Phosphorus Retention and Internal Loading in the Bay of Quinte, Lake Ontario, Using Diagenetic Modelling

Science of the Total Environment 636 (2018) 39–51

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Science of the Total Environment

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Phosphorus retention and internal loading in the Bay of Quinte, Lake Ontario, using diagenetic modelling

Phuong T.K. Doan a,d,⁎, Sue B. Watson b, Stefan Markovic a,AnqiLianga,JayGuob, Shan Mugalingam c, Jonathan Stokes a, Andrew Morley e,WeitaoZhangf, George B. Arhonditsis a, Maria Dittrich a a University of Toronto Scarborough, 1265 Military Trail, Toronto, ON M1C 1A4, Canada b Environment and Climate Change Canada, Watershed Hydrology and Ecology Research Division, Water Science and Technology, 867 Lakeshore Road, Burlington, ON L7S 1A1, Canada c Lower Trent Conservation Authority, 714 Murray Street, Trenton, ON K8V 5P4, Canada d The University of Danang-University of Science and Technology, 54 Nguyen Luong Bang, Danang, Viet Nam e Ontario Ministry of the Environment and Climate Change, Eastern Region, 1259 Gardiners Road, Unit 3, P.O. Box 22032, Kingston, ON K7M 8S5, Canada f AEML Associates LTD, Canada

HIGHLIGHTS GRAPHICAL ABSTRACT

• Internal P flux contributes significantly to P budget in the Bay of Quinte. • Dynamics of sediment P transformations were studied using diagenetic modelling. • Summer sediment P diffusive fluxes varied between 1.5 and 3.6 mg P m−2 d−1. • Diagenesis of redox sensitive and organic P forms drives substantial P diffusive flux. • Sediment P retention was dominated by apatite formation and varied between 71 and 75%.

article info abstract

Article history: Internal phosphorus (P) loading significantly contributes to hysteresis in ecosystem response to nutrient reme- Received 31 December 2017 diation, but the dynamics of sediment P transformations are often poorly characterized. Here, we applied a Received in revised form 18 April 2018 reaction-transport diagenetic model to investigate sediment P dynamics in the Bay of Quinte, a polymictic, spa- Accepted 18 April 2018 tially complex embayment of Lake Ontario, (Canada). We quantified spatial and temporal variability of sediment Available online xxxx P binding forms and estimated P diffusive fluxes and sediment P retention in different parts of the bay. Our model Editor: D. Barcelo supports the notion that diagenetic recycling of redox sensitive and organic bound P forms drive sediment P release. In the recent years, summer sediment P diffusive fluxes varied in the range of 3.2–3.6 mg P m−2 d−1 in the −2 −1 Keywords: upper bay compared to 1.5 mg P m d in the middle-lower bay. Meanwhile sediment P retention ranged be- Bay of Quinte tween 71% and 75% in the upper and middle-lower bay, respectively. The reconstruction of temporal trends of Internal phosphorus loading internal P loading in the past century, suggests that against the backdrop of reduced external P inputs, sediment Lake Ontario P exerts growing control over the lake nutrient budget. Higher sediment P diffusive fluxes since mid-20th century Reaction-transport diagenetic modelling with particular increase in the past 20 years in the shallower upper basins, emphasize limited sediment P reten- Sediments tion potential and suggest prolonged ecosystem recovery, highlighting the importance of ongoing P control measures. © 2018 Elsevier B.V. All rights reserved.

⁎ Corresponding author at: Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1265 Military Trail, ON M1C 1A4, Canada. E-mail address: [email protected].(P.T.K.Doan).

1. Introduction internal P loading and P retention in the sediments, however, have still not been unequivocally investigated. Phosphorus (P) is a major limiting nutrient in lakes and reservoirs. In One of the major challenges in numerical modelling is to effectively many of these environments, however, accelerated P loading due to ur- balance between model complexity and data availability to maximize banization, industrial activities, agricultural fertilization, and internal the model performance and minimize the underlying uncertainty nutrient recycling may lead to excessive primary productivity, algal (Grayson and Blöschl, 2000; Arhonditsis et al., 2007; Doan et al., 2015). blooms, bottom water hypoxia, and deteriorated water quality (Smith Sediment diagenesis models require a comprehensive dataset of et al., 1999; Qiu et al., 2014). The amount of P in the water column is de- vertical profiles of dissolved and solid components (Dittrich et al., termined by the balance of inputs and outputs from catchment drain- 2009). In this study we combine our field data and diagenetic modelling age, atmospheric loading, and groundwater, and also the release from with the aim to advance the quantitative understanding of sediment P and burial in the sediments. The release of P from sediments (or internal dynamics and the impact of diagenetic processes on water quality in loading) is of great concern because it can contribute significantly to the ecosystem undergoing prolonged drastic reduction of external nutrient total in-lake bioavailable P pool and can have a profound impact on the loading. The main objectives of this study are (i) to evaluate the long- trophic state and water quality (Nürnberg, 2009; McCulloch et al., 2013; term dynamics of P binding forms in the sediments, (ii) to estimate Matisoff et al., 2016). the seasonal dynamics of sediment P diffusive fluxes, and (iii) to delin- The investigation of P release and the immobilization mecha- eate the spatio-temporal trends of P sediment retention. nisms in sediments is indispensable for understanding P budgets of lakes (Dillon and Molot, 1996; Hupfer and Lewandowski, 2005; 2. Methods Dittrich et al., 2013). Internal P loading depends on the ability of sediments to retain P, the conditions of overlying water, and early P dia- 2.1. Study site genesis in sediments (Abdel-Satar and Sayed, 2010; Dittrich et al., 2013). P retention due to burial in deeper sediment layers is also a The Z-shaped Bay of Quinte is located at the northeastern shore of factor regulating algal productivity in the water column (Boers Lake Ontario, Canada, and is surrounded by an 18,604 km2 watershed. et al., 1998; Katsev et al., 2006). The bay is approximately 100 km long, covers an area of about Total P in natural waters consists of a variety of inorganic and or- 254 km2, and has a volume of 2.67 km3 (Fig. 1). The Bay of Quinte sup- ganic forms, and knowledge of their abundance, distribution, chemical ports a variety of human uses, such as a resource for drinking water, as speciation, and environmental behavior is important to understanding well as swimming, boating, and both commercial and recreational fish- P release from sediments to the water column (Karl and Björkman, ing. Historically, minimally treated wastewater from municipal sewage 2001). Inorganic forms are typically adsorbed to sediment metallic ox- treatment plants, mines, and industries is discharged directly into the ides, such as Al- or Fe-(oxy)hydroxides. Organic forms can be found in system or into the tributaries that feed the bay. Extensive remedial ef- microorganisms, detritus, humic compounds, poly-phosphates, and forts and advances in wastewater treatment since the 1970s have phospholipids (Ribeiro et al., 2008). Different P forms have distinct en- curtailed the external point-source P inputs by more than 90% (Minns vironmental behavior and varying bioavailability to aquatic organisms et al., 1986, 2011). These efforts have resulted in decreased ambient (Karl and Björkman, 2001). Detailed chemical speciation of P and its total P concentrations and reduced phytoplankton biomass volume by causal association with algal blooms, however, remains poorly charac- approximately 50% (Nicholls et al., 1986; Shimoda et al., 2016). terized and quantified (Lin et al., 2016). The Bay of Quinte consists of three morphologically distinct seg- In situ measurements or laboratory experiments to estimate fluxes ments: the upper, middle and lower bay. Historically, the shallow at the sediment-water interface (SWI), or both, are sparse and difficult upper area (mean depth of 5 m) has experienced the most severe eutro- to obtain. Furthermore, most field measurements can only represent phic conditions (Johnson and Owen, 1971; Minns et al., 1986). The bay snapshots of highly dynamic processes (Luff and Moll, 2004). In this re- deepens abruptly in the middle and lower segments to a maximum gard, diagenetic modelling is a powerful tool to provide insights into the depth of 35 m at its outflow to Lake Ontario (Fig. 1). Our model de- nature of sediment diagenesis processes at the SWI, and to generate hy- scribes the geochemistry of sediments at three different sites, based potheses about the sediment-water column coupling (Boudreau, 1999; on their trophic status and degree of impairment. The Belleville site Canavan et al., 2007; Lewis et al., 2007; McCulloch et al., 2013). This (B, 44°9′15″N, 77°20′45.00″E) is located offshore from the city of Belle- family of models has the capacity to provide the foundation for both ret- ville about 2 km from the Moira River mouth and represents conditions rospective and prospective studies in the dynamics of P in sediments in the upper bay. The Napanee site (N, 44°10′49.00″N, 77°2′25″E) is lo- (Dittrich et al., 2013; Torres et al., 2015; Gudimov et al., 2016). For in- cated offshore from the town of Deseronto proximal to the mouth of the stance, diagenetic models are used to outline retention and mobilization Napanee River, representing a transitional zone between the upper and of sediment P under different loading regimes, examine sediment re- middle bay. The Hay Bay site (HB, 44°6′25.00″N, 77°1′51″E) is located sponse to planned nutrient control strategies and help identify causes south of Ram Island in Hay Bay and represents conditions in the middle of temporal discrepancy between nutrient control measures and sedi- bay. The depths at stations B, N, and HB are 4.6 m, 5.0 m, and 15.0 m, re- ment P release on decadal time scales (e.g., Katsev et al., 2006; Katsev spectively. Upper bay stations (B and N) are well mixed throughout and Dittrich, 2013; McCulloch et al., 2013). While diagenetic modelling summer, while HB is ephemerally stratified, as a result of intrusion of enables the calculation of fluxes across the SWI, as well as concentra- cold lake Ontario bottom waters with typical temperature difference be- tions and reaction rates at a high-temporal and -spatial resolution, it is tween surface and bottom waters of 5–8°C(e.g.,Oveisy et al., 2015). Of rarely applied in water quality management studies (Smits and van the three basins, HB has the longest water retention time (154 days), Beek, 2013; Paraska et al., 2014). while those at B and N are 90 and 110 days, respectively (Oveisy et al., In the present study, we adopted McCulloch et al. (2013) model to 2015). characterize diagenetic processes in the sediments of an eutrophic system, the Bay of Quinte, Ontario, Canada. The embayment has a long his- 2.2. Field data tory of eutrophication problems, such as extensive harmful algal blooms, and heavy metals pollutants in the sediments and has been Sediment and pore-water datasets collected at stations B, N, and HB classified as an “Area of Concern” under the U.S.-Canada Great Lakes from the 2013 summer season (August) and 2014 winter season (Feb- Water Quality Agreement since 1986 (Minns et al., 2011). Recent ruary) were used to calibrate and validate the sediment diagenesis modelling analysis suggested that the Bay of Quinte receives substantial model, respectively. In brief, 6–7 cores were collected using Uwitec internal subsidies (Kim et al., 2013; Arhonditsis et al., 2016). The actual corer with polycarbonate liners 5.5 cm in diameter and 70 cm in length, P.T.K. Doan et al. / Science of the Total Environment 636 (2018) 39–51 41

Fig. 1. Study site: (a) Location of Great Lakes in North America; (b) location of the Bay of Quinte in Lake Ontario; and (c) map of the Bay of Quinte and the three sampling locations (B, N, and HB). and the sediment cores were sealed on-site and then transferred to the mathematical descriptions of the different diagenetic reactions, and laboratory in a custom-built thermo-isolated storage box, maintained at values assigned to the associated rates are provided in the Supporting 4 °C. In the field, microsensor measurements were carried out for dis- Information (Tables 1S–4S). solved oxygen (DO), redox potential, and pH at the sediment surface Our model has been developed to study P transformations among the with high vertical resolution (0.5 mm). Vertical core splits were first vi- major P binding forms: adsorbed P, redox-sensitive Fe-P (BD-P), sually logged to identify distinct sedimentary layers. Following this step, aluminum-bound P (Al-P), apatite P, organic P including NaOH-NRP and separate cores were sectioned into 1–2 cm intervals in the top 15 cm refract-P (Figs. 1S & 2S). The modelling of P sorption capacity (adsorbed and 2–5 cm intervals thereafter. Core samples representing the same P, Table 3S, PBR1) was calculated using a modified Langmuir adsorption depth intervals from 2 to 3 cores were then combined and homogenized isotherm equation (Kopáček et al., 2005). The redox-sensitive BD-P frac- to create composite samples which were subsequently subsampled for tion was modelled based on the assumption that Fe-P is formed in the determination of porosity, dry weight, total organic matter, and P frac- presence of oxygen (Table 3S, PBR3) but will be reduced in the absence tions. The P fractionation technique that was applied in our analysis of oxygen (Table 3S, PBR4; Reed et al., 2011). The aluminum-bound Al- was based on the Psenner method (Psenner and Pucsko, 1988), as mod- P fraction (Table 3S, PBR5) was modelled based on empirical experiments ified by Rydin (2000). Peepers were applied to collect pore-water sam- ontheimpactofAlonsedimentsorptioncapacity(Kopáček et al., 2005). ples, where metal content, alkalinity, and soluble reactive phosphorus The apatite P fraction (Table 3S, PBR2) was modelled using a precipitation (SRP) have been measured. dissociation reaction (Stumm and Morgan, 1996). The organic P fraction For modelling purposes, the temperature through the sediment pro- was modelled as a portion of degradable and inert organic matter based files was treated as a constant across the SWI. Sedimentation rates were on the Redfield stoichiometric composition. determined using excess 210Pb activity analyzed by gamma ray spectros- The P forms separated in this sequential fractionation include loosely copy (Goldberg, 1963). One core per site was sectioned into 1 cm intervals adsorbed (labile) P (extracted with NH4Cl, NH4Cl-P), which is in equilib- down to ~60 cm and 210Pb activity in selected intervals was measured rium with dissolved P in pore-water; redox-sensitive bound P (BD-P, ex- (Fig. 5S). Calculations of sedimentation rates and ages associated with var- tracted with bicarbonate dithionite); P bound to hydrated oxides of ious depths of sediments were made according to the constant rate of sup- aluminum (Al-P, extracted with NaOH, NaOH-SRP); carbonate-bound P ply (CRS) model (Appleby and Oldfield, 1978; Appleby, 2001). (apatite-P, extracted with HCl, HCl-P), which is redox-insensitive and represents an immobilized P pool; and organic P (extracted with NaOH, NaOH- 2.3. Model description NRP). The BD-P and organic P are mostly subjected to early diagenetic transformations and play an important role in P release from sediments We used a 1-D non-steady state reactive-transport model for sedi- (Gonsiorczyk et al., 1998). Total P is the sum of all of the above fractions ment diagenesis of solid and dissolved substances, as implemented in (Psenner and Pucsko, 1988; Rydin, 2000). A detailed description of the frac- the computer program Aquasim, version 2.1e (Reichert, 1994; tionation technique has been recently presented in Dittrich et al. (2013). Reichert, 1998). The sediment depth profile of 60 cm was discretized through a vertical grid of 600 layers. Model calibration was performed 2.4. Boundary conditions with the simplex (Nelder and Mead, 1965) and secant (Ralston and Jennrich, 1978) optimization methods. The conceptual diagram of the Boundary conditions at the SWI are fixed-concentration (Dirichlet, sediment diagenesis model comprises a wide range of processes, such or first-type, boundary) for dissolved species Si: as primary and secondary redox reactions, mineral precipitation dissolution reactions, acid dissociation reactions, and P binding form reac- ðÞ¼¼ ; 0ðÞ ð Þ tions (Figs. 1S & 2S). The species considered in the model, Si z 0 t Si t 1 42 P.T.K. Doan et al. / Science of the Total Environment 636 (2018) 39–51 and fixed-fluxes (Neumann, or second-type, boundary) for solid species summer season (August). In the validation dataset, the organic matter

Xi: and SRP concentrations were distinctly higher than those used for model calibration (Fig. 7S). ∂Xi v X − D ;X ¼ F ðÞt ð2Þ sed i B i ∂z i 2.6. Calculations of P diffusive ﬂux and retention

fl where vsed is the velocity of movement of the solid phase of sediments 2.6.1. P diffusive ux relative to a coordinate system with an origin at the SWI (m d−1); and The SRP concentration profiles in pore-water are used to estimate P fl DB, Xi is the effective diffusion coefficient of particulate substance i diffusive ux from sediments into overlying water, assuming Fickian 2 −1 2 −1 (m d ). Fi is the solid substance flux (g m d )attheSWI.Nogradi- diffusion transport (Schulz and Zabel, 2000). ent is postulated for all species at the deepest sediment layer zmax: φ ∂c Prelease ¼ Dsw ð4Þ ∂c θ2 ∂z i ðÞ¼z 0 ð3Þ ∂z max −2 −1 where Prelease is the diffusive P flux from sediments (mg m d ); C is −3 where C is the concentrations of solid and dissolved chemical species in the concentration of dissolved P (mg m ); z is the sediment depth sediments. The measured sedimentation flux of total matter was used as (m); φ is the sediment porosity (dimensionless); represents tortuosity, the boundary conditions at the SWI (Fig. 3S; see also Fig. 5S for 210Pb un- or the degree of deviation around particles, which was calculated using θ2 − φ2 supported activity in supplementary material). The breakdown of or- empirical relationship =1 ln ( )(Boudreau, 1997); and Dsw is a ganic and inorganic components of the total sedimentation flux are molecular diffusion coefficient of SRP in pore-water, assuming sediment provided in Fig. 4S. temperature (Boudreau, 1997). The beginning of the simulations for each station was determined using measured sedimentation rates (Fig. 3S). The starting dates 2.6.2. P retention reflected the sediment depth determined as 1649, 1854, and 1871 for Sediment P retention represents a fraction of the P load that is per- stations B, N, and HB, respectively (Fig. 3S). To account for the seasonal manently retained in the lake's sediments. The overall capacity of sedi- variation in sedimentation rates and lake stratification, the sedimenta- ments to retain deposited P depends on the exchange of dissolved and tion flux of organic matter, DO, and SRP concentrations at the SWI particulate P between sediment and water column and diagenetic pro- were set to mimic the likely seasonal variability over the last 10 years cesses that control the mineralization of labile P forms (redox sensitive

(Fig. 6S). That is, high values of organic matter ﬂux (XOM) and SRP con- and organic P) and formation of inert P mineral phases (e.g., apatite) centration at the SWI occurred in summer (from June to October), while (e.g., Moosmann et al., 2006). The overall output of these processes is ﬂ the seasonal lows were assigned to the winter period (from November expressed in the ratio between uxes of P burial (Fburial) and settling to May) (Fig. 6S). The boundary conditions of other variables are pro- (Fsettling)(Moosmann et al., 2006) and determines P retention in our vided in Table 5S. study: ÀÁ ðÞ% ¼ = ð Þ 2.5. Model calibration and validation Pretention 100 Fburial Fsettling 5

The model was calibrated to reproduce the vertical profiles of the The burial flux of particulate P (Fburial) from surface sediment layer various P binding forms, total P, and the levels of solid and dissolved to deeper parts of sediments is equal to accumulative P, which is calcu- −2 −1 compounds during the winter (February) of 2014. Table 6S lists all of lated by multiplying sediment accumulation rate (Sedacc,gm d ) −1 the fitted parameters for station N, a representative site for the entire with total P concentration (Pd-sed,mgg ) at stabilization depth Bay of Quinte. Equilibrium constants for fast chemical equilibria were (Slomp et al., 2013). derived from Stumm and Morgan (1996). Initial values of the reaction −2 −1 parameters were taken from the literature. In the next step parameter Fburial mg m d ¼ Sedacc Pd‐sed ð6Þ values were evaluated on the basis of potential variability within the published ranges and the quality of fitwiththemeasurementdata. The flux of P settling (F ), phosphorus settling into sediments The quality of model calibration fit for all parameters represents the settling from water column, is calculated by multiplying sediment accumulation minimum of the sum of weighted squares to the deviations between −2 −1 rate (Sedacc, gm d ) with total P content in the top layer of sedi- model outputs and measurements for all data (Reichert, 1998). The − ments, P (mg g 1)(Johnson and Nicholls, 1989; Némery et al., steps were repeated iteratively until convergence of all fitted parame- t-sed 2015). ters occurred which finally led to parameter set used in the model χ2 (Table 6S). The iterative approach minimizes for the sum of calibra- −2 −1 F mg m d ¼ Sed P ‐ ð7Þ tion variables (Reichert, 1998). The residual deviation between simu- settling acc t sed lated and measured data likely reflects lack of understanding of mixing processes which can significantly affect pH gradients (Jourabchi et al., 2005) and solute transport as well as temporal and spa- 3. Results tial heterogeneity of the sediment (e.g., Smith et al., 2011; Lewandowski and Hupfer, 2005). 3.1. Model calibration and validation Generally, model calibration (or training) does not provide much information about its predictive power, but merely examines the ability of The dataset from February 2014 (winter season) was used to cali- aspecific model structure to match a single dataset (Chapra, 1997). The brate the model, while the data collected in August 2013 (summer sea- calibration should always be followed by the predictive evaluation, son) formed the basis for model validation. Figs. 2 and 3 show the which tests the model against an independent set of data, which, ideally, observed and simulated depth profiles of solid matter and dissolved should be significantly different from the dataset used during the cali- substances at the three stations (B, N, and HB) of the Bay of Quinte in bration phase (Reckhow and Chapra, 1999). This phase is also referred February 2014. The overall trends of measured of all measured variables to as model validation (Zhang et al., 2013). In this regard, our model are reasonably well represented by model simulations, with relatively was validated against data from the Bay of Quinte during the 2013 larger systematic deviations being present between measured and P.T.K. Doan et al. / Science of the Total Environment 636 (2018) 39–51 43 simulated pH (Fig. 2). However, sharp drop of pH immediately follow- SWI and lower in the deep sediment layers (Fig. 3), decreasing from ing SWI as a first order feature of pH gradients at all stations is well 2.1 mg P g DM−1 at the SWI to 1.5 mg P g DM−1 in the deep layer at sta- reproduced by the model (Fig. 2b). DO concentrations decreased signif- tion B (Fig. 3a). Total P concentrations showed a similar decrease at sta- icantly within the uppermost millimeters of the sediments. Anoxic con- tion N, from 1.7 mg P g DM−1 at the SWI to 1.2 mg P g DM−1 in the ditions prevailed 1 cm below the SWI of stations B and N, while station deep layer (Fig. 3b). The change in total P with sediment depth was HB was characterized by anoxic conditions below the depth of 0.5 cm steepest at station HB, decreasing from 1.8 mg P gDM−1 at the SWI and (Fig. 2c). SRP concentration was low in the oxidized surface layers and 1.0mgPgDM−1 in the deep layer (Fig. 3c). increased with sharply near SWI (Fig. 2d). Station B was characterized Adsorbed P represented the smallest fraction (0.04–0.08 mg g−1) by the highest organic matter concentration of 115 mg C g DM−1 at across the three sites (Fig. 3). In general, the BD-P and organic P concen- the SWI, which decreased to 90 mg C g DM−1 in the deep layers trations were higher at the SWI and lower in the deep layers across all (Fig. 2e). At station HB, the organic matter concentration decreased three stations (Fig. 3), and BD-P concentrations declined from from 93 mg C g DM−1 at the SWI to 67 mg C g DM−1 in the deep layers, 0.4–0.8 mg g−1 at the SWI to 0–0.2 mg g−1 in the deep layers (Fig. 3). while at station N, the concentration was 100 mg C g DM−1 at the SWI The organic P and Al-P concentrations in the sediments ranged from and93mgCgDM−1 in the deep layers (Fig. 2e). 0.2 to 0.5 mg g−1 (Fig. 3), while the apatite P fraction varied from 0.4 The model reproduced the different P fractions, such as adsorbed P, to 0.55 mg g−1 across the three sites. Overall, our model results showed redox-sensitive fraction of P (BD-P), organic P, aluminum-bound P (Al- that BD-P and organic P displayed the most significant changes with P), apatite-bound P (apatite P), and total P in the sediments of the three depth at all three stations, while adsorbed P, apatite P, and Al-P are rel- sampling sites (Fig. 3). Overall, total P concentrations were higher at the atively resilient to the diagenetic processes. BD-P was the most

Fig. 2. Measured and simulated depth proﬁles from SWI in February 2014: (a) porosity; (b) pH; (c) DO; (d) SRP; and (e) organic matter at three stations (B, N, and HB). The measured data are represented by asterisks, and the simulated results are depicted by solid lines. 44 P.T.K. Doan et al. / Science of the Total Environment 636 (2018) 39–51

B -1 3.2. P dynamics in the sediments a) P fractions (mg P g DM ) 0.0 0.4 0.8 1.2 3.2.1. Depth profiles of P binding forms over the past 70 years 0.0 The nutrient-related water quality deterioration has been recorded Adsorbed P since 1930, and eutrophic conditions prevailed in the Bay of Quinte by Adsorbed P BD-P the mid-1950s (Johnson and Hurley, 1986). The control of water pollu- -0.1 BD-P tion in the Bay of Quinte began in the 1970s, with strategies mainly in- Organic P Organic P volving the mitigation of external nutrient loads (Minns et al., 1986; Al-P Minns et al., 2011). Dreissenid colonization was documented after the Al-P Depth (m) -0.2 Apatite P mid-1990s, which led to a distinct increase in water transparency and Apatite P macrophyte beds, which remain one of the predominant features in Total P Total P the nearshore zone (Nicholls and Carney, 2011). In this study, our -0.3 model results examined the average sediment-depth profiles of P binding forms during the summer season (from June to October) in the years 0.0 0.6 1.2 1.8 2.4 1940, 1970, 1986, 2000, and 2014 (Figs. 4–6). Total P (mg P g DM-1) Depth profiles of P binding forms over the past 70 years show a decrease in sediment total P with depth at all three stations (B, N, and HB), N -1 b) P fractions (mg P g DM ) but the relative contribution of the various P binding forms differed be- 0.0 0.4 0.8 1.2 tween the shallower sites and the deep site (Figs. 4–6). At the shallower 0.0 stations (B and N), the concentrations of P forms at the SWI followed the order of BD-P N Apatite P N Al-P N Organic P N Adsorbed P (Figs. 4 & 5). In Adsorbed Adsorbed the deep sediment layers, the ranked order of the P form concentrations -0.1 BD-P was Apatite P N Al-P N Organic P N BD-P N Adsorbed P (Figs. 4 & 5). In BD-P Organic P contrast, at the deep HB station, the rank orders at the SWI were BD-P Organic P N Organic P N Apatite P N Al-P N Adsorbed P, and in the deep layers, Ap- Al-P Al-P N N N N Depth (m) -0.2 atite P Organic P Al-P BD-P Adsorbed P (Fig. 6). Apatite P Adsorbed P, a pool of P compounds, which is in equilibrium with dis- Apatite P Total P solved P in pore-water, was the lowest among the fractions measured Total P (Figs. 4–6). Adsorbed P concentrations at the three stations were rela- -0.3 tively stable during the past years, but they were generally lower at sta- tionsBandHBthanatstationN(i.e.,0.04mgg−1 at station B compared 0.0 0.6 1.2 1.8 2.4 to ~ 0.08 mg g−1 at station N; Figs. 4–6). BD-P, the redox-sensitive form TotalP(mgPgDM-1) of P, is a source for internal P loading (Hupfer et al., 1995; Rydin, 2000). BD-P concentrations were fairly constant in the recent past years at the HB -1 – c) P fractions (mg P g DM ) three sites (Figs. 4 6), but higher in the SWI than in the deep layers, par- 0.00.40.81.2 ticularly at station B, in the upper bay, where the SWI concentration was 0.0 highest (0.8 mg g−1; Fig. 4). Organic P sediment content was fairly high across all three sites, but did not change significantly over time. Al-P frac- Adsorbed P Adsorbed P tion was quite high and vertically constant, but displayed distinct differ- BD-P ences among the three sampling sites, ranging from 0.2 to 0.5 mg g−1. -0.1 BD-P Organic P Apatite P vertical distribution varied slightly over the past 70 years. Nota- Organic P bly, the concentrations of apatite P were lower in 1940 at stations B and N Al-P Al-P (Figs. 4 & 5), but relatively stable at station HB (Fig. 6).

Depth (m) -0.2 Apatite P Apatite P Total P 3.2.2. Long-term and seasonal dynamics of sediment P release and retention Total P Our model aimed to reproduce the spatio-temporal variability of SRP -0.3 concentrations and subsequently offer estimates of sediment P diffusive fluxes in the system over the past 70 years (Section 2.6.1). Summer P diffusive fluxes varied from 0.8 to 3.2 mg m−2 d−1 at station B, and 0.0 0.6 1.2 1.8 2.4 −2 −1 -1 from 0.4 to 3.6 mg m d at station N during the 1940–2014 period Total P (mg P g DM ) (Fig. 7a, b). In contrast, estimated summer P diffusive fluxes were approximately 1.5 mg m−2 d−1 at station HB (Fig. 7c). Interestingly, P dif- Fig. 3. Vertical profiles of total P and P fractions for three sites in February 2014. Measured fusive fluxes were low at stations B and N during the early data are indicated by symbols: triangle for adsorbed P, square for BD-P, star for organic P, −2 −1 cross for Al-P, circle for apatite P, and asterisk for total P. Model results are represented by eutrophication stages in the mid-1950s (e.g., 0.8 and 0.4 mg m d lines: adsorbed P by light-solid line, BD-P by dot line, organic P by dash line, Al-P by solid at stations B and N in 1940, respectively) and increased slightly thereaf- line, apatite P by bold-dash line, and total P by bold-solid line. ter (Fig. 7a, b). Sediment P diffusive fluxes increased dramatically at stations B and N between 2000 and 2014 (e.g., from 2.0 mg m−2 d−1 in dominant P fraction at the SWI. In the deep layers, however, apatite P 2000 to 3.5 mg m−2 d−1 in 2014 at station N; Fig. 7b), with compara- accounted for the main portion of total P. tively smaller increase at HB during this period (mean summer monthly The model was validated against data collected in August 2013 from diffusive fluxes of 1.42 mg m−2 d−1 in 2000 compared to the same stations (B, N, and HB), by testing the model under distinctly 1.58 mg m−2 d−1 in 2014) at HB station during this period (Fig. 7c). different meteorological and water quality conditions with different The P retention at stations B and N was low before the early stages of seasonal boundary conditions but the same biogeochemical parameter eutrophication in the 1950s (58% at station B and 42% at station N in values. There was a reasonable agreement between measured solid 1940) and increased after the period of external P loading reduction in matter and dissolved substances depth profiles at the three stations, the 1970s, from ~ 67% in 1970 to 75% in 1986 (Fig. 7a, b). A slight decrease and model-generated profiles shown in Figs. 7S and 8S. of P retention at these two stations was observed after 2000 (Fig. 7a, b). P.T.K. Doan et al. / Science of the Total Environment 636 (2018) 39–51 45

Fig. 4. Historical long-term dynamics of P binding forms averaged during summer at station B. The sum of these fractions represents the sediment total P concentration.

Between 2000 and 2014, it decreased from 75% to 71% at station B, and comparison, the temporal variability of pore-water SRP concentrations from 76% to 71% at station N (Fig. 7a, b). In contrast, the P retention at and P diffusive fluxes in the deep station (HB) in Hay Bay is smaller, HB station over the same period was quite high, varying between 74% with maximum and minimum diffusive fluxes of 1.6 mg P m−2 d−1 and and 76% (Fig. 7c). Our findings suggest a recent increase in internal load- 1.2 mg P m−2 d−1 in summer and winter, respectively (Fig. 7f). ing at all three basins and a decline of P retention in the two shallow basins (B and N), along with a steady trend in the deep HB basin. 4. Discussion The estimated monthly diffusive P fluxes vary from 1.7 mg P m−2 d−1 − − in the winter to 3.4 mg P m 2 d 1 in the summer of 2014 at station B, with 4.1. Trophic state of the Bay of Quinte over the past 70 years, as evidenced − − the highest value (3.55 mg P m 2 d 1)predictedinOctober(Fig. 7d). Sim- by sediment P ilarly, at the shallower sampling site near Napanee (station N), high P dif- − − fusive fluxes occurred during the summer period (3.5 mg P m 2 d 1), and The total P concentration in the sediments is influenced by many fac- − − lower fluxes occurred in the winter (2.2 mg P m 2 d 1; Fig. 7d). In tors, such as lake trophic status, sediment geochemical composition,

Fig. 5. Historical long-term dynamics of P binding forms averaged during summer at station N. The sum of these fractions represents the sediment total P concentration. 46 P.T.K. Doan et al. / Science of the Total Environment 636 (2018) 39–51

Fig. 6. Historical long-term dynamics of P binding forms averaged during summer at station HB. The sum of these fractions represents the sediment total P concentration. and diagenetic processes (Hupfer et al., 1995; Gao et al., 2005). Depend- potentially mobile pool that has not yet undergone diagenetic transfor- ing on the lake trophic state, sediment P exhibits one of the three pro- mation, and thus is temporarily stored in the sediments (Hupfer and ﬁles: a) an increase with depth indicating diagenetic sequestration Lewandowski, 2005; Rydin et al., 2011). The depth where P content (oligotrophic) b) rapid decrease with depth at surface and constant reaches constant value is controlled by many processes, including sedi- values in deeper sediments (eutrophic lakes) and c) constant P concen- ment accumulation, external inputs, internal P recycling, and physical trations (mesotrophic). In eutrophic lakes, the difference between P mixing (i.e., wind/wave resuspension and bioturbation) (Søndergaard content depleted deep layers and enriched surface represents a et al., 1996; Weyhenmeyer et al., 1997). Below the stabilization depth,

Fig. 7. Averaged annual summer P diffusive ﬂuxes and sediment P retention: (a) station B; (b) station N; and (c) HB station; Seasonal dynamics of sediment P release during 2014 reference year: (d) station B; (e) station N; and (f) HB station. P.T.K. Doan et al. / Science of the Total Environment 636 (2018) 39–51 47

P remains permanently buried in the deep sediments (Rydin, 2000; 2010). In the summer, oxygen supply from overlying water is often re- Häkanson, 2003). duced, temperature is higher, and metabolic rates are increased; there- Based on our sediment P depth profiles in the Bay of Quinte over the fore, the intensive organic matter degradation throughout the iron past 70 years, we estimated the slopes of the linear function of total P reduction zone reduces the Fe-(oxy)hydroxide layer thickness and in- with sediment depth, along with the stabilization depth for each station creases P mobility in shallow eutrophic systems (Smith et al., 2011). (Table 1). The vertical profiles of the P binding forms are indicative of a Moreover, the location of the redox front, defined by the transition decrease of total P with sediment depth at the three sites over the last from oxic to suboxic conditions, is strongly affected by physical, chemi-

70 years (Figs. 4–6). The negative linear slopes suggest persistent prev- cal, and biological factors controlling O2 supply. For example, the sedi- alence of eutrophic conditions in all three basins of the bay. The differ- ment bioturbation is more intense with higher temperature, stronger ence between the total P concentration at the SWI and the light intensity, and elevated productivity (Brönmark and Hansson, stabilization depth (or the potentially mobile P) was the highest at sta- 2005). Diffusive P fluxes can thus be higher during summer than in win- tion B, whereas the lowest mobile P estimate was recorded at station ter months. This was also observed and confirmed in Mona Lake and HB. Furthermore, at site B, it is also interesting to note that the stabiliza- Lake Simcoe, where the summer diffusive P fluxes were distinctly tion depth was fairly constant for most of the past years, but it has in- higher (Steinman et al., 2007; Dittrich et al., 2013). creased more rapidly in recent years (from 0.36 m in 2000 to 0.41 m Our model results indicate that P diffusive fluxeswerehigherat depth in 2014; Table 1). Moreover, the total P concentration at the shallow stations than those at deeper stations (Fig. 7). This likely reflects SWI at this same site demonstrates a moderate increase in recent relative proximity to riverine inputs of fresh particulate P as well as years, which in turn increased the difference between total P concentra- higher summer temperatures at shallower stations. Upper bay stations tions at the SWI and the stabilization depth. Thus, a combination of receive steady supply of organic matter and particulate P, due to prox- higher potentially mobile P and lower buried P currently characterizes imity to major tributaries (Trent, Moira and Napanee river), while Hay our sampling location in Belleville (Fig. 4). bay receives only minor subsidies from the watershed of much smaller In the same context, the exponential decrease of total P with sedi- Wilton Creek and some transfers from upper bay outflow (Manning, ment depth could also reflect organic P and BD-P degradation and sub- 1996; Kim et al., 2013; Arhonditsis et al., 2016). Consequently, concen- sequent release back into the water column due to the limited capacity trations of reactive P forms (BD_P and organic P) in the HB sediments of the sediments to retain mineralized P upon burial (Rydin, 2000; are lower than at two upper bay stations (Fig. 6; Figs. 4–5). On the Rydin et al., 2011; Rothe et al., 2015). In particular, the organic P concen- other hand, hypolimnetic summer temperatures are considerably trations in the deep layers of station N were remarkably lower in 1940 higher in the upper bay compared to station HB, which receives spo- (Fig. 5), which can be attributed to rapid diagenetic P mobilization radic inflows of cold lake Ontario bottom waters (difference of up to and subsequent release into the water column. The largest stabilization 5–8°C,Oveisy et al., 2015). Since lower bottom water temperature im- depth (0.6 m depth) was observed at station N during the same period. plies lower diffusive fluxes, decreased bioturbation and suppressed mi- In recent years, the stabilization depth increased from 0.26 m in 2000 to crobial organic matter mineralization, sediment P recycling is less 0.3 m in 2014 (Table 1), which coincided with a recent increase in P dif- intense at deeper station HB. Note that similar pattern is also observed fusive fluxes as well as a decrease in retention at this sampling site along the depth transect of limnologically similar stations in (Fig. 5). In contrast, the stabilization depth has been relatively constant neighbouring mesotrophic Lake Simcoe (Dittrich et al., 2013). in Hay Bay over the past 70 years (0.44–0.48 m; Table 1). Likewise, the total P concentrations at the SWI were relatively stable at the same site 4.3. Temporal trends of sediment P release and retention for most of the past years, although somewhat higher in recent years (e.g., 1.8 mg g−1 in 2014 compared to 1.6 mg g−1 in 2000). These trends Our analysis showed that sediment P diffusive fluxes have increased suggest a steady P diagenetic recycling and retention in the past, as well in Belleville and Napanee since 1978 (Fig. 7a, b), despite the significant as marginally higher P diffusive fluxes at station HB in recent years reduction of point-source loadings (Minns et al., 2011). Total P concen- (Fig. 6). trations in the water column also declined but did not follow the same trajectory, presumably influenced by many other factors, including trib- 4.2. Inter-basin comparison of seasonal P release utary loadings, sediment resuspension, and sediment P diagenetic recycling (Munawar et al., 2012; Munawar et al. 2014). On the other Our simulations of dissolved SRP profiles suggest considerable sea- hand, sediment P diffusive fluxes appear to have increased at the sonal variability of SRP concentrations in pore-water (e.g., ranging be- same sampling locations during the 2000s (Fig. 7). Along the same tween 0.005 and 0.030 mmol L−1 in 2014, Figs. 3d and 7S). SRP line of evidence, sediment P diffusive fluxes were not affected by the concentration gradients were steeper and diffusive P fluxes were ac- variability of the external P loading in the deeper Hay Bay (Fig. 7c). cordingly higher in summer than those predicted in winter in all sites. Our results are conceptually on par with the recent empirical and Diffusive P flux captures seasonal and spatial variations of physical, bio- modelling evidence that the anticipated response from the reduction logical, and chemical processes occurring in sediments and overlying of external P loading along the severity of eutrophication phenomena water (McCulloch et al., 2013). P mobilization in conjunction with de- in the Bay of Quinte is profoundly modulated by internal P recycling composition of organic matter could be stimulated by oxygen and processes (Kim et al., 2013; Arhonditsis et al., 2016). higher temperatures (Hupfer and Lewandowski, 2008; Gudasz et al., The arrival of dreissenid mussels in early 1990s likely affected sediment P dynamics (Hecky et al., 2004). In shallow nearshore areas, dreissenid colonies changed depositional patterns, intensified particu- Table 1 late matter eposition and bioavailable nutrient recycling (Howell et al., The linear slope of the function of sediment total P profiles (mg g−1) with depth (cm), and 1996; Hecky et al., 2004; Ozersky et al., 2013; Mosley and Bootsma, stabilization depth at the three stations over the past 70 years. 2015). Prior to dreissenid colonization, fine grained P associated with Station Linear slope Stabilization depth (m) clay-organic matter-iron oxide assemblages was retained in suspension Year B N HB B N HB over extended periods and largely exported to lower reaches of the Bay

1940 −0.0045 −0.0114 −0.007 0.33 0.6 0.47 of Quinte or lake Ontario (Manning, 1996). Post-colonization, dreissenid 1970 −0.005 −0.007 −0.0081 0.26 03 0.48 filtration turnover times reached between 0.01 and 10 days, far exceed- 1986 −0.0074 −0.0078 −0.0068 0.31 0.35 0.46 ing water residence time (Bailey et al., 1999). These high filtration vol- 2000 −0.0082 −0.0073 −0.0082 0.36 0.26 0.44 umes have reduced suspended matter water column residence times 2014 −0.0084 −0.0063 −0.0092 0.41 0.3 0.45 and thus effectively entrained organic and inorganic P forms from fine 48 P.T.K. Doan et al. / Science of the Total Environment 636 (2018) 39–51 grained suspended matter. Subsequent deposition of intercepted parti- that generate greater runoff, or both (Withers and Jarvie, 2008; Pfeifer cles as faeces and pseudofaeces, effectively enriches surface sediment in and Bennett, 2011; Arhonditsis et al., 2016). While many point source in- both P and organic matter (Howell et al., 1996; Ozersky et al., 2013) puts from the urbanized areas of Belleville and Napanee have been re- which in turn fuels diagenetic recycling of nutrients. Packaging of par- duced, our results suggest that the overall shift from point to non-point ticulate P with organic matter in mussel excretions creates anaerobic sources in combination with ecological changes and shallow nature of microenvironments at sediment surface which likely accelerates release these basins, have increased diagenetic recycling of sediment P and de- of redox sensitive P upon deposition (Hecky et al., 2004). Moreover, ox- creased its permanent retention. ygen depletion over mussel infested lake bed stimulates breakdown of By contrast, our modelling analysis suggests that the P retention at redox sensitive P forms (e.g., Ozersky et al., 2013; Tyner et al., 2015), the HB station has been steadily high over the past 70 years. High sedi- while anaerobic environments in mussel guts create favorable condi- mentation rates and P retention at Hay Bay may be explained by the his- tions for breakdown and release of redox sensitive P forms (Hecky torically intensive agricultural activities and deforestation in the et al., 2004). Our model captures dreissenid mussel reengineering of surrounding catchment (Minns et al., 1986; Sly, 1986), as well as the sediment P dynamics, insofar the recent increase in P diffusive fluxes deeper morphology (15 m depth) and longer water-residence time in the upper bay stations are concerned. However, similar increase (154 days) in this relatively isolated embayment (Oveisy et al., 2015). was not observed in the deeper Hay bay, suggesting that impact of The aforementioned land-use changes have increased inputs of inert P dreissenid colonization on diagenetic sediment P cycle was less pro- phases (particularly apatite) in the deep sediments, sustaining high P nounced than in upper bay sites. This is in line with findings by burial flux. This result is consistent with previous studies showing that Arhonditsis et al. (2016), who argued that macrophytes primarily mod- apatite P is a significant fraction of the repository pool in sediments ulate P dynamics in Hay bay. Alternatively, post-colonization entrap- (Dittrich et al., 2009; Hiriart-Baer et al., 2011), and high P retention oc- ment of particulate P in the upper segments of the bay and curs in the deeper parts of lakes (Boers et al., 1998; Dittrich et al., 2013). consequently reduced inflow of fresh particulate matter to Hay bay is Overall, our analysis suggests that P retention in the Bay of Quinte largely counterbalanced by amplification of diagenetic P recycling has evolved differently in the three basins, depending on P loading, caused by dreissenid activity. the ability of sediments to retain P, sedimentation rates, basin morphol- Dreissenid colonization induced precipitous decline of phytoplank- ogy, and historical land-use practices in the corresponding watersheds. ton and ultimately enabled macrophyte resurgence (Nicholls and The main P binding form that has been immobilized through diagenesis Carney, 2011). In turn, macrophyte proliferation introduced both posi- is the apatite P fraction, which is also the dominant fraction of total P in tive and negative feedback mechanisms affecting sediment P fluxes. the three studied stations of the bay. In recent years, P retention demon- Macrophytes preferred form of P acquisition through active transport strated decreasing trends in the shallow Belleville and Napanee basins of dissolved P from sediment pore water (so called nutrient pump, in the upper bay. On the other hand, in the deep Hay Bay basin, the P re- e.g., Asaeda et al., 2000), enhanced by the tendency to accumulate P be- tention has remained consistently high compared to the shallow basins yond immediate physiological needs (luxury uptake, e.g., Bini et al., over the past 70 years (Fig. 7). 2010), promotes more efficient P exchange between sediments and water column (Kim et al., 2013; Arhonditsis et al., 2016). On the other 4.4. Linking sediment diagenesis with total P in the water column hand, sediment P recycling is also indirectly modulated by macrophyte diurnal metabolic activity. For instance, daytime photosynthesis in- We used P input and output, and water column data over the creases oxygen levels close to SWI creating an oxidized barrier to P dif- 2002–2009 period from previous studies (Zhang et al., 2013; Kim fusion (Jaynes and Carpenter, 1986; Qu et al., 2003; Tian et al., 2017), et al., 2013) along with our inference of diagenetic processes to evaluate while photosynthetic pH increase supports P release through competi- the relative importance of external and internal P sources in the Bay of tive desorption of phosphate by OH– (e.g., Hupfer and Lewandowski, Quinte. Table 2 presents surface area weighted external P inputs and 2008 and references therein). In contrast, night time respiration de- transfers between different segments of the Bay of Quinte and respec- pletes hypolimnetic oxygen levels promoting P release (e.g., Bini et al., tive estimates of internal P fluxes averaged over the 2002–2009 period. 2010). Our model does not resolve the impact of these processes on The external total P (TP) inputs including the transfers downstream the overall P transfer from sediment into the water column. However, from upper to lower bay segments are 5.6 mg P m−2 d−1 at station B and combined effects of metabolic activity, growth and decay of macro- 25.1 and 23.5 mg P m−2 d−1 at stations N and HB, respectively. At the phytes likely increases the overall sediment P recycling beyond esti- same time, sediment P diffusive fluxes were 1.8 mg P m−2 d−1, 1.9 P mated diffusive P fluxes. mg m−2 d−1 and 1.4 P mg m−2 d−1, at stations B, N and HB, respectively. Another objective of our work was to evaluate how external nutrient The relative contribution of sediment P diffusive fluxes amounts to 32% loading into different basins of the Bay of Quinte could impact the cor- of external inputs at station B and 8% and 6% at stations HB. Thus, inter- responding P sediment retention and, consequently, the water quality. nal loading represents the major source of P at station B, while its rela- The low apatite P concentrations found at stations B and N during the tive contribution appears to be lower at stations N and HB due to 1940s (Figs. 4–5) suggest a low P retention (58% at B and 42% at N; significant transfer of P from the upper bay segments. The overall vol- Fig. 7a, b), which in turn reflects the less intensive agricultural activities ume of internal P loading is relatively small compared to TP inputs and lower erosion rates during the same period. According to our analysis, and thus unlikely to be the sole cause of algal blooms. However, it is there has been a temporal mismatch between the external nutrient load- mostly delivered as seasonally constrained summer and early autumn ing reduction (Minns et al., 1986) and P retention at the shallow sampling nutrient pulse (Fig. 7d,e,f) at the time when the risk of nuisance algal sites in the upper bay (Belleville and Napanee), as the latter process con- blooms is at the highest. Furthermore, diffusive sediment P fluxes in- tinued to increase from ~ 67% in 1970 to 75% in 1986 (Fig. 7a, b). We hy- crease water column SRP concentrations, contributing to summer sea- pothesize that the gradual proliferation of macrophytes in the system and son elevated SRP:TP ratios, which are recognized as one of the the morphology, history, and land-use practices of the corresponding primary factors influencing recent proliferation of toxin producing catchments could be some of the factors that shaped P retention during Microcystis algal blooms in the Bay of Quinte (Shimoda et al., 2016). that period (Dittrich et al., 2013; Gudimov et al., 2015; Tian et al., 2017). On the other hand, the decrease of P retention at the same sites after 5. Conclusions the 2000s may reflect the urban expansion at the Moira River close to the Belleville and Napanee stations (Kim et al., 2016). The increased ur- Our results suggest that the sediments are dominated by redox- banization in this region is likely to have altered the hydrological cycle sensitive P and organic P fractions, while apatite P and Al-P appear to or the inputs with less frequent but more intense precipitation events be playing a key role in the permanent P burial in the Bay of Quinte. P.T.K. Doan et al. / Science of the Total Environment 636 (2018) 39–51 49

Table 2 Appleby, P.G., Oldﬁeld, F., 1978. The calculation of lead-210 dates assuming a constant 210 – Estimation of surface area weighted average P ﬂuxes at the three stations over the rate of supply of unsupported Pb to the sediment. Catena 5:1 8. https://doi.org/ 10.1016/S0341-8162(78)80002-2. 2002–2009 period. Note that inputs (Finput)aretakenfrom(Kim et al., 2013). Arhonditsis, G.B., Qian, S.S., Stow, C.A., Lamon, E.C., Reckhow, K.H., 2007. Eutrophication

Flux/station Finput Frelease Frelease/Finput risk assessment using Bayesian calibration of process-based models: application to a mesotrophic lake. Ecol. Model. 208, 215–229. −2 −1 −2 −1 mg TP m d mg SRP m d Arhonditsis, G.B., Kim, D.K., Shimoda, Y., Zhang, W., Watson, S., Mugalingam, S., Dittrich, M., Geater, K., McClure, C., Keene, B., Morley, A., Richards, A., Long, T., Rao, Y.R., Station B 5.6 1.8 32.1% Kalinauskas, R., 2016. Integration of best management practices in the Bay of Quinte Station N 25.1 1.9 7.6% watershed with the phosphorus dynamics in the receiving water body: what do the Station HB 23.5 1.4 6.0% models predict? Aquat. Ecosyst. Health Manag. 19:1–18. https://doi.org/10.1080/ 14634988.2016.1130566. Asaeda, T., Trung, V.K., Manatunge, J., 2000. Modelling the effects of macrophyte growth Steady loss of redox-sensitive P with sediment depth without equivalent and decomposition on the nutrient budget in shallow lakes. Aquat. Bot. 68 (3), 217–237. increase in more stable apatite or Al-P, suggests a limited sediment capac- Bailey, R.C., Stewart, T.J., Schaner, T., Chase, M.E., Mitchell, J.S., Coulas, R.A., 1999. ity to permanently retain all deposited P. We show that substantial diage- Dreissenidae in Lake Ontario: impact Assessment at the whole lake bay of Quinte spa- netic P recycling has sustained eutrophication in the Bay of Quinte for tial scales. J. Great Lakes Res. 25 (3). Bini, L., Thomaz, S., Carvalho, P., 2010. Limnological effects of Egeria najas Planchon several decades, despite considerable efforts to reduce point and non- (Hydrocharitaceae) in the arms of Itaipu Reservoir (Brazil, Paraguay). Limnology 11 point source loading. This result also reinforces the tenet that the reduc- (1), 39–47. tion of external P loading may not necessarily render a prompt recovery Boers, P.C.M., Van Raaphorst, W., Van der Molen, D.T., 1998. Phosphorus retention in sediments. Eutrophication Research State-of-the Art: Inputs, Processes, Effects, Model- from eutrophication, highlighting the importance of internal P recycling ling, Management Specialist Symposium Dedicated to Lambertus Lijklema. Water processes which should be factored into expectations for full recovery. Sci. Technol. 37:pp. 31–39. https://doi.org/10.1016/S0273-1223(98)00053-5. Any attempt to reduce internal loading is likely prohibitive due to lake Boudreau, B.P., 1997. Diagenetic Models and their Implementation. Modelling Transport and Reactions in Aquatic Sediments. Springer, New York. size. However, limited application of Ca(OH)2 in eutrophication hot Boudreau, B.P., 1999. Metals and models: diagenic modelling in freshwater lacustrine sed- spots could promote precipitation of apatite and increase P burial iments. J. Paleolimnol. 22:227–251. https://doi.org/10.1023/A:1008144029134. (Dittrich et al., 2011). While this can help reduce localized internal load- Brönmark, C., Hansson, L.-A., 2005. The biology of lakes and ponds. Biology of Habitats. ing, overall management options are likely limited to continuing efforts Canavan, R.W., Van Cappellen, P., Zwolsman, J.J.G., van den Berg, G.A., Slomp, C.P., 2007. Geo- chemistry of trace metals in a fresh water sediment: field results and diagenetic model- to reduce point and non-point P sources in the watershed. ling. Sci. Total Environ. 381:263–279. https://doi.org/10.1016/j.scitotenv.2007.04.001. Our modelling analysis provided improved estimates of sediment P Chapra, S.C., 1997. Surface Water-quality Modeling. McGraw-Hill, New York (844 pp). diffusive fluxes in the eutrophic polymictic Bay of Quinte, where most Dillon, P.J., Molot, L.A., 1996. Long-term phosphorus budgets and an examination of a “ ” fi steady-state mass balance model for Central Ontario lakes. 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Dittrich, M., Chesnyuk, A., Gudimov, A., McCulloch, J., Quazi, S., Young, J., Winter, J., importance of integrating in-lake and watershed processes through Stainsby, E., Arhonditsis, G., 2013. Phosphorus retention in a mesotrophic lake management efforts, which will allow water-quality managers to target under transient loading conditions: insights from a sediment phosphorus binding specific time periods or regions associated with high loadings, and to form study. Water Res. 47:1433–1447. https://doi.org/10.1016/j.watres.2012.12.006. Doan, P.T.K., Némery, J., Schmid, M., Gratiot, N., 2015. Eutrophication of turbid tropical address pressing water-quality issues more effectively in the area. reservoirs: scenarios of evolution of the reservoir of Cointzio, Mexico. Eco. Inform. 29:192–205. https://doi.org/10.1016/j.ecoinf.2015.01.006. Acknowledgements Gao, L., Zhou, J.M., Yang, H., Chen, J., 2005. Phosphorus fractions in sediment profiles and their potential contributions to eutrophication in Dianchi Lake. Environ. Geol. 48: 835–844. https://doi.org/10.1007/s00254-005-0131-y. This project was funded by the Great Lakes Sustainability Fund Goldberg, E.D., 1963. Geochronology with 210Pb, Radioactive Dating. International (GCXE17P158), Ontario Ministry of the Environment and Climate Atomic Energy Agency, Vienna, pp. 121–131. Change (1402721), and Lower Trent Conservation Authority awarded Gonsiorczyk, T., Casper, P., Koschel, R., 1998. Phosphorus binding forms in the sediment of an oligotrophic and an eutrophic hardwater lake of the Baltic district (Germany). to MD, University of Toronto Scarborough. We are thankful to the gen- WaterSci.Technol.37(3),51–58. erous support by the Environment and Climate Change Canada, Lower Grayson, R.B., Blöschl, G. (Eds.), 2000. Spatial Patterns in Catchment Hydrology: Observa- Trent Conservation Authority, Bay of Quinte Remediation Action Plan tions and Modelling. 355-367. Cambridge University Press, Cambridge, UK. fi Gudimov, A., Kim, D.-K., Young, J.D., Palmer, M.E., Dittrich, M., Winter, J.G., Stainsby, E., Of ce, Ontario Ministry of the Environment and Climate Change, and Arhonditsis, G.B., 2015. Examination of the role of dreissenids and macrophytes in Quinte Conservation Association. Funding for this study was also pro- the phosphorus dynamics of Lake Simcoe, Ontario, Canada. Eco. Inform. 26, 36–53. vided by the Mitacs-Accelerate Graduate Research Internship Program Gudimov, A., McCulloch, J., Chen, J., Doan, P., Arhonditsis, G., Dittrich, M., 2016. Modelling the interplay between Deepwater oxygen dynamics and sediment diagenesis in a through a postdoctoral fellowship (PTKD). We wish to express our ap- hard-water mesotrophic lake. Eco. 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PHOSPHORUS RETENTION AND INTERNAL LOADING IN THE BAY OF QUINTE, LAKE ONTARIO, USING DIAGENETIC MODELLING

Supplementary Material

Phuong T. K. Doan1,4*, Sue B. Watson2, Stefan Markovic1, Anqi Liang1, Jay Guo2, Shan Mugalingam3, Jonathan Stokes1, Andrew Morley5, Weitao Zhang6, George B. Arhonditsis1, Maria Dittrich1

1 University of Toronto Scarborough, 1265 Military Trail, Toronto, ON, M1C 1A4, Canada, 2 Environment and Climate Change Canada, Watershed Hydrology and Ecology Research Division, Water Science and Technology, 867 Lakeshore Road, Burlington, ON, L7S 1A1, Canada, 3 Lower Trent Conservation Authority, 714 Murray Street, Trenton, ON, K8V 5P4, Canada, 4 The University of Danang-University of Science and Technology, 54 Nguyen Luong Bang, Danang, Vietnam, 5 Ontario Ministry of the Environment and Climate Change, Eastern Region, 1259 Gardiners Road, Unit 3, P.O. Box 22032, Kingston, ON, K7M 8S5, Canada, 6 AEML Associates LTD, Canada.

*Corresponding author at: Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1265 Military Trail, ON M1C 1A4, Canada Tel: +1 416 208 2786; fax: +1 416 287 7279 Email address: [email protected] (P. Doan)

A. Reaction-Transport Diagenetic Model

The following two differential equations were used in the Aquasim non-steady state reaction-transport diagenetic model to represent solid and dissolved substances:

where Si is the concentration of dissolved substance i in pore-water (mass per volume of pore-

-3 SWI water; kg m ); Si is the concentration of dissolved substance i at the sediment-water interface

-3 (SWI), kg m ; Xi is the concentration of particulate substance i in sediments (mass per total

-3 sediment volume; kg m ); t is time (d); z (m) is the depth coordinate within the sediment (z = 0 at the SWI, positive downward orientation); DSi is the molecular diffusion coefficient of

2 -1 dissolved substance i (m d ); vsed is the velocity of movement of the solid phase of sediments

-1 relative to a coordinate system with an origin at the SWI (m d ); DB is the bioturbation

2 -1 2 -1 coefficient (m d ); DB,Xi is the effective diffusion coefficient of particulate substance i (m d ); rSi is the total transformation rate of dissolved substance i (mass per total sediment volume and

-1 -1 time; mg l d ); rXi is the total transformation rate of particulate substance i (mass per total

-1 -1 sediment volume and time; mg l d ); αbioirrig is the bioirrigation coefficient; is the porosity of a newly deposited sediment at the SWI; and is the sediment porosity.

The Aquasim program solves the two partial differential equations (1 and 2) by first discretizing their spatial derivatives, and then numerically integrating the resulting system of ordinary differential equations in time with the Solution of Differential Algebraic Equation

(DASSL) implementation (Petzold, 1983) of the implicit (backward differencing) variable-step, variable-order Gear integration technique (Gear, 1971).

Figure 1S: Conceptual diagram of processes included in our diagenetic reaction transport model.

The model includes a variety of geochemical reactions, such as primary and secondary redox reactions, dissolution, acid-base dissociations, and P binding forms reactions. G is a Gipps energy;

ΔG is a quantitative measure of the likelihood of a given reaction at constant temperature and pressure.

Release Sedimentation Inorganic P Organic P

Deep Water

Sediment-Water SRP Absorptive Apatite Al(OH)3 Redox OP

Interface (SWI)

- P

Sediment -

water water

Apatite Apatite

Organic P Organic Absorbed P Absorbed Pore Figure 2S: Conceptual diagram of P binding forms and their diagenetic transformations

Figure 3S: Total sedimentation fluxes at three stations of the Bay of Quinte: (a) station B; (b)

station N; and (c) station HB. Measured points are depicted by asterisks

1. State variables

The dissolved components (Oxygen, Nitrate, Manganese, Iron, Ammonium and

Ammonia, Calcium, Bicarbonate and Carbonate, Dihydrogen Phosphate, Monohydrogen

Phosphate, Hydrogen Sulfide, Sulfide, and Hydrogen and Hydroxide) and the solid components

(Inert Organic Matter, Degradable Organic Matter, Manganese Oxide, Anhydrous iron (III) oxide – hydroxide, Manganese Carbonate, Iron Bound/Redox Sensitive Phosphorus, Calcium

Carbonate, Calcium Bound Phosphorus, Aluminium Bound Phosphorus, Absorbed Phosphorus,

Iron Sulfide, Organic Phosphorus, and Inorganic Matter) were simulated in the model (Table 1S and 2S). The organic particles are characterized by the mass fractions αC, αH, αO, αN, αP, and αS for the elements C, H, O, N, P, and S, respectively. Other elements contained in organic materials are neglected. The organic particles with mass composition are presented in Table 2S.

Table 1S: State variables of the model

Dissolved components Solid components Oxygen Inert Organic Matter Nitrate Degradable Organic Matter Manganese Manganese Oxide Iron (II) Anhydrous iron (III) oxide - hydroxide Ammonium and Ammonia Manganese Carbonate Calcium Redox Sensitive Phosphorus (BD_P) Bicarbonate and Carbonate Calcium Carbonate Calcium Bound Phosphorus (Apatite P) Dihydrogen Phosphate Aluminium Bound Phosphorus (Al_P) Monohydrogen Phosphate Adsorbed P Hydrogen Sulfide Iron Sulfide Carbonate Sulfid Organic P Hydrogen and Hydroxide Inorganic Matter

Table 2S: Composition of organic components Atoms Mass fraction

-1 αC 106 0.358 gC gOM -1 αH 263 0.074 gH gOM -1 αO 110 0.496 gO gOM -1 αN 16 0.063 gN gOM -1 αP 1 0.009 gP gOM -1 αS 0 0.0 gOM Total Redfield compositiona) 3550 1 gtot gOM-1

a) Klausmeier et al. (2004)

Figure 4S: Schematic diagram for the breakdown of the total flux of settling matter

2. Model processes:

The kinetics of diagenetic reactions is also a subject worthy of its own monograph

(Brezonik, 1994). The different diagenetic reactions in the model are described in Table 3S. The primary redox reactions for organic matter bacterial degradation are established to account for gradients in redox potential among oxidants (Van Cappellen and Gaillard, 1996), which is one of the major processes driving chemical changes in sediments (Gaillard and Rabouille, 1992;

- Middelburg et al., 1997). The modelled oxidants of these reactions are oxygen (O2), nitrate (NO3

2- ), manganese oxide (XMnO2), iron hydroxides (XFeOOH), and sulfate (SO4 ) (PR1-PR5). In addition, we have incorporated the secondary redox reactions, including the oxidations of

+ ammonium (NH4 ), hydrogen sulfide (H2S), iron-hydroxides (XFeOOH), and iron-sulfides (XFeS)

(SR1-SR4). Furthermore, the mineral precipitation and dissolution reactions for carbonates

(XMnCO3, XCaCO3, XFeCO3) and iron sulfides (XFeS) are included in the model (MR1-MR4), as are the acid base equilibrium conditions for carbonic acid (H2CO3) and bicarbonate dissociation

- + 2- (HCO3 ), ammonium dissociation (NH4 ), orthophosphate dissociation (H2PO4 ), and sulphide

- dissociation (H2S, HS ) (ER1-ER7). Lastly, the P binding forms reactions are considered in the model (PBR1-PBR5). In this study, we used the P sequential fractionation method from Psenner and Pucsko (1988) as modified by Rydin (2000). With this method, the P binding forms include loosely adsorbed (labile) P (extracted with NH4Cl, NH4Cl-TP), redox-sensitive bound P

(extracted with bicarbonate dithionite, BD-TP), P bound to hydrated oxides of aluminum or iron oxides (extracted with NaOH, NaOH-SRP, Al-P), carbonates bound P (extracted with HCl, HCl-

TP, apatite P), organic bound P (extracted with NaOH, NaOH-NRP, and refractory P).

Table 3S: Diagenetic reactions in the model. Xorg indicates organic matter with the composition:

CC/12HHOO/16NN/14PP/31SS/32

Diagenetic Reactants Products Rates reactions + - - + - Xorg + O2 + H2O NH4 + HPO4 + HCO3 + H + HS PR1 - + - - + - Primary Xorg + NO3 + H2O NH4 + HPO4 + HCO3 + H + HS + N2 PR2 + + - - - 2+ redox Xorg + XMnO2 + H NH4 + HPO4 + HCO3 + HS + H2O + Mn PR3 + + - - + - 2+ reactions Xorg + X FeOOH + H NH4 + HPO4 + HCO3 + H + HS + H2O + Fe PR4 2- + - - + - Xorg + SO4 + H2O NH4 + HPO4 + HCO3 + H + HS PR5

+ - + NH4 + 2O2 NO3 + 2H + H2O SR1 Secondary 2- + H2S + 2O2 SO4 + 2H SR2 redox + 2+ 2- 8XFeOOH + H2S + 14H 8Fe + SO4 + 12H2O SR3 reactions 2+ 2- FeS + 2O2 Fe + SO4 SR4

2+ - + Mineral Mn + HCO3 XMnCO3 + H MR1 2+ - + precipitation Ca + HCO3 XCaCO3 + H MR2 2+ 2- dissolution Fe + CO3 2XFeCO3 MR3 2+ - + reactions Fe + HS XFeS + H MR4 + - H2O H + OH ER1 * - + H2CO3 HCO3 + H ER2 Acid - 2- + HCO3 CO3 + H ER3 dissociation + + NH4 NH3 + H ER4 reactions 2- - + H2PO4 HPO4 + H ER5

- + H2S HS + H ER6 HS- S2- + H+ ER7 - HPO4 XAdsorbed_P PBR1 2+ 2- + Phosphorus 3Ca + 2HPO4 XApatite_P + 4H PBR2 2+ 2- - binding forms 4Fe +4HPO4 +8HCO3 +O2 4XFe_P + 8CO2 +4XFeOOH PBR3 2+ - reactions XFe_P Fe + HPO4 PBR4 - HPO4 XAl_ P PBR5

The associated reaction rates of the different reactions in the model are described in Table

4S. The degradation of sedimentary organic matter is driven by bacterial activity and the

appropriate expression for the dependence of organic matter degradation rate on the oxidant concentration is the Monod (or Michaelis-Menten) kinetic scheme. The presence of some

- oxidants may inhibit other metabolic pathways, i.e., the oxidants O2, NO3 , MnO2, FeOOH, and

2- SO4 (Boudreau, 1997). Inhibition by oxidants is represented by an additional term in the rate equations (PR1-5, Table 3S). The secondary redox reactions such as oxidation of HS-, nitrification, formations of Fe2+ from FeOOH, and FeS are represented in the model by a biomolecular rate law with apparent rate coefficients (SR1-4). The rate expressions for precipitation and dissolution are functions of the saturation rates in the pore-water (MR1-4). All the potential effects of inhibitors and specific surface areas are incorporated into the apparent rate constants. The acid dissociation reactions are kind of reactions in diagenetic equations results from the local equilibrium assumption for fast reversible reactions (Boudreau, 1997).

Such reactions are almost invariably acid-base dissociations in pore-water (ER1-5).

Ultimately, the P diagenesis model structure demonstrates the incorporation of these P fractions into the model, along with the processes and relevant reaction rates considered. The conceptual diagram of the P diagenesis model is the implication of the formation of major P binding forms, i.e., adsorbed P, redox-sensitive (bicarbonate-dithionite) BD-P, aluminum-bound

P (Al-P), apatite P, organic P including NaOH-NRP and refract-P, and dissolved P in pore-water

(SRP) (Fig. 1S&2S).

The modelling of the sorption capacity of P by sediments (Table 3S, PBR1) was calculated using a modified Langmuir adsorption isotherm equation (Zhou et al., 2005). The apatite P fraction (Table 3S, PBR2) is modelled using a precipitation dissociation reaction

(Stumm and Morgan, 1996). The redox-sensitive Fe-P fraction (Table 3S, PBR3) is modelled based on the assumption that Fe-P is formed in the presence of oxygen (Table 3S, PBR3) and

will be reduced in the absence of oxygen (Table 3S, PBR4; Reed et al., 2011). The aluminum- bound Al-P fraction (Table 3S, PBR5) is modelled based on laboratory experiments on the impact of Al on sediment sorption capacity (Kopáček et al., 2015). The organic P is modelled as a portion of degradable and inert organic matters based on the Redfield stoichiometric composition.

Figure 5S: 210Pb unsupported activity at three Bay of Quinte stations (DPM-disintegrations per

minute)

Figure 6S: (a) The seasonal sedimentation flux of organic matter (XOM) and the concentrations of DO and SRP over a one-year period for site N in 2014; (b) these seasonal variations were considered during the last 10 years (2004-2014), e.g., for sedimentation flux of organic matter at site N.

Table 4S: Process rates of reactions in the model. Xorgfast is the concentration of rapidly degradable organic particles

Primary redox reactions

S O2 PR1 = k O2 X org fast KO2  S O2

K O2 S NO3 X org fast PR2 = k NO3 K O2  S O2 K NO3  S NO3

O2 K K NO3 X MnO2 PR 3  k MnO2 X org, fast K O2  S O2 K NO3  S NO3 K MnO2  X MnO2

K O2 K NO3 K MnO2 X FeOOH PR4  k FeOOH X org, fast K O2  S O2 K NO3  S NO3 K MnO2  X MnO2 K FeOOH  X FeOOH

K O2 K NO3 K MnO2 K FeOOH X SO4 PR5  k X org,fast SO4  K O2  S O2 K NO3  S NO3 K MnO2  X MnO2 K FeOOH  X FeOOH K SO4 X SO4

Secondary redox reactions

SR3 = kFeOOHSXFeOOHSHS

SR4 = k X S SR2 = koxi,HSSHSSOs FeSO FeS O2

Non -redox mineral precipitation-dissolution reactions

Acid dissociation reactions

   S S   S S  SHSOH  H NH3  H HS ER1  k 1  ER4  keq,N SNH4  ER6  k S   eq,w  K   K  eq,S2 H2S K   eq,w   eq,N   eq,S1 

 S S   S S  ER2  k S  H HCO3  ER7  k S  H S2  eq,1 CO2 K  eq,S1  HS K   eq,1   eq,S1 

Phosphorus binding form reactions

KAbsorbSHPO4MHPO4 푃퐵푅1 = kAbsorb Qmax 1 + KAbsorbSHPO4MHPO4

− XAbsorbed, 3 2 Sca SHPO4 KAbsorb,AlSHPO4MHPO4 푃퐵푅5 = kAbsorb,Al Qmax,Al 1000 1000 푃퐵푅2 = −4푝퐻 1 + KAbsorb,AlSHPO4MHPO4 Keq, Apatite ∗ 10 − XAl,P

Table 5S: Boundary conditions of other variables at station N.

Boundary conditions Concentrations at the SWI -1 SHCO3 Bicarbonate 0.89 mmol l

-1 SH2PO4, mean Dihydrogen phosphate, annual average 0.01 mmol l

-1 SMn Dissolved manganese 0.0004 mmol l

-1 SFe Dissolved iron 0.008 mmol l

-1 SSO4 Sulfate 0.03 mmol l

-1 SCa Dissolved calcium 1.42 mmol l

-1 SH Hydrogen ion 3.2e-5 mmol l

Fluxes at the SWI -2 -1 FMnO2 Manganese oxide, annual average 6.2e-6 mol m d -2 -1 FCaCO3 Calcium carbonate, annual average 0.02 mol m d -2 -1 FAdsorbed_P P flux of adsorbed P 1.4e-4 g m d

-2 -1 FFe_P P flux of redox-sensitive P 9.9e-4 g m d

-2 -1 Forganic P P flux of organic P 7.5e-4 g m d

-2 -1 FAl_P P flux of aluminum P 7.2e-4 g m d

-2 -1 FApatite P P flux of apatite P 13.5e-4 g m d

Table 6S: Parameters used in the diagenetic sediment model for station N. * denotes a fitted

parameter. DM and OM indicate dry matter and organic matter, respectively.

Symbol Description Value Unit

Proportional breakdown of Total Flux

Symbol Description Value Unit

* αOrg Fraction of OM 0.27

αInorg Fraction of inorganic matter, 1-αOrg 0.73

* -6 αInorg_P Fraction of inorganic P 9e

* αInorg_P_Fe-P Fraction of redox-sensitive P 0.2

* αOrg_inert Fraction of refractory OM 0.49

αdeg Fraction of degradable OM 1- αOrg_inert

αInorg_Total Fe Fraction of total settled iron 1- (αInorg_Other+ αInorg_P)

αInorg_Fe_FeOOH Fraction of settled FeOOH 1-αInorg_Fe_Other

* αInorg_Fe_Other Fraction of settled inorganic Fe, 0.99 excluding FeOOH

αInorg_P_ApatiteP Fraction of settled apatite_P 1- αInorg_P_Fe-P

* αInorg_Other Fraction of inorganic matter without 0.999 FeOOH and P

Primary redox reactions

* -1 kO2 Rate constant of OM degradation with 0.003 d oxygen PR1

* -1 kNO3 Rate constant of OM degradation with 2.7 d nitrate PR2

* -4 -1 kMnO2 Rate constant of OM degradation with 1.8e d manganese oxides PR3

* -6 -1 kFeOOH Rate constant of OM degradation with 8.3e d iron hydroxides PR4

5) -4 -1 kSO4 Rate constant of OM degradation with 1.0e d sulfate PR5

satur * -1 K O2 Half-saturation constant for OM 0.006 mmol l degradation with oxygen

Symbol Description Value Unit

satur * -1 K NO3 Half-saturation constant for OM 0.01 mmol l degradation with nitrate

satur * -1 K MnO2 Half-saturation constant for OM 0.08 mmol g degradation with manganese oxide

satur * -1 K FeOOH Half-saturation constant for OM 0.3 mmol g degradation with iron hydroxide

satur 5) -1 K SO4 Half-saturation constant for OM 0.005 mmol l degradation with sulfate

Secondary redox reactions

* -1 knitri Rate constant for nitrification SR1 0.01 d

satur * -1 K nitriNH4 Half-saturation constant for nitrification 0.05 mmol l

* -1 -1 koxiHS Rate of secondary reaction SR2 0.028 mmol l d

6) kFeOOHS Rate of secondary reaction SR3 0.1 mmol l-1 d-1

6) kFeSO Rate of secondary reaction SR4 54.79 mmol l-1 d-1

Mineral dissolution and precipitation

1) -1 -1 keqMnCO3prec Rate constant for MnCO3 precipitation, 1.4e-5 mmol l d MR1

1) -4.4 2 -2 KeqMnCO3 Equilibrium constant for MnCO3, MR1 10 mmol l

* -1 keqMnCO3diss Rate constant for MnCO3 dissolution, 0 d MR1

*) -1 -1 keqCaCO3prec Rate constant for CaCO3 precipitation, 0.001 mmol l d MR2

1) (19.87-3059/(273.15+T)- 2 -2 KeqCaCO3 Equilibrium constant for CaCO3, MR2 10 mmol l 0.04035*(273.15+T))

* -7 -1 keqCaCO3diss Rate constant for CaCO3 dissolution, 2.5e d MR2

Symbol Description Value Unit

* -5 -1 -1 keqFeCO3prec Rate constant for FeCO3 precipitation, 1.3e mmol l d MR3

1) -4.59 2 -2 KeqFeCO3 Equilibrium constant for FeCO3, MR3 10 mmol l

* -1 keqFeCO3diss Rate constant for FeCO3 dissolution, 0 d MR3

5) -1 -1 keqFeSprec Rate constant for FeS precipitation, 0.002 mmol l d MR4

5) -12.1 2 -2 KeqFeS Equilibrium constant for FeS, MR4 10 mmol l

5) -1 keqFeSdiss Rate constant for FeS dissolution, MR4 0 d

Acid base equilibrium conditions

-1 keqw* Rate constant ER1 1000 d

1) (-4470.99/(273.15+T) + 2 -2 Keqw Water dissociation constant 10 mmol l

12.0875-0.01706*(273.15+T))

* -1 keq1 Rate constant ER2 1000 d

1) (-17.843-3404.71/(273.15+T)- 2 -2 Keq1 Dissociation constant ER2 10 mmol l 0.032786*(273.15+T))

* -1 keq2 Rate constant ER3 1000 d

1) (9.494-2902.39/(273.15+T)- 2 -2 Keq2 Dissociation constant ER3 10 mmol l 0.02379*(273.15+T))

* -1 keqN Equilibrium rate constant ER4 1000 d

2) (2.891-2727/(273.15+T)) 2 -2 KeqN Dissociation constant ER4 10 mmol l

* -1 keqP Equilibrium rate constant ER5 4.72 d

1) (-3.46-219.4/(273.15+T)) 2 -2 KeqP Dissociation constant ER5 10 mmol l

* -1 keqS1 Equilibrium rate constant ER6 10000 d

1) (-0.14-1158/(273.15+T)) 2 -2 KeqS1 Dissociation constant ER6 10 mmol l

Symbol Description Value Unit

* -1 keqS2 Equilibrium rate constant ER7 10000 d

1) (-2.03-2646/(273.15+T)) 2 -2 KeqS2 Dissociation constant ER7 10 mmol l

P binding form reactions

* -1 kAbsorb Adsorption rate, PBR1 0.42 d

3) -1 KAbsorb Adsorption constant, PBR1 118.8 mg l

3) -1 Qmax Maximal P adsorption sediment 0.08 mg g capacity, PBR1

* 20.6 2 -2 KeqApatite Dissociation constant PBR2 10 mmol l

4) -4 -1 kFe-P Rate constant for Fe-P formation, PBR3 1.5e (mM d)

* -1 kdegFe-P Rate constant for Fe-P degradation, 0.00027 d PBR4

* -1 kAdsorb_Al Adsorption rate for Al-P, PBR5 0.41 d

3) -1 KAdsorb_Al Adsorption constant for Al-P, PBR5 1 mg l

7) -1 Qmax_Al Maximal P adsorption sediment 0.46 mg g capacity for Al-P, PBR5

Compaction

* -1 kθ Rate of porosity compaction 0.0004 d

(1) Stumm and Morgan (1996); (2) Clegg and Whitfield (1995); (3) Dong et al. (2011); (4) Reed

et al. (2011); (5) Dittrich et al. (2009); (6) Katsev et al. (2006); (7) Kopáček et al. (2005)

B. Model validation

The model was validated using the set of data at the same stations (B, N, and HB) in

August 2013. Validation consists of testing the model under other meteorological and water- quality conditions. Figures 6S and 7S show measured solid matter and dissolved substances depth profiles at three stations (B, N, and HB) of the Bay of Quinte from August 2013, and model-generated profiles. A fit between measurement and simulation of porosity and organic matter at the three sites was achieved (Fig. 6S a, c). A good agreement between measured and simulated DO and SRP vertical profiles was also achieved (Fig. 6S b, d) and reproduced different P fractions at the three stations (Fig. 7S).

Fiure 7S: Measured and simulated profiles in August 2013: (a) porosity; (b) DO; (c) organic matter; and (d) SRP at the three stations (B, N, and HB). The measured data are represented by asterisks, and the simulated results are depicted by lines.

B -1 a) P fractions (mg P g DM ) 0.0 0.4 0.8 1.2 0.0

-0.1

Depth (m) -0.2

-0.3

0.6 1.2 1.8 2.4 Total P (mg P g DM-1)

b) N 0.0 0.4 0.8 1.2 0.0

Adsorbed -0.1 Adsorbed BD-P BD-P Organic P Organic P

-0.2 Al-P Al-P Apatite P Apatite P Total P -0.3 Total P

0.0 0.6 1.2 1.8 2.4

c) HB 0.0 0.4 0.8 1.2 0.0

-0.1

-0.2

-0.3

0.0 0.6 1.2 1.8 2.4

Figure 8S: Total P and P fraction profiles for the three sites in August 2013. Measured data are indicated by symbols: triangle for adsorbed P, square for BD-P, star for organic P, cross for Al-P, circle for apatite P, and asterisk for total P. Model results are represented by lines: adsorbed P by light-solid line, BD-P by dot line, organic P by dash line, Al-P by solid line, apatite P by bold- dash line, and total P by bold-solid line.

References

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