Exploring the Trends in Sediment and Phosphorus Concentrations and Loads in Part of the Canadian Great Lakes Basin

Exploring the Trends in Sediment and Phosphorus Concentrations and Loads in Part of the Canadian Great Lakes Basin | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Exploring the Trends in Sediment and Phosphorus Concentrations and Loads in Part of the Canadian Great Lakes Basin Pranesh Kumar Paul, Anant Goswami, Ramesh Pall Rudra, Pradeep Kumar Goel, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4164984/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 31 May, 2024 Read the published version in Environmental Processes → Version 1 posted 6 You are reading this latest preprint version Abstract The specific objective of this study is to explore the long-term trend of total phosphorus (TP) and total suspended sediment (TSS) concentrations and loads (C/L)s in various streams/rivers in the Great Lakes Basin. This includes related statistical analyses, such as confidence intervals, to assess variability and identify cases where measures should be taken to reduce TSS and TP. Trend analysis of TSS and TP (C/L)s are performed, combining bootstrapping with the Weighted Regressions on Time, Discharge, and Season i.e., WRTDS_BT technique. The technique is used at ten selected monitoring stations of Northern Lake Erie, Eastern Lake Huron, and Lake Ontario & Niagara Peninsula in Ontario, Canada. Trend analysis over selected tributaries using flow-normalized (FN) TSS and TP (C/L)s reveals that trends in [FN-TSS] and [FN-TP] (C/L)s were highly variable, with significant decrease in a few stations. However, in most tributaries, TSS concentration levels are significantly higher than Canadian Water Quality Guidelines (CWQG) limit of 30 mg/L (following Toronto Region Conservation Authority (TRCA), Ontario) and TP concentration levels are significantly higher than the Ontario’s provincial water quality objectives (PWQO) limit of 0.03 mg/L. Measures to reduce TSS and TP is effective at five tributaries (Humber River, Don River, Saugeen River, Big Creek, Nottawasaga River). Although the drivers are not explicitly identified, potential attributions are discussed for policymakers in the study area. WRTDS_BT Trend analysis Total Phosphorus Total Suspended Sediments Lake Erie Lake Huron Lake Ontario Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Highlights Four tributaries had [FN-TSS] concentrations below CWQG limit (30 mg/L). Two tributaries had [FN-TP] concentration below PWQO limit (0.03 mg/L). Two tributaries had concentrations below both CWQG and PWQO limit. BMPs are effective at six tributaries. 1. Introduction The escalating concentrations and loads (C/L)s of phosphorus, and sediment in water bodies, such as lakes and coastal waters, is a complex and growing global concern due to their adverse impacts on water quality and environmental health (Stammler et al., 2017 ; Wang et al., 2021 ; Scavia et al., 2023 ). Phosphorus is an essential nutrient in aquatic systems, vital for various life forms. However, an excess of phosphorus in water bodies can lead to increased algal growth, causing eutrophication in lakes and reservoirs, as well as excessive periphyton growth in rivers (Wang et al., 2021 ; Scavia et al., 2023 ). Concerns associated with eutrophic water bodies include health and aesthetic issues in natural waters and drinking water sources, along with diminished levels of dissolved oxygen, adversely impacting fish and other aquatic life. While phosphorus is naturally present in some soils, significant contributions to aquatic systems can be attributed to anthropogenic sources like fertilized fields, animal waste, wastewater treatment plants, and industries utilizing phosphorus in cleaning and production processes (Nava-López et al., 2016 ; Wang et al., 2021 ; Scavia et al., 2023 ). Depending on the source, phosphorus is often linked with suspended sediments, posing additional water quality concerns (Suplee, 2021 ; Kozyrev, 2023). Not only do suspended sediments transport phosphorus, but high levels of suspended sediment can also be detrimental to aquatic life, diminish the recreational quality of water bodies, complicate water treatment, and interfere with the operation of hydraulic structures, particularly in lakes and stratified estuaries such as the Great Lakes, a series of five large lakes situated along the Canada-United States border (Akinnawo, 2023 ). In recent times, elevated phosphorus and sediment levels have been entering the Great Lakes from contributing basins on both the Canadian and American sides (EPA, 2022 ). This paper specifically focuses on the Canadian side of the basin. Excess sediment and phosphorus, primarily associated with soil erosion, agricultural runoff, and fertilizers, originate predominantly from three agriculture dominant basins in Southern Ontario, Canada: Lake Ontario & Niagara Peninsula, Northern Lake Erie, and Eastern Lake Huron. The expansion of croplands, livestock production, and new industrial developments in these basins over the past few decades has raised serious concerns about water quality in downstream waters due to increased manure and fertilizer use, as well as heightened erosion (Singh and Craswell, 2021 ). Additionally, the 2003 census report (Statistics Canada, 2003 ) indicated a projected 40% increase in the human population over the following 25 years, with significant rises in water consumption and wastewater discharge to streams is expected. This prediction aligns with the observed consequences of anthropogenic changes in Lake Ontario since European settlement (Estepp and Reavie, 2015 ). In recent times, best management practices (BMPs) have been implemented in various basins in southern Ontario to reduce nutrient losses from agricultural fields (Hanief and Laursen, 2019 ; Miele et al., 2023 ). To assess the effectiveness of ongoing and past efforts, continuous analysis of historical monitored data, such as grab sampled data is crucial. Trend analysis, specifically the Weighted Regression on Time, Discharge, and Season (WRTDS) (Hirsch et al., 2010 ; Goswami et al. 2023 ) method developed by the united States Geological Survey (USGS), is employed for this purpose. The WRTDS method, coupled with bootstrap technique (WRTDS_BT), allows for the derivation of estimates of standard errors and confidence intervals using a limited number of samples, without further sampling. The decision to use any given trend analysis procedure hinges on two major considerations: the ability of the test outputs to describe the nature and magnitude of the trend, and its accuracy in representing the level of variability in the results. Several related studies, such as those by Debues et al. (2019), and Yates et al. ( 2022 ), have been conducted and are summarized in the supplementary section SM1 (Table SM2). These studies, along with the advantages of the WRTDS_BT technique (supplementary section SM 1.2), are omitted here for brevity. The lack of comprehensive studies, coupled with limited data, and the robustness of WRTDS_BT have motivated this research to implement the methodology to compute sediment and phosphorus trends based on limited information. The specific objective of this research is to explore the long-term trend of total suspended sediment (TSS) and TP (C/L)s in various streams/rivers in the Great Lakes Basin (Ontario, Canada). This includes related statistical analyses, such as identifying confidence intervals, to assess variability and identify cases where measures should be taken to reduce TSS and TP. This study can provide valuable insights to international audiences, helping to identify areas where more intensive measures are needed to reduce TSS and TP losses below suggested limits in diverse locations. 2. Study Area and Data The study area encompasses three primary Great Lakes Basins in Southern Ontario, Canada: Lake Ontario & Niagara Peninsula, Northern Lake Erie, and Eastern Lake Huron (Fig. 1 ). The Lake Ontario & Niagara Peninsula basin, situated in south-eastern Ontario, consists of 40% forests. It boasts the largest drainage area among the selected basins, covering approximately 28,500 km 2 and draining into Lake Ontario. The Northern Lake Erie basin, situated in Southern Ontario, is predominantly characterized by agricultural row crops, constituting 60.8% of total land use (Table SM3), covering a drainage area of approximately 22,647 km 2 . The basin primarily drains into Lake Erie, with a portion along the Thames River diverting to Lake St. Clair and eventually reaching Lake Erie. Moving to the Eastern Lake Huron basin, located in South-Western Ontario, it spans a drainage area of around 15,000 km 2 , draining primarily into Lake Huron and parts of Georgian Bay. With 42.8% of its total land use dedicated to agricultural activities, the Eastern Lake Huron basin is also dominated by agriculture. This study primarily focuses on the analysis of two water quality constituents: TSS and TP at selected ten monitoring stations. The data from each monitoring station (with relevant details) are presented in Table SM4, with additional information available in the supplementary section SM2. To facilitate future analysis and enhance data monitoring policies at the selected monitoring stations, the detailed Flow Duration Curve (FDC) is provided in supplementary section SM 2.2. 3. Methodology Gauged streamflow and grab sampled TSS and TP data are used in WRTDS_BT model (The WRTDS method, coupled with bootstrap technique) to analyze flow-normalized (FN) TSS and TP (C/L)s trends. Later trend direction (s) are used to identify cases where measures should be taken to reduce TSS and TP. It is noted that in cases where no increasing trend is observed, it indicates the effectiveness of BMPs. Conversely, if at least one increasing trend is identified, it suggests that further actions should be taken. The details of WRTDS method and its computational techniques are described in Hirsch et al. ( 2010 ) and Hirsch and De Cicco ( 2015 ). We have discussed WRTDS_BT model development, for this study, in section 3.1 . More details of WRTDS_BT implementation are omitted in the main text for brevity, and have been provided in the supplementary section SM3. The brief methodology of the study (using WRTDS_BT for trend analysis) has been summarized in Fig. 2 . 3.1. Model Development Using WRTDS we estimated water-quality trends in annual mean (C/L)s between the mentioned monitoring periods at Table SM4 for each monitoring station. For a detailed explanation of WRTDS and the weighted regression approach for estimating annual mean (C/L)s see Hirsch et al. ( 2010 ) and Hirsch and De Cicco ( 2015 ). Estimating trends in WRTDS proceeds in two steps (Hirsch et al., 2010 ). First, the sample data (a concentration value coupled with a daily discharge from the day of sample collection) for a given site and parameter were used to locally fit weighted regression models using the following equation, $$\text{ln}\left(c\right)= {{\beta }}_{0}+ {{\beta }}_{1}t+ {{\beta }}_{2} \text{ln}\left(Q\right)+ {{\beta }}_{3} \text{sin}\left(2\pi t\right)+ {{\beta }}_{4} \text{cos}\left(2\pi t\right)+\epsilon$$ 1 Where, ln is the natural log, c is concentration, β n are fitted coefficients, t is time, Q is mean daily discharge, and ε is an unexplained residual. The WRTDS model employs weighted regression, allowing coefficients (β n ) to vary across the calibration-period and streamflow values. Each day, in the calibration-period, is treated individually, with Eq. ( 1 ) calibrated by weighing observations based on time, season, and discharge similarities to the calibrated day. Default values are maintained for WRTDS trend analysis functions, with optimal half window widths (window, window, windowS) determined based on default values (7, 2, 0.5 years, respectively) or site-specific considerations (Oelsner et al., 2017 ). Observations closer to the calibration-day conditions receive higher weights (Hirsch et al., 2010 ). In WRTDS_BT, 100 bootstrap replicates (M) and a block length of 200 days are set following Hirsch ( 2015 ). Trends in TP and TSS (C/L)s are analyzed using the first and last years of the monitoring period on a water-year basis (October 1st to September 30th ). The half-window width for time adjusts near the record’s beginning and end for consistent calibration-year counts. Weighted regression flexibility accommodates evolving relations between concentration and variables over time, producing daily (C/L)s that are aggregated to mean annual (C/L)s. After Eq. ( 1 ) is fitted across the calibration-period, WRTDS employs flow-normalization to estimate water quality trends. This physically based smoothing technique mitigates random streamflow variability effects on water-quality estimates, clarifying relevant changes. Random variability, being non-contributory to systematic trends, is addressed (Kumar et al., 2019 ; Murphy and Sprague, 2019 ). Utilizing block-bootstrap replicates, likelihoods of correct trend directions and 90% confidence intervals for trend magnitudes are computed using the EGRETci R-package (Hirsch et al., 2018b). 4. Results and Discussion 4.1. Trends of Total Suspended Sediments (TSS) and Total Phosphorus (TP) In this section, we present findings on the trends of TSS (Fig. 3 a, 3 b; Table SM 4a, 4b) and TP (Fig. 4 a, 4 b; Table SM 5a, 5b) using mean annual flow-normalized (FN) (C/L)s at ten selected stations in Southern Ontario. 4.1.1. Tributaries draining into Lake Ontario At the Humber River outlet, [FN-TSS] concentration exhibited an increasing trend from 1979 to the mid-1980s, stabilized or slightly decreased in the mid-1980s, then decreased again from 1986 to 1995. A slight increase occurred in 2003, followed by a stable trend until 2019 (Fig. 3 a). Conversely, the [FN-TSS] load trend steadily decreased, with a small increase in the early 1990s (Fig. 3 b). The [FN-TP] concentration trend continuously decreased, with a sudden increase in the early 2000s and a slight uptick after 2010 (Fig. 4 a). The [FN-TP] load trend decreased consistently until the late 1990s, increased till 2003, and then continuously decreased until 2019 (Fig. 4 b) (Water Quality in Ontario Report, 2012 ; TRCA, 2020 ). At the Don River outlet, both [FN-TSS] (C/L)s followed a similar pattern. From 1979 to 1985, both increased, then continuously decreased, with intermittent sudden increases (Fig. 3 a and 3 b). [FN-TSS] (C/L)s notably decreased after 1985 until the early 1990s, followed by a consistent decrease until 2019 (Fig. 3 a, 3 b). For [FN-TP] concentration, a rapid decreasing trend occurred until the early 1990s, followed by a consistent decrease until 2019 (Fig. 4 a). [FN-TP] load exhibited a continuous decrease with minor increases in between (Water Quality in Ontario Report; 2012 ; TRCA, 2020 ). In summary, both tributaries, Humber River and Don River, experienced significant decreases in [FN-TSS] (C/L)s from 1979 to 2019. For Humber River, there was an 84 mg/L concentration decrease (likelihood: 0.76, p-value: 0.50) and a 55.96 t/year load decrease (likelihood: 0.76, p-value: 0.46) (Table SM 4a, 4b). Similarly, for Don River, a 128 mg/L concentration decrease (likelihood: 0.79, p-value: 0.43) and a 36.31 t/year load decrease (likelihood: 0.69, p-value: 0.61) were observed (Table SM 4a, 4b). Regarding [FN-TP], both tributaries showed decreasing trends in (C/L)s. The concentration decrease was 0.08 mg/L (likelihood: 0.97, p-value: 0.05) and 0.39 mg/L (likelihood: 0.99, p-value: 0.05) for Humber and Don River, respectively (Table SM 5a, 5b). The load decrease was 0.05 t/year (likelihood: 0.93, p-value: 0.13) and 0.07 t/year (likelihood: 0.99, p-value: 0.05) for Humber and Don River, respectively (Table SM 5a, 5b). Although [FN-TSS] concentration for Humber River slightly exceeded the Canadian Water Quality Guidelines (CWQG) limit of 30 mg/L, the concentration at Don River remained below the CWQG limit from 2016 to 2019. However, neither station showed a [FN-TP] concentration trend below the Provincial Water Quality Objective (PWQO) level (TRCA, 2020 ). 4.1.2. Tributaries draining into Lake Erie The trends for [FN-TSS] concentration (above the CWQG limit), at Thames River at Thamesville, exhibit continuous decrease, with an exception of an increase from the mid-1980s to the early 1990s (Fig. 3 (a)). The [FN-TSS] load trend, on the other hand, shows high variability. From 1976, the [FN-TSS] load increased until the late 1980s, then decreased until 1990. There was an increase afterward until the mid-1990s, followed by a decrease until the early 2000s, a small increase for two years, mixed variation till the early 2010s, a small increase till the mid-2010s, and then a stable trend until 2019 (Fig. 3 (b)) (Upper Thames River & Lower Thames Valley Source Protection Areas, 2008; Nürnberg and LaZerte, 2015 ; Kao et al., 2022 ). As for [FN-TP] concentrations (above the PWQO limit) and loads, the trends at the location were highly variable over the entire period. [FN-TP] concentration trends increased between 1976 and the late 1990s, with a sudden increase from 1990 for a few years. After that, the trend exhibited an abrupt decrease until the mid-2000s, followed by a small increase for a year. Subsequently, the trend decreased consistently until 2019 (Fig. 4 (a)). The [FN-TP] load trend increased from 1976 until the late 1980s, with variability (a mix of increasing and decreasing trends) until the mid-1990s. Afterward, a consistent decrease in trend is visible until the mid-2000s. There was a small increase for two years, followed by a consistent decrease until 2019 (Fig. 4 (b)) (Upper Thames River & Lower Thames Valley Source Protection Areas, 2008; Nürnberg and LaZerte, 2015 ; Kao et al., 2022 ). In summary, the trends over the period 1976–2019 indicate a decrease in [FN-TSS] concentration (10 mg/L decrease, likelihood: 0.86, p-value: 0.27) and no trend for [FN-TSS] load (13.82 t/year decrease, likelihood: 0.61, p-value: 0.75). For [FN-TP], there is a decrease in both concentration (-0.07 mg/L, likelihood: 0.99, p-value: 0.05) and load (-0.18 t/year, likelihood: 0.99, p-value: 0.05) (Tables SM4, 5). At Big Otter Creek, [FN-TSS] (C/L)s trends showed stability from 2014 to 2019 before increasing from the late 2000s (Fig. 3 ). The overall trends indicate an increase in [FN-TSS] (16.9 mg/L concentration increase, likelihood: 0.74, p-value: 0.54, and 25.45 t/year load increase, likelihood: 0.84, p-value: 0.32) over the period 2002–2019 (Table SM4). Although figures suggest a narrow decreasing trend for both [FN-TP] (C/L)s, statistical values indicated no trend for both [FN-TP] C/L over Big Otter Creek tributary (concentration likelihood: 0.54, p-value: 0.90, load likelihood: 0.54, p-value: 0.92). However, [FN-TP] concentration trend showed small but abrupt changes from the late 2000s to mid-2010s (Fig. 4 , Table SM5) (Loomer, 2011 ; Stow et al. 2015 ). At Sydenham River, [FN-TSS] (C/L)s trends (2002–2019) exhibited a stable decrease from 2014 to 2019, with a small but consistent increase noticed until the mid-2010s (for concentration) and a consistent decrease from 2002 to 2009 before a consistent increase until 2019 (for load). Overall, [FN-TSS] load increased (2.63 t/year, likelihood: 0.74, p-value: 0.55) with no trend for concentration (likelihood: 0.59, p-value: 0.82) in Sydenham River from 2002 to 2019 (Fig. 3 , Table SM4). On the contrary, [FN-TP] (C/L)s consistently decreased (C/L decreased by 0.02 mg/L, likelihood: 0.76, p-value: 0.49, and 0.01 t/year, likelihood: 0.76, p-value: 0.49, respectively) at Sydenham River over the period from 2002 to 2019 (Stammler et al. 2017 ) (Fig. 4 , Table SM5) (Staton et al., 2003 ; Stammler et al. 2017 ). At Thames River at Innerkip, [FN-TSS] concentration (below CWQG limit) trend exhibited a decrease from 1988 to the late 1990s before taking a consistent increasing turn until 2019. However, [FN-TSS] load trend remained stable throughout. Besides, [FN-TP] concentration (above PWQO limit) decreased from 1988 to 1999, after which stability is visible until 2019. In addition, [FN-TP] load exhibited a consistent decrease in trend from 1988 to 2019. Overall, at Thames River at Innerkip, there was an increase in [FN-TSS] concentration trend (0.14 mg/L, likelihood: 0.69, p-value: 0.64) and no trend (likelihood: 0.61, p-value: 0.79) was visible for loads (Fig. 3 , Table SM4). Decrease in trend for both [FN-TP] (C/L)s (concentration decrease is 0.05 mg/L, likelihood: 0.93, p-value: 0.14, load decrease is 0.03 t/year, likelihood: 0.95, p-value: 0.10) was also visible (Nürnberg and LaZerte, 2015 ; Upper Thames River Watershed Report Card, 2022 ) (Fig. 4 , Table SM5). At Big Creek near Walsingham, trends for [FN-TSS] (C/L)s decreased consistently (concentration decrease is 15.60 mg/L, likelihood: 0.97 and p-value: 0.08, load decrease is 8.81 t/year, likelihood: 0.95 and p-value: 0.11) with a slight increase around the year 2010 (Fig. 3 , Table SM4). Trends for [FN-TP] (C/L)s decreased consistently (concentration decrease is 0.03 mg/L, likelihood: 0.97 and p-value: 0.05, load decrease is 0.01 t/year, likelihood: 0.97 and p-value: 0.05) from 2002 to 2019 (Fig. 4 , Table SM5). Besides, [FN-TSS] concentration trend went below the CWQG limit around the late 2000s, while [FN-TP] concentration trend touched the PWQO limit by 2019 (Lake Erie Source Protection Region Technical Team, 2008 ) (Fig. 3 , 4 ). 4.1.3. Tributaries draining into Lake Huron In the Saugeen River, [FN-TSS] concentrations (below CWQG limit) and loads decreased over the period 2002–2019, with a small and stable increase observed from the year 2010 (Fig. 3 ). Specifically, a 3.35 mg/L concentration decrease (likelihood: 0.88, p-value: 0.23) and a 13.26 t/year load decrease (likelihood: 0.90, p-value: 0.22) were reported (Saugeen Valley Source Protection Area 2015 ; Falk et al. 2021 ) ((Fig. 3 , Table SM4)). The analysis also demonstrated a decrease in [FN-TP] loads during the same period, with an abrupt decrease from 2002 to 2009 (0.01 mg/L concentration decrease, likelihood: 0.86, p-value: 0.28, and 0.03 t/year load decrease, likelihood: 0.90, p-value: 0.19) (Fig. 4 , Table SM5). [FN-TP] concentration levels consistently remained below PWQO levels from 2009 through 2019, making Saugeen River the tributary with the lowest [FN-TP] concentration magnitude among all (Fig. 4 (a)) (Saugeen Valley Source Protection Area 2015 ; Falk et al. 2021 ). In the Ausable River at Springbank, [FN-TSS] concentration trends showed a decrease with an abrupt decrease after 2013 (3.56 mg/L, likelihood: 0.81, p-value: 0.36) (above CWQG limit). However, [FN-TSS] load exhibited no trend (likelihood: 0.56, p-value: 0.86), despite a slight increase from 2010 to 2013 (Fig. 3 , Table SM4). For [FN-TP], concentration showed no trend (likelihood: 0.66, p-value: 0.69) (above PWQO limit), while the load increased by 0.0002 t/year (likelihood: 0.69, p-value: 0.61) (Skaggs et al., 1994 ; Nelson et al., 2003 ) (Fig. 4 , Table SM5). In the Nottawasaga River at Baxter, trends for both [FN-TSS] (C/L)s exhibited variability, with an overall decrease of 10.8 mg/L concentration (likelihood: 0.90, p-value: 0.21) and 11.37 t/year load (likelihood: 0.93, p-value: 0.13) (Fig. 3 , Table SM4). The decrease occurred from 2002 to 2009, followed by a small increase from 2010 to 2013, a decrease in 2014, and a consistent increase thereafter (Fig. 3 a). Notably, [FN-TSS] concentration trend followed the CWQG limit from 2010 to 2015 but exceeded it afterward (Fig. 3 a). For [FN-TP], both (C/L)s consistently decreased from 2002–2019 (overall, decrease of 0.03 mg/L concentration, likelihood: 0.95, p-value: 0.01, and 0.03 t/year load, likelihood: 0.95, p-value: 0.11) (Fig. 4 , Table SM5). [FN-TP] concentration was very close to the PWQO limit for three years before 2019 (Falk et al., 2021 ; Rutledge and Chow-Fraser, 2019 ) (Fig. 4 a). Figure 3 (a) Long-term trends of [FN-TSS] concentration across selected monitoring stations on tributaries of Southern Ontario Figure 4 (a) Long-term trends of [FN-TP] concentration across selected monitoring stations on tributaries of Southern Ontario 4.2. Spatial Pattern of [FN-TSS] and [FN-TP] Trends The spatial variation of [FN-TSS] and [FN-TP] trends, indicating increase, decrease, or no trend, across tributaries in Southern Ontario is presented to discern combined patterns TSS and TP (Fig. 5 and Table 1 ). In the selected tributaries of Lake Ontario, namely the Don and Humber rivers, both [FN-TSS] and [FN-TP] show decreasing trends in (C/L)s. A similar scenario is observed for two Lake Huron tributaries, the Saugeen and Nottawasaga rivers, with the exception of the Ausable River tributary; where, [FN-TSS] concentration increases, while [FN-TP] load decreases, and no trend is observed for [FN-TSS] load and [FN-TP] concentration. Additionally, decreasing trends are identified for both (C/L)s of [FN-TSS] and [FN-TP] in the Big Creek near Walsingham tributary of Lake Erie. Thames River at Thamesville exhibits similar results, except for a no-trend condition for [FN-TSS] load (Fig. 5 ). Furthermore, decreasing trends in [FN-TP] (C/L)s are noted at Sydenham River at Florence and Thames River at Innerkip. However, [FN-TSS] load shows an increasing trend, with no trend for concentration at Sydenham River at Florence. Conversely, the scenario is reversed for Thames River at Innerkip, where [FN-TSS] (C/L)s increase, while [FN-TP] (C/L)s show no trend. The only case no trend is observed for both [FN-TP] (C/L)s, accompanied by an increasing trend for [FN-TSS] (C/L)s, is apparent at Big Otter Creek near Calton (Fig. 5 and Table 1 ). The observations of variable trend directions have been consolidated in Table 1 , along with corresponding remarks. It is noted that in cases where no increasing trend is observed, it indicates the effectiveness of BMPs. Conversely, if at least one increasing trend is identified, it suggests that further actions should be taken. Following this evaluation, potential future steps have been identified for tributaries such as Big Otter Creek, Sydenham River, Thames River at Innerkip, and Ausable River. However, it is emphasized that detailed analysis is imperative to determine the appropriate course of action moving forward. 4.3. Discussion We identified decreasing trends in [FN-TSS] and [FN-TP] (C/L)s at 50% of the selected stations, with varying directions observed at other locations. Only two stations (Big Creek at Walsingham and Saugeen) demonstrated concentration trends below both CWQG and PWQO limits for [FN-TSS] and [FN-TP] by 2019. Additionally, two other stations (Don River and Thames River at Innerkip) exhibited [FN-TSS] concentration trends below the CWQG limit by 2019. At Nottawasaga River, [FN-TSS] concentration approached the CWQG limit in 2012 before rebounding, while [FN-TP] concentration remained close to the PWQO limit. These trend directions are summarised in Table 1 offering insights for future considerations to identify cases where measures should be taken to reduce TSS and TP. Various literature did identify that agricultural BMPs, including changes in fertilizer application, manure management, and tillage practices are responsible for decreasing trends in phosphorus in agricultural streams (Tuppad et al., 2010 ; Liu et al., 2017 ; Miele et al., 2023 ). Other contributing factors noted in literature include improvements in wastewater treatment plants (WWTP) and the removal of phosphate from detergents, combined with agricultural BMPs (Luo et al., 2011 ; Istvánovics and Honti, 2012 ; Stammler et al., 2017 ). Most of the prior research has concentrated on specific watershed or land use types to assess the impact of targeted phosphorus mitigation strategies. Notably, comprehensive studies spanning multiple watersheds with diverse land use types, such as Luo et al. ( 2011 ), Istvánovics and Honti, ( 2012 ) attributed decreasing trends in phosphorus to a multitude of factors. Unlike these large-scale investigations, studies in Ontario have linked decreasing phosphorus to distinct causes, including recovery from logging (O’Brien et al., 2013) and urbanization (Raney and Eimers, 2014 ). It's noteworthy that many studies, including those in Ontario, often drew conclusions about causal mechanisms based on circumstantial evidence, noting that reductions in phosphorus coincided with phosphorus mitigation efforts. However, the observed trends in Ontario may be linked to substantial shifts in agricultural and urban land use practices. These changes include a reduction in cattle numbers, an uptick in the adoption of conservation and no-till practices, and a transition from corn to soy crops, as documented by Smith (2015). Understanding these alterations in land use and practices is crucial in elucidating the complex dynamics contributing to the observed trends in phosphorus in Ontario. Unfortunately, detailed watershed-scale data for these changes at our sites are unavailable. Conservation and no-till practices, advocated for soil conservation and economic benefits, may contribute to observed decreasing trends in [FN-TP] in agricultural sites, as reductions in [FN-TSS] can explain such trends due to the particulate nature of stream [FN-TP] (Clark et al., 1985). However, at some sites, [FN-TP] decreased without a corresponding decrease in [FN-TSS] (Fig. 5 , Table 1 ). The Canadian Census of Agriculture data, starting in 1991, indicates a decrease in conventional tillage from 78–37% of tilled land by 2011 (Stammler et al. 2017 ). While this coincided with decreases in [FN-TP], the widespread adoption of conservation and no-till practices didn’t occur until the mid-1990s, suggesting other factors contribute to [FN-TP] decreases in agricultural or mixed watersheds. Studies in forested watersheds in central Ontario also reported decreasing trends in phosphorus since 1980, attributing these trends to long-term recovery from logging (Eimers et al., 2009; O’Brien et al., 2013; Stammler et al. 2017 ). Urban areas, subject to GLWQA mandates for phosphate removal from detergents and improved phosphorus removal from WWTP effluent, also experienced decreasing phosphorus trends. Specifically, in the Nottawasaga River, urban growth might have contributed to increased [FN-TSS] after 2012, despite effective BMPs (NVCA, 2019). Based on the evidence presented, our study does not conclusively attribute the cause of decreasing [FN-TP] to any specific mechanism, whether across southern Ontario as a whole or within individual watershed types. This indicates a pervasive cause for observed decreasing trends (Stammler et al. 2017 ). Potential factors include changes in rainfall composition or runoff timing, with acid deposition affecting soil phosphate binding capacity. Although our study area has mostly alkaline and well-buffered soils, acid rainfall could mobilize phosphate associated with carbonates (Stammler et al. 2017 ). Finally, limitations and implications of the study are discussed in the supplementary sections SM5 and SM6. 5. Conclusion In conclusion, the study provides critical information on trend dynamics (using WRTDS_BT modeling tool) in ten tributaries of Lake Ontario, Erie, and Huron. Although the drivers are not explicitly identified, potential attributions are discussed for policymakers in the study area. The precise conclusions of this study are listed below: Four tributaries reported lower [FN-TSS] concentration than the CWQG limit (30 mg/L): Don river, Thames river, Big Creek and Saugeen river. Two tributaries reported lower [FN-TP] concentration than the PWQO limit (0.03 mg/L): Big Creek and Saugeen river. At two tributaries both [FN-TSS] and [FN-TP] concentrations are below CWQG and PWQO limits: Big Creek and Saugeen river. BMPs and other management efforts are effective at five tributaries (Humber River, Don River, Big Creek, Saugeen River, Nottawasaga River). Trend-based observations for [FN-TSS] and [FN-TP] (C/L)s, provides insights for future steps and considerations (Table 1 ). This work represents a critical scientific effort to identify potential vulnerable areas for sediment and phosphorus losses. The apparaoch presented should, therefore, be used judiciously in improving management actions and policy decisions in the other part of the world. Declarations Acknowledgements -Ethical Approval: Not Applicable -Consent to Participate: We agree among ourselves to outline the roles and responsibilities towards one another throughout the whole research and publication process. -Consent to Publish: We all give consent to publish. -Authors Contributions: Pranesh Kumar Paul: Conceptualization, data management, analysis, First draft, review of draft; Anant Goswami: analysis; Ramesh Rudra: review of draft; Pradeep Kumar Goel: review of draft; Prasad Daggupati: project management and review of draft. -Funding: This research was funded by the Natural Science and Engineering Research Council of Canada Discovery Grant (#401257). -Competing Interests: There is no competing interest between us. -Availability of data and materials: Due to privacy, ethical concerns, and confidentiality agreements the supporting data cannot be made available. 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Meeting updated phosphorus reduction goals by applying best management practices in the Grand River watershed, southern Ontario. Ecological Engineering. 130: 169-175. Hirsch RM, De Cicco LA (2015) User guide to Exploration and Graphics for RivEr Trends (EGRET) and dataRetrieval: R packages for hydrologic data, Version 2.0: February 5, 2015 edn., Reston, VA, USA. https://doi.org/10.3133/tm4A10 Hirsch RM, Moyer DL, Archfield SA (2010) Weighted regressions on time, discharge, and season (WRTDS), with an application to ydenhame bay river inputs. JAWRA, 46(5): 857–880. https://doi.org/10.1111/j.1752-1688.2010.00482.x Istvánovics V, Honti M. (2012). Efficiency of nutrient management in controlling eutrophication of running waters in the Middle Danube Basin. Hydrobiologia 686, 55–71. Kao N, Mohamed M, Sorichetti RJ, Niederkorn A, van Cappellen P, Parsons CT (2022) Phosphorus retention and transformation in a dammed reservoir of the Thames River, Ontario: Impacts on phosphorus load and speciation. J. Gt. Lakes Res. 48(1): 84–96. https://doi.org/10.1016/j.jglr.2021.11.008 Kozyrev R, Umezawa Y, Yoh M (2023) Total phosphorus and phosphorus forms change in sediments along the Tone River. Front. Earth Sci. 11:1060312. Kumar S, Godrej A, Post H (2019) The value of Intensive Sampling- A comparison of Fluvial Loads. Water Resour Manag 33: 4303-4318. Lake Erie Source Protection Region Technical Team (2008). Grand River Watershed Characterization Report. Liu Y, Engel BA, Flanagan DC, Gitau MW, McMillan SK, Chaubey I (2017) A review on effectiveness of best management practices in improving hydrology and water quality: Needs and opportunities. Sci. Total Environ. 601: 580-593. 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Environ. Process. 3, 277–305. https://doi.org/10.1007/s40710-016-0145-3 Nelson M, Veliz M, Staton S, Dolmage E (2003) Species at risk. Prepared for Ausable river recovery team. Nottawasaga Valley Conservation Authority (NVCA) (2019). Nottawasaga Valley Integrated Watershed Management Plan. Nürnberg G, LaZerte B (2015) Water Quality Assessment in the Thames River Watershed – Nutrient and Sediment Sources. For: The Upper Thames River Conservation Authority, London, Ontario. Oelsner GP, Sprague LA, Murphy JC, Zuellig RE, Johnson HM, Ryberg KR, Falcone JA, Stets EG, Vec-chia AV, Riskin ML, De Cicco, LA, Mills TJ, Farmer WH (2017). Water-quality trends in the Nation’s rivers and streams, 1972–2012—data preparation, statistical methods, and trend results. U.S. Geological Survey Scientific Investigations Report 2017–5006 (136 pp.). EPA (2022) An overview of the status and trends of the Great Lakes ecosystem. State of the Great lakes 2022 report. Raney SM, Eimers MC (2014). A comparison of nutrient export at two agricultural catchments: insight into the effect of increasing urban land cover in southern Ontario. Hydrol. Process. 28, 4328–4339. Rutledge JM, Chow-Fraser P (2019) Landscape characteristics driving spatial variation in total phosphorus and sediment loading from sub-watersheds of the Nottawasaga River, Ontario. J. Environ. Manage. 234: 357-366. Saugeen Valley Source Protection Area, (2015). Approved Assessment Report for the Saugeen Valley Source Protection Area. Chapter-2: Watershed Characterization. Scavia D, Wang YC, Obenour DR (2023). Advancing freshwater ecological forecasts: harmful algal blooms in Lake Erie. Sci. Total Environ. 856, 158959. Singh B, Craswell E (2021) Fertilizers and nitrate pollution of surface and ground water: an increasingly pervasive global problem. SN Appl. Sci. 3: 51. https://doi.org/10.1007/s42452-021-04521-8 Skaggs RW, Brevé MA, Gilliam JW (1994). Hydrologic and water quality impacts of agricultural drainage∗, Critical Reviews in Environmental Science and Technology, 24(1): 1-32. Stammler KL, Taylor WD, Mohamed MN (2017) Long-term decline in stream total phosphorus concentrations: A pervasive pattern in all watershed types in Ontario. J Great Lakes Res 43(5): 930–937. https://doi.org/10.1016/j.jglr.2017.07.005 Statistics Canada (2003) Agricultural ecumene census division boundary file for the 2001 census of agriculture: Reference guide. Ottawa, Ontario: Statistics Canada. Catalogue no. 92F0175GIE Staton SK, Dextrase A, Metcalfe-Smith JL, Maio J di, Nelson M, Parish J, Kilgour B, Holm E (2003) Status and trends of Ontario’s Sydenham river ecosystem in relation to aquatic species at risk. Environ. Monit. Assess. 88: 283–310. Stow CA, Cha Y, Johnson LT, Confesor R, Richards RP (2015). Long-term and seasonal trend decomposition of Maumee River nutrient inputs to Western Lake Erie. Environ. Sci. Technol. 49: 3392–3400. https://doi.org/10.1021/es5062648 Suplee MW (2021). Determination of bioavailable phosphorus from water samples with low suspended sediment using an anion exchange resin method. MethodsX. 8, 2021, 101343. TRCA (2020). Conservation Matters. Toronto and Region Conservation Authority Annual Report. Tuppad P, Santhi C, Srinivasan R (2010). Assessing BMP effectiveness: multiprocedure analysis of observed water quality data. Environ. Monit. Assess. 170, 315–329. Upper Thames River & Lower Thames Valley Source Protection Areas, (2008). Thames-Sydenham and Region Watershed Characterization Summary Report. Upper Thames River Watershed Report Card (2022) North Woodstock. https://thamesriver.on.ca/wp-content/uploads/RC_NorthWoodstock.pdf Wang, Y.T., Zhang, T.Q., Zhao, Y.C., Ciborowski, J.J.H., Zhao, Y.M., O’Halloran, I.P., Qi, Z.M., Tan, C.S., (2021). Characterization of sedimentary phosphorus in Lake Erie and on-site quantification of internal phosphorus loading. Water Res. 188, 116525. Water Quality in Ontario Report (2012). Archived: https://www.ontario.ca/page/water-quality-ontario-report-2012 Yates AG, Brua RB, Friesen A, Reedyk S, Benoy, G (2022). Nutrient and suspended solid concentrations, loads, and yields in rivers across the Lake Winnipeg Basin: A twenty year trend assessment. 44, 101249. Additional Declarations No competing interests reported. Supplementary Files supplementaryfinal.docx Cite Share Download PDF Status: Published Journal Publication published 31 May, 2024 Read the published version in Environmental Processes → Version 1 posted Reviews received at journal 09 May, 2024 Reviewers agreed at journal 27 Apr, 2024 Reviewers invited by journal 27 Apr, 2024 Editor assigned by journal 26 Mar, 2024 Submission checks completed at journal 26 Mar, 2024 First submitted to journal 25 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4164984","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":284105541,"identity":"2a1748c3-87d6-4440-9a51-8279b1d3a851","order_by":0,"name":"Pranesh Kumar Paul","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Pranesh","middleName":"Kumar","lastName":"Paul","suffix":""},{"id":284105543,"identity":"9d113c1a-fe52-40a0-a63b-c7af27658dcd","order_by":1,"name":"Anant Goswami","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Anant","middleName":"","lastName":"Goswami","suffix":""},{"id":284105545,"identity":"e4fd2ceb-01a5-425f-9657-47d7903f65d7","order_by":2,"name":"Ramesh Pall Rudra","email":"","orcid":"","institution":"University of Guelph","correspondingAuthor":false,"prefix":"","firstName":"Ramesh","middleName":"Pall","lastName":"Rudra","suffix":""},{"id":284105547,"identity":"c7df3eac-c859-46c4-8dca-7f066e17a660","order_by":3,"name":"Pradeep Kumar Goel","email":"","orcid":"","institution":"Ontario Ministry of the Environment, Conservation and Parks","correspondingAuthor":false,"prefix":"","firstName":"Pradeep","middleName":"Kumar","lastName":"Goel","suffix":""},{"id":284105551,"identity":"2cfd7799-2e57-4b84-bc24-63a1b262af6c","order_by":4,"name":"Prasad Daggupati","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYFCCBAjFD6EsGAyI1iLZAKYkSNBicIBYLebsyY9ffm27I298I/nwa54KiTxzBuaHH/Bpsex5ZmYt2/bMcNuNtDRrnjMSxZYNbMYS+LQY3EgwM5ZsO8y47UaOmTFvm0TihgM8DAS0pH8DabHfPAOk5R9YC/MP/FpyjB9+bDucuEEix/gxbwNYCxteWyx73pQxM5x7ljzjzLM0xjnHJIoNDrOZWeDTYs6evvnjj7I7tv3tyYc/vKmxyTM43vz4Bl6HMTCwSfMwHACxwe5JYGDGpx6ihfnjD4gW5g8M8JgdBaNgFIyCUYAAAKyPUYv6RvvAAAAAAElFTkSuQmCC","orcid":"","institution":"University of Guelph","correspondingAuthor":true,"prefix":"","firstName":"Prasad","middleName":"","lastName":"Daggupati","suffix":""}],"badges":[],"createdAt":"2024-03-25 17:46:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4164984/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4164984/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s40710-024-00710-w","type":"published","date":"2024-05-31T16:05:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53754127,"identity":"c5d45233-86e8-4fbb-929c-99167a0a422d","added_by":"auto","created_at":"2024-03-29 18:56:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2608200,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing location of TSS and TP sampling stations (selected ten stations) for trend analysis. The numbers on the figure correspond to the monitoring stations numbered in Table SM4.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4164984/v1/bb040ec7ecd541c3b601bbca.png"},{"id":53751834,"identity":"b467a811-6219-4548-a007-3b6960b8409d","added_by":"auto","created_at":"2024-03-29 18:48:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":177030,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of the process followed in the study\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4164984/v1/1ea84b8decf97d8705ed51a5.png"},{"id":53751831,"identity":"1a70af9f-b6e9-4087-95d8-ed5ee97fe3af","added_by":"auto","created_at":"2024-03-29 18:48:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1904713,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) \u003c/strong\u003eLong-term trends of [FN-TSS] concentration across selected monitoring stations on tributaries of Southern Ontario\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b)\u003c/strong\u003e Long-term trends of [FN-TSS] load across selected monitoring stations on tributaries of Southern Ontario\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4164984/v1/753e779488e0ff1253914bf2.png"},{"id":53751833,"identity":"da505dbc-ea84-41d8-8ad5-b74789a4938a","added_by":"auto","created_at":"2024-03-29 18:48:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1841268,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e Long-term trends of [FN-TP] concentration across selected monitoring stations on tributaries of Southern Ontario\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b)\u003c/strong\u003e Long-term trends of [FN-TP] load across selected monitoring stations on tributaries of Southern Ontario\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4164984/v1/1619fb6884af78ef9a5cb3c2.png"},{"id":53751836,"identity":"db9329af-79e9-4e34-b98b-52d9a5d6c025","added_by":"auto","created_at":"2024-03-29 18:48:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2597213,"visible":true,"origin":"","legend":"\u003cp\u003eModelled trends in concentrations and loads total suspended sediments ([FN-TSS]) and total phosphorus ([FN-TP]) for ten river monitoring stations in the Southern Ontario. The numbers on the figure correspond to the monitoring stations numbered in Table SM4.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4164984/v1/aeaa96cea1b42fed67682436.png"},{"id":59509486,"identity":"b9cba962-2327-45d7-bd8a-e19ccf5c38c2","added_by":"auto","created_at":"2024-07-02 16:06:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11646263,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4164984/v1/af9cdde9-8811-471e-9836-85dea2cdcfa0.pdf"},{"id":53751835,"identity":"2c5620db-e7fa-4c4d-890d-61baba8c3fef","added_by":"auto","created_at":"2024-03-29 18:48:07","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":5866900,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfinal.docx","url":"https://assets-eu.researchsquare.com/files/rs-4164984/v1/ad6398814b504c62dc1a78bb.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring the Trends in Sediment and Phosphorus Concentrations and Loads in Part of the Canadian Great Lakes Basin","fulltext":[{"header":"Highlights","content":"\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003eFour tributaries had [FN-TSS] concentrations below CWQG limit (30 mg/L).\u003c/li\u003e\n \u003cli\u003eTwo tributaries had [FN-TP] concentration below PWQO limit (0.03 mg/L).\u003c/li\u003e\n \u003cli\u003eTwo tributaries had concentrations below both CWQG and PWQO limit.\u003c/li\u003e\n \u003cli\u003eBMPs are effective at six tributaries.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eThe escalating concentrations and loads (C/L)s of phosphorus, and sediment in water bodies, such as lakes and coastal waters, is a complex and growing global concern due to their adverse impacts on water quality and environmental health (Stammler et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Scavia et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Phosphorus is an essential nutrient in aquatic systems, vital for various life forms. However, an excess of phosphorus in water bodies can lead to increased algal growth, causing eutrophication in lakes and reservoirs, as well as excessive periphyton growth in rivers (Wang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Scavia et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Concerns associated with eutrophic water bodies include health and aesthetic issues in natural waters and drinking water sources, along with diminished levels of dissolved oxygen, adversely impacting fish and other aquatic life. While phosphorus is naturally present in some soils, significant contributions to aquatic systems can be attributed to anthropogenic sources like fertilized fields, animal waste, wastewater treatment plants, and industries utilizing phosphorus in cleaning and production processes (Nava-L\u0026oacute;pez et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Scavia et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Depending on the source, phosphorus is often linked with suspended sediments, posing additional water quality concerns (Suplee, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kozyrev, 2023). Not only do suspended sediments transport phosphorus, but high levels of suspended sediment can also be detrimental to aquatic life, diminish the recreational quality of water bodies, complicate water treatment, and interfere with the operation of hydraulic structures, particularly in lakes and stratified estuaries such as the Great Lakes, a series of five large lakes situated along the Canada-United States border (Akinnawo, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn recent times, elevated phosphorus and sediment levels have been entering the Great Lakes from contributing basins on both the Canadian and American sides (EPA, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This paper specifically focuses on the Canadian side of the basin. Excess sediment and phosphorus, primarily associated with soil erosion, agricultural runoff, and fertilizers, originate predominantly from three agriculture dominant basins in Southern Ontario, Canada: Lake Ontario \u0026amp; Niagara Peninsula, Northern Lake Erie, and Eastern Lake Huron. The expansion of croplands, livestock production, and new industrial developments in these basins over the past few decades has raised serious concerns about water quality in downstream waters due to increased manure and fertilizer use, as well as heightened erosion (Singh and Craswell, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Additionally, the 2003 census report (Statistics Canada, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) indicated a projected 40% increase in the human population over the following 25 years, with significant rises in water consumption and wastewater discharge to streams is expected. This prediction aligns with the observed consequences of anthropogenic changes in Lake Ontario since European settlement (Estepp and Reavie, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In recent times, best management practices (BMPs) have been implemented in various basins in southern Ontario to reduce nutrient losses from agricultural fields (Hanief and Laursen, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Miele et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To assess the effectiveness of ongoing and past efforts, continuous analysis of historical monitored data, such as grab sampled data is crucial. Trend analysis, specifically the Weighted Regression on Time, Discharge, and Season (WRTDS) (Hirsch et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Goswami et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) method developed by the united States Geological Survey (USGS), is employed for this purpose. The WRTDS method, coupled with bootstrap technique (WRTDS_BT), allows for the derivation of estimates of standard errors and confidence intervals using a limited number of samples, without further sampling.\u003c/p\u003e \u003cp\u003eThe decision to use any given trend analysis procedure hinges on two major considerations: the ability of the test outputs to describe the nature and magnitude of the trend, and its accuracy in representing the level of variability in the results. Several related studies, such as those by Debues et al. (2019), and Yates et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), have been conducted and are summarized in the supplementary section SM1 (Table SM2). These studies, along with the advantages of the WRTDS_BT technique (supplementary section SM 1.2), are omitted here for brevity. The lack of comprehensive studies, coupled with limited data, and the robustness of WRTDS_BT have motivated this research to implement the methodology to compute sediment and phosphorus trends based on limited information. The specific objective of this research is to explore the long-term trend of total suspended sediment (TSS) and TP (C/L)s in various streams/rivers in the Great Lakes Basin (Ontario, Canada). This includes related statistical analyses, such as identifying confidence intervals, to assess variability and identify cases where measures should be taken to reduce TSS and TP. This study can provide valuable insights to international audiences, helping to identify areas where more intensive measures are needed to reduce TSS and TP losses below suggested limits in diverse locations.\u003c/p\u003e"},{"header":"2. Study Area and Data","content":"\u003cp\u003eThe study area encompasses three primary Great Lakes Basins in Southern Ontario, Canada: Lake Ontario \u0026amp; Niagara Peninsula, Northern Lake Erie, and Eastern Lake Huron (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The Lake Ontario \u0026amp; Niagara Peninsula basin, situated in south-eastern Ontario, consists of 40% forests. It boasts the largest drainage area among the selected basins, covering approximately 28,500 km\u003csup\u003e2\u003c/sup\u003e and draining into Lake Ontario. The Northern Lake Erie basin, situated in Southern Ontario, is predominantly characterized by agricultural row crops, constituting 60.8% of total land use (Table SM3), covering a drainage area of approximately 22,647 km\u003csup\u003e2\u003c/sup\u003e. The basin primarily drains into Lake Erie, with a portion along the Thames River diverting to Lake St. Clair and eventually reaching Lake Erie. Moving to the Eastern Lake Huron basin, located in South-Western Ontario, it spans a drainage area of around 15,000 km\u003csup\u003e2\u003c/sup\u003e, draining primarily into Lake Huron and parts of Georgian Bay. With 42.8% of its total land use dedicated to agricultural activities, the Eastern Lake Huron basin is also dominated by agriculture.\u003c/p\u003e \u003cp\u003eThis study primarily focuses on the analysis of two water quality constituents: TSS and TP at selected ten monitoring stations. The data from each monitoring station (with relevant details) are presented in Table SM4, with additional information available in the supplementary section SM2. To facilitate future analysis and enhance data monitoring policies at the selected monitoring stations, the detailed Flow Duration Curve (FDC) is provided in supplementary section SM 2.2.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eGauged streamflow and grab sampled TSS and TP data are used in WRTDS_BT model (The WRTDS method, coupled with bootstrap technique) to analyze flow-normalized (FN) TSS and TP (C/L)s trends. Later trend direction (s) are used to identify cases where measures should be taken to reduce TSS and TP. It is noted that in cases where no increasing trend is observed, it indicates the effectiveness of BMPs. Conversely, if at least one increasing trend is identified, it suggests that further actions should be taken. The details of WRTDS method and its computational techniques are described in Hirsch et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and Hirsch and De Cicco (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). We have discussed WRTDS_BT model development, for this study, in section \u003cspan refid=\"Sec4\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e. More details of WRTDS_BT implementation are omitted in the main text for brevity, and have been provided in the supplementary section SM3. The brief methodology of the study (using WRTDS_BT for trend analysis) has been summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Model Development\u003c/h2\u003e \u003cp\u003eUsing WRTDS we estimated water-quality trends in annual mean (C/L)s between the mentioned monitoring periods at Table SM4 for each monitoring station. For a detailed explanation of WRTDS and the weighted regression approach for estimating annual mean (C/L)s see Hirsch et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and Hirsch and De Cicco (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Estimating trends in WRTDS proceeds in two steps (Hirsch et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFirst, the sample data (a concentration value coupled with a daily discharge from the day of sample collection) for a given site and parameter were used to locally fit weighted regression models using the following equation,\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\text{ln}\\left(c\\right)= {{\\beta }}_{0}+ {{\\beta }}_{1}t+ {{\\beta }}_{2} \\text{ln}\\left(Q\\right)+ {{\\beta }}_{3} \\text{sin}\\left(2\\pi t\\right)+ {{\\beta }}_{4} \\text{cos}\\left(2\\pi t\\right)+\\epsilon$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere,\u003c/p\u003e \u003cp\u003eln is the natural log,\u003c/p\u003e \u003cp\u003ec is concentration,\u003c/p\u003e \u003cp\u003eβ\u003csub\u003en\u003c/sub\u003e are fitted coefficients,\u003c/p\u003e \u003cp\u003et is time,\u003c/p\u003e \u003cp\u003eQ is mean daily discharge, and\u003c/p\u003e \u003cp\u003eε is an unexplained residual.\u003c/p\u003e \u003cp\u003eThe WRTDS model employs weighted regression, allowing coefficients (β\u003csub\u003en\u003c/sub\u003e) to vary across the calibration-period and streamflow values. Each day, in the calibration-period, is treated individually, with Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) calibrated by weighing observations based on time, season, and discharge similarities to the calibrated day. Default values are maintained for WRTDS trend analysis functions, with optimal half window widths (window, window, windowS) determined based on default values (7, 2, 0.5 years, respectively) or site-specific considerations (Oelsner et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Observations closer to the calibration-day conditions receive higher weights (Hirsch et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn WRTDS_BT, 100 bootstrap replicates (M) and a block length of 200 days are set following Hirsch (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Trends in TP and TSS (C/L)s are analyzed using the first and last years of the monitoring period on a water-year basis (October 1st to September 30th ). The half-window width for time adjusts near the record\u0026rsquo;s beginning and end for consistent calibration-year counts. Weighted regression flexibility accommodates evolving relations between concentration and variables over time, producing daily (C/L)s that are aggregated to mean annual (C/L)s.\u003c/p\u003e \u003cp\u003eAfter Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) is fitted across the calibration-period, WRTDS employs flow-normalization to estimate water quality trends. This physically based smoothing technique mitigates random streamflow variability effects on water-quality estimates, clarifying relevant changes. Random variability, being non-contributory to systematic trends, is addressed (Kumar et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Murphy and Sprague, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Utilizing block-bootstrap replicates, likelihoods of correct trend directions and 90% confidence intervals for trend magnitudes are computed using the EGRETci R-package (Hirsch et al., 2018b).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Results and Discussion","content":"\u003cdiv id=\"Sec6\"\u003e\n \u003ch2\u003e4.1. Trends of Total Suspended Sediments (TSS) and Total Phosphorus (TP)\u003c/h2\u003e\n \u003cp\u003eIn this section, we present findings on the trends of TSS (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003ea, \u003cspan\u003e3\u003c/span\u003eb; Table SM 4a, 4b) and TP (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003ea, \u003cspan\u003e4\u003c/span\u003eb; Table SM 5a, 5b) using mean annual flow-normalized (FN) (C/L)s at ten selected stations in Southern Ontario.\u003c/p\u003e\n \u003cdiv id=\"Sec7\"\u003e\n \u003ch2\u003e4.1.1. Tributaries draining into Lake Ontario\u003c/h2\u003e\n \u003cp\u003eAt the Humber River outlet, [FN-TSS] concentration exhibited an increasing trend from 1979 to the mid-1980s, stabilized or slightly decreased in the mid-1980s, then decreased again from 1986 to 1995. A slight increase occurred in 2003, followed by a stable trend until 2019 (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003ea). Conversely, the [FN-TSS] load trend steadily decreased, with a small increase in the early 1990s (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003eb). The [FN-TP] concentration trend continuously decreased, with a sudden increase in the early 2000s and a slight uptick after 2010 (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003ea). The [FN-TP] load trend decreased consistently until the late 1990s, increased till 2003, and then continuously decreased until 2019 (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003eb) (Water Quality in Ontario Report, \u003cspan\u003e2012\u003c/span\u003e; TRCA, \u003cspan\u003e2020\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eAt the Don River outlet, both [FN-TSS] (C/L)s followed a similar pattern. From 1979 to 1985, both increased, then continuously decreased, with intermittent sudden increases (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003ea and \u003cspan\u003e3\u003c/span\u003eb). [FN-TSS] (C/L)s notably decreased after 1985 until the early 1990s, followed by a consistent decrease until 2019 (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003ea, \u003cspan\u003e3\u003c/span\u003eb). For [FN-TP] concentration, a rapid decreasing trend occurred until the early 1990s, followed by a consistent decrease until 2019 (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003ea). [FN-TP] load exhibited a continuous decrease with minor increases in between (Water Quality in Ontario Report; \u003cspan\u003e2012\u003c/span\u003e; TRCA, \u003cspan\u003e2020\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eIn summary, both tributaries, Humber River and Don River, experienced significant decreases in [FN-TSS] (C/L)s from 1979 to 2019. For Humber River, there was an 84 mg/L concentration decrease (likelihood: 0.76, p-value: 0.50) and a 55.96 t/year load decrease (likelihood: 0.76, p-value: 0.46) (Table SM 4a, 4b). Similarly, for Don River, a 128 mg/L concentration decrease (likelihood: 0.79, p-value: 0.43) and a 36.31 t/year load decrease (likelihood: 0.69, p-value: 0.61) were observed (Table SM 4a, 4b). Regarding [FN-TP], both tributaries showed decreasing trends in (C/L)s. The concentration decrease was 0.08 mg/L (likelihood: 0.97, p-value: 0.05) and 0.39 mg/L (likelihood: 0.99, p-value: 0.05) for Humber and Don River, respectively (Table SM 5a, 5b). The load decrease was 0.05 t/year (likelihood: 0.93, p-value: 0.13) and 0.07 t/year (likelihood: 0.99, p-value: 0.05) for Humber and Don River, respectively (Table SM 5a, 5b). Although [FN-TSS] concentration for Humber River slightly exceeded the Canadian Water Quality Guidelines (CWQG) limit of 30 mg/L, the concentration at Don River remained below the CWQG limit from 2016 to 2019. However, neither station showed a [FN-TP] concentration trend below the Provincial Water Quality Objective (PWQO) level (TRCA, \u003cspan\u003e2020\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003e4.1.2. Tributaries draining into Lake Erie\u003c/h2\u003e\n \u003cp\u003eThe trends for [FN-TSS] concentration (above the CWQG limit), at Thames River at Thamesville, exhibit continuous decrease, with an exception of an increase from the mid-1980s to the early 1990s (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e (a)). The [FN-TSS] load trend, on the other hand, shows high variability. From 1976, the [FN-TSS] load increased until the late 1980s, then decreased until 1990. There was an increase afterward until the mid-1990s, followed by a decrease until the early 2000s, a small increase for two years, mixed variation till the early 2010s, a small increase till the mid-2010s, and then a stable trend until 2019 (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e (b)) (Upper Thames River \u0026amp; Lower Thames Valley Source Protection Areas, 2008; N\u0026uuml;rnberg and LaZerte, \u003cspan\u003e2015\u003c/span\u003e; Kao et al., \u003cspan\u003e2022\u003c/span\u003e). As for [FN-TP] concentrations (above the PWQO limit) and loads, the trends at the location were highly variable over the entire period. [FN-TP] concentration trends increased between 1976 and the late 1990s, with a sudden increase from 1990 for a few years. After that, the trend exhibited an abrupt decrease until the mid-2000s, followed by a small increase for a year. Subsequently, the trend decreased consistently until 2019 (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e (a)). The [FN-TP] load trend increased from 1976 until the late 1980s, with variability (a mix of increasing and decreasing trends) until the mid-1990s. Afterward, a consistent decrease in trend is visible until the mid-2000s. There was a small increase for two years, followed by a consistent decrease until 2019 (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e (b)) (Upper Thames River \u0026amp; Lower Thames Valley Source Protection Areas, 2008; N\u0026uuml;rnberg and LaZerte, \u003cspan\u003e2015\u003c/span\u003e; Kao et al., \u003cspan\u003e2022\u003c/span\u003e). In summary, the trends over the period 1976\u0026ndash;2019 indicate a decrease in [FN-TSS] concentration (10 mg/L decrease, likelihood: 0.86, p-value: 0.27) and no trend for [FN-TSS] load (13.82 t/year decrease, likelihood: 0.61, p-value: 0.75). For [FN-TP], there is a decrease in both concentration (-0.07 mg/L, likelihood: 0.99, p-value: 0.05) and load (-0.18 t/year, likelihood: 0.99, p-value: 0.05) (Tables SM4, 5).\u003c/p\u003e\n \u003cp\u003eAt Big Otter Creek, [FN-TSS] (C/L)s trends showed stability from 2014 to 2019 before increasing from the late 2000s (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e). The overall trends indicate an increase in [FN-TSS] (16.9 mg/L concentration increase, likelihood: 0.74, p-value: 0.54, and 25.45 t/year load increase, likelihood: 0.84, p-value: 0.32) over the period 2002\u0026ndash;2019 (Table SM4). Although figures suggest a narrow decreasing trend for both [FN-TP] (C/L)s, statistical values indicated no trend for both [FN-TP] C/L over Big Otter Creek tributary (concentration likelihood: 0.54, p-value: 0.90, load likelihood: 0.54, p-value: 0.92). However, [FN-TP] concentration trend showed small but abrupt changes from the late 2000s to mid-2010s (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e, Table SM5) (Loomer, \u003cspan\u003e2011\u003c/span\u003e; Stow et al. \u003cspan\u003e2015\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eAt Sydenham River, [FN-TSS] (C/L)s trends (2002\u0026ndash;2019) exhibited a stable decrease from 2014 to 2019, with a small but consistent increase noticed until the mid-2010s (for concentration) and a consistent decrease from 2002 to 2009 before a consistent increase until 2019 (for load). Overall, [FN-TSS] load increased (2.63 t/year, likelihood: 0.74, p-value: 0.55) with no trend for concentration (likelihood: 0.59, p-value: 0.82) in Sydenham River from 2002 to 2019 (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e, Table SM4). On the contrary, [FN-TP] (C/L)s consistently decreased (C/L decreased by 0.02 mg/L, likelihood: 0.76, p-value: 0.49, and 0.01 t/year, likelihood: 0.76, p-value: 0.49, respectively) at Sydenham River over the period from 2002 to 2019 (Stammler et al. \u003cspan\u003e2017\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e, Table SM5) (Staton et al., \u003cspan\u003e2003\u003c/span\u003e; Stammler et al. \u003cspan\u003e2017\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eAt Thames River at Innerkip, [FN-TSS] concentration (below CWQG limit) trend exhibited a decrease from 1988 to the late 1990s before taking a consistent increasing turn until 2019. However, [FN-TSS] load trend remained stable throughout. Besides, [FN-TP] concentration (above PWQO limit) decreased from 1988 to 1999, after which stability is visible until 2019. In addition, [FN-TP] load exhibited a consistent decrease in trend from 1988 to 2019. Overall, at Thames River at Innerkip, there was an increase in [FN-TSS] concentration trend (0.14 mg/L, likelihood: 0.69, p-value: 0.64) and no trend (likelihood: 0.61, p-value: 0.79) was visible for loads (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e, Table SM4). Decrease in trend for both [FN-TP] (C/L)s (concentration decrease is 0.05 mg/L, likelihood: 0.93, p-value: 0.14, load decrease is 0.03 t/year, likelihood: 0.95, p-value: 0.10) was also visible (N\u0026uuml;rnberg and LaZerte, \u003cspan\u003e2015\u003c/span\u003e; Upper Thames River Watershed Report Card, \u003cspan\u003e2022\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e, Table SM5).\u003c/p\u003e\n \u003cp\u003eAt Big Creek near Walsingham, trends for [FN-TSS] (C/L)s decreased consistently (concentration decrease is 15.60 mg/L, likelihood: 0.97 and p-value: 0.08, load decrease is 8.81 t/year, likelihood: 0.95 and p-value: 0.11) with a slight increase around the year 2010 (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e, Table SM4). Trends for [FN-TP] (C/L)s decreased consistently (concentration decrease is 0.03 mg/L, likelihood: 0.97 and p-value: 0.05, load decrease is 0.01 t/year, likelihood: 0.97 and p-value: 0.05) from 2002 to 2019 (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e, Table SM5). Besides, [FN-TSS] concentration trend went below the CWQG limit around the late 2000s, while [FN-TP] concentration trend touched the PWQO limit by 2019 (Lake Erie Source Protection Region Technical Team, \u003cspan\u003e2008\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e, \u003cspan\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003e4.1.3. Tributaries draining into Lake Huron\u003c/h2\u003e\n \u003cp\u003eIn the Saugeen River, [FN-TSS] concentrations (below CWQG limit) and loads decreased over the period 2002\u0026ndash;2019, with a small and stable increase observed from the year 2010 (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e). Specifically, a 3.35 mg/L concentration decrease (likelihood: 0.88, p-value: 0.23) and a 13.26 t/year load decrease (likelihood: 0.90, p-value: 0.22) were reported (Saugeen Valley Source Protection Area \u003cspan\u003e2015\u003c/span\u003e; Falk et al. \u003cspan\u003e2021\u003c/span\u003e) ((Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e, Table SM4)). The analysis also demonstrated a decrease in [FN-TP] loads during the same period, with an abrupt decrease from 2002 to 2009 (0.01 mg/L concentration decrease, likelihood: 0.86, p-value: 0.28, and 0.03 t/year load decrease, likelihood: 0.90, p-value: 0.19) (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e, Table SM5). [FN-TP] concentration levels consistently remained below PWQO levels from 2009 through 2019, making Saugeen River the tributary with the lowest [FN-TP] concentration magnitude among all (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e (a)) (Saugeen Valley Source Protection Area \u003cspan\u003e2015\u003c/span\u003e; Falk et al. \u003cspan\u003e2021\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eIn the Ausable River at Springbank, [FN-TSS] concentration trends showed a decrease with an abrupt decrease after 2013 (3.56 mg/L, likelihood: 0.81, p-value: 0.36) (above CWQG limit). However, [FN-TSS] load exhibited no trend (likelihood: 0.56, p-value: 0.86), despite a slight increase from 2010 to 2013 (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e, Table SM4). For [FN-TP], concentration showed no trend (likelihood: 0.66, p-value: 0.69) (above PWQO limit), while the load increased by 0.0002 t/year (likelihood: 0.69, p-value: 0.61) (Skaggs et al., \u003cspan\u003e1994\u003c/span\u003e; Nelson et al., \u003cspan\u003e2003\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e, Table SM5).\u003c/p\u003e\n \u003cp\u003eIn the Nottawasaga River at Baxter, trends for both [FN-TSS] (C/L)s exhibited variability, with an overall decrease of 10.8 mg/L concentration (likelihood: 0.90, p-value: 0.21) and 11.37 t/year load (likelihood: 0.93, p-value: 0.13) (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e, Table SM4). The decrease occurred from 2002 to 2009, followed by a small increase from 2010 to 2013, a decrease in 2014, and a consistent increase thereafter (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003ea). Notably, [FN-TSS] concentration trend followed the CWQG limit from 2010 to 2015 but exceeded it afterward (Fig.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003ea). For [FN-TP], both (C/L)s consistently decreased from 2002\u0026ndash;2019 (overall, decrease of 0.03 mg/L concentration, likelihood: 0.95, p-value: 0.01, and 0.03 t/year load, likelihood: 0.95, p-value: 0.11) (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e, Table SM5). [FN-TP] concentration was very close to the PWQO limit for three years before 2019 (Falk et al., \u003cspan\u003e2021\u003c/span\u003e; Rutledge and Chow-Fraser, \u003cspan\u003e2019\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003ea).\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan\u003e3\u003c/span\u003e \u003cstrong\u003e(a)\u003c/strong\u003e Long-term trends of [FN-TSS] concentration across selected monitoring stations on tributaries of Southern Ontario\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan\u003e4\u003c/span\u003e \u003cstrong\u003e(a)\u003c/strong\u003e Long-term trends of [FN-TP] concentration across selected monitoring stations on tributaries of Southern Ontario\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003e4.2. Spatial Pattern of [FN-TSS] and [FN-TP] Trends\u003c/h2\u003e\n \u003cp\u003eThe spatial variation of [FN-TSS] and [FN-TP] trends, indicating increase, decrease, or no trend, across tributaries in Southern Ontario is presented to discern combined patterns TSS and TP (Fig.\u0026nbsp;\u003cspan\u003e5\u003c/span\u003e and Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). In the selected tributaries of Lake Ontario, namely the Don and Humber rivers, both [FN-TSS] and [FN-TP] show decreasing trends in (C/L)s. A similar scenario is observed for two Lake Huron tributaries, the Saugeen and Nottawasaga rivers, with the exception of the Ausable River tributary; where, [FN-TSS] concentration increases, while [FN-TP] load decreases, and no trend is observed for [FN-TSS] load and [FN-TP] concentration. Additionally, decreasing trends are identified for both (C/L)s of [FN-TSS] and [FN-TP] in the Big Creek near Walsingham tributary of Lake Erie. Thames River at Thamesville exhibits similar results, except for a no-trend condition for [FN-TSS] load (Fig.\u0026nbsp;\u003cspan\u003e5\u003c/span\u003e). Furthermore, decreasing trends in [FN-TP] (C/L)s are noted at Sydenham River at Florence and Thames River at Innerkip. However, [FN-TSS] load shows an increasing trend, with no trend for concentration at Sydenham River at Florence. Conversely, the scenario is reversed for Thames River at Innerkip, where [FN-TSS] (C/L)s increase, while [FN-TP] (C/L)s show no trend. The only case no trend is observed for both [FN-TP] (C/L)s, accompanied by an increasing trend for [FN-TSS] (C/L)s, is apparent at Big Otter Creek near Calton (Fig.\u0026nbsp;\u003cspan\u003e5\u003c/span\u003e and Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). The observations of variable trend directions have been consolidated in Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e, along with corresponding remarks. It is noted that in cases where no increasing trend is observed, it indicates the effectiveness of BMPs. Conversely, if at least one increasing trend is identified, it suggests that further actions should be taken. Following this evaluation, potential future steps have been identified for tributaries such as Big Otter Creek, Sydenham River, Thames River at Innerkip, and Ausable River. However, it is emphasized that detailed analysis is imperative to determine the appropriate course of action moving forward.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cdiv align=\"left\"\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1711688924.png\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003e4.3. Discussion\u003c/h2\u003e\n \u003cp\u003eWe identified decreasing trends in [FN-TSS] and [FN-TP] (C/L)s at 50% of the selected stations, with varying directions observed at other locations. Only two stations (Big Creek at Walsingham and Saugeen) demonstrated concentration trends below both CWQG and PWQO limits for [FN-TSS] and [FN-TP] by 2019. Additionally, two other stations (Don River and Thames River at Innerkip) exhibited [FN-TSS] concentration trends below the CWQG limit by 2019. At Nottawasaga River, [FN-TSS] concentration approached the CWQG limit in 2012 before rebounding, while [FN-TP] concentration remained close to the PWQO limit. These trend directions are summarised in Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e offering insights for future considerations to identify cases where measures should be taken to reduce TSS and TP.\u003c/p\u003e\n \u003cp\u003eVarious literature did identify that agricultural BMPs, including changes in fertilizer application, manure management, and tillage practices are responsible for decreasing trends in phosphorus in agricultural streams (Tuppad et al., \u003cspan\u003e2010\u003c/span\u003e; Liu et al., \u003cspan\u003e2017\u003c/span\u003e; Miele et al., \u003cspan\u003e2023\u003c/span\u003e). Other contributing factors noted in literature include improvements in wastewater treatment plants (WWTP) and the removal of phosphate from detergents, combined with agricultural BMPs (Luo et al., \u003cspan\u003e2011\u003c/span\u003e; Istv\u0026aacute;novics and Honti, \u003cspan\u003e2012\u003c/span\u003e; Stammler et al., \u003cspan\u003e2017\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eMost of the prior research has concentrated on specific watershed or land use types to assess the impact of targeted phosphorus mitigation strategies. Notably, comprehensive studies spanning multiple watersheds with diverse land use types, such as Luo et al. (\u003cspan\u003e2011\u003c/span\u003e), Istv\u0026aacute;novics and Honti, (\u003cspan\u003e2012\u003c/span\u003e) attributed decreasing trends in phosphorus to a multitude of factors. Unlike these large-scale investigations, studies in Ontario have linked decreasing phosphorus to distinct causes, including recovery from logging (O\u0026rsquo;Brien et al., 2013) and urbanization (Raney and Eimers, \u003cspan\u003e2014\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eIt\u0026apos;s noteworthy that many studies, including those in Ontario, often drew conclusions about causal mechanisms based on circumstantial evidence, noting that reductions in phosphorus coincided with phosphorus mitigation efforts. However, the observed trends in Ontario may be linked to substantial shifts in agricultural and urban land use practices. These changes include a reduction in cattle numbers, an uptick in the adoption of conservation and no-till practices, and a transition from corn to soy crops, as documented by Smith (2015). Understanding these alterations in land use and practices is crucial in elucidating the complex dynamics contributing to the observed trends in phosphorus in Ontario. Unfortunately, detailed watershed-scale data for these changes at our sites are unavailable.\u003c/p\u003e\n \u003cp\u003eConservation and no-till practices, advocated for soil conservation and economic benefits, may contribute to observed decreasing trends in [FN-TP] in agricultural sites, as reductions in [FN-TSS] can explain such trends due to the particulate nature of stream [FN-TP] (Clark et al., 1985). However, at some sites, [FN-TP] decreased without a corresponding decrease in [FN-TSS] (Fig.\u0026nbsp;\u003cspan\u003e5\u003c/span\u003e, Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). The Canadian Census of Agriculture data, starting in 1991, indicates a decrease in conventional tillage from 78\u0026ndash;37% of tilled land by 2011 (Stammler et al. \u003cspan\u003e2017\u003c/span\u003e). While this coincided with decreases in [FN-TP], the widespread adoption of conservation and no-till practices didn\u0026rsquo;t occur until the mid-1990s, suggesting other factors contribute to [FN-TP] decreases in agricultural or mixed watersheds.\u003c/p\u003e\n \u003cp\u003eStudies in forested watersheds in central Ontario also reported decreasing trends in phosphorus since 1980, attributing these trends to long-term recovery from logging (Eimers et al., 2009; O\u0026rsquo;Brien et al., 2013; Stammler et al. \u003cspan\u003e2017\u003c/span\u003e). Urban areas, subject to GLWQA mandates for phosphate removal from detergents and improved phosphorus removal from WWTP effluent, also experienced decreasing phosphorus trends. Specifically, in the Nottawasaga River, urban growth might have contributed to increased [FN-TSS] after 2012, despite effective BMPs (NVCA, 2019).\u003c/p\u003e\n \u003cp\u003eBased on the evidence presented, our study does not conclusively attribute the cause of decreasing [FN-TP] to any specific mechanism, whether across southern Ontario as a whole or within individual watershed types. This indicates a pervasive cause for observed decreasing trends (Stammler et al. \u003cspan\u003e2017\u003c/span\u003e). Potential factors include changes in rainfall composition or runoff timing, with acid deposition affecting soil phosphate binding capacity. Although our study area has mostly alkaline and well-buffered soils, acid rainfall could mobilize phosphate associated with carbonates (Stammler et al. \u003cspan\u003e2017\u003c/span\u003e). Finally, limitations and implications of the study are discussed in the supplementary sections SM5 and SM6.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, the study provides critical information on trend dynamics (using WRTDS_BT modeling tool) in ten tributaries of Lake Ontario, Erie, and Huron. Although the drivers are not explicitly identified, potential attributions are discussed for policymakers in the study area. The precise conclusions of this study are listed below:\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cul\u003e \u003cli\u003e \u003cp\u003eFour tributaries reported lower [FN-TSS] concentration than the CWQG limit (30 mg/L): Don river, Thames river, Big Creek and Saugeen river.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTwo tributaries reported lower [FN-TP] concentration than the PWQO limit (0.03 mg/L): Big Creek and Saugeen river.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAt two tributaries both [FN-TSS] and [FN-TP] concentrations are below CWQG and PWQO limits: Big Creek and Saugeen river.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eBMPs and other management efforts are effective at five tributaries (Humber River, Don River, Big Creek, Saugeen River, Nottawasaga River).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eTrend-based observations for [FN-TSS] and [FN-TP] (C/L)s, provides insights for future steps and considerations (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003eThis work represents a critical scientific effort to identify potential vulnerable areas for sediment and phosphorus losses. The apparaoch presented should, therefore, be used judiciously in improving management actions and policy decisions in the other part of the world.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e-Ethical Approval: Not Applicable\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;-Consent to Participate: We agree among ourselves to outline the roles and responsibilities towards one another throughout the whole research and publication process.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;-Consent to Publish: We all give consent to publish.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;-Authors Contributions: Pranesh Kumar Paul: Conceptualization, data management, analysis, First draft, review of draft; Anant Goswami: analysis; Ramesh Rudra: review of draft; Pradeep Kumar Goel: review of draft; Prasad Daggupati: project management and review of draft.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;-Funding: This research was funded by the Natural Science and Engineering Research Council of Canada Discovery Grant (#401257).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;-Competing Interests: There is no competing interest between us.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;-Availability of data and materials: Due to privacy, ethical concerns, and confidentiality agreements the supporting data cannot be made available.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAkinnawo SO (2023) Eutrophication: Causes, consequences, physical, chemical and biological techniques for mitigation strategies. 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Archived: https://www.ontario.ca/page/water-quality-ontario-report-2012\u003c/li\u003e\n\u003cli\u003eYates AG, Brua RB, Friesen A, Reedyk S, Benoy, G (2022). Nutrient and suspended solid concentrations, loads, and yields in rivers across the Lake Winnipeg Basin: A twenty year trend assessment. 44, 101249.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-processes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"enpr","sideBox":"Learn more about [Environmental Processes](https://www.springer.com/journal/40710)","snPcode":"40710","submissionUrl":"https://submission.nature.com/new-submission/40710/3","title":"Environmental Processes","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"WRTDS_BT, Trend analysis, Total Phosphorus, Total Suspended Sediments, Lake Erie, Lake Huron, Lake Ontario","lastPublishedDoi":"10.21203/rs.3.rs-4164984/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4164984/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe specific objective of this study is to explore the long-term trend of total phosphorus (TP) and total suspended sediment (TSS) concentrations and loads (C/L)s in various streams/rivers in the Great Lakes Basin. This includes related statistical analyses, such as confidence intervals, to assess variability and identify cases where measures should be taken to reduce TSS and TP. Trend analysis of TSS and TP (C/L)s are performed, combining bootstrapping with the Weighted Regressions on Time, Discharge, and Season i.e., WRTDS_BT technique. The technique is used at ten selected monitoring stations of Northern Lake Erie, Eastern Lake Huron, and Lake Ontario \u0026amp; Niagara Peninsula in Ontario, Canada. Trend analysis over selected tributaries using flow-normalized (FN) TSS and TP (C/L)s reveals that trends in [FN-TSS] and [FN-TP] (C/L)s were highly variable, with significant decrease in a few stations. However, in most tributaries, TSS concentration levels are significantly higher than Canadian Water Quality Guidelines (CWQG) limit of 30 mg/L (following Toronto Region Conservation Authority (TRCA), Ontario) and TP concentration levels are significantly higher than the Ontario\u0026rsquo;s provincial water quality objectives (PWQO) limit of 0.03 mg/L. Measures to reduce TSS and TP is effective at five tributaries (Humber River, Don River, Saugeen River, Big Creek, Nottawasaga River). Although the drivers are not explicitly identified, potential attributions are discussed for policymakers in the study area.\u003c/p\u003e","manuscriptTitle":"Exploring the Trends in Sediment and Phosphorus Concentrations and Loads in Part of the Canadian Great Lakes Basin","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-29 18:48:02","doi":"10.21203/rs.3.rs-4164984/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2024-05-09T11:25:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"69935418819352999166227843908812201371","date":"2024-04-27T16:46:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-27T14:27:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-26T13:18:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-26T12:29:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Processes","date":"2024-03-25T17:45:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-processes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"enpr","sideBox":"Learn more about [Environmental Processes](https://www.springer.com/journal/40710)","snPcode":"40710","submissionUrl":"https://submission.nature.com/new-submission/40710/3","title":"Environmental Processes","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4ff48bf8-f8e5-4ad1-908a-9135789e9cdf","owner":[],"postedDate":"March 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-07-02T16:05:52+00:00","versionOfRecord":{"articleIdentity":"rs-4164984","link":"https://doi.org/10.1007/s40710-024-00710-w","journal":{"identity":"environmental-processes","isVorOnly":false,"title":"Environmental Processes"},"publishedOn":"2024-05-31 16:05:52","publishedOnDateReadable":"May 31st, 2024"},"versionCreatedAt":"2024-03-29 18:48:02","video":"","vorDoi":"10.1007/s40710-024-00710-w","vorDoiUrl":"https://doi.org/10.1007/s40710-024-00710-w","workflowStages":[]},"version":"v1","identity":"rs-4164984","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4164984","identity":"rs-4164984","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}