Ariele R. Kramer Thomas J. Williams 20240201 model archive summary ScienceBase U.S. Geological Survey https://doi.org/10.5066/P13YQYVQ https://doi.org/10.5066/P13YQYVQ https://nrtwq.usgs.gov/explore/dyplot?site_no=06887000 https://waterdata.usgs.gov/nwis/inventory?site_no=06887000&agency_cd=USGS This data release provides details on a turbidity-derived suspended-sediment concentration (SSC) model for USGS site 06887000, the Big Blue River near Manhattan, Kansas. This includes a model archival summary for SSC, developed to compute 5- to 15-minute, hourly, or daily SSC from July 26, 2018, onward. This model is specific to USGS site 06887000, the Big Blue River near Manhattan, Kansas, during this study period and cannot be applied to data collected from other locations on the Big Blue River or data collected from other water bodies. The methods follow USGS guidance as referenced in relevant Central Plains Water Science Center methods, Office of Surface Water/Office of Water Quality Technical Memoranda and USGS Techniques and Methods, book 3, chapter C4 (Rasmussen and others, 2009; U.S. Geological Survey, 2016; Stone and others, 2024). This version supercedes the previous model version published in Kramer and Williams, 2024 (https://doi.org/10.5066/p9z2dj6p) The purpose of this data release is to document the techniques and methods used to develop a turbidity-derived SSC computation model for the Big Blue River near Manhattan, Kansas site (USGS site 06887000). This new model supersedes the model published in Kramer and Williams (2024; https://doi.org/10.5066/P9Z2DJ6P). 20180717 20251117 ground condition In work As needed Big Blue River -96.6700 -96.5100 39.3000 39.1800 ISO 19115 Topic Category inlandWaters USGS Thesaurus suspended material (water) streamflow sediment transport water sampling turbidity surface water (non-marine) surface water quality scientific interpretation mathematical modeling USGS Metadata Identifier USGS:6977ea13d4be02609dd040e9 Common geographic areas Big Blue River Tuttle Creek Lake Kansas Manhattan None. Please see 'Distribution Info' for details. None. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations. U.S. Geological Survey, MIDCONTINENT REGION Central Plains Water Science Center mailing address

1217 Biltmore Drive

Lawrence KS 66049 US 785-842-9909 GS-W-CPWSC_DC@usgs.gov U.S. Army Corps of Engineers, Kansas Water Office Ordinary least squares regression analysis was done using the wren (v1.0.0) package in R programming language (Eslick-Huff and Puls, 2025; R Core Team, 2025) to relate discretely collected SSC to sensor-measured turbidity. Patrick J. Eslick-Huff Kyle A Puls 20260108 application/service https://code.usgs.gov U.S. Geological Survey https://doi.org/10.5066/p13q4uph Dennis R. Helsel Robert M. Hirsch Karen R. Ryberg Stacey A. Archfield Edward J. Gilroy 20200522 publication Techniques and Methods vol. 4-A3 https://pubs.usgs.gov US Geological Survey https://doi.org/10.3133/tm4A3 Ariele R Kramer Thomas J Williams 20240201 Dataset https://www.sciencebase.gov U.S. Geological Survey https://doi.org/10.5066/p9z2dj6p R Core Team 20250402 application/service https://www.r-project.org/ Patrick P. Rasmussen John R. Gray G. Douglas Glysson Andrew C. Ziegler 20180815 publication Techniques and Methods vol. 3-C4 https://pubs.usgs.gov US Geological Survey https://doi.org/10.3133/tm3C4 Mandy L. Stone Casey J. Lee Teresa J. Rasmussen Thomas J. Williams Ariele R. Kramer Brian J. Klager 20240801 publication Open-File Report vol. 2024-1049 https://pubs.usgs.gov US Geological Survey https://doi.org/10.3133/ofr20241049 U.S. Geological Survey 20180820 publication n/a US Geological Survey https://doi.org/10.3133/twri09A4 U.S. Geological Survey publication https://water.usgs.gov/admin/memo/SW/sw.2016.07+wq.2016.10.pdf United States Geological Survey 20150224 dataset https://waterdata.usgs.gov U.S. Geological Survey https://doi.org/10.5066/f7p55kjn Richard J. Wagner Robert W. Boulger Carolyn J. Oblinger Brett A. Smith 20180815 publication Techniques and Methods vol. 1-D3 https://pubs.usgs.gov US Geological Survey https://doi.org/10.3133/tm1D3 All SSC and continuous water-quality data during July 2018 through November 2025 were collected using USGS protocols, reviewed and approved following USGS guidance, and are stored in the USGS National Water Information System (https://doi.org/10.5066/F7P55KJN) database and available to the public. The methods for data collection and review follow USGS guidance as referenced in relevant Office of Surface Water/Office of Water Quality Technical Memoranda and USGS Techniques and Methods, book 3, chapter C4 (Wagner and others, 2006; Rasmussen and others, 2009; U.S. Geological Survey, 2016). Data accuracy was evaluated by comparing the SSC observations to the regression-computed SSC and the 95-percent prediction intervals (Model calibration dataset section of the model archive summary). The 95-percent prediction intervals represent the range in uncertainty associated with each regression-computed SSC value. Accuracy is also evaluated by examining the residual plots of regression-computed and observed values of SSC. All data were subject to multiple levels of review which included checking for sampling errors, numerical errors, data entry errors, duplication, omission, expected range of results, model review, final data review, and metadata review. The data and resultant regression equation generally conform with the five assumptions for ordinary least squares regression: the dependent variable was linearly related to the explanatory variables, data used to fit the model were representative of the data of interest, the variance of the residuals was constant (homoscedastic), the residuals were independent of the explanatory variables, and the residuals were normally distributed (Helsel and others, 2020; https://doi.org/10.3133/tm4A3). The data represent discrete sample results of SSC at a specific location, USGS site ID 06887000, Big Blue River near Manhattan, Kansas. The data also includes concomitant turbidity data collected using a multiparameter water-quality monitor deployed at this location. Additional documentation can be found in the model archive summary associated with this data release. No formal positional accuracy tests were conducted. No formal positional accuracy tests were conducted. During August 2018 through November 2025, suspended-sediment samples were collected over a range of hydrologic conditions. Of the 76 samples included in this dataset, 72 suspended-sediment samples were collected using the isokinetic equal-width or equal-discharge increment collection methods (U.S. Geological Survey, 2006). Three samples, collected during September 2020, were collected using the non-isokinetic single-vertical collection method (U.S. Geological Survey, 2006) due to estimated stream-surface velocities of less than one foot per second and personnel constraints influenced by the COVID-19 pandemic. One sample was collected using a non-isokinetic multiple vertical collection method (U.S. Geological Survey, 2006) on February 21, 2019, due to ice cover. Sample collection was suspended during October 2020 through March 2023 due to project delays and funding constraints. U.S. Geological Survey, 2006 U.S. Geological Survey, 2026 20260109 Continuous (5- to 15-minute) water temperature, specific conductance, and TBY data were measured using a water-quality multiparameter monitor during July 26, 2018, onward. Continuous dissolved oxygen and pH were added to the monitor during December 2018 and April 2023, respectively. Continuous water-quality data collection was suspended during October 2020 through March 2023 due to project delays and funding constraints. The water-quality monitor was operated and maintained according to USGS protocols (Wagner and others, 2006) and was deployed by suspension from a bridge about 1 to 3 feet below the water surface. During 2018–20, the monitor was suspended closer to the right bank and when it was reinstalled in 2023, it was placed about 100 feet from the original location to be nearer the centroid of flow. All continuous water-quality monitor data for the Big Blue River near Manhattan, Kans. are available in near real time (hourly) in the USGS National Water Information System database (https://doi.org/10.5066/F7P55KJN; U.S. Geological Survey, 2026) using site number 06887000. U.S. Geological Survey, 2026 Wagner and others, 2006 20260109 Ordinary least squares (OLS) regression analysis was done using the wren (v1.0.0) package in R programming language (Eslick-Huff and Puls, 2025; R Core Team, 2025) to relate discretely collected SSC to sensor-measured turbidity. Potential explanatory variables were evaluated individually (simple linear regression) and in combination with other explanatory variables (multiple linear regression). Evaluated explanatory variables included streamflow, water temperature, specific conductance, dissolved oxygen, pH, and turbidity. These potential explanatory variables were time interpolated between the two nearest continuous water-quality readings.The maximum time span between two continuous data points used for interpolation was 2 hours. Seasonal components (sine and cosine variables) also were evaluated as potential explanatory variables. Eslick-Huff and Puls, 2025 R Core Team, 2025 20260116 All potential outliers were investigated as described in the model archive summary and were not determined to have errors associated with sample collection, processing, or analysis and were therefore considered valid and included in the model calibration dataset. 20260120 A model archive summary was completed using the wren (v1.0.0) package in R programming language (Eslick-Huff and Puls, 2025; R Core Team, 2025) which produced model statistics, data, and plots. All of the data and information relevant to the SSC linear regression model is included in the model archive summary package in accordance with Office of Surface Water Technical Memorandum 2016.07 (https://water.usgs.gov/admin/memo/SW/sw.2016.07+wq.2016.10.pdf). Eslick-Huff and Puls, 2025 R Core Team, 2025 U.S. Geological Survey, 2016 20260126 06887000_ssc_tby_modeldata.csv Comma Separated Value (CSV) file containing data. Producer Defined dateTime_CT Date and time sample was collected in the North American Central Time Zone. USGS National Water Information System 2018-08-14 09:10:00 2025-11-17 14:00:00 SSC_mgL Discrete suspended sediment concentration data used as the response variable in the model. Producer Defined 7 1810 milligrams per liter Turbidity_FNU Time interpolated turbidity time-series data used as the explanatory variable. Producer Defined 2.9 1010.0 formazin nephelometric units Included is a model archival summary for suspended-sediment concentration (SSC), developed to compute 5- to 15-minute, hourly, or daily SSC from July 2018, onward. This model is specific to USGS site 06887000, the Big Blue River near Manhattan, Kansas, during this study period and cannot be applied to data collected from other locations on the Big Blue River or data collected from other water bodies. This model and archival summary includes an expanded model calibration dataset with greater calibration range superseding the model published previously in Kramer and Williams (2024). GS ScienceBase U.S. Geological Survey mailing address

Denver Federal Center, Building 810, Mail Stop 302

Denver CO 80225 United States 1-888-275-8747 sciencebase@usgs.gov Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data for other purposes, nor on all computer systems, nor shall the act of distribution constitute any such warranty. Digital Data https://waterdata.usgs.gov/nwis/inventory?site_no=06887000&agency_cd=USGS None 20260225 U.S. Geological Survey, MIDCONTINENT REGION Central Plains Water Science Center mailing address

1217 Biltmore Drive

Lawrence KS 66049 US 785-842-9909 GS-W-CPWSC_DC@usgs.gov FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata FGDC-STD-001.1-1999