Scientific Literature

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1 Updated: 7 April 03 Print version Lecture #4 TOC & THMFP Models II Scientific Literature CEE 577 #4

2 NYC: Cannonsville Case Study CEE 577 #4

3 Cannonsville Reservoir Study Algal & THM Precursor Models Doerr, Stepczuk and others Cannonsville Reservoir Part of Catskill-Delaware Supply for NYC Dimictic; Eutrophic (impounded in 965) P avg = 30 µg/l Characteristics for 995 Hydraulics H mean = 9 m V = 373 x0 6 m 3 τ mean = 4.7 months SA = 9.3 x0 6 m DA = 60 x0 6 m Loading TOC =? x 0 kg/yr P =? x 0 3 kg/yr For more, see the literature at: CEE 577 #4 3

4 Inflow West Branch of Delaware River (WBDR) ~80% Three outflows Over spillway Withdrawal to aqueduct 0, 0** or 37 m below spillway Release at base of dam CEE 577 #4 4

5 Individual models CEE 577 #4 5

6 Forcing Functions Lower flows in 995, resulted in lower loadings CEE 577 #4 6

7 PAR Photosyntheticallyactive radiation Often defined as the light between 400 and 700 nm CEE 577 #4 7

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9 SOD For CEE 577 #4 9

10 SOD continued In-situ device CEE 577 #4 0

11 Model Performance Weekly measurement in water column Objective: monthly average within standard deviations CEE 577 #4

12 Performance II Systematic depletions of: Epilimnetic NO x Hypolimnetic DO Over-prediction of ammonia? CEE 577 #4

13 Performance: DO Progressive depletion of DO in hypolimnion CEE 577 #4 3

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15 Verification Problem with limited data in 994 CEE 577 #4 5

16 Verification CEE 577 #4 6

17 Verification CEE 577 #4 7

18 Performance: Withdrawal CEE 577 #4 8

19 Cannonsville THMs: General Info Major Papers Stepczuk, Martin, Longabucco, Bloomfield & Effler, 998 Allochthonous Contributions of THM Precursors in a Eutrophic Reservoir, J. Lake & Res. Mgmt., 4(/3) Stepczuk, Martin, Effler, Bloomfield & Auer, 998 Spatial and Temporal Patterns of THM Precursors in a Eutrophic Reservoir, J. Lake & Res. Mgmt., 4(/3) Stepczuk, Owens, Effler, Bloomfield & Auer, 998 A Modeling Analysis of THM Precursors for a Eutrophic Reservoir, J. Lake & Res. Mgmt., 4(/3) THMFP Method Method 570B of Standard Methods ph 7.0, 7 days, 5 C, dosed to get >.0 mg/l residual Average CV was 4% for field replicates CEE 577 #4 9

20 995 Data Severe Drought Net production of precursors in Epilimnion is evident from THMFP data Stepczuk et al., 998, J. Lake & Res. Mgmt., 4(/3) CEE 577 #4 0

21 Mass Balance Model: THMFP M = W E + S S = M W + E Terms W = allochthonous mass loading From tributaries E = mass export by outflow Spill + release + water supply withdrawal S = net autochthonous production Gross production - decay autochthonous allochthonous Stepczuk et al., 998, J. Lake & Res. Mgmt., 4(/3) CEE 577 #4

22 Mass Balance Model: DOC Mid-summer drop in S Not seen with THMFP Lower average S:W ratio.7 for THMFP 0.7 for TOC autochthonous allochthonous Stepczuk et al., 998, J. Lake & Res. Mgmt., 4(/3) CEE 577 #4

23 Mass Balance Model: S Monthly changes in S Incremental not cumulative No apparent correlation between net production of THMFP and DOC Raises questions about use of TOC as a surrogate for THMFP Stepczuk et al., 998, J. Lake & Res. Mgmt., 4(/3) CEE 577 #4 3

24 -Layer model Spatial resolution Epilimnion Designated or E Hypolimnion Designated or H Loading (W) Measured stream data for epilimnion V V dc dt dc dt = W = W Q c + Q c 0 + E Outflow (Q) Separated based on withdrawal location Mixing (E) From temperature data Net production (S) Not directly observed + E ( c ( c c c ) V S ) V S Stepczuk et al., 998, J. Lake & Res. Mgmt., 4(/3) CEE 577 #4 4

25 Estimation of vertical Dispersion Coefficient Use analogous -layer temperature model V T t E = E A z = ( ) ( T T ) ( t ) ( t ) T T V z T T ta Apply measured temperature profiles to get E Owens, 998, J. Lake & Res. Mgmt., 4(/3)5-6 CEE 577 #4 5

26 Fitting S to Data S & S determined by fitting curves to data Adjust S to match model predictions to data Keep S at zero S & S equal to 0 CEE 577 #4 6

27 Select of S (cont.) Intermediate option Fit S to data Set S to zero Justification for S =0 No algal growth in hypolimnion Allochthonous THMFP originally trapped in hypolimnion is recalcitrant Stepczuk et al., 998, J. Lake & Res. Mgmt., 4(/3) CEE 577 #4 7

28 Mechanistic Model for S d Sub-model for algal FP production ( THMFP) dt = α = α TTHMFP TTHMFP Depends on: µ A Algal concentration (A) from measured Chl (C T ) Light Function From Microcosm studies Data fit data to Steele s Equation E =50 µ I FLz µ max ( FN)( FL I L = z z m s Stepczuk et al., 998, J. Lake & Res. exp Mgmt., 4(/3) K CEE 577 #4 8 L K L R = z ) A µ g THMPF max 5 µ g Chl day K

29 Mechanistic Model for S Sub-model for degradation of THMFP Independent st order loss terms for autochthonous and allochthonous forms d ( THMFP ) d dt THMFP dt autochthonous ( ) allochthonous = k = k L( au) L( al) THMFP THMFP autochthonous allochthonous CEE 577 #4 9

30 Mechanistic Model Results based on: Two Scenarios No decay of any THMFP in hypolimnion No decay of allochthonous THMFP Fitted K L values Epilimnion: k L(al) =k L(au) =0.08d - Hypolimnion: k L(al) =k L(au) =0.00d - Epilimnion: k L(al) =0.00; k L(au) =0.5d - Hypolimnion: k L(al) =0.00; k L(au) =0.5d - Stepczuk et al., 998, J. Lake & Res. Mgmt., 4(/3) CEE 577 #4 30

31 -Layer model Spatial resolution Epilimnion Designated or E Hypolimnion Designated or H S & S determined by fitting curves to data V V dc dt dc dt = W = W Q c + Q c 0 + E Stepczuk et al., 998, J. Lake & Res. Mgmt., 4(/3) E ( c ( c c c ) V S ) V S CEE 577 #4 3

32 To next lecture CEE 577 #4 3