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Home My WebLink AboutDWQ-2024-004845Charge Questions Update and Next Steps Science Panel Meeting | June 20, 2024 Overarching Charge Questions 1.What was the historical condition of Utah Lake with respect to nutrients and ecology pre-settlement and along the historical timeline with consideration of trophic state shifts and significant transitions since settlement? 2.What is the current state of the lake with respect to nutrients and ecology? 3.What additional information is needed? [addressed as part of strategic research plan] 4.What additional information is needed to define nutrient criteria that support existing beneficial uses? Sub-Questions Divided into Theme Areas Historical condition Macrophytes and diatoms Fish, aquatic life, birds HABs Sediments Criteria development Charge Question Responses 1.Evidence Evaluation Focus: technical Detailed analysis of studies that inform the question (Utah Lake and related) Figures from cited studies 2.Synthesis Focus: plain-language, non-technical Overall response to the question Includes assessment of SP confidence in the response Historical Condition •1.1. What does the diatom community and macrophyte community in the paleo record tell us about the historical trophic state and nutrient regime of the lake? •1.1.i. Can diatom (benthic and planktonic) and/or macrophyte extent or presence be detected in sediment cores? And if so, what are they? •1.1.iii. How have environmental conditions changed over time? •1.2. What were the historic phosphorus, nitrogen, and silicon concentrations as depicted by sediment cores? (add calcium, iron, and potentially N and P isotopes) •1.4. What do photopigments and DNA in the paleo record tell us about the historical water quality, trophic state, and nutrient regime of the lake? •4.1. What would be the current nutrient regime of Utah Lake assuming no nutrient inputs from human sources? This question may require the identification of primary sources of nutrients. Macrophytes and Diatoms •1.1.ii. What were the environmental requirements for diatoms and extant macrophyte species? •2.2 What are the environmental requirements for submerged macrophytes currently present at Utah Lake? •2.2.i. What is the role of lake elevation and drawdown in macrophyte recovery? Are certain species more resilient to drawdowns and nutrient related impacts? Can some species establish/adapt more quickly? •2.2.ii. What is the relationship between carp, wind, and macrophytes on non-algal turbidity and nutrient cycling in the lake? What impact could macrophyte reestablishment have? Fish, Aquatic Life, Birds •1.3. What information do paleo records (eDNA/scales) provide on the population trajectory/growth of carp over time? What information do the paleo records provide on the historical relationship between carp and the trophic state and nutrient regime of the lake? •2.1. What are the impacts of carp on the biology/ecology and nutrient cycling of the lake and how are those impacts changing with ongoing carp removal efforts? •2.1.i. What contribution do carp make to the total nutrient budget of the lake via excretion rates and bioturbation? How much nutrient cycling can be attributed to carp? •2.1.ii. What is the effect of carp removal efforts on macrophytes, nutrients, secchi depth, turbidity, and primary productivity? •2.1.iii. How much non-algal turbidity and nutrient cycling is due to wind action versus carp foraging? How much does sediment resuspension contribute to light limitation, and does wind resuspension contribute substantially in the absence of carp? •2.5. For warm water aquatic life, waterfowl, shorebirds, and water-oriented wildlife: i. Where and when in Utah Lake are early life stages of fish present? ii. Which species are most sensitive and need protection from nutrient-related impacts? •4.2. Assuming continued carp removal and current water management, would nutrient reductions support a shift to a macrophyte-dominated state within reasonable planning horizons (i.e., 30¬50 years)? HABs •2.3. What are the linkages between changes in nutrient regime and Harmful Algal Blooms (HABs)? •2.3.i. Where do HABs most frequently start/occur? Are there hotspots and do they tend to occur near major nutrient sources? Data analysis •2.3.ii. Which nutrients are controlling primary production and HABs and when? •2.3.iii. If there are linkages between changes in nutrient regime and HABs, what role if any does lake elevation changes play? •2.3.iv. How do other factors affect HAB formation in Utah Lake (e.g., climate change; temperature; lake stratification; changes in zooplankton and benthic grazers and transparency) •2.3.vi. What is the relationship between light extinction and other factors (e.g., algae, TSS, turbidity)? •4.3. If the lake stays in a phytoplankton-dominated state, to what extent can the magnitude, frequency, and extent of harmful and nuisance algal blooms be reduced through nutrient reductions? Sediments •2.3.v. What is the role of calcite “scavenging” in the phosphorus cycle? •2.4. How do sediments affect nutrient cycling in Utah Lake? •2.4.i. What are current sediment equilibrium P concentrations (EPC) throughout the lake? What effect will reducing inputs have on water column concentrations? If so, what is the expected lag time for lake recovery after nutrient inputs have been reduced? •2.4.ii. What is the sediment oxygen demand of, and nutrient releases from, sediments in Utah Lake under current conditions? •2.4.iii. Does lake stratification [weather patterns] play a result in anoxia and phosphorus release into the water column? Can this be tied to HAB formation? Criteria Development •3. What additional information is needed to define nutrient criteria that support existing beneficial uses? •3.1. For warm water aquatic life, waterfowl, shorebirds, and water- oriented wildlife •3.2. For primary contact recreation •3.3. For agricultural uses including irrigation of crops and stock watering Overview of Subgroup Outcomes & Next Steps •April-May 2024: Subgroups met to discuss updates to interim charge question responses •SP subgroups discussed: Minor edits to evidence evaluation Additional citations of related studies Additional context for interpretations Recommendations for translating synthesis bullets into paragraph form Recommendations for level of confidence In a few cases, more substantive recommendations for deeper dives into existing and/or upcoming studies Overview of Subgroup Outcomes & Next Steps June-July TT to incorporate straightforward edits SP subgroups meet to discuss substantial edits/evidence evaluation August TT to compile all charge question responses into a master document SP reviews charge question responses September At in-person SP meeting, seek to approve charge question responses Potential discussion with Steering Committee? Confidence Evaluation Confidence Evaluation •High confidence Direct evidence in Utah Lake Well-established methods Consistent behavior of Utah Lake compared to lakes in the literature If multiple studies/lines of evidence, findings were consistent •“Big picture” conclusions more often resulted in high confidence •Sometimes very specific items or interacting drivers resulted in lower confidence •Questions needing analysis from mass balance and/or mechanistic models were not assessed for confidence yet Conclusions with < high confidence, or less SP agreement •Geographic specificity of historical macrophyte cover outside of bays/shallow areas (limited evidence) •Specifics on interacting factors for macrophyte requirements & reestablishment (individual impacts known, but restoration requirements are complex) •Causal spatial linkages for HAB formation and persistence (what can be attributed to proximity to nutrient sources vs. hydrodynamics of the system?) •Causation of the role of lake elevation on HABs (high confidence in correlation, but difficult to disentangle several possible causal drivers) Items for Remaining Analysis & Discussion •Cross-referencing studies for evidence of Si concentrations (Bioassay study) •Zooplankton role in grazing (Richards and Aanderud reports) •Further discussions with sediments subgroup: much to unpack! Remaining Evidence to Generate and Evaluate •Brett Mass Balance Analysis What would be the current nutrient regime of Utah Lake assuming no nutrient inputs from human sources? run scenario with minimal nutrient inputs Where do HABs most frequently start/occur? Are there hotspots and do they tend to occur near major nutrient sources? why are chlorophyll concentrations higher in Provo Bay? Deep dive on nutrient concentrations and clarity If the lake stays in a phytoplankton-dominated state, to what extent can the magnitude, frequency, and extent of harmful and nuisance algal blooms be reduced through nutrient reductions? analyze length of time the lake will take to respond to external nutrient loadings What is the expected lag time for lake recovery after nutrient inputs have been reduced? analyze length of time the lake will take to respond to external nutrient loadings Remaining Evidence to Generate and Evaluate •Utah Lake mechanistic watershed and lake models What would be the current nutrient regime of Utah Lake assuming no nutrient inputs from human sources? run model in reference scenario mode Where do HABs most frequently start/occur? Are there hotspots and do they tend to occur near major nutrient sources? run hydrodynamic analysis to better define causal spatial linkages for HABs Which nutrients are controlling primary production and HABs and when? test nutrient reduction scenarios to provide additional line of evidence alongside bioassays If the lake stays in a phytoplankton-dominated state, to what extent can the magnitude, frequency, and extent of harmful and nuisance algal blooms be reduced through nutrient reductions? analyze impact of nutrient reduction scenarios on primary productivity Questions and Discussion Note: all information and data presented are considered draft, in-process material June-July TT to incorporate straightforward edits SP subgroups meet to discuss substantial edits/evidence evaluation August TT to compile all charge question responses into a master document SP reviews charge question responses September At in-person SP meeting, move to approve charge question responses Potential discussion with Steering Committee? Technical Support Update and Next Steps Science Panel Meeting | June 20, 2024 Note: all information and data presented are considered draft, in-process material •Provide the technical basis for the development of numeric nutrient criteria (NNC) to protect designated uses •Recreation •Aquatic Life •Others (Agriculture, Downstream) •Conduct analyses to support multiple lines of evidence in the NNC framework Purpose of the Technical Support Document Note: all information and data presented are considered draft, in-process material Lines of Evidence 1.Reference-based Results from paleolimnological studies Utah Lake Nutrient Model prediction/extrapolation of reference conditions 2.Stressor-response analysis Utah Lake Nutrient Model output Statistical models 3.Scientific literature Scientific studies of comparable/related lake ecosystems Support/supplement other lines of evidence Note: all information and data presented are considered draft, in-process material TSD Document Status and Upcoming Analyses Background Reference Analysis Paleolimnological analysis Mechanistic model analysis Stressor-Response Analysis Empirical analysis (pending target selection by criteria subgroup) Mechanistic model analysis Literature Analysis Weight of Evidence Note: all information and data presented are considered draft, in-process material Reference-Based Analysis •Intended to set a “floor” & add context for how the lake has changed over time •Paleolimnological reconstruction of past conditions Quantify pre-settlement nutrient conditions and how they have changed over time Multiple studies, SC charge question responses Note: all information and data presented are considered draft, in-process material Reference: Paleolimnological Reconstruction •Lines of Evidence Diatom community Macrophytes: physical remains, eDNA, C:N, H index Anodonta and Gastropods: physical remains C, N, H index/ratios and isotopes Cyanobacteria: eDNA, phytopigments Charcoal Sediment P concentrations and speciation Metals Note: all information and data presented are considered draft, in-process material Reference: Paleolimnological Reconstruction •Quantitative vs. Qualitative? Many lines of evidence are directional rather than directly quantifiable Some lines of evidence support inferences about nutrient concentrations –Shift from meso-oligotrophic to eutrophic –Approximate doubling of P concentrations Paleo reference evidence can be used as supporting evidence for stressor-response Note: all information and data presented are considered draft, in-process material Reference: Paleolimnological Reconstruction •Paleo evidence: several events occurring simultaneously Nutrient enrichment (increase in loading) Carp introduction Loss of macrophytes Population growth and land use change in watershed Sewage treatment Note: all information and data presented are considered draft, in-process material Reference-Based Analysis •Intended to set a “floor” & add context for how the lake has changed over time •Model-based prediction Run watershed model under a “reference conditions” scenario watershed nutrient loading Watershed conditions then used as boundary conditions for the lake model Run lake model with new boundary conditions, then analyze in-lake nutrient concentrations quantitative estimation of historical nutrient concentrations Note: all information and data presented are considered draft, in-process material TSD Document Status and Upcoming Analyses Background Reference Analysis Paleolimnological analysis Mechanistic model analysis Stressor-Response Analysis Empirical analysis (pending target selection by criteria subgroup) Mechanistic model analysis Literature Analysis Weight of Evidence Note: all information and data presented are considered draft, in-process material Stressor-Response Analysis: Empirical •Nearly complete, pending selection of targets •Target decisions are risk management decisions Exceedance frequency (e.g., prediction interval, certainty level) Chlorophyll target value/range to input into TN and TP models •Which decisions are SP members comfortable making? SP subgroup could select target values/ranges SP could send to Steering Committee and/or EPA to help decide Note: all information and data presented are considered draft, in-process material Stressor-Response Analysis: Mechanistic •EFDC-WASP will be run under different scenarios: Current Reference Reduced nutrients •Can treat each of these scenarios as a point along the stressor-response curve, then run S-R models: Chlorophyll ~ TN Chlorophyll ~ TP Can use chlorophyll targets generated by other models and/or the mechanistic model to identify TN and TP targets Note: all information and data presented are considered draft, in-process material TSD Document Status and Upcoming Analyses Background Reference Analysis Paleolimnological analysis Mechanistic model analysis Stressor-Response Analysis Empirical analysis (pending target selection by criteria subgroup) Mechanistic model analysis Literature Analysis Weight of Evidence Note: all information and data presented are considered draft, in-process material Literature Analysis Note: all information and data presented are considered draft, in-process material Approach for Magnitude, Frequency, Duration Components •Lines of evidence can “easily” identify magnitude •Criteria and assessment require frequency and duration as well, e.g., Not to exceed Growing season mean, 1 in 3 years 10% exceedance rate (current Utah assessment method for pH, temperature, DO, TDS) •Most S-R analyses are on a single-day basis may need to translate this to a longer duration •Researched what other states have done (next slides) Note: all information and data presented are considered draft, in-process material Other State Frequency and Duration Components: Chlorophyll •AL: Mean •A. Samoa & HI: median/geomean not to exceed, 10% exceedance, 2% exceedance •CA: Monthly mean •FL: Annual mean, annual geomean, 10% exceedance •GA & TN: Monthly mean in growing season •MN: Maximum •NV: Growing season mean Note: all information and data presented are considered draft, in-process material Other State Frequency and Duration Components: TN •A. Samoa & HI: median/geomean not to exceed, 10% exceedance, 2% exceedance •CA: Monthly mean, 90th percentile, annual mean •FL: Annual mean, annual geomean, 10% exceedance •NV: Not to exceed, annual mean, growing season mean •Northern Mariana & Puerto Rico: Not to exceed Note: all information and data presented are considered draft, in-process material Other State Frequency and Duration Components: TP •A. Samoa & HI: median/geomean not to exceed, 10% exceedance, 2% exceedance •CA: Monthly mean, 90th percentile, annual mean, not to exceed in hypolimnion •FL: Annual mean, annual geomean, 10% exceedance •IN: Daily maximum, monthly mean •NV: Growing season mean •Northern Mariana & Puerto Rico & USVI: Not to exceed Note: all information and data presented are considered draft, in-process material Approach for Magnitude, Frequency, Duration Components What input would the SP like to have on frequency and duration? SP subgroup could advise SP could defer to Utah standards group SP could send to Steering Committee and/or EPA to help decide Note: all information and data presented are considered draft, in-process material Discussion with Utah Standards Group •TT has periodic meetings with the UDWQ standards group •Goal: Ensure that TSD and SP & SC recommendations are consistent with: State water quality criteria State assessment methods EPA guidance Lessons learned from other criteria development efforts Note: all information and data presented are considered draft, in-process material Discussion with Utah Standards Group •TSD will help lay the groundwork for a site-specific standard for Utah Lake Updates in state criteria Updates in state assessment methods Main basin and Provo Bay are already separate assessment units TN and TP will be separate indicators •Weight of Evidence: most sensitive use should take precedent, then can use weight of evidence within the use •Extent: One site exceedance can lead to an impairment of the AU, but there is language reserved in the assessment methods for judgement calls •Consider adaptive management: is the lake moving toward supporting its uses? (this is more a question for implementation) Note: all information and data presented are considered draft, in-process material Weight of Evidence •Most sensitive use will dictate nutrient targets •But, ranges of nutrients may be deemed protective of most sensitive use across lines of evidence how to combine into a recommendation? Note: all information and data presented are considered draft, in-process material Combining Lines of Evidence: Weight of Evidence If more than one line of evidence has sufficient weight, need to merge Note: all information and data presented are considered draft, in-process material Approach for Weight of Evidence What input would the SP like to have on weight of evidence? TT can present a framework for applying weight of evidence SP could weigh lines of evidence on their own Could bring in EPA staff for presentation and guidance Note: all information and data presented are considered draft, in-process material Pathway to Criteria (ULWQS Technical Framework) •SP recommendation SC recommendation Utah Lake Authority endorsement •Regulatory process multiple other groups involved with the process DWQ Water Quality Standards workgroup Legislature EPA Note: all information and data presented are considered draft, in-process material Questions and Discussion Note: all information and data presented are considered draft, in-process material Eutrophication Management in Utah Lake - are phosphorus concentrations regulated by nutrient external inputs? Michael Brett Professor of Limnology Department of Civil & Environmental Engineering University of Washington Key points 1. “Through statistical analysis, we showed that volumes are variable but that dissolved phosphorus concentrations are relatively constant.” 2. “We show that monthly changes in mass are large compared to estimated loads to the lake and that these changes switch from representing net sinks to net sources from one month to the next, a finding that is not consistent with simple mass balance models.” 3. “Data from published studies highlight the fact that P [in] sediments and soils in and around Utah Lake are geologic in origin, not anthropogenic, and represent a very large, essentially infinite reservoir for P.” 4. “the P content of Utah Lake sediments is high (with an average concentration of 666 mg/kg) . . . These P-rich sediments act as P reservoirs and are able to support P equilibrium with the water column through sorption processes.” 5. “We show, through several lines of evidence, that [Utah Lake] water column phosphorus concentrations are insensitive to external loads.” 6. If “lakes have sediments with high concentrations of P from geologic sources, water column concentrations could behave independently from external loads.” 7. “For sorption to dominate in this manner requires several unique circumstances, including shallow water with no stratification, significant water–sediment interaction, and high background P concentrations in the sediment.” 8. “This study has implications for other shallow lakes with significant sediment–water interactions. . . For lakes and reservoirs that have water column P concentrations primarily driven by sorption processes, costs and efforts aimed at nutrient load reductions may prove ineffective.” !"#$%& "'= *+,-−*+/0'−1!+/0' Change = Input –Output –Removal V = lake volume Q = water flow into/out of lake C = concentration into/out of lake s = first order loss rate of nutrients The general mass balance model The general mass balance model !"#$%& "'= *+,-−*+/0'−1!+/0' Change = Input –Output –Removal If we assume steady-state or long term average conditions 0 The general mass balance model Input = Output + Removal V = lake volume Q = water flow into/out of lake C = concentration into/out of lake s = first order loss rate of nutrients !"#$=!"&'(+*+"&'( The general mass balance model If we express this equation in terms of total phosphorus (TP) and rearrange, it can be expressed as: !"#$%&= !")*+ =!",-.)*+.,-/+ 1 ∗3 where θ represents the lake’s hydraulic residence time (i.e., θ = V/QIN), and it is assumed the lake is well mixed The general mass balance model !"#$%&= !")*+ =!",- .)*+.,-/+ 1 ∗3 •This equation gives a very clear mechanistic explanation for the main processes that determine the average phosphorus concentration in lakes •The Lake TP concentration is directly linearly related to the flow wt’d input TP concentration •Evaporative losses from the lake will concentrate TP within the lake •Lakes with long hydraulic residence times will have lower TP concentrations (relative to TPIN) •Lakes with high loss rate constants will have lower TP concentrations The general mass balance model We can use this mass balance approach to predict how the lake’s phosphorus concentration will depend on the input concentrations for the major point sources 𝑇𝑃!"=∑𝑇𝑃∗𝑄 ∑𝑄 𝑇𝑃!" =∑$∗&'!"#$% ) $∗&'&"'(#& ) $∗&'))*+% ) *+ ∑$!"#$% ) $&"'(#& ) $))*+% !"#$%&= !")*+ =!",- .)*+.,-/+ 1 ∗3 •Phosphorus removal depends on the water residence time (θ) and the loss rate (s) •Utah Lake is a very effective sink for phosphorus •The 96th percentile for TP removal relative to these data •This is probably due to reactions with CaCO3 in the lake and formation of calcium-P mineral complexes in the sediments From: Brett and Benjamin (2008) Freshwater Biology 53: 194–211 n = 305 Phosphorus sequestration in the sediments of Utah Lake We can use this mass balance approach to predict how the lake’s phosphorus concentration will depend on the input concentrations for the major point sources •Biological-Phosphorus removal is economically feasible and can get WWTP effluents down to 200-300 µg TP L-1 •Capital and O&M costs, energy use, and greenhouse gas emissions rapidly increase at lower WWTP effluent concentrations (Falk et al. 2013. Wat. Env. Res. 85: 2307−) We can use this mass balance approach to predict how the lake’s phosphorus concentration will depend on the input concentrations for the major point sources •At WWTP effluent TP concentrations < 1 mg L-1, wastewater discharges constitute < 50% of phosphorus inputs to Utah Lake •At WWTP effluent TP concentrations < 0.5 mg L-1, the phosphorus inputs to Utah Lake become increasingly dominated by Particulate P •A higher fraction of Particulate P loading should result in less phytoplankton biomass production and greater P removal in Utah Lake relative to TP TPeff WWTP Flow WWTP load Total load TDP load TPin TPlake Prop. TP Prop. TDP Prop. from WWTPs from WWTPs Part. P µg/L m3/yr tonnes/yr tonnes/yr tonnes/yr µg/L µg/L unitless unitless unitless 2314 66493539 129 196 134 316 65.4 0.66 0.82 0.32 1000 66493539 55.6 122 71.5 198 40.9 0.45 0.66 0.42 250 66493539 13.9 80.8 36.0 131 27.0 0.17 0.33 0.55 25 66493539 1.39 68.3 25.4 110 22.8 0.020 0.05 0.63 1000 132987079 111 178 119 260 59.1 0.62 0.80 0.33 250 132987079 27.8 94.7 47.8 138 31.4 0.29 0.49 0.49 25 132987079 2.78 69.6 26.6 102 23.1 0.040 0.09 0.62 If WWTP effluent TPeff concentrations go down to 1,000 µg L-1 and WWTP outflows double, there is only be a minimal improvement in Utah Lake water quality Internal loading comparison with Upper Klamath Lake (in south-central Oregon) TPIN adjusted for evaporation ≈ 10% removal ≈ 94% removal Interestingly, this internal loading tends to follow the summer phytoplankton bloom, and not vice-versa •This internal loading averages +38 µg/L •This is equivalent to about 25.9 tonnes P/yr of internal loading •If a more flexible approach is used this estimate increases to +38 µg/L or 29.3 tonnes P/yr •During the peak summer bloom period internal loading is equal to 15% of annual external loading Phosphorus vs. Phytoplankton Biomass 0.1 1 10 100 1000 Ch l o r o p h y l l (µg L-1) 1 10 100 1000 Total Phosphorus (µg L-1) y = 0.08x1.5 r2 = 0.91 Jones and Bachmann (1976) •Mass balance tells us that nutrients are either in the water or in the sediments! •Due to Stoichiometric constraints only the nutrients in the water at any given time contribute to phytoplankton biomass! •The nutrients in the water column on average equal the output/advected concentration that regulates phytoplankton biomass 𝐶!= 𝐶"+ (𝐶#−𝐶")∗𝑒$%&'( 𝑉)*!"# )!= 𝑄𝐶+,−𝑄𝐶#-!−𝜎𝑉𝐶#-! A few calculus steps 𝐶! = concentration at time t 𝐶" = new steady-state concentration 𝐶# = initial concentration r = flushing rate = 1/θ Transition to a new steady-state in Utah Lake 𝐶!= 𝐶"+ (𝐶#−𝐶")∗𝑒$%&'( Transition to a new steady-state in Utah Lake 𝐶,= 68 µg TP L-1 𝐶-= 31 µg TP L-1 s = 4.05 yr-1 r = 0.29 yr-1 This model predicts the step transition to a new steady-state in Utah Lake will be mainly governed by the removal term (s) and will be rapid 𝐶!= 𝐶"+ (𝐶#−𝐶")∗𝑒$%&'( Transition to a new steady-state in Utah Lake 𝐶,= 68 µg TP L-1 𝐶-= 31 µg TP L-1 s = 4.05 yr-1 r = 0.29 yr-1 This model predicts the step transition to a new steady-state in Utah Lake will be mainly governed by the removal term (s) and will be rapid Transition to a new steady-state in Utah Lake 𝑇𝑃!= 𝑇𝑃"+ (𝑇𝑃#−𝑇𝑃")∗𝑒$$.&' () &&.*+ ()( Key points 3. “Data from published studies highlight the fact that P [in] sediments and soils in and around Utah Lake are geologic in origin, not anthropogenic, and represent a very large, essentially infinite reservoir for P.” Key points 3. “Data from published studies highlight the fact that P [in] sediments and soils in and around Utah Lake are geologic in origin, not anthropogenic, and represent a very large, essentially infinite reservoir for P.” Bowen, DHM 1970. The great phosphorus controversy. Environ. Sci. Technol. 4: 725-726. Key points 3. “Data from published studies highlight the fact that P [in] sediments and soils in and around Utah Lake are geologic in origin, not anthropogenic, and represent a very large, essentially infinite reservoir for P.” Bowen, DHM 1970. The great phosphorus controversy. Environ. Sci. Technol. 4: 725-726. Key points 3. “Data from published studies highlight the fact that P [in] sediments and soils in and around Utah Lake are geologic in origin, not anthropogenic, and represent a very large, essentially infinite reservoir for P.” Bowen, DHM 1970. The great phosphorus controversy. Environ. Sci. Technol. 4: 725-726. Key points 3. “Data from published studies highlight the fact that P [in] sediments and soils in and around Utah Lake are geologic in origin, not anthropogenic, and represent a very large, essentially infinite reservoir for P.” Utah Lake is a very effective sink for phosphorus The 96th percentile for these data n = 305 Key points 3. “Data from published studies highlight the fact that P [in] sediments and soils in and around Utah Lake are geologic in origin, not anthropogenic, and represent a very large, essentially infinite reservoir for P.” Key points 4. “the P content of Utah Lake sediments is high (with an average concentration of 666 mg/kg) . . . These P-rich sediments act as P reservoirs and are able to support P equilibrium with the water column through sorption processes.” Key points 4. “the P content of Utah Lake sediments is high (with an average concentration of 666 mg/kg) . . . These P-rich sediments act as P reservoirs and are able to support P equilibrium with the water column through sorption processes.” The earth’s crust has an average phosphorus concentration of 1,200 mg/kg. Phosphorus in upper 5 cm of soil Key points “Our hypothesis is that the water column and sediments in Utah Lake behave as a sorption system that is in equilibrium with respect to P. . . If this hypothesis is true, then water column concentrations should be relatively insensitive to changes in nutrient loads or lake volumes.” 5. “We show, through several lines of evidence, that [Utah Lake] water column phosphorus concentrations are insensitive to external loads.” 6. If “lakes have sediments with high concentrations of P from geologic sources, water column concentrations could behave independently from external loads.” Context •“If most of the phosphorus removal/control projects being seriously considered by the Utah State Division of Water Quality are actually undertaken, the large collateral damage will be the waste of many hundreds of millions of dollars that becomes the burden of area citizens as, through taxation, wastewater service fees and lost opportunity costs, the wasted project-cost indebtedness is paid off – likely more than a thousand dollars per year per household and well more than a billion dollars over the next 30 years or so. What a waste!” Merritt, L.B. 2020. Open Letter to the Utah Lake Science Panel & Lake Steering Committee. Memo dated 23 Jan., 2020. Provo Bay versus the main basin of Utah Lake •Provo Bay is a fascinating sub-basin of Utah Lake because it is mostly (but not entirely) separated from the main lake and manifests very different limnological conditions. •Thus, we can conceptualize Provo Bay as a microcosm of the main lake that allows us to ask “what-if” questions about how Utah Lake might respond if it had different external loading, morphology, and hydraulic and geologic conditions, etc. •Provo Bay currently has much higher nutrient loading than the main lake because it receives discharges from three of the larger WWTPs in the Utah Lake catchment. •Therefore, we can look at Provo Bay’s responses to the higher nutrient loading rate as a test of the main lake’s supposed insensitivity to external nutrient inputs. Provo Bay versus the main basin of Utah Lake Provo Bay versus the main basin of Utah Lake Provo Bay versus the main basin of Utah Lake Provo Bay versus the main basin of Utah Lake •TP concentrations are 5.6 times higher in Provo Bay (384 µg L-1) than the main lake (68 µg L-1) •Annual average Chl-a concentrations are 5.1 times higher in Provo Bay than the main lake (74 and 14 µg L-1, respectively) •Peak July-September Chl-a concentrations are 5.6 times higher (190 and 35 µg L-1, respectively) •However, the mean Secchi disc depths for Provo Bay and the main lake are nearly identical (≈ 0.25 m) •Additionally, the mean Chl-a to TP ratio is ≈ 0.5 for both Provo Bay and the main lake Provo Bay versus the main basin of Utah Lake •TP concentrations are 5.6 times higher in Provo Bay (384 µg L-1) than the main lake (68 µg L-1) •annual average Chl-a concentrations are 5.1 times higher in Provo Bay than the main lake (74 and 14 µg L-1, respectively) •Peak July-September Chl-a concentrations are 5.6 times higher (190 and 35 µg L-1, respectively) •However, the mean Secchi disc depths for Provo Bay and the main lake are nearly identical (≈ 0.25 m) •Additionally, the mean Chl-a to TP ratio is ≈ 0.5 for both Provo Bay and the main lake •Based on these comparisons, I conclude phytoplankton biomass in Utah Lake is directly linearly related to phosphorus availability and light limitation is not indicated for these conditions Provo Bay versus the main basin of Utah Lake Parameter Symbol Units Provo Bay Main Lake 50th percentile* Wt'd input concentration TPIN µg L-1 517 343 73 outflow/inflow QOUT/QIN unitless 0.88 0.32 NA First-order rate constant σTP yr-1 9.62 4.31 0.88 Hydrualic retention time θ yrs 0.05 1.09 0.58 Areal TP loading L mg m-2 yr-1 5651 633 980 Phosphorus Removal R unitless 0.34 0.94 0.45 Areal hydrualic loading qs m yr-1 10.9 1.8 13.8 Flushing rate ρ yr-1 20.9 0.91 1.7 Mean depth z m 0.52 2.0 6.4 But, why does Provo Bay have such high TP concentrations? The higher TP concentrations in Provo Bay are mainly due to the very short hydraulic residence time for this sub-basin Water moves through Provo Bay so rapidly that there isn’t adequate time for substantial phosphorus removal to occur This result is predicted by theory and commonly observed in other lakes (see Brett & Benjamin 2008) The results of the Provo Bay total phosphorus mass balance compared to a similar mass balance for the whole lake. The 50th percentile results are from a summary of mass balance results for 305 lakes published by Brett and Benjamin (2008). Key points 1. “Through statistical analysis, we showed that volumes are variable but that dissolved phosphorus concentrations are relatively constant.” Key points 1. “Through statistical analysis, we showed that volumes are variable but that dissolved phosphorus concentrations are relatively constant.” Mean = 31 ± 11 µg L-1 Coefficient of Variation = 35% Key points Why did Taggart et al. (2024) only consider dissolved phosphorus? Key points Why did Taggart et al. (2024) only consider dissolved phosphorus? It is well established that Total Nutrients are the key drivers of eutrophication. In eutrophic lakes, the large majority of P is usually incorporated in phytoplankton biomass. Quibbly points “Hogsett et al. [9] demonstrated that benthic sediments release P into Utah Lake’s water column, suggesting that internal loading can contribute up to 1500 t of TP/year.” Quibbly points “Hogsett et al. [9] demonstrated that benthic sediments release P into Utah Lake’s water column, suggesting that internal loading can contribute up to 1500 t of TP/year.” 𝑇𝑃!"#$=𝑀𝑎𝑠𝑠 𝑉𝑜𝑙𝑢𝑚𝑒=1,500 𝑡𝑜𝑛𝑛𝑒𝑠 800,000,000 𝑚% ≈2 𝑚𝑔 𝐿&' Quibbly points “Hogsett et al. [9] demonstrated that benthic sediments release P into Utah Lake’s water column, suggesting that internal loading can contribute up to 1500 t of TP/year.” 𝑇𝑃!"#$=𝑀𝑎𝑠𝑠 𝑉𝑜𝑙𝑢𝑚𝑒=1,500 𝑡𝑜𝑛𝑛𝑒𝑠 800,000,000 𝑚% ≈2 𝑚𝑔 𝐿&' This internal loading rate estimate is only plausible for very short intervals at small spatial scales Conclusions 1.Utah Lake has a fantastic capacity to sequester phosphorus in its sediments, probably due to extensive calcite formation 2. Currently, WWTPs account for about 66% of TP and 82% of TDP loading to the Lake 3. Lake TP concentrations and phytoplankton biomass are directly dependent on external nutrient inputs and light limitation is not indicated 4. Internal loading increases summer phosphorus concentrations by 60-65% during the peak bloom period 5. Biological phosphorus removal in the WWTPs that discharge to Utah Lake would likely reduce average TPLAKE concentrations by >50% 6. Mass balance calculations indicate Utah Lake would recover from reduced external phosphorus loading very rapidly (< 1 year)