A Review of the Components, Coefficients and Technical Assumptions of Ontario's Lakeshore Capacity Model (original) (raw)
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Water Resources Research, 2004
A steady state lake phosphorus (P) mass balance model was used to predict the equilibrium P concentration (annual, volume-weighted average) of the lake water from natural and anthropogenic, external and internal P inputs. Internal P load was modeled as the product of sediment release rates and anoxic factors. Both these components were predicted from lake P concentration computed from external load to create a link between external and internal load components. Such estimates allow the modeling and setting of objectives of several hundred lakes on the Canadian Shield. In particular, estimates of predevelopment lake P concentration made by removing all anthropogenic inputs were compared with postdevelopment conditions in which additional loading was added to the model. This was accomplished by determining how much development would increase external as well as internal phosphorus load and ultimately annual average lake P concentrations. By comparing proposed lake development scenarios with existing or predevelopment scenarios, it can be determined whether water quality objectives will be exceeded.
2002
Lake eutrophication continues to be a major concern in many lake regions, but long-term monitoring data are often lacking. Therefore, indirect proxy methods must be used to infer these missing data sets. Two methods were applied to infer pre-industrial and present-day lakewater total phosphorus concentrations (TP) in a suite of 50 hardwater lakes in southern Ontario (Canada). One method inferred TP from the diatom species composition in the tops (present-day inferences) and bottoms (pre-1850 inferences) of sediment cores. The other method applied the Lakeshore Capacity Model (LCM), which is a mass-balance model based on phosphorus export coefficients that relate lakes and their watershed characteristics to epilimnetic nutrient concentrations. Diatom-based estimates of preindustrial to present-day change show that 78% of the lakes increased in TP (29% significantly) and 8% decreased. According to model error, 63% of the lakes have not significantly changed. LCM estimates show that 56% of the lakes have increased in TP, and the remainder (44%) have not changed. The average inferred increase in TP was similar for both models, but a lake-by-lake comparison indicated marked differences in model output. In particular, a paired comparison of diatom-based and LCM-based inferences of preindustrial TP shows no correlation. It is suggested that lake managers be thorough when collecting data for either model, and model selection should be carefully considered. The LCM and diatom-based models perform better in regions that are geologically similar to where the respective models were calibrated. Advantages and disadvantages of each model are further discussed.
Great Lakes total phosphorus revisited: 2. Mass balance modeling
Journal of Great Lakes Research, 2012
Mass balance models are used to simulate chloride and total phosphorus (TP) trends from 1800 to the present for the North American Great Lakes. The chloride mass balance is employed to estimate turbulent eddy diffusion between model segments. Total phosphorus (TP) concentrations are then simulated based on estimated historical and measured TP loading time series. Up until about 1990, simulation results for all parts of the system generally conform to measured TP concentrations and exhibit significant improvement due primarily to load reductions from the Great Lakes Water Quality Agreement. After 1990, the model simulations diverge from observed data for the offshore waters of all the lakes except Lake Superior with the observations suggesting a greater improvement than predicted by the model. The largest divergence occurs in Lake Ontario where the model predicts that load reductions should bring the lake to oligo-mesotrophic levels, whereas the data indicate that it is solidly oligotrophic and seems to be approaching an ultra-oligotrophic state. Less dramatic divergences also occur in the offshore waters of lakes Michigan, Huron and Erie. In order to simulate these outcomes, the model's apparent settling velocity, which parameterizes the rate that total phosphorus is permanently lost to the lake's deep sediments, must be increased significantly after 1990. This result provides circumstantial support for the hypothesis that Dreissenid mussels have enhanced the Great Lakes phosphorus assimilation capacity. Finally, all interlake mass transfers of TP via connecting channels have dropped since phosphorus control measures were implemented beginning in the mid-1970s.
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Managing Phosphorus Inputs Into Lakes II. Crafting an Accurate Phosphorus Budget for Your Lake
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Ecological Modelling, 2013
We test the capacity of an existing simple mass-balance total phosphorus (TP) model to evaluate nutrient loading scenarios in the Bay of Quinte, Ontario, Canada. Our study examines whether model parameters and loading inputs are well characterized and relevant to the current conditions in the Bay of Quinte and its drainage areas. We also identify critical data gaps and influential assumptions in regard to the uncertainty of model outputs and the credibility of predictive statements about the achievability of delisting objectives of the system. Our analysis shows that the model closely reproduced the observed variability of the TP seasonal averages during the calibration period 1972-2001, but its performance was significantly reduced when the actual predictive capacity was assessed in the 2002-2009 validation period. The most troublesome result is the inability of the model to reproduce the observed TP variability at temporal scales that are more meaningful from an environmental management point of view (i.e., monthly averages or daily snapshots from the system). Sensitivity analysis shows that several parameters associated with the role of the sediments were significant drivers of the model outputs, suggesting that considerable uncertainty exists in regard to the characterization of the sediments. The loadings from Trent River and the TP levels of the inflowing water masses from Lake Ontario predominantly shape the variability in the upper and lower segments of the Bay of Quinte, respectively. We also present a critical review of the suitability of the existing water quality criteria to depict the trophic status throughout the system. Our study contends that the summer average TP concentrations do not adequately reflect the prevailing conditions and that the development of proper water quality criteria should place more emphasis on inshore sites, where the eutrophication problems are more frequently manifested. Finally, we pinpoint factors unaccounted for by the original model that are likely to modulate the response of the system in its present state. We also discuss important directions of model structure augmentation and ways to optimize the spatial segmentation.
A budget model accounting for the positional availability of phosphorus in lakes
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The mass balance relationships of Tonnolli (Mera. 1st. ltal. ldrobiol. 17, 247-266. 1964) and Vollenweider (Archs Hydrobiol. 66, 1-36. 1969) are combined in a phosphorus budget model. This model accounts for both the rapid settling of allochthonous particles and the slow settling of autochthonous particles that remove phosphorus from the water column. The effect of resuspension of bottom sediments is modeled by making the apparent settling velocity a function of lake depth. The resuspension effect is important for lakes less than 10 m deep.
A multi-model approach to evaluating target phosphorus loads for Lake Erie
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Lake models that predict phosphorus (P) concentrations from P-loading have provided important knowledge enabling successful restoration of many eutrophic lakes during the last decades. However, the first-generation (static) models were rather imprecise and some nutrient abatement programs have therefore produced disappointingly modest results. This study compares 12 first-generation models with three newer ones. These newer models are dynamic (time-dependent), and
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