Appendix 2. Model Archival Summary for Chlorophyll Concentration

at Station 06892350; Kansas River at De Soto, Kansas, during July 26, 

2012, through June 10, 2014

This model archival summary summarizes the chlorophyll (Chl; uncorrected for degradation products) concentration model developed 

to estimate Chl concentrations using YSI Model 6025 sensor-measured 15-minute chlorophyll fluorescence (fChl) data during July 26, 

2012, through June 10, 2014. 

Site and Model Information

Site number: 06892350

Site name: Kansas River at De Soto, Kansas

Location: Lat 38°59'00", long 94°57'52" referenced to North American Datum of 1927, in NE 1/4 SE 1/4 SE 1/4 sec.28, T.12 S., R.22 

E., Leavenworth County, KS, Hydrologic Unit 10270104.

Equipment: A YSI 6600 water-quality monitor equipped with model 6025 fChl sensor was installed during July 2012 through June

2014. The monitor was housed in a 4-inch diameter galvanized steel pipe. Readings from the water-quality monitor were recorded 

every 15 minutes and transmitted by way of satellite, hourly. Sensor maximum was not exceeded during this time (operable range: 0 

to 400 micrograms per liter).

Date model was created: August 3, 2017

Model calibration data period and application date: July 26, 2012–June 10, 2014

Model-Calibration Dataset

All data were collected using U.S. Geological Survey protocols (U.S. Geological Survey, variously dated; 

https://water.usgs.gov/owq/FieldManual/; Wagner and others, 2006) and are stored in the National Water Information System (U.S. 

Geological Survey, 2018) database and available to the public. Calibration of the fChl sensor was periodically checked (quarterly), 

and recalibrated if needed, using the YSI-recommended Rhodamine WT dye solution and YSI-provided calibration tables (Yellow 

Springs Instruments, 2012). If recalibration was required, calibration check data were used to apply prorated calibration drift 

corrections to the sensor-measured fChl data during the sensor-deployment time period. Ordinary least squares analysis was used to 

develop regression models between sensor-measured fChl and laboratory-measured Chl (uncorrected for degradation products) at the 

Kansas River at De Soto, Kansas (Kans.), site using the open-source software package “R.” This model is specific to the Kansas River 

at De Soto site during this study period and cannot be applied to data collected from other sites on the Kansas River or data collected 

from other water bodies.

The final selected regression model is based on 30 concurrent measurements of sensor-measured fChl and laboratory-measured Chl 

collected during July 26, 2012, through June 10, 2014. Samples were collected throughout the range of continuously observed 

hydrologic conditions. No samples were below laboratory detection limits. Summary statistics and the complete model-calibration 

dataset are provided below. Studentized residuals from the final model were inspected for values greater than three or less than 

negative three. Values outside of that range were considered potential outliers and were investigated. None of the samples in this 

dataset were deemed outliers or removed from the model calibration dataset.

Chlorophyll Sampling Details

Cross-section samples were typically collected either from the downstream side of the bridge or instream within 100 feet of the bridge. 

The equal-width-increment method was used, and samples typically were composited for analysis. During August 2012 through June 

2014, cross-section samples were collected every 2 weeks during March through October, once a month during November through 

February, and during selected reservoir release and runoff events. A FISP US DH-95 or D-95 depth integrating sampler was used from 

the downstream side of the bridge. Additional detail on sample collection is available in Graham and others (2018). Chl (uncorrected 

for degradation products) was analyzed fluorometrically using U.S. Environmental Protection Agency Method 445.0 (Arar and 

Collins, 1997) modified for heated ethanol extraction (Sartory and Grobbelaar, 1984 and a fluorometer equipped with a flow-through 

cell (Knowlton, 1984) at the U.S. Geological Survey Kansas Water Science Center in Lawrence, Kans.
Model Development

Ordinary least squares regression analysis was done using R version 3.4.2 (R Core Team, 2017) with sensor-measured fChl as the 

explanatory variable for laboratory-measured Chl concentrations. The distribution of residuals was examined for normality, and the 

plots of residuals (the difference between the measured and computed values) were examined for homoscedasticity (meaning that their 

departures from zero did not change substantially over the range of computed values). 

Values for all the aforementioned statistics were computed and are included below along with all relevant sample data and more indepth statistical information. 

Model Summary

The following is a summary of final regression analysis for sensor-measured fChl and laboratory-measured Chl at the Kansas River at 

De Soto, Kans., streamgage (U.S. Geological Survey station number 06892350) during July 26, 2012, through June 10, 2014.

Chl concentration model:

CChllEE = 2.29 × ff hll + 14

where 

ChlE = regression estimated chlorophyll (uncorrected for degradation products) concentration in micrograms per liter; and 

fChl = sensor-measured chlorophyll fluorescence in micrograms per liter.
R Output for the relation between YSI model 6025 sensor-measured chlorophyll 

fluorescence and laboratory-measured chlorophyll concentration; 06892350; 

Kansas River at De Soto, Kansas

Model Statistics, Data, and Plots

Definitions for terms used in this output can be found at the end of this 

document. 

Model

ChlE = + 2.29 * fChl + 14

Variable Summary Statistics

 Chl fChl

Minimum 11.3 2.63

1st Quartile 27.6 8.60

Median 82.0 23.60

Mean 81.3 29.40

3rd Quartile 125.0 49.00

Maximum 181.0 67.60

Box Plots
Exploratory Plots

Red line shows the locally weighted scatterplot smoothing (LOWESS).
Basic Model Statistics

For a detailed explanation of the terms used below, refer to Helsel and Hirsch (2002). 

 

Number of Observations 30

Standard error (RMSE) 21.6

Upper Model standard percentage error (MSPE) 26.5

Lower Model standard percentage error (MSPE) 26.5

Coefficient of determination (R2) 0.835

Adjusted Coefficient of Determination (Adj. R2) 0.829

Explanatory Variables

 Coefficients Standard Error t value Probability(>|t|)

(Intercept) 14.00 6.890 2.04 5.09e-02

fChl 2.29 0.192 11.90 1.78e-12
Correlation Matrix

 Intercept fChl

Intercept 1.00 -0.82

fChl -0.82 1.00

Outlier Test Criteria

Leverage Cook's D DFFITS 

 0.100 0.106 0.365

Flagged Observations

 Chl Estimate Residual Standard Residual Studentized Residual Leverage Cook's D DFFITS

5 159.0 126 32.6 1.560 1.610 0.0639 0.0833 0.420

7 94.9 130 -35.0 -1.680 -1.740 0.0692 0.1050 -0.476

19 181.0 116 65.2 3.100 3.760 0.0518 0.2630 0.879

30 125.0 169 -43.6 -2.190 -2.370 0.1490 0.4210 -0.991

42 150.0 168 -17.9 -0.899 -0.896 0.1470 0.0695 -0.371
Statistical Plots

Cross Validation

Fold - equal partition of the data (10 percent of the data)

Large symbols – observed value of a data point removed in a fold

Small symbols – recomputed value of a data point removed in a fold

Recomputed regression lines – adjusted regression line with one fold removed

 

 Minimum MSE of folds: 9.82

 Mean MSE of folds: 489.00

 Median MSE of folds: 290.00

 Maximum MSE of folds: 1720.00

(Mean MSE of folds) / (Model MSE): 1.05
Red line - Model MSE 

Blue line - Mean MSE of folds

Model-Calibration Data Set

 Date Chl fChl Computed Residual Normal Censored

 0 ChlE Quantiles Values

 1 7/30/2012 118 53.8 137 -19.5 -1.37 --

 2 8/9/2012 89.3 39.9 105 -16.1 -0.777 --

 3 8/13/2012 88.5 36.8 98.4 -9.9 -0.569 --

 4 8/27/2012 159 49 126 32.6 1.62 --

 5 9/10/2012 111 40.4 107 3.97 0.383 --

 6 9/24/2012 94.9 50.6 130 -35 -1.62 --

 7 10/15/2012 117 37.6 100 17.1 0.895 --

10 11/19/2012 39.8 11.9 41.3 -1.44 0.125 --

11 12/17/2012 17.1 4.65 24.7 -7.64 -0.383 --

12 1/14/2013 17.9 2.63 20.1 -2.18 -0.0415 --

13 2/11/2013 38.5 8.6 33.7 4.8 0.474 --

14 3/11/2013 57.6 19.8 59.3 -1.77 0.0415 --

15 4/8/2013 164 56.7 144 19.6 1.03 --
17 5/6/2013 45 12.7 43.2 1.81 0.209 --

18 5/20/2013 181 44.6 116 65.2 2.06 --

19 6/3/2013 75.4 16.6 52 23.5 1.18 --

20 6/17/2013 22.8 6.7 29.4 -6.64 -0.295 --

21 7/1/2013 27.6 7.8 31.9 -4.35 -0.125 --

22 7/15/2013 72.2 21.1 62.4 9.85 0.669 --

24 8/5/2013 23.7 9.9 36.7 -13 -0.669 --

26 8/19/2013 11.3 7.22 30.6 -19.3 -1.18 --

28 9/23/2013 94 21.7 63.7 30.2 1.37 --

29 10/21/2013 125 67.6 169 -43.6 -2.06 --

30 11/18/2013 67 25.5 72.4 -5.45 -0.209 --

32 12/16/2013 11.8 6.42 28.7 -16.9 -0.895 --

36 3/10/2014 18.3 5.3 26.2 -7.86 -0.474 --

38 4/7/2014 134 50.3 129 4.96 0.569 --

40 5/5/2014 136 47.7 123 12.7 0.777 --

41 5/19/2014 150 67.1 168 -17.9 -1.03 --

43 6/2/2014 132 50.6 130 2.23 0.295 --

Definitions

Chl: Chlorophyll a, fluorometric method, uncorrected, micrograms per liter (parameter 

code 32217).

ChlE: Estimated chlorophyll concentration, micrograms per liter.

Cook’s D: Cook’s distance (Helsel and Hirsch, 2002).

DFFITS: Difference in fits statistic (Helsel and Hirsch, 2002).

Leverage: An outlier’s measure in the x direction (Helsel and Hirsch, 2002).

LOWESS: Locally weighted scatterplot smoothing (Cleveland, 1979; Helsel and Hirsch,

2002).

MSE: Model standard error (Helsel and Hirsch, 2002).

MSPE: Model standard percentage error (Helsel and Hirsch, 2002).

Probability(>|t|): The probability that the independent variable has no effect on the

dependent variable (Helsel and Hirsch, 2002).

RMSE: Root mean square error (Helsel and Hirsch, 2002).

fChl: Chlorophyll, total, water, fluorometric, 650-700 nanometers, in situ sensor, 

micrograms per liter (parameter code 62361).

t value: Student’s t value; the coefficient divided by its associated standard error

(Helsel and Hirsch, 2002).
References Cited

Arar, E.J., and Collins, G.B., 1997, Method 445.0—In vitro determination of 

chlorophyll a and pheophytin a in marine and freshwater algae by 

fluorescence (rev. 1.2): U.S. Environmental Protection Agency, Office of 

Research and Development, 22 p.

Cleveland, W.S., 1979, Robust locally weighted regression and smoothing

scatterplots: Journal of the American Statistical Association, v. 74, p. 

829-836.

Graham, J.L., Foster, G.M., Williams, T.J., Mahoney, M.D., May, M.R., and Loftin, 

K.A., 2018, Water-quality conditions with an emphasis on cyanobacteria and associated 

toxins and taste-and-odor compounds in the Kansas River, Kansas, July 2012 through 

September 2016: U.S. Geological Survey Scientific Investigations Report 2018–5089, 55 

p., https://doi.org/10.3133/sir20185089.

Helsel, D.R., and Hirsch, R.M., 2002, Statistical methods in water resources—Hydrologic 

analysis and interpretation: U.S. Geological Survey Techniques of Water-Resources

Investigations, book 4, chap. A3, 510 p.

Knowlton, M.F., 1984, Flow-through microcuvette for fluorometric determination of 

chlorophyll: Water Resources Bulletin, v. 20, p. 1198–1205.

R Core Team, 2017, R——A language and environment for statistical computing: Vienna, 

Austria, R Foundation for Statistical Computing. [Also available at https://www.Rproject.org/.]

Sartory, D.P., and Grobbelaar, J.U., 1984, Extraction of chloro¬phyll a from 

freshwater phytoplankton for spectrophotomet¬ric analysis: Hydrobiologia, v. 114, no. 

3, p. 177–187.

U.S. Geological Survey, variously dated, National field manual for the collection of

water-quality data: U.S. Geological Survey Techniques of Water-Resources

Investigations, book 9, chaps. A1–A9 [variously paged].

U.S. Geological Survey, 2018, National Water Information System—Web interface: accessed 

January 2017 at https://doi.org/10.5066/F7P55KJN.

Wagner, R.J., Boulger, R.W., Jr., Oblinger, C.J., and Smith, B.A., 2006, Guidelines 

and standard procedures for continuous water-quality monitors—Station operation, 

record computation, and data reporting: U.S. Geological Survey Techniques and 

Methods, book 1, chap. D3, 51 p. + 8 attachments, accessed April 10, 2006, at 

https://pubs.water.usgs.gov/tm1d3.

Yellow Springs Instruments, 2012, 6-Series Multiparameter Water Quality Sondes—User 

manual: Yellow Springs Instruments, 379 p.