A comparison of water quality and greenhouse gas emissions in constructed wetlands and conventional retention basins with and without submerged macrophyte management for storm water regulation

Ecological Engineering 127 (2019) 292–301

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A comparison of water quality and greenhouse gas emissions in constructed wetlands and conventional retention basins with and without submerged macrophyte management for storm water regulation

T

Pascal Badioua, Bryan Pagea, , Lisette Rossb ⁎

a b

Institute for Wetland and Waterfowl Research Ducks Unlimited Canada, Stonewall, Manitoba R0C 2Z0 204-467-3277, Canada Native Plant Solutions, Winnipeg, Manitoba R3T 1Y3, Canada

ARTICLE INFO

ABSTRACT

Keywords: Urban constructed wetland Stormwater retention basin Water quality Aquatic vegetation removal Greenhouse gas emissions

The city of Winnipeg (Manitoba, Canada) has numerous conventional stormwater retention basins to attenuate stormwater runoff. Significant operational resources are applied to control the proliferation of aquatic macrophytes and filamentous algal mats in these conventional stormwater retention basins to meet the aesthetic expectations of surrounding residents. Recent urban developments in the city of Winnipeg have used constructed wetlands to handle stormwater as opposed to conventional basins. We examined the differences in water quality, greenhouse gas emissions and cumulative greenhouse gas fluxes between conventional stormwater retention basins and urban constructed wetlands. Additionally, we examined how water quality and greenhouse gas emissions were impacted by the removal of submersed aquatic vegetation in conventional stormwater retention basins. Our results indicate large phytoplankton blooms were consistently reduced both pre and post treatment in the urban constructed wetlands (chlorophyll-a = 13 µg l−1 and 33 µg l−1) relative to the untreated conventional stormwater retention basins (chlorophyll-a = 56 µg l−1 and 128 µg l−1) and treated conventional stormwater retention basins (chlorophyll-a = 58 µg l−1 and 405 µg l−1). Mean daily greenhouse gas fluxes were lower pre and post treatment in the urban constructed wetlands (CO2eq = 26.5 kg ha−1 d−1 and 53.1 kg ha−1 d−1) relative to the untreated (CO2eq = 85.5 kg ha−1 d−1 and 89.0 kg ha−1 d−1) and treated conventional stormwater retention basins (CO2eq = 98.5 kg ha−1 d−1 and 129.8 kg ha−1 d−1). Over the 22 week period, mean total basin cumulative CO2eq flux was lowest in the urban constructed wetlands (6,447 g ha−1 d−1) compared to the untreated (12,631 g ha−1 d−1) and treated (17,633 g ha−1 d−1) conventional stormwater retention basins. The combined treatments (herbicides and harvesting) applied to the conventional stormwater retention basins to remove aquatic vegetation result in poorer water quality and appear to stimulate methane emissions resulting in noticeably higher cumulative fluxes of greenhouse gases from these basins. The use of urban constructed wetlands in new residential areas should result in enhanced water quality and reduced cumulative greenhouse gas fluxes, while avoiding the cost associated with macrophyte removal.

1. Introduction There are in excess of 100 stormwater retention basins (SRBs) in the City of Winnipeg (Manitoba, Canada), servicing more than 10,000 ha. Conventional stormwater retention basins (CSRBs) were initially constructed as hydraulic-control structures to dampen hydraulic loads by attenuating hydrograph run-off peaks in residential communities (Wakelin et al., 2003). Although the City of Winnipeg places priority on the functionality and safety of these basins, significant operational

resources are applied to controlling the proliferation of aquatic macrophytes and filamentous algal mats to meet the aesthetic expectations of surrounding residents (Wardrop, 2001). The pressure to control growth of vegetation and algae in these systems is due to the fact that residents pay a premium to build homes along their shores and view aquatic vegetation as unsightly. With projected significant increases in population growth and subsequent suburban development, stormwater management costs associated with vegetation control will similarly increase.

Abbreviations: CO2eq, carbon dioxide equivalent; SRB, stormwater retention basin; CSRB, conventional stormwater retention basin; UCW, urban constructed wetland ⁎ Corresponding author. E-mail addresses: [email protected] (P. Badiou), [email protected] (B. Page), [email protected] (L. Ross). https://doi.org/10.1016/j.ecoleng.2018.11.028 Received 20 June 2018; Received in revised form 16 November 2018; Accepted 24 November 2018 0925-8574/ © 2018 Elsevier B.V. All rights reserved.

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To address the overgrowth of aquatic macrophytes and algae, the city has implemented a rigorous program to reduce and control the amount of aquatic vegetation in CSRBs, often increasing vegetation management practices in response to complaints from the public. Submerged aquatic vegetation, such as sago pondweed (Stuckenia pectinatus), which is often abundant in conventional stormwater retention basins, is controlled using a large harvester that cuts and physically removes vegetation from the pond. In basins that are too small or irregularly shaped, where harvesting is not practical, an aquatic herbicide (Diquat or Diuron) was used to control submerged vegetation. Herbicides are also used on occasion to treat ponds where filamentous algal mats have become abundant. In addition to issues with aquatic macrophytes and algal mats, CRSBs experience blue-green algal blooms regularly, which produce odor and aesthetic issues for residents. Managing these various issues is costly and time consuming. As a result, developers in the City of Winnipeg have been installing urban constructed wetlands (UCWs) that integrate functionally and floristically diverse wetland and upland plant communities into their suburban water management plans in lieu of CSRBs. Benefits of the ‘wetland’ approach to storm water management include cost savings, less maintenance, natural aesthetics and improved water quality (Altor and Mitsch, 2004; Economides, 2014; Greenway, 2010). Natural inland wetlands provide a suite of valuable ecological goods and services including flood mitigation, groundwater recharge, erosion control, sediment retention, improved water quality and climate change mitigation (Costanza et al., 1997; Mitsch and Gosselink, 2007). Similarly, CSRBs and UCWs will provide an assortment of these ecological services to some degree. However, the various management techniques applied to deal with nuisance vegetation issues within the CRSBs likely affects the function of these systems and may potentially have implications for water quality and GHG emissions. For example it is well established that aquatic vegetation plays an important role in regulating the water quality of aquatic ecosystems (Dierberg et al., 2002; Srivastava et al., 2008; Takamura et al., 2003). It is also known that GHG emissions from aquatic ecosystems are affected by water quality (Baron et al., 2013; Davidson et al., 2015; DelSontro et al., 2018) and aquatic vegetation (Davidson et al., 2015; Mander et al., 2014a) As cities plan and implement green infrastructure to support their growing economies in a sustainable fashion, information to guide the decision making process to reach their goals is imperative. Improved water quality and reducing urban contributions of GHG emissions are key goals for many growing urban areas in Canada and around the world. As such, the primary objective of our research was to examine the differences in water quality and GHG emissions between CRSBs and UCWs. The second objective of our research was to determine what effects the management of aquatic macrophytes in CRSBs has on water quality and GHG emissions from these systems relative to un-managed CRSBs. To our knowledge there has been no formal comparison of water quality and greenhouse gas (GHG) emissions between CRSBs and UCWs. Similarly, there has been no examination of the various techniques used to manage vegetation within CSRBs and the resulting impacts on water quality and GHG emissions.

Scirpus spp.) in the littoral zone 4–6 m wide. Both basin types contain submersed aquatic vegetation (primarily Stuckenia spp.) as well as emergent vegetation in the littoral zone of the basins. All basins have fixed spill elevations. 2.2. Management of aquatic vegetation in CSRBs The treatment of aquatic vegetation in the six treated CSRBs occurred between the start of week 8 and the end of week 11 (June 27, 2007 to July 18, 2007) of the 22 week study period. Treatments to remove aquatic vegetation were done by 1) mechanical removal via a large paddlewheel harvester that cuts and physically removes the vegetation from the basin or by 2) chemical removal through application of the aquatic herbicide Diquat or Diuron (Reward or Karmex-DF). Herbicide application was administered either basin wide or along the perimeter of the littoral zone of the basin. Treatments were administered either as one or as a combination of both techniques (physical removal and herbicide application). Treatment type and timing was dependent on the weather condition, the availability of the contractor, the operational state of the harvesting equipment and the need to respond to public complaints. 2.3. Water quality monitoring Water samples were collected by boat every week from May to October at all 15 basins from the center of each basin in pre-rinsed bottles by submerging the bottles 5 cm below the air/water interface. Samples were placed into a dark cooler and stored at 4 °C and transported to the City of Winnipeg water quality laboratory located at the North End Water Pollution Control Center in Winnipeg Manitoba. Water samples were analyzed for total phosphorus (TP), soluble reactive phosphorus (SRP), nitrate (NO3–), ammonium (NH4 + ) and chlorophyll-a (Chl-a). TP and SRB were analyzed by ascorbic acid reduction, NO3– was analyzed by cadmium reduction, NH4 + was analyzed by the phenate method and Chl-a was analyzed via spectrophotometric determination (Clesceri et al., 1989). 2.4. Greenhouse gas monitoring and flux estimates GHG samples were collected every three weeks on the same day water samples were collected. GHG fluxes were monitored using floating, one-piece, static-vented chambers. Chambers (22 cm high; 20 cm i.d.) were covered with reflective material to stabilize chamber internal temperature. Sealed PVC pipe was attached to the outside of the chamber to provide flotation while the bottom circular edge of the chamber penetrated slightly below the air/water interface. Our gas sampling was based on the procedure described in Tenuta et al. (2010). Floating chambers were deployed at two locations in each basin. The first chamber was located in the littoral zone of the basin and the second chamber was situated in the pelagic zone. Gas samples were collected at 0, 5, 10, 20 and 30 min using 60 mL syringes (BectonDickinson, Franklin Lakes, NJ). Gas collected within the syringe was transferred into a 12 mL pre-evacuated Exetainer® vial (Labco Limited, Buckinghamshire, UK). All gas samples were transported to the University of Manitoba’s Soil Ecology Laboratory in Winnipeg and stored at room temperature until analyzed. GHG samples were analyzed using a gas chromatograph (GC) (Varian GP3800; Varian Canada, Mississauga, ON) fitted with an electron capture detector, flame ionization detector, and thermal conductivity detector (Tenuta et al., 2010). A Combi-PAL auto sampler (CTC Analytics, Switzerland) injected a 2.5 mL volume of sample into the GC. Calibration check vials were run with sample vials and a run was either repeated or the GC column was reconditioned and calibration redone if check vials were off by more than 5% from the concentration of the standard (Dunmola et al., 2010). Flux rates were calculated using the gas concentration, molecular mass of carbon or nitrogen, chamber area, chamber volume, air

2. Material and methods 2.1. Characteristics of conventional stormwater retention basin and constructed wetlands The 10 CSRBs (Fig. 1) at normal water level have a surface area range of 0.27 ha–2.97 ha, a depth range of 1.22 m–2.50 m, and a volume range of 2.14 ML–39.97 ML. The uplands surrounding the CSRBs are predominantly managed sod. The 5 UCWs (Fig. 1) at normal water levels have a surface area range of 0.80 ha–9.11 ha, a depth range of 1.50 m–3.90 m, and a volume range of 8.93 ML–191.54 ML The uplands surrounding the UCWs are predominantly native grasses. The UCWs also have an established ring of emergent vegetation (Typha spp. and 293

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Fig. 1. Location of 5 UCWs, 6 treated CSRBs and 4 untreated CSRBs within the city of Winnipeg, Manitoba, Canada.

temperature at the time of sampling and atmospheric pressure using the Ideal Gas Law (pV = nRT). The mass of gas in the chamber’s atmosphere (g gas-element) was determined and converted to mass of gas per chamber area (g gas-element ha−1). From this, the flux rate of the gas-element (g gas-element ha−1 d−1) was determined using the slope of a linear regression plot of g gas-element ha−1 versus time. Data filtering for fluxes was adapted from Churchill (2007). Gas concentrations over time were visually examined for outliers. A minimum of three of the four sampling points were used to calculate fluxes and an r2 value of 0.85 or greater was usually obtained. Cumulative seasonal GHG fluxes (May–October) were calculated for each of the basins by multiplying flux rates by the time that had elapsed between sampling dates. Cumulative fluxes of CO2, CH4 and N2O were combined and expressed as CO2 equivalents to determine the global warming potential (GWP) associated with these fluxes using the 100 year time horizon factors of 25 for CH4 and 298 for N2O (Solomon, 2007). To standardize GHG flux data between the two types of basin (CSRBs vs. UCWs) the ratio of pelagic to littoral zone in the UCWs was assessed as being 2.5:1, and 4:1 in CSRBs.

effect of basin-type was treated as a between basin factor, while the effects of pre vs post treatment application and the interaction between basin-type and pre vs post treatment application were treated as within basin factors. A random effect to account for basin-to-basin variability within treatment condition was included in the models to serve as the error term for assessing overall effects of basin-type. The within subject error corresponding to the weekly data obtained within each of the pre and post intervention periods was specified to follow an auto-regressive order 1 structure (i.e. observations obtained more closely in time on the same basin have the highest correlation, with correlation exponentially decaying as the number of weeks between observations increases). Significance of the interaction between basin-type and pre vs. post treatment was used to assess whether differences between basin-types changed following treatment application. Responses were ln-transformed since initial analyses revealed evidence of non-normality and non-constant variance of the residuals. Since some calculated basinspecific changes in GHG emissions were negative, constants were added prior to ln-transformation. Statistical contrasts among least-square means were used to assess the nature of differences among basin-types prior to and following treatment application. Cumulative emissions data (as CO2eq) were analyzed by examining whether the overall changes in emissions levels from week 1–22 differed by basin-type (CSRB-untreated, CSRB-treated, UCW). For each basin the changes in emissions (Week 22–Week 1) were calculated and treated as response variables, with basin type as the predictor in oneway analyses of variance. Responses were ln-transformed since initial analyses revealed evidence of non-normality and non-constant variance of the residuals. When significant differences were observed among

2.5. Statistical analysis In the CSRBs where vegetation management occurred, treatments took place over a three week period. Due to this, for our statistical analysis we defined the pre treatment period as week 1–week 10 and the post treatment period as week 13–week 22. Water quality and GHG emissions data were analyzed as a before-after-control-impact (BACI) design using repeated measures models (Wiens and Parker, 1995). The 294

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Table 1 Before After Control Impact water quality means ( ± S.E.) of the untreated and treated conventional stormwater retention basins (CSRBs) and the urban constructed wetlands (UCWs). Water Quality Parameter

Chl-a (μg L−1) NO3– (μg L−1) NH4+ (μg L−1) DIN (μg L−1) SRP (μg L−1) TP (μg L−1)

Untreated CSRB

Treated CSRB

UCW

Pre Treatment

Post Treatment

Pre Treatment

Post Treatment

Pre Treatment

Post Treatment

56 ± 9 173 ± 36 107 ± 7 280 ± 42 25 ± 6 160 ± 10

128 ± 9 141 ± 21 100 ± 1 241 ± 21 30 ± 3 181 ± 13

58 ± 9 76 ± 13 158 ± 16 234 ± 26 109 ± 10 253 ± 13

405 ± 74 80 ± 15 214 ± 86 294 ± 98 111 ± 13 467 ± 48

13 ± 4 61 ± 27 100 ± 1 161 ± 27 26 ± 2 178 ± 28

33 ± 4 49 ± 33 130 ± 30 179 ± 36 38 ± 11 175 ± 14

basin-types, contrasts among least-square means (adjusted using Tukey’s method for multiple comparisons) were used to determine which basin types differed in their change in emission levels. The magnitude of the treatment effect on cumulative GHG fluxes expressed as CO2eq was evaluated using the Hedges’s g metric. Positive Hedge’s g values suggest that treatments (treated CSRBs and UCWs) increased cumulative GHG flux relative to those measured in the un-treated CSRBs, while negative values suggest treatments decreased cumulative GHG flux. Values of 0.2 are associated with a small effect size, values of between 0.2 and 0.8 are indicative of medium effect, and values above 0.8 suggest a large effect.

four times higher than those recorded in untreated CSRBs and UCWs, but also remained stable from pre to post treatment (Table 1, Fig. 2). Nitrate concentrations decreased slightly pre to post treatment in the untreated CSRBs and UCWs while remaining stable for the entire duration of the study in the treated CSRBs. Additionally, nitrate concentrations in the untreated CSRBs were 2–3 times higher than concentrations recorded in the other basin types (Table 1). Ammonia concentrations were highest in the treated CSRBs and increased from pre to post treatment, while ammonia concentrations were lower and consistent throughout the 22 week monitoring period in the untreated CSRBs and UCWs. Overall, DIN concentrations were the lowest in the UCWs pre and post treatment (Table 1).

3. Results

3.2. Daily greenhouse gas emissions

3.1. Water quality

Pre and post treatment means for daily greenhouse gas emissions for the littoral zone, pelagic zone and the calculated total basin from the three basin types are presented in Table 2. Time series for total basin mean daily CO2, CH4, N2O emissions and mean total basin cumulative CO2eq emissions from all three basin types are presented in Fig. 3.

Pre and post treatment means for all water quality variables for all three basin types are presented in Table 1. Time series for Chl-a, TP and SRP concentrations for all three basin types are shown in Fig. 2. Repeated-measures ANOVA analysis showed Chl-a concentrations were significantly different among basin types (p = 0.0149) and increased significantly from the pre to post treatment period (p < 0.0001). Contrasts of least square means showed that compared to UCWs, untreated and treated CSRBs had significantly higher Chl-a concentrations (p = 0.0453 and p = 0.0178) over the 22 week period of the study. Maximum Chl-a concentrations occurred post treatment on week 12 for both the treated CRSBs (677 µg L−1) and the untreated CSRBs (165 µg L−1; Fig. 2). Conversely, Chl-a concentrations in the UCWs were fairly consistent throughout the open-water season, and only reached a maximum of 43 µg L−1 during week 22 (Fig. 2). Mean post treatment Chl-a concentrations for treated CSRBs (405 µg L−1) were much higher than those for the un-treated CSRBs (128 µg L−1) and the UCWs (33 µg L−1; Table 2). TP concentrations were significantly different among basin types (p = 0.0216) and increased significantly from the pre to post treatment period (p = 0.0396). Contrasts of least square means showed that the treated CSRBs had significantly higher TP concentrations than the UCWs over the measured period (p = 0.0353). The untreated CSRBs and UCWs TP concentrations remained fairly consistently throughout the open-water season (near 150 µg L−1), while the treatment CSRBs increased in TP concentrations immediately post treatment rising from 250 µg L−1 at week 11 up to 608 µg L−1 on week 14 (Fig. 2). Treated CSRBs post treatment mean TP concentrations of 467 µg L−1 were much higher than the UCWs and the untreated CSRBs with mean TP concentrations of 175 µg L−1 and 181 µg L−1 respectively (Table 1). Repeated-measures ANOVA analysis of SRP concentrations indicated that there were significant differences among basin types (p = 0.0364) but not between treatment periods. In addition, there was a significant interaction between basin type and treatment period (p = 0.0054). SRP concentrations for untreated CSRBs and UCWs remained stable showing very little increase over the 22 week period (Table 2, Fig. 2). SRP concentrations for the treated CSRBs were three to

3.2.1. Daily CO2 flux Repeated-measures ANOVA analysis showed daily CO2 emissions increased significantly in the littoral zone from pre to post treatment period (p = 0.0006) among basin types. The UCWs littoral zone had the greatest daily CO2 emission increase from 1.2 kg ha−1 day−1 during the pre-treatment period to 3.5 kg ha−1 day−1 during the post-treatment period (Table 2). Daily pelagic CO2 emissions were significantly different between basin types (p = 0.0445). Daily pelagic zone CO2 emissions were lowest in the treated CSRBs increasing from −0.2 to 0.4 kg ha−1 day−1 pre to post treatment, while the pelagic zone UCWs generated the highest daily CO2 emissions across all treatments at 3.5 and 3.8 kg ha−1 day−1 pre and post treatment. Mean daily total basin CO2 emissions increased from pre to post treatment in all basins (Table 2). There were difference between basin types (p = 0.0420) with contrast of least square means showing the UCWs having significantly higher daily total basin CO2 emissions than the treated CSRBs (p = 0.0337). No significant differences were found in the interaction between basin type and treatment period for CO2 emissions. 3.2.2. Daily CH4 flux There were significant differences in mean daily CH4 emissions between basin types in the pelagic zone (p = 0.0052) and for the total basin (p = 0.0418) and were highest in the treated and untreated CSRBs. Littoral zone mean daily CH4 emissions were highest in the treated CSRBs pre and post treatment when compared to untreated CSRBs and UCWs (Table 2). However, CH4 emissions from these basins were highly variable over the course of the monitoring period (Fig. 3B). Littoral zone daily CH4 emissions decreased form the pre to post treatment period in the untreated CSRBs but increased in the treated CSRBs and in the UCWs. Contrasts of least square means indicate that the pelagic zone in the treated and untreated CSRBs have significantly 295

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Fig. 2. Weekly concentrations of TP, SRP and Chl-a in all 3 basin types from week 1 (May 8, 2007) to week 22 (October 4, 2007).

higher daily CH4 emissions compared to the UCWs (p = 0.0240 and p = 0.0059). Pelagic zone daily CH4 emissions remained similar in the untreated CSRBs pre to post treatment while daily CH4 emissions increased post treatment both in the treated CSRBs and UCWs. Total basin daily CH4 emissions were similar between the pre and post treatment periods in the untreated CSRBs while total basins emissions were substantially higher during the post treatment period in the treated CSRBs and the UCWs. However, the UCWs showed the lowest daily CH4 emissions both pre and post treatment (Table 2). The largest increase in

daily total basin CH4 emissions was observed in the treated CSRBs, where emissions reached 8,724 g ha−1 day−1 two weeks after treatment ceased on week 13. Total basin daily CH4 emissions in the treated CSRBs then sharply decreased by week 16, and were comparable to the emissions observed for the untreated CSRBs and UCWs (Fig. 3). 3.2.3. Daily N2O flux Littoral zone mean daily N2O emissions decreased pre to post treatment in all basin types. Mean daily littoral zone N2O emission were 296

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Table 2 Mean daily greenhouse gas and CO2eq flux ( ± S.E.) of untreated and treated conventional stormwater retention basins (CSRBs) and urban constructed wetlands (UCWs) from the littoral zone, pelagic zone and calculated total basin. Mean Daily GHG Flux

Untreated CSRB

Treated CSRB

UCW

Before Control

After Control

Before Control

After Control

Before Control

After Control

Littoral

CO2-C (kg ha−1 d−1) CH4-C (g ha−1 d−1) N2O-N (g ha−1 d−1) CO2eq (kg ha−1 d−1)

−1.0 ± 0.3 278 ± 195 0.82 ± 0.20 5.3 ± 6.9

0.4 ± 0.6 152 ± 64 0.61 ± 0.39 6.4 ± 1.8

−1.3 ± 0.4 5514 ± 4237 0.52 ± 0.42 164.4 ± 130.0

0.3 ± 0.6 7307 ± 4264 0.43 ± 0.46 225.7 ± 129.0

1.2 ± 1.0 1134 ± 850 0.40 ± 0.27 39.8 ± 24.1

3.5 ± 1.0 2462 ± 1368 0.05 ± 0.26 88.4 ± 40.6

Pelagic

CO2-C (kg ha−1 d−1) CH4-C (g ha−1 d−1) N2O-N (g ha−1 d−1) CO2eq (kg ha−1 d−1)

1.0 ± 0.5 3522 ± 865 1.03 ± 0.35 112.2 ± 26.1

1.9 ± 0.5 3554 ± 676 0.86 ± 0.26 116.5 ± 22.5

−0.2 ± 0.7 2507 ± 972 0.68 ± 0.43 76.6 ± 30.9

0.4 ± 0.4 3136 ± 768 0.43 ± 0.26 97.8 ± 22.8

3.5 ± 0.5 170 ± 80 0.07 ± 0.18 15.9 ± 3.6

3.8 ± 0.9 551 ± 232 −0.01 ± 0.17 27.9 ± 6.3

Total Basin

CO2-C (kg ha−1 d−1) CH4-C (g ha−1 d−1) N2O-N (g ha−1 d−1) CO2eq (kg ha−1 d−1)

0.5 ± 0.4 2711 ± 625 0.98 ± 0.31 85.5 ± 18.7

1.6 ± 0.3 2703 ± 523 0.80 ± 0.29 89.0 ± 17.0

−0.5 ± 0.6 3259 ± 1290 0.64 ± 0.38 98.5 ± 41.1

0.4 ± 0.5 4178 ± 1534 0.44 ± 0.32 129.8 ± 46.0

2.6 ± 0.2 555 ± 385 0.20 ± 0.07 26.5 ± 11.8

3.7 ± 0.6 1291 ± 674 0.01 ± 0.16 53.1 ± 19.5

highest in the untreated CSRBs during the pre treatment period (0.82 g ha−1 day−1) and lowest in the UCWs during the post treatment period at 0.05 g ha−1 day−1. There were significant differences in pelagic mean daily N2O emissions among basin types (p = 0.0496). Contrasts of least square means indicated that the untreated CSRBs had significantly higher pelagic mean daily N2O emissions compared to UCWs (p = 0.0402), while treated CSRBs had slightly lower but no significant difference in daily N2O emissions than the untreated CSRBs. As was the case in the littoral zone, daily pelagic zone N2O emissions decreased in all three basin types from pre to post treatment. The untreated CSRBs had the highest total basin mean daily N2O emissions pre

and post treatment followed by the treated CSRBs. The UCWs had the lowest mean daily N2O emissions of all the basin types. 3.3. Total basin cumulative GHG flux One-way ANOVA of total basin cumulative GHG (CO2eq) emissions showed no significant differences among basin types (p = 0.0823; Fig. 3). However, there did appear to be noticeable differences between basins in terms of final cumulative emissions and their trajectory over the course of the open-water season. Relative to the CSRBs (untreated and treated) cumulative GHG emissions from UCWs increased at a

Fig. 3. Mean daily total basin A) CO2-C B) CH4-C C) N2O-N and mean total basin cumulative D) CO2eq flux for all three basin types from week 1 (May 8, 2007) to week 22 (October 4, 2007). 297

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Fig. 4. Relationship between total basin cumulative CH4 flux and total basin cumulative GHG emissions across all basin types with upper and lower 95% confidence limits.

Fig. 5. Relationship between mean Chl-a concentrations and total basin cumulative CH4 flux across all basin types with upper and lower 95% confidence limits.

slower rate throughout the open-water season, reaching a mean total basin cumulative GHG flux of 6,447 kg CO2eq ha−1 (Fig. 3). The final cumulative GHG emission for UCWs was substantially lower than those measured for the untreated CRSBs (12,632 kg CO2eq ha−1) and the treated CRSBs (17,633 kg CO2eq ha−1, Fig. 3). Cumulative GHG fluxes for the untreated and treated CRSB were very similar during the pre treatment and treatment periods. However, shortly after the treatment period cumulative GHG fluxes between the untreated and treated CRSBs began to diverge from one another as a result of the large CH4 flux that was associated with treated CSRBs during and immediately after the treatment period (Fig. 3). Comparing cumulative fluxes using Hedges’s g indicated that treatment of the basins had a positive, moderate effect (g = 0.463) on cumulative GHG flux. Conversely, when comparing the cumulative GHG flux between untreated CSRBs and UCWs we found a large negative effect (g = -0.919). 3.4. Relationships between water quality and total basin cumulative GHG flux

Fig. 6. DIN:DP ratios and total basin cumulative CH4 flux across all basin types in relation to the Redfield Ratio of 16:1 which is show here as the red dashed line.

Total basin cumulative CH4 flux was strongly positively correlated with total basin cumulative GHG emissions (r2 = 0.98, p = 0.0001; Fig. 4). In general, across all basin types, cumulative CH4 emissions accounted for greater than 70% of total cumulative GHG emissions. There was also a strong positive relationship observed between mean Chl-a concentrations and total basin cumulative CH4 flux (r2 = 0.64, p = 0.0002; Fig. 5). Lastly, total basin cumulative CH4 flux appears to become more variable and increases substantially when mean DIN:DP is below the Redfield Ratio of 16:1 (Fig. 6).

was low (Table 1) and resulted in cyanobacterial blooms. These differences are not surprising given that emergent macrophytes which are abundant in our UCWs but not the CSRBs can effectively remove nutrients and reduce phytoplankton biomass (Rodrigo et al., 2018; Shoemaker et al., 2017). The treatments applied to CSRBs appeared to promote poor water quality. Mechanical removal of submerged macrophytes by the harvester likely increased light penetration and released phytoplankton from competition with submerged macrophytes. It is also possible that the harvester released a substantial amount of nutrients to the water column through disturbance of the surface sediments during macrophyte removal, and potentially further stimulated the rapid increase in algal biomass that occurred post treatment. Unlike mechanical removal, which can actually remove P from the system stored in submerged vegetation, chemical removal of macrophytes via herbicides reduces plant biomass in-situ resulting in nutrient release from decaying plant matter to the water column (Engel, 1990). Like mechanical removal, chemical treatment results in the same physical alterations to the system of increased light penetration and increased open-water area. The combined effects of mechanical and chemical removal were evident in treated CSRBs where TP increased immediately post treatment for three straight weeks with Chl-a emulating this increase and reaching concentrations as high as 677 µg L−1. However, while TP increased

4. Discussion 4.1. Impacts of basin type and treatment on water quality Submerged macrophytes are important for the stabilization of the clear water stable state in shallow mesotrophic and eutrophic lakes (van Donk and van de Bund, 2002). While submerged macrophytes are known to enhance water quality (Kuiper et al., 2017), biodiversity (Ali et al., 2007; Thomaz and Cunha, 2010) and enhance ecosystem services of aquatic systems (Engelhardt and Ritchie, 2001), their presence does not always align with the recreational and aesthetic preferences of homeowners who live in close proximity to stormwater retention basins. In our study, UCWs had substantially lower levels of algal biomass (based on Chl-a concentrations) relative to both types of CSRBs. However, the biggest differences in algal biomass were between the UCWs which had high DIN:SRP relative to the treated CSRBs where DIN:SRP 298

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immediately post harvest in the treated CRSBs, SRP concentrations decreased. This suggests that increases in TP are related to the increased uptake of soluble P by phytoplankton and incorporation into algal biomass. The release of soluble P forms as a result of herbicide application to submerged vegetation and subsequent rapid uptake by phytoplankton was also reported by Brooker and Edwards (1973) and by Peverly and Johnson (1979). The combination of physical changes due to macrophyte removal and the high concentrations of SRP in the treated CSRBs contributed to the significantly higher Chl-a concentrations observed relative to those in the untreated CSRBs and UCWs. Lastly, our results suggest that macrophyte management in CSRBs has resulted in significantly higher SRP concentrations in these basins relative to untreated CSRBs and UCWs. In total, the moderately high nutrient loading to the CSRBs in combination with macrophyte management appear to favor establishment of the turbid phytoplankton dominated state. This agrees well with the alternative stable states theory in shallow lakes (Scheffer et al., 1993) where perturbations/ disturbance such as macrophyte removal are known to destabilize the system and result in a switch to the turbid phytoplankton dominated state. While we did not examine the taxonomic composition of the phytoplankton blooms that occurred in our study basins it was evident based on visual observations that they were dominated by cyanobacteria. Similarly, Dong et al. (2014) also found a shift to cyanobacteria after removal of submerged macrophytes.

combination with anoxic conditions would be expected to enhance methanogenesis resulting in increased CH4 emissions. This is also supported by the fact that pelagic CH4 emissions were the lowest in UCWs relative to the treated and untreated CSRBs, which both had significantly higher algal biomass. The measured CH4 flux in our study for treated and untreated CSRBs (total basin flux) were on average almost double the fluxes reported for constructed wetlands used for treating wastewater (McPhillips and Walter, 2015), while those in the UCWs were comparable. However, when looking at CH4 emissions from constructed wetlands based on wastewater sources, the emissions from our UCWs are generally lower compared to those treating domestic wastewater and dairy farm wastewater but much higher than those treating agricultural runoff. 4.2.3. N2O N2O emissions were lower in the UCWs compared to the CSRBs, especially during the post treatment phase. These differences are potentially explained by the higher DIN concentrations in the CSRBs relative to the UCWs (Table 1). As NO3– concentrations increase, denitrification rates increase (Beaulieu et al., 2011) which in turn has been reported to increase the emission ratio of N2O:N2 (Silvennoinen et al., 2008). Conversely, emergent and submerged vegetation and their associated epiphytic communities are known to enhance the efficiency of nitrate removal in wetlands (Weisner et al., 1994) and may potentially limit the production of N2O. Given the relatively high methane emissions measured across CSRBs and UCWs we expect that N2O emissions are likely limited due to anaerobic conditions. The N2O emissions from CSRBs measured in our study are similar to those reported for stormwater detention basins (McPhillips and Walter, 2015) and constructed wetlands use for treating domestic and synthetic wastewater (Mander et al., 2014a), but much lower than those reported for constructed wetlands treating municipal wastewater (Søvik et al., 2006). N2O emissions from the UCWs was generally lower than those reported in the literature for constructed wetlands (Mander et al., 2014b; McPhillips and Walter, 2015; Søvik et al., 2006) and restored prairie wetlands (Badiou et al., 2011) but similar to those measured in intact prairie pothole wetlands (Badiou et al., 2011).

4.2. Daily and cumulative GHG emissions 4.2.1. CO2 Daily CO2 emissions in our study were highest in the UCWs and lowest in the treated CSRBs, however CO2 emissions increased from the pre to post treatment period in all three basins. The CO2 emissions measured in our study were much lower than those reported for constructed wetlands treating wastewater (Mander et al., 2014b; Teiter and Mander, 2005) and for duckweed ponds used for stormwater treatment (Dai, 2014), but were similar to CO2 emissions reported for shallow temperate lakes (Trolle et al., 2012). The lower CO2 emissions measured in our CSRBs are likely due to the dominance of phytoplankton in these systems relative to UCWs which had the lowest Chl-a concentrations. This is supported by Brothers et al. (2013) who concluded that regime shifts from macrophyte dominance to phytoplankton dominance enhanced carbon burial and reduced mineralization in the sediments.

4.2.4. Cumulative GHG flux Individually, the three GHGs (CO2, CH4, and N2O) we monitored seemed to be quite variable throughout the open-water season, with only CH4 changing notably in response to macrophyte removal in the treated CSRBs. However, when all three gases are expressed as a cumulative gas flux and expressed as CO2eq, it is evident that macrophyte removal in the treated CSRBs results in these basins being a greater source of GHGs relative to the untreated CSRBs and UCWs. Furthermore, regardless of the basin type and/or treatment applied, CH4 emissions explained most of the variation in cumulative GHG flux (Fig. 4). The high rates of methane production and hence overall cumulative GHG flux from the CSRBs is likely related to the high algal biomass, eutrophic conditions present in those basins. In fact we found a significant positive relationship between mean Chl-a concentrations in our study basins and cumulative CH4 flux (Fig. 5). Others have also linked enhanced productivity and eutrophication of aquatic ecosystems with increasing CH4 emissions (Davidson et al., 2015; DelSontro et al., 2018). More specifically, the dominance and occurrence of cyanobacterial blooms have been linked to enhanced CH4 emissions through the contribution of labile organic carbon and the creation of anoxic conditions (West et al., 2012; Yan et al., 2017). This is supported by our finding that at N:P molar ratios below 20:1, cumulative methane emissions in our basins increase dramatically (Fig. 6). At these ratios cyanobacteria would be expected to dominate (Smith et al., 1995) and while we did not carry out taxonomic analysis to determine cyanobacterial abundance we visually verified the occurrence of blooms in the majority of CSRBs we sampled. Conversely, blooms were never observed in the UCWs.

4.2.2. CH4 In the CSRBs, CH4 emissions were much lower in the littoral regions of the untreated basins relative to those in the treated basins. One of the main drivers of methanogenesis is the availability of an organic carbon source that can be mineralized and transformed into CH4 by microbes under anaerobic conditions when all other electron acceptors have been depleted (Laanbroek, 2010). The treatment of removing macrophytes with both a harvester and the herbicide application to eliminate submersed vegetation would have resulted in a source of new organic carbon along the sediment/water interface of the treated CSRBs associated with decomposing submersed vegetation left behind after treatment. This added organic carbon may have resulted in the increased CH4 emissions observed post treatment. Additionally, disturbance of littoral sediments has been found to enhance CH4 emissions (Bussmann, 2005) and therefore it is possible that increased methane emissions in the littoral regions of the treated CSRBs were associated with use of the mechanical harvester. However, CH4 emissions were dramatically higher in the treated CSRBs relative to the untreated CSRBs even prior to macrophyte removal. This suggests that macrophyte removal may induce a carryover effect that results in sustained increases in CH4 emissions in treated CSRBs. As mentioned earlier, shifting from a submerged macrophyte dominated state to a phytoplankton dominated state enhances carbon burial, reduces mineralization rates, and in 299

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5. Conclusions

water quality within the CSRBs and higher cumulative GHG fluxes. Our findings also highlight that the deployment of UCWs throughout the City of Winnipeg to manage stormwater in new residential areas is an attractive alternative to CSRBs based on water quality and cumulative GHG flux.

To our knowledge there has been no other examination of the effects of macrophyte removal in CSRBs on water quality performance and GHG fluxes. Our result suggest that the current treatments being applied to CSRBs in the City of Winnipeg are resulting in poor water quality conditions and the proliferation of cyanobacterial blooms. The difference in CH4 emissions and cumulative GHG flux between the treated and untreated CSRBs appears to be related to the removal of macrophytes. However, the specific mechanism is not clear as the decaying vegetation left by chemical removal, the disturbance of sediments associated with mechanical removal, and the higher productivity observed after treatment can all result in enhanced CH4 emissions. Our findings suggest that the City of Winnipeg should reconsider the macrophyte removal program that is currently in place as it results in poor

Acknowledgements The authors would like to thank Mr. Grant Mohr and other staff from the City of Winnipeg’s Water and Waste Department who provided support for sample collection and laboratory services. We would also like to thank Ainsley Chaze, Dale Boskwick, Moktar Joundi, and Asseel Ebtail for carrying out the field monitoring activities. This study was supported by the province of Manitoba’s Sustainable Development Innovation Fund.

A. Appendix See Table A1

Table A1 Location, characteristics, age and recent management history of all 15 stormwater retention basins (NWL = Normal Water Level). Basin

Latitude

Longitude

Study Treatment

Surface Area NWL (ha)

Depth NWL (m)

Volume NWL (ML)

Perimeter NWL (m)

Drainage Area (ha)

Upland Slope

Age in 2006

2006 Treatment

2005 Treatment

2004 Treatment

2–4 4–5 5–18 5–21 6–8 6–9 2–2 6–10 6–11 6–26 4–8 4–9 5–13 5–24 5–25

49.893897° 49.910850° 49.807491° 49.851042° 49.805786° 49.808844° 49.893457° 49.784582° 49.781201° 49.801910° 49.931466° 49.918531° 49.824572° 49.825706° 49.821938°

-97.307260° -97.020792° -97.088060° -97.044921° -97.166539° -97.168708° -97.317060° -97.154528° -97.154496° -97.144628° -97.042203° -97.041757° -97.135941° -97.075817° -97.073616°

Treatment Treatment Treatment Treatment Treatment Treatment Control Control Control Control Wetland Wetland Wetland Wetland Wetland

0.28 2.97 2.48 1.99 1.28 1.47 0.27 2.27 1.04

1.22 1.83 1.83 1.83 1.52 1.52 1.47 1.71 1.71 2.5 2.75 1.5 1.83 3.9 3

2.14 38.97 35.81 28.36 14.87 17.7 2.63 26.98 12.2

274 907 854 883 608 605 219 1059 532

10.33 85.85

*

*

191.54 21.2 8.93 88.73 31.8

4064 670 523 * *

156 34.62 17.98 140 40.5

7 7 7 7 7 7 7 8 8 7 5 7 7 7 7

25 21 19 19 26 26 25 35 35 7 27 22 29 3 3

Herbicideт Harvested Herbicideт Herbicideт Harvested Harvested None None None None None None None None None

Herbicide Harvested Herbicideт Herbicide Harvested Harvested None None None None None Herbicideт None None None

Herbicide Harvested Herbicide Herbicide Harvested Harvested None None None None None Herbicideт None None None

*

9.11 1.5 0.8 4.45 2.02

*

*

44.82 40.69 24.09 17.25 126.78 48.8

* No data. т Herbicide application to perimeter of wetland only.

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