U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2013–5071

Prepared in cooperation with the city of Wichita, Kansas 

Continuous Real-Time Water-Quality Monitoring and 

Regression Analysis to Compute Constituent Concentrations

and Loads in the North Fork Ninnescah River Upstream from 

Cheney Reservoir, South-Central Kansas, 1999–2012
Cover photograph. Downstream view from the bridge, North Fork Ninnescah River above Cheney Reservoir, Kansas, 2010. Photograph by 

Barbara Dague, U.S. Geological Survey.

Back cover photograph. Upstream view from the bridge, North Fork Ninnescah River above Cheney Reservoir, Kansas, 2007. Photograph by 

Trudy Bennett, U.S. Geological Survey.
Continuous Real-Time Water-Quality 

Monitoring and Regression Analysis to 

Compute Constituent Concentrations and 

Loads in the North Fork Ninnescah River 

Upstream from Cheney Reservoir, SouthCentral Kansas, 1999–2012

By Mandy L. Stone, Jennifer L. Graham, and Jackline W. Gatotho

Prepared in cooperation with the city of Wichita, Kansas 

Scientific Investigations Report 2013–5071

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2013

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Suggested citation:

Stone, M.L., Graham, J.L., and Gatotho, J.W., 2013, Continuous real-time water-quality monitoring and regression 

analysis to compute constituent concentrations and loads in the North Fork Ninnescah River upstream from Cheney 

Reservoir, south-central Kansas, 1999–2012: U.S. Geological Survey Scientific Investigations Report 2013–5071, 44 p.
iii

Acknowledgments

The authors appreciate the assistance of Howard Miller and Lisa French of Cheney Lake Watershed, Inc. for providing best management practices data. Vernon Strasser and laboratory staff of 

the Wichita Municipal Water and Wastewater Quality Laboratory provided laboratory analyses. 

The authors thank Jennifer Lanning-Rush and Spoorthi Tammareddi of the U.S. Geological Survey (USGS) Kansas Water Science Center (KSWSC) for creating maps and assistance with data 

analysis, respectively. Trudy Bennett and USGS Wichita Field Office employees collected waterquality samples that were used to develop this report. Teresa Rasmussen of the USGS KSWSC 

and Nathan Schaepe of the USGS Nebraska Water Science Center provided helpful reviews that 

improved earlier drafts of this report.
iv

Contents

Acknowledgements......................................................................................................................................iii

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................2

Purpose and Scope ..............................................................................................................................3

Description of Study Area ...................................................................................................................4

Related Water-Quality Studies ...........................................................................................................5

Methods...........................................................................................................................................................6

Continuous Water-Quality Monitoring...............................................................................................6

Discrete Water-Quality Samples........................................................................................................6

Quality Assurance and Quality Control .............................................................................................7

Development of Regression Models to Compute Constituent Concentrations..........................8

Calculation of Annual Streamflow-Separation Points and Constituent Loads and Yields .......8

Calculation of Conversion Factors for Turbidity Sensors...............................................................9

Results of Continuously Monitored Variables...........................................................................................9

Results of Regression Analysis for Selected Constituents...................................................................11

Dissolved Solids, Chloride, and Other Major Ions.........................................................................11

Total Suspended Solids and Sediment............................................................................................16

Nutrients...............................................................................................................................................17

Escherichia coli Bacteria ..................................................................................................................17

New Models and Changes in Updated Models.............................................................................18

Turbidity, YSI Model 6026 and 6136 Sensors ...........................................................................................18

Computed Constituent Concentrations, Loads, and Yields...................................................................19

Dissolved Solids, Chloride, and Other Major Ions.........................................................................19

Total Suspended Solids and Sediment............................................................................................19

Nutrients...............................................................................................................................................20

Escherichia coli Bacteria ..................................................................................................................22

Comparison of Total Suspended Solids, Nitrate, and Total Phosphorus with Cheney

Reservoir Task Force Goals .................................................................................................25

Summary........................................................................................................................................................28

References Cited..........................................................................................................................................29
v

Figures

1. Map showing location of continuous real-time water-quality monitoring site and

land use in the Cheney Reservoir watershed ..........................................................................3

2. Map showing location of implemented best management practices in the Cheney

Reservoir watershed, 1994–2011................................................................................................4

3. Graphs showing duration curves for hourly measured streamflow, specific

conductance, pH, water temperature, dissolved oxygen, and turbidity at the 

North Fork Ninnescah River upstream from Cheney Reservoir, south-central

Kansas, during 1999 through 2012............................................................................................10

4. Graphs showing relation between Yellow Springs Instruments model 6026 

and YSI model 6136 turbidity sensor values at the North Fork Ninnescah River 

upstream from Cheney Reservoir, south-central Kansas, October 2009 through 

October 2010................................................................................................................................18

5. Graphs showing duration curves for hourly computed dissolved solids, sodium, 

chloride, sulfate, total suspended solids, and suspended sediment at the North 

Fork Ninnescah River upstream from Cheney Reservoir, south-central Kansas, 

during 1999 through 2012...........................................................................................................21

6. Graphs showing computed annual streamflow, total suspended solids, 

suspended-sediment, total nitrogen, nitrate, and total phosphorus loads at the 

North Fork Ninnescah River upstream from Cheney Reservoir south-central

Kansas, during 1999 through 2012............................................................................................24

7. Graphs showing duration curves for hourly computed total nitrogen, nitrate, 

total phosphorus, and Escherichia coli bacteria at the North Fork Ninnescah

River upstream from Cheney Reservoir, south-central Kansas, during 1999 

through 2012 ................................................................................................................................25

8. Graphs showing annual mean streamflow, computed total suspended solids,

computed nitrate, and computed total phosphorus concentrations during base 

flow, runoff, and long-term streamflow conditions at the North Fork Ninnescah 

River upstream from Cheney Reservoir, south-central Kansas, during 1999 

through 2012 ................................................................................................................................27
vi

Tables

1. Cheney Reservoir Task Force mean stream water-quality goals for total suspended

solids, dissolved nitrate as nitrogen, and total phosphorus concentrations in

Cheney Reservoir watershed streams during base flow, runoff, and long-term

streamflow conditions1 ...............................................................................................................3

2. Total annual and annual mean precipitation during 1999 through 2012 and annual

mean precipitation during 1954 through 2012 at the “Wichita Mid Continent Airport”

(Global Historical Climatology Network–Daily:USW00003928) station1..............................5

3. Summary statistics for variables measured continuously at the North Fork

Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central

Kansas, for the period of record (daily) and 1999 through 2012 (hourly).............................7

4. Christensen and others (2006), updated, and new regression models and summary

statistics for continuous concentration computations for the North Fork Ninnescah

River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 1999

through 2009 ................................................................................................................................12

5. Summary of hourly statistics for selected water-quality constituents computed with

updated regression models and continuously measured variables at the North Fork

Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central

Kansas, 1999 through 2012 ........................................................................................................20

6. Annual means for continuously measured and computed constituents at the North

Fork Ninnescah River upstream from Cheney Reservoir (site 07144780),

south-central Kansas, during 1999 through 2012 ..................................................................22

7. Computed annual loads and yields for selected constituents at the North Fork

Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central

Kansas, during 1999 through 2012............................................................................................23

8. Summary statistics for selected water-quality constituents computed with updated

regression models and continuously measured physical properties at the North

Fork Ninnescah River upstream from Cheney Reservoir (site 07144780),

south-central Kansas, 1999 through 2012...............................................................................26
vii

Appendix Tables

1. Sample collection dates and streamflow conditions for discrete water-quality

samples included in regression model development for the North Fork Ninnescah

River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 

1999 through 2009 .......................................................................................................................36

 2. Christensen and others (2006), updated, and new regression models and

summary statistics for continuous concentration computations for the North Fork

Ninnescah River upstream from Cheney Reservoir, south-central Kansas, 1999 

through 2009 ................................................................................................................................38

3. Tobit regression models and summary statistics for constituents with leftcensored data for the North Fork Ninnescah River (site 07144780) upstream 

from Cheney Reservoir, south-central Kansas, 1999 through 2009 ....................................41

 4. Summary statistics for data used in turbidity sensor linear regression analyses 

for the North Fork Ninnescah River upstream from Cheney Reservoir, south-central 

Kansas, October 1999 through October 2010 .........................................................................42

5. Updated Christensen and others (2006) regression models for the North Fork 

Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central 

Kansas ..........................................................................................................................................43

6. Updated new regression models for the North Fork Ninnescah River upstream from 

Cheney Reservoir, south-central Kansas ...............................................................................44
viii

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

meter (m) 3.281 foot (ft) 

mile (mi) 1.609 kilometer (km)

micrometer (μm) 0.001 millimeter (mm)

Area

square mile (mi2) 2.590 square kilometer (km2) 

square meter (m2) 10.76 square feet (ft2)

Volume

milliliter (mL) 0.0338 ounce, fluid (oz)

cubic foot (ft3) 28.32 cubic decimeter (dm3) 

acre-foot (acre-ft) 1,233 cubic meter (m3)

Flow rate

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

milligram per liter (mg/L) 1 parts per million (ppm)

microgram per liter (μg/L) 1 parts per billion (ppb)

Mass

milligram (mg) 0.001 gram (g)

microgram (μg) 0.000001 gram (g)

ton per year (ton/yr) 0.9072 metric ton per year

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Temperature in degrees Fahrenheit (°F) may be converted to degrees Celsius (°C) as follows:

°C=(°F-32)/1.8

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius (μS/cm at 

25 °C).

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) 

or micrograms per liter (μg/L).
Continuous Real-Time Water-Quality Monitoring 

and Regression Analysis to Compute Constituent 

Concentrations and Loads in the North Fork Ninnescah 

River Upstream from Cheney Reservoir, South-Central 

Kansas, 1999–2012

By Mandy L. Stone, Jennifer L. Graham, and Jackline W. Gatotho

Abstract 

Cheney Reservoir, located in south-central Kansas, is the 

primary water supply for the city of Wichita. The U.S. 

Geological Survey has operated a continuous real-time 

water-quality monitoring station since 1998 on the North 

Fork Ninnescah River, the main source of inflow to Cheney 

Reservoir. Continuously measured water-quality physical 

properties include streamflow, specific conductance, pH, 

water temperature, dissolved oxygen, and turbidity. Discrete 

water-quality samples were collected during 1999 through 

2009 and analyzed for sediment, nutrients, bacteria, and 

other water-quality constituents. Regression models were 

developed to establish relations between discretely sampled 

constituent concentrations and continuously measured 

physical properties to compute concentrations of those 

constituents of interest that are not easily measured in real 

time because of limitations in sensor technology and fiscal 

constraints. 

Regression models were published in 2006 that were 

based on data collected during 1997 through 2003. This report 

updates those models using discrete and continuous data collected during January 1999 through December 2009. Models 

also were developed for four new constituents, including 

additional nutrient species and indicator bacteria. In addition, a conversion factor of 0.68 was established to convert 

the Yellow Springs Instruments (YSI) model 6026 turbidity 

sensor measurements to the newer YSI model 6136 sensor at 

the North Fork Ninnescah River upstream from Cheney Reservoir site. Newly developed models and 14 years of hourly 

continuously measured data were used to calculate selected 

constituent concentrations and loads during January 1999 

through December 2012. The water-quality information in 

this report is important to the city of Wichita because it allows 

the concentrations of many potential pollutants of interest to 

Cheney Reservoir, including nutrients and sediment, to be 

estimated in real time and characterized over conditions and 

time scales that would not be possible otherwise.

In general, model forms and the amount of variance 

explained by the models was similar between the original 

and updated models. The amount of variance explained by 

the updated models changed by 10 percent or less relative to 

the original models. Total nitrogen, nitrate, organic nitrogen, 

Escherichia coli bacteria, and total organic carbon models 

were newly developed for this report. Additional data collection over a wider range of hydrological conditions facilitated the development of these models. The nitrate model is 

particularly important because it allows for comparison to 

Cheney Reservoir Task Force goals.

Mean hourly computed total suspended solids concentration during 1999 through 2012 was 54 milligrams per liter 

(mg/L). The total suspended solids load during 1999 through 

2012 was 174,031 tons. On an average annual basis, the 

Cheney Reservoir Task Force runoff (550 mg/L) and longterm (100 mg/L) total suspended solids goals were never 

exceeded, but the base flow goal was exceeded every year 

during 1999 through 2012. Mean hourly computed nitrate 

concentration was 1.08 mg/L during 1999 through 2012. The 

total nitrate load during 1999 through 2012 was 1,361 tons. 

On an annual average basis, the Cheney Reservoir Task Force 

runoff nitrate goal (6.60 mg/L) was never exceeded, the longterm goal (1.20 mg/L) was exceeded only in 2012, and the 

base flow goal of 0.25 mg/L was exceeded every year. Mean 

nitrate concentrations that were higher during base flow, 

rather than during runoff conditions, suggest that groundwater 

sources are the main contributors of nitrate to the North Fork 

Ninnescah River above Cheney Reservoir. Mean hourly computed phosphorus concentration was 0.14 mg/L during 1999 

through 2012. The total phosphorus load during 1999 through 

2012 was 328 tons. On an average annual basis, the Cheney 

Reservoir Task Force runoff goal of 0.40 mg/L for total 

phosphorus was exceeded in 2002, the year with the largest 
2 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

yearly mean turbidity, and the long-term goal (0.10 mg/L) was 

exceeded in every year except 2011 and 2012, the years with 

the smallest mean streamflows. The total phosphorus base 

flow goal of 0.05 mg/L was exceeded every year. Given that 

base flow goals for total suspended solids, nitrate, and total 

phosphorus were exceeded every year despite hydrologic conditions, the established base flow goals are either unattainable 

or substantially more best management practices will need to 

be implemented to attain them.

On an annual average basis, no discernible patterns were 

evident in total suspended sediment, nitrate, and total phosphorus concentrations or loads over time, in large part because 

of hydrologic variability. However, more rigorous statistical 

analyses are required to evaluate temporal trends. A more 

rigorous analysis of temporal trends will allow evaluation of 

watershed investments in best management practices.

Introduction

Cheney Reservoir (fig. 1), located in south-central Kansas, was constructed between 1962 and 1965 by the Bureau 

of Reclamation, U.S. Department of the Interior, to provide a 

municipal water supply for the city of Wichita, downstream 

flood control, wildlife habitat, and recreational areas. From 

1995 through 2010, water from Cheney Reservoir contributed 

between 51 and 69 percent of Wichita’s water supply (Ziegler 

and others, 2010). Water-supply needs and reliance on Cheney 

Reservoir will continue to increase with ongoing population 

growth and urban development. 

Cyanobacterial blooms can be harmful, and may result 

in high concentrations of toxins and taste-and-odor causing compounds. Taste-and-odor problems are a concern to 

drinking-water suppliers because of customer dissatisfaction with unpalatable drinking water and increased treatment 

costs to remove taste-and-odor causing compounds (Taylor 

and others, 2005). Sedimentation decreases reservoir life, 

may have a negative effect on benthic organisms, and creates 

lower light conditions which may favor cyanobacterial growth 

and proliferation (Waters, 1995; Chorus and Bartram, 1999; 

Graham and others, 2008). Excessive nutrients also may cause 

cyanobacterial blooms. Decomposition of these blooms may 

cause oxygen depletion and fish kills (Wehr and Sheath, 2003). 

The reduction in transport of sediment and nutrients would 

reduce excessive sedimentation and may reduce taste-and-odor 

problems in Cheney Reservoir by decreasing cyanobacterial 

abundance.

Taste-and-odor occurrences in Cheney Reservoir in 1990 

and 1991 prompted a task force to be formed in 1992. The 

Cheney Reservoir Task Force was asked to prepare a pollution 

management plan to identify and mitigate sources of water 

pollution in the watershed. The Cheney Reservoir Task Force 

consisted of members of the Reno and Sedgwick County Conservation Districts, Reno County Health Department, Wichita 

Water and Sewer Department, and other local, State, and 

Federal agencies. The Cheney Reservoir Task Force prepared 

a water-quality plan to abate the transport of suspended solids, 

nutrients, and pesticides into the reservoir.

 The Cheney Reservoir Task Force identified total phosphorus and total suspended solids as primary pollutants of 

concern because of their relation to taste-and-odor producing 

cyanobacterial blooms and the effect they have on the quality 

and quantity of water in Cheney Reservoir. The Cheney Reservoir Task Force established stream water-quality goals for total 

suspended solids, nitrate, and total phosphorus during base 

flow, runoff, and long-term streamflow conditions (table 1; 

Cheney Reservoir Task Force, 1994). Total phosphorus and 

total suspended-solids concentration goals were established 

to reduce pollution and extend the life of Cheney Reservoir 

from 130 to 200 years (Cheney Reservoir Task Force, 1994). 

To achieve these goals, approximately 1,500 contracts were 

established for implementation of best management practices 

(BMPs) in the Cheney Reservoir watershed between 1994 and 

2011 and Conservation Reserve Program (CRP) land increased 

by approximately 20,475 acres (fig. 2; Cheney Lake Watershed Incorporated, written commun., 2011). 

The U.S. Geological Survey (USGS), in cooperation with 

the city of Wichita, has continuously monitored water quality 

on the North Fork Ninnescah River upstream from Cheney 

Reservoir (USGS stream-gaging station 07144780; fig. 1) 

since October 1998. Streamflow has been measured continuously on the North Fork Ninnescah River above Cheney 

Reservoir since July 1965. Water budget analysis during 1997 

through 2003 indicated that the North Fork Ninnescah River 

contributes about 70 percent of the water flowing into the 

reservoir (Christensen and others, 2006). Water-quality monitoring on the North Fork Ninnescah River provides hourly 

measures of specific conductance, pH, water temperature, dissolved oxygen, and turbidity. Numerous discrete water-quality 

samples have been collected at this site and used to develop 

regression models establishing relations between continuously 

monitored water-quality physical properties and water-quality 

constituents of interest that are not monitored continuously. 

These models are useful for evaluating concentrations of 

water-quality constituents to compare with water-quality criteria, and for computing loads and yields to assess watershed 

transport. 

Twelve years (1997 through 2008) of regressioncomputed total suspended solids and total phosphorus data 

for the North Fork Ninnescah River were compared with the 

water-quality goals set by the Cheney Reservoir Task Force 

(Stone and others, 2009; table 1). Base flow total suspended 

solids and total phosphorus goals were not met based on 

1997 through 2008 data; however, long-term and runoff total 

suspended solids and runoff total phosphorus goals rarely were 

exceeded. Because total suspended solids and total phosphorus 

concentrations exceeded base flow goals in 2006, an extremely 

dry year, it was concluded that the established base flow goals 

may be unattainable or substantially more BMPs would be 

needed to attain them. The current (2013) study is a more 

comprehensive evaluation of water-quality conditions and 
Introduction 3

watershed transport of constituents of concern in the North 

Fork Ninnescah River, the main tributary to, and thus one of 

the key contributors to, water quality in Cheney Reservoir. 

Previously published models were improved by incorporating 

more data, models for additional constituents were developed, 

and loads were calculated for a longer time period using the 

updated models. 

Purpose and Scope

The purpose of this report is to update regression models 

that establish relations between continuous and discrete 

water-quality data collected from the North Fork Ninnescah River upstream from Cheney Reservoir (USGS site 

07144780; fig. 1). The models are used to compute concentrations and loads for 20 water-quality constituents of interest 

and to describe water-quality during 1999 through 2012. 

Irish Cr

Silver Creek

Goose Creek

Red Rock Creek

North Fork Ninnescah River

Wolf Creek

Cheney

Reservoir

Nester Creek

Mod Cr

Polecat

Creek Soldier Cr

Smoots Creek

Wild Run Cr

Arkansas River

Pat Creek

Rock Creek

Kisiwa Creek

Coon Cr

Silver Creek

Turkey Cr

Goose Creek

Petyt Creek

Salt Creek

Mead Creek

Rattlesnake Creek

Pickle Creek

Wild Horse Creek

Little Wild Horse Creek

Bear Creek

Peace Creek

Sugar Creek

Big Slough

Red Rock Creek

North Fork Ninnescah River

Wolf Creek

Thompson

Sand Creek

South Fork Ninnescah River

Painter Creek

Negro Cr

Hunter Creek

Cheney

Reservoir

SpringCreek

Gar

Creek

Cr

Irish Cr

!

!

07144780

SEDGWICK

COUNTY

KINGMAN

COUNTY

KIOWA

COUNTY

PRATT

COUNTY

PAWNEE

COUNTY STAFFORD

COUNTY

EDWARDS

COUNTY

RENO

COUNTY

Castleton

Stafford

Castleton

Dooleyville Cr

99° 98°45' 98°30' 98°15' 98° 97°45'

38°

37°50'

37°40'

Dooleyville Cr

Base modified from U.S. Geological Survey

1:100,000-scale digital data, 2005

Land use data modified from Kansas Applied 

Remote Sensing Program (2009)

Wichita

Land use, 2005

Urban

Cropland

Grassland

Conservation Reserve Program

EXPLANATION

Woodland

Water

Wheat

Cheney Reservoir

drainage area

07144780 U.S. Geological Survey station and identifier

0

0

5 10 15 MILES 20

5 15 KILOMETERS 10 20

KANSAS

Watershed boundary

Figure 1. Location of continuous real-time water-quality monitoring site and land use in the Cheney Reservoir watershed.

Table 1. Cheney Reservoir Task Force mean stream waterquality goals for total suspended solids, dissolved nitrate as 

nitrogen, and total phosphorus concentrations in Cheney 

Reservoir watershed streams during base flow, runoff, and longterm streamflow conditions.*

Water-quality constituent

Mean water-quality goal 

(milligrams per liter)

Base flow Runoff Long term

Total suspended solids 20 550 100

Dissolved nitrate as nitrogen 0.25 6.60 1.20

Total phosphorus 0.05 0.40 0.10

*

Cheney Reservoir Task Force, 1994.
4 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

Silver Creek

Goose Creek

Red Rock Creek

North Fork Ninnescah River

Wolf Creek

Cheney

Reservoir

Nester Creek

Mod Cr

Polecat

Creek Soldier Cr

Smoots Creek

Wild Run Cr

Arkansas River

Pat Creek

Rock Creek

Kisiwa Creek

Coon Cr

Silver Creek

Turkey Cr

Goose Creek

Petyt Creek

Salt Creek

Mead Creek

Rattlesnake Creek

Pickle Creek

Wild Horse Creek

Little Wild Horse Creek

Bear Creek

Peace Creek

Sugar Creek

Big Slough

Red Rock Creek

North Fork Ninnescah River

Wolf Creek

Thompson

Sand Creek

South Fork Ninnescah River

Painter Creek

Negro Cr

Hunter Creek

Cheney

Reservoir

SpringCreek

Gar

Creek

Cr

Irish CrIrish Cr

!

!

07144780

SEDGWICK

COUNTY

KINGMAN

COUNTY

KIOWA

COUNTY

PRATT

COUNTY

PAWNEE

COUNTY STAFFORD

COUNTY

EDWARDS

COUNTY

RENO

COUNTY

Castleton

Stafford

Castleton

Dooleyville Cr

99° 98°45' 98°30' 98°15' 98° 97°45'

38°

37°50'

37°40'

Dooleyville Cr

Base modified from U.S. Geological Survey

1:100,000-scale digital data, 2005

EXPLANATION

Conservation practices, various years 1994–2011

Water boundary dataset subbasin, 12-digit hydrologic unit code

U.S. Geological Survey streamgaging station and identifier

Data from the U.S. Department of Agriculture, 2012

07144780

0

0

5 10 15 MILES 20

5 15 KILOMETERS 10 20

Watershed boundary

Figure 2. Location of implemented best management practices in the Cheney Reservoir watershed, 1994–2011.

Regression models originally were published by Christensen Description of Study Area and others (2006) using data collected during 1997 through 

2003 for 15 water-quality constituents, including total 

suspended solids, suspended-sediment, dissolved solids and 

major ions, total Kjeldahl nitrogen, total phosphorus, orthophosphate, and fecal coliform bacteria. In this report, those 

regression models are updated using data collected through 

2009, and additional models are developed for nitrate, organic 

nitrogen, Escherichia coli (E. coli) bacteria, and total organic 

carbon. A site-specific relation between continuous turbidity measurements from the older Yellow Springs Instruments 

(YSI) model 6026 and newer YSI model 6136 turbidity 

sensors also was developed so the YSI 6026 sensor could be 

replaced with the YSI 6136 sensor while retaining the ability 

to make comparisons to historical data. The updated and new 

models in this report are useful for evaluating concentrations 

of water-quality constituents to compare with water-quality 

criteria and for computing loads and yields to assess constituent transport through the watershed. The water-quality 

information in this report is important to the city of Wichita 

because it quantifies and characterizes potential pollutants, 

including nutrients and sediment, transported into Cheney 

Reservoir. 

The Cheney Reservoir watershed is located in southcentral Kansas (fig. 1) and has a contributing drainage area 

of 933 square miles (mi2

). The North Fork Ninnescah River 

is the largest tributary to Cheney Reservoir and contributes 

about 70 percent of the inflow (Christensen and others, 2006). 

The North Fork Ninnescah River above Cheney Reservoir, 

Kansas monitoring site (USGS stream-gaging station number 

07144780), where continuous water-quality data have been 

collected since October 1998, has a drainage area of 734 mi2

.

Land use in the Cheney Reservoir watershed predominately is rural (fig. 1); less than 1 percent of the land use in 

the watershed is classified as urban. All agricultural crops, 

including wheat, comprise about 55 percent of land use in the 

watershed above the North Fork Ninnescah River site. About 

25 percent of the North Fork Ninnescah River site’s watershed is grassland and about 18 percent is conservation reserve 

program (CRP) land (Peterson and others, 2005).

The mean annual temperature (1954 through 2012) in 

the study area is 57 degrees Fahrenheit (°F) and was approximately 1 degree higher (58 °F) for the 1999 through 2012 

study period (National Climatic Data Center, 2012). Mean 
Introduction 5

annual precipitation in the study area was about 31 inches during 1954 through 2012, and averaged 34 inches for the period 

during 1999 through 2012 (“Wichita Mid Continent Airport” 

station; National Climatic Data Center, 2012; table 2).

Kansas Department of Health and Environment (KDHE) 

defined designated uses for several streams within the Cheney 

Reservoir watershed (figs. 1, 2; Kansas Department of Health 

and Environment, 2010). Domestic water supply, food procurement (obtaining edible aquatic life for human consumption), groundwater recharge, industrial water supply, irrigation, 

and livestock watering are designated uses for parts of the 

North Fork Ninnescah River, Red Rock Creek, and Silver 

Creek. Food procurement, groundwater recharge, irrigation, 

and livestock watering are designated uses for Dooleyville 

Creek and Goose Creek. Domestic water supply, groundwater recharge, industrial water supply, irrigation, and livestock 

watering are designated uses for Rock Creek, Spring Creek, 

and Wolf Creek. Within the Cheney Reservoir watershed, 

Goose Creek, Red Rock Creek, and Silver Creek (figs. 1, 2) 

have food procurement as a designated use. 

KDHE has listed one stream in the North Fork Ninnescah 

River watershed and Cheney Reservoir as impaired waterways 

under section 303(d) of the 1972 Clean Water Act (Kansas 

Department of Health and Environment, 2012). Atrazine 

in Red Rock Creek (fig. 1) is listed as a pollutant impairing aquatic life. Siltation is listed as an impairment to water 

supply, and eutrophication and pH are listed as impairments to 

aquatic life in Cheney Reservoir. The North Fork Ninnescah 

River watershed had a total maximum daily load (TMDL) for 

pH starting above Cheney Reservoir and ending in Stafford 

County near Stafford (fig. 1) that was delisted in 2010; the 

water-quality standard stated that “artificial sources of pollution shall not cause the pH of any surface water outside the 

zone of initial dilution to be below 6.5 or above 8.5” (Kansas 

Department of Health and Environment, 2001). 

Related Water-Quality Studies

Since 1996, USGS has conducted several studies in the 

Cheney Reservoir watershed in cooperation with the city 

of Wichita, Kansas. During June and September 1996, the 

spatial variability in concentrations of dissolved nutrients, 

atrazine, and fecal coliform bacteria was evaluated at 34 sites 

in the Cheney Reservoir watershed during low-flow conditions. With the exception of dissolved solids, which generally 

originated from natural sources, these constituents originated 

from nonpoint sources associated with agricultural activities 

(Christensen and Pope, 1997). Phosphorus was identified as 

a constituent of concern that could increase the growth of 

cyanobacteria, thereby increasing the occurrence of taste-andodor episodes (Pope and Christensen, 1997; Pope, 1998; and 

Pope and Milligan, 2000). Phosphorus control measures were 

suggested as a method to mitigate the taste-and-odor occurrences which were strongly linked to growth of cyanobacteria 

(Smith and others, 2001).

Sediment deposition, water-quality trends, and mass 

transport of phosphorus, nitrogen, selected trace elements, and 

selected pesticides within the Cheney Reservoir watershed 

were investigated using bathymetric survey data and reservoir 

bottom sediment cores collected during 1997 through 1999. 

Core analysis indicated total phosphorus concentrations in 

reservoir bottom sediment had increased with time, which was 

likely the result of nonpoint source activities in the watershed, 

such as increased fertilizer use and livestock production (Mau, 

2001). Sediment concentrations of arsenic, chromium, copper, 

and nickel at many sites exceeded levels at which adverse 

effects on aquatic organisms may occur, but these compounds 

likely were of natural origin in the watershed (Mau, 2001). 

Soil cores were examined from 43 nonagricultural sites in the 

Cheney Reservoir watershed. Historical mean total phosphorus concentrations in the bottom sediment of Cheney 

Reservoir were approximately 3 times larger than the natural 

concentrations found in the sample cores collected from nonagricultural watershed soils, indicating that agricultural activities within the watershed have increased total phosphorus 

concentrations in soil to about 3 times natural concentrations 

(Pope and others, 2002). Results also indicated that water from 

two of five streamflow sampling sites did not meet the Cheney 

Reservoir Task Force long-term total phosphorus water-quality 

goal of 0.10 mg/L.

Table 2. Total annual and annual mean precipitation during 1999 

through 2012 and annual mean precipitation during 1954 through 

2012 at the “Wichita Mid Continent Airport” (Global Historical 

Climatology Network–Daily:USW00003928) station.*

Year or time period Total precipitation, in inches

1999 45

2000 32

2001 24

2002 33

2003 33

2004 38

2005 37

2006 29

2007 38

2008 54

2009 38

2010 28

2011 26

2012 25

Average annual during 

1999 through 2012

34

Average annual during 

1954 through 2012

31

*

National Climatic Data Center data available at http://www.ncdc.noaa.

gov/oa/ncdc.html.
6 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

Regression models relating constituent concentrations 

from discretely collected samples to continuously measured 

physical properties at the North Fork Ninnescah River above 

Cheney Reservoir site (hereinafter called the inflow site) were 

developed using data collected during January 1997 through 

April 2003. These models were used to compute concentrations of sediment, nutrients, bacteria, and other water-quality 

constituents (Christensen and others, 2006). Regression-computed concentrations of total suspended solids from the inflow 

site during 2001 through 2003 were near the Cheney Reservoir 

Task Force base flow goal most of the time. The long-term 

goal was exceeded only during periods of runoff and the runoff goal was exceeded several times during 2001 through 2003 

(Christensen and others, 2006). The regression-computed total 

phosphorus concentration always exceeded the base flow goal 

during 2001 through 2003, and was close to the long-term goal 

during base flow conditions; the runoff goal was exceeded 

several times during 2001 and 2002 and during three high 

flow periods in 2003 (Christensen and others, 2006). Using the 

Christensen and others (2006) models [hereinafter referred to 

as original model(s)], Cheney Reservoir Task Force base flow 

goals for total suspended solids and total phosphorus goals 

were not met during 1997 through 2008 (Stone and others, 

2009).

Methods

Continuous and discrete water-quality data were collected 

at one site on the North Fork Ninnescah River (fig. 1; USGS 

stream-gaging station 07144780, North Fork Ninnescah River 

above Cheney Reservoir). The North Fork Ninnescah River 

is the largest contributing tributary to Cheney Reservoir, and 

thus one of the main contributors to reservoir water quality. 

Streamflow has been measured continuously at the inflow site 

since July 1965 and water quality has been measured continuously since October 1998. Discrete water-quality samples 

routinely have been collected since February 1996. Continuous and discrete water-quality data collected by the USGS at 

the inflow site from January 1999 through December 2009 

were used to develop updated and new site-specific regression 

models. Continuously measured water-quality data collected 

during January 1999 through December 2012 were used to 

compute concentrations, loads, and yields for water-quality 

constituents of interest, and evaluate water-quality conditions. 

Continuous Water-Quality Monitoring

Continuous water-quality data were collected from the 

inflow site and were recorded hourly. Streamflow was measured using standard USGS methods (Sauer and Turnipseed, 

2010; Turnipseed and Sauer, 2010). The inflow site was 

equipped with a YSI 6600 Extended Deployment System 

water-quality monitor that measured specific conductance, pH, 

water temperature, dissolved oxygen (YSI Clark cell or optical 

dissolved oxygen sensors), and turbidity (YSI model 6026 or 

6136 optical turbidity sensors). The YSI Clark cell dissolvedoxygen sensor was used from November 1998 through March 

2008 and was replaced by the YSI optical dissolved-oxygen 

sensor from March 2008 through 2012. The YSI model 6026 

turbidity sensor was used during December 1998 through May 

2011 and the YSI model 6136 turbidity sensor was used from 

October 2009 through 2012. The monitor was installed near 

the centroid of streamflow to best represent conditions across 

the width of the stream and was maintained in accordance with 

standard USGS procedures (Wilde and Radke, 1998; Wagner 

and others, 2006). Continuous streamflow and water-quality 

data were recorded hourly and are available on the USGS 

website at http://nrtwq.usgs.gov/ks.

The specific conductance, pH, water temperature, and 

dissolved oxygen sensors have wide ranges of operation (Wagner and others, 2006) that were not exceeded in this study. 

Individual turbidity sensors vary in maximum readings. The 

maximum reading recorded at this site during 1999 through 

2012 was 1,700 formazin nephelometric units (FNU) and 

the instrument maximum was not exceeded during the study 

period. Continuous data during the study period generally 

required corrections of less than 10 percent, which classifies 

the data quality as “good” according to established guidelines (Wagner and others, 2006). Time-series measurements 

occasionally were missing or deleted from the dataset because 

of low-flow conditions, equipment malfunction, or excessive 

fouling caused by environmental conditions. During 1999 

through 2012, less than 1 percent of the streamflow record, 

approximately 7 percent of the specific conductance record, 

5 percent of the pH record, 3 percent of the water temperature 

record, 8 percent of the dissolved oxygen record, and 7 percent of the turbidity record were missing or deleted (table 3), 

largely because of low-flow conditions causing sensors to be 

out of water and, in some cases, sensor fouling.

Discrete Water-Quality Samples

Discrete water-quality samples were collected over a 

range of streamflow conditions (appendix 1) during January 

1999 through September 2009 using depth- and width- integrating sample-collection techniques (Wilde and Radke, 1998; 

U.S. Geological Survey, 2006). Samples collected using this 

approach are representative of the average chemical composition of the stream cross-sectional area. All water samples 

were analyzed for dissolved solids and major ions, alkalinity, 

suspended solids and sediment, nutrients (nitrogen and phosphorus species), indicator bacteria, and organic carbon. Dissolved and suspended solids, major ions, alkalinity, nutrients 

(except for total Kjeldahl nitrogen), fecal coliform bacteria, 

and organic carbon were analyzed by the Wichita Municipal 

Water and Wastewater Laboratory in Wichita, Kansas according to standard methods (American Public Health Association 

and others, 1995). Selected replicate samples were sent to 

the USGS National Water Quality Laboratory in Lakewood, 
Methods 7

Table 3. Summary statistics for variables measured continuously at the North Fork Ninnescah River upstream from Cheney 

Reservoir (site 07144780), south-central Kansas, for the period of record (daily) and 1999 through 2012 (hourly).

[Continuous real-time water-quality data are available on the U.S. Geological Survey National Real-Time Water-Quality Web site (http://nrtwq.usgs.

gov/ks); n, number of measurements; ft3/s, cubic feet per second; μS/cm, microsiemens per centimeter at 25 degrees Celsius; °C, degrees Celsius; 

mg/L, milligrams per liter; FNU, formazin nephelometric units; <, less than]

Continuous variable n Minimum Maximum Mean Median

Percent 

missing 

data

Daily streamflow (ft3

/s), for period of record* 17,351 0 39,700 141 78.0 0

Hourly streamflow (ft3

/s)** 122,627 0 8,460 129 84 0.1

Hourly specific conductance (μS/cm) 113,955 103 1,760 1,144 1,170 7.2

Hourly pH 117,224 7.0 9.5 8.3 8.4 4.5

Hourly water temperature (°C) 118,673 -0.2 39.8 15.1 15.4 3.3

Hourly dissolved oxygen (mg/L) 112,851 2.1 18.4 10.2 10.0 8.1

Hourly turbidity (FNU) 114,091 <1.0 1,700 44 25 7.0

*

The period of record is July 1965 through December 2012.

**The period during 1999 through 2012.

Colorado and analyzed according to methods presented in 

Fishman and Friedman (1989). E. coli was analyzed at the 

USGS Wichita Field Office in Wichita, Kansas using methods 

described by Wilde and Radke (1998). Suspended sediment 

was analyzed at the USGS Iowa Sediment Laboratory in Iowa 

City, Iowa according to methods described in Guy (1969). 

Quality Assurance and Quality Control

Replicate, standard reference, and blank samples were 

collected over a range of streamflow conditions as part of 

quality assurance/quality control (QA/QC). About 8 percent 

of discrete water-quality samples were QA/QC samples. 

Approximately 180 sequential replicate constituent pairs were 

collected during 1999 through 2009 for the inflow site. Replicate samples were analyzed to identify variability in sampling 

and analysis methods (Wilde and Radke, 1998). Relative 

percentage difference (RPD) was used to evaluate differences 

in analyte concentrations detected in replicate water samples. 

The RPD was calculated using the following equation:

RPD A B A B = −  +









































 / 2 x100 (1)

where A and B are concentrations in each replicate pair. 

Replicate pairs with an RPD within 10 percent were considered acceptable for inorganic constituents (Ziegler and Combs, 

1997). Replicate pairs with an RPD within 20 percent were 

considered acceptable for organic constituents (including total 

phosphorus), and RPDs within 50 percent were considered 

acceptable for bacterial analysis. The median RPD between 

all constituent replicate pairs was less than their respective 

acceptability limits. All constituent replicate pairs had median 

RPDs that were less than 5 percent, except for total Kjeldahl 

nitrogen (12 percent), total phosphorus (15 percent), E. coli

(25 percent), and suspended sediment (6 percent). Larger 

RPDs generally occurred when the values were near the 

method reporting level.

Approximately 65 sequential constituent replicate pairs 

were analyzed by the Wichita Municipal Water and Wastewater Laboratory and the USGS National Water Quality Laboratory. The median RPD between laboratories for ions was 6 

percent. The median RPD between laboratories for nutrients 

was 12 percent. Larger nutrient RPDs generally occurred 

because of differences in laboratory method reporting levels 

and when the values were at or near the method or laboratory 

reporting level. 

Blank sample analysis included approximately 210 

constituent concentrations. All constituents were below the 

method reporting level with the exception of ammonia. One 

ammonia value was 0.01 mg/L above the method reporting 

level. Median blank bicarbonate concentration was 2.4 mg/L. 

Median blank alkalinity concentration was 2.0 mg/L.

Standard reference samples were analyzed by the Wichita 

Municipal Water and Wastewater Laboratory at least annually and submitted to the USGS Branch of Quality Systems 

for sample analysis and evaluation of laboratory performance. 

Median major ion constituent RPDs ranged from 1 to 6 percent and median nutrient constituent RPDs ranged from 3 to 

5 percent during this study. Results are available at http://bqs.

usgs.gov/srs/.

Cross-sectional measurements of water-quality physical 

properties measured with an independent field water-quality 

monitor were compared to concomitant continuous measurements to provide verification that minimum bias occurred as 

a result of water-quality monitor location within the stream 

cross-section. Cross-sectional water-quality physical properties were measured during discrete sampling and measurements across the stream channel at ten evenly spaced locations 
8 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

were recorded. The median RPD between cross-sectional and 

concomitant continuous monitor measurements was approximately 2 percent for all measurements. Larger differences 

(greater than 5 percent RPD) between cross-sectional and 

continuous monitor measurements occurred during stormwater 

runoff events when conditions were changing rapidly. 

Development of Regression Models to Compute 

Constituent Concentrations 

Models were developed using simple linear (ordinary 

least squares) regression analyses to relate discrete sample 

concentrations or densities of water-quality constituents to 

continuously measured water-quality physical properties 

(Helsel and Hirsch, 2002; Rasmussen and others, 2008). The 

methods used for the development of these models, quantifying uncertainty, and computation of loads and yields are 

described in detail in Rasmussen and others (2009). All data 

for this report were analyzed using TIBCO Spotfire S+® 8.1 

for Windows® statistical software (TIBCO Software, Inc., 

2008). Stone and others (2013) provide model documentation, 

including datasets and S+® statistical output.

Although Christensen and others (2006) included 

discrete data collected in 1997 and 1998 in their regression 

analyses, these data were not included in the current analysis. 

Christensen and others (2006) used cross-sectional means of 

continuously measured physical properties as explanatory 

variables, whereas this current analysis uses continuously 

measured water-quality data after the Rasmussen and others 

(2009) protocol. Christensen and others (2006) also included 

discrete data collected by autosamplers as response variables; 

this report did not use autosampled data because the autosamples represented a relatively small part of the dataset and may 

not be representative of the average chemical composition of 

the stream cross-sectional area (Christensen and others, 2006; 

Rasmussen and others, 2008). Original models had numbers of 

discrete samples ranging from 20 to 127, with a median of 27. 

The numbers of discrete samples for models in this report 

range from 22 to 61, with a median of 54.

All continuously measured variables and seasonal components (sine and cosine variables) were tested for significance 

for each response variable. Concomitant in-stream continuous 

measurements were used to correspond with discrete measurements as described in Rasmussen and others (2009). In-stream 

continuous data corresponding to each discrete sample were 

determined from time-series datasets by using time-weighted 

averages of continuous data values recorded immediately 

before, during, and after the discrete sample collection. 

Outliers were identified and removed as described in Rasmussen and others (2009). Outliers in discrete samples were 

removed when there was large heterogeneity in corresponding 

physical properties of cross-sectional data recorded during 

discrete sampling and when there were issues with laboratory analysis (such as an orthophosphate concentration being 

higher than the concomitant total phosphorus concentration). 

Overall, approximately 5 percent of the discrete-sample data 

were considered outliers and were removed from regression models. Three percent of the discrete-sample data was 

removed because of large heterogeneity in corresponding 

physical properties of cross-sectional data recorded during 

discrete sampling. One percent of the discrete-sample data 

was removed because of a large specific conductance value 

likely affected by road salt application. One percent of the 

discrete-sample data was removed because of laboratory 

analysis issues. Uncertainty in regression model predictions is 

unknown when the cross-sectional measurements vary greatly 

from the in situ measurements and when road salt is applied.

Regression models were evaluated based on diagnostic 

statistics [R2, coefficient of determination; Mallow’s Cp; root 

mean square error (RMSE); PRESS, prediction error sum of 

squares], patterns in residual plots, and the range and distribution of discrete and continuous data. The best model for each 

constituent was selected to maximize the amount of variance 

in the response variable that is explained by the model (multiple R2

 for models with one explanatory variable and adjusted 

R2 for models with more than one explanatory variable), that 

best fit the data (Mallow’s Cp), and that minimized heteroscedasticity (irregular scatter) in the residual plots and uncertainty 

associated with computed values (RMSE and PRESS). Model 

simplicity also was considered for model selection because, 

as more variables are included, the likelihood increases that 

the variability of the system is not described by the sampling 

dataset. 

Mean square error (MSE) and RMSE was calculated 

for each model to assess the variance between predicted and 

observed values (Helsel and Hirsch, 2002). The model standard percentage error (MSPE) was calculated as a percentage 

of the RMSE (Hardison, 1969). Because transformation of 

estimates back into original units results in a low biased estimate (Helsel and Hirsch, 2002), a bias correction factor (BCF) 

was calculated for models with logarithmically transformed 

response variables (Duan, 1983). 

To avoid false-positive quantification of a constituent, 

low concentrations are left-censored and reported as “less 

than” values by the laboratory (Childress and others, 1999). 

Two constituents had left-censored data: organic nitrogen 

(15 percent of samples) and orthophosphate (33 percent of 

samples). These data initially were analyzed using tobit regression (Judge and others, 1985). After the tobit regressions were 

completed, the left-censored data arbitrarily were assigned a 

value of one-half of the censoring level and were analyzed in 

the same manner as the constituents without left-censored data 

for comparison with the tobit regressions. 

Calculation of Annual Streamflow-Separation 

Points and Constituent Loads and Yields

Continuous hourly concentrations of select constituents 

were calculated using the newly developed regression models and continuous water-quality data (available online at 
Results of Continuously Monitored Variables 9

http://nrtwq.usgs.gov/ks/). Measured and computed continuous concentration data were evaluated from January 1, 1999, 

through December 31, 2012. Continuous data occasionally 

were missing during periods when extreme weather conditions occurred, water-quality monitors malfunctioned, or 

during routine maintenance visits. Two methods were used to 

compute constituent concentrations during periods of missing continuous data. Continuous hourly measurements were 

linearly interpolated when one or two values were missing 

using the least squares method (Sokal and Rohlf, 1995). 

When more than two values of hourly data were missing, 

a streamflow-based regression model was used to compute 

continuous concentrations because flow data were available for almost all (99.9 percent) of the period. Computed 

constituent concentration data varied because of differences 

in continuously monitored data-based and streamflow-based 

regression models. To “smooth” out steps in computed 

constituent concentration data from the different regression 

models, the streamflow-based constituent concentrations 

were shifted to the next available continuous datum based 

on methods described in Porterfield (1972). When no flow or 

other continuous data were available, concentrations, loads, 

and yields were not computed. Uncertainty associated with 

regression-computed constituent concentrations was quantified using 90-percent prediction intervals (Helsel and Hirsch, 

2002). 

Duration curves are cumulative distribution functions and were constructed using hourly values to evaluate 

frequency and magnitude characteristics (Rasmussen and 

Ziegler, 2003; Rasmussen and others, 2005). The curves indicate either the percentage of time that specified conditions 

were equaled or exceeded, or the frequency of exceedance 

(Maidment, 1993). The Weibull formula (Helsel and Hirsch, 

2002) was used for calculating plotting position. Streamflow 

and water-quality constituent duration curves with uncertainty, represented by 90-percent prediction intervals, for 

the inflow site are available for the period of record on the 

USGS website at http://nrtwq.usgs.gov/ks/. Water-quality 

criteria exceedances were determined using duration curves. 

Because of uncertainty associated with quantifying criteria 

exceedances on the basis of duration curves, the exceedances 

in this report should be considered as approximations. All 

duration curves for computed constituent concentrations in 

this report are plotted with 90-percent prediction intervals. 

Definition of streamflow conditions was required to 

compare water-quality conditions to Cheney Reservoir 

Task Force goals for total suspended solids, nitrate, and 

total phosphorus (table 1). The discharge duration curve 

calculated from hourly discharge data during January 1999 

through December 2012 was used to define base flow, runoff, 

and long-term streamflow conditions for the entire 14-year 

period. A 10 percent streamflow-separation point, determined 

by the discharge duration curve, was used to define base 

flow and runoff conditions following KDHE’s TMDL curve

methodology for characterizing flood conditions (Kansas 

Department of Health and Environment, [n.d.]).

Load and yield data were calculated from January 1, 

1999, through December 31, 2012. Hourly constituent loads 

were calculated by multiplying the calculated hourly concentrations (in milligrams per liter; mg/L) determined by regression models by hourly streamflow (in cubic feet per second; 

ft3/s) and a unit conversion factor (0.22427). This calculation 

assumes that hourly computed instantaneous load was constant 

during the preceding hour. Annual loads were calculated by 

summing the hourly loads. Annual yields (in pounds per acre) 

were calculated by dividing the annual loads by the contributing drainage at the inflow site (in square miles; mi2

).

Calculation of Conversion Factors for Turbidity 

Sensors

Turbidity sensors were updated from the YSI model 6026 

(YSI6026) to the YSI model 6136 (YSI6136) sensors in January 

2011. YSI6136 turbidity sensors were operated alongside the 

YSI6026 turbidity sensors during October 2009 through December 2010. Because of the change in turbidity sensor instrumentation, 1 year of concurrent YSI6026 and YSI6136 hourly turbidity 

measurements (October 2009 through October 2010) was used 

to develop a conversion factor. Ordinary least squares regression analyses were performed on the concurrent turbidity 

measurements to aid in conversion factor selection (Helsel and 

Hirsch, 2002). A median conversion factor was calculated as 

the ratio of the YSI6136 sensor value to the YSI6026 sensor value 

because the median was less likely to be affected by outliers 

(Rasmussen and others, 2009). The conversion factor was then 

applied to YSI6026-based models without additional modification so the models developed in this report could incorporate 

turbidity data collected by both instruments. 

Results of Continuously Monitored 

Variables

Streamflow is one of the key variables that shape the 

structure and function of stream ecosystems (Allan, 1995). 

Hourly streamflows ranged from 0 to 8,460 cubic feet per 

second (ft3/s) during 1999 through 2012; mean streamflow was 

129 ft3/s, which was about 12 ft3/s less than the mean streamflow for the period of record (July 1965–December 2012; 

table 3). The 10 percent streamflow-separation point used to 

define base flow and runoff conditions occurred at 208 ft3/s 

(fig. 3A).

Specific conductance, pH, water temperature, dissolved 

oxygen, and turbidity are described using the hourly continuous data collected at the inflow site during 1999 through 2012 

(table 3). The dataset for each constituent was 92 to 97 percent 

complete depending on the amount of missing hourly values. 

Specific conductance is an indirect measure of dissolved solids 
10 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

Frequency of exceedance, in percent

Turbidity, in formazin nephelometric units

0.01

0.1

1

10

100

1,000

10,000

Frequency of exceedance, in percent

Dissolved oxygen, in milligrams per liter (mg/L)

5

0

10

15

20

pH, in standard units

6.5

7.0

7.5

8.0

8.5

9.0

9.5

10.0

Streamflow, in cubic feet per second (ft3/s)

0.001

0.01

0.1

1

10

100

1,000

10,000

Streamflow-separation point: 208 ft3/s

Kansas Department of Health and Environment 

aquatic-life-support criterion: 6.5–8.5

E

Kansas Department of Health andEnvironment 

aquatic-life-support criterion: 5.0 mg/L

A

F

U.S. Environmental Protection Agency

level III ecoregion 27 guideline: 22.13 nephelometric

turbidity units

Specific conductance,

 in microsiemens per centimeter at 25 degrees Celsius

0

500

1,000

1,500

2,000

B

C

Water temperature, in degrees Celsius

-10

0

10

20

30

40

50

D

0 20 40 60 80 100 0 20 40 60 80 100

Figure 3. Duration curves for hourly measured A, streamflow; B, specific conductance; C, pH; D, water temperature; E, dissolved 

oxygen; and F, turbidity at the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 

during 1999 through 2012.
Results of Regression Analysis for Selected Constituents 11

in water (Hem, 1992). Specific conductance ranged from 103 

to 1,760 microsiemens per centimeter (μS/cm) at 25 degrees 

Celsius (°C), and had a mean value of 1,144 μS/cm during 

1999 through 2012 (table 3, fig. 3B). Large specific conductance values are likely the result of seepage of groundwater 

with relatively high dissolved solids concentrations affected 

by the Salt Plain Formation in the Ninnescah Shale (not 

shown) that underlies the south-central part of the study area 

(Gillespie and Hargadine, 1994).

pH is a measure of the effective hydrogen ion concentration and often is used to evaluate chemical and biological reactions in water; temperature affects the solubility of 

chemicals in water and biological activity (Hem, 1992). pH 

ranged from 7.0 to 9.5 and had a mean of 8.3 (table 3). Kansas aquatic-life-support criteria require that pH in streams 

not measure less than 6.5 or more than 8.5 standard units 

(Kansas Department of Health and Environment, 2008). 

Measured pH was never lower than 6.5, but exceeded 8.5 

approximately 19 percent of the time during 1999 through 

2012 (fig. 3C). Exceedances primarily occurred during base 

flow conditions during May through August and likely were 

caused by increased algal photosynthesis (Graham and others, 2010). Water temperature ranged from -0.2 to 39.8 °C 

and had a mean of 15.1 °C (table 3, fig. 3D). 

Dissolved oxygen is important for aquatic organisms 

and concentrations in surface water primarily are related 

to photosynthesis, respiration, atmospheric reaeration, and 

water temperature (Lewis, 2006). Dissolved oxygen concentrations ranged from 2.1 to 18.4 mg/L and had a mean of 

10.2 mg/L (table 3). A Kansas aquatic-life-support criterion 

requires that dissolved oxygen concentrations are not less 

than 5.0 mg/L (Kansas Department of Health and Environment, 2008). Dissolved oxygen concentrations were less 

than the minimum aquatic-life-support criterion less than 

1 percent of the time during 1999 through 2012 (fig. 3E). 

The lowest dissolved oxygen concentrations (less than 

5 mg/L) occurred in June, July, and August during periods 

of increased water temperatures (greater than 20 °C) and 

seasonal low flows. 

Turbidity is a measure of the optical properties of water 

that decrease the passage of light and is caused by suspended 

and dissolved matter such as clay, silt, finely divided organic 

material, plankton and other microscopic organisms, organic 

acids, and dyes (ASTM International, 2003; Anderson, 

2005). Turbidity ranged from less than 1.0 to 1,700 FNU and 

had a mean of 44 FNU (table 3). Kansas does not currently 

(2013) have water-quality criteria for turbidity. U.S. Environmental Protection Agency (USEPA) guidelines for turbidity 

(based on reference conditions) list 22.13 nephelometric 

turbidity units (NTU) for level III ecoregion 27 streams, 

which includes the North Fork Ninnescah River (U.S. 

Environmental Protection Agency, 2000). Guidelines are 

non-enforceable goals developed for the protection of water 

quality, aquatic life, and human health. Turbidity exceeded 

the USEPA criterion of 22.13 NTU approximately 55 percent 

of the time during 1999 through 2012 (fig 3F); these exceedances occurred across the range of streamflows. 

Results of Regression Analysis for 

Selected Constituents

Relations between in-stream continuous measurements 

and discrete constituent concentrations were developed and 

evaluated using ordinary least squares regression. Regression 

models for 15 constituents developed from data collected during 1997 through 2003 (Christensen and others, 2006) were 

updated and new models were developed for 5 additional constituents not described in Christensen and others (2006). The 

updated models were for dissolved solids, sodium, chloride, 

sulfate, calcium, magnesium, potassium, alkalinity, bicarbonate, total suspended solids, suspended-sediment, total Kjeldahl 

nitrogen, orthophosphate, total phosphorus, and fecal coliform 

bacteria. The newly developed models were for nutrients (total 

nitrogen, nitrate, and organic nitrogen), E. coli bacteria, and 

total organic carbon. Updated and newly developed models 

were developed from data collected during 1999 through 

2009. Models are shown in table 4 and appendix 2. Models for 

10 constituents of interest are presented in table 4 and models 

for 15 constituents are presented in appendix 2. Model datasets 

and additional statistical output are presented in Stone and 

others (2013). 

The tobit (appendix 3) and simple linear (appendix 2, 

table 4) regression model coefficients for organic nitrogen 

and orthophosphate were either identical or similar. The 

tobit regression model diagnostics were minimal and did not 

include information necessary for calculating and publishing constituent concentration information in real time on the 

USGS website (http://nrtwq.usgs.gov/ks). As such, the simple 

linear regression models for organic nitrogen and orthophosphate were selected for constituent concentration calculation.

Dissolved Solids, Chloride, and Other Major 

Ions

Dissolved solids in surface water primarily consist of the 

major cations calcium, magnesium, potassium, and sodium, 

and the anions bicarbonate, chloride, and sulfate. These ions 

come from decomposing rocks and soils. Concentrations of 

dissolved solids in stream water may increase because of 

atmospheric deposition, sewage inputs, industrial effluents, 

agricultural runoff, and urban runoff (Hem, 1992; Wetzel, 

2001). Dissolved solids in the Cheney Reservoir watershed 

occur naturally as the result of the dissolution of rocks and 

ancient marine sediments containing large salt deposits (Christensen and Pope, 1997). Dissolved solids often are used as a 

general indicator of salinity or water quality. Excessively large 

concentrations of dissolved solids are undesirable in drinking 

water because of possible physiological effects, strong mineral 
12 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas Table 4. Christensen and others (2006), updated, and new regression models and summary statistics for continuous concentration computations for the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 1999 through 2009.

[R2, coefficient of determination; MSE, mean square error; RMSE, root mean square error; MSPE, model standard percentage error; %, percent; ±, plus or minus; n, number of discrete samples; mg/L, milligrams per liter; log, log10; SC, specific conductance in microsiemens per centimeter at 25 degress Celsius; Q, streamflow in cubic feet per second; TBY6026, turbidity from YSI sensor 6026 in formazin nephelometric units; TKN, total Kjeldahl nitrogen; NO NO 3 2, nitrate plus nitrate in milligrams per liter; sin, sine; D, day of year; cos, cosine; <, less than; colonies/100 mL, colonies per 100 milliliters]

Regression model

Location of 

additional 

model 

information 

in Stone and 

others (2013)

Multiple 

R2

Adjusted 

R2

MSE RMSE MSPE (upper) MSPE (lower)

Bias 

correction 

factor 

(Duan, 1983)

90 % 

prediction 

interval, 

in ± %

Discrete data

n

Range of 

values in 

variable 

measurements

Mean Median Standard deviation

Dissolved solids (DS), mg/L

Christensen and others (2006)

log(DS) = 0.910log(SC) + 0.0101 0.87 0.87 0.0044 0.0663 17 14 1.01 40 127 DS: 140–707 461 472 168

SC: 198–1,300 821 837 303

Updated

log(DS) = 0.892log(SC) + 0.0810 figs. 2, 3; 

table 2

0.98 0.98 0.0006 0.0250 6 6 1.00 39 61 DS: 191–798 507 548 172

SC: 258–1,430 883 976 326

log(DS) = -0.225log(Q) + 3.19 figs. 4, 5; 

table 2

0.68 0.67 0.01 0.1036 27 21 1.03 40 61 DS: 191–798 507 548 172

Q: 9.4–3,725 564 223 873

Sodium (Na), dissolved, mg/L

Christensen and others (2006)

log(Na) = 1.17log(SC) - 1.41 0.89 0.89 0.0061 0.0784 20 17 1.02 40 127 Na: 19.5–180 104 101 46.5

SC: 198–1,300 821 837 303

Updated

log(Na) = 1.33log(SC) - 1.86 figs. 10, 11; 

table 2

0.99 0.98 0.0011 0.0330 8 7 1.00 40 61 Na: 22.8–185 117 130 53.4

SC: 258–1,430 883 976 326

log(Na) = -0.351log(Q) + 2.81 figs. 12, 13; 

table 2

0.74 0.74 0.0187 0.1367 37 27 1.05 41 61 Na: 22.8–185 117 130 53.4

Q: 9.4–3,725 564 223 873

Chloride (Cl), dissolved, mg/L

Christensen and others (2006)

log(Cl) = 1.37log(SC) - 1.82 0.97 0.97 0.0018 0.0420 10 9 1.00 41 27 Cl: 34.0–289 155 159 71.0

SC: 322–1,250 844 903 297

Updated

log(Cl) = 1.39log(SC) - 1.90 figs. 14, 15; 

table 3 

0.96 0.96 0.0035 0.0591 15 13 1.01 40 48 Cl: 30.8–289 147 139 82.7

SC: 258–1,430 822 837 339

log(Cl) = -0.401log(Q) + 3.06 figs. 16, 17; 

table 3

0.77 0.76 0.0212 0.1457 40 29 1.05 42 48 Cl: 30.8–289 147 139 82.7

Q: 15–3,725 697 321 942
Results of Regression Analysis for Selected Constituents 13

Table 4. Christensen and others (2006), updated, and new regression models and summary statistics for continuous concentration computations for the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 1999 through 2009.—Continued[R2, coefficient of determination; MSE, mean square error; RMSE, root mean square error; MSPE, model standard percentage error; %, percent; ±, plus or minus; n, number of discrete samples; mg/L, milligrams per liter; log, log10; SC, specific conductance in microsiemens per centimeter at 25 degress Celsius; Q, streamflow in cubic feet per second; TBY6026, turbidity from YSI sensor 6026 in formazin nephelometric units; TKN, total Kjeldahl nitrogen; NO NO 3 2, nitrate plus nitrate in milligrams per liter; sin, sine; D, day of year; cos, cosine; <, less than; colonies/100 mL, colonies per 100 milliliters]

Regression model

Location of 

additional 

model 

information 

in Stone and 

others (2013)

Multiple 

R2

Adjusted 

R2

MSE RMSE MSPE (upper) MSPE (lower)

Bias 

correction 

factor 

(Duan, 1983)

90 % 

prediction 

interval, 

in ± %

Discrete data

n

Range of 

values in 

variable 

measurements

Mean Median Standard deviation

Sulfate (SO4), dissolved, mg/L

Christensen and others (2006)

log(SO4) = 0.961log(SC) - 1.26 0.85 0.85 0.0059 0.0765 19 16 1.01 41 27 SO4: 11.0–61.0 35.8 37.9 13.7

SC: 322–1,250 844 903 297

Updated

SO4 = 0.0408(SC) - 0.002 figs. 20, 21; 

table 3

0.87 0.87 29.56 5.4369 16 -16 1.00 40 48 SO4: 8.5–61.0 33.6 29.0 18.9

SC: 258–1,430 822 837 339

SO4 = -20.1log(Q) + 82.6 figs. 22, 23; 

table 3

0.77 0.76 51.89 7.2035 21 -21 1.00 40 48 SO4: 8.5–61.0 33.6 29.0 18.9

Q: 15–3,725 697 321 942

Total suspended solids (TSS)

Christensen and others (2006)

log(TSS) = 0.893log(TBY6026) + 0.253 0.92 0.92 0.0233 0.1525 42 30 1.06 43 29 TSS: 8–696 156 55 186

TBY6026: 7.9–575 154 40 188

log(TSS) = 0.682log(Q) + 0.431 0.61 0.59 0.1190 0.3454 122 55 1.34 54 29 TSS: 8–696 156 55 186

Q: 9.3–3,460 406 106 775

Updated

log(TSS) = 0.903log(TBY6026) + 0.252 figs. 28, 29; 

table 5

0.87 0.87 0.0295 0.1718 49 33 1.08 42 57 TSS: 8–696 153 119 144

TBY6026: 13–600 136 110 138

 log(TSS) = 0.575log(Q) + 0.624 figs. 30, 31; 

table 5

0.64 0.63 0.0810 0.2846 93 48 1.25 49 57 TSS: 8–696 153 119 144

Q: 9.4–3,725 600 238 892

Suspended-sediment concentration (SSC), mg/L

Christensen and others (2006)

log(SSC) = 1.10log(TBY6026) +0.0037 0.85 0.85 0.0589 0.2426 75 43 1.18 48 22 SSC: 22–2,150 385 93 625

TBY6026: 15–575 170 60.8 194

log(SSC) = 0.934log(Q) +0.043 0.76 0.78 0.0959 0.3097 104 51 1.26 51 22 SSC: 22–2,150 385 93 625

Q: 20–3,460 482 120 870
14 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas Table 4. Christensen and others (2006), updated, and new regression models and summary statistics for continuous concentration computations for the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 1999 through 2009.—Continued

[R2, coefficient of determination; MSE, mean square error; RMSE, root mean square error; MSPE, model standard percentage error; %, percent; ±, plus or minus; n, number of discrete samples; mg/L, milligrams per liter; log, log10; SC, specific conductance in microsiemens per centimeter at 25 degress Celsius; Q, streamflow in cubic feet per second; TBY6026, turbidity from YSI sensor 6026 in formazin nephelometric units; TKN, total Kjeldahl nitrogen; NO NO 3 2, nitrate plus nitrate in milligrams per liter; sin, sine; D, day of year; cos, cosine; <, less than; colonies/100 mL, colonies per 100 milliliters]

Regression model

Location of 

additional 

model 

information 

in Stone and 

others (2013)

Multiple 

R2

Adjusted 

R2

MSE RMSE MSPE (upper) MSPE (lower)

Bias 

correction 

factor 

(Duan, 1983)

90 % 

prediction 

interval, 

in ± %

Discrete data

n

Range of 

values in 

variable 

measurements

Mean Median Standard deviation

Suspended-sediment concentration (SSC), mg/L—Continued

Updated

log(SSC) = 0.540log(Q) + 0.559log(TBY6026) - 0.110 figs. 32, 33; 

table 6

0.90 0.90 0.0347 0.1862 54 35 1.09 43 52 SSC: 19–2,690 439 208 596

Q: 15–3,725 645 263 919

TBY6026: 13–600 146 113 139

log(SSC) = 0.861log(Q) + 0.209 figs. 34, 35; 

table 6

0.82 0.81 0.0622 0.2494 78 44 1.18 47 53 SSC: 19–2,690 439 208 596

Q: 15–3,725 645 263 919

Nitrogen, total (TN), mg/L (TKN + NO NO 3 2

)

New

log(TN) = 0.0218sin(2πD/365) + 0.112cos(2πD/365) + 0.182log(TBY6026) - 0.0012 figs. 36, 37; 

table 7

0.63 0.60 0.0077 0.0876 22 18 1.02 40 54 TN: 0.99–4.43 2.18 2.02 0.72

TBY6026: 12–600 141 113 140

log(TN) = 0.0209sin(2πD/365) + 0.105cos(2πD/365) + 0.0822log(Q) + 0.150 figs. 38, 39; 

table 7

0.38 0.34 0.0127 0.1129 30 23 1.03 41 54 TN: 0.99-4.43 2.18 2.02 0.72

Q: 15–3,725 632 256 906

Nitrogen, ammonia plus organic (TKN), total, mg/L

Christensen and others (2006)

TKN = -0.0004(Q) + 0.0054(TBY6026) + 0.790 0.92 0.91 0.0881 0.2968 20 -20 1.00 41 20 TKN: 0.48–3.5 1.45 1.24 0.91

Q: 20–2,360 367 108 590

TBY6026: 15–532 151 41 177

Updated

log(TKN) = 0.426log(TBY6026) - 0.700 figs. 40, 41; 

table 8

0.83 0.83 0.0079 0.0888 23 18 1.02 40 50 TKN: 0.48–3.40 1.57 1.55 0.69

TBY6026: 13–600 155 121 141

Nitrate (NO3), mg/L

New

NO3 = 0.0519sin(2πD/365) + 0.619cos(2πD/365) - 0.389log(TBY6026) + 1.63 figs. 44, 45; 

table 10

0.63 0.61 0.0954 0.3088 45 -45 1.00 39 61 NO3: 0.03–2.38 0.69 0.52 0.49

TBY6026: 12–600 129 92 136

NO3 = 0.0903sin(2πD/365) + 0.652cos(2πD/365) - 0.278log(Q) + 1.55 figs. 46, 47; 

table 10

0.60 0.58 0.1028 0.3206 46 -46 1.00 39 61 NO3: 0.03–2.38 0.69 0.52 0.49

Q: 9.40–3,725 564 223 873
Results of Regression Analysis for Selected Constituents 15

Table 4. Christensen and others (2006), updated, and new regression models and summary statistics for continuous concentration computations for the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 1999 through 2009.—Continued[R2, coefficient of determination; MSE, mean square error; RMSE, root mean square error; MSPE, model standard percentage error; %, percent; ±, plus or minus; n, number of discrete samples; mg/L, milligrams per liter; log, log10; SC, specific conductance in microsiemens per centimeter at 25 degress Celsius; Q, streamflow in cubic feet per second; TBY6026, turbidity from YSI sensor 6026 in formazin nephelometric units; TKN, total Kjeldahl nitrogen; NO NO 3 2, nitrate plus nitrate in milligrams per liter; sin, sine; D, day of year; cos, cosine; <, less than; colonies/100 mL, colonies per 100 milliliters]

Regression model

Location of 

additional 

model 

information 

in Stone and 

others (2013)

Multiple 

R2

Adjusted 

R2

MSE RMSE MSPE (upper) MSPE (lower)

Bias 

correction 

factor 

(Duan, 1983)

90 % 

prediction 

interval, 

in ± %

Discrete data

n

Range of 

values in 

variable 

measurements

Mean Median Standard deviation

Phosphorus, total (TP), mg/L

Christensen and others (2006)

TP = 0.0001(Q) + 0.0008(TBY6026) + 0.0863 0.84 0.83 0.0661 0.0661 33 -33 1.00 40 26 TP: 0.03–0.58 0.20 0.13 0.16

Q: 9.3–2,360 293 103 533

TBY6026: 7.9–532 125 39.0 163

Updated

log(TP) = 0.611log(TBY6026) -1.829 figs. 48, 49; 

table 11

0.83 0.82 0.0189 0.1375 37 27 1.05 42 55 TP: 0.04–0.58 0.27 0.26 0.16

TBY6026: 13–600 137 110 139

TP = 0.191log(Q) - 0.174 figs. 50, 51; 

table 11

0.57 0.56 0.0115 0.1073 39 -39 1.00 40 55 TP: 0.04–0.58 0.27 0.26 0.16

Q: 9.4–3,725 596 238 904

Orthophosphate, filtered (OP), mg/L as phosphate

Christensen and others (2006)

OP = -0.0002(SC) + 0.237 0.84 0.83 0.0007 0.0263 66 -66 1.00 40 25 OP: <0.01–0.19 0.04 0.01 0.06

SC: 322–1,250 966 1,087 288

Updated

OP = -0.0002(SC) + 0.224 figs. 52, 53; 

table 12

0.74 0.73 0.0011 0.0339 56 -56 1.00 40 54 OP: 0.01–0.23 0.06 0.03 0.07

SC: 317–1,430 907 977 311

Escherichia coli bacteria (EC), colonies/100 mL

New

log(EC) = 0.0032(TBY6026) - 0.0016(SC) + 4.01 figs. 56, 57; 

table 14

0.87 0.85 0.0965 0.3106 104 51 1.20 49 22 EC: 17–30,000 5,086 1,400 8,319

TBY6026: 13–280 130 121 87.3

SC: 200–1,430 797 755 347

log(EC) = 0.977log(Q) + 0.650 figs. 58, 59; 

table 14

0.73 0.71 0.1902 0.4361 173 63 1.45 59 22 EC: 17–30,000 5,086 1,400 8,319

Q: 15–4,780 993 402 1,321
16 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

tastes, increased treatment costs, and corrosion in plumbing. 

Regression relations for dissolved solids, sodium, chloride, 

and sulfate are described in this section; regression relations 

for other ions that contribute to dissolved solids are shown in 

appendix 2.

 Dissolved solids at the inflow site were strongly positively correlated with specific conductance; the updated model 

reflects this with specific conductance as the only explanatory 

variable. The general form of the updated model is the same as 

the original model; however, the regression statistics, including the coefficients, are slightly different because the updated 

model encompasses a broader range of dissolved solids 

concentrations and specific conductance values. The updated 

model explained 11 percent more of the variance in dissolved 

solids concentrations (98 percent) compared to the original 

model (87 percent; table 4). The model based only on streamflow explained 30 percent less of the variance in dissolved solids concentrations (68 percent) than the specific conductance 

model. The strong relation between specific conductance and 

dissolved solids is expected because specific conductance is an 

indirect measure of the ionized substances in water. 

Sodium is present in igneous rocks and sediments and is 

the most abundant alkali-metal (Hem, 1992). Specific conductance explained the most variance for the old and new sodium 

models. The updated model form is similar to the original 

model (table 4). The updated model explained 99 percent of 

the variance in sodium concentrations versus 89 percent in the 

original model (table 4). The model based only on streamflow 

explained 25 percent less variance than the specific conductance-based model. 

Chloride occurs naturally in various rock types, generally in low concentrations and most often as an impurity 

(Hem, 1992). Potential anthropogenic sources of chloride in 

streamwater generally are agricultural and industrial runoff 

and wastewater treatment facility discharges. Certain forms of 

chloride also are major components of road deicers. Chloride 

is a charged ionic species and the model shows a positive relation between chloride and specific conductance. The updated 

model coefficients for chloride are similar to the original 

model and specific conductance is the only explanatory variable for both models (table 4). The updated and the original 

model explained about the same amount of chloride concentration variance (96 percent for the updated model and 97 percent 

for the original model). Streamflow explained 19 percent less 

variance than specific conductance (77 percent). 

Rock weathering, oxidation of sulfide minerals, and biological processes are natural sources of sulfate in surface water 

(Hem, 1992). Atmospheric deposition from the combustion 

of coal and petroleum products and irrigation return flows are 

the main anthropogenic sources of sulfate. Sulfate is a charged 

ionic species and it was positively correlated to specific 

conductance. Sulfate was correlated with specific conductance in the original and updated models; the updated model 

explained 87 percent of the variance in sulfate concentrations 

and the original model explained 85 percent (table 4). The 

streamflow-based model explained 10 percent less variance 

than the specific conductance-based model (77 percent).

Total Suspended Solids and Sediment 

Total suspended solids and suspended-sediment concentration are the two analytes typically used to describe concentrations of suspended solid-phase material in surface water. 

Although the terms often are used interchangeably, the laboratory analytical methods differ, and therefore the measured 

concentrations differ as well. Total suspended solids represent 

suspended solid material and may consist of organic or inorganic materials. They originate from sources such as algae, 

decaying vegetation, agricultural and urban runoff, municipal 

and industrial discharges, and physical degradation of geologic 

formations. The amount of total suspended solids in a medium 

is equal to the dry weight of organic and inorganic solids 

filtered from a subsample of the original sample. Suspended 

solids provide a medium for the accumulation and transport of 

other constituents of concern, such as phosphorus and bacteria. 

Suspended-sediment concentration is the measure of the dry 

weight of the organic and inorganic sediment in a full sample 

volume of a water-sediment mixture (Guy, 1969). Suspended 

sediment may consist of clay, silt, sand, or organic material. 

Sediment originates primarily from surface soils and 

geology, channel bank erosion, and streambed sediment that is 

resuspended during high-flow events. Suspended particulates 

provide attachment sites for nutrients, organic compounds, and 

other potential contaminants. Turbidity, caused by suspended 

and dissolved material, often is used as a surrogate for suspended solids and sediment. 

Turbidity is a physical property related to total suspended 

solids and is an indicator of sediment and other solid material 

transported in streams. Turbidity was related to total suspended solids in the original and updated models; the updated 

model explained about 5 percent less variance (87 percent) in 

total suspended solids concentration than the original model 

(92 percent; table 4). Streamflow also was related to total suspended solids but the streamflow model explained 23 percent 

less variance than the turbidity model (64 percent; table 4). 

Turbidity is a suitable surrogate for the estimation of 

continuous suspended-sediment concentration and was used 

by Christensen and others (2006); however, unlike the original 

model, the updated suspended-sediment concentration model 

also included streamflow as an explanatory variable (table 4). 

The updated model that included turbidity and streamflow 

explained 90 percent of the variance in suspended-sediment 

concentrations whereas the turbidity-based original model 

explained 85 percent of the variance. The updated suspendedsediment concentration model using only streamflow 

explained 8 percent less variance than the model that included 

turbidity and streamflow (table 4). 
Results of Regression Analysis for Selected Constituents 17

The newly developed nitrate model had turbidity and 

a seasonal component as explanatory variables (table 4). 

Sixty-one percent of the variance in nitrate concentration was 

explained by the turbidity-and-season-based model. A streamflow-and-season-based model explained about 3 percent less 

variance (58 percent) in nitrate concentration than the turbidityand-season-based model. Nitrate was negatively correlated 

with turbidity and streamflow. Streamflow-related runoff events 

increase turbidity and likely diluted the ambient nitrate.

Phosphorus is introduced into the environment by the 

breakdown of soil and rock minerals. Most phosphorus in 

surface water is bound organically, and much of the organic 

phosphorus fraction is in the particulate phase of living cells, 

primarily algae (Wetzel, 2001). Sources of phosphorus in the 

North Fork Ninnescah River watershed include inorganic 

phosphates from fertilizer, manure from animal production, and 

runoff. Turbidity was an explanatory variable in the original 

and updated total phosphorus models, likely because phosphorus adsorbs to suspended sediment and other particulate 

matter. The updated and original models explained 83 percent 

of the variance in total phosphorus concentrations (table 4). 

The newly developed model for total phosphorus based on 

streamflow alone explained about 26 percent less variance than 

the total phosphorus model based on turbidity (57 percent). 

Orthophosphate represented an average of about 27 percent 

of total phosphorus concentration in discrete samples. The 

original and updated models included specific conductance as 

the explanatory variable. The original model explained about 

10 percent more variance (84 percent) than the updated model 

(74 percent; table 4). 

Escherichia coli Bacteria

E. coli are a type of coliform bacteria that are specific to 

fecal material from humans and other homeothermic animals 

and are a common type of bacteria used as an indicator of 

pathogens in surface water. E. coli is carried into water from 

septic systems, sewer pipes, wastewater treatment plants, 

farms, yards, wildlife, pets, feedlots, and pastures. E. coli

bacteria indicate the potential for pathogens that can cause 

diarrhea, headaches, nausea, and abdominal cramping and may 

pose a more serious health risk for younger individuals and 

people with compromised immune systems [National Research 

Council (U.S.), 2004]. Suspended material in streams provide 

a medium for bacterial accumulation and transport. As such, 

turbidity can be an important surrogate for the estimation of 

E. coli densities. The newly developed E. coli model included 

turbidity and specific conductance as explanatory variables 

and explained 85 percent of the variance in E. coli densities. E. 

coli had a positive relation with turbidity and a negative relation with specific conductance because fecal coliform bacteria

sources are associated with runoff events, which generally 

increase turbidity and decrease specific conductivity in streamwater. A model based on streamflow alone explained 12 percent 

Nutrients

Streams receive nutrients from upstream sources, terrestrial runoff, groundwater, and the atmosphere. Nutrients, 

including species of nitrogen and phosphorus, are necessary 

for plant and animal growth but can lead to eutrophication, 

algal blooms, low dissolved oxygen, fish kills, and taste-andodor problems when present in excess amounts. Nutrients, 

particularly nitrogen and phosphorus, have been identified as 

a primary source of water-quality degradation in Kansas and 

the Nation (Kansas Department of Health and Environment, 

2004a; U.S. Environmental Protection Agency, 2000, 2006). 

Point sources of nutrients include municipal and industrial 

wastewater effluent and storm sewer discharge. The Cheney 

Reservoir watershed has very few point sources of pollution. 

Nonpoint sources of nutrients include livestock, crop fertilizers, 

and urban runoff. Nutrients in the Cheney Reservoir watershed generally originate from nonpoint sources and likely are 

related to agricultural activities (Christensen and Pope, 1997). 

Regression relations for total nitrogen, total Kjeldahl nitrogen, 

nitrate, total phosphorus, and orthophosphate are described in 

this section; regression relations for other nutrients are shown 

in appendix 2.

Nitrogen occurs as ammonia, nitrite, nitrate, and as part 

of organic compounds. Most algae utilize dissolved forms of 

inorganic nitrogen (Hem, 1992). Nitrate is the form of nitrogen 

most easily used by plants and algae and is the most common 

ion in many oxygen-rich waters because the nitrite ion is easily 

oxidized. The large increase in amounts of nitrogen fertilizers 

used on agricultural land in recent decades has prompted considerable concern about increases in nitrate concentrations in 

surface and groundwater (Hem, 1992). Excessive nitrate concentrations in drinking water can pose adverse health effects on 

humans, such as methemoglobinemia, a condition also known 

as blue baby syndrome. This condition restricts the oxygencarrying capacity of blood and may be fatal (Walton, 1951). 

The newly developed total nitrogen (total Kjeldahl nitrogen plus nitrate plus nitrite) model includes turbidity and a 

seasonal component (expressed as sine and cosine variables) as 

explanatory variables (table 4). Because of the predominately 

agricultural land use in the watershed, total nitrogen likely 

had a seasonal component because of the timing of fertilizer 

application. Sixty percent of the variance in total nitrogen 

concentration was explained by the turbidity-and-season-based 

model. A total nitrogen model based on streamflow and a 

seasonal component explained 26 percent less variance than the 

turbidity-based model (34 percent). 

Total Kjeldahl nitrogen (ammonia plus organic nitrogen) 

comprised an average of 68 percent (range: 17–99 percent) 

of the total nitrogen concentration in discrete samples. The 

original and updated total Kjeldahl nitrogen model had turbidity as an explanatory variable (table 4). The updated model 

explained about 8 percent less (83 percent) of the variance in 

total Kjeldahl nitrogen concentration than the original model 

(91 percent). 
18 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

less variance (73 percent; table 4) than the model based on 

turbidity and specific conductance. 

New Models and Changes in Updated Models

Total nitrogen, nitrate, organic nitrogen, E. coli bacteria, 

and total organic carbon (table 4; appendix 2) models were 

newly developed for this report. Additional data collection 

over a wider range of hydrological conditions facilitated the 

development of these models. The nitrate model is particularly 

important because it allows for comparison to Cheney Reservoir Task Force goals. 

In general, model forms and the amount of variance 

explained by the models was similar between the original 

(Christensen and others, 2006) and updated models. The 

model forms for most updated models remained unchanged. 

The two exceptions were suspended sediment concentration 

and total Kjeldahl nitrogen. The updated suspended-sediment 

concentration model includes streamflow as an additional 

explanatory variable and the updated total Kjeldahl model 

excludes streamflow as an additional explanatory variable 

(table 4). The amount of variance explained by the updated 

models decreased by 10 percent or less relative to the original 

models. Variance explained increased for the updated dissolved solids, sodium, sulfate, and suspended-sediment concentration models and decreased for the updated chloride, total 

suspended solids, total Kjeldahl nitrogen, total phosphorus, 

and orthophosphate models.

Turbidity, YSI Model 6026 and 6136 

Sensors

Regression models were developed in this report and by 

Christensen and others (2006) using YSI6026 turbidity sensor data to compute concentrations or densities of physical, 

chemical, and biological water properties, and associated loads 

and yields at the inflow site. Because of the change in turbidity 

instrumentation fromYSI6026 toYSI6136 sensorsin January 2011, 

the regression models that were developed using YSI6026 data 

require modification. The computation of a conversion factor 

allows the YSI6026 sensor regression models to accommodate 

turbidity measurements from the YSI6136 sensor. 

The ordinary least squares regression shows the relation 

between the YSI6026 and YSI6136 turbidity sensors and explains 

96 percent of the variance in turbidity readings (fig. 4, appendix 4). YSI6136 sensor measurements were on average 27 percent lower than YSI6026 measurements. The ratios of the YSI6136

sensor values to theYSI 6026 sensor values ranged from 0.19 to 

3.92 and had a median of 0.68 (appendix 4). To convert YSI6026

turbidity measurements to YSI6136 turbidity measurements at 

the inflow site, the YSI6026 turbidity measurement should be 

multiplied by the conversion factor of 0.68. The original and 

newly developed models from this report are shown in appendixes 5 and 6 in addition to converted models that should be 

used to calculate concentrations when turbidity is measured 

using the YSI6136 turbidity sensor at the inflow site.

Yellow Springs Instruments (YSI) model 6026 (YSI6026) turbidity sensor values, 

in formazin nephelometric units

0 300 600 900 1,200 1,500 1,800

Yellow Springs Instruments (YSI) model 6136 (YSI6136) turbidity 

sensor values, in formazin nephelometric units

0

300

600

900

1,200

1,500

1,800

YSI6136= 0.701(YSI6026)

Coefficient of determination (R 2

) = 0.96 

Number of observations (n) = 7,429 

1:1 line

Figure 4. Relation between Yellow 

Springs Instruments (YSI) model 6026 

(YSI6026) and YSI model 6136 (YSI6136) 

turbidity sensor values at the North Fork 

Ninnescah River upstream from Cheney 

Reservoir (site 07144780), south-central 

Kansas, October 2009 through October 

2010.
Computed Constituent Concentrations, Loads, and Yields 19

Computed Constituent Concentrations, 

Loads, and Yields

Hourly constituent concentrations were computed using 

continuous data from January 1999 through December 2012 

with the updated and newly developed models from table 4. 

Concentration data were useful for evaluating the waterquality conditions of the North Fork Ninnescah River as well 

as calculating constituent loads. Load is the mass quantity of 

a constituent transported by the river during a given period of 

time. 

Dissolved Solids, Chloride, and Other Major 

Ions

The models using specific conductance as explanatory 

variables (table 4) were used for ion concentration computations when specific conductance data were available. Ninetythree percent of the hourly specific conductance values were 

available during 1999 through 2012. When specific conductance data were not available the streamflow-based models 

(table 4) were used for constituent concentration computations. Comparisons of ambient water-quality constituents 

with drinking-water guidelines or advisories in this section of 

the report provide an indication of the water quality of water 

flowing into Cheney Reservoir.

The USEPA has established National Secondary Drinking Water Regulations that set nonmandatory water-quality 

standards. The USEPA does not enforce these secondary 

maximum contaminant levels (SMCLs); they were established as guidelines to assist public water-supply systems in 

managing their drinking water for aesthetic considerations 

such as taste, color, and odor (U.S. Environmental Protection Agency, 2005). The USEPA (2005) has established a 

SMCL for dissolved solids in drinking water of 500 mg/L. 

Computed dissolved solids ranged from 12.8 to 3,360 mg/L 

(mean: 652 mg/L; table 5). Based on the computed hourly 

dissolved solids concentrations, the USEPA SMCL of 500 

mg/L was exceeded about 93 percent of the time during 1999 

through 2012 (fig. 5A).

The USEPA (1995) has established a Drinking Water 

Advisory (DWA) for sodium of 20 mg/L for individuals on a 

50 milligrams per day (mg/d) restricted sodium diet. Regression-computed sodium concentrations ranged from 6.54 to 

2,172 mg/L, with a mean of 168 mg/L (table 5). Based on the 

computed hourly sodium concentrations, the USEPA DWA of 

20 mg/L was exceeded nearly 100 percent of the time during 

1999 through 2012 (fig. 5B). The mean sodium concentration of 168 mg/L was approximately 19 times higher than the 

North American average for river water, which is approximately 9 mg/L (Wetzel, 2001). High sodium concentrations 

likely are the result of seepage of groundwater affected by the 

Salt Plain Formation in the Ninnescah Shale (not shown) that 

underlies the south-central part of the study area (Gillespie 

and Hargadine, 1994). The groundwater with naturally 

elevated sodium concentrations also caused the relatively high 

dissolved solids concentrations in the North Fork Ninnescah 

River.

Chloride is an ion of interest because of the aquatic-life 

criteria established by KDHE and USEPA. The USEPA has 

an SMCL for chloride in drinking water of 250 mg/L (U.S. 

Environmental Protection Agency, 2005) and KDHE has 

established an aquatic-life-support criterion for chloride of 

860 mg/L (Kansas Department of Health and Environment, 

2004b). The mean computed hourly chloride concentration 

was 234 mg/L and ranged from 7.88 to 4,482 mg/L (table 5). 

Based on the computed hourly chloride concentrations, the 

USEPA SMCL for chloride (250 mg/L) was exceeded about 

26 percent of the time during 1999 through 2012 (fig. 5C), 

generally during winter and lower flows likely because of road 

salt application and contribution of chloride by groundwater. 

The KDHE aquatic-life-support criterion for chloride (860 

mg/L) was exceeded less than 1 percent of the time during 

extremely low flows in July and August 2012.

The USEPA has an SMCL for sulfate in drinking water 

of 250 mg/L (U.S. Environmental Protection Agency, 2005). 

The mean computed sulfate concentration was 46.9 mg/L and 

ranged from 4.20 to 90.7 mg/L (table 5). Based on the computed hourly sulfate concentrations, the USEPA SMCL for 

sulfate (250 mg/L) was never exceeded during 1999 through 

2012 (fig. 5D). 

Total Suspended Solids and Sediment

The model using turbidity as the explanatory variable 

(table 4) was used for suspended solids concentration computations when turbidity data were available. Ninety-three 

percent of the hourly turbidity values were available during 

1999 through 2012. When turbidity data were not available 

the streamflow-based total suspended solids model (table 4) 

was used for concentration computations. 

Based on computed hourly concentrations, total suspended solids ranged from less than 1 to 1,595 mg/L (mean: 

54 mg/L) during 1999 through 2012 (table 5). Annual mean 

total suspended solids concentrations were largest in 2002 

(86 mg/L) and smallest in 2012 (23 mg/L), corresponding 

with the largest (80 FNU in 2002) and smallest (18 FNU in 

2012) annual mean turbidities (table 6). The smallest annual 

mean total suspended solids concentration (23 mg/L) also 

corresponds to the smallest annual mean streamflow (45 ft3/s).

The total suspended solids load for 1999 through 2012 

was 174,031 tons (table 7). The smallest annual total suspended solids load was 1,457 tons in 2011, corresponding to 

the second-smallest annual mean streamflow and streamflow 

load (57 ft3/s and 41,114 acre feet, respectively). The largest 

annual total suspended solids load was 23,620 tons in 2010, 

corresponding to the largest annual mean streamflow and 

streamflow load (215 ft3/s and 155,856 acre feet, respectively; 

tables 6, 7; figs. 6A,B).
20 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

Table 5. Summary of hourly statistics for selected water-quality constituents computed with updated regression models and 

continuously measured variables at the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), southcentral Kansas, 1999 through 2012.

[Continuous real-time water quality data are available on the U.S. Geological Survey National Real-Time Water-Quality Web site (http://nrtwq.usgs.

gov/ks); n, number of measurements; mg/L, milligrams per liter; <, less than; col/100 mL, colonies per 100 milliliters]

Continuous variable n Minimum Maximum Mean Median

Dissolved solids (mg/L) 112,692 12.8 3,360 652 657

Sodium (mg/L) 122,736 6.54 2,172 168 166

Chloride (mg/L) 122,736 7.88 4,482 234 230

Sulfate (mg/L) 122,736 4.20 90.7 46.9 47.7

Total suspended solids (mg/L) 122,696 <1 1,595 54 34

Suspended sediment (mg/L) 122,627 <1 3,737 88 54

Total nitrogen (mg/L) 122,696 0.75 4.29 1.87 1.84

Nitrate (mg/L) 122,501 <0.01 2.27 1.08 1.10

Total phosphorus (mg/L) 121,856 <0.01 1.46 0.14 0.11

Escherichia coli (col/100 mL) 122,696 <1 1,900,000,000 290,000 190

The model using turbidity and streamflow as explanatory variables (table 4) was used for suspended-sediment 

concentration computations when turbidity values were 

available. Ninety-three percent of the hourly turbidity and 

discharge values were available during 1999 through 2012 

(table 3). When turbidity values were not available, the 

streamflow-based suspended-sediment concentration model 

(table 4) was used. The duration curve for suspended-sediment 

concentrations is shown in figure 5F. Suspended-sediment 

concentrations for 1999 through 2012 ranged from less than 1 

mg/L to 3,737 mg/L (mean: 88 mg/L; table 5). Annual mean 

suspended-sediment concentrations ranged from 30 mg/L in 

2012 to 123 mg/L in 2009, corresponding to the smallest (45 

ft3/s) and second-largest (204 ft3/s) annual mean streamflows 

(table 6). Suspended-sediment load for 1999 through 2012 was 

518,321 tons (table 7). Suspended-sediment load ranged from 

2,455 tons in 2011 to 114,959 tons in 2010, corresponding to 

the second-smallest (57 ft3

/s) and largest (215 ft3/s) annual 

mean streamflows, respectively (table 7; fig. 6C). 

Nutrients

The model using turbidity as a surrogate (table 4) was 

used for total nitrogen concentration computations when 

turbidity values were available. Ninety-three percent of the 

hourly turbidity values during 1999 through 2012 were available (table 3). The streamflow-based total nitrogen model 

(table 4) was used when turbidity values were not available. 

Based on hourly concentrations, mean total nitrogen during 1999 through 2012 was 1.87 mg/L (range: 0.75 mg/L to 

4.29 mg/L; table 5). The USEPA total nitrogen guideline for 

level III ecoregion 27 streams is 0.84 mg/L (U.S. Environmental Protection Agency, 2002). The USEPA recommended 

total nitrogen guideline of 0.84 mg/L was exceeded nearly 

100 percent of the time from January 1999 through December 

2012 (fig. 7A).

Annual mean total nitrogen concentration ranged from 

1.79 mg/L in 2006 to 2.04 mg/L in 2001 and did not vary 

substantially among years (table 6). The total nitrogen load 

for 1999 through 2012 was 3,098 tons (table 7). Annual 

total nitrogen loads ranged from 88 tons in 2011 and 2012 to 

347 tons in 2010, corresponding to the smallest and largest 

annual mean streamflows (tables 6, 7; fig. 6D). 

The model using turbidity as a surrogate (table 4) was 

used for nitrate concentration computations when turbidity 

values were available. Ninety-three percent of hourly turbidity 

values were available during 1999 through 2012 (table 3). The 

discharge-based nitrate model was used (table 4) to compute 

nitrate concentrations when turbidity values were not available. The Federal maximum contaminant level (MCL) for 

nitrate in drinking water is 10 mg/L as nitrogen (U.S. Environmental Protection Agency, 2009). An MCL is the highest 

permissible level (on an annual basis) of a contaminant in 

water that is delivered to any user of a public water system. 

The 10 mg/L nitrate MCL was never exceeded during 1999 

through 2012 (table 5, fig. 7B).

Based on computed hourly nitrate concentrations, mean 

nitrate was 1.08 mg/L for all flow conditions and ranged from 

less than 0.01 mg/L to 2.27 mg/L during 1999 through 2012 

(table 5). Annual mean nitrate concentrations ranged from 

1.00 mg/L in 2001 to 1.25 mg/L in 2012 (table 6). The nitrate 

load for 1999 through 2012 was 1,361 tons and ranged from 

56 tons in 2006 to 145 tons in 2009, which corresponded to 

the third-lowest and second-highest annual mean streamflows 

and annual streamflow volumes (tables 6, 7; figs. 6A,E). 

The model using turbidity as a surrogate (table 4) was 

used for total phosphorus concentration computations when 

turbidity values were available. Ninety-three percent of 

the hourly turbidity values during 1999 through 2012 were 
Computed Constituent Concentrations, Loads, and Yields 21 Sulfate, in milligrams per liter

0

20

40

60

80

100

Chloride, in milligrams per liter (mg/L)

0

250

500

750

1,000

Frequency of exceedance, in percent

Suspended sediment, in milligrams per liter

0.1

1

10

100

1,000

10,000

Total suspended solids, in milligrams per liter (mg/L)

0

10

100

1,000

10,000

C D Sodium, in milligrams per liter (mg/L)

0

100

200

300

400

500

Dissolved solids, in milligrams per liter (mg/L)

0

500

1,000

1,500

2,000

Frequency of exceedance, in percent

A B

E F

U.S. Environmental Protection Agency

secondary maximum contaminant level: 500 mg/L 

U.S. Environmental Protection Agency

secondary maximum contaminant level: 250 mg/L 

U.S. Environmental Protection Agency

drinking-water advisory: 20 mg/L

Cheney Reservoir Task Force

long-term water-quality goal: 100 mg/L

Duration curve

90-percent prediction interval

0 20 40 60 80 100 0 20 40 60 80 100

EXPLANATION

Figure 5. Duration curves for hourly computed A, dissolved solids; B, sodium; C, chloride; D, sulfate; E, total suspended solids; and 

F, suspended sediment at the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 

during 1999 through 2012.
22 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

Table 6. Annual means for continuously measured and computed constituents at the North Fork Ninnescah River upstream from 

Cheney Reservoir (site 07144780), south-central Kansas, during 1999 through 2012.

[Continuous real-time water quality data are available on the U.S. Geological Survey National Real-Time Water-Quality Web site (http://nrtwq.usgs.gov/ks); 

ft3/s, cubic feet per second; μS/cm, microsiemens per centimeter at 25 degrees Celsius; °C, degrees Celsius; mg/L, milligrams per liter; FNU, formazin nephelometric units] 

Constituent

Year

1999 2000 2001 2002 2003 2004 2005

Streamflow (ft3

/s) 125 136 138 84 111 134 162

Specific conductance (μS/cm) 1,101 1,140 1,116 1,152 1,176 1,177 1,127

pH 8.3 8.3 8.4 8.4 8.2 8.3 8.2

Temperature (°C) 15.5 15.2 15.5 15.4 13.9 15.0 15.5

Dissolved oxygen (mg/L) 10.4 10.3 10.1 10.1 11.1 10.4 10.6

Turbidity (FNU) 50 53 68 80 44 43 40

Total suspended solids (mg/L) 63 63 81 86 54 52 51

Suspended sediment (mg/L) 97 99 116 89 87 94 98

Total nitrogen (mg/L) 1.96 1.91 2.04 1.96 1.89 1.88 1.88

Nitrate (mg/L) 1.04 1.07 1.00 1.05 1.08 1.08 1.08

Total phosphorus (mg/L) 0.15 0.15 0.18 0.17 0.13 0.13 0.13

Constituent

Year

2006 2007 2008 2009 2010 2011 2012

Streamflow (ft3

/s) 58 172 166 204 215 57 45

Specific conductance (μS/cm) 1,205 1,149 1,116 1,077 1,091 1,183 1,218

pH 8.1 8.4 8.4 8.4 8.4 8.5 8.4

Temperature (°C) 15.6 15.4 14.6 14.6 15.3 14.9 15.5

Dissolved oxygen (mg/L) 10.3 10.3 9.9 9.8 10.0 10.1 9.9

Turbidity (FNU) 27 41 41 49 43 19 18

Total suspended solids (mg/L) 38 54 52 63 55 27 23

Suspended sediment (mg/L) 45 101 100 123 114 35 30

Total nitrogen (mg/L) 1.79 1.92 1.87 1.95 1.90 1.69 1.61

Nitrate (mg/L) 1.12 1.05 1.07 1.03 1.06 1.18 1.25

Total phosphorus (mg/L) 0.11 0.14 0.13 0.15 0.14 0.09 0.08

available (table 3). When turbidity values were not available, the streamflow-based total phosphorus model (table 4) 

was used to compute hourly total phosphorus concentrations. 

The USEPA total phosphorus guideline for level III ecoregion 27 streams is 0.09 mg/L (U.S. Environmental Protection 

Agency, 2002). Based on hourly concentrations, mean total 

phosphorus concentration during 1999 through 2012 was 0.14 

mg/L (range: less than 0.01 mg/L to 1.46 mg/L; table 5). The 

USEPA level III ecoregion 27 total phosphorus guideline of 

0.09 mg/L was exceeded approximately 67 percent of the time 

from 1999 through 2012 (fig. 7C). Annual mean total phosphorus concentrations ranged from 0.08 mg/L in 2012 to 0.18 

mg/L in 2001 (table 6). The total phosphorus load for 1999 

through 2012 was 328 tons (table 7). The total phosphorus 

load ranged from 5 tons in 2011 and 2012 to 43 tons in 2010. 

These minimum and maximum annual loads correspond to the 

smallest and largest yearly streamflow volumes, respectively 

(table 7; figs. 6A,F). 

Escherichia coli Bacteria

The models using turbidity and specific conductance as 

explanatory variables (table 4) were used for E. coli concentration computations when these data were available. Ninetythree percent of the hourly turbidity and specific conductance 

values were available during 1999 through 2012 (table 3). 

When turbidity and specific conductance data were not available the streamflow-based models (table 4) were used to 

compute E. coli densities. 

The State of Kansas established surface-water recreational-use E. coli criteria in 2004 for streams with flows of at 

least 1 ft3

/s. The primary contact criterion for these publicly 

accessible Kansas streams is that the geometric mean of at 

least five samples, collected during separate 24-hour periods 

within a 30-day period, should not exceed 262 colony forming 

units per 100 milliliters (mL) during April 1 through October 

31 of each year, and 2,358 colony forming units per 100 mL 
Computed Constituent Concentrations, Loads, and Yields 23

Table 7. Computed annual loads and yields for selected constituents at the North Fork Ninnescah River upstream from Cheney 

Reservoir (site 07144780), south-central Kansas, during 1999 through 2012.

[All loads and yields are estimated. With the exception of streamflow, loads are expressed in tons and yields are expressed in pounds per square mile. Streamflow is expressed in acre feet and acre feet per acre for loads and yields, respectively.]

Constituent

Year

1999 2000 2001

Load Yield Load Yield Load Yield

Streamflow 90,624 0.19 98,581 0.21 99,616 0.21

Total suspended solids 11,534 31,006 17,637 47,410 17,771 47,771

Suspended sediment 25,997 69,886 53,775 144,558 38,600 103,763

Total nitrogen 217 584 263 708 257 691

Nitrate 96 258 120 322 102 273

Total phosphorus 22 60 30 81 31 82

Constituent

Year

2002 2003 2004

Load Yield Load Yield Load Yield

Streamflow 60,879 0.13 80,557 0.17 97,047 0.20

Total suspended solids 11,680 31,399 14,447 38,835 13,350 35,886

Suspended sediment 16,474 44,284 37,581 101,024 33,424 89,850

Total nitrogen 148 398 209 563 224 603

Nitrate 66 177 86 230 94 253

Total phosphorus 18 49 25 66 25 66

Constituent

Year

2005 2006 2007

Load Yield Load Yield Load Yield

Streamflow 117,044 0.25 42,204 0.09 123,240 0.26

Total suspended solids 13,602 36,563 2,205 5,927 14,526 39,049

Suspended sediment 41,199 110,749 3,244 8,720 57,760 155,269

Total nitrogen 264 708 92 247 287 772

Nitrate 116 312 56 150 108 290

Total phosphorus 27 73 6 16 30 82

Constituent

Year

2008 2009 2010

Load Yield Load Yield Load Yield

Streamflow 119,920 0.25 147,951 0.31 155,856 0.33

Total suspended solids 12,598 33,864 17,704 47,590 23,620 63,495

Suspended sediment 34,299 92,202 55,291 148,631 114,959 309,030

Total nitrogen 269 724 344 925 347 933

Nitrate 129 347 145 389 124 335

Total phosphorus 26 70 36 96 43 116

Constituent

Year

2011 2012 1999–2012

Load Yield Load Yield Load Yield

Streamflow 41,114 0.09 32,377 0.07 1,307,009 2.74

Total suspended solids 1,457 3,916 1,903 5,115 174,031 467,826

Suspended sediment 2,455 6,598 3,263 8,772 518,321 1,393,335

Total nitrogen 88 237 88 237 3,098 8,329

Nitrate 62 167 59 158 1,361 3,660

Total phosphorus 5 12 5 14 328 883
24 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas Streamflow load, in acre feet

0

40,000

80,000

120,000

160,000

200,000

A

Total suspended solids load, in tons

0

5,000

10,000

15,000

20,000

25,000

B

19992000200120022003200420052006200720082009201020112012

Nitrate load, in tons

0

30

60

90

120

150

180

E

19992000200120022003200420052006200720082009201020112012

Total phosphorus load, in tons

0

10

20

30

40

50

F

Suspended-sediment load, in tons

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

C

Total nitrogen load, in tons

0

100

200

300

400

D

Figure 6. Computed annual A, streamflow; B, total suspended solids; C, suspended-sediment; D, total nitrogen; E, nitrate; and F, 

total phosphorus loads at the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 

during 1999 through 2012.
Computed Constituent Concentrations, Loads, and Yields 25

Cheney Reservoir Task Force

long-term water-quality goal: 0.10 mg/L

Total nitrogen, in milligrams per liter (mg/L)

0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

Total phosphorus, in milligrams per liter (mg/L)

0.001

0.01

0.1

1

10

C

Escherichia coli bacteria, in colonies

per 100 milliliters (col/100 mL)

1

10

100

1,000

10,000

100,000

1,000,000

10,000,000

Kansas Department of Health and Environment

primary contact guideline for April through October: 262 col/100 mL

Kansas Department of Health and Environment

primary contact guideline for November through March

and secondary contact guideline: 2,358 col/100 mL

D

A

Nitrate, in milligrams per liter (mg/L)

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

B

U.S. Environmental Protection Agency

level III ecoregion 27 guideline: 0.84 mg/L

U.S. Environmental Protection Agency

level III ecoregion 27 guideline: 0.09 mg/L

Frequency of exceedance, in percent

0 20 40 60 80 100

Frequency of exceedance, in percent

0 20 40 60 80 100

Duration curve

90-percent prediction interval

EXPLANATION

Cheney Reservoir Task Force

long-term water-quality goal: 1.20 mg/L

Figure 7. Duration curves for hourly computed A, total nitrogen; B, nitrate; C, total phosphorus; and D, Escherichia coli

bacteria at the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, during 1999 

through 2012.

for primary contact during the rest of the year. The secondary contact criterion for publicly accessible Kansas streams 

requires that the geometric mean does not exceed 2,358 colony 

forming units per 100 mL at any time of the year (Kansas 

Department of Health and Environment, 2004b). Colony 

forming units per 100 mL is equivalent to colonies per 100 mL 

(col/100 mL) for this report. 

Mean computed E. coli bacteria density, during 1999 

through 2012, was 290,000 col/100 mL (range: less than 

1 col/100 mL to 1,900,000,000 col/100 mL; table 5). The 

KDHE primary contact guideline for April to October 

(262 col/100 mL) was exceeded about 30 percent of the time 

and the KDHE primary contact guideline for the months 

between November and March and secondary contact guideline (2,358 col/100 mL) was exceeded about 4 percent of the 

time (fig. 7D). Year-round data were used to quantify exceedances and geometric means were not calculated; therefore, 

exceedances of specified values do not indicate non-compliance with these water-quality standards, but do provide an 

indication of general conditions relative to the criteria. 

Comparison of Total Suspended Solids, Nitrate, 

and Total Phosphorus with Cheney Reservoir 

Task Force Goals

Streamflow, total suspended solids, nitrate, and total 

phosphorus data were separated into three flow class conditions: long term, which includes all streamflow conditions; 

base flow; and runoff for comparison with Cheney Reservoir 
26 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

Task Force goals (table 1). Although the USEPA does not have 

an established water-quality criterion for total suspended solids, the Cheney Reservoir Task Force developed a long-term 

mean water-quality goal of 100 mg/L for the North Fork Ninnescah River (table 1; Cheney Reservoir Task Force, 1994). 

Additionally, the Cheney Reservoir Task Force developed a 

total suspended solids goal of 20 mg/L for base flow conditions and 550 mg/L for runoff conditions (table 1; Cheney 

Reservoir Task Force, 1994). Total suspended solids concentrations ranged from less than 1 mg/L to 1,595 mg/L during 

1999 through 2012 (table 5). The Cheney Reservoir Task 

Force long-term water-quality goal for total suspended solids 

(100 mg/L) was exceeded approximately 10 percent of the 

time during 1999 through 2012 (fig. 5E, table 8). Mean total 

suspended solids concentration during base flow conditions 

was 45 mg/L and ranged from less than 1 mg/L to 1,595 mg/L 

during 1999 through 2012; the base flow goal for total suspended solids (20 mg/L) was exceeded about 79 percent of the 

time (table 8). Mean total suspended solids concentration during runoff conditions was 148 mg/L and ranged from 6 mg/L 

to 1,591 mg/L during 1999 through 2012; the runoff goal for 

total suspended solids (550 mg/L) was exceeded about 3 percent of the time (table 8). When annual mean total suspended 

solids concentrations were calculated for base flow, runoff, 

and long-term conditions, the Cheney Reservoir Task Force 

runoff and long-term goals were never exceeded and the base 

flow goal of 20 mg/L was exceeded by 1–4 fold every year 

during 1999 through 2012 (fig. 8B). 

The Cheney Reservoir Task Force set three goals for 

nitrate concentrations in Cheney Reservoir watershed streams 

based on streamflow conditions: 0.25 mg/L for base flow 

conditions, 6.60 mg/L for runoff conditions, and 1.20 mg/L 

for long-term conditions (Cheney Reservoir Task Force, 

1994; table 1). Nitrate concentrations ranged from less than 

0.01 mg/L to 2.27 mg/L during 1999 through 2012 (table 5). 

The Cheney Reservoir Task Force long-term water-quality 

goal for nitrate (1.20 mg/L) was exceeded approximately 

45 percent of the time (fig. 7B, table 8) during 1999 through 

2012. Mean nitrate concentration during base flow conditions was 1.11 mg/L and ranged from less than 0.01 mg/L to 

2.27 mg/L during 1999 through 2012; the base flow goal for 

nitrate (0.25 mg/L) was exceeded about 99 percent of the time 

(table 8). Mean nitrate concentration during runoff conditions was 0.85 mg/L and ranged from less than 0.01 mg/L 

to 2.02 mg/L during 1999 through 2012; the runoff goal for 

nitrate (6.60 mg/L) was never exceeded (table 8). When 

annual mean nitrate concentrations were calculated for base 

flow, runoff, and long-term conditions, the Cheney Reservoir Task Force runoff goal was never exceeded, the longterm goal was exceeded in 2012, and the base flow goal was 

exceeded by 4–5 fold every year during 1999 through 2012 

(fig. 8C). With the exception of the years 2000, 2011, and 

2012, annual mean nitrate concentrations were larger during 

base flow conditions than during runoff conditions (fig. 8C). 

Higher mean nitrate concentrations during base flow conditions, rather than runoff conditions, indicate that groundwater 

Table 8. Summary statistics for selected water-quality constituents computed with updated regression models and continuously 

measured physical properties at the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 

1999 through 2012.

[Continuous real-time water quality data are available on the U.S. Geological Survey National Real-Time Water-Quality Web site (http://nrtwq.usgs.gov/ks); n, 

number of measurements; mg/L, milligrams per liter; <, less than]

Water-quality constituent

Flow Condition

n Range Mean Median

Frequency of exceedance of 

Cheney Reservoir Task Force goal,*

in percent

Long-term

Total suspended solids (mg/L) 122,696 <1–1,595 54 34 10

Nitrate (mg/L) 122,501 <0.01–2.27 1.08 1.10 45

Total phosphorus (mg/L) 121,856 <0.01–1.46 0.14 0.11 57

Base flow

Total suspended solids (mg/L) 111,077 <1–1,595 45 33 79

Nitrate (mg/L) 110,980 <0.01–2.27 1.11 1.14 99

Total phosphorus (mg/L) 110,237 <0.01–1.46 0.12 0.11 95

Runoff

Total suspended solids (mg/L) 11,550 6–1,591 148 105 3

Nitrate (mg/L) 11,452 <0.01–2.02 0.85 0.74 0

Total phosphorus (mg/L) 11,550 0.03–1.46 0.27 0.23 16

*

Cheney Reservoir Task Force, 1994.
Computed Constituent Concentrations, Loads, and Yields 27

A

Streamflow, in cubic feet per second

0

500

2,500

2,0001,5001,000

Total suspended solids, in milligrams per liter

0

800

600400200

B

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Nitrate as nitrogen, in milligrams per liter

0

2.01.61.20.80.4

C Runoff goal: 6.60 milligrams per liter

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Total phosphorus, in milligrams per liter

0

1.00.80.60.40.2

D

Standard deviationMean

Cheney Reservoir Task Force goal

EXPLANATION

Mean annual (1999–2012)

Base flow

RunoffLong term

Base flowRunoff

Long term

Base flowRunoffLong term

Figure 8.

Annual mean A, streamflow; 

B, computed total suspended solids; 

C, computed nitrate; and 

D, computed total phosphorus concentrations during base 

flow, runoff, and long-term streamflow conditions at the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, during 1999 through 2012.
28 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

sources are the main contribution of nitrate to the North Fork 

Ninnescah River.

 The Cheney Reservoir Task Force established mean 

stream water-quality goals for total phosphorus concentrations 

under three streamflow conditions: 0.05 mg/L for base flow 

conditions, 0.40 mg/L for runoff conditions, and 0.10 mg/L 

for long-term conditions (Cheney Reservoir Task Force, 1994; 

table 1). Total phosphorus concentrations ranged from less 

than 0.01 mg/L to 1.46 mg/L during 1999 through 2012 (table 

5). The Cheney Reservoir Task Force long-term water-quality 

goal for total phosphorus (0.10 mg/L) was exceeded approximately 57 percent of the time during 1999 through 2012 

(fig. 7C; table 8). Mean total phosphorus during base flow conditions was 0.12 mg/L and ranged from less than 0.01 mg/L to 

1.46 mg/L during 1999 through 2012; the base flow goal for 

total phosphorus (0.05 mg/L) was exceeded about 95 percent 

of the time (table 8). Mean total phosphorus concentration 

during runoff conditions was 0.27 mg/L and ranged from 

0.03 mg/L to 1.46 mg/L during 1999 through 2012; the runoff 

goal for total phosphorus (0.40 mg/L) was exceeded about 

16 percent of the time (table 8). When annual mean total phosphorus concentrations were calculated for base flow, runoff, 

and long-term conditions, the Cheney Reservoir Task Force 

runoff goal was exceeded in 2002, which was the year with the 

largest annual mean turbidity (fig. 8D; tables 6,8); the longterm goal was exceeded every year except 2011 and 2012, 

which were the years with the smallest mean streamflows 

(fig. 8D; tables 6,8). The base flow goal was exceeded every 

year by 2–3 fold during 1999 through 2012 (fig. 8D).

Base flow goals for total suspended solids, nitrate, and 

total phosphorus were exceeded much more frequently (79 to 

99 percent of the time) than long-term (10 to 57 percent of the 

time) or runoff (0 to 16 percent of the time) goals. In addition, annual mean concentrations of these constituents during 

base flow exceeded base flow goals by up to 5 fold. A study 

by Pope and others (2002) indicated that natural background 

concentrations of phosphorus in some streams in the Cheney 

Reservoir watershed would not meet the base flow or longterm goals established by the Cheney Reservoir Task Force. 

Likewise, the current study indicates that groundwater has a 

substantial influence on nitrate concentrations in the North 

Fork Ninnescah River. Given natural background concentrations, groundwater influences, and the exceedance of base 

flow goals even during extremely dry years, the established 

base flow goals for total suspended solids, nitrate, and total 

phosphorus may be unattainable or substantially more BMPs 

may be needed to obtain them.

On an annual average basis no discernible patterns were 

evident in total suspended sediment, nitrate, and total phosphorus concentrations or loads over time, in large part because 

of hydrologic variability. However, more rigorous statistical 

analyses are required to evaluate temporal trends. A more 

rigorous analysis of temporal trends will allow evaluation of 

watershed investments in BMPs.

Summary 

The North Fork Ninnescah River is the largest contributing tributary to Cheney Reservoir in south-central Kansas. 

Cheney Reservoir is one of the primary sources of water 

for the city of Wichita. Site-specific regression models were 

originally published in 2006. Regression equations were 

updated based on continuous physical property measurements and analyses of discrete water samples collected from 

1999 through 2009. The original models for dissolved solids, 

sodium, chloride, sulfate, calcium, magnesium, potassium, 

alkalinity, bicarbonate, total suspended solids, suspendedsediment concentration, total Kjeldahl nitrogen, total phosphorus, orthophosphate, and fecal coliform bacteria were updated. 

New regression models were developed for total nitrogen, 

nitrate, organic nitrogen, Escherichia coli (E. coli) bacteria, 

and total organic carbon.

In general, model forms and the amount of variance 

explained by the models was similar between the original 

and updated models. The amount of variance explained by 

the updated models changed by 10 percent or less relative to 

the original models. Additional data collection over a wider 

range of hydrological conditions facilitated the development 

of the new models. The nitrate model is particularly important 

because it allows for comparison to Cheney Reservoir Task 

Force goals.

In-stream continuous turbidimeters were changed from 

Yellow Springs Instruments (YSI) model 6026 (YSI6026) to YSI 

model 6136 (YSI6136) sensors in 2011, and a relation between 

the continuous turbidity values of both sensors was developed. 

The relation between the different turbidity values measured 

by the different sensor models was updated and a conversion 

factor of 0.68 was established to convert the YSI6026 turbidity 

measurements to YSI6136 measurements at the North Fork Ninnescah River above Cheney Reservoir site.

Mean North Fork Ninnescah River streamflow during 

1999 through 2012 was 129 cubic feet per second (ft3/s) and 

was smaller than the mean streamflow for the period of record 

(July 1965 through December 2009; 141 ft3/s). Streamflows 

were smallest in 2012 and largest in 2010. A 10 percent 

streamflow-separation point occurred at 208 ft3/s and was used 

to define base flow and runoff conditions. Continuously measured pH exceeded the Kansas aquatic-life-support criterion 

of 8.5 about 19 percent of the time during 1999 through 2012, 

primarily during base flow conditions in spring and summer, 

and likely was caused by increased algal photosynthesis. Continuously measured dissolved oxygen concentrations were less 

than the Kansas aquatic-life-support criterion of 5.0 mg/L less 

than 1 percent of the time during 1999 through 2012. Continuously measured turbidity concentrations exceeded the U.S. 

Environmental Protection Agency’s (USEPA) turbidity guideline of 22.13 nephelometric turbidity units about 55 percent 

of the time during 1999 through 2012; these turbidity exceedances occurred during the range of streamflows.

Hourly concentrations or densities were calculated for 

selected constituents using the updated and newly developed 
References Cited 29

models. Mean and median hourly concentrations or densities 

were computed for each constituent and the percent of hourly 

values that exceeded relevant Federal, State, or Cheney Reservoir Task Force water-quality criteria or goals was calculated 

for 1999 through 2012. Loads for selected constituents also 

were quantified for 1999 through 2012.

Mean computed hourly sodium concentration during 

1999 through 2012 was 168 milligrams per liter (mg/L), likely 

resulting from the seepage of affected groundwater. Mean 

computed hourly chloride concentration was 234 mg/L. Mean 

computed total suspended solids concentration was 54 mg/L. 

The total suspended solids load was 174,031 tons. Mean suspended sediment was 88 mg/L; annual mean suspended sediment was lowest in 2012 and highest in 2009, corresponding 

to the smallest and second-largest annual mean streamflows. 

Suspended-sediment load for was 518,321 tons.

The USEPA recommended total nitrogen guideline of 

0.84 mg/L was exceeded nearly 100 percent of the time. The 

total nitrogen load was 3,098 tons and was smallest in 2011 

and 2012 and largest in 2010, corresponding to the smallest 

and largest annual mean streamflows and streamflow loads. 

Mean hourly nitrate was 1.08 mg/L during the study period. 

The nitrate load for the study period was 1,361 tons. The mean 

total phosphorus concentration was 0.14 mg/L. The USEPA 

level III ecoregion 27 total phosphorus guideline of 0.09 mg/L 

was exceeded approximately 67 percent of the time. The total 

phosphorus load for the study period was 328 tons.

When annual mean total suspended solids concentrations 

were calculated for base flow, runoff, and long-term conditions, the Cheney Reservoir Task Force runoff and long-term 

goals usually were never exceeded, but the base flow goal was 

exceeded every year. The Cheney Reservoir Task Force longterm water-quality goal for nitrate of 1.20 mg/L was exceeded 

about 45 percent of the time. When annual mean nitrate 

concentrations were calculated for base flow, runoff, and 

long-term conditions, the Cheney Reservoir Task Force runoff 

(6.60 mg/L) goal was never exceeded, the long-term goal was 

exceeded in 2012, and the base flow goal of 0.25 mg/L was 

exceeded every year. Mean nitrate concentrations that were 

higher during base flow, rather than runoff, conditions suggest 

that groundwater sources are the main contributors of nitrate 

to the North Fork Ninnescah River above Cheney Reservoir. 

The Cheney Reservoir Task Force long-term phosphorus goal of 0.10 mg/L was exceeded about 57 percent of the 

time. The Cheney Reservoir Task Force runoff goal for total 

phosphorus of 0.40 mg/L was exceeded in 2002, the year with 

the largest yearly mean turbidity, and the long-term goal was 

exceeded in every year except 2011 and 2012, the years with 

the smallest mean streamflows. The total phosphorus base 

flow goal of 0.05 mg/L was exceeded every year. 

Base flow goals for total suspended solids, nitrate, and 

total phosphorus were exceeded much more frequently (79 to 

99 percent of the time) than long-term (10 to 57 percent of the 

time) or runoff (0 to 16 percent of the time) goals. In addition, annual mean concentrations of these constituents during 

base flow exceeded base flow goals by up to 5 fold. Given 

natural background concentrations, groundwater influences, 

and the exceedance of base flow goals even during extremely 

dry years, the established base flow goals for total suspended 

solids, nitrate, and total phosphorus may be unattainable or 

substantially more best management practices (BMPs) may be 

needed to attain them.

On an annual average basis no discernible patterns were 

evident in total suspended sediment, nitrate, and total phosphorus concentrations or loads over time, in large part because 

of hydrologic variability. However, more rigorous statistical 

analyses are required to evaluate temporal trends. A more 

rigorous analysis of temporal trends will allow evaluation of 

watershed investments in BMPs.

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Appendixes 1–6
36 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

Appendix 1. Sample collection dates and streamflow conditions for discrete water-quality samples included in regression model 

development for the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 1999 through 

2009. 

[ft3/s, cubic feet per second; TDS, total dissolved solids; Na, sodium; Cl, chloride; SO4, sulfate; TSS, total suspended solids; SSC, suspended-sediment concentration; TN, total nitrogen; TKN, nitrogen, ammonia plus organic; NO3

, nitrate; TP, total phosphorus; OP, orthophosphate; EC, Escherichia coli bacteria; Ca, 

calcium; Mg, magnesium; K, potassium; ALK, alkalinity; HCO3, bicarbonate; ON, organic nitrogen; FC, fecal coliform bacteria; TOC, total organic carbon]

Sampling date Streamflow 

(ft3/s) Constituents sampled

January 26, 1999 106 TDS, Na, TSS, TN, TKN, NO3, TP, OP, Ca, Mg, K, ON, FC

February 1, 1999 437 FC

April 15, 1999 1,140 FC

April 16, 1999 684 TDS, Na, Cl, SO4, TSS, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

May 13, 1999 98 TDS, Na, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ON, FC

May 24, 1999 158 TDS, Na, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ON, FC

June 10, 1999 86 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

June 25, 1999 237 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

July 8, 1999 76 SSC

July 14, 1999 63 TDS, Na, TN, NO3, OP, Ca, Mg, K, ON

July 29, 1999 60 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

August 12, 1999 43 TDS, Na, TSS, NO3, TP, OP, Ca, Mg, K, FC 

August 26, 1999 34 TDS, Na, TSS, NO3, TP, OP, Ca, Mg, K, FC

September 22, 1999 49 TDS, Na, Cl, TSS, SSC, NO3, TP, Ca, Mg, K, ALK, HCO3, FC, TOC

December 2, 1999 62 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC 

February 25, 2000 256 TDS, Na, Cl, SO4, TSS, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

April 27, 2000 110 TDS, Na, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ON, FC

May 25, 2000 60 TDS, Na, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ON, FC

June 21, 2000 47 TDS, Na, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ON, FC

July 26, 2000 117 TDS, Na, TSS, NO3, TP, OP, Ca, Mg, K, FC

August 29, 2000 9.4 TDS, Na, TSS, NO3, TP, OP, Ca, Mg, K, FC

September 28, 2000 20 TDS, Na, TSS, NO3, Ca, Mg., K, FC

October 26, 2000 2,663 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

June 6, 2001 1,753 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

June 27, 2001 77 SSC

September 4, 2001 19 TDS, Na, Cl, SO4, TN, NO3, OP, Ca, Mg, K, ALK, HCO3, ON

January 8, 2002 81 SSC

May 13, 2002 318 SSC, TKN, TP

May 15, 2002 130 SSC

August 14, 2002 347 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

March 18, 2003 396 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

March 19, 2003 2,245 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

April 21, 2003 551 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

March 5, 2004 1,968 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

May 14, 2004 579 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

June 14, 2004 238 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

September 8, 2004 39 TDS, Na, Cl, SO4, TN, NO3, OP, Ca, Mg, K, ALK, HCO3, ON

March 24, 2005 381 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

May 16, 2005 524 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC
Appendix 1–6 37

Appendix 1. Sample collection dates and streamflow conditions for discrete water-quality samples included in regression model 

development for the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 1999 through 

2009.—Continued

[ft3/s, cubic feet per second; TDS, total dissolved solids; Na, sodium; Cl, chloride; SO4, sulfate; TSS, total suspended solids; SSC, suspended-sediment concentration; TN, total nitrogen; TKN, nitrogen, ammonia plus organic; NO3

, nitrate; TP, total phosphorus; OP, orthophosphate; EC, Escherichia coli bacteria; Ca, 

calcium; Mg, magnesium; K, potassium; ALK, alkalinity; HCO3, bicarbonate; ON, organic nitrogen; FC, fecal coliform bacteria; TOC, total organic carbon]

Sampling date Streamflow 

(ft3

/s) Constituents sampled

June 10, 2005 1,100 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

June 13, 2005 3,150 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

August 29, 2005 256 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

March 2, 2006 92 TDS, Na, Cl, SO4

, TSS, SSC, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC 

March 22, 2006 144 TSS, SSC, TN, TKN, TP, TOC

May 1, 2006 85 TDS, Na, Cl, SO4

, TN, NO3, OP, Ca, Mg, ALK, HCO3, ON

May 12, 2006 156 TDS, Na, Cl, SO4

, TN, NO3, Ca, Mg, K, ALK, HCO3, ON

June 5, 2006 39 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

July 31, 2006 15 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, EC, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

September 7, 2006 39 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, EC, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

September 21, 2006 24 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, EC, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

January 9, 2007 70 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, EC, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

March 14, 2007 67 TDS, Na, TSS, SSC, TN, TKN, NO3

, TP, OP, EC, Ca, Mg, K, ON, FC

March 22, 2007 98 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

March 26, 2007 295 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, EC, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

March 31, 2007 1,370 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

April 1, 2007 1,660 EC, FC

April 16, 2007 751 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

May 7, 2007 3,725 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

May 24, 2007 4,780 FC

June 29, 2007 401 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

September 4, 2007 28 TDS, Na, Cl, SO4

, TSS, NO3, TP, Ca, Mg, K, ALK, HCO3, FC, TOC

April 24, 2008 269 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

May 9, 2008 3,103 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

June 19, 2008 223 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

September 15, 2008 404 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

October 16, 2008 839 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

March 31, 2009 721 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

April 27, 2009 2,150 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

June 17, 2009 349 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

August 20, 2009 103 TDS, Na, Cl, SO4, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC

September 10, 2009 482 TDS, Na, Cl, SO4

, TSS, SSC, TN, TKN, NO3, TP, OP, Ca, Mg, K, ALK, HCO3, ON, FC, TOC
38 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas Appendix 2. Christensen and others (2006), updated, and new regression models and summary statistics for continuous concentration computations for the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 1999 through 2009.

[R2, coefficient of determination; MSE, mean square error; RMSE, root mean square error; MSPE, model standard percentage error; %, percent; ±, plus or minus; n, number of discrete samples; mg/L, milligrams per liter; log, log10; SC, specific conductance in microsiemens per centimeter at 25 degress Celsius; Q, streamflow in cubic feet per second; TBY6026, turbidity from YSI sensor 6026 in formazin nephelometric units; TKN, total Kjeldahl nitrogen; <, less than]

Regression model

Location of 

additional 

model 

information 

in Stone and 

others (2013)

Multiple 

R2

Adjusted 

R2 MSE RMSE MSPE (upper) MSPE (lower)

Bias 

correction 

factor 

(Duan, 1983)

90 % prediction interval, 

in ± %

Discrete data

n

Range of 

values in 

variable 

measurements

Mean Median Standard deviation

Calcium (Ca), dissolved, mg/L

Christensen and others (2006)

log(Ca) = 0.724log(SC) - 0.387 0.76 0.76 0.005 0.077 19 16 1.02 40 127 Ca: 19.7–88.7 52.9 50.7 17.8

SC: 198–1,300 821 837 303

Updated

log(Ca) = 0.120log(Q) + 0.964log(SC) - 1.37 figs. 6,7; 

table 2

0.89 0.89 0.002 0.048 12 10 1.01 40 61 Ca: 23.2–86.6 53.4 54.7 15.8

Q: 9.4–3,725 564 223 873

SC: 258–1,430 883 976 326

Magnesium (Mg), dissolved, mg/L

Christensen and others (2006)

Mg = 0.0086(SC) +1.68 0.80 0.80 1.750 1.321 15 -15 1.00 39 127 Mg: 3.52–13.8 8.77 9.27 2.93

SC: 198–1,300 821 837 303

Updated

log(Mg) = 0.698log(SC) - 1.08 figs. 8, 9; 

table 2

0.92 0.92 0.002 0.041 10 9 1.00 40 61 Mg: 3.66–13.0 9.26 10.0 2.63

SC: 258–1,430 883 976 326

Potassium (K), dissolved, mg/L

Christensen and others (2006)

log(K) = -0.0003(SC) + 0.944 0.54 0.54 0.008 0.092 24 19 1.02 40 127 K: 2.53–8.16 4.94 4.85 1.48

SC: 198–1,300 821 837 303

Updated

log(K) = -0.0011(SC) + 1.17log(SC) -1.80 figs. 18, 19; 

table 2

0.73 0.72 0.005 0.074 19 16 1.01 40 61 K: 2.89–8.41 4.93 5.00 1.56

SC: 258–1,430 883 976 326
Appendix 1–6 39

Appendix 2. Christensen and others (2006), updated, and new regression models and summary statistics for continuous concentration computations for the North Fork 

Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 1999 through 2009.—Continued

[R2, coefficient of determination; MSE, mean square error; RMSE, root mean square error; MSPE, model standard percentage error; %, percent; ±, plus or minus; n, number of discrete samples; mg/L, milligrams 

per liter; log, log10; SC, specific conductance in microsiemens per centimeter at 25 degress Celsius; Q, streamflow in cubic feet per second; TBY6026, turbidity from YSI sensor 6026 in formazin nephelometric 

units; TKN, total Kjeldahl nitrogen; <, less than]

Regression model

Location of 

additional 

model 

information 

in Stone and 

others (2013)

Multiple 

R2

Adjusted 

R2 MSE RMSE MSPE (upper) MSPE (lower)

Bias 

correction 

factor 

(Duan, 1983)

90 % prediction interval, 

in ± %

Discrete data

n

Range of 

values in 

variable 

measurements

Mean Median Standard deviation

Alkalinity (ALK), mg/L)

Christensen and others (2006)

log(ALK) = 0.659log(SC) +0.241 0.81 0.80 0.004 0.061 15 13 1.01 41 27 ALK: 74–222 147 153 42

SC: 322–1,250 844 903 297

Updated

log(ALK) = 0.114log(Q) + 0.810log(SC) - 0.447 figs. 24, 25; 

table 4 

0.87 0.86 0.002 0.046 11 10 1.01 40 48 ALK: 74–215 149 156 38

Q: 15–3,725 697 321 942

SC: 258–1,430 822 837 339

Bicarbonate (HCO3), mg/L

Christensen and others (2006)

log(HCO3) = 0.669log(SC) + 0.296 0.81 0.80 0.004 0.062 15 13 1.01 41 27 HCO3: 86–271 179 187 51

SC: 322–1,250 844 903 297

Updated

log(HCO3) = 0.113log(Q) + 0.813log(SC) - 0.368 figs. 26, 27; 

table 4

0.86 0.85 0.002 0.048 12 10 1.01 40 48 HCO3: 86–260 181 190 47

Q: 15–3,725 697 321 942

SC: 258–1,430 822 837 339

Organic Nitrogen (ON), mg/L (TKN - ammonia)

New

ON = 1.58log(TBY6026) + 1.04log(SC) - 4.65 figs. 42, 43; 

table 9

0.82 0.81 0.087 0.295 21 -21 1.00 40 54 ON: <0.07–3.26 1.40 1.38 0.68

TBY6026: 12–600 140 113 140

SC: 258–1,430 857 935 337
40 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas Appendix 2. Christensen and others (2006), updated, and new regression models and summary statistics for continuous concentration computations for the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), south-central Kansas, 1999 through 2009.—Continued

[R2, coefficient of determination; MSE, mean square error; RMSE, root mean square error; MSPE, model standard percentage error; %, percent; ±, plus or minus; n, number of discrete samples; mg/L, milligrams 

per liter; log, log10; SC, specific conductance in microsiemens per centimeter at 25 degress Celsius; Q, streamflow in cubic feet per second; TBY6026, turbidity from YSI sensor 6026 in formazin nephelometric 

Regression model

Location of 

additional 

model 

information 

in Stone and 

others (2013)

Multiple 

R2

Adjusted 

R2 MSE RMSE MSPE (upper) MSPE (lower)

Bias 

correction 

factor 

(Duan, 1983)

90 % prediction interval, 

in ± %

Discrete data

n

Range of 

values in 

variable 

measurements

Mean Median Standard deviation

Fecal coliform bacteria (FC), colonies/100 mL

Christensen and others (2006)

log(FC) = 0.714log(TBY6026) - 0.0016(SC) + 3.10 0.78 0.76 0.223 0.469 195 66 1.52 61 30 FC: 8–36,000 4,888 500 8,646

TBY6026: 7.9–575 152 41 185

SC: 322–1,250 944 1,070 292

Updated

log(FC) = 0.761log(TBY6026) - 0.0013(SC) + 2.73 figs. 54, 55; 

table 13 

0.72 0.71 0.237 0.487 207 67 1.71 67 60 FC: 8–65,000 6,207 880 11,736

TBY6026: 13–600 138 120 134

SC: 200–1,430 843 896 333

Total organic carbon (TOC), mg/L

New

log(TOC) = 0.485log(TBY6026) + 0.0080 figs. 60, 61; 

table 15

0.73 0.72 0.018 0.135 37 27 1.04 41 45 TOC: 2.5–20.5 11.2 12.6 5.3

TBY6026: 13–600 161 123 144

units; TKN, total Kjeldahl nitrogen; <, less than]
Appendix 1–6 41

Appendix 3. Tobit regression models and summary statistics for constituents with left-censored data for the North Fork Ninnescah River (site 07144780)upstream from Cheney Reservoir, south-central Kansas, 1999 through 2009.[%, percent; MSE, mean square error; RMSE, root mean square error; MSPE, model standard percentage error; n, number of observations; log, log10; ON, organic nitrogen (total Kjeldahl nitrogen minus ammonia); TBY6026, turbidity from YSI sensor 6026 in formazin nephelometric units; SC, specific conductance in microsiemens per centimeter at 25 degrees Celsius; --, no data (statistical package did not include this output for models that required addition or subtraction of response variables); <, less than; OP, orthophosphate in milligrams per liter]

Water-quality 

constituent, in 

milligrams per 

liter

Percent of 

data that 

is leftcensored 

(%)

Tobit regression model MSE RMSE MSPE (upper) MSPE (lower) Chi- square value Degrees of freedom p-value n

Organic nitrogen 15 ON = 1.58log(TBY6026) + 1.04log(SC) - 4.64 -- -- -- -- 92.72 2 <0.01 54Orthophosphate 33 OP = -0.0002(SC) + 0.243 0.002 0.042 70 -70 63.20 1 <0.01 54
42 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

Appendix 4. Summary statistics for data used in turbidity sensor linear regression analyses for the North Fork Ninnescah River 

upstream from Cheney Reservoir (site 07144780), south-central Kansas, October 1999 through October 2010.

[R2, coefficient of determination; n, number of observations; TBY6136, YSI model 6136 turbidity in formazin nephelometric units (FNU); TBY6026, YSI model 

6026 turbidity in FNU]

Regression equation R2 Turbidity sensor type 

or ratio n Range Mean Median

TBY6136 = 0.701(TBY6026) 0.96 YSI6026 7,429 4.0–1,570 44 28

YSI6136 7,429 1.8–1,160 32 19

YSI6136/YSI6026 ratio 7,429 0.19–3.92 0.70 0.68
Appendix 1–6 43

Appendix 5. Updated Christensen and others (2006) regression models for the North Fork Ninnescah River 

upstream from Cheney Reservoir (site 07144780), south-central Kansas.

[mg/L, milligrams per liter; 6026, YSI model 6026 turbidity sensor; log, log10; TSS, total suspended solids in milligrams per 

liter; TBY6026, turbidity from YSI sensor 6026 in formazin nephelometric units; 6136, YSI model 6136 turbidity sensor; TBY6136, 

turbidity from YSI sensor 6136 in formazin nephelometric units; SSC, suspended sediment concentration in milligrams per liter; 

TKN, total Kjeldahl nitrogen (total ammonia plus organic nitrogen) in milligrams per liter; Q, streamflow in cubic feet per second; TP, total phosphorus in milligrams per liter; col/100 mL, colonies per 100 milliliters; FC, fecal coliform bacteria in colonies 

per 100 milliliters; SC, specific conductance in in microsiemens per centimeter at 25 degrees Celsius]

Constituent Sensor 

type Regression model

Total suspended solids (mg/L) 6026 log(TSS) = 0.893log(TBY6026) + 0.253

6136 log(TSS) = 0.893log(TBY6136) + 0.402

Suspended sediment (mg/L) 6026 log(SSC) = 1.10log(TBY6026) + 0.0037

6136 log(SSC) = 1.10log(TBY6136) + 0.188

Total Kjeldahl nitrogen (mg/L) 6026 TKN = 0.0054(TBY6026) - 0.0004(Q) + 0.790

6136 TKN = 0.0079(TBY6136) - 0.0004(Q) + 0.790

Total phosphorus (mg/L) 6026 TP = 0.0008(TBY6026) + 0.0001(Q) + 0.0863

6136 TP = 0.0012(TBY6136) + 0.0001(Q) + 0.0863

Fecal coliform bacteria (col/100 mL) 6026 log(FC) = 0.714log(TBY6026) - 0.0016(SC) + 3.10

6136 log(FC) = 0.714log(TBY6136) - 0.0016(SC) + 3.22
44 Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas

Appendix 6. Updated new regression models for the North Fork Ninnescah River upstream from Cheney Reservoir (site 07144780), 

south-central Kansas.

[mg/L, milligrams per liter; 6026, YSI model 6026 turbidity sensor; log, log10, TSS, total suspended solids in milligrams per liter; TBY6026, turbidity from YSI 

sensor 6026 in formazin nephelometric units; 6136, YSI model 6136 turbidity sensor; TBY6136, turbidity from YSI sensor 6136 in formazin nephelometric units; 

SSC, suspended sediment concentration in milligrams per liter; Q, streamflow in cubic feet per second;TKN, total Kjeldahl nitrogen (ammonia plus organic 

nitrogen) in milligrams per liter; NO3, nitrate in milligrams per liter; sin, sine; D, day of year; cos, cosine; ON, organic nitrogen (total ammonia plus organic 

nitrogen minus ammonia); SC, specific conductance in microsiemens per centimeter at 25 degrees Celsius; TN, total nitrogen in milligrams per liter; TP, total 

phosphorus in milligrams per liter; col/100 mL, colonies per 100 milliliters; EC, Escherichia coli bacteria in colonies per 100 milliliters; FC, fecal coliform 

bacteria in colonies per 100 milliliters; TOC, total organic carbon in milligrams per liter]

Constituent Sensor 

type Regression model

Total suspended solids (mg/L) 6026 log(TSS) = 0.903log(TBY6026) + 0.252

6136 log(TSS) = 0.903log(TBY6136) + 0.404

Suspended sediment (mg/L) 6026 log(SSC) = 0.540log(Q) + 0.559log(TBY6026) - 0.110

6136 log(SSC) = 0.540log(Q) + 0.559log(TBY6136) - 0.0167

Total Kjeldahl nitrogen (mg/L) 6026 log(TKN) = 0.426log(TBY6026) - 0.700

6136 log(TKN) = 0.426log(TBY6136) - 0.628

Nitrate (mg/L) 6026 NO3 = 0.0519sin(2πD/365) + 0.619cos(2πD/365) - 0.389log(TBY6026) + 1.63

6136 NO3 = 0.0519sin(2πD/365) + 0.619cos(2πD/365) - 0.389log(TBY6026) + 1.57

Organic nitrogen (mg/L) 6026 ON = 1.58log(TBY6026) + 1.04log(SC) - 4.65

6136 ON = 1.58og(TBY6136) + 1.04log(SC) - 4.40

Total nitrogen (mg/L) 6026 log(TN) = 0.0218sin(2πD/365) + 0.112cos(2πD/365) + 0.182og(TBY6026) - 0.0012

6136 log(TN) = 0.0218sin(2πD/365) + 0.112cos(2πD/365) + 0.182log(TBY6136) + 0.0175

Total phosphorus (mg/L) 6026 log(TP) = 0.611log(TBY6026) - 1.83

6136 log(TP) = 0.611log(TBY6136) - 1.73

Escherichia coli bacteria (col/100 mL) 6026 log(EC) = 0.0032(TBY6026) - 0.0016(SC) + 4.01

6136 log(EC) = 0.0047(TBY6136) - 0.0016(SC) + 4.01

Fecal coliform bacteria (col/100 mL) 6026 log(FC) = 0.761log(TBY6026) - 0.0013(SC) + 2.73

6136 log(FC) = 0.761log(TBY6136) - 0.0013(SC) + 2.85

Total organic carbon (mg/L) 6026 log(TOC) = 0.485log(TBY6026) + 0.0080

6136 log(TOC) = 0.485log(TBY6136) + 0.0892
Publishing support provided by: 

Rolla Publishing Service Center

For additional information concerning this publication, contact:

Director, USGS Kansas Water Science Center 

4821 Quail Crest Place

Lawrence, KS 66049

(785) 842–9909

Or visit the Kansas Water Science Center Web site at:

http://ks.water.usgs.gov
Stone and others—Concentrations and Loads in the North Fork Ninnescah River Upstream from Cheney Reservoir, South-Central Kansas —SIR 2013–5071