Geology topics

Erin N. Coenen

Publications and source records attributed to Erin N. Coenen.

7 recordsLinked to original sources

USGS2025

Suspended sediment and bedload transport along the Main and South Branches, Wild Rice River, northwestern Minnesota, 1979 through 2023

The geologic history and anthropogenic modifications of Minnesota’s Wild Rice River have caused major morphological adjustments, which induce erosion and excess fluvial sediment transport. The excess sediment deposits in the lower Wild Rice River, exacerbating flooding. To help mitigate these problems, the Wild Rice Watershed District has future plans to implement a river restoration on the lower Wild Rice River. The Wild Rice Watershed District collaborated with the U.S. Geological Survey to measure and analyze sediment transport along the Wild Rice River’s Main and South Branches to assess any potential changes in sediment transport among sites and time periods. Time differencing results indicated that all suspended-sediment constituents showed a significant difference between the two sampling periods at one South Branch site but not at the Main Branch site. Piecewise regression analysis better matched the suspended-sediment constituents transport process at most sites by differentiating no relation between suspended-sediment constituents at lower streamflows and a positive relation at higher streamflows at most Wild Rice River sites. Five of the sites showed elevated sediment transport with increasing streamflow. In contrast, the site farthest downstream showed a negative relation with increasing streamflow, indicating that that the lower Wild Rice River is supply limited and deposition is likely occurring upstream and (or) near the site. Overall, the uncertainty in results indicates the complexity of sediment transport in a river when using streamflow as the sole explanatory variable and suggests a need for multisite, multiyear, and multifaceted data.

Minnesota↗

USGS2025

Using machine learning in Minnesota’s StreamStats to predict fluvial sediment

A thorough understanding of fluvial sediment transport is essential for addressing key environmental issues such as aquatic habitat degradation, flooding, excess nutrients, and challenges with river restoration. Fluvial sediment samples are valuable for addressing these concerns, but their collection is often impractical across all rivers and timeframes of interest. In addition, previously used analytical and numerical methods have not allowed for the transfer of knowledge from sites that have data to sites that do not have data. To overcome this limitation, the U.S. Geological Survey developed machine learning models to predict suspended-sediment concentrations and bedload transport in Minnesota rivers that lack physical sediment data and integrated them into the U.S. Geological Survey StreamStats web application.

Minnesota↗

USGS2023

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 sampling and total suspended solids (TSS) laboratory methods but are not widely used because they are expensive, time consuming, and not required as part of water quality standards in the United States. A new suspended-sediment sampling method called a depth-integrated grab (DIG) was developed by combining certain elements from both grab and depth-integrating sampling methods and suspended-sediment concentration (SSC) laboratory methods. The goal of the DIG method was to provide more accurate results than Grab-TSS while being easier and cheaper to sample than specialized samplers and methods. Approximately 50 paired comparison samples were collected at 9 sites in Minnesota from 2018 through 2019. Results showed no significant difference between the DIG and specialized sampling methods and a significant difference between both methods and the Grab-TSS method. The DIG-SSC provided an improved alternative to the Grab-TSS method, but additional research and testing is important to evaluate if this method is appropriate in different conditions than were observed in this study.

Minnesota↗

USGS2023

Comparing 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 and spatially. Having better estimates of fluvial sediment transport is important for understanding and solving these environmental issues when it is not possible to collect fluvial sediment samples. Different modeling approaches can be used to help estimate suspended sediment when sampling data are limited or unavailable. This study compared dimensionless sediment rating curves (DSRCs) developed in Pagosa Springs Colorado, Minnesota, and Michigan to determine if these DSRCs were suitable to make predictions of suspended sediment for Michigan rivers. Approximately 3,000 suspended sediment samples collected in or near Michigan from the mid-1960s through August 2022 were used to develop two DSRC models. The DSRCs developed in Michigan include a pooled DSRC model which uses nonlinear least squares regression, and a mixed-effects DSRC model which uses a mixed-effects modeling approach. In general, there was not a noticeable improvement in the performance of the Michigan mixed-effects DSRC model over the Michigan pooled DSRC model. The two Michigan DSRCs were evaluated against DSRCs developed for Pagosa Springs and Minnesota. The results showed DSRC models developed from Minnesota and Michigan were similar to each other. In contrast, the Pagosa Springs DSRC predicts higher suspended-sediment concentration (SSC) at low flows and increases at a higher rate due to having a greater exponent. The Pagosa Springs DSRC produces higher SSC predictions that do not approximate the observed data well at most of the Michigan sites in the study. The results suggest that the Pagosa Springs DSRC was not suitable to make predictions of suspended sediment for Michigan rivers. The similarity of the DSRC equations developed for Minnesota and Michigan compared to the Pagosa Springs DSRC equation suggest that there may be regional patterns of SSC in the upper Midwest rivers that differ from those in other areas of the country like Pagosa Springs. A regionally applicable model could be developed and strengthened by combining data from additional midwestern states. Since the Michigan DSRCs goodness-of-fit metrics were comparable to the site-specific simple linear regressions (SLRs) and outperformed them in the aggregate goodness-of-fit metrics, the Michigan DSRCs are suitable to make predictions of suspended sediment in Michigan rivers with limited data. However, the availability of the DSRCs from this study should not diminish the value of collecting physical samples and exploring alternative modeling approaches because of the uncertainty associated with using DSRCs. Approximately 3,000 suspended sediment samples collected in or near Michigan from the mid-1960s through August 2022 were used to develop two DSRC models. The DSRCs developed in Michigan include a pooled DSRC model which uses nonlinear least squares regression, and a mixed-effects DSRC model which uses a mixed-effects modeling approach. In general, there was not a noticeable improvement in the performance of the Michigan mixed-effects DSRC model over the Michigan pooled DSRC model. The two Michigan DSRCs were evaluated against DSRCs developed for Pagosa Springs and Minnesota. The results showed DSRC models developed from Minnesota and Michigan were similar to each other. In contrast, the Pagosa Springs DSRC predicts higher suspended-sediment concentration (SSC) at low flows and increases at a higher rate due to having a greater exponent. The Pagosa Springs DSRC produces higher SSC predictions that do not approximate the observed data well at most of the Michigan sites in the study. The results suggest that the Pagosa Springs DSRC was not suitable to make predictions of suspended sediment for Michigan rivers. The similarity of the DSRC equations developed for Minnesota and Michigan compared to the Pagosa Springs DSRC equation suggest that there may be regional patterns of SSC in the upper Midwest rivers that differ from those in other areas of the country like Pagosa Springs. A regionally applicable model could be developed and strengthened by combining data from additional midwestern states. Since the Michigan DSRCs goodness-of-fit metrics were comparable to the site-specific simple linear regressions (SLRs) and outperformed them in the aggregate goodness-of-fit metrics, the Michigan DSRCs are suitable to make predictions of suspended sediment in Michigan rivers with limited data. However, the availability of the DSRCs from this study should not diminish the value of collecting physical samples and exploring alternative modeling approaches because of the uncertainty associated with using DSRCs.

Michigan↗

USGS2022

Sediment 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 reduce associated costs of dredging a sedimentation pond. During the study there were several factors that introduced uncertainty in the sampling results; however, the sampling results indicated there was an increase in the post-stream restoration sediment data because of higher streamflows during the post-stream than the pre-stream restoration monitoring period. The negative relation between suspended fines and streamflow was explained by a reduction in the supply of fines with increasing streamflows. The positive relation among suspended sand, bedload, and streamflow was because of those constituents having a functional relation with the hydraulic properties of flow and a consistent supply of sand. Two-dimensional flow modeling simulations indicated the downstream restored section had less shear stress, more pools, and could access the floodplain at a lower streamflow than the original channel. Overall, the uncertainty of the sampling results indicates the complexity of sediment transport in a river and suggests a need for multisite, multifaceted, multiyear data, and tools to simulate those data to effectively evaluate river restorations.

Minnesota↗

USGS2019

Using acoustic Doppler velocity meters to estimate suspended sediment along the lower Minnesota and Mississippi Rivers

Lake Pepin is the largest naturally formed lake on the Mississippi River and has complex management needs to satisfy economic, environmental, and cultural demands. Lake Pepin is filling in with sediment at a rapid rate compared to conditions before settlement by European immigrants and intense agricultural cultivation. Accordingly, the Minnesota Pollution Control Agency has developed aggressive plans to prioritize sediment sources, understand transport mechanisms, and implement large-scale strategies to reduce sedimentation in Lake Pepin. The Minnesota River is the primary sediment source to Lake Pepin, and reductions in sediment loading from the Minnesota River are needed to reduce sedimentation in Lake Pepin. Current loading estimates were calculated from grab sampling and total suspended solids laboratory methods that greatly underestimate the actual concentrations in the rivers when compared to U.S. Geological Survey width and depth integrated sampling and laboratory methods for determining suspended-sediment concentration (SSC). Therefore, the U.S. Geological Survey, with funding from the Environment and Natural Resources Trust Fund and in cooperation with the U.S. Army Corps of Engineers, Lower Minnesota River Watershed District, Minnesota Pollution Control Agency, and Minnesota Department of Natural Resources, collected SSCs and acoustic backscatter data from acoustic Doppler velocity meters over a 2-year period at nine sites. The purpose of the study was to improve understanding of sediment-transport processes and increase accuracy of estimating SSCs and suspended-sediment loads for the lower Minnesota River and the Mississippi River compared to traditional measures. The study results indicated that acoustic backscatter worked well in estimating SSCs at sites not regulated by locks, dams, and lakes. The results also confirmed previous studies that determined most of the suspended-sediment loading into the Mississippi River is from the Minnesota River and the largest sediment sink is Lake Pepin. Suspended-sediment loading from site to site and year to year was often variable when compared to streamflow, which has been traditionally used to estimate SSC. As a result, this study demonstrates the value in having high temporal and spatial resolution of continuous sediment monitoring from acoustic devices to help manage the sources of sediment into Lake Pepin.

Minnesota River, Mississippi River↗

USGS2019

Sediment oxygen demand: A review of in situ methods

Sediment oxygen demand (SOD) plays a fundamental role in biological and chemical processes within the benthic layer of a water body. Land use, including agricultural land use, can affect SOD. However, a wide variety of approaches have been used for in situ SOD chamber construction and data collection, and modelers frequently use SOD values from the literature, without consideration of the differences in methods. Here, we review existing literature on SOD chambers (32 papers, 1974–2016), compare the differences between in situ and laboratory methods, evaluate the effects of in situ chamber mixing, and discuss common challenges associated with deployment. A cohesive in situ sealed chamber design for use with a multiparameter water-quality instrument is presented as an effort toward standardizing SOD methodology, an important consideration that may facilitate integration of SOD data sets among multiple research efforts.

Journal of Environmental Quality↗