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Initialization values of chemical parameters in early spring for the lake-wide simulation in 2002. Table 1

Table 1 Initialization values of chemical parameters in early spring for the lake-wide simulation in 2002. Table 1

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Fig. 1. Map of Lake Erie showing the stations used for lake wide initialization (Table 1) plus (east basin only) stations used for simulated nearshore-offshore comparison study (App. E). Data on in-lake concentrations of phytoplankton Chl a, light attenuation, and water chemistry for model initialization and validation were taken from an Environment Canada-University of Waterloo study that sampled nearshore and offshore stations, mainly in the east basin, monthly from April to September (Depew et al., 2006, Smith unpub. data). Many of these data also reside in the ‘Star Database’, housed by the NWRI (National Water Research Institute) of Environment Canada. Observations from the U.S. E.P.A. spring survey cruise (Barbiero and Tuchman, 2001 describe stations and methods) provided the additional data necessary to describe the initial conditions in the lake at the beginning of the simulation period. Additional observations, mostly for central and west basins, were made available from the U.S. E.P.A. Lake Erie Trophic Status project (Matisoff and Ciborowski, 2005), and provided data in June, July, Settling rates specified for each group were comparable to several previous modeling studies (App. C) and within the considerable range reported in the literature. Other loss rates (respiration, excretion and mortality) could vary from about 5 to 50% of biomass per day among groups and with changing temperature, given the chosen parameters. Under most conditions, losses would be in the range 6 to 25% of biomass per day. Respiration alone is mostly in the range 5-15% of
Fig. 1. Map of Lake Erie showing the stations used for lake wide initialization (Table 1) plus (east basin only) stations used for simulated nearshore-offshore comparison study (App. E). Data on in-lake concentrations of phytoplankton Chl a, light attenuation, and water chemistry for model initialization and validation were taken from an Environment Canada-University of Waterloo study that sampled nearshore and offshore stations, mainly in the east basin, monthly from April to September (Depew et al., 2006, Smith unpub. data). Many of these data also reside in the ‘Star Database’, housed by the NWRI (National Water Research Institute) of Environment Canada. Observations from the U.S. E.P.A. spring survey cruise (Barbiero and Tuchman, 2001 describe stations and methods) provided the additional data necessary to describe the initial conditions in the lake at the beginning of the simulation period. Additional observations, mostly for central and west basins, were made available from the U.S. E.P.A. Lake Erie Trophic Status project (Matisoff and Ciborowski, 2005), and provided data in June, July, Settling rates specified for each group were comparable to several previous modeling studies (App. C) and within the considerable range reported in the literature. Other loss rates (respiration, excretion and mortality) could vary from about 5 to 50% of biomass per day among groups and with changing temperature, given the chosen parameters. Under most conditions, losses would be in the range 6 to 25% of biomass per day. Respiration alone is mostly in the range 5-15% of
Loadings of suspended solids (SS), total P (TP) and total N (N) from Lake Erie tributaries for the period April 11-October 20, 2002, together with the cumulative flows.
Loadings of suspended solids (SS), total P (TP) and total N (N) from Lake Erie tributaries for the period April 11-October 20, 2002, together with the cumulative flows.
Fig. 2. Lake wide horizontal distribution of predicted epilimnetic chlorophyll-a concentrations (mg m7 3) with observed values for Aug 5-8, 2002.
Fig. 2. Lake wide horizontal distribution of predicted epilimnetic chlorophyll-a concentrations (mg m7 3) with observed values for Aug 5-8, 2002.
Fig. 3. Lake wide horizontal distribution of predicted epilimnetic TP concentrations (expressed here as mg L~') with observed values for August 5-8, 2002 methodology. Predictions and observations were nonetheless signif- icantly correlated overall, as seen best in log-log plots (Fig. 4c, R? =0.48, p<0.0001, n= 277; and 4 d, R*=0.40, p<0.0001, n= 208). The model tended to predict TP higher than the observations when observed TP was low (4 to 8 mgP m7). The cause for this bias is not known but may point to a need for more information about forms of P entering the lake (see Discussion). There was no evidence of bias in the relationship between predicted and observed Chl a (Fig. 4c). A similar analysis of predicted and observed soluble reactive silicate concentrations (not shown) indicated a highly significant correlation Time series comparisons between simulations and observations were made for several stations in east basin, where sampling was relatively frequent in 2002, and gave very similar results in terms of the predicted dynamics and correspondence with available observa- tions. At a station close to the deepest point of east basin (station 938, Fig. 1), for example, the simulated Chl a in the top 5 m was similar to observations (Fig. 5). Observations with a calibrated fluorometer gave better agreement with the simulated spring peak than did
Fig. 3. Lake wide horizontal distribution of predicted epilimnetic TP concentrations (expressed here as mg L~') with observed values for August 5-8, 2002 methodology. Predictions and observations were nonetheless signif- icantly correlated overall, as seen best in log-log plots (Fig. 4c, R? =0.48, p<0.0001, n= 277; and 4 d, R*=0.40, p<0.0001, n= 208). The model tended to predict TP higher than the observations when observed TP was low (4 to 8 mgP m7). The cause for this bias is not known but may point to a need for more information about forms of P entering the lake (see Discussion). There was no evidence of bias in the relationship between predicted and observed Chl a (Fig. 4c). A similar analysis of predicted and observed soluble reactive silicate concentrations (not shown) indicated a highly significant correlation Time series comparisons between simulations and observations were made for several stations in east basin, where sampling was relatively frequent in 2002, and gave very similar results in terms of the predicted dynamics and correspondence with available observa- tions. At a station close to the deepest point of east basin (station 938, Fig. 1), for example, the simulated Chl a in the top 5 m was similar to observations (Fig. 5). Observations with a calibrated fluorometer gave better agreement with the simulated spring peak than did
Fig. 4. Scatter plot of the observed vs. predicted epilimnetic (top 5 m) concentrations of chlorophyll-a (a, c) and total phosphorus (b, d) in all three basins; (a) and (b) show non- transformed data, while (c) and (d) show logarithmically transformed data.
Fig. 4. Scatter plot of the observed vs. predicted epilimnetic (top 5 m) concentrations of chlorophyll-a (a, c) and total phosphorus (b, d) in all three basins; (a) and (b) show non- transformed data, while (c) and (d) show logarithmically transformed data.
Fig. 5. Time series output of predicted concentrations of Chl-a, TP, TDP, SRP, SRSi and Kd for the top 5 m together with observations for station 938 (east basin).
Fig. 5. Time series output of predicted concentrations of Chl-a, TP, TDP, SRP, SRSi and Kd for the top 5 m together with observations for station 938 (east basin).
Fig. 6. Predicted phytoplankton succession in terms of biomass (treated as chlorophyll a equivalents) at 2 m depth at (a) station 23 in east basin and (b) station 970 in west basin.
Fig. 6. Predicted phytoplankton succession in terms of biomass (treated as chlorophyll a equivalents) at 2 m depth at (a) station 23 in east basin and (b) station 970 in west basin.
Fig. 7. Model predictions for May 15 (a, d, g), June 15 (b, e, h) and July 15 (c, f, i), showing vertically-averaged values of total P (a, b, c), Chl a (d, e, f) and SRP(g, h, i), all as mg m~° A simulated nearshore-offshore study was performed for east basin by computing the average values for a set of nearshore stations and comparing them to the averages for a set of offshore stations (Fig. 1). The comparison showed that nearshore stations were predicted to warm earlier than the offshore (Fig. 8). The simulation period was not long enough to capture the faster cooling that might be expected in the nearshore during the autumn. Nearshore stations were predicted to have higher concentrations of suspended solids Based on snapshot comparisons of spatial patterns and time series observations, ELCD appeared to generate values for all the variables examined that were in the correct range compared to available observations. For some of the key variables (Chl a, TP, SRP and SRSi)
Fig. 7. Model predictions for May 15 (a, d, g), June 15 (b, e, h) and July 15 (c, f, i), showing vertically-averaged values of total P (a, b, c), Chl a (d, e, f) and SRP(g, h, i), all as mg m~° A simulated nearshore-offshore study was performed for east basin by computing the average values for a set of nearshore stations and comparing them to the averages for a set of offshore stations (Fig. 1). The comparison showed that nearshore stations were predicted to warm earlier than the offshore (Fig. 8). The simulation period was not long enough to capture the faster cooling that might be expected in the nearshore during the autumn. Nearshore stations were predicted to have higher concentrations of suspended solids Based on snapshot comparisons of spatial patterns and time series observations, ELCD appeared to generate values for all the variables examined that were in the correct range compared to available observations. For some of the key variables (Chl a, TP, SRP and SRSi)
Nearshore-offshore comparison of chlorophyll-a (Chl-a, mg m~?) in the eastern basin of Lake Erie and the difference between nearshore and offshore Chl-a concentration: expressed as the percent of an average nearshore-offshore concentration (%). Observed values are reported as monthly averages for the years of 1973, 1974 and 1975 (EPA, 1980); * results with 11 inflows; ** results with 8 inflows, excluding all direct inflo o east basin.
Nearshore-offshore comparison of chlorophyll-a (Chl-a, mg m~?) in the eastern basin of Lake Erie and the difference between nearshore and offshore Chl-a concentration: expressed as the percent of an average nearshore-offshore concentration (%). Observed values are reported as monthly averages for the years of 1973, 1974 and 1975 (EPA, 1980); * results with 11 inflows; ** results with 8 inflows, excluding all direct inflo o east basin.
Fig. 8. Time series of nearshore and offshore epilimnetic (0-5 m) temperatures and concentrations of TSS, Chl a and SRP in the eastern basin of Lake Erie.
Fig. 8. Time series of nearshore and offshore epilimnetic (0-5 m) temperatures and concentrations of TSS, Chl a and SRP in the eastern basin of Lake Erie.
Average simulated concentrations of TP and SRP in the top 5m of nearshore and offshore zones of east basin of Lake Erie.
Average simulated concentrations of TP and SRP in the top 5m of nearshore and offshore zones of east basin of Lake Erie.
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Environmental EngineeringLake ErieENVIRONMENTAL SCIENCE AND MANAGEMENT
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