Joel Groten is a Hydrologist with the Upper Midwest Water Science Center.
He has a M.S. in Water Resources Science from the University of Minnesota and studied karst groundwater and surface water interactions in southeastern Minnesota under Dr. E. Calvin Alexander. Joel serves as a principal investigator related to USGS nutrient and sediment studies. In this capacity, he provides project oversight, technical assistance, teaching, training, data analysis, and reporting in support of projects for the Minnesota Pollution Control Agency, Minnesota Department of Natural Resources, U.S. Army Corps of Engineers, Lower Minnesota Watershed District, Rice Creek Watershed District, and the Institute for Technological Research in São Paulo, Brazil. These projects vary in scope and relate to continuous data acquisition in real-time, aquatic habitat, TMDL studies, stream restoration, geomorphology, nutrient and sediment budgets, and flood retention and diversion. Joel also is responsible for research and implementation of new technologies to improve understanding of nitrate and sediment sources, fate, and transport mechanisms.
Non-USGS Publications
Groten, J.T., and Alexander, E. C 2015, Karst Hydrogeologic Investigation of Trout Brook: Sinkholes and the Engineering and Environmental Impacts of Karst: Proceedings of the Fourteenth Multidisciplinary Conference, 1-7. http://dx.doi.org/10.5038/9780991000951.1012.
Luhmann, A. J., Covington, M. D., Alexander, S. C., Chai, S. Y., Schwartz, B. F., Groten, J. T., & Alexander, E. C., 2013, Comparison of discharge, chloride, temperature, uranine, δd, and suspended sediment responses from a multiple tracer test in karst: Carbonates and Evaporites, 28(1-2), 191-199. https://doi.org/10.1007/s13146-013-0127-8.
Groten, J.T., and Alexander, E. C., 2013, Karst Hydrogeologic Investigation of Trout Brook, Dakota County, Minnesota: Retrieved from the University of Minnesota Digital Conservancy, http://hdl.handle.net/11299/145674.
Luhmann, A. J., Covington, M. D., Alexander, S. C., Chai, S. Y., Schwartz, B. F., Groten, J. T., and Alexander Jr., E. C., 2012, Comparing conservative and nonconservative tracers in karst and using them to estimate flow path geometry: Journal of Hydrology, 448–449, 201–211, https://doi.org/10.1016/j.jhydrol.2012.04.044.
Groten, J.T., and Alexander, E. C, 2012, Hydrogeologic Monitoring at University of Minnesota Outreach, Research and Educational Park (UMore Park), 2011: Retrieved from the University of Minnesota Digital Conservancy, http://hdl.handle.net/11299/145679.
Science and Products
Lake Superior Beach Nourishment and Near-Shore Bathymetric Surveys of Minnesota Point at Duluth, Minnesota
Measuring Suspended-Sediment Concentrations, Grain Sizes and Bedload using Acoustic Doppler Velocity Meters and Echologgers in the Lower Chippewa River, Wisconsin
Sediment Acoustics
Model Archive Summary for Suspended-Sediment Concentration at Station 05321195; Blue Earth River at Highway 169 at Mankato, Minnesota
Extreme gradient boosting machine learning models, suspended sediment, bedload, streamflow, and geospatial data, Minnesota, 2007-2019
Suspended-sediment, bedload, bed-sediment, and multibeam sonar data in the Chippewa River, WI
Suspended sediment and bedload data, simple linear regression models, loads, elevation data, and FaSTMECH models for Rice Creek, Minnesota, 2010-2019
The Vigil Network: long-term, broad spectrum data collected to observe landscape change in drainage basins
Bedload Intake Efficiency: Comparison of measurements obtained using # bedload samplers in a flume
Suspended-sediment and sand concentrations, streamflow, acoustic data, linear regression models, and loads for the Lower Minnesota River, 2012-2019
Suspended-sediment concentrations, acoustic data, and a linear regression model for the Minnesota River at Mankato, Minnesota, 2016-2019
Suspended-sediment concentrations, acoustic data, and linear regression models for the Lower Minnesota River, Mississippi River, and Lake Pepin, 2015-2017

A novel suspended-sediment sampling method: Depth-Integrated Grab (DIG)
State of the science and decision support for measuring suspended sediment with acoustic instrumentation
How machine learning can improve predictions and provide insight into fluvial sediment transport in Minnesota
Sand- and gravel-trapping efficiencies derived for four types of pressure-difference bedload samplers
Comparing empirical sediment transport modeling approaches in Michigan rivers
Using machine learning to improve predictions and provide insight into fluvial sediment transport
The use of continuous sediment-transport measurements to improve sand-load estimates in a large sand-bedded river: The Lower Chippewa River, WI
Sediment monitoring and streamflow modeling before and after a stream restoration in Rice Creek, Minnesota, 2010–2019
Virtual training prepared for the former Afghanistan Ministry of Energy and Water—Streamgaging, fluvial sediment sampling, bathymetry, and streamflow and sediment modeling
Instruments, methods, rationale, and derived data used to quantify and compare the trapping efficiencies of four types of pressure-difference bedload samplers
Performance of bedload sediment transport formulas applied to the Lower Minnesota River
Estimation of suspended sediment at a discontinued streamgage on the lower Minnesota River at Fort Snelling State Park, Minnesota
Science and Products
- Science
Lake Superior Beach Nourishment and Near-Shore Bathymetric Surveys of Minnesota Point at Duluth, Minnesota
The shoreline, beaches, and infrastructure in Duluth, Minnesota have been degraded along the Minnesota Point barrier island because of high water levels and heavy wave action. The U.S. Army Corps of Engineers (USACE) is exploring the beneficial use of dredge material for beach nourishment on the Lake Superior side of the barrier island.Measuring Suspended-Sediment Concentrations, Grain Sizes and Bedload using Acoustic Doppler Velocity Meters and Echologgers in the Lower Chippewa River, Wisconsin
Sediment from the Chippewa River deposits in the Mississippi River navigation channel, sometimes disrupting commercial barge traffic and resulting in expensive and ecologically disruptive dredging operations. The USGS is using new applications of hydroacoustic technologies to better understand sediment transport in the Chippewa River and associated effects on commercial navigation.Sediment Acoustics
The U.S. Geological Survey recognizes the need to provide sediment acoustic training and to develop standardized techniques and practices. - Data
Model Archive Summary for Suspended-Sediment Concentration at Station 05321195; Blue Earth River at Highway 169 at Mankato, Minnesota
This model archive summary (MAS) documents the suspended-sediment concentration (SSC) model developed to compute 15-minute SSC from turbidity readings. This is the first model developed for the Blue Earth River at Highway 169 at Mankato, Minnesota (Station ID 05321195).Extreme gradient boosting machine learning models, suspended sediment, bedload, streamflow, and geospatial data, Minnesota, 2007-2019
A series of machine learning (ML) models were developed for Minnesota. The ML models were trained and tested using suspended sediment, bedload, streamflow, and geospatial data to predicted suspended sediment and bedload. Suspended sediment, bedload, and streamflow data were collected during water years 2007 through 2019. The ML models were used to improve understanding of sediment transport procesSuspended-sediment, bedload, bed-sediment, and multibeam sonar data in the Chippewa River, WI
These data were compiled for analyses of sediment transport within the Chippewa River, WI. Objective(s) of our study were to determine sand loads contributed by the Chippewa River to the Mississippi River. These data include physical suspended-sediment samples, acoustical suspended-sediment measurements, acoustical suspended-sediment loads, quasi-continuous measurements of bed-elevation, multibeamSuspended sediment and bedload data, simple linear regression models, loads, elevation data, and FaSTMECH models for Rice Creek, Minnesota, 2010-2019
A series of simple linear regression models were developed for the U.S. Geological Survey (USGS) streamgage at Rice Creek below Highway 8 in Mounds View, Minnesota (USGS station number 05288580). The simple linear regression models were calibrated using streamflow data to estimate suspended-sediment (total, fines, and sands) and bedload. Data were collected during water years 2010, 2011, 2014, 201The Vigil Network: long-term, broad spectrum data collected to observe landscape change in drainage basins
Long-term monitoring data of geomorphic, hydrological, and biological characteristics of landscapes. This information provides an effective means of relating observed change to possible causes of the change. Identification of changes in basin characteristics, especially in arid areas where the response to altered climate or land use is generally rapid and readily apparent, might provide the initiaBedload Intake Efficiency: Comparison of measurements obtained using # bedload samplers in a flume
Bedload and ancillary data herein were used to calculate and compare the bedload-trapping efficiencies of four types of pressure-difference bedload samplers as part of episodic, sediment-recirculating flume tests. The U.S. Geological Survey, in concert with the Federal Interagency Sedimentation Project (FISP), conducted the tests from January through March 2006 at the St. Anthony Falls Laboratory,Suspended-sediment and sand concentrations, streamflow, acoustic data, linear regression models, and loads for the Lower Minnesota River, 2012-2019
A series of linear regression models were developed and calibrated for two Lower Minnesota River sites. The linear regression models were either calibrated using acoustic or streamflow data to estimate suspended-sediment or sand concentration data. Data were collected during calendar years 2012 through 2019. The estimates of suspended-sediment and concentrations from the linear regression were useSuspended-sediment concentrations, acoustic data, and a linear regression model for the Minnesota River at Mankato, Minnesota, 2016-2019
A simple linear regression model was developed and calibrated for the Minnesota River at Mankato, Minnesota (Site Number: 05325000). The linear regression model was calibrated using acoustic and suspended-sediment concentration data collected from 2016 through 2019.The calibrated model will be used to improve understanding of sediment transport processes and increase accuracy of estimating sedimenSuspended-sediment concentrations, acoustic data, and linear regression models for the Lower Minnesota River, Mississippi River, and Lake Pepin, 2015-2017
A series of linear regression models were developed and calibrated for the Minnesota and Mississippi Rivers. The linear regression models were calibrated using acoustic and suspended-sediment concentration data collected from March through November 2016 and 2017. The estimates of suspended-sediment concentrations from the linear regression were used to calculate loads. The calibrated models were u - Multimedia
USGS meeting with National Agency for Water and Basic Sanitation (ANA) scientists in Brazil standing in front of flags
- Publications
Filter Total Items: 19
A novel suspended-sediment sampling method: Depth-Integrated Grab (DIG)
Measuring suspended sediment in fluvial systems is critical to understanding and managing water resources. Sampling suspended sediment has been the primary means of understanding fluvial suspended sediment. Specialized samplers, sampling methods, and laboratory methods developed by select U.S. Federal Agencies are more representative of river and stream conditions than commonly used grab samplingAuthorsJoel T. Groten, Sara B. Levin, Erin N. Coenen, John (William) Lund, Gregory D. JohnsonState of the science and decision support for measuring suspended sediment with acoustic instrumentation
Acoustic instrumentation can be used to provide time-series and discrete estimates of suspended-sediment concentration, load, and sediment particle sizes in fluvial systems, which are essential for creating informed solutions to many sediment-related environmental, engineering, and land management concerns. Historically, scientists have developed relations between suspended sediment characteristicAuthorsMolly S. Wood, Joel T. Groten, Timothy D. Straub, Dan R.W. Haught, Ronald E. Griffiths, Justin A. Boldt, Zulimar Lucena, Jeb E. Brown, Steven E. Suttles, Patrick J. DickhudtHow machine learning can improve predictions and provide insight into fluvial sediment transport in Minnesota
Understanding fluvial sediment transport is critical to addressing many environmental concerns such as exacerbated flooding, degradation of aquatic habitat, excess nutrients, and the economic challenges of restoring aquatic systems. However, fluvial sediment transport is difficult to understand because of the multitude of factors controlling the potential sources, delivery, mechanics, and storageAuthorsJohn (William) Lund, Joel T. Groten, Diana L. Karwan, Chad BabcockSand- and gravel-trapping efficiencies derived for four types of pressure-difference bedload samplers
Bedload-trapping efficiencies (coefficients) were derived for four types of pressure-difference bedload samplers at the St. Anthony Falls Laboratory, University of Minnesota during the first two phases of flume experiments in January-March, 2006, referred to as “StreamLab06.” The bedload-sampler research component was part of a series of community-led, large-scale laboratory experiments performedAuthorsJohn Gray, Joel T. Groten, Jonathan A. Czuba, Gregory E. Schwarz, Kyle Strom, Panayiotis DiplasComparing empirical sediment transport modeling approaches in Michigan rivers
Excess or limited fluvial sediment transport can contribute to and exacerbate many environmental issues including nutrient loading, aquatic habitat degradation, flooding, channel navigation dredging, dam operation, and stream degradation or aggradation. However, fluvial sediment transport is difficult and expensive to comprehensively characterize because it can vary substantially both temporally aAuthorsJoel T. Groten, Sara B. Levin, Erin N. Coenen, John (William) Lund, Bethany MatousekUsing machine learning to improve predictions and provide insight into fluvial sediment transport
A thorough understanding of fluvial sediment transport is critical to addressing many environmental concerns such as exacerbated flooding, degradation of aquatic habitat, excess nutrients, and the economic challenges of restoring aquatic systems. Fluvial sediment samples are integral for addressing these environmental concerns but cannot be collected at every river and time of interest. Therefore,AuthorsJ. William Lund, Joel T. Groten, Diana L. Karwan, Chad BabcockThe use of continuous sediment-transport measurements to improve sand-load estimates in a large sand-bedded river: The Lower Chippewa River, WI
Accurately determining sediment loads is necessary for managing river environments but is difficult because multiple processes can lead to large discharge-independent changes in sediment transport. Thus, estimations of sediment load using discharge–sediment rating curves fit to sparse or historical sediment-transport measurements can be inaccurate, necessitating alternative approaches to reduce unAuthorsDavid Dean, David Topping, D. D. Buscombe, Joel T. Groten, Jeffrey R. Ziegeweid, Faith A. Fitzpatrick, John (William) Lund, Erin Nicole CoenenSediment monitoring and streamflow modeling before and after a stream restoration in Rice Creek, Minnesota, 2010–2019
The Rice Creek Watershed District (RCWD) cooperated with the U.S. Geological Survey to establish a 10-year suspended sediment and bedload monitoring and streamflow modeling study to evaluate the effects of two restored meander sections on middle Rice Creek in Arden Hills, Minnesota. The RCWD goals of this stream restoration were to reduce water quality impairments, improve aquatic habitat, and redAuthorsJoel T. Groten, Colin T. Livdahl, Stephen B. DeLong, J. William Lund, Jonathan M. Nelson, Erin N. Coenen, Jeffrey R. Ziegeweid, Matthew J. KocianVirtual training prepared for the former Afghanistan Ministry of Energy and Water—Streamgaging, fluvial sediment sampling, bathymetry, and streamflow and sediment modeling
The U.S. Geological Survey (USGS) created a virtual training series for the Afghanistan Ministry of Energy and Water (MEW), now known as the National Water Affairs Regulation Authority (NWARA), to provide critical hydrological training as an alternative to an in-person training. The USGS was scheduled to provide in-person surface-water training for NWARA during 2020; however, travel was halted becAuthorsJoel T. Groten, Joshua F. Valder, Brenda K. Densmore, Logan W. Neal, Justin Krahulik, Thomas J. MackInstruments, methods, rationale, and derived data used to quantify and compare the trapping efficiencies of four types of pressure-difference bedload samplers
Bedload and ancillary data were collected to calculate and compare the bedload trapping efficiencies of four types of pressure-difference bedload samplers as part of episodic, sediment-recirculating flume experiments at the St. Anthony Falls Laboratory, University of Minnesota, Minneapolis, in January–March 2006. The bedload-sampler experiments, which were conceived, organized, and led by the U.S.AuthorsJohn R. Gray, Gregory E. Schwarz, David Dean, Jonathan A. Czuba, Joel T. GrotenPerformance of bedload sediment transport formulas applied to the Lower Minnesota River
Despite limitations in reproducing complex bedload sediment transport processes in rivers, formulas have been preferred over collection and analysis of field data due to the high cost and time-consuming nature of bedload discharge measurements. However, the performance of such formulas depends on the hydraulic and sedimentological conditions they attempt to describe. The availability of field measAuthorsElisa Armijos, Gustavo Henrique Merten, Joel T. GrotenEstimation of suspended sediment at a discontinued streamgage on the lower Minnesota River at Fort Snelling State Park, Minnesota
In the spring of 2019, ice sheets transported down-stream during a large streamflow rise event in the lower Minnesota River destroyed an index-velocity streamgage at the Minnesota River at Fort Snelling State Park, Minnesota (U.S. Geological Survey station 05330920; hereafter referred to as “Ft. Snelling”). The streamgage previously used an acoustic Doppler velocity meter to provide instantaneousAuthorsJoel T. Groten, Jon S. Hendrickson, Linda R. Loomis - News