Post-calibration of YSI chlorophyll A Gang of N Production 27 July 2005 Bill Romano – MD DNR Elgin...
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Transcript of Post-calibration of YSI chlorophyll A Gang of N Production 27 July 2005 Bill Romano – MD DNR Elgin...
Post-calibration of YSI chlorophyll
A Gang of N Production27 July 2005
Bill Romano – MD DNR
Elgin Perry – Statistics consultant
Beth Ebersole – MD DNR
Marcia Olson - NOAA
Elgin and I considered four methods
• Arithmetic mean ratio• First subtracting 0.03 x turbidity
from YSI chlorophyll then using a temperature adjustment (VIMS)
• Using temperature and turbidity• Temperature only
Data used in the analyses
• 522 station and time matched pairs of extractive and YSI chlorophyll data
• Data set was split into calibration and validation data sets using a random number SAS function
• The first 261 records were assigned to the calibration data set
Arithmetic mean ratio
• RatioAdj = Extractive chl-a / YSI chlorophyll
• Calculate the mean ratio for each station• Multiply the station mean ratio by YSI
chlorophyll from the validation data set• Calculate the root mean square error
using the difference between post calibrated and extractive chlorophyll from the validation data set
• RMSE across all stations is 21.17
Turbidity adjusted data
• Subtract the YSI recommended turbidity interference factor (0.03 μg/L per NTU) from each chlorophyll reading
• Calculate the log ratio (logCE – logCFtc)• Model the log ratio as a function of
temperature• Post calibrate using predicted ratio and
turbidity adjusted YSI chlorophyll• RMSE across all stations is 20.79
Temperature and turbidity adjustment
• Calculate the log ratio (logCE – logCF)
• Model the log ratio as a function of temperature and turbidity
• Post-calibrate using the predicted ratio and YSI chlorophyll
• RMSE across all stations is 20.43
Temperature only adjustment
• Calculate the log ratio (logCE – logCF)
• Model the log ratio as a function of temperature
• Post-calibrate using the predicted ratio and YSI chlorophyll
• RMSE across all stations is 20.96
Does turbidity contribute that much to the model?
• The p-value (type I and type III sums of squares) is 0.17 for the turbidity coefficient in the temperature and turbidity model
• The turbidity coefficient in: CHLapred = 3.230 + 1.132 x (chlYSI) – 0.015 x (turb), is half what YSI recommends (-0.03)
• Should we use it?
How do extractive and YSI chlorophyll compare?
• A comparison of log ratio (CF – CE) chlorophyll values using the Wilcoxon test indicates that many stations are significantly different
• Of the twenty-four station differences, only one was positive, so extractive chla exceeds YSI chlorophyll
• One would expect the opposite result, because the sonde provides a measure of “total” chlorophyll
Mean of extractive and YSI chlorophyll
Station YSI chl chla p-value
CCM0069 19.84 20.27 0.1187
CHE0348 10.19 15.27 0.1157
CTT0001 27.73 34.65 0.0775
FRG0002 11.00 13.43 0.0006
MDR0038 18.46 24.27 0.0068
MTI0015 3.60 4.83 0.9442
PXT0311 6.10 7.29 0.3258
PXT0455 5.66 6.74 0.9312
SEV0116 (+)
27.89 26.21 0.4903
TRQ0088 19.67 31.95 0.0020
TUV0021 24.07 30.32 0.0002
WXT0013 4.16 4.42 0.5112
Mean of extractive and YSI chlorophyll
Station YSI chl chla p-value
XCF9029 22.92 23.82 0.3484
XCH8097 8.42 10.68 0.0413
XDE4587 16.34 17.60 0.4307
XDM4486 49.49 70.93 0.0225
XED0694 20.82 56.72 <0.0001
XHE1973 16.18 22.62 <0.0001
XHF3719 27.71 30.42 0.0191
XIH0077 8.00 6.75 0.1074
XJF4289 6.48 10.02 0.0195
XJG2718 7.45 13.40 <0.0001
XJG4337 5.69 7.76 0.0006
XJG7035 5.64 12.03 <0.0001
Simple ratio adjustment factors differ from station to station
Station Ratio
CCM0069 0.928
CHE0348 1.203
CTT0001 1.424
FRG0002 1.421
MDR0038 1.344
MTI0015 0.956
PXT0311 1.002
PXT0455 1.195
SEV0116 0.842
TRQ0088 1.503
TUV0021 1.229
WXT0013 0.992
(see LSD output)
Simple ratio adjustment factors(continued)
Station Ratio
XCF9029 1.247
XCH8097 1.451
XDE4587 1.161
XDM4486 1.496
XED0694 1.713
XHE1973 1.864
XHF3719 1.223
XIH0077 0.834
XJF4289 1.600
XJG2718 1.696
XJG4337 1.363
XJG7035 1.966
(see LSD output)
Observations with RSTUDENT greater in absolute value than 2 may need some attention.
Are some values too “influential”?
Large values of DFFITS indicate influential observations. A general cutoff to consider is 2.
Influential data points?
- Ratio Method
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