Geology topics

Marian M. Domanski

Publications and source records attributed to Marian M. Domanski.

17 recordsLinked to original sources

USGS2025

Dynamic rating method for computing discharge and stage from time-series data

Ratings are used for several reasons in water-resources investigations. The simplest rating relates discharge to the stage of a river (the stage-discharge relation). From a pure hydrodynamics perspective, all rivers and streams have some form of hysteresis in the relation between stage and discharge because flow becomes unsteady as a flood wave passes. The stage-discharge relation is unable to represent hysteresis. However, a dynamic rating method can capture hysteresis, which is driven by the variable energy slope of a flood wave. A dynamic rating method called DYNPOUND, which accommodates compact and compound channel geometry, was developed by simplifying the one-dimensional Saint-Venant equations. The DYNPOUND method was developed in the Python programming language and computes discharge from stage and stage from discharge. Stage and discharge time series computed with this dynamic rating method were compared to the U.S. Geological Survey (USGS) published stage and discharge time series. The results from the DYNPOUND method were also compared to in-person field measurements of stage and discharge made at 10 USGS streamgages. DYNPOUND was calibrated for 10 USGS streamgages using published discharge time-series data computed with a simple rating method. The calibration objective was to minimize the mean squared logarithmic error (MSLE) of the DYNPOUND-computed discharge with respect to the discharge time series computed by a simple rating method. For each site, the calibration process also included comparing all field measurements within a selected water year to the corresponding DYNPOUND-computed discharge data points. The MSLE of the DYNPOUND-computed discharge time series for the 10 sites ranged from 8.51×10 −4 to 1.36×10 −1 . For each site, an event-based period was selected to compare the discharge time series computed with the dynamic rating method to discharge field measurements made at the streamgages; the range of MSLE for the 10 DYNPOUND-computed discharge sites was from 4.79×10 −4 to 2.30×10 −2 .

continental United States↗

USGS2024

Special Contributing Area Loading Program user’s manual

The Special Contributing Area Loading Program (SCALP) is a hydrologic routing program that simulates reservoir routing through a linear-reservoir-in-series method. The Java version of SCALP was developed to replicate and replace the functionality of an older version of the program written in Fortran. SCALP models flow through three reservoirs in series using an input runoff depth time series and information describing the hydrologic characteristics and sanitary flow for one or more land areas within a basin, supplied by the user. Each basin is herein referred to as a “Special Contributing Area” (SCA); the SCAs are a central concept in SCALP. Although flow through each SCA is routed separately, the user may simulate multiple SCAs in a batch simulation. The outputs of SCALP include information about flows through and overflows from the three reservoirs in the series.

Open-File Report↗

USGS2022

Dynamic rating method for computing discharge from time-series stage data

Ratings are used for a variety of reasons in water-resources investigations. The simplest rating relates discharge to the stage of the river. From a pure hydrodynamics perspective, all rivers and streams have some form of hysteresis in the relation between stage and discharge because of unsteady flow as a flood wave passes. Simple ratings are unable to represent hysteresis in a stage/discharge relation. A dynamic rating method is capable of capturing hysteresis owing to the variable energy slope caused by unsteady momentum and pressure. A dynamic rating method developed to compute discharge from stage for compact channel geometry, referred to as DYNMOD, previously has been developed through a simplification of the one-dimensional Saint-Venant equations. A dynamic rating method, which accommodates compound and compact channel geometry, referred to as DYNPOUND, has been developed through a similar simplification as a part of this study. The DYNMOD and DYNPOUND methods were implemented in the Python programming language. Discharge time series computed with the dynamic rating method implementations were then compared to simulated discharge time series and discrete discharge measurements made at U.S. Geological Survey streamgage sites. Four sets of stage and discharge time series were created using one-dimensional unsteady simulation software with compound channel geometry to compare the results of both dynamic rating methods to results from the full one-dimensional shallow water equations. Discharge time series were computed from stage time series using DYNMOD and DYNPOUND. DYNPOUND outperformed DYNMOD in all four scenarios. The minimum and maximum mean squared logarithmic error (MSLE) for the DYNMOD results were 2.75×10 −2 and 3.40×10 −2 , respectively. The minimum and maximum MSLE for the DYNPOUND results were 2.51×10 −7 and 1.91×10 −4 , respectively. The dynamic rating methods were calibrated for six U.S. Geological Survey streamgage sites using observed discharge data collected at the sites. The calibration objective for each site was to minimize the MSLE of the discharge computed with the rating method with respect to observed discharge. For each site, the calibration included all field measurements within a selected water year. The DYNMOD method failed to compute discharge for the full calibration time series for three sites. A method fails to compute when the implementation returns a nonfinite value at a time step. Because the values computed for following time steps are dependent on the previous time step, a nonfinite value results in nonfinite values that follow. For the three sites for which DYNMOD computed the complete discharge time series, the minimum MSLE for calibration was 2.19×10 −3 and the maximum was 9.77×10 −3 . The MSLE of the DYNPOUND computed discharge calibration time series for the six sites ranged from 3.70×10 −3 to 1.25. For each site, an event-based time period was selected to compare the discharge time series computed with the dynamic rating methods to discrete discharge field measurements made at the streamgage sites. The DYNMOD-computed discharge time series for the three sites had an MSLE range of 2.76×10 −3 to 3.14×10 −2 . The range of MSLE for the six DYNPOUND sites was 3.64×10 −3 to 7.23×10 −2 . Although the DYNMOD method outperforms the DYNPOUND method when calibrated streamgage sites are under consideration, the DYNMOD method failed to compute a discharge time series at three of the six sites. The DYNPOUND method, therefore, was more robust than the DYNMOD method. Improvements to the implementation of the DYNPOUND method may improve the accuracy of the method.

Open-File Report↗

USGS2021

Fluvial Egg Drift Simulator (FluEgg) user’s manual

The Fluvial Egg Drift Simulator (FluEgg) was developed to simulate the transport and dispersion of invasive carp eggs and larvae in a river. FluEgg currently (2020) supports modeling of bighead carp ( Hypophthalmichthys nobilis ), silver carp ( H. molitrix ), and grass carp ( Ctenopharyngodon idella ), with the planned addition of black carp ( Mylopharyngodon piceus ) once developmental data are available. FluEgg integrates the biological development of invasive carp eggs and larvae with a particle transport model that simulates the advection and dispersion of the eggs and larvae based on user-supplied one-dimensional hydraulic conditions. FluEgg can be used to evaluate the hydrodynamic suitability of a river for invasive carp spawning, to inform sampling and monitoring efforts, and to identify the most likely spawning areas of captured eggs or larvae.

Open-File Report↗

USGS2020

DTSGUI: A python program to process and visualize fiber‐optic distributed temperature sensing data

Fiber‐optic distributed temperature sensing (FO‐DTS) has proven to be a transformative technology for the hydrologic sciences, with application to diverse problems including hyporheic exchange, groundwater/surface‐water interaction, fractured‐rock characterization, and cold regions hydrology. FO‐DTS produces large, complex, and information‐rich datasets. Despite the potential of FO‐DTS, adoption of the technology has been impeded by lack of tools for data processing, analysis, and visualization. New tools are needed to efficiently and fully capitalize on the information content of FO‐DTS datasets. To this end, we present DTSGUI, a public‐domain Python‐based software package for editing, parsing, processing, statistical analysis, georeferencing, and visualization of FO‐DTS data.

Groundwater↗

USGS2019

Time-series sediment acoustics and LISST-ABS testing

Acoustics and other surrogates can be used to accurately and cost-effectively provide time-series estimates of suspended-sediment concentration and load, which is essential for creating informed solutions to many sediment-related environmental, engineering, and agricultural concerns. Interagency efforts in recent years have advanced the testing, methods development, operational guidelines, and training on sediment acoustics. This extended abstract provides an update on horizontal profiling methodologies and introduces the testing of the LISST-ABS (Acoustic Backscatter Sensor).

Conference Paper↗

USGS2019

Measuring suspended sediment in sand-bedded rivers using down-looking acoustic doppler current profilers

The use of side-looking acoustic Doppler velocity meters (ADVMs) to estimate fluvial suspended-sediment concentrations (SSC) has become more operational by the U.S. Geological Survey in recent years; however, direct transfer of these techniques to down-looking acoustic Doppler current profilers (ADCPs) currently is not widely feasible. Key assumptions in the sidelooking ADVM method related to sediment homogeneity within the acoustic measurement volume are almost never met in wide, sand-bedded rivers because SSC and particle size commonly vary with depth and location in the river cross section. The use of ADCPs to estimate SSC has been investigated by researchers, but the requirements and limitations of an operational method that could be successfully applied at many locations are not well defined. If an operational method could be developed, the use of ADCPs, which are routinely used for flow measurements, would revolutionize sediment science by providing rapid measurements of sediment flux and spatial distribution. We collected detailed datasets in six sand-bedded rivers in the U.S. in 2016-2018, to evaluate the efficacy of using down-looking ADCPs of multiple frequencies to estimate SSC. The datasets included replicate sets of point and depth-integrated suspended-sediment samples and stationary and cross-sectional backscatter profiles using multiple ADCPs with differing frequencies. Reasonable calibrations were developed at all sites measured when calibrating to the coarse fraction (R2 0.66 to 0.98 with slopes close to 0.1 using 1200kHz ADCPs). Calibrations to the fines fraction were problematic because acoustic backscatter response was dominated by coarse particles when present, and substantial attenuation was contributed by coarse particles at some sites. A sensitivity analysis on minimum datasets showed that good calibrations could be developed using two verticals of data collected over a range of backscatter and sediment conditions, with a minimum of three points sampled for sediment within each vertical. Overall, results to date show great promise in using ADCPs to rapidly estimate and visualize SSC with high spatial resolution, and a new beta software tool called Sediment Transect Acoustics simplifies data processing. Improvements are underway to the beta software used in processing to allow incorporation of more acoustic and sediment characteristics and to estimate SSC in areas of the river cross section unmeasured by the ADCP.

Conference Paper↗

USGS2017

FEQinput—An editor for the full equations (FEQ) hydraulic modeling system

Introduction The Full Equations Model (FEQ) is a computer program that solves the full, dynamic equations of motion for one-dimensional unsteady hydraulic flow in open channels and through control structures. As a result, hydrologists have used FEQ to design and operate flood-control structures, delineate inundation maps, and analyze peak-flow impacts. To aid in fighting floods, hydrologists are using the software to develop a system that uses flood-plain models to simulate real-time streamflow. Input files for FEQ are composed of text files that contain large amounts of parameters, data, and instructions that are written in a format exclusive to FEQ. Although documentation exists that can aid in the creation and editing of these input files, new users face a steep learning curve in order to understand the specific format and language of the files. FEQinput provides a set of tools to help a new user overcome the steep learning curve associated with creating and modifying input files for the FEQ hydraulic model and the related utility tool, Full Equations Utilities (FEQUTL).

Fact Sheet↗

USGS2017

Development and evaluation of a reservoir model for the Chain of Lakes in Illinois

Forecasts of flows entering and leaving the Chain of Lakes reservoir on the Fox River in northeastern Illinois are critical information to water-resource managers who determine the optimal operation of the dam at McHenry, Illinois, to help minimize damages to property and loss of life because of flooding on the Fox River. In 2014, the U.S. Geological Survey; the Illinois Department of Natural Resources, Office of Water Resources; and National Weather Service, North Central River Forecast Center began a cooperative study to develop a system to enable engineers and planners to simulate and communicate flows and to prepare proactively for precipitation events in near real time in the upper Fox River watershed. The purpose of this report is to document the development and evaluation of the Chain of Lakes reservoir model developed in this study. The reservoir model for the Chain of Lakes was developed using the Hydrologic Engineering Center–Reservoir System Simulation program. Because of the complex relation between the dam headwater and reservoir pool elevations, the reservoir model uses a linear regression model that relates dam headwater elevation to reservoir pool elevation. The linear regression model was developed using 17 U.S. Geological Survey streamflow measurements, along with the gage height in the reservoir pool and the gage height at the dam headwater. The Nash-Sutcliffe model efficiency coefficients for all three linear regression model variables ranged from 0.90 to 0.98. The reservoir model performance was evaluated by graphically comparing simulated and observed reservoir pool elevation time series during nine periods of high pool elevation. In addition, the peak elevations during these time periods were graphically compared to the closest-in-time observed pool elevation peak. The mean difference in the simulated and observed peak elevations was -0.03 feet, with a standard deviation of 0.19 feet. The Nash-Sutcliffe coefficient for peak prediction was calculated as 0.94. Evaluation of the model based on accuracy of peak prediction and the ability to simulate an elevation time series showed the performance of the model was satisfactory.

Illinois↗

USGS2016

Estimating suspended sediment using acoustics in a fine-grained riverine system, Kickapoo Creek at Bloomington, Illinois

Acoustic technologies have the potential to be used as a surrogate for measuring suspended-sediment concentration (SSC). This potential was examined in a fine-grained (97-100 percent fines) riverine system in central Illinois by way of installation of an acoustic instrument. Acoustic data were collected continuously over the span of 5.5 years. Acoustic parameters were regressed against SSC data to determine the accuracy of using acoustic technology as a surrogate for measuring SSC in a fine-grained riverine system. The resulting regressions for SSC and sediment acoustic parameters had coefficients of determination ranging from 0.75 to 0.97 for various events and configurations. The overall Nash-Sutcliffe model-fit efficiency was 0.95 for the 132 observed and predicted SSC values determined using the sediment acoustic parameter regressions. The study of using acoustic technologies as a surrogate for measuring SSC in fine-grained riverine systems is ongoing. The results at this site are promising in the realm of surrogate technology.

Illinois↗

USGS2016

Sediment acoustic index method for computing continuous suspended-sediment concentrations

Suspended-sediment characteristics can be computed using acoustic indices derived from acoustic Doppler velocity meter (ADVM) backscatter data. The sediment acoustic index method applied in these types of studies can be used to more accurately and cost-effectively provide time-series estimates of suspended-sediment concentration and load, which is essential for informed solutions to many sediment-related environmental, engineering, and agricultural concerns. Advantages of this approach over other sediment surrogate methods include: (1) better representation of cross-sectional conditions from large measurement volumes, compared to other surrogate instruments that measure data at a single point; (2) high temporal resolution of collected data; (3) data integrity when biofouling is present; and (4) less rating curve hysteresis compared to streamflow as a surrogate. An additional advantage of this technique is the potential expansion of monitoring suspended-sediment concentrations at sites with existing ADVMs used in streamflow velocity monitoring. This report provides much-needed standard techniques for sediment acoustic index methods to help ensure accurate and comparable documented results. A sediment acoustic index gage is used to collect continuous acoustic backscatter data, using an ADVM deployed in a fixed location, which are related to results from discrete suspended-sediment samples. The raw ADVM backscatter data are adjusted for variables affecting backscatter other than the sediment concentration to compute the sediment-corrected backscatter ( SCB ) and sediment attenuation coefficient ( SAC ). The sediment acoustic index rating (rating) is then developed by relating the sediment characteristics from the periodic samples to the SCB and (or) SAC and other explanatory variables in a site-specific, instrument-specific, simple or multiple linear regression model. The rating is reviewed and checked to ensure the technique has been applied appropriately. This review includes an assessment of the theoretical soundness, the adequacy of the model calibration dataset, and the quality of the regression model and regression diagnostics. The rating can then be applied to the acoustic surrogates and other explanatory variables to obtain continuous records of computed suspended-sediment concentration. The estimates of suspended-sediment concentration can then be paired with streamflow data, if available, to compute continuous records of suspended-sediment load. Once developed, sediment acoustic index ratings must be validated with additional suspended-sediment samples, beyond the period of record used in the rating development, to verify that the regression model continues to adequately represent sediment conditions within the stream. Changes in ADVM configuration or installation, or replacement with another ADVM, may require development of a new rating. The best practices described in this report can be used to develop continuous estimates of suspended-sediment concentration and load using sediment acoustic surrogates to enable more informed and accurate responses to diverse sedimentation issues.

Techniques and Methods↗

USGS2015

Surrogate Analysis and Index Developer (SAID) tool

The use of acoustic and other parameters as surrogates for suspended-sediment concentrations (SSC) in rivers has been successful in multiple applications across the Nation. Tools to process and evaluate the data are critical to advancing the operational use of surrogates along with the subsequent development of regression models from which real-time sediment concentrations can be made available to the public. Recent developments in both areas are having an immediate impact on surrogate research and on surrogate monitoring sites currently (2015) in operation. The Surrogate Analysis and Index Developer (SAID) standalone tool, under development by the U.S. Geological Survey (USGS), assists in the creation of linear regression models that relate constituent and surrogate parameters by providing visual and quantitative diagnostics to the user. SAID also processes acoustic parameters to be used as explanatory variables for SSC. The sediment acoustic method utilizes acoustic parameters from fixed-mount stationary equipment. The theory and method used by the SAID tool have been described in recent publications. The tool also serves to support sediment-acoustic-index methods and other surrogate guidelines such as turbidity and SSC (Rasmussen and others, 2009). The regression models created in SAID can be used in utilities that have been developed to work with the USGS National Water Information System (NWIS) and for the USGS National Real-Time Water Quality (NRTWQ) Web site. The real-time dissemination of predicted SSC and prediction intervals for each time step has substantial potential to improve understanding of sediment-related water quality and associated engineering and ecological management decisions.

Open-File Report↗

USGS2015

Comparison of fluvial suspended-sediment concentrations and particle-size distributions measured with in-stream laser diffraction and in physical samples

Laser-diffraction technology, recently adapted for in-stream measurement of fluvial suspended-sediment concentrations (SSCs) and particle-size distributions (PSDs), was tested with a streamlined (SL), isokinetic version of the Laser In-Situ Scattering and Transmissometry (LISST) for measuring volumetric SSCs and PSDs ranging from 1.8-415 µm in 32 log-spaced size classes. Measured SSCs and PSDs from the LISST-SL were compared to a suite of 22 datasets (262 samples in all) of concurrent suspended-sediment and streamflow measurements using a physical sampler and acoustic Doppler current profiler collected during 2010-12 at 16 U.S. Geological Survey streamflow-gaging stations in Illinois and Washington (basin areas: 38 – 69,264 km 2 ). An unrealistically low computed effective density (mass SSC / volumetric SSC) of 1.24 g/ml (95% confidence interval: 1.05-1.45 g/ml) provided the best-fit value (R 2 = 0.95; RMSE = 143 mg/L) for converting volumetric SSC to mass SSC for over 2 orders of magnitude of SSC (12-2,170 mg/L; covering a substantial range of SSC that can be measured by the LISST-SL) despite being substantially lower than the sediment particle density of 2.67 g/ml (range: 2.56-2.87 g/ml, 23 samples). The PSDs measured by the LISST-SL were in good agreement with those derived from physical samples over the LISST-SL's measureable size range. Technical and operational limitations of the LISST-SL are provided to facilitate the collection of more accurate data in the future. Additionally, the spatial and temporal variability of SSC and PSD measured by the LISST-SL is briefly described to motivate its potential for advancing our understanding of suspended-sediment transport by rivers.

Water Resources Research↗

USGS2015

Large-scale dam removal on the Elwha River, Washington, USA: fluvial sediment load

The Elwha River restoration project, in Washington State, includes the largest dam-removal project in United States history to date. Starting September 2011, two nearly century-old dams that collectively contained 21 ± 3 million m 3 of sediment were removed over the course of three years with a top-down deconstruction strategy designed to meter the release of a portion of the dam-trapped sediment. Gauging with sediment-surrogate technologies during the first two years downstream from the project measured 8,200,000 ± 3,400,000 tonnes of transported sediment, with 1,100,000 and 7,100,000 t moving in years 1 and 2, respectively, representing 3 and 20 times the Elwha River annual sediment load of 340,000 ± 80,000 t/y. During the study period, the discharge in the Elwha River was greater than normal (107% in year 1 and 108% in year 2); however, the magnitudes of the peak-flow events during the study period were relatively benign with the largest discharge of 292 m 3 /s (73% of the 2-year annual peak-flow event) early in the project when both extant reservoirs still retained sediment. Despite the muted peak flows, sediment transport was large, with measured suspended-sediment concentrations during the study period ranging from 44 to 16,300 mg/L and gauged bedload transport as large as 24,700 t/d. Five distinct sediment-release periods were identified when sediment loads were notably increased (when lateral erosion in the former reservoirs was active) or reduced (when reservoir retention or seasonal low flows and cessation of lateral erosion reduced sediment transport). Total suspended-sediment load was 930,000 t in year 1 and 5,400,000 t in year 2. Of the total 6,300,000 ± 3,200,000 t of suspended-sediment load, 3,400,000 t consisted of silt and clay and 2,900,000 t was sand. Gauged bedload on the lower Elwha River in year 2 of the project was 450,000 ± 360,000 t. Bedload was not quantified in year 1, but qualitative observations using bedload-surrogate instruments indicated detectable bedload starting just after full removal of the downstream dam. Using comparative studies from other sediment-laden rivers, the total ungauged fraction of < 2-mm bedload was estimated to be on the order of 1.5 Mt.

Washington↗

USGS2015

Continuous monitoring of sediment and nutrients in the Illinois River at Florence, Illinois, 2012-13

The Illinois River is the largest river in Illinois and is the primary contributing watershed for nitrogen, phosphorus, and suspended-sediment loading to the upper Mississippi River from Illinois. In addition to streamflow, the following water-quality constituents were monitored at the Illinois River at Florence, Illinois (U.S. Geological Survey station number 05586300), during May 2012–October 2013: phosphate, nitrate, turbidity, temperature, specific conductance, pH, and dissolved oxygen. The objectives of this monitoring were to (1) determine performance capabilities of the in-situ instruments; (2) collect continuous data that would provide an improved understanding of constituent characteristics during normal, low-, and high-flow periods and during different climatic and land-use seasons; (3) evaluate the ability to use continuous turbidity as a surrogate constituent to determine suspended-sediment concentrations; and (4) evaluate the ability to develop a regression model for total phosphorus using phosphate, turbidity, and other measured parameters. Reliable data collection was achieved, following some initial periods of instrument and data-communication difficulties. The resulting regression models for suspended sediment had coefficient of determination (R 2 ) values of about 0.9. Nitrate plus nitrite loads computed using continuous data were found to be approximately 8 percent larger than loads computed using traditional discrete-sampling based models. A regression model for total phosphorus was developed by using historic orthophosphate data (important during periods of low flow and low concentrations) and historic suspended-sediment data (important during periods of high flow and higher concentrations). The R 2 of the total phosphorus regression model using orthophosphorus and suspended sediment was 0.8. Data collection and refinement of the regression models is ongoing.

Illinois↗

USGS2015

Surrogate analysis and index developer (SAID) tool and real-time data dissemination utilities

The use of acoustic and other parameters as surrogates for suspended-sediment concentrations (SSC) in rivers has been successful in multiple applications across the Nation. Critical to advancing the operational use of surrogates are tools to process and evaluate the data along with the subsequent development of regression models from which real-time sediment concentrations can be made available to the public. Recent developments in both areas are having an immediate impact on surrogate research, and on surrogate monitoring sites currently in operation. The Surrogate Analysis and Index Developer (SAID) standalone tool, under development by the U.S. Geological Survey (USGS), assists in the creation of regression models that relate response and explanatory variables by providing visual and quantitative diagnostics to the user. SAID also processes acoustic parameters to be used as explanatory variables for suspended-sediment concentrations. The sediment acoustic method utilizes acoustic parameters from fixed-mount stationary equipment. The background theory and method used by the tool have been described in recent publications, and the tool also serves to support sediment-acoustic-index methods being drafted by the multi-agency Sediment Acoustic Leadership Team (SALT), and other surrogate guidelines like USGS Techniques and Methods 3-C4 for turbidity and SSC. The regression models in SAID can be used in utilities that have been developed to work with the USGS National Water Information System (NWIS) and for the USGS National Real-Time Water Quality (NRTWQ) Web site. The real-time dissemination of predicted SSC and prediction intervals for each time step has substantial potential to improve understanding of sediment-related water-quality and associated engineering and ecological management decisions.

Conference Paper↗

USGS2013

Ultimate pier and contraction scour prediction in cohesive soils at selected bridges in Illinois

The Scour Rate In COhesive Soils-Erosion Function Apparatus (SRICOS-EFA) method includes an ultimate scour prediction that is the equilibrium maximum pier and contraction scour of cohesive soils over time. The purpose of this report is to present the results of testing the ultimate pier and contraction scour methods for cohesive soils on 30 bridge sites in Illinois. Comparison of the ultimate cohesive and noncohesive methods, along with the Illinois Department of Transportation (IDOT) cohesive soil reduction-factor method and measured scour are presented. Also, results of the comparison of historic IDOT laboratory and field values of unconfined compressive strength of soils (Qu) are presented. The unconfined compressive strength is used in both ultimate cohesive and reduction-factor methods, and knowing how the values from field methods compare to the laboratory methods is critical to the informed application of the methods. On average, the non-cohesive method results predict the highest amount of scour, followed by the reduction-factor method results; and the ultimate cohesive method results predict the lowest amount of scour. The 100-year scour predicted for the ultimate cohesive, noncohesive, and reduction-factor methods for each bridge site and soil are always larger than observed scour in this study, except 12% of predicted values that are all within 0.4 ft of the observed scour. The ultimate cohesive scour prediction is smaller than the non-cohesive scour prediction method for 78% of bridge sites and soils. Seventy-six percent of the ultimate cohesive predictions show a 45% or greater reduction from the non-cohesive predictions that are over 10 ft. Comparing the ultimate cohesive and reduction-factor 100-year scour predictions methods for each bridge site and soil, the scour predicted by the ultimate cohesive scour prediction method is less than the reduction-factor 100-year scour prediction method for 51% of bridge sites and soils. Critical shear stress remains a needed parameter in the ultimate scour prediction for cohesive soils. The unconfined soil compressive strength measured by IDOT in the laboratory was found to provide a good prediction of critical shear stress, as measured by using the erosion function apparatus in a previous study. Because laboratory Qu analyses are time-consuming and expensive, the ability of field-measured Rimac data to estimate unconfined soil strength in the critical shear–soil strength relation was tested. A regression analysis was completed using a historic IDOT dataset containing 366 data pairs of laboratory Qu and field Rimac measurements from common sites with cohesive soils. The resulting equations provide a point prediction of Qu, given any Rimac value with the 90% confidence interval. The prediction equations are not significantly different from the identity Qu = Rimac. The alternative predictions of ultimate cohesive scour presented in this study assume Qu will be estimated using Rimac measurements that include computed uncertainty. In particular, the ultimate cohesive predicted scour is greater than observed scour for the entire 90% confidence interval range for predicting Qu at the bridges and soils used in this study, with the exception of the six predicted values that are all within 0.6 ft of the observed scour.

Illinois↗