Prepared in cooperation with the Kansas Water Office

Sediment Transport to and from 

Small Impoundments in Northeast Kansas,

March 2009 through September 2011

Scientific Investigations Report 2012–5269

U.S. Department of the Interior

U.S. Geological Survey
Cover. Upper photograph shows gagehouse and normal outflow structure at Atchison County Lake near Horton, Kansas (393806095273700). 

(Photograph by Eric Looper, U.S. Geological Survey, September 24, 2009). Lower photograph shows sediment sampling and discharge 

measurement during high flow at Clear Creek at Decatur Rd. near Horton, Kansas (393817095260100). (Photograph by Guy Foster, 

U.S. Geological Survey, August 17, 2009)
Sediment Transport to and from 

Small Impoundments in Northeast Kansas, 

March 2009 through September 2011

By Guy M. Foster, Casey J. Lee, and Andrew C. Ziegler

Prepared in cooperation with the Kansas Water Office

Scientific Investigations Report 2012–5269

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

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Suggested citation:

Foster, G.M., Lee, C.J., and Ziegler, A.C., 2012, Sediment transport to and from small impoundments in northeast 

Kansas, March 2009 through September 2011: U.S. Geological Survey Scientific Investigations Report 2012–5269, 

38 p. (Also available at http://pubs.usgs.gov/sir/2012/5269.)
iii

Contents

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

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

Purpose and Scope ..............................................................................................................................2

Description of Study Area ...................................................................................................................2

Previous Studies ...................................................................................................................................8

Methods...........................................................................................................................................................8

Data Collection and Analysis..............................................................................................................8

Quality Assurance.................................................................................................................................9

Regression Models...............................................................................................................................9

Computation of Sediment Concentrations, Trapping Efficiencies, Loads, and Yields.............14

Turbidity Truncation............................................................................................................................15

Estimating Sediment Transport During Periods of Missing Turbidity Data ...............................15

Collection, Analysis, and Computation of Sediment Loads at Selected Upstream Small 

Ponds ......................................................................................................................................17

Pond Locations and Descriptions ...........................................................................................17

Spatial Analysis of Selected Ponds........................................................................................17

Data Collection for Selected Small Ponds.............................................................................18

Pond Data Analysis Techniques..............................................................................................18

Characterization of Sediment Transport to and from Small Impoundments in Northeast 

Kansas..............................................................................................................................................19

Hydrologic Conditions........................................................................................................................19

Precipitation................................................................................................................................19

Streamflow..................................................................................................................................19

Sediment Transport ............................................................................................................................21

Trapping Efficiencies..........................................................................................................................22

Sediment Yields...................................................................................................................................25

Effect of Ponds on Total Watershed Sediment Yield.....................................................................29

Storms .........................................................................................................................................29

Little Delaware Mission Dam 5................................................................................................29

Little Delaware Mission Dam 17..............................................................................................29

Comparison of Results Between Ponds.................................................................................32

Comparison of Pond Results to Flow and Loads at Clear Creek at Decatur Rd. 

(upstream from Atchison County Lake) ....................................................................32

Comparison of Sediment Loads and Yields to other Watersheds in Northeast Kansas.........33

Comparison to Mill Creek Watershed, Johnson County, Kansas ......................................33

Comparison to Tuttle Creek Impoundment Watershed .......................................................34

Summary and Conclusions.........................................................................................................................35

References Cited..........................................................................................................................................36
iv

Figures

1. Map showing description of land use and location of study watersheds in 

northeast Kansas, 2009 through 2011........................................................................................3

2. Maps showing location of streamgages, sediment-sampling sites, watershed 

boundaries, National Inventory of Dams (NID) listed impoundments at A, Centralia 

Lake, B, Banner Creek Lake, and C, Atchison County Lake, 2009 through 2011 overlaid 

over 2010 aerial imagery..............................................................................................................5

3. Graph showing longitudinal profiles of streams upstream from study impoundments 

in northeast Kansas......................................................................................................................7

4. Graphs showing relation between cross-sectional mean (or independent reading in 

the case of the lakes) and in-place turbidity readings at study sites during 

March 2009 through September 2011......................................................................................10

5. Graphs showing comparison of measured and model-estimated suspendedsediment concentrations for the multiple linear regression at Clear Creek at 

Decatur Rd. (upstream from Atchison County Lake), and single linear regression 

relations between turbidity and suspended-sediment concentrations with removed 

outliers in red for other sediment sampling sites during March 2009 through 

September 2011...........................................................................................................................11

6. Graphs showing relations between discharge and suspended-sediment concentration at study sites with removed outliers in red (if removed from turbidity models, also 

removed from streamflow models) during March 2009 through September 2011...........12

7. Example hydrograph from Black Vermillion River above Centralia Lake showing 

differences between discharge- and turbidity-computed models, shifting results 

(Porterfield, 1972), and difference in prediction intervals between models during 

May 25–26, 2011 ..........................................................................................................................16

8. Graph showing percent of time each regression model was used and percent of 

total load computed by each model for each site during March 2009 through 

September 2011...........................................................................................................................16

9. Bar graph showing annual precipitation totals recorded by National Weather 

Service meteorological monitoring stations ..........................................................................20

10. Bar graph showing computed and estimated streamflow into and from each lake for 

study period during March 2009 through September 2011..................................................21

11. Graph showing streamflow duration curves for study sites upstream from lakes 

during March 2009 through September 2011 .........................................................................22

12. Bar graph showing computed and estimated sediment transport into and from each 

lake for study period during March 2009 through September 2011 ...................................25

13. Graph showing suspended-sediment load duration curves for study sites upstream 

from lakes during March 2009 through September 2011 .....................................................26

14. Pie charts showing total and mean annual trapping efficiencies and loads into and 

from each study lake during March 2009 through September 2011...................................27

15. Graph showing total and mean annual sediment yield and streamflow and 

corresponding depth of runoff for study period during March 2009 through 

September 2011...........................................................................................................................28

16. Graphs showing stormflow and suspended-sediment concentration hydrographs for 

Little Delaware Mission Dam (LDMD) 5 (A–E) and LDMD 17 (F–J) for each storm 

(rainfall totals recorded by National Weather Service (NWS) Weather Station at 

Horton, Kansas), April through August 2011 ..........................................................................30
v

17. Bar graph showing difference in sediment loads with and without the two small study 

ponds on total watershed sediment transport (during the five observed storms), and 

extrapolated during entire watershed and all four National Inventory of Dams listed 

ponds during April through August 2011.................................................................................33

18. Bar graphs showing comparison of mean annual sediment yield and streamflow 

yield with study watersheds and sub-watersheds in the Mill Creek Watershed, 

Johnson County, Kansas, and the Tuttle Creek lake watershed.........................................34

Tables

1. Location and contributing drainage area of streamgages and sediment-sampling 

stations in Atchison, Jackson, and Nemaha counties in northeast Kansas during 

March 2009 through September 2011........................................................................................4

2. Land use and sediment management practices upstream from sediment-sampling 

stations in northeast Kansas, obtained from on-site surveys, 2009.....................................6

3. Recent historical land use upstream from streamgages and sediment-sampling 

stations in northeast Kansas during March 2009 through September 2011 .......................6

4. Regression models and summary statistics for suspended-sediment concentration 

computations at study sites during March 2009 through September 2011.......................13

5. Turbidity truncation at study sites during March 2009 through September 2011 ............15

6. Location and contributing drainage area of small pond gaging sites in the Atchison 

watershed, northeast Kansas during March 2009 through September 2011 ...................17

7. Suspended-sediment concentration and percent silt/clay (<63 micrometers diameter) 

from discrete samples collected from study sites during March 2009 through 

September 2011...........................................................................................................................23

8. Stormflows, sediment transport, trapping efficiencies, and sediment yields for study 

ponds Little Delaware Mission Dam (LDMD) 5 and LDMD 17 (rainfall totals recorded 

by National Weather Service Weather Station at Horton, Kansas) from April through 

August 2011..................................................................................................................................29

9. Comparison of sediment loads between small study ponds Little Delaware Mission 

Dam (LDMD) 5 and LDMD 17, and Clear Creek at Decator Rd. (upstream from 

Atchison County Lake) during April through August 2011 ...................................................32
vi

Conversion Factors and Datum

Inch/Pound to SI

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

micrometer (μm) 0.00003937 inch (in.)

mile (mi) 1.609 kilometer (km)

Area

acre 4,047 square meter (m2)

square mile (mi2) 2.590 square kilometer (km2)

Volume

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

gallon (gal) 3.785 liter (L)

gallon (gal) 0.003785 cubic meter (m3)

Flow

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

cubic foot per second (ft3/s) 1.9835 acre-feet per day (acre-ft/d)

foot per mile (ft/mi) 0.1894 meter per kilometer (m/km)

million gallons per day (Mgal/d) 0.04381 cubic meter per second (m3/s)

Rate

acre-foot per square mile (acre-ft/mi2) 476.1 cubic meter per square kilometer (m3/km2)

inch per hour (in/hr) 25.40 millimeter per hour (mm/hr)

Weight

gram (g) 453.6 pound (lb)

pound per second (lb/s) 43.2 ton per day (ton/d)

ton 2,000 pound (lb)

Yield

ton per square mile (ton/mi2) 0.3503 tonne per square kilometer (tonne/km2)

Temperature can be converted to degrees Celsius (°C) or degrees Fahrenheit (°F) by the 

equations:

 °C = 5/9 (°F–32)

 °F = 9/5 (°C) + 32

Vertical coordinate information is referenced to North American Vertical Datum of 1988 

(NAVD 88).

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

Altitude, as used in this report, refers to distance above the vertical datum.

Suspended-sediment concentrations are report in milligrams per liter (mg/L).

Sediment loads are reported in tons.
Sediment Transport to and from Small Impoundments in 

Northeast Kansas, March 2009 through September 2011

By Guy M. Foster, Casey J. Lee, and Andrew C. Ziegler

Abstract

The U.S. Geological Survey, in cooperation with the 

Kansas Water Office, investigated sediment transport to and 

from three small impoundments (average surface area of 0.1 

to 0.8 square miles) in northeast Kansas during March 2009 

through September 2011. Streamgages and continuous turbidity sensors were operated upstream and downstream from 

Atchison County, Banner Creek, and Centralia Lakes to study 

the effect of varied watershed characteristics and agricultural 

practices on sediment transport in small watersheds in northeast Kansas. Atchison County Lake is located in a predominantly agricultural basin of row crops, with wide riparian 

buffers along streams, a substantial amount of tile drainage, 

and numerous small impoundments (less than 0.05 square 

miles; hereafter referred to as “ponds”). Banner Creek Lake 

is a predominantly grassland basin with numerous small 

ponds located in the watershed, and wide riparian buffers 

along streams. Centralia Lake is a predominantly agricultural 

basin of row crops with few ponds, few riparian buffers along 

streams, and minimal tile drainage. Upstream from Atchison 

County, Banner Creek, and Centralia Lakes 24, 38, and 32 percent, respectively, of the total load was transported during less 

than 0.1 percent (approximately 0.9 days) of the time. Despite 

less streamflow in 2011, larger sediment loads during that year 

indicate that not all storm events transport the same amount 

of sediment; larger, extreme storms during the spring may 

transport much larger sediment loads in small Kansas watersheds. Annual sediment yields were 360, 400, and 970 tons 

per square mile per year at Atchison County, Banner, and 

Centralia Lake watersheds, respectively, which were less than 

estimated yields for this area of Kansas (between 2,000 and 

5,000 tons per square mile per year). Although Centralia and 

Atchison County Lakes had similar percentages of agricultural land use, mean annual sediment yields upstream from 

Centralia Lake were about 2.7 times those at Atchison County 

or Banner Creek Lakes. These data indicate larger yields of 

sediment from watersheds with row crops and those with 

fewer small ponds, and smaller yields in watersheds which are 

primarily grassland, or agricultural with substantial tile drainage and riparian buffers along streams. These results also indicated that a cultivated watershed can produce yields similar 

to those observed under the assumed reference (or natural) 

condition. Selected small ponds were studied in the Atchison 

County Lake watershed to characterize the role of small ponds 

in sediment trapping. Studied ponds trapped about 8 percent 

of the sediment upstream from the sediment-sampling site. 

When these results were extrapolated to the other ponds in 

the watershed, differences in the extent of these ponds was 

not the primary factor affecting differences in yields among 

the three watersheds. However, the selected small ponds were 

both 45 years old at the time of this study, and have reduced 

capacity because of being filled in with sediments. Additionally, trapping efficiency of these small ponds decreased over 

five observed storms, indicating that processes that suspended 

or resuspended sediments in these shallow ponds, such as 

wind and waves, affected their trapping efficiencies. While 

small ponds trapped sediments in small storms, they could be 

a source of sediment in larger or more closely spaced storm 

events. Channel slope was similar at all three watersheds, 

0.40, 0.46, and 0.31 percent at Atchison County, Banner 

Creek, and Centralia Lake watersheds, respectively. Other factors, such as increased bank and stream erosion, differences in 

tile drainage, extent of grassland, or riparian buffers, could be 

the predominant factors affecting sediment yields from these 

basins. These results show that reference-like sediment yields 

may be observed in heavily agricultural watersheds through a 

combination of field-scale management activities and stream 

channel protection. When computing loads using published 

erosion rates obtained by single-point survey methodology, 

streambank contributions from the main stem of Banner Creek 

are three times more than the sediment load observed by this 

study at the sediment sampling site at Banner Creek, 2.6 times 

more than the sediment load observed by this study at the sediment sampling site at Clear Creek (upstream from Atchison 

County Lake), and are 22 percent of the load observed by this 

study at the sediment sampling site at Black Vermillion River 

above Centralia Lake. Comparisons of study sites to similarly 

sized urban and urbanizing watersheds in Johnson County, 

Kansas indicated that sediment yields from the Centralia 

Lake watershed were similar to those in construction-affected 

watersheds, while much smaller sediment yields in the Atchison County and Banner Creek watersheds were comparable to 

stable, heavily urbanized watersheds. Comparisons of study 

sites to larger watersheds upstream from Tuttle Creek Lake 
2 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

indicate the Black Vermillion River watershed continues to 

have high sediment yields despite 98 percent of sediment from 

the Centralia watershed (a headwater of the Black Vermillion 

River) being trapped in Centralia Lake. Estimated trapping 

efficiencies for the larger watershed lakes indicated that Banner Creek and Centralia Lakes trapped 98 percent of incoming 

sediment, whereas Atchison County Lake trapped 72 percent 

of incoming sediment during the 3-year study period. 

Introduction

In addition to natural variability in topography, soils, 

and geology, human activities affect the form, flow, and water 

quality of streams. Agricultural production has been the most 

widespread human-induced change to Kansas landscapes 

for the past 150 years (Broussard and Turner, 2009) and has 

been documented to accelerate surface erosion (Devlin and 

others, 2008), alter natural stream forms (Simon and Rinaldi, 

2000), and contribute excess nutrients and pesticides to 

streams (Alexander and others, 2008; Gilliom and Hamilton, 

2006). Among the most problematic issues created by these 

anthropogenic landscape changes is the increased transport of 

sediments, contributed from accelerated surface and stream 

channel erosion, to downstream impoundments used for flood 

control and drinking water. Large impoundments are the 

source of water for more than two-thirds of the population of 

the State of Kansas and sediment accumulation has decreased 

multipurpose pool capacity by more than 40 percent in several 

of these impoundments (deNoyelles and Jakubauskas, 2008). 

Although factors controlling sediment erosion from 

agricultural areas have been extensively studied, deposition of 

eroded sediments and erosion of stream channels obscure relations between management practices and sediment transport 

in streams and rivers. Clear cutting of forested areas and poor 

agricultural practices can substantially increase erosion rates 

from agricultural areas, but sediment deposition in intervening 

fields and flood plains can cause downstream sediment yields 

to remain constant (Trimble, 1999). Similarly, resuspension 

of legacy sediments and stream channel erosion can obscure 

decreases in field-scale erosion associated with improved 

soil management (Trimble, 1999). Characterization of factors affecting sediment transport is complicated by substantial 

uncertainty in sediment transport estimates. Samples that 

represent high streamflow conditions are difficult to collect 

because of rapid water-level changes at sampling sites in small 

watersheds (Walling, 1977).

To characterize factors affecting sediment transport from 

small, agricultural watersheds in Kansas, the U.S. Geological 

Survey (USGS), in cooperation with the Kansas Water Office, 

collected streamflow and sediment data at sites upstream 

and downstream from three small impoundments (Atchison 

County, Banner Creek, and Centralia Lakes) in northeast 

Kansas from 2009 through 2011. Impoundments selected for 

study are within watersheds that vary with respect to current 

agricultural activities and management practices (fig. 1). In 

addition, the sites were located upstream and downstream 

from impoundments to compute sediment transport to, and the 

trapping efficiency of, each impoundment. This study is one 

component of a larger effort in cooperation with Academic, 

State, and Federal agencies to compile sediment budgets 

for the watersheds upstream from these impoundments. 

This report and study were supported in part through the 

Kansas State Water Plan Fund and the USGS Cooperative 

Water Program. 

Purpose and Scope

The purpose of this report is to describe sediment 

transport to and from three small impoundments in northeast 

Kansas in relation to watershed characteristics and agricultural 

practices. This report describes data collected from March 

2009 through September 2011 using continuously recording 

stage and water quality sensors at six sites, one upstream and 

downstream from each impoundment. Data collected from this 

study can be used to characterize important factors affecting sediment transport from small watersheds in northeastern 

Kansas. These data support Federal, State, and local efforts 

to improve water quality and identify processes affecting the 

transport of fluvial sediment.

Description of Study Area

Impoundments in this study vary in age and storage 

capacity. Atchison County Lake was constructed for recreation 

in 1935 and had an original storage capacity of 819 acre-feet 

(acre-ft) to the crest of the dam (elevation 1,055.5 feet (ft) 

National Geodetic Vertical Datum (NGVD) (Stene, 1946). 

Based on a 2010 survey by the Kansas Biological Survey 

(KBS), sediment accumulation has decreased the current 

storage capacity at the crest of the dam to approximately 

185 acre-ft (Kansas Biological Survey, 2010a). Banner Creek 

Lake was completed in 1997 to serve as the water supply for 

the city of Holton, Kansas, and for recreational purposes. 

The approximate storage capacity of Banner Creek Lake is 

7,400 acre-ft at a lake elevation of 1,078.1 ft NGVD as measured by a 2010 KBS bathymetric survey (Kansas Biological 

Survey, 2010b). Centralia Lake was completed in 1991 for 

water supply (the impoundment is not currently (2011) used 

for municipal water supply) and for recreational purposes. The 

approximate storage capacity of Centralia Lake is 4,000 acreft at a lake elevation of 1,265.5 ft NGVD as measured by a 

2010 KBS survey (Kansas Biological Survey, 2010c).

Sediment-sampling sites (hereafter called “sampling 

sites”) were located upstream from, and in or directly downstream from, Atchison County, Banner, and Centralia Lakes 

(table 1, fig. 2). Upstream sites were located at the furthest 

downstream location to best characterize streamflow and sediment transport to each impoundment. Because of multiple tributary inputs into streams and the necessity to install sampling 
Introduction 

3

Atchison

Watershed

Banner

Watershed

Centralia

Watershed

KANSAS

Area enlarged

JOHNSON

 COUNTY

Mill CreekWatershed

NEBRASKA

Tuttle Creek Lake

Watershed

Baileyville

0 5 10 MILES0 5 10 KILOMETERS

DONIPHAN

COUNTY

ATCHISON

COUNTY

ATCHISON

COUNTY

JEFFERSON

COUNTY

BROWN COUNTY

NEMAHA COUNTY

JACKSON COUNTY

MARSHALL

COUNTY

POTTAWATOMIE COUNTY

DONIPHAN

COUNTY

ATCHISON

COUNTY

ATCHISON

COUNTY

JEFFERSON

COUNTY

BROWN COUNTY

NEMAHA COUNTY

JACKSON COUNTY

MARSHALL

COUNTY

POTTAWATOMIE COUNTY

Tarkio-Wolf

Basin

Middle

Kansas

Basin

Delaware

Basin

Lower

Kansas

Basin

Lower Big

Blue Basin

Banner Creek Lake

near Holton, Kansas

Banner Creek Lake

near Holton, Kansas

Banner Creek at M Rd.

near Holton, Kansas

Banner Creek at M Rd.

near Holton, Kansas

Black Vermillion River Tributary

above Centralia Lake, Kansas 

Black Vermillion River Tributary

above Centralia Lake, Kansas 

Black Vermillion River Tributary

below Centralia Lake, Kansas 

Black Vermillion River Tributary

below Centralia Lake, Kansas 

Centralia Lake near

Centralia, Kansas

Centralia Lake near

Centralia, Kansas

Atchison County Lake Atchison County Lake

 near Horton, Kansas near Horton, Kansas 

Clear Creek at Decatur Rd.

 near Horton, Kansas 

Clear Creek at Decatur Rd.

Base map from United States Department of AgricultureNational Agricultural Statistics Service, 2010Crop Data Layer

96°10' 95°50' 95°20' 95°30' 95°40' 96°00' 96°20'

39°45'

39°40'39°35'39°30'39°25'

U.S. Geological Survey baseline sediment study watershed boundaryU.S. Geological Survey 8-digit basin boundary and basin nameU.S. Geological Survey baseline sediment study site and station name— Continuous data collection from March 2009 to September 2011

2010 Land cover, by categoryAgriculture Alfalfa Corn Sorghum Soybeans Pasture/grass Winter wheatNon-agriculture Deciduous forest Developed Water

EXPLANATION

Black Vermillion River Tributary

above Centralia Lake, Kansas 

Atchison County Lake

 near Horton, Kansas 

Clear Creek at Decatur Rd.

 near Horton, Kansas 

U.S. Geological Survey station with continuous collection of discharge, 

gage height, specific conductance, temperature, and turbidity

 U.S. Geological Survey station with continuous collection of lake water surface elevation, specific conductance, temperature, turbidity, and precipitationU.S. Geological Survey station with continuous collection of lake water surface elevation and precipitation

Centralia

Holton

Horton

South Fork

big Nemeha

Basin

Independence

Creek Basin

Figure 1. Description of land use and location of study watersheds in northeast Kansas, 2009 through 2011.
4 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

Table 1. Location and contributing drainage area of streamgages and sediment-sampling stations in Atchison, Jackson, and Nemaha 

counties in northeast Kansas during March 2009 through September 2011.

[mi2, square miles]

U.S. Geological 

Survey identification numberStation name

Contributing 

drainage area 

(mi2

)

Latitude 

(degrees, minutes, seconds)

Longitude 

(degrees, minutes, seconds)

393817095260100 Clear Creek at Decator Rd. near Horton, Kansas1,4 5.6 39°38′17′′ 95°26′01′′

393806095273700 Atchison County Lake near Horton, Kansas1 9.1 39°38′06′′ 95°27′37′′

393806095274100 Clear Creek below Atchison County Lake near Horton, Kansas2 9.1 39°38′06′′ 95°27′37′′

392652095484100 Banner Creek at M Rd. near Holton, Kansas1,4 9.1 39°26′52′′ 95°48′41′′

392727095454900 Banner Creek Lake near Holton, Kansas1 19.1 39°27′27′′ 95°45′49′′

392727095454500 Banner Creek below Banner Creek Lake near Holton, Kansas2 19.1 39°27′27′′ 95°45′49′′

394126096073500 Black Vermillion River tributary above Centralia Lake, Kansas1,4 4.4 39°41′26′′ 96°07′35′′

394146096085500 Centralia Lake near Centralia, Kansas3 12.6 39°41′46′′ 96°08′55′′

394218096095000 Black Vermillion River tributary below Centralia Lake, Kansas1 12.6 39°42′18′′ 96°09′50′′

1

Sediment sampling station, water-quality monitor, and discharge gage.

2

Separate site number used for lake outflow discharge, location same as elevation and water-quality monitor.

3

Monitored only for continuous lake elevation.

4

Upstream sampling site.

sites upstream from impoundments to avoid backwater conditions, upstream sites characterize only a part of streamflow and 

sediment transport to the impoundments. Upstream sampling 

sites characterized streamflow and sediment transport from 

62 percent of the watershed upstream from Atchison County 

Lake (hereafter called ‘Atchison watershed’ or ‘Atchison’), 

48 percent of the watershed upstream from Banner Creek Lake 

(hereafter called ‘Banner watershed’ or ‘Banner’), and 35 percent of the watershed upstream from Centralia Lake (hereafter 

called ‘Centralia watershed’ or ‘Centralia’) (table 1). Sampling 

sites located within and downstream from impoundments 

were selected to describe sediment trapping efficiency within 

studied impoundments. 

Water elevation and turbidity also were collected at two 

small ponds (<0.05 mi2

) in the Atchison County Lake watershed to estimate sediment transport to and from small watershed ponds from April through August 2011. This information was then compared to the downstream sampling site to 

characterize the effect of the small ponds on total watershed 

sediment yield.

As part of an effort to compute sediment budgets 

upstream from each impoundment, Kansas State University 

(2009) characterized current land use and sediment management practices using surveys of selected local property owners 

(table 2). Assessed land use in the Atchison and Centralia 

watersheds consisted predominantly of cultivated crops (a 

minimum of 52 and 53 percent, respectively), and grassland 

(4.1 and 12 percent, respectively; table 2). The Banner watershed had minimal cultivated crops (2.9 percent), and primarily 

consisted of grassland (63 percent, table 2). 

Among watersheds with substantial cropland (Atchison 

and Centralia), management practices were implemented 

on most of the cultivated land. Soybeans and corn were the 

primary crops grown during the survey period and most of 

these were farmed using reduced or no-till farming techniques 

(87 percent of Atchison and 70 percent of Centralia; table 2). 

Terraces also were implemented on most of the fields in these 

watersheds (86 percent of Atchison and 96 percent of Centralia; table 2). Tile drains were more extensively used for drainage at Atchison (41 percent) than Centralia (22 percent). 

The USGS National Land Cover Database (2001) was 

used to characterize recent historical land use types among 

watersheds upstream from streamgages and sedimentsampling stations (table 3; fig. 1). Land uses were aggregated 

from 14 into a subset of 7 classes (open water, urban/barren 

land, forest, grassland/shrubland, pasture/hay, cultivated 

crops, and wetlands/streams; table 3). Land use was similar to 

data collected by current (2009) on-site surveys. Watersheds 

upstream from Atchison County and Centralia Lakes consisted 

predominantly of cultivated crops (53.5 and 56.2 percent, 

respectively), and secondarily pasture and grassland (34.4 and 

32.3 percent, respectively; table 3). The watershed upstream 

from Banner Creek Lake had minimal cultivated crops 

(3.9 percent) and primarily consisted of pasture (69.4 percent; 

table 3). 

The Atchison, Banner, and Centralia watersheds are 

located in the Dissected Till Plains section of the central 

lowland province of the interior plains. Soils in each watershed were formed from parent material consisting of limestone and shale, glacial till, loess, and alluvium. Upstream 

from each impoundment, soils generally are deep, moderately 
Introduction 

5

Clear

 Creek

 Lake LDMD 17

LDMD 5

KANSAS

A B C

95°53' 95°54' 95°45' 95°46' 95°47' 95°48' 95°49' 95°50' 95°51' 95°52'

39°28'39°27'39°26'39°25'39°24'

96°06' 96°05' 96°04' 96°03' 96°07' 96°08' 96°09' 96°10' 96°11' 96°12' 96°13'

39°43'39°42'39°41'39°40'39°39'

95°23' 95°24' 95°25' 95°26' 95°27' 95°28'

39°40'39°39'39°38'

95°25'

39°39'39°38'

95°24'

EXPLANATION

Watershed boundaryImpoundment with construction year (YR) and maximum storage (MS) area of pool in acre-feet (U.S. Army Corps of Engineers, National Inventory of Dams, 2011)U.S. Geological Survey streamgage,

 continuous water-quality monitoring

site, sampling site, and identifier

South inflow

LDMD, Little Delaware Mission Dam

Atchison County Lake Atchison County Lake

 near Horton, Kansas 

Clear Creek at Decatur Rd.

 near Horton, Kansas 

Clear Creek at Decatur Rd.

Banner Creek at M Rd.near Holton, Kansas

Banner Creek Lake

near Holton, Kansas

Black Vermillion River tributary

above Centralia Lake, Kansas

Centralia Lake near

Centralia, Kansas

Black Vermillion River tributary

below Centralia Lake, Kansas

Black Vermillion River tributary

above Centralia Lake, Kansas

Centralia Lake near

Centralia, Kansas

Black Vermillion River tributary

below Centralia Lake, Kansas

Outflow

Inflow

Outflow

South inflow

North inflow North inflow

South inflow

Outflow

Inflow

Outflow

North inflow

South inflow

Outflow

Inflow

Outflow

North inflow

South inflow

Outflow

Inflow

Outflow

A

C

B

D

YR: 1967MS: 120

YR: 1967

MS: 200

YR: 1967

MS: 200

YR: not listedMS: 34

YR: 2002MS: 209

YR: 1997MS: 22,976

YR: not listed

MS: 84

YR: 1971

MS: 27

YR: 1970

MS: 58

YR: 1997MS: 71

YR: 1987

MS: 232

YR: 1986MS: 240

YR: 1996MS: 172

YR: 2003MS: 201

YR: not listedMS: 27

YR: not listed

MS: 79

YR: 1935

MS: 1,134 YR: 1967

MS: 200

YR: 1967MS: 120

YR: 1967MS: 200

YR: 1991

MS: 11,187

YR: 1967MS: 120

YR: 1967

MS: 200

YR: 1967

MS: 200

YR: not listedMS: 34

YR: 2002MS: 209

YR: 1997MS: 22,976

YR: not listed

MS: 84

YR: 1971

MS: 27

YR: 1970

MS: 58

YR: 1997MS: 71

YR: 1987

MS: 232

YR: 1986MS: 240

YR: 1996MS: 172

YR: 2003MS: 201

YR: not listedMS: 27

YR: not listed

MS: 79

YR: 1935

MS: 1,134 YR: 1967

MS: 200

YR: 1967MS: 120

YR: 1967MS: 200

YR: 1991

MS: 11,187

0 0.5 1 MILE 0.25 0.750 0.5 1 KILOMETER 0.25 0.75

0 1 2 MILES 0.5 1.50 1 2 KILOMETERS 0.5 1.5

0 1 2 MILES 0.5 1.5

0 1 2 KILOMETERS 0.5 1.5

0 1 2 KILOMETERS 0.5 1.5

0 1 2 MILES 0.5 1.5

Base from United States Department of AgricultureFarm Service Agency National Agriculture Imagery Program county mosaicSeptember 2010, 1-meter resolution

Figure 2. Location of streamgages, sediment-sampling sites, watershed boundaries, National Inventory of Dams (NID) listed impoundments at A, Centralia Lake, B, Banner 

Creek Lake, and C, Atchison County Lake, 2009 through 2011 overlaid over 2010 aerial imagery.
6 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

Table 2. Land use and sediment management practices upstream from sediment-sampling stations in northeast Kansas, obtained 

from on-site surveys, 2009.

[Data from Kansas State University, 2009; mi2, square miles]

Station name

Contributing 

drainage 

area 

(mi2

)

Percentage land use Percentage of cropland

CroplandGrassland Other Not 

assessed

Under 

reduced or 

no tillage

Terraced Tile 

drained

Clear Creek at Decator Rd. near Holton, Kansas 5.6 63 2.9 3.3 31 91 82 44

Atchison County Lake near Horton, Kansas 9.1 52 4.1 7.3 37 87 86 41

Banner Creek at M Rd. near Holton, Kansas 9.1 3.3 66 9.2 22 22 3 6

Banner Creek Lake near Holton, Kansas 19.1 2.9 63 12 22 18 60 19

Black Vermillion River tributary above 

Centralia Lake, Kansas

4.4 58 15 4.1 23 73 92 18

Black Vermillion River tributary below 

Centralia Lake, Kansas

12.6 53 12 16 20 70 96 22

well-drained, and of moderately slow permeability (Campbell 

and others, 1979; Sallee and Watts, 1984; Abel, 2005). Erosivity (K) factors of the predominant soil types upstream from 

each impoundment are described as moderately (K factor from 

0.2 to 0.4) to highly erosive (greater than 0.4) (Campbell and 

others, 1979; Sallee and Watts, 1984; Abel, 2005). 

Surface topography in the Atchison County and 

Centralia Lake watersheds are affected predominantly by 

glacial till (Kansas Data Access and Support Center, 2011), 

whereas approximately 28 percent of the topography upstream 

from Banner watershed is affected by limestone and shale 

formations (the rest is primarily affected by glacial till). Given 

the low permeability of surficial soils in all watersheds, most 

of the stormflow likely originates from overland, shallow subsurface, or tile-drained flow. Streams generally flow through 

glacial till; streambeds at sampling sites are primarily silt/clay, 

sand, cobble, and rock. 

Mean annual temperature and precipitation were similar 

among meteorological stations near monitored impoundments despite varied lengths and missing records. Mean 

annual temperature at Horton, Kansas (near Atchison watershed from 1893–2008, excluding 1903, 1931, and 2006, 

National Weather Service (NWS) site number 00143810) was 

53.6 degrees Fahrenheit (°F) and mean annual precipitation 

from 1893–2008 (excluding 2006) was 35.6 inches (in.). Mean 

annual temperature at Holton, Kansas (near Banner watershed, NWS site number 00143759) from 1954–2008 (excluding 1955, 1968, 1979, 1984, 1987, 1998–2000, and 2004) 

was 53.0 °F and mean annual precipitation from 1931–2008 

(excluding 1979, 1984–87, and 1990–2000) was 35.2 in. 

Table 3. Recent historical land use upstream from streamgages and sediment-sampling stations in northeast Kansas during March 

2009 through September 2011.

[Data from the U.S. Geological Survey National Landcover Database, Homer and others, 2004; mi2, square miles]

Station name

Contributing drainage area 

(mi2

)

Percentage land use

Open 

water

Urban/

barren land Forest Grassland/shrubland

Pasture/

hay

Cultivated 

crops

Wetlands/

streams

Clear Creek at Decator Rd. near Holton, Kansas 5.6 0.7 5.5 4.1 0.9 29.0 59.7 0.1

Atchison County Lake near Horton, Kansas 9.1 1.7 5.6 4.6 2.6 31.8 53.5 0.2

Banner Creek at M Rd. near Holton, Kansas 9.1 0.2 5.1 11.6 11.7 67.0 4.3 0.1

Banner Creek Lake near Holton, Kansas 19.1 4.8 4.1 10.0 7.8 69.4 3.9 0.0

Black Vermillion River tributary above 

Centralia Lake, Kansas

4.4 0.3 3.7 1.4 19.7 6.0 68.9 0.0

Black Vermillion River tributary below 

Centralia Lake, Kansas

12.6 5.5 4.1 1.9 27.3 5.0 56.2 0.0
Introduction 7

Mean annual temperature at Centralia, Kansas (near Centralia 

watershed, NWS site number 00141408) from 1933–2006 

was 53.6 °F and mean annual precipitation from 1931–2006 

(excluding 1979, 1984–87, and 1990–2000) was 33.8 in. 

(National Oceanic and Atmospheric Administration, 2012). 

Stream-channel elevation was estimated along the length 

of the longest stream-reach contributing to each impoundment 

to characterize potential differences in sediment transport 

capacity (fig. 3; Horizon Systems, 2010). Stream elevation 

was estimated by dividing the longest stream channel contributing to each impoundment into equidistant, 30-meter 

(m) segments and obtaining the elevation for each point from 

the USGS 30-m digital elevation model (DEM) for the study 

area (Horizon Systems, 2010). Small-scale elevation changes 

among elevation points are dependent on the underlying 

accuracy of small-scale elevation changes in the DEM. DEMs 

were estimated before the impoundment of Banner Creek 

and Centralia Lakes and thus elevation continues to decrease 

within these impoundments (fig. 3). Banner Creek was the 

longest stream and had approximately twice the elevation loss 

compared with the other streams (fig. 3). Mean channel slope 

(in percent) was calculated by subtracting the stream elevation 

(in feet) at a location 10 percent of the stream channel length 

upstream from the downstream sampling site location from 

0 1 2 3 4 5 6 7 8 9

Distance, in miles from headwater

1,000

1,050

1,100

1,150

1,200

1,250

1,300

1,350

1,400

Altitude, in feet above North American Datum of 1988

Most upstream lake elevation 

Most upstream lake elevation 

Most upstream lake elevation 

Longitudinal profile of stream—Triangle indicates elevation

 and location of upstream or downstream sampling site.

 Most upstream lake elevation from the National Agriculture

 Imagery Program (U.S. Department of Agriculture, 2008)

 Clear Creek (Atchison County Lake)

 Banner Creek (Banner Creek Lake)

 Black Vermillion River (Centralia Lake) 

EXPLANATION

Figure 3. Longitudinal profiles of streams upstream from study impoundments in northeast Kansas.
8 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

the stream elevation at a point 85 percent of the stream length 

upstream from the downstream sampling site location, and 

dividing the elevation difference by the stream length (in feet) 

between these two points. Banner Creek had the steepest channel (0.46-percent slope), Clear Creek (upstream from Atchison 

County Lake) had a 0.40-percent slope, and the Black Vermillion River tributary upstream from Centralia Lake had a 

0.31-percent slope (fig. 3).

Small impoundments (hereafter referred to as ‘ponds’) 

upstream from monitored impoundments were characterized 

by analysis of surface-water from satellite data from the 

National Hydrography Database (NHDPlus; Horizon 

Systems, 2010) and by analysis of data from the National 

Inventory of Dams (NID; U.S. Army Corps of Engineers, 

2011). NHDPlus data provide a more complete picture of the 

number, spatial extent, and total surface area of dams within 

these watersheds because NID data do not include all dams 

(especially smaller dams); however, NID data indicate when 

dams were completed and estimate upstream drainage area 

and impoundment volume (fig. 2). Smaller ponds identified 

in the NHDPlus do not have any information other than 

that there is surface water, and therefore these ponds may 

not be permanent on an annual basis. Because of this, the 

NHDPlus could underrepresent the total number of ponds 

because of some ponds being dry at the time of the survey. 

The Banner watershed had the largest number of smaller, 

non-NID listed ponds (166) and largest area (0.15 square 

miles (mi2) of surface water (aside from Banner Creek Lake; 

fig. 2) (NHDPlus, Horizon Systems, 2010). The watershed 

upstream from Banner Creek Lake also had the largest 

number of NID dams (11) and six were constructed in the 

past 25 years (three NID dams did not have information 

on the date of construction; fig. 2) (NID, U.S. Army Corps 

of Engineers, 2011). The seven dams with information on 

upstream watershed area indicated that they affected 2.5 mi2

of the Banner Creek Lake watershed drainage area (draining 

approximately 13 percent of the entire Banner Creek Lake 

watershed). The Atchison watershed had 18 separate surfacewater bodies (other than Atchison County Lake) with a 

surface-water area totaling 0.06 mi2 (NHDPlus, Horizon 

Systems, 2010). Of the four NID dams, three were built in 

1967 (the fourth dam did not have construction data). The 

four NID listed ponds upstream from Atchison County Lake 

affected 2.4 mi2 of the Atchison watershed drainage area 

(approximately 26 percent of the entire Atchison watershed). 

The Centralia Lake watershed had 87 separate surface-water 

bodies (none by NID), with a surface-water area totaling 

0.04 mi2 (NHDPlus, Horizon Systems, 2010).

Previous Studies

Few studies have been completed on sediment transport 

from agricultural areas in northeastern Kansas. Collins 

(1965) calculated average sediment yields as ranging from 

2,000 to 5,000 tons per square mile per year (tons/mi2/yr) 

in northeast Kansas, and characterized erosion hazards as 

primarily relating to sheet and gully erosion from croplands. 

The Kansas Department of Health and Environment (KDHE) 

collects water-quality data in Atchison County, Banner Creek, 

and Centralia Lakes to establish total maximum daily loads 

(TMDLs). KDHE has established TMDLs for eutrophication, 

nutrients, and pH for Centralia Lake, but currently (2011) 

has not established TMDLs for Atchison County or Banner 

Creek Lakes. Banner Creek previously had a TMDL for 

eutrophication that was removed after observed chlorophyll 

levels decreased after best management practices were 

implemented from 1997 through 2007 (U.S. Environmental 

Protection Agency, 2009). 

Many studies have been completed that provide precedent for approaches used in this study. Christensen and others 

(2001), Putnam and Pope (2003), Rasmussen and others 

(2005, 2009), Lee and others (2008a, b), and Lee and Ziegler 

(2010a, b) have indicated that relations between continuous 

turbidity and discreet samples provide accurate computations 

of suspended-sediment concentrations, and combined with 

continuous streamflow data provide accurate estimations of 

loads and yields in Kansas streams. 

Methods

Data Collection and Analysis

Sampling sites were installed upstream from and in, 

or directly downstream from, study impoundments during 

March 2009. YSI (YSI Inc.) water quality monitors equipped 

with specific conductance, water temperature, and model 

6136 turbidity sensors were installed at each site and were 

housed in polyvinyl chloride (PVC) pipes with holes drilled 

to facilitate flow through the installation. Monitors were 

installed at the stream or impoundment edge, approximately 

0–2 ft above the stream or lakebed. Site locations upstream 

from study impoundments were selected to represent sediment transport from the largest sub-watershed contributing to 

each impoundment while accounting for site suitability and 

attempting to avoid backwater conditions. Data were collected every 15 minutes from March 2009 to September 2011; 

these data are available on the USGS Kansas Water Science 

Center Web page (http://nrtwq.usgs.gov/ks/). Monitor maintenance and data reporting generally followed procedures 

described in Wagner and others (2006) with the exception of 

increased length between calibration checks (approximately 

2–3 months), monitor cleanings were performed approximately every 6 weeks, or as needed. Length between calibration checks was extended beyond the recommended monthly 

frequency because of the absence of pH and dissolved 

oxygen sensors, which are prone to calibration drift. Turbidity records generally were rated good (error of 5–10 percent) 
Methods 9

and occasionally fair (error of 10–15 percent) on the basis of 

guidelines developed by Wagner and others (2006).

USGS-approved stage sensors were installed to measure 

water level (gage height in streams and elevation above 

mean sea level (M.S.L.) in lakes) using methods described 

in Sauer and Turnipseed (2010). Streamflow was measured 

and calculated using methods described in Rantz (1982), 

Turnipseed and Sauer (2010), Kennedy (1983), and Oberg 

and others (2005). Rating curves comparing gage height and 

streamflow were developed using streamflow measurements 

and the slope-conveyance method (Kennedy, 1984). 

Suspended-sediment samples were collected using 

methods described in Gray and others (2008) and Nolan and 

others (2005). Samples were analyzed for suspended-sediment 

concentration (SSC), percentage of sediments less than 

63 micrometers (μm) (sand-fine break), and loss of material 

on ignition (analogous to amount of organic matter). Selected 

samples also were analyzed for grain-size distribution (percent of sediment less than 2, 4, 8, 16, and 31 μm in diameter). 

Samples were analyzed at the USGS Sediment Laboratory in 

Iowa City, Iowa, using methods described by Guy (1969). 

Quality Assurance

Turbidity values were measured across the width of the 

stream or adjacent to the impoundment monitoring site during 

the collection of suspended-sediment samples. Mean values 

of cross-sectional measurements of turbidity are compared 

with fixed in-place turbidity sensors and analyzed by linear 

regression (Rasmussen and others, 2009) to confirm the ability of the in-place sensor to accurately represent the turbidity through the stream cross-section or lake discharge. Five 

samples were removed prior to making these comparisons 

because of errors identified in turbidity or suspended sediment 

values. At sites with more than 100 Formazin Nephelometric Units (FNU) range in values, in-place turbidity sensors 

accurately represented mean cross-sectional values. In-place 

sensors represented between 94 and 96 percent of the variability, and had slopes between .85 and 1 at Clear Creek at 

Decator Rd. (upstream from Atchison County Lake), Banner 

Creek at M Rd., Black Vermillion River above Centralia Lake, 

and Atchison County Lake (fig. 4). Variability at higher flows 

was likely caused by extreme temporal variability in turbidity 

during high flow conditions. The comparisons described 76 to 

96 percent of the variance. At Banner Creek Lake and Black 

Vermillion River below Centralia Lake, relatively small ranges 

in turbidity values increased variability among in-stream and 

cross-sectional median values. Measurements that plotted 

outside of a 1:1 fit likely were caused by localized differences 

in turbidity or instrument error. Specifically, Clear Creek at 

Decatur Rd. (upstream from Atchison County Lake), Atchison 

County Lake, and Banner Creek at M Rd. compared well, 

with slopes between 0.91 and 1.00. Banner Creek Lake had 

the smallest range of turbidity values, and consequently had 

a larger variance in the comparison between sensors (slope of 

1.17), which also was a result of the range of measured values 

that are at the low end of the sensor detection limit. At this 

low range, the difference can be explained in part because of 

calibration differences between instruments, and minor disturbances to the surrounding lake bed or monitor housing that 

could easily stir up enough material to cause a few turbidity 

units difference in recorded values. Turbidity values measured 

at Black Vermillion River above Centralia Lake indicated 

good agreement except for three samples in the upper range 

causing slope to decrease to 0.85. In each of the three cases 

the in-place monitor was higher than the field sonde used to 

sample, and could have been caused by sediment filling in the 

sonde housing (which was a common occurrence after storms 

at that site). Because consistent bias was not observed, with 

the exception of noted outliers, values from continuous-water 

quality monitors were considered representative of stream or 

impoundment-outflow water quality conditions. 

One set of double-blind samples (a total of 10 individual 

samples) were prepared and sent in to the Iowa sediment 

lab to assess the quality of the lab. Double-blind sample 

results were less than 6 percent error for 7 out of 10 of the 

samples. Samples prepared at 10 milligrams per liter (mg/L) 

were returned at 15 mg/L (all fines) and 17 mg/L (50 percent 

fines, 50 percent sand). One high SSC sample, 5,000 mg/L 

(50 percent fines, 50 percent sand) came back with a result 

of 2,507 mg/L; however, the lab sample sheet indicates a 

value transcription error. No other separate quality assurance 

samples were taken because of the large number of samples 

being taken over the study period, and the lack of variability 

typically seen in studies of this type (Lee and others, 2008a, 

2008b; Lee and Ziegler, 2010a, 2010b; Juracek, 2011). 

Numerous redundant samples were collected at similar 

turbidity values and flows (figs. 5 and 6). 

Regression Models

Ordinary-least squares regression was used to compute 

continuous, 15-minute estimates of SSC from in-stream 

turbidity measurements using methods described in 

Rasmussen and others (2009). SSC, turbidity, and discharge 

relations were evaluated at each site using single (SLR) 

and multiple (MLR) linear regressions for normal and logtransformed data (table 4; fig. 5). Samples collected during 

low (less than 0.5 cubic feet per second (ft3/s)) streamflow, or 

when turbidity was less than 2 NTU, were not used because of 

inherent error associated with those low readings (resolution is 

0.1 NTU), and accuracy is ±2 percent of reading or 0.3 NTU, 

whichever is greater; (YSI Incorporated, 2010), including 

5 samples from Clear Creek (upstream from Atchison Lake), 

4 from Banner Creek, 2 from Banner Lake, and 3 each from 

Black Vermillion above and below Centralia Lake. Statistics 

were evaluated for each of the resulting models from each site 

using guidelines described by Rasmussen and others (2009) 

and final models were selected based on the most statistically 

accurate model. A single outlying sample was removed at 
10 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

Clear Creek at Decatur Road

(upstream from Atchison County Lake)

y = 1.00x

R2 = 0.94

0

100

200

300

400

500

600

0 100 200 300 400 500 600

1:1 Line

Regression Fit

Atchison County Lake

y = 0.95x

R2 = 0.96

0

50

100

150

200

250

300

350

400

0 50 100 150 200 250 300 350 400

Banner Creek at M Road

y = 0.91x

R2 = 0.97

0

100

200

300

400

500

600

700

800

900

1,000

0 200 400 600 800 1,000

Banner Creek Lake

y = 1.17x

R2 = 0.76

0

5

10

15

20

25

30

0 5 10 15 20 25 30

Black Vermillion River above Centralia Lake

y = 0.85x

R2 = 0.91

0

100

200

300

400

500

600

700

800

900

1,000

0 200 400 600 800 1,000

In-stream turbidity, in formazin nephelometric units (FNUS)

Black Vermillion River below Centralia Lake

y = 0.97x

R2 = 0.93

0

5

10

15

20

25

30

0 5 10 15 20 25 30

EXPLANATION

Mean cross-sectional turbidity, in formazin nephelometric units (FNU)

study sites during March 2009 through September 2011.

Figure 4. Relation between cross-sectional mean (or independent reading in the case of the lakes) and in-place turbidity readings at 
Methods 11

Regression fit

90-percent prediction

interval

EXPLANATION

Removed outlier

Atchison County Lake

log(SSC) = 1.00log(Turb) + 0.04

R2 = 0.94

n = 24

Bias correction factor (Duan, 1983) = 1.02

Root mean square error = 0.087 (log units)

10

100

1,000

10 100 1,000

Suspended-sediment concentration,

in milligrams per liter

Turbidity, in formazin nephelometric units

Banner Creek Lake

log(SSC) = 0.87log(Turb) + 0.31

R2 = 0.47

n = 18

Bias correction factor (Duan, 1983) = 1.18

Root mean square error = 0.270 (log units)

1

10

100

1 10 100

Suspended-sediment concentration,

in milligrams per liter 

Black Vermillion River below Centralia Lake

log(SSC) = 0.535log(Turb) + 0.86

R2 = 0.70

n = 10

Bias correction factor (Duan, 1983) = 1.04

Root mean square error = 0.148 (log units)

0

1

10

100

1,000

1 10 100 1,000

Banner Creek at M Road

log(SSC) = 1.05log(Turb) + 0.18

R2 = 0.94

n = 21

Bias correction factor (Duan, 1983) = 1.04

Root mean square error = 0.123 (log units)

10

100

1,000

10,000

10 100 1,000 10,000

Suspended-sediment concentration,

in milligrams per liter 

Black Vermillion River above Centralia Lake

log(SSC) = 1.04log(Turb) + 0.33

R2 = 0.92

n = 19

Bias correction factor (Duan, 1983) = 1.05

Root mean square error = 0.141 (log units)

10

100

1,000

10,000

10 100 1,000 10,000

Regression fit slope

y = 0.99x

R2 = 0.97

0

100

200

300

400

500

600

700

800

900

1,000

0 200 400 600 800 1,000

Measured suspended-sediment concentration,

in milligrams per liter

Clear Creek at Decatur Road

(upstream from Atchison County Lake)

SSC = 1.26(Turb) + 1.14(Q) -2.29

R2

= 0.97

n = 17

Model-estimated suspended-sediment

Root mean square error = 40.46

concentration, in milligrams per liter 

Turbidity, in formazin nephelometric units Turbidity, in formazin nephelometric units

Suspended-sediment concentration,

in milligrams per liter 

Suspended-sediment concentration,

in milligrams per liter 

Turbidity, in formazin nephelometric units Turbidity, in formazin nephelometric units

Figure 5. Comparison of measured and model-estimated suspended-sediment concentrations for the multiple linear regression 

at Clear Creek at Decatur Rd. (upstream from Atchison County Lake), and single linear regression relations between turbidity and 

suspended-sediment concentrations with removed outliers in red for other sediment sampling sites during March 2009 through 

September 2011.
12 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

Regression fit

90-percent prediction

interval

EXPLANATION

Removed outlier

Streamflow (Q), in cubic feet per second

Streamflow (Q), in cubic feet per second

0.1 1 10 100 1,000

0.1 1 10 100 1,000

0.1 1 10 100 1,000

1 10 100 1,000

0.1 1 10 100 1,000

Suspended-sediment concentration (SSC), in milligrams per liter 

0.1

1

10

100

1,000

1

10

100

1,000

10,000

0.1

1

10

100

10

100

1,000

10,000

1

10

100

1,000

10,000

100,000

0.1

log(SSC) = 0.547log(Q) + 1.50

R2 = 0.92

n = 17

Bias correction factor (Duan, 1983) = 1.04

Root mean square error = 0.128 (log units)

log(SSC) = 0.061log(Q) + 0.96

R2 = 0.014

n = 18

Bias correction factor (Duan, 1983) = 1.35

Root mean square error = 0.367 (log units)

log(SSC) = 0.713log(Q) + 1.74

R2 = 0.66

n = 21

Bias correction factor (Duan, 1983) = 1.20

Root mean square error = 0.284 (log units)

log(SSC) = 0.522log(Q) + 2.17

R2 = 0.64

n = 19

Bias correction factor (Duan, 1983) = 1.25

Root mean square error = 0.309 (log units)

Banner Creek Lake Black Vermillion River above Centralia Lake

Black Vermillion River below Centralia Lake

Banner Creek at M Road

Clear Creek at Decatur Road

(upstream from Atchison County Lake)

log(SSC) = 0.213log(Q) + 1.28

R2 = 0.40

n = 10

Bias correction factor (Duan, 1983) = 1.10

Root mean square error = 0.210 (log units)

Figure 6. Relations between discharge and suspended-sediment concentration at study sites with removed outliers in red (if removed 

from turbidity models, also removed from streamflow models) during March 2009 through September 2011.
Methods 13

Table 4. Regression models and summary statistics for suspended-sediment concentration computations at study sites during March 2009 through September 2011.[R2, coefficient of determination; RMSE, root mean square error; MSPE, model standard percentage error; n, number of discrete samples; Turb, turbidity in Formazin Nephelometric Units (FNU); Q, streamflow in cubic feet per second; log, log10; LOADEST, S-Plus Load Estimator]

Regression model R2 R2 ad- justed RMSE Upper MSPE Lower MSPE Bias correction factor (Duan, 1983)

Discrete data

n Range of values in variable measurements Mean Median Standard deviation

Clear Creek at Decatur Rd. (upstream from Atchison County Lake)

SSC = 1.26(Turb) + 1.14(Q) – 2.29 0.97 0.97 40 13 -13 17 Turb: 8.7 – 480 182 170 123

Q: 0.9 – 243 77 71 70

log(SSC) = 0.547log(Q) + 1.50 0.92 0.91 0.13 34 -26 1.04 17 Q: 0.9 – 243 77 71 70*ln(SSC) = 1.171ln(Q) + 0.618ln(Turb) – 0.93 1.00 Turb: 8.7 – 480 182 170 123

Q: 0.9 – 243 77 71 70

*ln(SSC) = 1.557ln(Q) + 1.71 0.99 Q: 0.9 – 243 77 71 70

Atchison County Lake

log(SSC) = 1.00log(Turb) + 0.04 0.94 0.94 0.09 22 -18 1.02 24 Turb: 13 – 360 115 97 91

Banner Creek at M Rd.

log(SSC) = 1.05log(Turb) + 0.18 0.94 0.93 0.12 33 -25 1.04 21 Turb: 33 – 2,340 440 350 513log(SSC) = 0.713log(Q) + 1.74 0.66 0.64 0.28 92 -48 1.20 21 Q: 2.3 – 241 53 20 73*ln(SSC) = 1.173ln(Q) + 0.886ln(Turb) – 1.20 0.99 Turb: 33 – 2,340 440 350 513

Q: 2.3 – 241 53 20 73

*ln(SSC) = 1.703ln(Q) + 3.87 0.92 Q: 2.3 – 241 53 20 73

Banner Creek Lake

log(SSC) = 0.865log(Turb) + 0.31 0.47 0.43 0.27 86 -46 1.18 18 Turb: 2.5 – 26 8.3 5.4 6.5log(SSC) = 0.061log(Q) + 0.96 0.01 -0.05 0.37 133 -57 1.35 18 Q: 0.9 – 240 33 10 60

Black Vermillion River above Centralia Lake

log(SSC) = 1.04log(Turb) + 0.33 0.92 0.92 0.14 38 -28 1.05 19 Turb: 21 – 1,200 433 340 380log(SSC) = 0.522log(Q) + 2.17 0.64 0.62 0.31 104 -51 1.25 19 Q: 0.8 – 670 81 20 159*ln(SSC) = 1.143ln(Q) + 0.869ln(Turb) – 1.01 0.99 Turb: 21 – 1,200 433 340 380

Q: 0.8 – 670 81 20 159

*ln(SSC) = 1.530ln(Q) + 3.93 0.94 Q: 0.8 – 670 81 20 159

Black Vermillion River below Centralia Lake

log(SSC) = 0.54og(Turb) + 0.86 0.70 0.67 0.15 41 -29 1.04 10 Turb: 7.3 – 141 35 18 42log(SSC) = 0.213log(Q) + 1.28 0.40 0.33 0.21 62 -38 1.10 10 Q: 0.6 – 204 60 38 65

*LOADEST generated regression models.
14 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

Banner Creek at M Rd. and Black Vermillion River below 

Centralia Lake because of their large effect on overall slope, 

indicating an error in collection or analysis, although the 

specific issue was not readily apparent. After these outliers 

were removed from the first regression model assessed, no 

further samples were removed regardless of where on the 

regression line they plotted. 

Turbidity-SSC regressions were the primary method for 

computing the continuous SSC record; however, streamflowbased regressions also were developed for periods of variable flow in which turbidity sensors were not working. These 

methods are discussed in detail in the section titled “Estimating Sediment Transport During Periods of Missing Turbidity 

Data.” Regression relations using log-transformed data were 

retransformed back to a linear scale, which can cause bias 

when adding load estimates with time. To correct this, a biascorrection factor (Duan’s smearing estimator; Duan, 1983) 

was calculated to correct for potential bias (Helsel and Hirsch, 

2002). Uncertainty of regression estimates were determined 

by calculating 90-percent prediction intervals (Helsel and 

Hirsch, 2002) (fig. 5). The USGS LOADEST (Runkel and 

others, 2004) program was also used in order to evaluate the 

uncertainty of suspended-sediment load estimates, and is discussed in detail in the section titled “Computation of Sediment 

Concentrations, Trapping Efficiencies, Loads, and Yields.” 

Continuous suspended-sediment concentration and load computations, uncertainty, and duration curves are available on the 

World Wide Web at URL http://nrtqw.usgs.gov/ks/.

Similarities between regression equations at Atchison 

County Lake, Banner Creek at M Rd., and Black Vermillion 

River above Centralia Lake indicate similarities in sediment 

grain-size and color. Slopes in regression equations at Banner 

Creek Lake and Black Vermillion River below Centralia 

Lake were less than 1:1 (0.87 and 0.54, respectively) because 

of very low ranges of observed and measured turbidity and 

corresponding SSC values (table 4). Over the entire period 

of the study, turbidity ranged from 2.5 to 26 NTU at Banner 

Creek Lake, and 7.3 to 141 NTU at Black Vermillion River 

below Centralia Lake (table 4). Long residence times were 

expected at Banner Creek Lake and Centralia Lake (Centralia 

Lake outflow being gaged at the Black Vermillion River below 

Centralia Lake), allowing sediments carried in by the inflow 

streams to settle out in the impoundment before reaching the 

outflow structure (residence time is discussed in more detail 

in the section titled “Trapping Efficiencies”), which explains 

the limited range of recorded turbidity values. At these low 

turbidity ranges, sensor accuracy is less because the sensor 

values are easily affected by random suspended particles 

(such as small animals or algae) in the sensor’s detection 

zone. This has resulted in the poor coefficient of determination 

(R2) values in the regression models for both Banner Creek 

Lake and Black Vermillion River below Centralia Lake. 

In the case of Clear Creek at Decator Rd. (upstream from 

Atchison County Lake), a MLR was determined to be the 

most statistically valid model based on model standard 

percentage error (MSPE) as specified in Rasmussen and 

others (2009). MSPE is the root-mean-squared-error (RMSE, 

a measure of the variance between regression-computed and 

observed values) expressed as a percent, and represents the 

uncertainty associated with the regression-computed values 

(Rasmussen and others, 2009). The MLR model of SSC ≈ 

Turb, Q, indicated a MSPE of +13 to -13 percent, whereas 

the SLR model of log(SSC) ≈ log(Turb) (like that used in all 

other models) indicated a MSPE of +23.09 to -18.76 percent. 

Sediment loads computed using MLR and SLR models were 

similar, with the SLR model computing about 12 percent less 

sediment load during the study period than the MLR model. 

Because the MSPE of the MLR was the lowest, sediment 

loads from that model were used in the final computations.

Computation of Sediment Concentrations, 

Trapping Efficiencies, Loads, and Yields

The regression models were used to calculate continuous 

(15-minute) estimates of SSC at each sampling site. Timeseries (15-minute) discharge values (in ft3

/s) were multiplied 

by 15-minute computations of SSC and by a unit-conversion 

factor [× 1/1,000 mg/g (milligram per gram), × 1/453.6 g/lb 

(gram per pound), and × 28.32 L/ft3 (liter per cubic foot)] to 

compute time-series suspended-sediment discharge in pounds 

per second (lbs/s). Fifteen-minute sediment discharge computations were summed and multiplied by a unit conversion 

factor [× 900 seconds × 1 ton/2,000 lbs (pounds)] to compute 

sediment loads (in tons) for periods of interest. 

Sediment and streamflow yields were computed by dividing the total load (in tons) or total flow (in acre-ft) by drainage area (in mi2

). Streamflow yield was converted to depth 

of runoff (in inches) by a unit conversion factor [× 1 acre-ft/

mi2 × 43,560 ft3/acre × 1 mile/5,280 ft2 × 12 inches/1 ft], and 

represents the volume of water covering the entire watershed 

as depth. The trapping efficiency of each impoundment was 

calculated by subtracting the total sediment load transported 

from the impoundment from the estimated load transported 

into the impoundment and dividing by the estimated total 

sediment load transported into the impoundment, and then 

multiplying by 100. 

Suspended-sediment loads and yields were approximated 

for the ungaged drainage area upstream from each impoundment using data from existing monitoring sites. Sediment 

yields from upstream monitoring sites were multiplied by the 

entire impoundment drainage area to estimate total sediment 

transport to the impoundment for each time period of interest. 

These methods do not take into account heterogeneity in natural features, precipitation, and land practices across upstream 

watersheds, but provide an approximation of total streamflow 

and sediment transport to each impoundment. 

To better assess the uncertainty of computed sediment 

loads, sample data also were run through S-plus Load 

Estimator (LOADEST) software (Runkel and others, 2004). 

LOADEST primarily is designed for large watersheds (Runkel 

and Hippe, 2011), and does not allow user manipulations 
Methods 15

of software selected regression models. Each LOADEST 

model uses streamflow only, or a MLR with streamflow and 

turbidity (table 4). LOADEST also is limited in its ability to 

compute large amounts of unit value data, so a one hour timestep was used, which also was less than optimal considering 

the small size of the upstream watersheds. Watersheds, of 

the size in this study, typically have orders of magnitude 

differences in measured constituents over short periods and 

hysteretic responses of constituents to changing streamflows, 

and concentration peaks do not necessarily match peak 

streamflows (Runkel and Hippe, 2011), all of which make 

greater time resolutions inaccurate. Furthermore, flowonly models do not account for the hysteresis effect that is 

otherwise measured by turbidity sensors. Finally, there is no 

method to account for missing turbidity data in the LOADEST 

program. This makes LOADEST less optimal than methods 

described in this report based on Rasmussen and others 

(2009). Considering these factors, LOADEST-computed loads 

and associated confidence intervals should be considered less 

accurate than the primary method used, and only as another 

method to give a sense of the uncertainty inherent to sediment 

load computations.

Turbidity Truncation

Occasionally turbidity data were recorded above a sensor 

specific, maximum reporting limit, typically between 1,000 

to 1,500 FNUs, herein described as “turbidity truncation.” 

Turbidity truncation was observed at Banner Creek at M Rd. 

and Black Vermillion River above Centralia Lake. The actual 

peak sediment concentration was not estimated in final load 

computations, because truncation only occurred during small 

periods (table 5) and at two sites, Banner Creek at M Rd. 

and Black Vermillion River above Centralia Lake. Sediment 

loads were computed by interpolating slopes prior to and after 

truncated periods; this method increased annual sediment 

loads at Banner Creek at M Rd. from 5 to 7 percent, and Black 

Vermillion River above Centralia Lake from 0 to 2 percent; 

however because of the method of estimation, a large amount 

of uncertainty exists in these estimations, which led to their 

exclusion from final sediment load totals. 

Estimating Sediment Transport During Periods 

of Missing Turbidity Data

Two methods were used to estimate loads during periods 

of missing turbidity data (because of equipment malfunction or excessive fouling during storms caused by sediment 

build-up in the housing pipe). During periods of steady flow, 

turbidity data was estimated based on simple linear interpolation of turbidity between known values. When flow changed 

during periods of missing turbidity, streamflow models were 

used to compute SSC (table 4; fig. 6) using methods described 

in “Regression Models.” Normal and log-transformed 

regressions were evaluated, and picked based on statistical 

Table 5. Turbidity truncation at study sites during March 2009 

through September 2011.

Storm date Total time truncated

Banner Creek at M Rd.

3/9/2010 3 hours

3/24/2010 4 hours

4/23/2010 2 hours 45 minutes

5/25/2011 1 hour 45 minutes

6/2/2011 4 hours

Black Vermillion River above Centralia Lake

6/1/2009 1 hour

6/15/2009 3 hours

5/7/2010 1 hour

5/10/2010 1 hour 15 minutes

comparison. The same samples excluded from the turbiditybased regression models were excluded from the flow-based 

models.

Differences in computed SSC between turbidity-computed and discharge-computed methods sometimes produced 

different values of SSC because of differences in model equations (fig. 7). To “smooth” the transition of computed SSC 

values between methods, the discharge-based SSC was shifted 

to turbidity-computed SSC based on methods in Porterfield 

(1972) (fig. 7).

Turbidity was used to compute from 57 percent of the 

total loads (Black Vermillion River above Centralia Lake, 

2011) to 100 percent of total loads (Atchison County Lake, 

entire study) (fig. 8). A water year starts on October 1 and ends 

September 30, to roughly match the annual hydrologic cycle. 

From this point forward, water years will be designated as 

only the year, for example ‘water year 2009’ will be hereafter 

denoted as ‘2009.’ Turbidity sensors were operational from 

100 percent of the time at Atchison Lake throughout the study 

to 89 percent of the time at Black Vermillion River below 

Centralia Lake during 2010 (fig. 8). Because turbidity sensor 

fouling occurred during some high flow periods, large percentages of flow-only load totals were calculated at sites upstream 

from Banner and Centralia Lakes. 

SSC, computed by the two models covering the ranges 

of flows to which they were applied, indicate that at Clear 

Creek at Decatur Rd. (upstream from Atchison County Lake), 

discharge-computed SSC’s typically were less than turbiditycomputed SSC’s. At Banner Creek at M Rd., discharge-based 

SSC’s typically were less at discharges below 150 ft3

/s and 

above 450 ft3

/s. In-between these two ranges the variability is 

likely because of the lack of discharge-computed SSC’s being 

utilized, and therefore few periods with similar discharges 
16 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

0

2,000

4,000

6,000

8,000

10,000

12,000

Suspended sediment concentration, in milligrams per liter

Final computed suspended-sediment concentration

Shifted discharge-based suspended-sediment concentration

Original discharge-based suspended-sediment concentration

90-percent prediction intervals

Periods of missing turbidity data

Turbidity data temporarily returns

EXPLANATION

May 25, 2011 May 26, 2011 May 26, 2011

Figure 7. Example hydrograph from Black Vermillion River above Centralia Lake showing 

differences between discharge- and turbidity-computed models, shifting results (Porterfield, 

1972), and difference in prediction intervals between models during May 25–26, 2011.

All 2009 2010 2011 All 2009 2010 2011 All 2009 2010 2011 All 2009 2010 2011 All 2009 2010 2011 All 2009 2010 2011

100

90

80

70

60

50

40

30

20

10

0

Percent

Clear Creek at Decatur Rd.

(upstream from

Atchison County Lake)

Atchison County Lake Banner Creek at M Rd. Banner Creek Lake Black Vermillion River

above Centralia Lake

Black Vermillion River

below Centralia Lake

EXPLANATION

Percent of time flow-only regression model used

Percent of time turbidity-based regression model used

Percent of load computed by flow-only regression model

Percent of load computed by turbidity-based regression model

site during March 2009 through September 2011.

Figure 8. Percent of time each regression model was used and percent of total load computed by each model for each 
Methods 17

in those ranges were available for comparison. At Black 

Vermillion River above Centralia Lake, discharge-based SSC’s 

generally were less than turbidity-computed SSC’s from 

50 to 550 ft3

/s. Above 550 ft3/s, discharge-computed SSC’s 

had larger variability, but median values were somewhat 

higher than turbidity-computed SSC’s. Because of this, loads 

computed using the shifted discharge-based models are likely 

less than those that would have been computed if turbidity 

data were available, especially at higher flows when most 

sediment load is transported.

Collection, Analysis, and Computation of 

Sediment Loads at Selected Upstream Small 

Ponds 

Pond Locations and Descriptions

Sediment transport to and from two small (surface areas 

of approximately 0.013 mi2

) watershed ponds were studied to 

evaluate how these ponds affect sediment yields at upstream 

sediment sampling sites. Two small watershed ponds were 

selected upstream from Atchison County Lake watershed 

based on drainage area and land owner permission (fig. 2). The 

two sites selected (fig. 2; table 6) were Little Delaware Mission Dam 5 (LDMD 5) and Little Delaware Mission Dam 17 

(LDMD 17). LDMD 5 drains 0.78 mi2 and LDMD 17 drains 

0.77 mi2

. These two Atchison ponds drain 22 percent of the 

drainage area upstream from the USGS Clear Creek at Decator 

Rd. (upstream from Atchison Lake) site, which is 17 percent 

of the total watershed. 

LDMD 5 was constructed in 1967 and drains land used 

for pasture and row crops (fig. 2). During April through 

August 2011, soybeans and corn were planted in the surrounding fields, and livestock were frequently present. A grass buffer of at least 60 ft surrounded the pond. The outflow structure 

was a vertical corrugated steel pipe of 2.5 ft diameter with a 

top elevation of 1,109.80 ft above North American Vertical 

Datum of 1988 (NAVD 88).

LDMD 17 was constructed in 1967 and drains land used 

for row crops (fig. 2). During the period of study, the surrounding fields were planted (soybeans), and no livestock 

were observed near the pond. A grass buffer of 50 ft was 

planted at the beginning of the data collection period; no buffer existed before this. The grass buffer did not become fully 

established during the period studied. The outflow structure 

was a vertical corrugated steel pipe of 2.5 ft diameter with a 

top elevation of 1,110.39 ft above NAVD 88.

Spatial Analysis of Selected Ponds

The two pond sites were surveyed using a Trimble R8 

Global Navigation Satellite System (GNSS) survey-grade 

Global Positioning System (GPS) to obtain estimates of pond 

volume. A total of 370 points were surveyed for the LDMD 5 

site, whereas 294 points were surveyed for LDMD 17. Elevations were surveyed above the water level on the survey date; 

no bathymetric data were collected.

Table 6. Location and contributing drainage area of small pond gaging sites in the Atchison watershed, northeast Kansas during 

March 2009 through September 2011.

[mi2, square miles; LDMD, Little Delaware Mission Dam]

U.S. Geological 

Survey identification numberStation name

Contributing 

drainage 

area 

(mi2

)

Latitude 

(degrees, 

minutes, 

seconds)

Longitude 

degrees, 

minutes, 

seconds)

393847095242900 LDMD 5 Lake Inflow above Atchison Lake near Horton, Kansas1 0.68 39°38′47′′ 95°26′29′′

393851095244300 LDMD 5 Lake Outflow above Atchison Lake near Horton, Kansas1 0.78 39°38′51′′ 95°27′43′′

393851095244100 LDMD 5 Lake above Atchison Lake near Horton, Kansas2 0.78 39°38′51′′ 95°27′41′′

393803095243400 LDMD 17 Lake South Inflow above Atchison Lake near Horton, Kansas1 0.36 39°38′03′′ 95°24′34′′

393813095243300 LDMD 17 Lake North Inflow above Atchison Lake near Horton, Kansas1 0.32 39°38′13′′ 95°24′33′′

393809095244200 LDMD 17 Lake Outflow above Atchison Lake near Horton, Kansas1 0.77 39°38′09′′ 95°24′42′′

393809095244000 LDMD 17 Lake above Atchison Lake near Horton, Kansas2 0.77 39°38′09′′ 95°24′40′′

1

Site number used for lake water-quality monitor.

2

Site number used for continuous lake elevation.
18 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

Survey data (in feet) were imported into ArcGIS 

Geographic Information System (GIS) software (ESRI, 2011). 

These data were then converted to Triangulated Irregular 

Networks (TINs), which connect all survey points with 

triangular planes. Grids were then created at multiple specific 

elevations, and overlaid on the TIN to simulate various water 

surface elevations. The differences between the ground 

elevation and water level were then calculated using a “cut/

fill” operation, which yielded tables for elevation-area, raw 

elevation-volume, and elevation-volume above the outflow 

pipe opening. Raw volumes are defined by how ArcGIS 

interpolated the impoundment elevation during TIN creation, 

and can be inaccurate because of interpolations below the 

water surface, which was not surveyed. The raw volume data 

was subtracted from the outflow elevation-volume to produce 

volume above the outflow pipe. 

LDMD 5 survey data were not sufficient to cover the 

full range of expected impoundment elevations. Recent Light, 

Detection, and Ranging (lidar) data were available through the 

Kansas GIS website (www.kansasgis.org) and were used to fill 

in missing areas. The horizontal grid spacing of the lidar data 

was 1.4 m and vertical bare earth resolution of 1 m (Kansas 

Data Access and Support Center, 2011). The lidar data were 

converted to a TIN, then to an appropriately sized raster containing elevation data. Several ArcGIS tools (Spatial Analyst, 

3D Analyst; ESRI, 2011) were then employed to convert these 

into x-y-z point data. The new spatial-elevation data were 

appended to the original survey file.

Data Collection for Selected Small Ponds

To calculate pond trapping efficiency, it was necessary 

to compute a continuous record of incoming and outgoing 

streamflow and SSC. Impoundment elevation and turbidity 

were used to compute these parameters. Each pond was gaged 

for elevation near the outflow structure using Solinst “LevelLogger Gold” submersible pressure transducers. Fluctuations 

in elevation data caused by changes in atmospheric pressure 

were corrected by using a recording barometer Solinst “Barologger Gold” installed near the impoundments. The correction 

for atmospheric pressure was applied using Solinst software 

(Solinst, 2007). Elevation data were verified during each site 

visit using standard USGS stage measurement techniques 

(Sauer and Turnipseed, 2010). Turbidity data were collected 

using YSI 6136 turbidity sensors deployed near the outflow 

structure and near the impoundment inflow (in the case of 

LDMD 17, both inflows). 

To ensure the best resolution of data relative to the small 

watershed size, 5-minute recording intervals were used on 

all sensors. Site visits to clean sensors, verify impoundment 

elevations, and download data were made approximately 

every 2 weeks. Measurements of flow or SSC were not verified because of the rapid, high variability of the stormflow and 

driving distance to the sites. All computed discharges at the 

two ponds should be considered estimates.

Pond Data Analysis Techniques

Because each impoundment had a static outflow structure, only impoundment elevation and a corresponding stagestorage relation were needed to calculate flow into and out 

of each pond. Outflow was computed based on the hydraulic 

characteristics of the outflow structure and inflow was computed using a continuity routing equation (equation 1):

Inflow Storage

time Outflow Storagetime Outfl 2

2

2

1 2 2 = ∆

+ −

∆

+ 



 



 ow

Inflow Outflow

1

1 1 2





 





− +

(1)

Where inflow2 is the discharge in cubic feet per second (ft3/s) 

at time 2, storage2 is the volume in acre-feet (acre-ft) at time 

2 as determined by stage-volume tables, Δtime is the time difference between recording intervals in seconds (s), outflow2

 is 

the outflow discharge in cubic feet per second at time 2 based 

on outflow hydraulics, storage1 is the pond volume in acre-ft 

at time 1, outflow1 is the outflow discharge in cubic feet per 

second at time 1, and inflow1 is the inflow discharge in cubic 

feet per second as computed from the previous time-step.

Flow equations based on weir flow (Qweir) and orifice flow 

(Qorifice) were applied, depending on water elevation above 

the riser, to compute outflow discharge (equations 2, 3; U.S. 

Bureau of Reclamation, 1987). 

Q C dh weir = w

3

2 (2)

Q C d gh orifice c =  2

4

2 (3)

Where Cw is the graphically determined circular crest coefficient (U.S. Bureau of Reclamation, 1987), Cc

 is the coefficient 

of contraction (0.5 for a sharp crest), d is the pipe diameter 

in decimal-feet, h is the water elevation above the inlet in 

decimal-feet, g is gravity in feet per second squared (ft/s2), and 

both Q terms are in cubic feet per second. 

Anomalies caused by wave action are visible in the elevation record as large oscillations in stage that did not follow the 

general trend of the hydrograph. These anomalies in the stage 

data were deleted, and the missing data during periods without 

precipitation were estimated by simple linear interpolation. 

Also, pressure transducers are prone to a slight drift in time. 

To compensate for this, the pond elevation data were corrected 

based on field visit verification of elevation by applying an 

increasing or decreasing correction between known, fieldverified elevations. 
Characterization of Sediment Transport to and from Small Impoundments in Northeast Kansas 19

Initial computed inflows exhibited large, instantaneous 

increases and decreases in discharge because of the 0.02-ft 

resolution of impoundment elevation data, which was recorded 

at 0.01-ft intervals (±0.02 ft), and storage, and was estimated 

based on elevation-storage tables that ranged from 0.08 to 

0.21 acre-ft difference for 0.01-ft change in elevation. This 

oscillation was amplified during windy days that caused wave 

action, resulting in erratic impoundment elevation. A movingaverage smoothing function was applied to the elevation 

record to address these oscillations. 

SSC was computed using YSI 6136 turbidity sensor 

data and regression procedures outlined in Rasmussen and 

others (2009). The regression developed for Clear Creek at 

Decatur Rd. (upstream from Atchison County Lake) (table 4) 

was used for SSC calculations in the Atchison watershed, 

because Lee and Ziegler (2010b) indicated that turbiditySSC relations within the same watershed remain constant 

because of similarities in soil type in northeast Kansas. A 

possible source of error in this study is turbidity truncation. 

Turbidity truncation was observed at the LDMD 17 south 

inflow during several recorded storm events. The actual peak 

suspended-sediment concentration was not estimated in final 

load totals, because truncation only occurred during a small 

period (a total of 1 hour and 55 minutes during one 5-hour 

storm, 40 minutes during two other storm events, both which 

lasted approximately 1 hour and 15 minutes, both based on 

inflow hydrograph), and estimations based on interpolating 

slopes prior to and after truncated periods are prone to large 

uncertainty. These estimations increased loads roughly 3 to 

22 percent when truncated peaks were visual by hydrographic 

fitting. Because these estimates are qualitative, they are not 

included in final load computations; however, it is possible 

that incoming loads were approximately 10 percent higher 

than computed loads.

LDMD 17 had two inflow streams, hereinafter referred 

to as north fork (NF) and south fork (SF). Delineation of each 

inlet in GIS indicated NF drained 46.5 percent of the LDMD 

17 watershed, and the SF the other 53.5 percent. For inflow 

calculations, total inflow was split according to each inlet’s 

percentage of the total drainage area. During one storm, which 

affected LDMD 17 from May 31 to June 6, 2011, both inlets 

experienced long periods of missing turbidity data because 

of sensor malfunction or fouling at different times during the 

event. To account for the missing data, the missing data from 

one inflow tributary was set to be equal to the existing data 

from the other inflow tributary, and the subsequent computed loads were adjusted by percent drainage area. Because 

recorded turbidity values were not always equal during storms, 

if both sensors were operational, a large but unknown amount 

of error was inherent to this method of estimation during periods of missing turbidity data at LDMD 17.

Characterization of Sediment Transport 

to and from Small Impoundments in 

Northeast Kansas

Hydrologic Conditions

Precipitation

Annual precipitation data during 2009 at Atchison Lake 

and Banner Creek Lake watersheds and at all three watersheds 

in 2010 were larger than the mean annual precipitation as 

recorded by nearby meteorological stations (National Oceanic 

and Atmospheric Administration, 2012) over the stations’ 

period of record. The meteorological station operated by the 

National Weather Service (NWS) at Horton, Kansas (near the 

Atchison Lake watershed) recorded 43.2 in. during 2009 and 

47.7 in. during 2010, as compared to a long-term mean annual 

precipitation total of 35.6 in. (fig. 9). The meteorological station run by the NWS at Holton, Kansas (near the Banner Lake 

watershed) recorded 38.9 in. during 2009 and 41.6 in. during 

2010, as compared to a long-term mean annual precipitation 

total of 35.2 in. (fig. 9). The meteorological station run by the 

NWS at Baileyville, Kansas (near the Centralia Lake watershed, NWS site number 00140482, there was no precipitation 

gage at the Centralia 00141408 NWS station) did not record 

a complete record during 2009, but did record 35.8 in. during 

2010, as compared to a long-term mean annual precipitation 

total of 33.8 in. (fig. 9). Lower than average precipitation was 

recorded at Banner and Centralia watersheds by the NWS 

during 2011 with 27.4 in. at Holton (mean annual 35.2 in.) 

and 21.6 in. at Baileyville (mean annual 33.8 in.) (fig. 9). Only 

Atchison had slightly above average precipitation during 2011 

with 36.2 in. at Horton (mean annual 35.6 in.).

Streamflow

No historical data exist for the study sites to determine 

long term mean streamflows to compare to those observed 

during the study. Because data collection began in March 

2009, 2009 is based on only one-half of that year’s length, but 

it is still referred to as “2009” in this report. Because of this, 

calculated flow totals for 2009 are lower than when taken in 

comparison to the following complete years of data (fig. 10). 

Duration curves, which graphically represent the relation 

between the magnitude and frequency of streamflow during 

a period of time, were computed for March 2009 through 

September 22, 2011 (fig. 11). The lack of streamflow data 

during the lower flow, winter months in beginning of 2009 
20 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

35.6 in. 35.2 in. 33.8 in.

43.2 in.

47.7 in.

36.2 in.

38.9 in.

41.6 in.

27.4 in.

*23.9 in.

35.8 in.

21.6 in.

2009* 2010 2011 2009* 2010 2011 2009* 2010 2011

Year

Precipitation, in inches (in.)

60

50

40

30

20

10

0

Atchison County Lake watershed Banner Creek Lake watershed Centralia Lake watershed

NWS weather station at Horton, Kansas NWS weather station at Holton, Kansas NWS weather station at Baileyville, Kansas

NWS, National Weather Service EXPLANATION

Mean annual precipitation

Partial year reported, rough estimate for total year

 based on average differences between sites

*

Figure 9. Annual precipitation totals recorded by National Weather Service meteorological monitoring stations.

likely bias these durations toward high flows compared to 

normal conditions. The greatest streamflows were generally in 

2010 and the lowest in 2011, which corresponds with observed 

rainfall totals. The Centralia watershed was the exception 

because of several large storms in late May and early June 

2011 that produced 62 percent of that year’s flow.

Total flow into the lakes from March 2009 to September 

2011, including the estimated flow for the ungaged part of the 

watershed, was 15,000, 20,500, and 18,000 ac-ft for Atchison, 

Banner, and Centralia Lake watersheds, respectively (fig. 10). 

During that time 17,000, 18,000, 13,000 ac-ft of water was 

released from Atchison, Banner, and Centralia Lake, respectively. Lower outflow totals at Banner and Centralia compared 

to total inflows can be explained by evaporation, or seepage 

to groundwater. Evaporation and seepage losses from Banner Lake and Centralia Lake are likely a larger percentage of 

water loss than Atchison County Lake because Banner Lake 

and Centralia Lake are larger relative to upstream drainage 

area, and thus have longer residence times (residence time 

is the amount a given unit of water will remain in the lake). 

However, larger outflows than inflows from Atchison County 

Lake could be explained by a combination of increased rainfall and runoff from the ungaged part of the upstream watershed, and tile drains draining subsurface water into the lake 

downstream from the Clear Creek at Decator Rd. streamgage 

(fig. 10). 

Duration curves (fig. 11) for each upstream sample site 

indicate that the greatest streamflow at 99-percent exceedance was at Banner with 0.08 ft3

/s, as compared to Atchison 

and Centralia, which had 99-percent exceedance of 0.01 ft3

/s. 

This indicates that Banner, which was the largest watershed, 

had higher baseflow volumes during the period of the study, 

likely because of more contributions from groundwater. During the entire study period, frequencies of exceedance greater 

than 1 percent (approximately 9.3 days), accounted for 40, 

34, and 50 percent of the total flows during the period of the 

study for Atchison Lake, Banner Lake, and Centralia Lake 

watersheds, respectively. Distributions of 1-percent frequency 

of exceedance during each individual year (approximately 

2 days for partial 2009, approximately 3.6 days for 2010 and 

2011) for each watershed are 44, 32, and 44 percent for each 

year, respectively, at Atchison; 31, 27, and 41 percent for each 

year, respectively, at Banner; and 40, 41, and 66 percent for 
Characterization of Sediment Transport to and from Small Impoundments in Northeast Kansas 21

*Individual years may not sum to

 total due to rounding errors.

Inflow

 Estimated

 Recorded

Outflow

EXPLANATION

0

5,000

10,000

15,000

20,000

25,000

30,000

Total 2010 2011 2009 2010 Total 2009 2010

Atchison County Lake watershed

38-percent inflow estimated

Flow in acre-feet:

Total*: 15,000 ac-ft in, 17,000 ac-ft out

2009: 4,500 ac-ft in, 7,900 ac-ft out

2010: 7,000 ac-ft in, 13,000 ac-ft out

2011: 3,600 ac-ft in, 3,900 ac-ft out

Banner Creek Lake watershed

52-percent inflow estimated

Flow in acre-ft:

Total*: 20,500 ac-ft in, 18,000 ac-ft out

2009: 6,800 ac-ft in, 6,400 ac-ft out

2010: 10,600 ac-ft in, 9,800 ac-ft out

2011: 3,000 ac-ft in, 2,000 ac-ft out

Centralia Lake watershed

65-percent inflow estimated

Flow in acre-ft:

Total*: 18,000 ac-ft in,13,000 ac-ft out

2009: 3,300 ac-ft in, 3,100 ac-ft out

2010: 8,400 ac-ft in, 6,300 ac-ft out

2011: 6,300 ac-ft in, 3,600 ac-ft out

2009 Total 2011 2011

Total flow in acre-feet

Figure 10. Computed and estimated streamflow into and from each lake for study period during March 2009 through September 2011. 

each year, respectively, at Centralia. The more gradual rise of 

the duration curve between 10- to 1-percent exceedances at 

Clear Creek (upstream from Atchison County Lake) compared with the other two sites could be because of upstream 

impoundments and tile retaining storm-flows and releasing 

them at more steady rates than if the watershed was without 

the impoundments. 

Sediment Transport

Sediment samples collected at study sites indicated most 

of the suspended-sediments were comprised of silts and clays 

(table 7). Sediment transport into each of the three study 

watersheds during the study period, including the estimated 

ungaged parts, was 9,700; 23,000; and 35,700 tons at Atchison, Banner, and Centralia, respectively (fig. 12). Transport 

from study impoundments was 3,000 tons from Atchison, 

360 tons from Banner, and 780 tons from Centralia during 

the duration of the study. LOADEST-computed transport and 

95-percent confidence intervals for upstream gaging sites also 

are plotted on figure 12, and indicate greater sediment transport at Centralia compared with the other two watersheds.

To evaluate how sediment was transported, suspendedsediment duration curves were plotted for each upstream 

gaging site during the entire period of the study (fig. 13). 

Upstream from Atchison County, Banner Creek, and Centralia 

Lakes 73, 85, and 84 percent of the total load was transported 

during less than 1 percent (approximately 9 days) of the time 

(fig. 13). Upstream from Atchison County, Banner Creek, 

and Centralia Lakes 24, 38, and 32 percent of the total load 

was transported during less than 0.1 percent (approximately 

0.9 days) of the time (fig. 13). Ninety-three percent of total 

transport at less than 1-percent exceedance occurred at Centralia during 2011, which was the year with the least annual 

precipitation. This large load was because of strong storms 

from May 24 to June 19, 2011 (field personnel noted the fields 

recently were planted throughout the watershed), which transported 11,200 tons, or 71 percent, of the 15,700 tons of sediment total for the year (31 percent of the sediment transport 

computed during the entire study). The same storm system at 

Banner transported 3,060 tons of the 3,140 tons of sediment 

total for 2011, or 97 percent (13 percent of the sediment transport computed during the entire study). 
22 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

0 10 20 30 40 50 60 70 80 90 100

Frequency of exceedance, in percent

0.001

0.01

0.1

1

10

100

1,000

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

Streamflow at 90 percent:

 Clear Creek, 0.05 ft3/s

 Banner Creek, 0.4 ft3/s

 Black Vermillion River, 0.03 ft3/s

Streamflow at 99 percent:

 Clear Creek, 0.01 ft3/s

 Banner Creek, 0.08 ft3/s

 Black Vermillion River, 0.01 ft3/s

Streamflow at 95 percent:

 Clear Creek, 0.02 ft3/s

 Banner Creek, 0.2 ft3/s

 Black Vermillion River, 0.03 ft3/s

Streamflow at 75 percent:

 Clear Creek, 0.1 ft3/s

 Banner Creek, 0.8 ft3/s

 Black Vermillion River, 0.07 ft3/s

Streamflow at 50 percent:

 Clear Creek, 0.4 ft3/s

 Banner Creek, 1.4 ft3/s

 Black Vermillion River, 0.3 ft3/s

Streamflow at 25 percent:

 Clear Creek, 1.0 ft3/s

 Banner Creek, 3.6 ft3/s

 Black Vermillion River, 1.3 ft3/s

Streamflow at 5 percent:

 Clear Creek, 20 ft3/s

 Banner Creek, 14 ft3/s

 Black Vermillion River, 11 ft3/s

Streamflow at 10 percent:

 Clear Creek, 4.4 ft3/s

 Banner Creek, 7.5 ft3/s

 Black Vermillion River, 4.2 ft3/s

Streamflow at 1 percent:

 Clear Creek, 112 ft3/s

 Banner Creek, 88 ft3/s

 Black Vermillion River, 50 ft3/s

Streamflow duration curve, by stream

 Clear Creek at Decatur Rd. (above Atchison County Lake)

 Banner Creek at M Rd. (above Banner Creek Lake)

 Black Vermillion River (above Centralia Lake)

EXPLANATION

Figure 11. Streamflow duration curves for study sites upstream from lakes during March 2009 through September 2011.

Trapping Efficiencies

Trapping efficiencies for each of the three study lakes 

range from 72 percent at Atchison County Lake and 98 percent for Banner Creek and Centralia Lakes during the entire 

study (fig. 14). Trapping efficiencies remained at 98 percent 

or greater for Banner Creek and Centralia Lakes each year 

recorded. These lakes are large relative to watershed drainage 

area and because outlet discharge is small, sediment remains 

in the lake longer (longer residence time) and settles to the 

lake bottom. Flow through Banner Creek and Centralia Lakes 

was constrained by the outlet structure over the duration of the 

study. Flow at Atchison County Lake was primarily through 

a small outlet structure, but during high flow events flow was 

diverted over an emergency spillway, which greatly increased 

the outflow discharge. At the maximum observed lake volumes 

(Kansas Biological Survey, 2010a, b, c) with corresponding 

maximum computed outlet discharges, residence times were 

approximately 6 hours at Atchison, 14 days at Banner, and 

11 days at Centralia. Atchison County Lake, built in 1935, 

besides having been built with a smaller volume than Banner 

Creek and Centralia Lakes, has mostly silted in, resulting in 

a smaller volume and lower residence times as discussed in 

“Streamflow.” Trapping efficiencies at Atchison County Lake 

ranged from 64 to 84 percent for each year during the study 

period (fig. 14), with the greatest trapping efficiency during 

2011, which corresponds to the year with the lowest annual 

flow volume, and fewer high flow events that topped the emergency spillway.
Characterization of Sediment Transport to and from Small Impoundments in Northeast Kansas 23

Table 7. Suspended-sediment concentration and percent silt/clay (<63 micrometers diameter) from discrete samples collected from 

study sites during March 2009 through September 2011.

[mg/L, milligrams per liter; FNU, Formazin Nepholemetric Units; ft3/s, cubic foot per second; <, less than; μm, micrometer]

Sample 

date

Suspendedsediment 

concentration 

(mg/L)

In-situ 

turbidity 

(FNU)

Streamflow 

(ft3/s)

Percent 

silt/clay

<63 μm

Clear Creek near Decatur Rd. (upstream from Atchison County Lake)

3/24/2009 481 320 78 99

4/9/2009 28 10 0.86 78

4/10/2009 276 210 64 99

4/28/2009 314 250 51 99

6/11/2009 614 360 131 99

6/29/2009 50 37 0.13 98

8/10/2009 113 84 0.46 98

8/17/2009 941 480 243 99

8/17/2009 436 210 200 99

8/17/2009 380 180 123 99

8/17/2009 314 170 90 89

10/15/2009 50 9.5 0.1 63

10/22/2009 69 50 8.1 99

3/25/2010 168 110 14 98

4/23/2010 241 140 71 99

6/14/2010 192 130 30 97

9/1/2010 154 120 0.18 97

9/22/2010 269 170 84 99

11/3/2010 8 6.8 0.39 93

3/25/2011 27 8.7 0.91 93

5/26/2011 190 89 8.1 65

6/2/2011 424 200 120 97

Atchison County Lake

3/24/2009 262 280 168 99

4/9/2009 107 100 1.6 98

4/10/2009 152 120 122 98

4/28/2009 309 300 72 99

5/18/2009 210 230 7.3 100

6/11/2009 438 360 320 100

7/17/2009 120 97 4.6 99

8/10/2009 34 49 2.9 93

8/21/2009 124 120 7.4 99

10/15/2009 12 13 0.01 93

10/22/2009 22 22 0.01 97

3/25/2010 128 110 54 99

4/22/2010 107 69.5 0.75 99

4/23/2010 61 84.2 287 99

5/25/2010 64 54 3.4 98

6/14/2010 49 47 5.3 97

Sample 

date

Suspendedsediment 

concentration 

(mg/L)

In-situ 

turbidity 

(FNU)

Streamflow 

(ft3/s)

Percent 

silt/clay

<63 μm

Atchison County Lake—Continued

7/21/2010 86 76 4.3 98

9/1/2010 110 96 0.04 99

9/22/2010 182 170 202 100

11/3/2010 113 120 0.19 100

11/30/2010 83 53 2.2 99

3/25/2011 35 29 1.9 99

5/26/2011 99 70 20 99

6/2/2011 107 97 222 99

Banner Creek at M Rd.

3/17/2009 17 0.4 0.89 40

3/24/2009 705 390 32 97

4/10/2009 1,000 490 12 99

4/27/2009 798 400 165 99

4/30/2009 758 440 64 98

6/9/2009 490 320 6.4 99

6/15/2009 755 430 20 95

8/10/2009 99 14 1.4 79

8/17/2009 565 350 12 96

9/21/2009 73 33 2.3 55

10/15/2009 49 1.8 1.4 9

10/22/2009 173 140 8.9 96

10/22/2009 114 95 7.7 97

3/11/2010 114 69 17 93

3/24/2010 4,760 2,340 237 90

3/25/2010 289 110 25 94

4/22/2010 346 160 11 97

4/22/2010 595 260 37 95

4/23/2010 1,820 480 103 93

6/14/2010 226 94 18 94

9/1/2010 881 500 21 97

11/3/2010 4 0.4 1.2 68

3/24/2011 16 0.4 1.4 40

5/24/2011 241 130 6.8 99

5/25/2011 1,970 1,130 59 93

6/2/2011 3,020 880 241 74

Banner Creek Lake

3/17/2009 9 2.5 0.88 76

3/24/2009 30 20 21 96

4/10/2009 23 6.9 30 74
24 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

Table 7. Suspended-sediment concentration and percent silt/clay (<63 micrometers diameter) from discrete samples collected from 

study sites during March 2009 through September 2011.—Continued

[mg/L, milligrams per liter; FNU, Formazin Nepholemetric Units; ft3/s, cubic foot per second; <, less than; μm, micrometer]

Sample 

date

Suspendedsediment 

concentration 

(mg/L)

In-situ 

turbidity 

(FNU)

Streamflow 

(ft3

/s)

Percent 

silt/clay

<63 μm

Banner Creek Lake—Continued

4/28/2009 27 17 240 88

7/17/2009 2 3.8 7.7 40

8/11/2009 22 8.4 5.5 77

10/15/2009 6 7 <.01 84

3/25/2010 5 6.8 47 96

5/25/2010 15 5.3 25 96

6/14/2010 7 4.5 18 86

7/21/2010 4 5.2 5.9 86

9/1/2010 4 4.8 2.9 93

10/21/2010 10 8.9 2.2 87

11/3/2010 15 12 1.9 97

11/29/2010 43 26 1.1 81

1/25/2011 4 0.1 0.15 77

3/24/2011 5 4.2 12 95

5/24/2011 10 5.4 2.9 93

5/26/2011 8 3.9 39 96

6/2/2011 16 3.1 133 95

Black Vermillion River above Centralia Lake

3/17/2009 21 4.6 0.3 93

4/10/2009 1,090 460 23 99

4/27/2009 1,320 510 39 99

4/28/2009 210 96 7.6 98

4/30/2009 211 70 4.3 91

5/15/2009 85 21 1.5 73

6/2/2009 601 240 18 92

6/9/2009 2,320 1,020 24 98

7/14/2009 408 200 2.2 98

8/17/2009 1,030 370 45 98

Sample 

date

Suspendedsediment 

concentration 

(mg/L)

In-situ 

turbidity 

(FNU)

Streamflow 

(ft3

/s)

Percent 

silt/clay

<63 μm

Black Vermillion River above Centralia Lake—Continued

11/17/2009 173 110 18 99

3/11/2010 1,310 340 38 76

3/24/2010 5,060 1,200 210 96

3/24/2010 4,320 1,030 200 86

3/24/2010 2,250 600 202 85

3/25/2010 350 140 20 92

4/23/2010 313 140 13 99

9/1/2010 469 340 0.83 99

11/4/2010 40 3.3 0.05 100

3/24/2011 45 36 <0.01 90

5/25/2011 533 250 10 97

5/25/2011 2,530 1,090 670 95

Black Vermillion River below Centralia Lake

3/17/2009 45 29 0.4 93

4/27/2009 26 7.3 68 81

4/30/2009 63 8.5 38 92

5/15/2009 23 9.7 5 98

6/2/2009 27 14 28 79

7/14/2009 31 30 0.6 93

11/17/2009 19 20 7.5 96

3/11/2010 38 11 44 94

3/25/2010 43 16 72 93

6/17/2010 36 25 32 81

9/1/2010 47 37 0.48 99

11/4/2010 13 38 0.02 89

3/24/2011 21 5.3 0.1 99

5/26/2011 118 141 139 97

6/3/2011 93 74 204 99
Characterization of Sediment Transport to and from Small Impoundments in Northeast Kansas 25

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

Total load in tons

38-percent inflow estimated

Load in tons:

Total*: 9,700 tons in, 3,000 tons out

2009: 4,600 tons in, 1,700 tons out

2010: 3,300 tons in, 740 tons out

2011: 2,200 tons in, 360 tons out

52-percent inflow estimated

Load in tons:

Total*: 23,000 tons in, 360 tons out

2009: 9,600 tons in, 150 tons out

2010: 10,300 tons in, 180 tons out

2011: 3,100 tons in, 20 tons out

65-percent inflow estimated

Load in tons:

Total*: 35,700 tons in,780 tons out

2009: 8,300 tons in, 140 tons out

2010: 12,600 tons in, 290 tons out

2011: 15,700 tons in, 360 tons out

Total 2009 2010 2011 Total 2009 2010 2011 Total 2009 2010 2011

LOADEST computed loads

and 95 percent confidence

intervals on gaged portion

of the watershed

Atchison County Lake watershed Banner Creek Lake watershed Centralia Lake watershed

*Individual years may not sum to

 total due to rounding errors.

Inflow

 Estimated

 Recorded

Outflow

EXPLANATION

Figure 12. Computed and estimated sediment transport into and from each lake for study period during March 2009 through 

September 2011.

Sediment Yields

Total sediment yield at the upstream gage at Centralia 

(2,800 tons per square mile (tons/mi2

)) was about 2.7 times 

that computed at the Atchison (1,100 tons/mi2

) and Banner 

upstream gages (1,200 tons/mi2

) during the study period 

(fig. 15). Computed mean annual sediment yields 

(360 tons/mi2

/yr at Atchison, 400 tons/mi2/yr at Banner, and 

970 tons/mi2

/yr at Centralia) were less at all three watersheds 

than those estimated by Collins (1965), who estimated 

between 2,000 and 5,000 tons/mi2

/yr for this area of Kansas. 

The difference between the results in this study and those of 

Collins are likely a combination of the use of more accurate 

techniques in this study and the difference in scale between the 

studies, Collins examined and averaged much larger regions 

while this study examined small headwater watersheds. 

Streamflow yield did not vary substantially between the three 

watersheds during the same period (fig. 15), with the largest 

total streamflow yield computed at Atchison, 1,700 acre feet 

per square mile (acre-ft/mi2

), which equals a depth of runoff 

of 31.1 in. Although more water was transported per unit 

area at Atchison, which has similar land use to Centralia, 

less sediment was transported (per unit area) from Atchison 

than Centralia. Atchison yields were similar to Banner, which 

represented the reference grassland condition for the purposes 

of this study (Kansas Water Office, 2009). LOADEST was 

used to compute sediment transport and 95-percent confidence 

intervals, which are included on figure 15. The LOADEST 

sediment transport estimates indicate that suspended-sediment 

yields at Centralia are significantly larger (at 95 percent 

confidence) than the other two watersheds. Despite an 

incomplete understanding of all the factors affecting sediment 

yields in Atchison (no complete survey of tile drains, riparian 

areas, and channelization), these results indicated that a 

cultivated watershed can carry yields similar to those observed 

under the assumed reference (or natural) condition. 

Sediment transport at Banner may not represent a true 

reference condition if the streams were still adjusting to best 

management practices implemented from 1997 through 2007. 

These practices included 36 acres of agricultural land restored 
26 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

0 10 20 30 40 50 60 70 80 90 100

Frequency of exceedance, in percent

Suspended-sediment load, in pounds per second

0.0000001

0.000001

0.00001

0.0001

0.001

0.01

0.1

1

10

100

Percent of total suspended-sediment load

 at less than 0.1 percent:

 Clear Creek, 24 percent

 Banner Creek, 38 percent

 Black Vermillion River, 32 percent

Percent of total suspended-sediment load

 at less than 5 percent:

 Clear Creek, 97 percent

 Banner Creek, 98 percent

 Black Vermillion River, 98 percent

Percent of total suspended-sediment load

 at less than 25 percent:

 Clear Creek, 100 percent

 Banner Creek, 100 percent

 Black Vermillion River, 100 percent

Suspended-sediment load

 at less than 75 percent:

 Clear Creek, 100 percent

 Banner Creek, 100 percent

 Black Vermillion River, 100 percent

Suspended-sediment load

 at less than 95 percent:

 Clear Creek, 100 percent

 Banner Creek, 100 percent

 Black Vermillion River, 100 percent

Suspended-sediment load

 at less than 90 percent:

 Clear Creek, 100 percent

 Banner Creek, 100 percent

 Black Vermillion River, 100 percent

Suspended-sediment load

 at less than 99 percent:

 Clear Creek, 100 percent

 Banner Creek, 100 percent

 Black Vermillion River, 100 percent

Percent of total suspended-sediment load

 at less than 50 percent:

 Clear Creek, 100 percent

 Banner Creek, 100 percent

 Black Vermillion River, 100 percent

Percent of total suspended-sediment load

 at less than 10 percent:

 Clear Creek, 99 percent

 Banner Creek, 99 percent

 Black Vermillion River, 99 percent

Percent of total suspended-sediment load

 at less than 1 percent:

 Clear Creek, 73 percent

 Banner Creek, 85 percent

 Black Vermillion River, 84 percent

Suspended-sediment load duration curve, by stream

 Clear Creek at Decatur Rd. (above Atchison County Lake)

 Banner Creek at M Rd. (above Banner Creek Lake)

 Black Vermillion River (above Centralia Lake)

EXPLANATION

Figure 13. Suspended-sediment load duration curves for study sites upstream from lakes during March 2009 through 

September 2011.

to native grass, an unspecified number of acres of brome 

grassland reseeded, and a reduction in the number of cattle 

crossings (U.S. Environmental Protection Agency, 2009). All 

of these practices may decrease sediment yields; however, not 

enough data were collected during this or previous studies to 

confirm this. Streambank sediment erosion was determined to 

be the highest at Banner (0.45 tons/foot/year) by a 2010 survey 

led by The Watershed Institute (TWI) as compared to Atchison 

(0.26 tons/foot/year) and Centralia (0.05 tons/foot/year) (The 

Watershed Institute and Gulf South Research Corporation, 

2010). This streambank sediment erosion could be a factor 

in each watershed, under base-flow conditions, with Banner 

Creek having higher erosion and greater baseflow, resulting 

in greater low streamflow transport and causing an increase 

in subsequent estimated yields. Additionally, Juracek and 

Ziegler (2007) determined that channel-bank sources were the 

largest source of sediment to Banner Lake based on analysis 

of cesium-137 determined in sediment cores taken in the lake. 

Based on the high rates of erosion observed by TWI, and the 

corresponding information from Juracek, sediments in Banner 

Creek likely have a substantial streambank source.

Sediment loads extrapolated from streambank surveys 

varied widely in comparison to sediment loads computed at 

downstream USGS monitoring sites. Average streambank 

sediment erosion estimates computed by TWI (2010) were 

multiplied by the length of the main stem above the three 

upstream sampling sites, and then multiplied by the 3 years 

of the study. Because precipitation conditions during the 

period of study represent average conditions (fig. 9) mean 

annual estimates of streambank erosion should approximate 

conditions observed during the study period. Streambank 

contributions from the main stem of Banner Creek are three 
Characterization of Sediment Transport to and from Small Impoundments in Northeast Kansas 27

4,600 tons 

in

1,700 tons

out

2,200 tons 

in

360 tons

out

23,000 tons

in

360 tons

out

9,600 tons 

in

150 tons 

out

10,300 tons 

in

180 tons 

out 

3,100 tons 

in

20 tons 

out

35,700 tons

in

780 tons

out

8,300 tons 

in

140 tons 

out

12,600 tons 

in

290 tons 

out

15,700 tons 

in

360 tons 

out

Trapping

efficiency

72 percent 

Trapping

efficiency

64 percent 

Trapping

efficiency

78 percent 

Trapping

efficiency

84 percent 

Trapping

efficiency

98 percent 

Trapping

efficiency

98 percent 

Trapping

efficiency

98 percent 

Trapping

efficiency

99 percent 

Trapping

efficiency

98 percent 

Trapping

efficiency

98 percent 

Trapping

efficiency

98 percent 

Trapping

efficiency

98 percent 

* Individual years may not sum to total due to rounding errors

Total*

2009

2010

2011

Total*

2009

2010

2011

Total*

2009

2010

2011

Atchison County Lake Banner Creek Lake Centralia Lake

9,700 tons

in

2,800 tons

out

3,300 tons

in

740 tons

out

Figure 14. Total and mean annual trapping efficiencies and loads into and from each study lake during March 2009 through September 

2011.

times more than the sediment load observed at Banner Creek 

at M. Rd., 2.6 times more than the sediment load observed at 

Clear Creek at Decator Rd. (upstream from Atchison County 

Lake), and are 22 percent of the load computed at the Black 

Vermillion River above Centralia Lake. Substantially larger 

estimates of sediment contributions from only a portion of 

the streams in the Banner and Atchison County watersheds 

indicate that the extrapolation of average streambank-erosion 

rates from discrete, nonrandomized surveys can misrepresent 

the relative importance of streambanks when compiling 

sediment budgets. These survey-based estimations directly 

contradict the results found by the continuous monitoring and 

regression model methods used for this study, and indicate 

the best quantification methods are needed to determine the 

effectiveness of best management practices.

The larger sediment yield in 2011 at the Centralia Lake 

watershed, a year with lower precipitation, can be explained 

by a large storm that transported 890 tons/mi2

 during a 27-day 

period. This large storm occurred while fields were observed 

to be recently plowed throughout the watershed, which 

would have exposed and loosened field topsoils. Despite 

less streamflow in 2011, greater sediment loads indicate that 

not all storm events transport the same amount of sediment; 

larger, extreme storms during the spring may transport much 

larger sediment loads in small Kansas watersheds. Seasonal 

comparisons between fall and spring are problematic because 
28 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

0

1,000

2,000

3,000

4,000

5,000

Sediment yield in tons per square mile,

streamflow yield in acre-feet per square mile

Depth of Runoff (inches):

Total*: 31.1"

2009: 9.3"

2010: 14.4"

2011: 7.4"

Depth of Runoff (inches):

Total*: 20.1"

2009: 6.7"

2010: 10.4"

2011: 3.0"

Depth of Runoff (inches):

Total*: 26.6"

2009: 4.9"

2010: 12.5"

2011: 9.3"

Total 2009 2010 2011 Total 2009 2010 2011 Total 2009 2010 2011

Mean Annual Sediment 

Yield: 360 tons per square mile

Mean Annual Streamflow 

Yield: 550 acre-feet per square mile

LOADEST computed

yields and 95-percent

confidence intervals 

Atchison County Lake watershed Banner Creek Lake watershed Centralia Lake watershed

Mean Annual Sediment 

Yield: 400 tons per square mile

Mean Annual Streamflow 

Yield: 360 acre-feet per square mile

Mean Annual Sediment 

Yield: 970 tons per square mile

Mean Annual Streamflow 

Yield: 470 acre-feet per square mile

*Individual years may not sum to

total due to rounding errors.

Sediment yield—Turbidity model

Sediment yield—Flow model

Streamflow yield

EXPLANATION

Figure 15. Total and mean annual sediment yield and streamflow and corresponding depth of runoff for study period during March 

2009 through September 2011.

of the dry fall seasons observed during the study period; 

however, mean sediment yields and mean runoff depths during 

spring were 200 tons/mi2

 (4.8 in. runoff depth) at Atchison, 

260 tons/mi2 (3.7 in. runoff depth) at Banner, and 560 tons/mi2

(5.4 in. runoff depth) at Centralia, whereas mean fall sediment 

yields were 46 tons/mi2 (1.7 in. runoff depth) at Atchison, 

2 tons/mi2 (0.5 in. runoff depth) at Banner, and 10 tons/mi2

(0.5 in. runoff depth) at Centralia. These estimates do indicate 

greater yields during spring, which typically has greater 

precipitation and cultivation, as opposed to the post-harvest 

fall season, which has less rainfall and field topsoil that could 

be protected by leaf litter or are more compacted and less 

easily transported.

Stream channels in Centralia have been straightened 

(The Watershed Institute and Gulf South Research Corporation, 2010), which causes incision and increased transport 

because of channel adjustment resulting from increased 

stream velocities. Atchison County Lake and Banner Creek 

Lake watersheds had some vegetated riparian buffer along 

upstream banks (The Watershed Institute and Gulf South 

Research Corporation, 2010) which may increase the stability 

of streambanks, potentially decreasing downstream sediment 

transport (Sheridan and others, 1999, Zaimes and others, 

2004). The presence of more tile drains in Atchison as compared to Centralia, 41 and 22 percent, respectively (table 2), 

may decrease sediment yields, because tile drains have been 

indicated to decrease sediment erosion from fields (Istok & 

Kling, 1983; Food and Agricultural Policy Research Institute, 

2008). The difference in sediment yield between the Centralia 

Lake watershed and the other two study watersheds could 

also be related to increased channel adjustment, fewer riparian 

buffers, increased agricultural land use, and fewer upstream 

sub-impoundments relative to Banner Creek Lake watershed, 

and the potential for increased channel adjustment, fewer 

small upstream sub-impoundments, less tile drains, and less 

vegetated riparian buffers on upstream tributaries relative to 

Atchison County lake watershed (fig. 2; table 2). To quantify 

the effects of ponds on watershed sediment yields, streamflow 

and sediment transport were computed at two small NID 

listed ponds in the Atchison watershed during April through 

August 2011.
Characterization of Sediment Transport to and from Small Impoundments in Northeast Kansas 29

Effect of Ponds on Total Watershed Sediment 

Yield

Storms

Five storms occurred during the study period, which 

resulted in flow through the Atchison ponds. Rainfall depths 

for each storm were recorded at the NWS weather station at 

Horton, Kansas (table 8). For both ponds, outflow volumes 

were less than inflow volumes for all of these storms because 

some of the inflow remained stored in the ponds.

Little Delaware Mission Dam 5

Stormflow, sediment transport, yields, and trapping 

efficiency for LDMD 5 are indicated in table 8. Graphs of 

estimated discharge and SSC are indicated in figures 16A–E. 

Computed inflow discharges ranged from 18 to 99 ft3/s, and 

storm loads (“load in” on table 8) ranged from 0.5 to 9.7 tons. 

Trapping efficiencies, by storm, ranged from 68 percent during 

storm 1 to -0.1 percent (the negative implying resuspension 

of previously deposited sediment, as a result of the age of the 

ponds indicating they are mostly silted in) estimated during 

storm 3. Average trapping efficiency during the five observed 

storms was 23 percent.

Little Delaware Mission Dam 17

Stormflow, loads, yields, and trapping efficiency for 

LDMD 17 are indicated in table 8. Graphs of estimated 

discharge and SSC are indicated in figures 16F–J. Computed 

inflow discharges ranged from 33 to 148 ft3/s, and storm loads 

(“load in” on table 8) ranged from 6.5 to 43 tons. Trapping 

efficiencies, by storm, ranged from 69 percent during storm 1 

to -24 percent (the negative implying resuspension of previously deposited sediment, as a result of the age of the ponds 

indicating they are mostly silted in) estimated during storm 5. 

Average trapping efficiency during the five observed storms 

was 30 percent.

Table 8. Stormflows, sediment transport, trapping efficiencies, and sediment yields for study ponds Little Delaware Mission Dam 

(LDMD) 5 and LDMD 17 (rainfall totals recorded by National Weather Service Weather Station at Horton, Kansas) from April through 

August 2011.

[LDMD, Little Delaware Mission Dam; ft3/s, cubic foot per second; AF, acre-feet; %, percentage; tons/mi2, ton per square mile]

Storm Dates Precipitation 

(inches)

LDMD 5

Peak inflow 

(ft3/s)

Flow IN 

(AF)

Flow OUT 

(AF)

Load IN 

(tons)

Load OUT 

(tons)

Trapping 

efficiency 

(%)

Sediment 

yield 

(tons/mi2)

1 May 25 to May 26 2.3 38 13 7.8 3.8 1.2 68 4.8

2 May 31 to June 6 2.5 59 37 27 9.7 6.1 37 12

3 June 25 to June 29 2.5 84 42 32 8.5 8.6 -0.1 11

4 July 3 to July 5 0.3 18 7.0 2.6 0.5 0.3 27 0.6

5 July 7 to July 9 2.0 99 39 32 7.8 7.2 8 10

Totals 139* 101* 30* 23* 23* 39*

Average

Storm Dates

LDMD 17

Peak inflow 

(ft3/s)

Flow IN 

(AF)

Flow OUT 

(AF)

Load IN 

(tons)

Load OUT 

(tons)

Trapping 

efficiency 

(%)

Sediment 

yield 

(tons/mi2)

1 May 25 to May 26 39 28 16 12 3.6 69 15

2 May 31 to June 6 53 36 34 18 9.2 49 23

3 June 25 to June 29 85 51 47 43 25 42 56

4 July 3 to July 5 33 10 9.0 6.5 4.2 36 8.4

5 July 7 to July 9 148 57 56 24 30 -24 31

Totals 182* 161* 103* 72* 30* 134*

Average

*

Sum of individual columns might not match total due to rounding errors.
30 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011 Discharge, in cubic feet per second

0

40

80

120

160

0

40

80

120

160

0

40

80

120

160

0

40

80

120

160

0

40

80

120

160

0

500

1,000

1,500

2,000

2,500

0

500

1,000

1,500

2,000

2,500

0

500

1,000

1,500

2,000

2,500

0

500

1,000

1,500

2,000

2,500

0

500

1,000

1,500

2,000

2,500

Suspended-sediment concentration, in milligrams per liter

7/3/2011 7/4/2011

14:10 18:00 00:00 06:00 12:00 18:00 23:45

7/7/2011 7/8/2011

09:25 12:00 18:00 00:00 06:00 12:00 18:00 23:45

6/25/2011 6/26/2011 6/27/2011 6/28/2011

12:15 00:00 12:00 00:00 12:00 00:00 12:00 16:15

5/31/2011 6/1/2011 6/2/2011 6/3/2011

07:30 12:00 00:00 12:00 00:00 12:00 00:00 12:00 23:40

5/25/2011 5/26/2011

20:25 00:00 06:00 12:00 18:00 19:05

A. LDMD 5 storm 1

B. LDMD 5 storm 2

C. LDMD 5 storm 3

D. LDMD 5 storm 4

E. LDMD 5 storm 5

Discharge, in cubic feet per second

 Inflow

 Outflow

Suspended sediment,

 in milligrams per liter

 Inflow

 Outflow

EXPLANATION

LDMD, Little Delaware Mission Dam

Figure 16. Stormflow and suspended-sediment concentration hydrographs for Little Delaware Mission Dam (LDMD) 5 (A–E) and 

LDMD 17 (F–J) for each storm (rainfall totals recorded by National Weather Service (NWS) Weather Station at Horton, Kansas), April 

through August 2011.
Characterization of Sediment Transport to and from Small Impoundments in Northeast Kansas 31

Discharge, in cubic feet per second

0

40

80

120

160

0

40

80

120

160

0

40

80

120

160

0

40

80

120

160

0

40

80

120

160

0

500

1,000

1,500

2,000

2,500

0

500

1,000

1,500

2,000

2,500

0

500

1,000

1,500

2,000

2,500

0

500

1,000

1,500

2,000

2,500

0

500

1,000

1,500

2,000

2,500

Suspended sediment concentration, in milligrams per liter

7/7/2011 7/8/2011

09:35 12:00 18:00 00:00 06:00 12:00 16:40

5/25/2011 5/26/2011 5/27/2011

19:12 00:00 06:00 12:00 18:00 00:00

5/31/2011 6/1/2011 6/2/2011 6/3/2011 6/4/2011

07:1212:00 00:00 12:00 00:00 12:00 00:00 12:00 00:00 12:00 23:50

6/25/2011 6/26/2011 6/27/2011 6/28/2011 6/29/2011

11:15 00:00 12:00 00:00 12:00 00:00 12:00 00:00 14:30

7/3/2011 7/4/2011

14:05 18:00 00:00 06:00 12:00 18:00 23:50

F. LDMD 17 storm 1

G. LDMD 17 storm 2

H. LDMD 17 storm 3

I. LDMD 17 storm 4

J. LDMD 17 storm 5

Discharge, in cubic feet per second

 Inflow

 Outflow

Suspended sediment,

 in milligrams per liter

 North inflow

 South inflow

 Outflow

EXPLANATION

LDMD, Little Delaware Mission Dam

Figure 16. Stormflow and suspended-sediment concentration hydrographs for Little Delaware Mission Dam (LDMD) 5 (A–E) and 

LDMD 17 (F–J) for each storm (rainfall totals recorded by National Weather Service (NWS) Weather Station at Horton, Kansas), 

April through August 2011.—Continued
32 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

Comparison of Results Between Ponds

Inflow SSC was larger at LDMD 17 than those at LDMD 

5 (fig. 16). Initial storm sediment loads were typically high, 

and were followed by a more gradual increase in sediment 

outflows (fig. 16). Sediment inflows at LDMD 5 were much 

less than at LDMD 17 and subsequent sediment outflows were 

steady during the period of the storm (fig. 16). Sediment transport at LDMD 17 experienced more fluctuation (table 8) leaving the pond, and similar to much higher sediment loading into 

that site. Given similar channel slopes, land use, and management practices in both ponds, the presence of an established 

grass buffer at LDMD 5 may be the most important factor 

contributing to smaller sediment loads entering the pond.

Two factors may influence variation in sediment trapping among the 5 storms observed at LDMD 5 and 17. First, 

sediment trapping generally decreased through time at both 

sites, possibly indicating that sediments stayed suspended after 

storms only to be flushed out by subsequent storms. Second, 

sediment trapping efficiencies are smallest during the highest 

flow events, implying that sediments are transported through, 

or resuspended from these ponds. This second factor implies 

that during the largest storms (which previously were shown 

to transport the majority of sediments at primary study sites) 

small farm ponds may not serve as sinks for sediments transported from upstream fields.

Trapping efficiency decreased to a net loss of sediment at 

LDMD 17 over each individual storm event, the average trapping efficiency over all five storm events was 30 percent. Loss 

of trapping efficiency is expected as pond volume decreases 

due to sediment deposition; however, causes for this decrease 

were not readily apparent in the streamflow or turbidity data. 

Steady SSC at the outflow during storms (fig. 16), after the 

initial sediment inflow passed through, can be explained by 

resuspended sediment or algae growth, data errors, or some 

combination of these factors. One possible cause of the trapping efficiency decrease is that sediment flushed into the 

ponds from earlier storms stayed suspended, allowing it to be 

flushed with the initial inflow of the next storms flow. Short 

intervals occurred between storms 1 and 2, and storms 4 and 

5, and trapping efficiency decreases between these two events 

dropped considerably (table 8). 

Because this study only spanned 4 months and five 

storms, these results could indicate that during periods with 

low flows, such as winter, sediments may fall out or become 

compacted, and are thus less likely to stay suspended or 

be resuspended by subsequent flows. During periods when 

storm events are more closely spaced, trapping efficiency 

becomes less changed to almost unchanged. Because most 

of the suspended load was composed of silts and clays 

(94 percent average less than 63 micrometers, table 7), long 

suspension times can be expected. By Stokes law (Daugherty 

and Ingersoll, 1954), a computation of the settling rates 

of silts and clays range from 9.02 × 10-3 to 2.62 × 10-4 feet 

per second. Days of moderate to high winds would assist 

in maintaining suspension, and may cause resuspension of 

previously deposited sediments. The relatively short interval 

between the final two storms was likely a factor in the flushing 

of previously suspended sediments. In addition, negative and 

small sediment trapping efficiencies were estimated in each 

pond during storm 5, the largest storm in terms of peak and 

total flow at both sites. High flows may resuspend previously 

deposited sediments, and thus trapping efficiency of ponds of 

this age may remain unchanged (or even contribute sediments 

to downstream loads) during large storms.

Comparison of Pond Results to Flow and Loads 

at Clear Creek at Decatur Rd. (upstream from 

Atchison County Lake)

Although the studied farm ponds comprised 22 percent 

of the drainage upstream from the Clear Creek (upstream from 

Atchison County Lake) site, flow from these ponds during 

Table 9. Comparison of sediment loads between small study ponds Little Delaware Mission Dam (LDMD) 5 and LDMD 17, and Clear 

Creek at Decator Rd. (upstream from Atchison County Lake) during April through August 2011.

Load observed entering 

ponds 

(tons)

Load trapped in study 

ponds 

(tons)

Load passing Clear Creek 

gage 

(tons)

Percent of total load trapped 

(tons)

Storm 1 16 11 73 12

Storm 2 28 13 104 10

Storm 3 51 18 125 10

Storm 4 7.0 2.5 8.9 16

Storm 5 32 -5.3 105 -4

Totals 134* 38* 416* 8*

Percent of total load (trapped/

(load entered+load passed))

*

Sum of individual columns might not match total due to rounding errors.
Characterization of Sediment Transport to and from Small Impoundments in Northeast Kansas 33

0

200

400

600

800

1,000

1,200

Sediment load, in tons 

Sediment load 

Without ponds 

With ponds 

Observed and estimated load

at Clear Creek at Decatur Road

with and without sediment

trapped by LDMD 5 and 17

Results extrapolated over entire

Atchison Watershed, including

all four NID impoundments

EXPLANATION

Figure 17. Difference in sediment loads with and without the 

two small study ponds on total watershed sediment transport 

(during the five observed storms), and extrapolated during entire 

watershed and all four National Inventory of Dams listed ponds 

during April through August 2011.

the 5 storms comprised 28 percent of the flow observed at 

the Clear Creek (upstream from Atchison County Lake) site. 

Increased downstream flows may be because of uneven distribution of rainfall, agricultural diversions, tile drains draining 

groundwater, or stream losses to groundwater. 

For these five storm events, a total of 416 tons of 

sediment passed by the Clear Creek streamgage at Decatur 

Rd. (upstream from Atchison County Lake) (table 9). It is 

estimated that 38 tons of sediment were trapped in the two 

study ponds during the study period, amounting to 8 percent 

of the load upstream from the Clear Creek at Decatur Rd. 

(upstream from Atchison County Lake) gage during the five 

observed storm events. Sediment inflow during periods when 

the pond elevation was below the outflow structure was 

not estimated, and would increase the amount of sediment 

trapped (assuming all inflows carry some sediment). There 

are two more NID listed ponds in the Atchison watershed, and 

numerous non-listed smaller ponds likely trap sediment in the 

same manner as LDMD 5 and LDMD 17. By extrapolating 

these results to the other two NID listed impoundments in the 

Atchison watershed, which drain 26 percent of the watershed, 

about 9 percent of total watershed sediment loads (including 

the ungaged drainage area) could be retained by these 

impoundments (fig. 17). These results do not explain the large 

difference in yields between Atchison County Lake watershed 

and Centralia Lake watershed, implying that differences in 

factors, such as riparian buffers, stream channelization, or 

the extent of tile drains, may better explain differences in 

sediment loading.

Comparison of Sediment Loads and Yields to 

other Watersheds in Northeast Kansas

Comparison to Mill Creek Watershed, Johnson 

County, Kansas

Lee and Ziegler (2010a) characterized sediment transport 

from basins in the urban and urbanizing Mill Creek watershed 

in Johnson County, Kansas, from February 2006 through 

November 2008. Monitoring sites drained basins of similar 

size to headwater basins in this report, and streamflow and turbidity data were collected using similar methods. Land use in 

the watersheds in the Lee and Ziegler (2010a) study included 

urban watersheds with large percentages of impervious surface 

as well as or urbanizing watersheds with extensive construction and therefore, was much different than the watersheds 

described in this report. Urbanizing watersheds can have one 

hundred times the sediment loads of agricultural or undeveloped watersheds (Walling and Gregory, 1970). Although 

the Mill Creek sites were different in terms of location and 

precipitation conditions, insights into the relative role of agricultural land use compared with urban land use can be gained 

through comparison of similarly sized basins with similar silt 

and clay soils. 

Streamflow yields were larger throughout all Mill 

Creek sub-watersheds as compared with this study’s baseline 

watersheds and are attributed to larger rainfall during the 

study period and more impervious surfaces resulting in larger 

volumes of surface and shallow sub-surface flow during 

storm events (fig. 18). Sediment yields from the urbanizing 

Clear Creek at Clare Rd. site [390051094522200, not to be 

confused with the Clear Creek at Decatur Rd. site (upstream 

from Atchison County Lake)] were only slightly larger than 

those from the Black Vermillion River above Centralia Lake 

in the agricultural Centralia watershed, despite increased 

flow (fig. 18). This comparison indicates that at the small 

(5–10 mi2) watershed scales, small, primarily agricultural 

basins have the potential to export sediment at levels 

comparable to small urbanizing watersheds.

Sites downstream from established urban areas 

(385952094454000 Little Mill Creek at Lackman Rd. and 

385404094485800 Mill Creek at Woodland Rd.) had similar 

sediment yields in comparison to Clear Creek at Decatur Rd. 

(upstream from Atchison County Lake) and Banner Creek 

at M Rd. (Banner) (fig. 18) despite increased flow. Given 

that Banner represents “reference” grassland conditions, 

results indicate that among small, 5–10 mi2

 basins, sediment 

yields from stable urban areas can be similar to primarily 

grassland conditions.
34 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

Clear Creek at Decatur Rd. 

(upstream from Atchison County Lake)

Banner Creek Lake at M Road 

(upstream from Banner Lake)

Black Vermillion River 

above Centralia Lake

Clear Creek at Clare Rd.

Mill Creek at Woodland Rd.

Black Vermillion River 

near Frankfort

Little Mill Creek 

at Lackman Rd.

Little Blue River 

near Barnes

Big Blue River 

near Marysville

1,400

1,200

1,000

800

600

400

200

0

1,400

1,200

1,000

800

600

400

200

0

Sediment yield, in tons per square mile per year

Streamflow yield, in acre-feet per square mile

Drainage area

5.6 square miles

Drainage area

9.1 square miles

Drainage area

4.4 square miles

Drainage area

5.5 square miles

Drainage area

2.8 square miles

Drainage area

410 square miles

Drainage area

8.8 square miles

Drainage area

3,351 square miles

Drainage area

4,777 square miles

Mean annual sediment yield, in

tons per square mile 

Mean annual streamflow yield,

in acre-feet per square mile

EXPLANATION

March 2009 through September 2011 February 2006 through November 2008 October 2008 through September 2010

Baseline watersheds Mill Creek sub-watersheds Tuttle Creek Lake sub-watersheds

Figure 18. Comparison of mean annual sediment yield and streamflow yield with study watersheds and sub-watersheds in the Mill 

Creek Watershed, Johnson County, Kansas, and the Tuttle Creek lake watershed (Lee and others, 2010b; Juracek, 2011).

Comparison to Tuttle Creek Impoundment 

Watershed

Juracek (2011) monitored three sites within the Tuttle 

Creek Lake watershed from October 2008 through September 

2010 for streamflow and suspended-sediment using similar 

methods to those described in this report. The Centralia 

watershed is a headwater watershed that drains into the 

Tuttle Creek Lake watershed (fig. 1). The Tuttle Creek Lake 

watershed drains an area of 9,628 mi2

 and encompasses 

parts of southeast Nebraska and northeast Kansas. The three 

monitored sites were 06882510 Big Blue River at Marysville, 

Kansas, which drains 4,777 mi2

; 06884400 Little Blue River 

near Barnes, Kansas, which drains 3,351 mi2

; and 06885500 

Black Vermillion River near Frankfort, Kansas, which drains 

410 mi2, and is downstream and surrounds the Centralia 

watershed. The Tuttle Creek Lake watershed is 70 percent 

agricultural, 24 percent grassland, and the remainder woodland 

and urban (Juracek, 2011). 

Mean annual suspended-sediment yield for the Black 

Vermillion River near Frankfort watershed was estimated 

to be 850 tons/mi2

/yr (Juracek, 2011); smaller than the 

mean annual sediment yield for the Centralia watershed 

(970 tons/mi2/yr), but substantially larger than mean annual 

sediment yields at Clear Creek at Decatur Rd. (upstream from 

Atchison County Lake) (350 tons/mi2/yr) and Banner Creek 
Summary and Conclusions 35

at M Rd. (400 tons/mi2/yr; fig. 18). While sediment yields 

are thought to decrease from headwater to downstream sites 

because of decreasing channel slope and increased area for 

temporary storage and deposition of sediments (Schumm, 

1977), sediment yields are much larger relative to other 

headwater sites, especially considering that 98 percent of the 

Centralia watershed’s load is trapped within Centralia Lake. 

Larger yields in the Black Vermillion River watershed could 

be related to natural factors, such as soil type, channel slopes, 

and local geology, but without more information on reference 

yields, the degree of streambank erosion, or the extent of best 

management practices, it is difficult to ascertain the extent to 

which human actions or natural factors are causing increased 

sediment transport. The gaging sites at Barnes and Marysville 

had sediment yields of 410 and 270 tons per mi2, respectively, 

which, despite their vastly larger size, were similar to those 

yields estimated at Atchison and Banner (fig. 18). As with the 

Black Vermillion River watershed, more information is needed 

to determine why sediment yields in much larger basins are 

similar to those observed in small watersheds.

Summary and Conclusions

The U.S. Geological Survey, in cooperation with the 

Kansas Water Office, investigated sediment transport to and 

from three small impoundments in northeast Kansas from 

March 2009 through September 2011. Streamgages and turbidity sensors collected continuous 15-minute data upstream 

and downstream from Atchison County, Banner Creek, and 

Centralia Lakes in northeast Kansas. These sites were selected 

for study because they differed with respect to the extent or 

management of upstream agricultural activities. The Atchison 

County Lake and Centralia Lake watersheds have extensive 

agricultural activity, but both are similar with regard to installation of terraces and implementation of reduced and no tillage. However Atchison has more farms ponds, more tile drainage, and has more streams with riparian buffers. The Centralia 

Lake watershed is less tile drained, and streams are generally 

more channelized and have less riparian buffer. The Banner 

Creek Lake watershed is primarily grassland and pasture, has 

stream channels with riparian buffers, and has many farm 

ponds. Data from sampling sites were used to estimate sediment transport to and from each reservoir, and to characterize 

how natural factors and agricultural practices affect sediment 

transport in small watersheds in northeast Kansas.

The vast majority of sediment was transported to studied reservoirs during high flow conditions. Seventy-three 

to eighty-five percent of sediment loads were transported 

past headwater monitoring stations 1 percent of the time. 

Computed mean annual sediment yields (360 tons/mi2

/yr at 

Atchison, 400 tons/mi2

/yr at Banner, and 970 tons/mi2/yr at 

Centralia) were less at all three watersheds than those estimated by Collins (1965), who estimated between 2,000 and 

5,000 tons/mi2

/yr for this area of Kansas. Although small 

yields from Banner Creek were expected because of little 

agricultural activity, sediment yields at heavily cultivated 

Atchison County site were less than expected relative to Banner Creek or Centralia sites. These results also indicated that a 

cultivated watershed can carry yields similar to those observed 

under the assumed reference (or natural) condition. Data 

collected at two farm ponds upstream from Atchison County 

Lake in 2010 indicated average trapping efficiencies of 23 to 

30 percent during five storms, but only 8 percent of the total 

load upstream from the Clear Creek at Decatur Rd. (upstream 

from Atchison County Lake) streamgage. Extrapolation of 

these results across the basin indicated that sediment trapping 

in farm ponds likely explain little of the difference in sediment 

yields observed among the three monitoring sites. Farm pond 

data indicate that less sediment is trapped during large storms 

and when sediments may remain in suspension when multiple 

storms occur within weeks or months. 

Differences in sediment yields among Atchison and 

Centralia watersheds may be attributed to some combination 

of increased channelization, lack of riparian buffers, and less 

tile drainage in the Centralia basin. Equivalent sediment yields 

among the Atchison County and Banner Creek watersheds 

indicate that reference-like sediment yields may be observed 

in heavily agricultural watersheds through a combination of 

field-scale management activities and stream channel protection. When computing loads using published erosion rates 

obtained by single-point survey methodology, streambank 

contributions from the main stem of Banner Creek are three 

times more than the sediment load observed by this study at 

the sediment sampling site at Banner Creek, 2.6 times more 

than the sediment load observed by this study at the sediment 

sampling site at Clear Creek (upstream from Atchison County 

Lake), and are 22 percent of the load observed by this study 

at the sediment sampling site at Black Vermillion River above 

Centralia Lake. Comparisons of study sites to similarly sized 

urban and urbanizing watersheds in Johnson County, Kansas, 

indicated that sediment yields from the Centralia watershed 

were similar to those in construction-affected watersheds, 

while much smaller sediment yields in the Atchison County 

and Banner Creek watersheds were comparable to stable, 

heavily urbanized watersheds. Comparisons of study sites to 

larger watersheds upstream from Tuttle Creek Lake indicate 

the Black Vermillion River watershed continues to have high 

sediment yields despite 98 percent of sediment from the 

Centralia watershed (a headwater of the Black Vermillion 

River) being trapped in Centralia Lake.

In comparison to upstream data, sediment loading data 

collected downstream from each impoundment indicated 

sediment trapping efficiencies of 72, 98, and 98 percent in 

Atchison, Banner, and Centralia Lakes, respectively. This 

is because storage volume of Atchison County Lake is less 

than that of Banner and Centralia Lakes relative to the size of 

upstream drainage area.
36 Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011

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Prepared by the Rolla and Pembroke Publishing 

Service Centers.

For more information concerning this report, contact:

Office Chief

U.S. Geological Survey

Kansas Water Science Center

4821 Quail Crest Place

Lawrence, KS 66049

dc_ks@usgs.gov

or visit our Web site at:

http://ks.water.usgs.gov
Foster and others—Sediment Transport to and from Small Impoundments in Northeast Kansas, March 2009 through September 2011—Scientific Investigations Report 2012–5269