June until the end of October.