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Title:Predicting suspended sediment in Illinois rivers using dimensionless rating curves
Author(s):Jenkins, Emily Poynter
Director of Research:Kalita, Prasanta K.
Doctoral Committee Chair(s):Kalita, Prasanta K.
Doctoral Committee Member(s):Bartosova, Alena; Czapar, George; Bhattarai, Rabin
Department / Program:Engineering Administration
Discipline:Agricultural & Biological Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Dimensionless sediment rating curve
Illinois
river
suspended sediment concentration
geomorphic parameters
seasonal effects
Pagosa dimensionless sediment rating curve
Abstract:Suspended sediment concentrations in Illinois are a serious concern to the environment and navigability of Illinois rivers, the Mississippi River and the Gulf of Mexico. Therefore, understanding the amount of sediment in a river is important. Measuring the sediment, though, can be a lengthy, time-consuming, and expensive process. In this study, dimensionless suspended sediment concentrations are predicted in Illinois by creating dimensionless suspended sediment rating curves. Suspended sediment concentration (SSC) data, collected by the Illinois State Water Survey monitoring program, and discharge data, collected by the U.S. Geological Survey (USGS), from ten sites across the state of Illinois are used in the sediment rating curve analysis. Field measurements of bankfull height at each site were taken and cross-referenced with the USGS discharge to determine bankfull discharge. The suspended sediment concentration at that bankfull discharge is referred to as the bankfull suspended sediment concentration. Data at each site were normalized by dividing discharges and sediment concentrations by bankfull flow and bankfull suspended sediment concentrations, respectively. The first objective in this study is to examine if geomorphic and hydraulic parameters can increase the predictability of dimensionless suspended sediment concentrations from dimensionless discharges for rivers within Illinois. Rating curves using non-linear least squares regression with an additive coefficient for individual watersheds, when limiting discharge data to either the rising limb or falling limb of the hydrograph yielded predictive sediment models. The data from all watersheds were then combined and normalized to create a dimensionless sediment rating curve for Illinois. Model efficiency was low, but improved when data was subdivided by landuse, channel slope, or drainage area. Forested watersheds of less than 1000 square miles with channel slopes greater than 0.0004 trended toward the most predictive dimensionless sediment rating curves for Illinois rivers. The second objective is to evaluate the effect of seasons on dimensionless suspended sediment rating curves. Nash-Sutcliffe efficiency coefficients were as high as 0.93 for non-linear with an additive coefficient regression models when individual watersheds are evaluated using data from summer months only (April – September). Sediment rating curve model efficiency was also high for combined watershed data when subdivided into two seasons: winter and summer. The similarities in precipitation and runoff during the summer months (April – September), as opposed to the winter months (October – March), assists in creating a predictive model for suspended sediment concentrations during each of those timeframes. The third objective is to compare Illinois dimensionless suspended sediment rating curves to previous research performed on Colorado streams (Rosgen, 2007) to determine if one dimensionless rating curve is applicable to rivers in multiple locations across the United States. When the Colorado dimensionless sediment rating curve was compared to the ten studied Illinois watersheds, few similarities were found. Additional smaller watersheds within Illinois were compared to the Colorado curves, however, and show close visual agreement between modeled data and measured data. Quantification of the model efficiency for the small Illinois watersheds indicates that the Colorado curves have low predictability for Illinois streams. Overall, Illinois rivers create unique challenges for developing dimensionless sediment rating curves. The sand, silt and clay in the streambank and bed of Illinois rivers makes is easy for sediment particles to become suspended and remain suspended in the water column. Variability of management techniques between farm fields, rainfall distribution across large drainage areas, and in-stream disturbances contributing to sediment suspension (ie. log jams, animal activity, low-flow crossings) all hinder the predictability of a single sediment rating curve for Illinois rivers. Further study on small watersheds or on multiple locations of a single watershed will help to limit variability in the model and may lead to a more predictive solution to predicting suspended sediment concentrations within Illinois rivers.
Issue Date:2015-07-10
Type:Thesis
URI:http://hdl.handle.net/2142/88014
Rights Information:Copyright 2015 Emily Poynter Jenkins
Date Available in IDEALS:2015-09-29
Date Deposited:August 201


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