Sediment Concentrations and Loads Upstream from and through John Redmond Reservoir, East-Central Kansas, 2010–19

Scientific Investigations Report 2021-5037
Prepared in cooperation with the Kansas Water Office
By: , and 

Links

  • Document: Report (3.50 MB pdf)
  • Appendixes:
    • Appendix 1 (408 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182250, Cottonwood River near Plymouth, Kansas, during January 1, 2010, through April 22, 2015
    • Appendix 2 (414 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07179750, Neosho River at Burlingame Road near Emporia, Kansas, during January 1, 2010, through December 16, 2012
    • Appendix 3 (432 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182390, Neosho River at Neosho Rapids, Kansas, during January 1, 2010, through September 24, 2015
    • Appendix 4 (455 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182510, Neosho River at Burlington, Kansas, during January 1, 2010, through October 16, 2015
    • Appendix 5 (376 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182250, Cottonwood River near Plymouth, Kansas, during April 22, 2015, through December 31, 2019
    • Appendix 6 (399 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07179750, Neosho River at Burlingame Road near Emporia, Kansas, during May 2, 2015, through December 31, 2019
    • Appendix 7 (391 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182390, Neosho River at Neosho Rapids, Kansas, during November 13, 2015, through December 31, 2019
    • Appendix 8 (427 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182510, Neosho River at Burlington, Kansas, during October 23, 2015, through December 31, 2019
    • Appendix 9 (457 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182250, Cottonwood River near Plymouth, Kansas, during January 1, 2010, through December 31, 2019
    • Appendix 10 (418 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07179750, Neosho River at Burlingame Road near Emporia, Kansas, during January 1, 2010, through December 31, 2019
    • Appendix 11 (449 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182390, Neosho River at Neosho Rapids, Kansas, during January 1, 2010, through December 31, 2019
    • Appendix 12 (451 kB pdf) — Model Archive Summary for Suspended-Sediment Concentration at U.S. Geological Survey Site 07182510, Neosho River at Burlington, Kansas, during January 1, 2010, through December 31, 2019
  • Dataset: U.S. Geological Survey National Water Information System database — USGS water data for the Nation
  • Download citation as: RIS | Dublin Core

Abstract

Streambank erosion and reservoir sedimentation are primary concerns of resource managers in Kansas and throughout many regions of the United States and negatively affect flood control, water supply, and recreation. The Cottonwood and upper Neosho Rivers drain into John Redmond Reservoir, and since reservoir completion in 1964, there has been substantial conservation-pool sedimentation and storage loss in John Redmond Reservoir, causing storage capacity losses more rapidly than most other Federal reservoirs in Kansas. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office, has monitored water quality (temperature, specific conductance, and turbidity) on the Cottonwood River (upstream from the reservoir) and Neosho River (upstream and downstream from the reservoir) since 2007 with additional sites added in 2009. The purpose of this report is to quantify suspended-sediment concentrations, loads, and yields entering and exiting John Redmond Reservoir during January 1, 2010, through December 31, 2019.

Three water-quality monitoring sites were upstream from the reservoir (Cottonwood River near Plymouth, Kansas [USGS site 07182250; hereinafter referred to as “Cottonwood”]; Neosho River at Burlingame Road near Emporia, Kans. [USGS site 07179750; hereinafter referred to as “Burlingame”]; and Neosho River at Neosho Rapids, Kans. [USGS site 07182390; hereinafter referred to as “Neosho Rapids”]), and one water-quality monitoring site was downstream from the reservoir (Neosho River at Burlington, Kans. [USGS site 07182510; hereinafter referred to as “Burlington”]). The Neosho Rapids streamgage is downstream from the confluence of the Cottonwood and upper Neosho Rivers and has a contributing drainage area accounting for 91 percent of the total contributing drainage area to John Redmond Reservoir.

Continuously measured streamflow, water quality, and discrete water-quality data were used to develop updated regression models to compute suspended-sediment concentrations, loads, and yields upstream and downstream from John Redmond Reservoir in east-central Kansas. Several turbidity sensors were deployed during the analysis period, and there are no established relations between the sensors; therefore, individual models for each sensor were developed. Model statistics for the turbidity and suspended-sediment concentration linear regression models were better (based on the coefficient of determination, root mean square error, and model standard percentage error) than the streamflow and suspended-sediment concentration linear regression models, indicating better model performance. Computed concentrations, loads, and yields do not account for the ungaged 9 percent of the drainage basin downstream from the Neosho Rapids streamgage.

Mean daily suspended-sediment loads upstream from the reservoir were largest at Neosho Rapids (2,250 tons), second largest at Cottonwood (2,180 tons), and smallest at Burlingame (624 tons). Streamflow at Burlington was predominately regulated by reservoir releases, and mean daily suspended-sediment loads were smaller (286 tons) than at upstream sites. Among the upstream sites, Cottonwood had the largest mean daily suspended-sediment concentration (179 milligrams per liter [mg/L]), followed by Neosho Rapids (162 mg/L), and Burlingame (108 mg/L). Burlington had the smallest mean daily suspended-sediment concentration of all sites (46 mg/L).

Annual reservoir trapping efficiency ranged from 82 to 94 percent, and the largest sediment mass trapped was during 2019 (2,230,000 tons). Reservoir storage decreased an estimated 7,750 acre-feet during 2010 and 2014–19. Using the mean trapping efficiency to estimate suspended-sediment loads during years with missing data (2011–13), the total estimated reservoir storage lost to sedimentation for the analysis period (2010–19) was 8,690 acre-feet, about 17 percent of the remaining storage space reported in 2007. The mean annual sedimentation rate during the analysis period (747 acre-feet per year) was about 85 percent larger than the design sedimentation rate (404 acre-feet per year) originally projected during construction. Different reservoir outflow management strategies, including operating near normal capacity as opposed to higher flood pool levels, could reduce the total reservoir storage lost by 3 percent (about 261 acre-feet), which is equal to 14 percent of the total sediment removed during the dredging operation in 2016.

During the study period, about 56 percent of the total suspended-sediment load was transported during streamflows greater than the National Weather Service flood action stage at the upstream sites (0.1–5 percent of the record; Cottonwood mean: 48 percent; Burlingame mean: 40 percent; Neosho Rapids mean: 78 percent). Disproportionately large sediment loads were delivered during short periods of time, and localized efforts of stream erosion protection (streambank stabilization, riparian buffers) were likely to be overwhelmed. Precipitation frequency and intensity are projected to continue to increase in this region; therefore, future sediment reduction strategies that account for extreme episodic events may be beneficial. Changes to reservoir outflow management could also minimize sediment accumulation while still preserving flood control. Continued investigation of sediment reduction measures is necessary for future mitigation with the understanding that sedimentation rate is largely driven by high flows. Results from this study can be used to calibrate sediment models, explore sediment reduction strategies, highlight the importance of continued water-quality monitoring to determine effectiveness and changes in sediment transport, and assess the ability of John Redmond Reservoir to support designated uses into the future.

Suggested Citation

Kramer, A.R., Peterman-Phipps, C.L., Mahoney, M.D., and Lukasz, B.S., 2021, Sediment concentrations and loads upstream from and through John Redmond Reservoir, east-central Kansas, 2010–19: U.S. Geological Survey Scientific Investigations Report 2021–5037, 49 p., https://doi.org/10.3133/sir20215037.

ISSN: 2328-0328 (online)

Study Area

Table of Contents

  • Acknowledgments
  • Abstract
  • Introduction
  • Methods
  • Streamflow Conditions and Continuously Monitored Water-Quality Variables
  • Regression Models and Computed Concentrations, Loads, and Yields for Suspended Sediment
  • Summary
  • References Cited
  • Appendixes 1–12
  • Appendix 13
Publication type Report
Publication Subtype USGS Numbered Series
Title Sediment concentrations and loads upstream from and through John Redmond Reservoir, east-central Kansas, 2010–19
Series title Scientific Investigations Report
Series number 2021-5037
DOI 10.3133/sir20215037
Year Published 2021
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Kansas Water Science Center
Description Report: ix, 50 p; Appendixes: 12; Dataset
Country United States
State Kansas
Other Geospatial John Redmond Reservoir
Online Only (Y/N) Y
Additional Online Files (Y/N) Y
Google Analytic Metrics Metrics page
Additional publication details