U.S. Department of the Interior 

U.S. Geological Survey 

Scientific Investigations Report 2016–5177 

Prepared in cooperation with the Texas Water Development Board and the 

Galveston Bay Estuary Program 

Characterization of Streamflow, Suspended Sediment, and 

Nutrients Entering Galveston Bay from the Trinity River, 

Texas, May 2014–December 2015 
Cover. U.S. Army Corps of Engineers navigational locks near U.S. Geological Survey streamflow-gaging 

station 08067252 Trinity River at Wallisville, Texas. 
Characterization of Streamflow, Suspended 

Sediment, and Nutrients Entering 

Galveston Bay from the Trinity River, Texas, 

May 2014–December 2015 

By Zulimar Lucena and Michael T. Lee 

Prepared in cooperation with the Texas Water Development Board and the 

Galveston Bay Estuary Program 

Scientific Investigations Report 2016–5177 

U.S. Department of the Interior 

U.S. Geological Survey 
U.S. Department of the Interior 

SALLY JEWELL, Secretary 

U.S. Geological Survey 

Suzette M. Kimball, Director 

U.S. Geological Survey, Reston, Virginia: 2017 

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Suggested citation:
 

Lucena, Zulimar, and Lee, M.T., 2017, Characterization of streamflow, suspended sediment, and nutrients entering 


Galveston Bay from the Trinity River , Texas, May 2014–December 2015: U.S. Geological Survey Scientific 


Investigations Report 2016–5177, 38 p., https://doi.org/10.3133/sir20165177.
 

ISSN 2328-031X (print) 

ISSN 2328-0328 (online) 

ISBN 978-1-4113-4107-4 

Photograph, preceding page: U.S. Geological Survey streamflow-gaging station 08067252 Trinity River 

at Wallisville, Texas, during a high-flow event. 
iii 

Contents 

Abstract...........................................................................................................................................................1
 

Introduction.....................................................................................................................................................2
 

Purpose and Scope ..............................................................................................................................3
 

Description of the Study Area ............................................................................................................3
 

Previous Studies ...................................................................................................................................5
 

Methods...........................................................................................................................................................5
 

Analytical Methods...............................................................................................................................7
 

Quality Control.......................................................................................................................................7
 

Suspended-Sediment Acoustic Surrogate Methods .....................................................................9
 

Instrument Configuration............................................................................................................9
 

Acoustic Surrogate Model Development and Evaluation.....................................................9
 

Streamflow Characterization in the Lower Trinity River Watershed...................................................11
 

Suspended-Sediment Concentrations and Loads..................................................................................13
 

Suspended-Sediment Acoustic Surrogate Model Results..........................................................15
 

Continuous Suspended-Sediment Concentrations..............................................................16
 

Suspended-Sediment Loads....................................................................................................18
 

Characterization of Water-Quality Conditions .......................................................................................20
 

Field Properties ...................................................................................................................................20
 

Nutrients...............................................................................................................................................20
 

Summary .......................................................................................................................................................24
 

References Cited..........................................................................................................................................25
 

Appendix 1. Model Archival Summary for Suspended-Sediment Concentration 


at U.S. Geological Survey Streamflow-Gaging Station 08067252 Trinity River 


at Wallisville, Texas........................................................................................................................29
 

Figures 

1.	 Map showing location of monitoring sites in the lower Trinity River watershed 


downstream from Lake Livingston, Texas ................................................................................4
 

2.	 Map showing wetland cover and classification in the lower Trinity River 


watershed downstream from Lake Livingston, Texas ............................................................6
 

3.	 Photographs showing the A, data collection platform and B, Acoustic Doppler 


velocity meter installed at U.S. Geological Survey streamflow-gaging 


station 08067252 Trinity River at Wallisville, Texas................................................................10
 

4.	 Graph showing annual daily mean discharge at U.S. Geological Survey streamflowgaging station 08066250 Trinity River near Goodrich, Texas, 1966–2015 ...........................12
 

5.	 Graph showing instantaneous discharge at U.S. Geological Survey streamflowgaging stations in the lower Trinity River watershed, Texas, May 2014– 

December 2015............................................................................................................................12 

6.	 Graph showing discharge-duration curve indicating the streamflow at which 


each sample was collected at U.S. Geological Survey streamflow-gaging 


station 08067252 Trinity River at Wallisville, Texas, May 2014–December 2015...............14
 
7.	 Graph showing relation between sand-fine separation results and discharge 

measured at U.S. Geological Survey streamflow-gaging station 08067252 

Trinity River at Wallisville, Texas, May 2014–December 2015.............................................14 

8.	 Estimated suspended-sediment concentrations for residual plot and normal 

probability plot for a multiple linear regression model developed for the Trinity 

River at U.S. Geological Survey streamflow-gaging station 08067252 Trinity River 

at Wallisville, Texas, May 2014–December 2015 ...................................................................16 

9.	 Graph showing estimated and measured suspended-sediment concentrations 

determined from a multiple linear regression model at U.S. Geological Survey 

streamflow-gaging station 08067252 Trinity River at Wallisville, Texas.............................16 

10.	 Example of acoustic backscatter profiles from Acoustic Doppler current profiler 

showing backscatter distributions in cross sections at discharges of 2,370 cubic 

feet per second (ft

3

/s), and 13,700 ft

3

/s....................................................................................17 

11.	 Graph showing suspended-sediment concentrations estimated by using a 

regression model developed for the Trinity River at U.S. Geological Survey 

streamflow-gaging station 08067252 Trinity River at Wallisville, Texas, 

January–December 2015...........................................................................................................18 

12.	 Graph showing estimated monthly suspended-sediment loads at U.S. Geological 

Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas, 

May 2014–December 2015 ........................................................................................................19 

13.	 Graphs showing time series depicting concentrations of total nitrogen; total 


phosphorus; and associated daily mean discharge for samples collected at 


U.S. Geological Survey streamflow-gaging station 08067252 Trinity River at 

Wallisville, Texas, May 2014–December 2015........................................................................21 

14.	 Graph showing percentages of nitrogen constituents in water-quality samples 

collected at U.S. Geological Survey streamflow-gaging station 08067252 Trinity 

River at Wallisville, Texas, May 2014–December 2015.........................................................23 

15.	 Graph showing relation between phosphorus concentrations and suspendedsediment concentrations at U.S. Geological Survey streamflow-gaging station 

08067252 Trinity River at Wallisville, Texas, May 2014–December 2015............................23 

1–1.	 Streamflow and sediment corrected backscatter duration curves at U.S. 

Geological Survey streamflow-gaging station 08067252 Trinity River at 

Wallisville, Texas, May 2014–December 2015........................................................................30 

1–2.	 Diagnostics plots for selected regression model developed for U.S. Geological 

Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas ...............34 

1–3.	 Model predicted and measured suspended-sediment concentrations at U.S. 

Geological Survey streamflow-gaging station 08067252 Trinity River at 

Wallisville, Texas.........................................................................................................................35 

1–4.	 Continuous suspended-sediment concentration record at U.S. Geological 

Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas, 

January–December 2015...........................................................................................................37 

iv 
v 

Tables 

1.	 Description of monitoring sites in the lower Trinity River watershed downstream 


from Lake Livingston, Texas, May 2014–December 2015.......................................................5
 

2.	 Analytes measured, sample treatment and preservation, analytical methods, 


and reporting limits for samples collected at U.S. Geological Survey streamflowgaging station 08067252 Trinity River at Wallisville, Texas ....................................................8
 

3.	 Peak discharges measured at U.S. Geological Survey streamflow-gaging stations 


in the lower Trinity River watershed, Texas, May 2014–December 2015 ..........................13
 

4.	 Results from suspended-sediment size analysis for selected samples in U.S. 


Geological Survey streamflow-gaging station 08067252 Trinity River at Wallisville, 


Texas, April 3, 2015–June 10, 2015 ...........................................................................................15
 

5.	 Summary of linear regression evaluation statistics for equation using 


discharge and sediment corrected backscatter to estimate suspended-


sediment concentration in U.S. Geological Survey streamflow-gaging 


station 08067252 Trinity River at Wallisville, Texas, May 2014–December 2015...............16
 

6.	 Suspended-sediment load during high-flow events at U.S. Geological Survey 

streamflow-gaging station 08067252, Trinity River at Wallisville, Texas, May 2014– 

December 2015............................................................................................................................19 

7.	 Summary statistics for water-quality field properties measured at U.S. Geological 


Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas, 


May 2014–December 2015 ........................................................................................................20
 

8.	 Summary statistics for nutrient parameters measured in the Trinity River at 


Wallisville, Texas, May 2014–December 2015........................................................................20
 

1–1. Acoustic Doppler velocity meter specifications ...................................................................30
 

1–2. Acoustic Doppler velocity meter configuration settings. ....................................................30
 

1–3. Summary statistics for suspended-sediment concentration data collected at 


U.S. Geological Survey streamflow-gaging station 08067252 Trinity River at 


Wallisville, Texas, May 2014–December 2015........................................................................30
 

1–4. Acoustic Doppler velocity meter settings used to process backscatter data 


with the Surrogate Analysis and Index Developer tool........................................................31
 

1–5. Alternatives models considered for estimating suspended-sediment 


concentrations at U.S. Geological Survey streamflow-gaging station 08067252 


Trinity River at Wallisville, Texas..............................................................................................31
 

1–6. Suspended-sediment regression model and nonparametric smearing bias 


correction factor for U.S. Geological Survey streamflow-gaging station 08067252
 

Trinity River at Wallisville, Texas..............................................................................................32
 

1–7. Summary statistics for the selected model and statistical measures to evaluate 


the suspended-sediment regression model for U.S. Geological Survey streamflowgaging station 08067252 Trinity River at Wallisville, Texas ..................................................33
 

1–8. Calibration data used for suspended-sediment model development at U.S. 


Geological Survey streamflow-gaging station 08067252 Trinity River at Wallisville, 


Texas and selected statistical results.....................................................................................35
 
 

vi 

Conversion Factors 

U.S. customary units to International System of Units 

Multiply By To obtain 

Length 

inch (in.) 25.4 millimeter (mm) 

foot (ft) 0.3048 meter (m) 

mile (mi) 1.609 kilometer (km) 

Area 

square mile (mi2

) 259.0 hectare (ha) 

square mile (mi2

) 2.590 square kilometer (km2) 

Volume 

acre-foot (acre-ft) 1,233 cubic meter (m3

) 

Flow rate 

foot per second (ft/s) 0.3048 meter per second (m/s) 

cubic foot per second (ft3

/s) 0.02832 cubic meter per second (m3/s) 

Mass 

ton, short (2,000 lb) 0.9072 metric ton (t) 

International System of Units to U.S. customary units 

Multiply By To obtain 

Length 

millimeter (mm) 

meter (m) 

0.03937 

3.281 

inch (in.) 

foot (ft) 

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows: 

°F = (1.8 × °C) + 32. 

Datum 

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83) 

and the North American Datum of 1927 (NAD 27). 

Supplemental Information 

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius 

(μS/cm at 25 °C). 

Concentrations of chemical constituents in water are given in milligrams per liter (mg/L). 
 

 

 

 

 

 

 

 

 

 

 

 

vii 

Abbreviations
 

ADVM Acoustic Doppler velocity meter 

BCF bias correction factor 

EDI equal discharge increment 

MAPE mean absolute percent error 

NWIS National Water Information System R2 coefficient of determination R2 

a adjusted coefficient of determination 

RMSE root mean square error 

RPD relative percent difference 

SCB sediment corrected backscatter 

SSL suspended-sediment load 

VIF variance inflation factor 

Characterization of Streamflow, Suspended Sediment, and 

Nutrients Entering Galveston Bay from the Trinity River, 

Texas, May 2014–December 2015 

By Zulimar Lucena and Michael T. Lee 

Abstract 

The U.S. Geological Survey (USGS), in cooperation with 

the Texas Water Development Board and the Galveston Bay 

Estuary Program, collected streamflow and water-quality data 

at USGS streamflow-gaging stations in the lower Trinity River 

watershed from May 2014 to December 2015 to characterize 

and improve the current understanding of the quantity and 

quality of freshwater inflow entering Galveston Bay from 

the Trinity River. Continuous streamflow records at four 

USGS streamflow-gaging stations were compared to quantify 

differences in streamflow magnitude between upstream and 

downstream reaches of the lower Trinity River. Water-quality 

conditions were characterized from discrete nutrient and sediment samples collected over a range of hydrologic conditions 

at USGS streamflow-gaging station 08067252 Trinity River 

at Wallisville, Tex. (hereinafter referred to as the “Wallisville 

site”), approximately 4 river miles upstream from where the 

Trinity River enters Galveston Bay. 

Based on streamflow records, annual mean outflow from 

Livingston Dam into the lower Trinity River was 2,240 cubic 

feet per second (ft3

/s) in 2014 and 22,400 ft3/s in 2015, the 

second lowest and the highest, respectively, during the entire 

period of record (1966–2015). During this study, only about 

54 percent of the total volume measured at upstream sites was 

accounted for at the Wallisville site as the Trinity River enters 

Galveston Bay. This difference in water volumes between 

upstream sites and the Wallisville site indicates that at high 

flows a large part of the volume released from Lake Livingston 

does not reach Galveston Bay through the main channel of the 

Trinity River. These findings indicate that water likely flows 

into wetlands and water bodies surrounding the main channel 

of the Trinity River before reaching the Wallisville site and is 

being stored or discharged through other channels that flow 

directly into Galveston Bay. 

To characterize suspended-sediment concentrations and 

loads in Trinity River inflow to Galveston Bay, a regression 

model was developed to estimate suspended-sediment concentrations by using acoustic backscatter data as a surrogate. 

The model yielded an adjusted coefficient of determination 

value of 0.92 and a root mean square error of 1.65 milligrams 

per liter (mg/L). The mean absolute percentage error between 

measured and estimated suspended-sediment concentration 

was 35 percent. During this study, estimated suspendedsediment concentrations ranged from 2 to 701 mg/L, with a 

mean of 97 mg/L. Suspended-sediment concentrations varied 

in response to changes in discharge, with peak suspendedsediment concentrations occurring 1 to 2 days before the 

peak discharge for each event. The total suspended-sediment 

load at the Wallisville site during May 2014–December 2015 

was approximately 2,200,000 tons, with a minimum monthly 

suspended-sediment load of 100 tons in October 2014 and a 

maximum monthly load of 441,000 tons in November 2015. 

Results from nutrient samples collected at the Wallisville 

site indicate that total nitrogen and total phosphorus concentrations fluctuated at a similar rate, with the highest nutrient 

concentrations occurring during periods of high flow corresponding to releases from Lake Livingston. The mean concentrations of total nitrogen and total phosphorus were approximately 75 percent higher during high flow releases than during 

periods of low flow, overshadowing variations in nutrient 

concentrations caused by seasonality at the Wallisville site.

 Results from the study indicate nutrient delivery to 

Galveston Bay from the main channel of the Trinity River is 

likely controlled primarily by high-flow releases from Lake 

Livingston. For most samples collected at the Wallisville 

site, organic nitrogen was the predominant form of nitrogen; 

however, when discharge increased because of releases from 

Lake Livingston, the percentage of organic nitrogen typically 

decreased and the percentage of nitrate increased. The concentrations of total phosphorus also increased during high-flow 

events, likely as a result of suspended sediment within Lake 

Livingston releases and mobilization of sediment particles in 

the river channel and flood plain during these periods of high 

flow. The predominant source of phosphorous to Galveston 

Bay from the Trinity River is in particulate form closely tied 

to suspended-sediment concentrations. The changes in nutrient 

concentration and composition caused by releases from Lake 
2 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

Livingston during this study indicate the reservoir may play an 

important role in the delivery of nutrients into Galveston Bay. 

Further study is required to better understand the processes 

in Lake Livingston influencing the characteristics of nutrient 

and sediment inflow to Galveston Bay. With phosphorous 

concentrations correlated to suspended-sediment concentrations (coefficient of determination value of 0.75) and with the 

concentrations of nutrients changing as the discharge changes, 

the diversion of water and suspended sediment into surrounding wetlands and channels outside of the main channel of 

the Trinity River may play a large role in regulating nutrient 

inputs into Galveston Bay. 

Introduction 

Estuarine ecosystems such as Galveston Bay on the Texas 

Gulf Coast depend on freshwater inflows to maintain adequate 

levels of salinity, nutrients, and sediment to support healthy 

ecosystem function and diverse biological communities. The 

delivery of freshwater into estuaries may be affected by alterations in the river course, including channelization and dam 

construction, resulting in changes in sedimentation patterns 

and biogeochemistry (Sklar and Browder, 1998). In Texas, 

the quantity of water flowing to the bays and estuaries is often 

influenced by withdrawals, diversions, and retention. The 

volume and timing of freshwater inflow typically influence 

nutrient and sediment loading into estuaries, affecting ecosystem communities (Sklar and Browder, 1998; Kimmerer, 2002). 

During periods of reduced freshwater inflow or drought, primary production and the trophic structure in estuarine systems 

can be altered as a result of changes in salinity, nutrient loading, or increased light penetration from reduced sediment input 

(Montagna and Kalke, 1992; Livingston and others, 1997). 

Reduced sediment supply can also result in degradation and 

morphologic shifts in deltaic environments (Yang and Others, 

2011), particularly when coupled with erosion, sea level rise 

(Lester and Gonzalez, 2011), and subsidence (Kennish, 2002). 

Increased sediment and nutrient loading to estuaries can also 

have detrimental effects in coastal systems. Excess sediment 

supply to estuarine systems increases turbidity and reduces 

light penetration (Harding and others, 1986; Cloern, 1987), 

limiting primary production. Nutrient enrichment in estuaries 

can cause an increase in the biomass of phytoplankton and 

algae, shifts in phytoplankton and animal species composition, 

and nuisance or toxic algal blooms (Smith and others, 1999; 

Kennish, 2002; Bricker and others, 2008). 

The delivery of nutrients to coastal ecosystems has varied 

historically on a global basis and depends on several physical and biogeochemical factors. Galloway and others (2004) 

estimated that global nitrogen riverine export to the coast 

increased by approximately 78 percent between 1860 and 

the early 1990s primarily as a result of anthropogenic influences. In 1995, the human-induced contribution to total river 

nitrogen export was estimated to be 37 percent, an increase of 

11 percent since 1970 (Bouwman and others, 2005). Nitrogen 

transported to streams from diffuse and point sources can be 

retained, transformed into other forms of nitrogen, or removed 

through physical and biogeochemical processes, such as 

assimilative uptake of nitrogen and denitrification of nitrate, 

before reaching the coastal environment (Alexander and others, 2000; Hamilton and others, 2001; Peterson and others, 

2001). Seitzinger and others (2005) estimated that approximately 38 percent and 41 percent of the total nitrogen transported to coastal ecosystems from riverine systems in North 

America are in the forms of dissolved inorganic nitrogen and 

dissolved organic nitrogen, respectively. The sources of dissolved inorganic nitrogen are mostly anthropogenic nonpoint 

sources (fertilizers, agricultural fixation, and manure), whereas 

sources of dissolved organic nitrogen are predominantly natural. Seitzinger and others (2005) also estimated that approximately 82 percent of phosphorus delivered to estuaries from 

riverine systems in North America occurs in particulate form. 

Phosphorus has a strong affinity to sediment particulates; 

therefore, a large amount of the phosphorus load transported 

in riverine systems is attached to soil particles delivered in 

surface runoff (Mainstone and Parr, 2002). As a result, phosphorus transport is highest during rainfall events that produce 

runoff and during periods of high river discharge, when 

deposition and resuspension of sediment particles from the 

streambed result in transfer of phosphorus between the water 

column and the streambed. Other processes, such as adsorption and desorption reactions, are also important mechanisms 

that influence the concentrations of dissolved and particulate 

phosphorus in the water column (Sharpley and others, 1981; 

House, 2003) and phosphorus export to bays and estuaries. 

As the largest and most biologically productive estuary in 

Texas, Galveston Bay is an important resource with a number 

of environmental challenges, many of which pertain directly 

or indirectly to the inflows from the heavily populated Trinity 

River watershed (Galveston Bay Estuary Program, 2016). The 

ability to accurately estimate the loads of sediment and nutrients entering Galveston Bay from the Trinity River watershed 

depends on accurate estimates of freshwater inflows and the 

concentrations of suspended sediment and nutrients associated 

with those inflows. Population and water demand are projected 

to continue to increase rapidly in the Trinity River watershed 

(Texas Water Development Board, 2016), underscoring the 

need for accurate streamflow, nutrient, and sediment load data. 

Available data on sediment and nutrient loads in the lower 

reaches of the Trinity River are scant, and the majority of 

water-quality samples have been collected in reaches of the 

river located 30 to 75 river miles upstream from where the 

river empties into Galveston Bay. To obtain better estimates 

of the nutrients and sediment entering Galveston Bay from the 

Trinity River, the U.S. Geological Survey (USGS), in cooperation with the Texas Water Development Board and the Galveston 

Bay Estuary Program, collected water-quality samples during 

May 2014–December 2015 at USGS streamflow-gaging station 08067252 Trinity River at Wallisville, Tex. (hereinafter 

referred to as the “Wallisville site”), approximately 4 miles 
Introduction 3 

upstream from Galveston Bay. Backscatter data from an 

Acoustic Doppler velocity meter (ADVM) were also collected 

and used in a regression model as a surrogate for suspendedsediment concentrations. Surrogate regressions provide an 

opportunity to obtain data of increased temporal resolution, 

allowing more accurate estimates of suspended-sediment 

concentrations and loads compared to discrete water-quality 

samples. 

Purpose and Scope 

This report documents and characterizes freshwater 

streamflow volume, nutrient concentrations, and sediment 

concentrations and loads entering Galveston Bay through 

the main channel of the Trinity River watershed during May 

2014–December 2015. Continuous streamflow records from 

four USGS streamflow-gaging stations are compared to assess 

changes in streamflow magnitude and to quantify discrepancies in streamflow between upstream and downstream reaches 

of the Trinity River separated by Lake Livingston. Water 

quality is characterized from discrete nutrient and sediment 

samples collected at the Wallisville site over a range of 

hydrologic conditions. Techniques used to collect and analyze 

these samples are documented. This report also describes a 

regression model developed to estimate suspended-sediment 

concentrations and loads from discharge and acoustic surrogate data in the lower reaches of the Trinity River and presents 

a continuous record of suspended-sediment concentrations 

and loads for the Wallisville site. This report helps address the 

need for discharge and water-quality data in the lower reaches 

of the Trinity River to improve the understanding of the volume and quality of freshwater inflow to Galveston Bay. 

Description of the Study Area 

Galveston Bay covers approximately 600 square miles 

(mi2

) and is the largest estuary in Texas (Lester and Gonzalez, 

2011). Freshwater inflows into Galveston Bay originate from 

the Trinity and San Jacinto Rivers and smaller bayous and 

creeks. Estimates show that the Trinity River is the major 

source of inflow into Galveston Bay, contributing more than 

half of the total freshwater inflow (Lester and Gonzalez, 

2011). The watershed of the Trinity River covers approximately 

18,000 mi2 and is the largest watershed entirely in Texas. 

From its headwaters near Dallas, Tex., the Trinity River flows 

approximately 715 miles before emptying into Galveston 

Bay (Trinity River Authority of Texas, 2012). The watershed 

of the Trinity River is typically divided into upper and lower 

parts delineated by Lake Livingston (fig. 1). Upstream from 

Lake Livingston, the Trinity River is hereinafter referred to as 

“upper Trinity River;” downstream from Lake Livingston, the 

Trinity River is hereinafter referred to as the “lower Trinity 

River.” The flows in the lower Trinity River are regulated by 

continuous releases from Lake Livingston. During low-flow 

conditions in the extreme lowermost part of the Trinity River 

near Galveston Bay, tides control daily flow patterns (Texas 

Parks and Wildlife Department, 1974). 

The USGS currently (2016) operates four streamflowgaging stations in the lower Trinity River watershed. These 

stations are: 08066250 Trinity River near Goodrich, Tex. 

(hereinafter referred to as “the Goodrich site”), 08066500 

Trinity River at Romayor, Tex. (hereinafter referred to as 

“the Romayor site”), 08067000 Trinity River at Liberty, Tex. 

(hereinafter referred to as the “Liberty site”), and the Wallisville site (table 1). The Wallisville site is approximately 4 river 

miles upstream from where the Trinity River enters Galveston 

Bay. The Liberty site is approximately 30 river miles upstream 

from the Wallisville site; the Romayor site is approximately 

40 river miles upstream from the Liberty site; and the Goodrich 

site is approximately 20 river miles upstream from the 

Romayor site. The Goodrich site is about 10 river miles downstream from the Livingston Dam.

 Because of a lack of streamflow data in the lower 

reaches of the Trinity River before 2014, most estimates of 

freshwater inflow made prior to 2014 (Lee and others, 2001; 

Powell and others, 2002) relied upon data collected at the 

Romayor site (fig. 1, table 1). Discharge measurements made 

in the lower reaches of the Trinity River during high-flow 

events in 2009 and 2010 indicated discrepancies in discharge 

between the Romayor site and the lower reaches of the Trinity 

River (Lee, 2010). It is possible that the streamflow data from 

the Romayor site may not accurately represent the inflow from 

the main channel of the Trinity River to Galveston Bay. In 

2014, the USGS installed an index-velocity gage in the lower 

reaches of the Trinity River at the Wallisville site to better estimate the inflow from the Trinity River into Galveston Bay and 

improve the understanding of streamflow patterns in the lower 

Trinity River watershed. 

The lower Trinity River drains a low gradient watershed 

with land cover characterized by woody wetlands (29 percent), 

pasture (17 percent), and evergreen forest (13 percent) (Homer 

and others, 2015). South of the Liberty site, a system of 

wetlands and lakes are hydrologically connected to the main 

channel of the Trinity River (fig. 2). Old River Lake and 

Lost Lake form the nexus of a system of wetlands and lakes 

referred to in this report as the “Old River system.” The Old 

River system diverges from the main Trinity River channel 

downstream from the Liberty site and upstream from Interstate 10 and rejoins the main channel of the Trinity River 

approximately 3 miles upstream from where the Trinity River 

empties into Galveston Bay. The two main types of wetlands 

connecting the main Trinity River channel with the Old River 

system upstream from Interstate 10 are classified as freshwater 

emergent and freshwater forested/shrub that are seasonally or 

temporarily flooded conditional to tides and streamflow (U.S. 

Fish and Wildlife Service, 2016). Near the Wallisville site, as 

the Trinity River empties into Galveston Bay, the wetlands 

form a delta consisting of estuarine intertidal and marine wetlands. The Old River system is also hydrologically connected 

to these estuarine and marine wetlands in the delta adjacent to 

Galveston Bay. 
 

 

4 

r 

Gulf of 

Mexico 

San Jacinto River 

San Jacinto River 

San Jacinto

River 

East Fork 

West 

Fork 

Trinity 

River 

Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

95° 94°30' 

EXPLANATION 

T R I N I T Y C O U N T Y 08067252 U.S. Geological Survey streamflow-gaging 

31° 

TYLER COUNTY station where suspended-sediment and 

water-quality samples were collected 

(table 1) 

Lower Trinity River watershed 

Upper Trinity River watershed 

P O L K C O U N T Y 

Lake

Livingston Upper Trinity River 

watershed 

LIVINGSTON DAM 

Dallas 

Goodrich TEXAS

08066250 (Goodrich site) 

30°30' 

Lower Trinity Romayor H A R D I N C O U N T Y 

S A N J A C I N T O C O U N T Y River watershed 

787

59

08066500 

(Romayor site) 

M O N T G O M E R Y 

C O U N T Y 105

321

L I B E R T Y C O U N T Y 

Liberty 

08067000 

Lake (Liberty site) 30° 

Houston

90

Lost 

Lake Wallisville 

610 Old River

H A 

Houston 

R R I S C O 

10

U N T Y 

L a k e 08067252 

(Wallisville site) 

GalvestonGalveston 

Bay 

0 5 10 15 20 MILES 

45 C H A M B E R S C O U N T Y 

0 5 10 15 20 KILOMETERS 

Base modified from U.S. Geological Survey digital data, various scales 

USA Contiguous Albers Equal Area Projection 

North American Datum 1983 

Figure 1. Location of monitoring sites in the lower Trinity River watershed downstream from Lake Livingston, Texas. 
Methods 5 

Table 1. Description of monitoring sites in the lower Trinity River watershed downstream from Lake Livingston, 

Texas, May 2014–December 2015. 

[USGS, U.S. Geological Survey] 

USGS station number 

(fig. 1) 

USGS station name Short name 

(fig. 1) 

Latitude 

(degrees, minutes, seconds) 

Longitude 

(degrees, minutes, seconds) 

Drainage area 

(square miles) 

08066250 Trinity River near Goodrich, Texas Goodrich site 30°34'19" 94°56'55" 16,844 

08066500 Trinity River at Romayor, Texas Romayor site 30°25'30" 94°51'02" 17,186 

08067000 Trinity River at Liberty, Texas Liberty site 30°03'27" 94°49'05" 17,468 

08067252 Trinity River at Wallisville, Texas Wallisville site 29°48'44" 94°43'52" 17,796 

Previous Studies 

In 2009, the U.S. Geological Survey, in cooperation with 

the Texas Water Development Board, began evaluating the 

variability of sediment and nutrient characteristics in the lower 

reaches of the Trinity River during a variety of hydrologic 

conditions. High-flow events were evaluated to demonstrate 

the variability of sediment and nutrient characteristics caused 

by differences in flood-discharge magnitude and duration. 

During high-flow events, discharge was measured at the 

Wallisville site; however, maximum measured discharge was 

approximately 35 to 50 percent lower than the discharge computed at upstream streamflow-gaging stations (Lee, 2010). The 

overall decrease in flow observed at the Wallisville site compared to the flow at upstream streamflow-gaging stations could 

possibly be attributed to the distribution of water into the wetlands surrounding the river as water levels in high-flow events 

overtopped the banks of the main channel of the lower Trinity 

River. Two scenarios could have occurred: (1) water was 

temporarily stored in wetlands and gradually released to the 

main channel of the Trinity River when flows were receding or 

(2) water was directly discharged into Galveston Bay through 

channels in the delta. If scenario 1 occurred, a continuous 

record of discharge would show longer periods of high flow in 

the lower reaches of the Trinity River and a total water volume 

similar to the volume observed in upstream streamflow-gaging 

stations. If scenario 2 occurred, a hydrograph would follow 

a streamflow pattern similar to those observed at upstream 

streamflow-gaging stations, but discharge and total volume 

would be of lower magnitude. Each scenario would have 

potentially different resulting loads of sediment and nutrients 

ultimately reaching the Galveston Bay ecosystem. Because of 

these findings, an index-velocity gage was installed in 2014 

at the Wallisville site to examine the hydrodynamics in the 

extreme low reaches of the Trinity River. 

Methods 

Discharge, stage, and water-velocity data at the Goodrich, 

Romayor, Liberty, and Wallisville sites were collected 

according to USGS methods described by Rantz and others 

(1982a, b), Sauer and Turnipseed (2010), Levesque and Oberg 

(2012), and Mueller and others (2013). Discharge at the 

Goodrich, Romayor, and Liberty gages was computed using 

stage-discharge rating techniques (Rantz and others, 1982a, b; 

Sauer and Turnipseed, 2010). At the Wallisville site, discharge 

was computed by using index-velocity rating techniques 

(Levesque and Oberg, 2012). The index-velocity method 

allows the computation of discharge at streamflow-gaging 

stations where a rating cannot be solely based on stage, such 

as the tidally affected flows at the Wallisville site. Discrete 

streamflow measurements were made at the Wallisville site 

with an acoustic Doppler current profiler according to methods 

described by Mueller and others (2013) during each visit prior 

to the collection of water-quality and sediment samples. 

During May 2014–December 2015, 34 discrete waterquality samples were collected over a range of hydrologic 

conditions at the Wallisville site. Samples were analyzed for 

suspended-sediment concentration, total nitrogen, nitrate 

plus nitrite, nitrite, ammonia, total phosphorus, and orthophosphate; a sand-fine separation was done to determine 

the amounts of sand-sized suspended sediment (greater than 

0.0625 and less than or equal to 2 millimeters [mm]) and finesized suspended sediment (less than or equal to 0.0625 mm) 

(Guy, 1969). 

Water-quality samples for the analysis of total nitrogen, 

nitrate plus nitrite, nitrite, ammonia, total phosphorus, and 

orthophosphate were collected at the Wallisville site in accordance with guidelines described in the USGS National Field 

Manual (U.S. Geological Survey, variously dated). Suspendedsediment samples were collected in accordance with USGS 

methods described in Edwards and Glysson (1999). During the 

collection of water-quality and sediment samples, a multiparameter water-quality sonde was used in the field to measure 

dissolved oxygen concentration, pH, specific conductance, 

water temperature, and turbidity. 

Water-quality and suspended-sediment samples were 

collected from a boat by either the equal discharge increment 

(EDI) or the multiple grab sample method (Edwards and Glysson 1999; U.S. Geological Survey, variously dated). When 

measured mean water velocity exceeded 1.5 feet per second 

(ft/s), EDI samples were collected using a cable-suspended 
6 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River

Lower Trinity 

River Watershed

Enlarged 

area

U.S. Geological Survey streamflow-gaging station

where suspended-sediment and water-quality

samples were collected (table 1)

Lower Trinity River watershed

Wetland classification

Freshwater emergent wetland

Freshwater forested/shrub wetland

Estuarine and marine wetland

Estuarine and marine deepwater

Riverine

Freshwater pond

Lake

Other

08067000

Gulf of 

Mexico

EXPLANATION Lower Trinity 

River watershed

Enlarged 

area

Gulf of 

Mexico

Galveston 

Bay

08067252 (Wallisville site)

08067000 (Liberty site)

Trinity River

Lost

Lake

Old River

Lake

321

90

10

94°50' 94°40'

30°

29°50'

0 3 6 MILES

0 3 6 KILOMETERS

Base modified from U.S. Geological Survey

and U.S. Fish and Wildlife Service, various scales

USA Contiguous Albers Equal Area Projection

North American Datum 1983

LIBERTY COUNTY

CHAMBERS COUNTY

Figure 2. Wetland cover and classification in the lower Trinity River watershed downstream from Lake Livingston, Texas.
Methods 7 

US DH–2 sampler after dividing a cross section into five sections, each representing equal volumes of stream discharge. 

The EDI method allows the collection of an isokinetic depthintegrated sample that represents the discharge-weighted concentrations of the stream cross section being sampled. When 

measured mean water velocity was less than 1.5 ft/s, nonisokinetic grab samples were collected at the center of five equal 

width sections using a weighted bottle sampler (U.S. Geological Survey, variously dated). Of the 34 collected samples, 16 

were collected with the EDI method. 

Water-quality and suspended-sediment samples for each 

vertical were composited in a polyethylene churn splitter 

and subsamples for unfiltered constituents were transferred 

into sample bottles while mixing at a constant rate. The use 

of a churn splitter can potentially bias suspended-sediment 

concentration because sand-sized particles (greater than or 

equal to 0.625 mm and smaller than 2.0 mm) may not remain 

uniformly suspended in the churn while obtaining the sample 

aliquot (Capel and Larson, 1995; Horowitz and others, 1997). 

However, the accuracy is considered to be acceptable when 

the churn is used to split samples with particle sizes smaller 

than 0.250 mm and suspended-sediment concentration less 

than 1,000 mg/L (U.S. Geological Survey, variously dated). 

This potential bias was not expected to substantially influence 

suspended-sediment concentration results during this study 

because data from previous samples collected at the Wallisville site indicate fine particles (smaller than 0.0625 mm) 

typically dominate the distribution of suspended-sediment 

size classes and because during high-flow events, suspendedsediment particles are usually fine sand particles (less than 

0.250 mm) or smaller. Water-quality samples for dissolved 

nutrients analysis were filtered using a 0.45-micron (μm) pore 

size capsule filter and decanted into sample bottles. 

Analytical Methods 

Samples for suspended-sediment concentration, sand-fine 

separation analysis, and full particle-size distribution analysis 

were shipped to the USGS Kentucky Water Science Center 

Sediment Laboratory in Louisville, Kentucky. Methods for 

sediment sample analyses are documented in Guy (1969). 

Samples for nutrient analysis were preserved, chilled, and 

shipped overnight to the National Water Quality Laboratory in 

Lakewood, Colorado, for analysis. Methods for nutrient analysis are documented in Fishman (1993), U.S. Environmental 

Protection Agency (1993), and Patton and Kryskalla (2003, 

2011). Samples were analyzed for nutrients by using approved 

methods; the analysis method and method detection limit for 

each constituent are provided in table 2. Water-quality data 

are stored in the National Water Information System (NWIS) 

database (U.S. Geological Survey, 2016) in accordance with 

USGS protocols. 

Experiments at the USGS National Water Quality Laboratory 

in 2007 and 2009–10 indicate that the alkaline-persulfate 

digestion of whole water samples resulted in a potential negative bias in total nitrogen concentrations in the presence of 

suspended sediment (Rus and others, 2013). This negative 

bias may be site specific and varies in magnitude, depending 

on the origin and concentration of suspended sediment. At 

the time of this report (2016), the magnitude of potential bias 

is unknown at the Wallisville site, and the total nitrogen data 

from this study are reported as the minimum concentration of 

this constituent in each sample. 

Quality Control 

To evaluate the variability of sample processing and 

analysis in water-quality constituents, data from field replicate 

samples collected at the Wallisville site from 2009 to 2015 

were used. The dataset consists of 17 split replicates, which 

are prepared from a single sample that is collected and then 

subdivided into two samples. Quality-control data collected 

outside of the study period can be used to increase the size of 

the dataset and improve the understanding of variability in the 

environmental data as long as the samples can be considered 

to be in same inference space (Mueller and others, 2015). It 

was determined that replicate samples collected at the Wallisville site prior to this study share the same inference space 

(Lorenzen and Anderson, 1993) as the samples collected 

during the study because they represent similar conditions in 

terms of potential variability. This assumption was based on 

(1) consistent sampling methods and equipment were used for 

the collection of all samples, (2) hydrologic conditions and 

concentrations in the quality-control dataset are representative of those observed during the study period, (3) analytical 

methods for most constituents did not change throughout the 

sampling period, and (4) sample collection and processing 

were conducted at the same location. 

For nitrate plus nitrite, 4 out of the 17 replicate samples 

were used in the analysis because of a change in the analytical method in 2011, and because some results were less than 

the method detection limit, the “minimum concentration of a 

substance that can be measured and reported with 99 percent 

confidence that the analyte concentration is greater than 

zero” (Childress and others, 1999, p. 19). For the rest of 

the constituents, replicate samples were only used in the 

analysis when results were greater than or equal to the method 

reporting limit. 
8 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

Table 2. Analytes measured, sample treatment and preservation, analytical methods, and reporting limits for samples collected at 

U.S. Geological Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas. 

[mg/L, milligrams per liter; μm, micrometer; USGS, U.S. Geological Survey; NWQL, National Water Quality Laboratory; H2SO4, sulfuric acid ;USEPA, 

U.S. Environmental Protection Agency; mm, millimeter; WSC, Water Science Center; ASTM, American Society for Testing and Materials] 

Constituent 

Sample 

treatment and 

preservation 

method(s) 

Analyzing laboratory Analytical method(s) Method 

number 

Method 

reporting limit 

(mg/L) 

Analytical 

method 

reference 

Ammonia 0.45 μm filter USGS NWQL, 

Lakewood, Colorado 

Salicylate-hypochlorite 

reaction and colorimetry, discrete analyzer USGS I-2522-90 0.01 Fishman (1993) 

Nitrite 0.45 μm filter USGS NWQL, 

Lakewood, Colorado 

Diazotization and 

colorimetry, discrete 

analyzer 

USGS I-2540-90 0.001 Fishman (1993) 

Nitrate plus nitrate 0.45 μm filter USGS NWQL, 

Lakewood, Colorado 

Enzymatic reduction, 

Griess Reaction colorimetry, automated 

discrete analyzer 

USGS I-2547-11 0.04 Patton and 

Kryskalla 

(2011) 

Total nitrogen H2

SO4 USGS NWQL, 

Lakewood, Colorado 

Alkaline-persulphate 

digestion and colorimetry, continuous flow 

analyzer 

USGS I-4650-03 0.05 Patton and 

Kryskalla 

(2003) 

Orthophosphate 0.45 μm filter USGS NWQL, 

Lakewood, Colorado 

Phosphomolybdate formation and colorimetry, discrete analyzer USGS I-2601-90 0.004 Fishman (1993) 

Total phosphorus H2

SO4 USGS NWQL, 

Lakewood, Colorado 

Acid-persulphate 

digestion and colorimetry, continuous flow 

analyzer 

USEPA 365.1 0.004 United States 

Environmental 

Protection 

Agency (1993) 

Suspended sediment 

less than or equal 

to 0.0625 mm, 

sieve diameter 

None Sediment Lab- USGS 

Kentucky WSC, 

Louisville, Kentucky 

Wet Seive ASTM D3977-97 1.00 Guy (1969) 

Suspended-sediment 

concentration 

None Sediment Lab- USGS 

Kentucky WSC, 

Louisville, Kentucky 

Evaporation of material 

from sediment size 

analysis 

ASTM D3977-97 1.00 Guy (1969) 
 

Methods 9 

To determine variability in environmental samples, the 

relative percent difference (RPD) was calculated between each 

pair of duplicate analyses by the following equation 

|C −C | RPD = 1 2 ×100 , (1)

(C + C )/ 2 1 2

where 

C1 is the constituent concentration in the 

environmental sample, and 

C2 is the constituent concentration in the split 

replicate sample. 

The mean RPD of replicate concentrations was less than 

9 percent for all analytes. This estimate, although low, is also 

conservative, because high RPD values from low concentration samples with a small absolute difference were used in the 

analysis. Overall, these replicate samples indicate low variability in nutrient and sediment analyses. 

Equipment blanks were collected prior to the study period 

to determine potential contamination introduced to samples 

by personnel, sampling equipment, and shipping. The blanks 

were collected as part of the water-quality monitoring effort at 

the Wallisville site by using the same equipment that was used 

to collect environmental samples. Because analytical results 

for equipment blanks did not indicate that contamination 

affected environmental data, no additional equipment blanks 

were collected during the period of this study. 

Suspended-Sediment Acoustic Surrogate 

Methods 

Although Acoustic Doppler velocity meters are primarily used to measure water velocity, the acoustic backscatter 

measured by ADVMs makes them useful for computing 

suspended-sediment concentrations in streams. Acoustic 

backscatter increases as more particles are suspended in the 

water, reflecting the acoustic pulse emitted by the ADVM 

(Wood and Teasdale, 2013; Landers and others, 2016; 

Topping and Wright, 2016). Regression equations that contain 

acoustic backscatter, turbidity, or streamflow can be used to 

compute suspended-sediment concentrations at a high temporal resolution (typically every 15 minutes), providing an 

advantage over discrete suspended-sediment concentration 

samples. For example, during high-flow events, the concentrations of suspended-sediment can vary considerably within 

a short time. This temporal variability with discrete samples 

is difficult to capture because there are typically long gaps 

between sample collection and analysis. Discrete samples also 

provide information only for the time in which the sample was 

collected, resulting in interpolation between sampling points 

that may not accurately characterize variability in suspendedsediment concentrations. 

Instrument Configuration 

The data from an index-velocity gage installed at the 

Wallisville site, in accordance with USGS guidelines for 

streamflow and acoustic sediment surrogate data collection (Levesque and Oberg, 2012, Landers and others, 2016), 

were used to develop an acoustic surrogate for suspendedsediment concentration. The index-velocity gage consists of 

a 1.5-megahertz (MHz) SonTek Argonaut-SL (Side-Looker) 

ADVM (Xylem Analytics, 2016) bolted to a 2-inch diameter 

pipe (fig. 3). The pipe, which can be lowered and raised as 

needed to access the ADVM, is mounted vertically on the right 

bank with the ADVM at a fixed position perpendicular to flow. 

Power is provided by a marine battery charged by a 30-watt 

solar panel installed above a gage house. The data are recorded 

every 15 minutes by a Sutron SatLink2–V2 Data Collection 

Platform and then transmitted every hour by antenna to the 

Geostationary Operational Environmental Satellite system, 

which transmits the data to a downlink at the USGS office for 

display on the Web and storage in the USGS NWIS database. 

The Acoustic Doppler velocity meter is configured to 

measure velocity and acoustic backscatter as signal-to-noise 

ratio in five cells of equal size throughout a sample volume that 

extends from 10 to 60 feet (ft) from the instrument (15–20 percent 

of channel width). The range of the horizontal sample volume 

was determined after evaluating the acoustic data for interferences and obstructions along the beam path. This configuration 

was verified before each water-quality sample was collected to 

ensure no changes occurred in the sample volume that could 

affect acoustic backscatter data between site visits. Additional 

instrument setup details are included (app. 1). 

Throughout the duration of the study, two averaging 

intervals were used to collect backscatter data during sample 

collection for model calibration. During May 16, 2014– 

January 15, 2015, acoustic backscatter measurements for 

the surrogate model calibration dataset were averaged over 

10 minutes and reported every 15 minutes. Because discharge 

measurements for developing the index-velocity rating to 

estimate streamflow were being made concurrently with the 

collection of suspended-sediment concentration samples, 

for calibration samples collected during January 16, 2015– 

December 31, 2015, acoustic backscatter measurements were 

averaged and recorded every 60 seconds as recommended by 

index-velocity rating guidelines (Levesque and Oberg, 2012). 

Acoustic Surrogate Model Development and 

Evaluation 

Prior to using acoustic backscatter measurements as input 

in a surrogate regression model, the raw measured acoustic 

backscatter data for each cell in the sample volume requires 

corrections for beam spreading and for acoustic attenuation 

as the sound signal is transmitted through the water and 

sediment (Landers and others, 2016). Raw measured acoustic 
 

 

 

 

10 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

A B
 

Figure 3. The A, data collection platform and B, Acoustic Doppler velocity meter installed at U.S. Geological 

Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas. 

backscatter (as signal-to-noise-ratio) for each cell was corrected and averaged by using methods described in Landers 

and others (2016). Data corrections produce a mean sediment 

corrected backscatter (SCB) value, which is determined for 

each measurement in the dataset. The Surrogate Analysis and 

Index Developer (SAID) tool (Domanski and others, 2015), 

an application written for the evaluation of acoustic surrogates 

and the development of a suspended-sediment concentration 

rating based on acoustic backscatter data, was used to perform 

these corrections. 

A sediment acoustic surrogate linear regression model 

was developed with suspended-sediment concentration data 

from discrete samples collected at the Wallisville site and 

continuous streamflow and corrected acoustic backscatter 

data recorded at the index-velocity gage. Thirty-one observations were used to calibrate the surrogate model. Although 35 

suspended-sediment samples were collected, 2 were removed 

from the dataset because of data gaps in the acoustic backscatter time series, and 2 were removed because of potential issues 

with data quality indicated by outlier tests and further evaluation of field measurements. The calibration data, including 

removed data points, are provided (app. 1). 

The SAID tool was used to match discrete suspended-sediment concentration samples with a concurrent 

measurement and develop an ordinary least squares regression 

model to predict suspended-sediment concentration from the 

resulting calibration dataset. Suspended-sediment concentration data were log transformed to improve distribution prior 

to being included in a regression model. The use of a log 

transformation introduces a bias when retransforming data to 

its original units. This bias was corrected with the nonparametric bias correction factor (BCF) introduced by Duan (1983). 

The equation to compute the BCF for log transformations is as 

follows: 

10

BCF = ∑i

n

1 ei

, (2) 

n

where 

n is the number of samples, and 

ei is the residual, in log units. 

Regression-estimated suspended-sediment concentrations 

were retransformed and then corrected for bias by multiplying 

concentrations by the BCF. 

The adjusted coefficient of determination (R2

a

), root mean 

square error (RMSE), mean absolute percent error (MAPE), 
 

 

 

 

 

Streamflow Characterization in the Lower Trinity River Watershed 11 

variance inflation factor (VIF), Cook’s distance (Cook’s D), 

and the difference in fit statistic (DFFITS) are some of the 

statistical measures used to evaluate the regression models 

in this report (Belsley and others, 1980; Mayer and Butler, 

1993; Helsel and Hirsch, 2002). The coefficient of determination (R2

) is a value from 0 to 1 that describes the variability in 

the response explained by the regression model (Helsel and 

Hirsch, 2002). In multiple linear regression, R2

 will increase 

as additional explanatory variables are added to the model; 

thus adjusted R2

 (R2

a

) was determined because this measure 

compensates for the number of explanatory variables and 

allows the comparison of models that have different numbers 

of explanatory variables. The RMSE of the regression is a 

measure of the variance between regression-computed and 

measured values (Chai and Draxler, 2014). The RMSE is 

expressed in the same units as the response variable, which 

in this case is milligrams per liter once retransformed from 

log Also, as another measure to assess the differences 10. 

between regression-computed and measured suspendedsediment concentration, the mean absolute percent error 

(MAPE) (Mayer and Butler, 1993) was determined using the 

following equation: 

100 SSC − SSC ∑

n

MAPE Mi Ei , (3) = n i SSCMi

where 

n is the number of samples, 

SSCMi is the measured suspended-sediment 

concentration, and, 

SSCEi is the regression-computed suspendedsediment concentration. 

Models with more than one predictive variable were 

evaluated for multicollinearity to determine if the predictive 

variables showed any correlation between each other, because 

this can result in undesirable consequences when making 

inferences about the model (Helsel and Hirsch, 2002). The 

variance inflation factor (VIF) was used to measure multicollinearity. An ideal VIF is close to 1, whereas a VIF larger than 

10 indicates multicollinearity between variables and that either 

variable would explain about the same amount of variability 

(Helsel and Hirsch, 2002). Cook’s D and DFFITS measure the 

influence of individual observations on the regression equation; compared to other observations that plot more closely 

to the regression line, those with high leverage, which are 

large outliers, exert a stronger influence on the position of the 

regression line (Helsel and Hirsch, 2002, p. 248). To verify if 

the selected model met assumptions of constant variance and 

normality of residuals, residuals were plotted against estimated 

suspended-sediment concentration to determine any issues 

of nonconstant variance and on a normal-probability plot to 

evaluate normality of residuals (Helsel and Hirsch, 2002). 

Streamflow Characterization in the 

Lower Trinity River Watershed 

Streamflow measured at the Goodrich site corresponds to 

outflow from Lake Livingston into the Trinity River. Annual 

daily mean discharge (annual mean discharge) has been 

determined for each calendar year since the Goodrich site 

was installed. The annual mean discharge at the Goodrich site 

has varied during the 50-year period of record since the start 

of data collection in 1966; the long-term annual discharge 

for the 50-year period of record is 7,960 ft3

/s (fig. 4). The 

minimum annual mean discharge for the period of record 

(1966–2015) is 1,710 ft3

/s in 2011, followed by 2,240 ft3/s in 

2014. The maximum annual mean discharge is 22,400 ft3

/s 

in 2015. This study from May 2014 through December 2015 

incorporates hydrologic data from periods of extreme low 

and high streamflow on the lower Trinity River. The dataset 

for this study includes observations from 2014 and 2015, the 

year with the second lowest annual discharge and the year 

with the maximum annual mean discharge, respectively. The 

large variation in annual mean discharge during the study 

was caused by below average precipitation in calendar year 

2014 followed by above average annual precipitation in the 

upper Trinity River watershed in calendar year 2015 (National 

Oceanic and Atmospheric Administration National Centers for 

Environmental Information, 2016) resulting in the release of 

a large volume of water from Lake Livingston for extended 

periods. The water volume measured at the Goodrich site in 

2015 accounted for 95 percent of the total volume measured at 

this site during the study period. 

The streamflow patterns from May 2014 through December 2015 at the Goodrich, Romayor, and Liberty sites were 

similar (fig. 5). Daily mean discharge ranged from 984 to 

72,400 ft3

/s at the Goodrich site and from 945 to 71,800 ft3/s at 

the Romayor site. Minimum discharge at the Liberty site could 

not be determined as the station only computes discharge 

greater than 10,000 ft3

/s, when tides do not affect streamflow 

computations. The maximum discharge at the Liberty site was 

76,200 ft3

/s, an increase likely attributed to local overland 

runoff in the lower reaches of the river. However, the distance 

between Lake Livingston to Galveston Bay is relatively short 

(100 river miles), so increases in discharge in the lower Trinity 

River as a result of overland runoff are minor when compared 

to the volume of water released from Lake Livingston. The 

peak discharge at the Liberty site in March and May 2015 

was approximately 5,000 ft3

/s higher than at the Goodrich and 

Romayor sites (fig. 5), indicating that only 5–10 percent of the 

total discharge may be a result of overland runoff. 

At the Wallisville site, daily mean discharge ranged from 

-669 ft3

/s (a reversal of flow caused by tidal influences) on 

August 17, 2014, to 24,440 ft3

/s on December 17, 2015. During events in which discharge exceeded approximately 14,000 ft3

/s 

at the Goodrich, Romayor, and Liberty sites, only part of the 
12 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

25,000 

20,000 

Discharge, in cubic feet per second Discharge, in cubic feet per second

10,000 

15,000 

Long-term annual 

mean discharge 

5,000 

0 

1966

1967

1968

1969

1970

1971

1972

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015 

Year 

Figure 4. Annual daily mean discharge at U.S. Geological Survey streamflow-gaging station 08066250 Trinity River 

near Goodrich, Texas, 1966–2015. 

80,000 EXPLANATION 

Measured discharge at monitoring sites (table 1) 

70,000 Trinity River near Goodrich, Tex. (Goodrich site) 

Trinity River at Romayor, Tex. (Romayor site) 

60,000 

Trinity River at Liberty, Tex. (Liberty site) 

Trinity River at Wallisville, Tex. (Wallisville site) 

50,000 

40,000 

30,000 

20,000 

10,000 

0 

May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 

2014 2015 

Date 

Figure 5. Instantaneous discharge at U.S. Geological Survey streamflow-gaging stations in the lower Trinity River 

watershed, Texas, May 2014–December 2015. 
Suspended-Sediment Concentrations and Loads 13 

volume was measured at the Wallisville site. For example, the 

peak discharge at the Liberty site during the high-flow event 

in December 2015 was 67,400 ft3

/s, whereas at the Wallisville site peak discharge was 24,440 ft3

/s, accounting for only 

36 percent of the streamflow measured upstream. The peak 

discharge at each site for seven high-flow events during the 

study period in which streamflow exceeded 14,000 ft3

/s and 

the percentage of the peak discharge measured at the Wallisville site as compared to the Liberty site, the closest upstream 

USGS streamflow-gaging station, are shown in table 3. The 

percentage of the peak discharge measured at the Wallisville 

site ranged from about 28 to 82 percent and decreased with 

event magnitude. 

Differences between upstream stations and the Wallisville 

site were also observed in total volume computations for the 

study period. A total of 17,200,000 acre-feet (acre-ft) of water 

were measured at the Goodrich site, 17,700,000 acre-ft at 

the Romayor site, 15,400,000 acre-ft at the Liberty site, and 

9,270,000 acre-ft at the Wallisville site. The water volume at 

the Liberty site is likely underestimated because of missing 

data from periods in which discharge was less than 10,000 ft3

/s 

and not reported (approximately 38 percent of the study 

period); however, because the majority of the water volume 

is transported during events exceeding this discharge, periods 

of missing data did not account for a large part of the total 

water volume. 

Only about 54 percent of the total water volume released 

from Lake Livingston during May 2014–December 2015 

(as measured at the Goodrich site) was accounted for at the 

Wallisville site. This difference in water volumes between 

upstream sites and the Wallisville site indicates that, at high 

flows, a large percentage of the volume released from Lake 

Livingston does not reach Galveston Bay through the main 

channel of the Trinity River. In addition, discharge at the 

Wallisville site increased and decreased at the same rate as 

upstream stations but at a lower magnitude; the main channel 

of the Trinity River at the Wallisville site only accommodated 

discharges of as much as approximately 24,000 ft3

/s, even 

when discharges at upstream sites were approximately 2 to 

4 times higher. These findings indicate that water likely flows 

into wetlands and water bodies surrounding the main channel 

of the Trinity River before reaching the Wallisville site and is 

being stored or discharged through other channels that flow 

directly into Galveston Bay. 

Suspended-Sediment Concentrations 

and Loads 

Suspended-sediment samples were collected at the 

Wallisville site at streamflow ranging from 238 to 22,700 ft3

/s, 

accounting for approximately 72 percent of the range in 

streamflow for the period of record (May 2014–December 

2015). A discharge-duration curve was prepared indicating the 

streamflow at which each sample was collected (fig. 6). This 

duration curve was developed using data collected during the 

20-month period in which the streamflow-gaging station at 

the Wallisville site had been operating, the same period of this 

study. Because there were extended periods of both extreme 

low and high streamflow and a relatively short period of 

record for the Wallisville site, this duration curve may not be 

representative of long-term probability of exceedance; however, it is expected to be representative of the observed range 

of flows. 

Table 3. Peak discharges measured at U.S. Geological Survey streamflow-gaging stations in the lower Trinity River 

watershed, Texas, May 2014–December 2015. 

[ft3/s; cubic feet per second] 

High-flow Short name for sampling site (table 1) Percentage of peak 

event Start date Peak discharge (ft3

/s) discharge measured at 

number Goodrich Romayor Liberty Wallisville Wallisville site 

1 1/2/2015 18,000 18,500 18,000 14,700 81.7 

2 1/22/2015 18,800 18,700 18,800 14,900 79.3 

3 3/7/2015 45,300 45,200 50,500 19,800 39.2 

4 4/12/2015 26,400 26,800 25,400 17,500 68.9 

5 5/13/2015 72,400 71,800 76,200 21,200 27.8 

6 10/24/2015 54,000 55,300 53,300 24,300 45.6 

7 12/5/2015 69,900 70,000 67,400 24,400 36.2 
14 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

Exceedance probability, in percent 

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

-5,000 0 5,000 10,000 15,000 20,000 25,000 30,000 

Discharge, in cubic feet per second 

Figure 6. Discharge-duration curve indicating the 

streamflow at which each sample was collected at U.S. 

Geological Survey streamflow-gaging station 08067252 

Trinity River at Wallisville, Texas, May 2014–December 2015. 

100 

Suspended-sediment concentrations measured in samples 

collected during May 2014–December 2015 ranged from 5 to 

453 mg/L, with a median of 65 mg/L. Sand-fine separation 

analysis was done for 27 samples. In those samples, fine-sized 

suspended sediment represented 37 to 100 percent of all 

suspended-sediment particles, with the median composition 

consisting of 85.5 percent fine-sized particles and 14.5 percent 

sand-sized particles. The percentage of fine-sized particles 

decreased as discharged increased, indicating higher transport 

of sand-size particles at high flows (fig. 7). 

A full particle-size distribution analysis was done for six 

samples collected between April 3, 2015, and June 10, 2015, 

mostly during high-flow events. In a suspended-sediment full 

particle-size distribution analysis, the percentages of material 

of each sediment size class (typically sand, silt, and clay) are 

determined (Guy, 1969). For the six samples analyzed for fullsize distribution during this study, the percentage of material 

smaller than 0.0625, 0.125, 0.250, and 0.500 mm was determined. In these samples, all sediment particles were smaller 

than medium sand particles (0.500 mm). In addition, the percentage of sediment particles smaller than fine sand (smaller 

than 0.250 mm) ranged from 96 to 100 percent (table 4), indicating that the majority of the suspended-sediment particles 

were silts, clays, and very fine and fine sand particles. 

Suspended sediment smaller than 0.0625 millimeter, in percent 

90 

80 

70 

60 

50 

40 

0 5,000 10,000 15,000 20,000 25,000 

Discharge, in cubic feet per second 

Figure 7. Graph showing relation between sand-fine separation results and discharge measured at U.S. Geological 

Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas, May 2014–December 2015. 
 

 

 

 

 

 

 

Suspended-Sediment Concentrations and Loads 15 

Table 4. Results from suspended-sediment size analysis for selected samples in U.S. Geological Survey 

streamflow-gaging station 08067252 Trinity River at Wallisville, Texas, April 3, 2015–June 10, 2015. 

[ft3/s, cubic feet per second; mm, millimeters; –, no data] 

Suspended-sediment sieve diameter 

Date Discharge 

(ft3

/s) 

Percent finer than 

0.0625 mm; 

Percent finer than 

0.125 mm; 

Percent finer than 

0.250 mm; 

Percent finer than 

0.500 mm; 

silt and clay very fine sand fine sand medium sand 

4/3/2015 5,060 96 99 100 – 

5/4/2015 15,800 49 70 98 100 

5/18/2015 18,900 57 79 98 100 

5/22/2015 20,400 49 76 98 100 

5/30/2015 22,200 47 66 98 100 

6/10/2015 21,600 37 46 96 100 

Suspended-Sediment Acoustic Surrogate 

Model Results 

Simple and multiple linear regression models were evaluated to find the best predictor of suspended-sediment concentration. Discharge and SCB were used as predictive variables 

to develop different regression equations with the objective of 

identifying the regression equation that was the best predictor of 

suspended-sediment concentration. A log transformed regression 

model based on the combination of discharge and SCB showed 

the best relation to suspended-sediment concentration. The 

resultant suspended-sediment concentration equation for the 

selected model, after transformation to its original units, is: 

SSC SCB Q = + 0 0269 100 0416 0 000031 . . . × ×1 0. 9 , (4) 

where 

SSC is the suspended-sediment concentration, in 

milligrams per liter; 

SCB is the mean sediment corrected backscatter 

(signal-to-noise ratio corrected for water 

and sediment attenuation); 

Q is discharge, in cubic feet per second; and 

1.09 is Duan’s bias correction factor (Duan, 1983). 

The model in equation 4 was determined to be the 

best predictor of suspended-sediment concentration based 

on regression evaluation statistical measures. The model 

yielded an R2

a of 0.92 and a RMSE of 1.65 mg/L; the VIF 

for discharge and SCB is 2.41, indicating little collinearity 

between variables (table 5). Residual and probability plots 

(fig. 8) indicate that the selected model resulted in residuals 

that met regression model assumptions of normality and constant variance. A model summary (app. 1) documenting calibration data and additional information on evaluation statistics 

of the acoustic surrogate model was created and reviewed as 

recommended by Landers and others (2016). 

The relation between regression-estimated suspendedsediment concentrations and measured suspended-sediment 

concentrations is depicted on figure 9. The MAPE between 

estimated and measured suspended-sediment concentration 

was 35 percent. At suspended-sediment concentrations less 

than 350 mg/L, the regression model generally overestimates 

suspended-sediment concentration. At suspended-sediment 

concentrations higher than 350 mg/L, the regression model 

underestimates suspended-sediment concentration by an average of 48 percent. These patterns were also observed when 

evaluating other explanatory variables to estimate suspendedsediment concentrations; hence, the use of other explanatory 

variables was not a solution. A possible explanation for the 

underestimation at higher concentrations relates to the distribution of suspended sediment in the cross section at higher 

flows, when high suspended-sediment concentrations are 

typically observed. Backscatter contour plots from Acoustic 

Doppler current profiler (ADCP) measurements 
16 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

Table 5. Summary of linear regression evaluation 500 

statistics for equation using discharge and sediment 450 

corrected backscatter to estimate suspended-sediment 

400

Estimated suspended-sediment concentration,

in milligrams per liter

1:1 line 

0 50 100 150 200 250 300 350 400 450 500 

concentration in U.S. Geological Survey streamflowgaging station 08067252 Trinity River at Wallisville, Texas, 

May 2014–December 2015. 

[mg/L, milligrams per liter] 

Model evaluation statistics 

Number of observations 31 

Root mean suqare error (mg/L) 1.65 

Adjusted coefficient of determination (R2 

a

) 0.92 

Nonparametric smearing bias correction factor 1.09 

Variance inflation factor 2.41 

350 

300 

250 

200 

150 

100 

50 

0 

A

2 

1 

0 

-1 

-2 

Regression-computed log10 suspended-sediment concentration 

B

3 

2 

1 

0 

-1 

-2 

-3 

Normal quantiles 

Figure 8. Estimated suspended-sediment concentrations 

for A, residual plot and B, normal probability plot for a 

multiple linear regression model developed for the Trinity 

River at U.S. Geological Survey streamflow-gaging station 

08067252 Trinity River at Wallisville, Texas, May 2014– 

December 2015. 

0 0.5 1.0 1.5 2.0 2.5 3.0 

-3 -2 -1 0 1 2 3 

Measured suspended-sediment concentration, in milligrams per liter 

Figure 9. Estimated and measured suspended-sediment 

concentrations determined from a multiple linear 

regression model at U.S. Geological Survey streamflowgaging station 08067252 Trinity River at Wallisville, Texas. 

(fig. 10) are shown to demonstrate the typical distribution of acoustic backscatter along the sampled cross section at 

various flow conditions. The backscatter profile is not homogeneous during high flows of more than approximately 6,000 

ft3/s, and the highest acoustic backscatter values typically are 

observed near the left bank and closer to the riverbed. In the 

example shown (fig. 10B), the highest backscatter values are 

measured approximately 200–260 ft from the ADVM, whereas 

the sample volume measured by the ADVM only extends 

approximately 60 ft. During high flows of approximately 

6,000 ft3/s or larger, suspended-sediment concentrations are 

estimated from acoustic backscatter data that are not representative of the entire cross section area. In order to represent 

the entire cross section area during these types of high-flow 

conditions, a lower frequency ADVM would have to be used; 

however, lower frequencies would not have the acoustic backscatter resolution to capture the fine-sized sediment particles 

typically found in the lower reaches of the Trinity River and 

may potentially underestimate suspended-sediment concentration over a larger range of suspended-sediment concentrations. 

Continuous Suspended-Sediment

Concentrations 

Corrected acoustic backscatter and computed discharge 

data collected from May 16, 2014, through December 31, 

2015, were used as input in the regression model to estimate 

suspended-sediment concentrations at the Wallisville site at 

15-minute intervals. Approximately 11 percent of the data 

used to estimate suspended-sediment concentration were 

outside the calibration range of the model; thus, these concentrations were extrapolated to obtain estimates of suspendedsediment concentrations for the entire study period. 

Residuals 
 

 

 

 

 

Suspended-Sediment Concentrations and Loads 17 

A

B

0 58.20 116.40 174.60 232.80 291.00 

0 

7.50 

15.00 

22.50 

30.00 

0 

7.50 

15.00 

22.50 

30.00 

Depth, in feet 

95 99 102 106 110 

Average backscatter, in decibels 

68 72 76 80 85 

Average backscatter, in decibels 

0 58.00 116.00 174.00 232.00 290.00 

Left Bank Distance from left bank, in feet 

EXPLANATION 

Right Bank 

(Location of Acoustic 

Doppler Velocity Meter) 

Top of velocity profile 

Bottom of velocity profile 

Bottom of channel 

Figure 10. Example of acoustic backscatter profiles from Acoustic Doppler current profiler showing backscatter 

distributions in cross sections at discharges of A, 2,370 cubic feet per second (ft3

/s), and B, 13,700 ft3/s. The Acoustic 

Doppler velocity meter at U.S. Geological Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas, 

is located on the right bank. 

A 90-percent prediction interval was calculated for every obtained from student’s t distribution 

observation to evaluate the uncertainty of regression-computed tables) for a 90-percent prediction interval 

suspended-sediment concentrations. The 90-percent prediction α = 0.10; and 

interval represents a range of values within which there is a s is the RMSE of the regression. 

90-percent certainty that the true suspended-sediment concentration value occurs (Rasmussen and others, 2009). The A time series of suspended-sediment concentration 

prediction interval for a single response (yi

) is approximately showing estimated suspended-sediment concentration and 

prediction intervals from January to December 2015 shows a 

E( yi ) +/- t × s, (5) similar pattern between suspended-sediment concentration and 

where discharge (fig. 11). Suspended-sediment concentrations varied 

in response to changes in discharge, with peak suspendedE( yi ) is the regression-estimated value, at a single sediment concentration occurring 1–2 days before the peak 

set of values of the predictors; discharge for that event. Suspended-sediment concentrations 

t is the value of the student’s t distribution also showed hysteresis, meaning that suspended-sediment 

having n-2 degrees of freedom (n is concentrations on the rising limb of the hydrograph were 

the number of observations) with the higher than suspended-sediment concentrations at identical 

exceedance probability of α/2 (alpha value discharge on the falling limb. Because of the hysteresis in 
18 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

1,500 25,000 

EXPLANATION 

90 percent prediction 

interval 

Suspended-sediment concentration, in milligrams per liter1,250 Estimated suspended- 20,000 

sediment concentration 

Discharge 

1,000 15,000 

750 10,000 

500 5,000 

250 0 

0 -5,000 

Jan. Feb. Mar. Apr. May June July Aug, Sept. Oct. Nov. Dec. 

Date 

Figure 11. Suspended-sediment concentrations estimated by using a regression model developed for the 

Trinity River at U.S. Geological Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas, 

January–December 2015. 

Daily mean discharge, in cubic feet per second 

suspended-sediment concentrations, discharge as the single 

predictor of suspended-sediment concentration would have 

overestimated values on the falling limb of the hydrograph. 

During this study, estimated suspended-sediment concentration ranged from 2 to 701 mg/L, with a mean of 97 mg/L. 

The highest suspended-sediment concentrations were observed 

during the March 2015 event, which is the first event during 

this study with a large peak discharge similar in magnitude to 

the maximum discharge measured during the study period at 

the Wallisville site. 

Suspended-Sediment Loads 

Suspended-sediment loads (SSL) were computed 

from the suspended-sediment concentrations estimated by 

the regression equation and the corresponding streamflow. 

Instantaneous sediment load was computed by using the 

following equation: 

SSLi i = × SSC Q c × , (6) 

where 

SSLi is the computed instantaneous suspendedsediment load, in tons per 15 minutes,

 SSCi

 is the computed instantaneous suspendedsediment concentration, in milligrams 

per liter,

 Q is the streamflow for the ith value, in cubic 

feet per second, and

 c is a constant, 0.000028, to convert the units to 

tons per 15 minutes (Porterfield, 1972). 

The resulting 15-minute estimates for a day were 

summed to determine the total daily SSL. The monthly SSL 

was computed by summing each daily SSL for that month. 

Because the estimated suspended-sediment concentrations 

computed from the regression equation contained error components as indicated by the RMSE and MAPE calculations 

between estimated and measured concentrations, the computed 

load estimates are inferred to also include errors. 
Suspended-Sediment Concentrations and Loads 19 

May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 

0 

100,000 

200,000 

300,000 

400,000 

500,000 

2014 2015 

Suspended-sediment load, in tons 

(383) (304) (100) (708) 

Date 

Figure 12. Estimated monthly suspended-sediment loads at U.S. Geological Survey streamflowgaging station 08067252 Trinity River at Wallisville, Texas, May 2014–December 2015. 

The estimated minimum monthly SSL was 100 tons in 

October 2014, and the maximum monthly load was 441,000 

tons in November 2015 (fig. 12). The total SSL at the Wallisville site during the study was approximately 2,200,000 tons, 

with approximately 96 percent of this load measured during 

the seven high-flow events in 2015 (table 6). High-flow event 

5 contributed the largest SSL, approximately 27 percent of the 

Table 6. Suspended-sediment load during high-flow 

events at U.S. Geological Survey streamflow-gaging 

station 08067252, Trinity River at Wallisville, Texas, May 

2014–December 2015. 

High-flow Suspendedevent Start date End date sediment load 

number (tons) 

1 1/2/2105 1/12/2015 26,176 

2 1/22/2015 2/3/2015 67,887 

3 3/7/2015 4/6/2015 430,959 

4 4/12/2015 5/12/2015 200,445 

5 5/13/2015 8/9/2015 593,764 

6 10/24/2015 12/4/2015 475,563 

7 12/5/2015 12/31/2015 315,289 

total load measured (table 6). This event started in May 2015 

and ended in August 2015, making it the longest duration 

high-flow event during this study. 

The water volume measured at the Wallisville site during 

high-flow events is a percentage of the volume measured at 

the Goodrich, Romayor, and Liberty sites; thus, the total SSL 

measured in the main channel of the Trinity River is considered to be a part of the total SSL transported from the Trinity 

River watershed into Galveston Bay. The remaining volume 

and SSL are believed to be diverted into adjacent wetlands and 

channels in the delta, which may be most of the SSLs during some high-flow events. The effect of these wetlands, in 

particular the Old River system, on the delivery of suspended 

sediment into Galveston Bay is not well understood; a decrease 

in water velocity caused by increasing vegetation and 

channel area could promote deposition of suspended-sediment 

particles, altering the quantity of SSLs and size distribution of 

suspended-sediment particles, and an unknown amount of the 

diverted SSL could be transported to Galveston Bay. Further 

study is needed to determine if the SSLs decrease and if the 

size distribution of suspended-sediment particles shifts as the 

Trinity River traverses the wetlands of the Old River System 

before emptying into Galveston Bay. 
 

 

20 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

Characterization of Water-Quality 

Conditions 

Water-quality samples and field properties were collected 

at the Wallisville site concurrently with suspended-sediment 

samples over the range of flows shown in figure 6. Field 

properties include dissolved oxygen concentration, pH, specific conductance, water temperature, and turbidity that were 

measured onsite during each sampling event of this study. 

Summary statistics for field properties at the Wallisville site 

are provided (table 7). 

Field Properties 

Dissolved oxygen concentration ranged from 4.3 to 

13.4 mg/L and followed a seasonal pattern of higher concentrations during winter and spring and lower concentrations 

during summer and fall. Measured pH ranged from 7.1 to 8.2 

and generally decreased when discharge was higher. Similar to 

pH, specific conductance also decreased during higher flows, 

which is to be expected in watersheds where increased runoff 

dilutes the concentrations of ions. Specific conductance ranged 

from 276 microsiemens per centimeter at 25 degrees Celsius 

(μS/cm at 25 °C) to 433 μS/cm at 25 °C, a considerably low 

range for a site affected by tides (Miller, 1962); however, a 

lock and dam saltwater barrier operated by the U.S. Army 

Corp of Engineers approximately 2 river miles downstream 

from the Wallisville site prevents saltwater from entering the 

Trinity River by opening and closing gates, depending on tides 

and river flows. Turbidity ranged from 2.7 to 133 Formazin 

Nephelometric Units and increased with discharge, which is 

typical when larger amounts of suspended sediment are being 

transported during higher flows (table 7). 

Nutrients 

Water-quality samples were analyzed for ammonia, 

nitrate plus nitrite, nitrite, total nitrogen, orthophosphate, and 

total phosphorus. Summary statistics for nutrient samples collected at the Wallisville site are shown in table 8. As explained 

in the “Analytical Methods” section of this report, concentrations of total nitrogen are considered estimates because of 

potential method bias.. 

Concentrations of total nitrogen and total phosphorus in 

samples collected at the Wallisville site during May 2014– 

December 2015 were plotted as separate time series (figs. 13A 

and 13B) to evaluate variability of nutrient concentrations 

resulting from seasonality and changes in discharge (fig. 13C). 

Total nitrogen and total phosphorus concentrations fluctuated 

in a similar manner. During periods of low flow during June– 

December 2014 (fig. 13C), when tidal influences controlled 

discharge in the lower Trinity River, the mean total nitrogen 

concentrations and total phosphorus concentrations were 0.66 

and 0.092 mg/L, respectively. A small peak in total nitrogen 

and total phosphorus concentrations is observed during 

September–October 2014 (figs. 13A and 13B), possibly the 

result of localized runoff and agricultural activities (fall fertilization of crops, rice field flooding). 

Table 7. Summary statistics for water-quality field properties measured at U.S. Geological 


Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas, 


May 2014–December 2015.
 

[mg/L, milligrams per liter; μS/cm at 25 °C, microseimens per cetimeter at 25 degrees Celsius; °C, degrees Celsius; 

FNU, Formazin Nephelometric Units] 

Dissolved oxygen pH Specific con- Water Turbidity concentration (standard ductance (μS/ temperature (FNU) (mg/L) units) cm at 25 °C) (°C) 

Maximum 13.4 8.2 433 32.5 133
 

Mimimum 4.3 7.1 276 8.8 2.7
 

Median 7.5 7.6 364 22.3 28
 

Table 8. Summary statistics for nutrient parameters measured in the Trinity River at Wallisville, Texas, 

May 2014–December 2015. 

[mg/L, milligrams per liter; N, nitrogen; P, phosphorus; <, less than] 

Ammonia 

(mg/L as N) 

Nitrate plus 

nitrite 

(mg/L as N) 

Nitrite 

(mg/L as N) 

Total nitrogen 

(mg/L)1 

Orthophosphate 

(mg/L as P) 

Total 

phosphorus 

Maximum 0.08 0.779 0.030 1.64 0.100 0.274 

Mimimum <0.01 <0.040 <0.001 0.56 0.006 0.067 

Median 0.02 0.195 0.006 0.93 0.037 0.120 

1

Concentrations of total nitrogent are considered estimates because of potential method bias (Rus and others, 2013). 
Characterization of Water-Quality Conditions 21 

Daily mean discharge, in cubic feet per second Total phosphorus, in milligrams per liter Total nitrogen, in milligrams per liter

A

2.00 

1.50 

1.00 

0.50 

0 

B

0.300 

0.250 

0.200 

0.150 

0.100 

0.050 

0 

C

25,000 

20,000 

15,000 

10,000 

5,000 

0 

-5,000 May June July Aug. Sept. Oct. Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. 

2014 2015 

Date 

Figure 13. Time series depicting concentrations of A, total nitrogen; B, total phosphorus; and C, 

associated daily mean discharge for samples collected at U.S. Geological Survey streamflow-gaging 

station 08067252 Trinity River at Wallisville, Texas, May 2014–December 2015. 
22 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

The highest nutrient concentrations are observed during periods of high flow corresponding to releases from Lake 

Livingston. For samples collected during the seven high-flow 

events in 2015 (table 3), when releases from Lake Livingston 

composed most of the discharge in the lower Trinity River, 

mean total nitrogen and total phosphorus concentrations 

were 1.15 mg/L and 0.165 mg/L, respectively, which are 

approximately 75 percent higher than the mean concentrations 

measured during periods of low flow. Increases in nutrient 

concentrations with flow may be caused by (1) transportation 

of water with high nutrient concentrations from Lake Livingston and the upper Trinity River watershed and (2) mobilization 

of nutrients stored in the lower Trinity River channel and 

flood plain during periods of high flow. The small contribution 

of overland runoff to stream discharge indicates overland 

runoff within the lower Trinity River watershed is not responsible for increases observed in nutrient concentrations. The 

high concentrations of nutrients delivered to the Wallisville 

site because of increased discharge from these releases also 

overshadow the influence of seasonal effects in nutrient variability at the Wallisville site; as a result, nutrient delivery to 

Galveston Bay from the main channel of the Trinity River 

likely is controlled primarily by high-flow releases from 

Lake Livingston. 

To determine the effect of streamflow variability on the 

relative amounts of ammonia, nitrate, nitrite, and organic 

nitrogen at the Wallisville site, the percentage of the composition of each form of nitrogen was computed for each sample. 

Censored values for ammonia, nitrate, and nitrite were substituted by using one-half the method reporting limit (Helsel 

and Hirsch, 2002). Maximum likelihood and robust methods 

are recommended over simple substitution for censored values 

(Helsel and Hirsch, 2002; Helsel, 2012); however, the chosen substitution method was used because censored results 

represent a relatively small percentage (less than 1 percent for 

ammonia and nitrite and less than 5 percent for nitrate) of the 

total nitrogen in each sample and do not appreciably affect the 

overall proportion of each form of nitrogen. 

For most samples collected at the Wallisville site, organic 

nitrogen was the predominant form of nitrogen, ranging from 

approximately 44 to 96 percent (fig. 14). Land cover in the 

lower Trinity River watershed is predominantly forest and 

wetlands, indicating that natural inputs are likely the main 

source of organic nitrogen (and total nitrogen) during low-flow 

conditions. When discharge increases as a result of releases 

from Lake Livingston, the concentration of organic nitrogen 

typically decreased and the concentration of nitrate increased. 

This shift in nitrogen composition may be the result of a 

change in the source of nitrogen inputs to the lower Trinity 

River, from natural inputs derived from wetlands and forested 

areas to nitrogen from fertilizers carried in runoff in the upper 

Trinity River watershed. Releases from Lake Livingston 

are typically triggered by rainfall in the upper Trinity River 

watershed, where approximately half of the land cover is 

categorized as developed or agricultural (Homer and others, 

2015). Runoff in the upper Trinity River watershed likely carries nitrate from fertilizers that flow into Lake Livingston and 

are transported into the lower Trinity River watershed during 

releases. Because organic nitrogen and nitrate are the predominant forms of nitrogen in the Trinity River, the proportion of 

ammonia and nitrite was low, ranging from 0.4 to 9 percent 

and 0.1 to 5 percent, respectively. 

Releases from Lake Livingston also appear to influence 

the composition of phosphorus being transported in the lower 

Trinity River. Dissolved phosphorus (predominantly orthophosphate) interacts with sediment particles through adsorption, often causing a proportional increase in particulate phosphorus concentrations with increasing suspended-sediment 

concentrations (Sharpley and others, 1981, House and others, 

1998). This pattern is observed at the Wallisville site (fig. 15), 

potentially as a result of sediment suspended within releases of 

water from Lake Livingston and mobilization during periods 

of high flow of previously deposited sediment particles from 

the river channel and flood plain (Dorioz, 1995; Withers and 

Jarvie, 2008). Orthophosphate concentrations do not appear 

to vary considerably with suspended-sediment concentrations 

or discharge; however, the difference between orthophosphate 

concentrations and total phosphorous concentrations increased 

as suspended-sediment concentrations increased, indicating 

that the variability of phosphorus concentrations is a result of 

an increase in particulate phosphorus and not of orthophosphate. Consequently, the predominant source of phosphorous 

to Galveston Bay from the Trinity River was in particulate 

form tied closely to suspended-sediment concentrations. 

The changes in nutrient concentration and composition 

during this study, caused by high flow from Lake Livingston 

releases, indicate that the reservoir likely plays an important 

role in the delivery of nutrients into Galveston Bay. However, 

the role of Lake Livingston in the transforming and trapping of 

nutrients and sediment and the extent of nutrient and sediment 

mobilization in the lower Trinity River, triggered by releases, 

are not well understood. Further study is needed to better 

understand the processes driven by Lake Livingston that could 

be influencing the characteristics of nutrients and sediments 

in inflows to Galveston Bay. Additionally, because phosphorous 

concentrations were correlated with suspended-sediment 

concentrations (R2

 value of 0.75) and because the relative 

amounts of phosphorous and some nitrogen forms (organic 

nitrogen and nitrate) varied with discharge, the diversion of 

water and suspended sediment into surrounding wetlands 

and channels outside of the main channel of the Trinity River 

may play a large role in the regulation of nutrient inputs into 

Galveston Bay. 
Characterization of Water-Quality Conditions 

EXPLANATION 

Organic nitrogen 

Nitrate 

Nitrite 

Ammonia 

23 

Nitrogen composition, in percent 

100 

80 

60 

40 

20 

0 

238256269366405539674859921

1,2902,0402,3705,0605,9206,1208,540

10,40011,10011,20013,70014,00014,10015,80016,10016,30017,80018,90019,80020,10020,30020,40021,60022,20022,700 

Measured discharge, in cubic feet per second 

Figure 14. Percentages of nitrogen constituents in water-quality samples collected at 

U.S. Geological Survey streamflow-gaging station 08067252 Trinity River at Wallisville, 

Texas, May 2014–December 2015. 

0.300 

0.250 

Concentration, in milligrams per liter 0.200 

0.150 

0.100 

0.050 

0 

EXPLANATION 

Total phosphorus 

Orthophosphate 

0 100 200 300 400 500 

Suspended-sediment concentration, in milligrams per liter 

Figure 15. Relation between phosphorus concentrations and suspendedsediment concentrations at U.S. Geological Survey streamflow-gaging 

station 08067252 Trinity River at Wallisville, Texas, May 2014–December 2015. 
24 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

Summary 

The U.S. Geological Survey (USGS), in cooperation with 

the Texas Water Development Board and the Galveston Bay 

Estuary Program, collected streamflow and water-quality data 

at USGS streamflow-gaging stations in the lower Trinity River 

watershed from May 2014 to December 2015 to characterize 

and improve the current understanding of the quantity and 

quality of freshwater inflows entering Galveston Bay from the 

Trinity River. Continuous streamflow records at four USGS 

streamflow-gaging stations were compared to assess changes 

in streamflow magnitude and to quantify discrepancies in 

streamflow between upstream and downstream reaches of 

the Trinity River separated by Lake Livingston, and waterquality conditions were characterized from discrete nutrient 

and sediment samples collected over a range of hydrologic 

conditions at USGS streamflow-gaging station 08067252 

Trinity River at Wallisville, Tex. (hereinafter referred to as 

“the Wallisville site”). 

During May 2014–December 2015, 08066250 Trinity 

River near Goodrich, Tex. (hereinafter referred to as “the 

Goodrich site”), 08066500 Trinity River at Romayor, Tex. 

(hereinafter referred to as “the Romayor site”), 08067000 

Trinity River at Liberty, Tex. (hereinafter referred to as “the 

Liberty site”), and at the Wallisville site followed a similar 

streamflow pattern in which computed discharge was of comparable magnitude; however, during events in which discharge 

exceeded approximately 14,000 cubic feet per second at the 

Goodrich, Romayor, and Liberty sites, only part of the volume 

was measured at the Wallisville site. During this study, only 

about 54 percent of the total volume released from Lake Livingston was accounted for at the Wallisville site. Additionally, 

discharge at the Wallisville site increased and decreased at the 

same rate as upstream stations but at a lower magnitude. This 

difference in water volume and discharge between upstream 

sites and the Wallisville site indicates that, at high flows, a 

large part of the volume released from Lake Livingston did 

not reach Galveston Bay through the main channel of the 

Trinity River. It is likely that water flowed into wetlands and 

water bodies surrounding the main channel of the Trinity 

River before reaching the Wallisville site and was stored or 

discharged through channels in the Old River system that flow 

directly into Galveston Bay. 

To characterize suspended-sediment concentrations and 

loads in Trinity River inflows to Galveston Bay, a regression 

model was developed to estimate suspended-sediment concentrations using acoustic data as a surrogate. The selected regression was based on the combination of water and sediment 

corrected backscatter and discharge. Suspended-sediment 

concentrations varied in response to changes in discharge, 

where peak suspended-sediment concentrations occurred 1 to 

2 days before the peak discharge for that event. Suspendedsediment concentrations also showed hysteresis, meaning that 

suspended-sediment concentrations on the rising limb of the 

hydrograph were higher than suspended-sediment concentrations at identical discharge on the falling limb.

 Because the water volume measured at the Wallisville 

site during high-flow events is a percentage of the volume 

measured at the Goodrich, Romayor, and Liberty sites, the 

total suspended-sediment load measured at the Wallisville 

site was considered to be a percentage of the total suspendedsediment load transported from the Trinity River watershed 

into Galveston Bay. The remaining volume and suspendedsediment load may be diverted into adjacent wetlands and 

channels in the delta, which may be the majority of the 

suspended-sediment loads during some high-flow events, and 

an unknown amount of this diverted load could be transported 

to Galveston Bay. 

Results from nutrient samples collected at the Wallisville 

site indicated that total nitrogen and total phosphorus concentrations fluctuated at a similar rate, with the highest nutrient 

concentrations occurring during periods of high flows corresponding to releases from Lake Livingston. The mean concentrations of total nitrogen and total phosphorus were approximately 75 percent higher during high flow releases than during 

periods of low flow, overshadowing the influence of seasonal 

effects in nutrient variability at the Wallisville site; as a result, 

nutrient delivery to Galveston Bay from the main channel of 

the Trinity River likely is controlled primarily by high flow 

releases from Lake Livingston from transportation of water 

with high nutrient concentrations from Lake Livingston and 

the upper Trinity River watershed and mobilization of nutrients 

stored in the lower Trinity River channel and flood plain. 

Increases in streamflow also appeared to influence the 

composition of nitrogen and phosphorus constituents. For 

most samples collected at the Wallisville site, organic nitrogen was the predominant form of nitrogen; however, when 

discharge increased because of releases from Lake Livingston, 

the percentage of organic nitrogen typically decreased and the 

percentage of nitrate increased. This shift in nitrogen composition was attributed to a change in the source of nitrogen, 

from natural inputs derived from wetlands and forested areas 

to nitrogen from fertilizers carried in runoff from the upper 

Trinity River watershed. The concentrations of total phosphorus also increased during high-flow events, likely because of 

suspended-sediment concentrations within Lake Livingston 

releases and mobilization of sediment particles in the river 

channel and flood plain during these periods of high flow. The 

increase of total phosphorous concentrations with suspendedsediment concentrations, while orthophosphate concentrations 

remained constant, indicated that the variability of phosphorus 

concentrations was a result of an increase in particulate phosphorus. Consequently, the predominant source of phosphorous 

to Galveston Bay from the Trinity River was in particulate 

form tied closely to suspended-sediment concentrations. 

The changes in nutrient concentration and composition caused by releases from Lake Livingston during this 

study indicated that the reservoir plays an important role 

in the delivery of nutrients into Galveston Bay, but further 

study is needed to better understand the processes in Lake 

Livingston that influence the characteristics of nutrients and 

sediments in inflows to Galveston Bay. Because phosphorous 
 

 

 

 

25 

concentrations were correlated with suspended-sediment 

concentrations (coefficient of determination [R2

] value of 0.75) 

and because the relative amounts of nutrients responded to 

changes in discharge, the diversion of water and suspended 

sediment into surrounding wetlands and channels outside of 

the main channel of the Trinity River may play a large role in 

the regulation of nutrient inputs into Galveston Bay. 

References Cited 

Alexander, R.B., Smith, R.A., and Schwarz, G.E., 2000, Effect 

of stream channel size on the delivery of nitrogen to the 

Gulf of Mexico: Nature, v. 403, p. 758–761. 

Belsley, D.A., Kuh, Edwin, and Welsch, R.E., 1980, Regression diagnostics—Identifying influential data and sources of 

collinearity: New York, Wiley, 300 p. [Available online at 

http://onlinelibrary.wiley.com/book/10.1002/0471725153]. 

Bouwman, A.F., Van Drecht, G., Knoop, J.M., Beusen, A.H.W., 

and Meinardi, C.R., 2005, Exploring changes in river nitrogen export to the world’s oceans: Global Biogeochemical 

Cycles, v. 19, no. 1, accessed November 28, 2016, at http:// 

onlinelibrary.wiley.com/doi/10.1029/2004GB002314/epdf. 

Bricker, S.B., Longstaff, B., Dennison, W., Jones, A., 

Boicourt, K., Wicks, C., and Woerner, J., 2008, Effects 

of nutrient enrichment in the nation’s estuaries— 

A decade of change: Harmful Algae, v. 8, no. 1, 

p. 21–32, accessed November 28, 2016, at http://dx.doi. 

org/10.1016/j.hal.2008.08.028. 

Capel, P.D., and Larson, S.J., 1995, Evaluation of selected 

information on splitting devices for water samples: U.S. 

Geological Survey Water-Resources Investigations Report 

95–4141, 103 p. [Also available at http://pubs.usgs.gov/ 

wri/1995/4141/report.pdf.] 

Chai, T., and Draxler, R.R., 2014, Root mean square error 

(RMSE) or mean absolute error (MAE)?—Arguments 

against avoiding RMSE in the literature: Geoscience Model 

Development, v. 7, p. 1247–1250, accessed November 28, 

2016, at http://www.geosci-model-dev.net/7/1247/2014/. 

Childress, C.J.O., Foreman, W.T., Connor, B.F., and Maloney, T.J., 1999, New reporting procedures based on longterm method detection levels and some considerations 

for interpretations of water-quality data provided by the 

U.S. Geological Survey National Water Quality Laboratory: U.S. Geological Survey Open-File Report 99–193, 

19 p. [Also available online at http://water.usgs.gov/owq/ 

OFR_99-193/.] 

Cloern, J.E., 1987, Turbidity as a control on phytoplankton 

biomass and productivity in estuaries: Continental Shelf 

Research, v. 7, p. 1367–1381. 

References Cited 

Domanski, M.M., Straub, T.D., and Landers, M.N., 2015, 

Surrogate Analysis and Index Developer (SAID) tool 

(version 1.0, September 2015): U.S. Geological Survey 

Open-File Report 2015–1177, 38 p., accessed November 28, 

2016, at http://pubs.usgs.gov/of/2015/1177/ofr20151177.pdf. 

Dorioz, J.M., 1995, Phosphorus storage, transport and transformations in river systems of the Lake Leman basin, in 

Kronvang B., Svendsen L.M., Sibbesen E., eds., Phosphorus 

and sediment: Ministry of Environment and Energy International Workshop, Silkeborgm Denmark, October 9–12, 1995 

[Proceedings], p. 81–88. 

Duan, Naihua, 1983, Smearing estimate—A nonparametric 

retransformation method: Journal of the American Statistical Association, v. 78, no. 383, p. 605–610. 

Edwards, T.K., and Glysson, G.D., 1999, Field methods for 

measurement of fluvial sediment: U.S Geological Survey 

Techniques of Water-Resource Investigations, book 3, 

chap. C2 (rev.), 89 p. [Also available at http://pubs.usgs. 

gov/twri/twri3-c2/.] 

Fishman, M.J., ed., 1993, Methods of analysis by the U.S. 

Geological Survey National Water Quality Laboratory— 

Determination of inorganic and organic constituents in 

water and fluvial sediments: U.S. Geological Survey OpenFile Report 93–125, 217 p. [Available online at http://pubs. 

usgs.gov/of/1993/0125/report.pdf.] 

Galloway, J.N., Dentener, F.J., Capone, D.G., Boyer, 

E.W., Howarth, R.W., Seitzinger, S.P., Asner, G.P., 

Cleveland, C.C., Green, P.A., Holland, E.A., and Karl, 

D.M., 2004, Nitrogen cycles—Past, present, and future: 

Biogeochemistry, v. 70, no. 2, p. 153–226. 

Galveston Bay Estuary Program, 2016, The Bay’s priority 

problems, accessed October 19, 2017, at http://www.gbep. 

state.tx.us/the-bays-priority-problems/. 

Guy, H.P., 1969, Laboratory theory and methods for sediment 

analysis: U.S. Geological Survey Techniques of WaterResources Investigations, chap. Cl, book 5, 58 p. 

Hamilton, S.K., Tank, J.L., Raikow, D.F., Wollheim, W.M., 

Peterson, B.J., and Webster, J.R., 2001, Nitrogen uptake 

and transformation in a Midwestern U.S. stream—A stable 

isotope enrichment study: Biogeochemistry, v. 54, no. 3, 

p. 297–340, accessed November 28, 2016, at http://link. 

springer.com/article/10.1023/A:1010635524108. 

Harding, L.W., Meeson, B.W., and Fisher, T. R., 1986, 

Phytoplankton production in two east coast estuaries— 

Photosynthesis-light functions and patterns of carbon 

assimilation in Chesapeake and Delaware bays: Estuarine, 

Coastal and Shelf Science, v. 23, no. 6, p. 773–806. [Also 

available at http://www.sciencedirect.com/science/article/ 

pii/0272771486900740]. 
 

 

 

 

26 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

Helsel, D.R., 2012, Statistics for censored environmental 

data using Minitab and R (2d ed.): New York, John Wiley 

and Sons, 344 p. [Also available at http://www.wiley.com/ 

WileyCDA/WileyTitle/productCd-0470479884.html.] 

Helsel, D.R., and Hirsch, R.M., 2002, Statistical methods 

in water resource: U.S. Geological Survey Techniques of 

Water-Resources Investigations, book 4, chap. A3, 510 p., 

accessed September 16, 2016, at https://pubs.usgs.gov/twri/ 

twri4a3/#pdf. 

Homer, C.G., Dewitz, J.A., Yang, L., Jin, S., Danielson, P., 

Xian, G., Coulston, J., Herold, N.D., Wickham, J.D., and 

Megown, K., 2015, Completion of the 2011 National Land 

Cover Database for the conterminous United States— 

Representing a decade of land cover change information: 

Photogrammetric Engineering and Remote Sensing, v. 81, 

no. 5, p. 345–354. 

Horowitz, A.J., Hayes, T.S., Gray, J.R., and Capel, P.D., 1997, 

Selected laboratory tests of the whole-water sample splitting 

capabilities of the 14-liter churn and the Teflon cone splitters: 

U.S. Geological Survey Office of Water Quality Technical 

Memorandum No. 97.06, 28 p. 

House, W.A., 2003, Geochemical cycling of phosphorus in 

rivers: Applied Geochemistry, v. 18, no. 5, p. 739–748. 

House, W.A., Jickells, T.D., Edwards, A.C., Praska, K.E., 

and Denison, F.H., 1998, Reactions of phosphorus with 

sediments in fresh and marine waters: Soil Use and Management, v. 14, p. 139–146. 

Kennish, M.J., 2002, Environmental threats and environmental future of estuaries: Environmental Conservation, v. 29, 

no. 1, p. 78–107. 

Kimmerer, W.J., 2002, Physical, biological, and management responses to variable freshwater flow into the San 

Francisco Estuary: Estuaries, v. 25, no. 6, p. 1275–1290, 

accessed October 13, 2016, at http://link.springer.com/ 

article/10.1007/BF02692224. 

Landers, M.N., Straub, T.D., Wood, M.S., and Domanski, 

M.M., 2016, Sediment acoustic index method for computing continuous suspended-sediment concentrations: 

U.S. Geological Survey Techniques and Methods, book 3, 

chap. C5, 63 p., accessed October 3, 2016, at http://dx.doi. 

org/10.3133/tm3C5. 

Lee, M.T., 2010, A preliminary evaluation of Trinity River 

sediment and nutrient loads into Galveston Bay, Texas, 

during two periods of high flow, in Second Joint Federal 

Interagency Conference, Las Vegas, Nevada, June 27–July 1, 

2010, Proceedings: Ninth Federal Interagency Sedimentation Conference and Fourth Federal Interagency Hydrologic 

Modeling Conference, 12 p. 

Lee, W., Buzan, D., Eldridge, P., and Pulich, W., 2001, 

Freshwater inflow recommendation for the TrinitySan Jacinto Estuary of Texas: Austin, Tex., Texas Parks 

and Wildlife, 59 p. 

Lester, L.J., and Gonzalez, L.A., eds., 2011, The state of the 

bay—A characterization of the Galveston Bay ecosystem 

(3d ed.): Houston, Tex., Texas Commission on Environmental Quality, Galveston Bay Estuary Program, 356 p., 

accessed November 28, 2016, at http://galvbaydata.org/ 

StateoftheBay/tabid/1846/Default.aspx. 

Levesque, V.A., and Oberg, K.A., 2012, Computing discharge using the index velocity method: U.S. Geological 

Survey Techniques and Methods, book 3, chap. A23, 148 p., 

accessed September 16, 2016, at http:// pubs.usgs.gov/ 

tm/3a23. 

Livingston, R.J., Niu, X., Lewis, F.G., and Woodsum, G.C., 

1997, Freshwater input to a gulf estuary—Long-term control of trophic organization: Ecological Applications, v. 7, 

no. 1, p. 277–299. 

Lorenzen, T.J., and Anderson, V.L., 1993, Design of experiments—A no-name approach: New York, Marcel Dekker, 

414 p. 

Mainstone, C.P., and Parr, William, 2002, Phosphorus in 

rivers—Ecology and management: Science of the Total 

Environment, v. 282–283, p. 25–47, accessed December 9, 

2016, at http://www.sciencedirect.com/science/article/pii/ 

S0048969701009378. 

Mayer, D.G., and Butler, D.G., 1993, Statistical validation: Ecological modelling, v. 68, no. 1–2, p. 21–32, 

accessed January 9, 2017, at http://www.sciencedirect.com/ 

science/article/pii/0304380093901052. 

Miller, E.G., 1962, Observations of tidal flow in the Delaware 

River: U.S. Geological Survey Water-Supply Paper 1586–C, 

26 p., accessed October 3, 2016, at http://pubs.usgs.gov/ 

wsp/1586c/report.pdf. 

Montagna, P.A., and Kalke, R.D., 1992, The effect of 

freshwater inflow on meiofaunal and macrofaunal 

populations in the Guadalupe and Nueces Estuaries, 

Texas: Estuaries, v. 15, no. 3, p. 307–326. 

Mueller, D.K., Schertz, T.L., Martin, J.D., and Sandstrom, 

M.W., 2015, Design, analysis, and interpretation of field 

quality-control data for water-sampling projects: U.S. 

Geological Survey Techniques and Methods, book 4, 

chap. C4, 54 p., accessed October 3, 2016, at http://dx.doi. 

org/10.3133/tm4C4. 
 

 

 

 

27 

Mueller, D.S., Wagner, C.R., Rehmel, M.S., Oberg, K.A, 

and Rainville, Francois, 2013, Measuring discharge with 

acoustic Doppler current profilers from a moving boat (ver. 

2.0, December 2013): U.S. Geological Survey Techniques 

and Methods, book 3, chap. A22, 95 p., accessed October 3, 

2016, at http://dx.doi.org/10.3133/tm3A22. 

National Oceanic and Atmospheric Administration, 2016, 

National Centers for Environmental Information— 

Climatological rankings, accessed September 16, 

2016, at http://www.ncdc.noaa.gov/temp-and-precip/ 

climatological-rankings/. 

Patton, C.J., and Kryskalla, J.R., 2003, Methods of analysis 

by the U.S. Geological Survey National Water Quality 

Laboratory—Evaluation of alkaline persulfate digestion 

as an alternative to Kjeldahl digestion for determination 

of total and dissolved nitrogen and phosphorus in water: 

U.S. Geological Survey Water-Resources Investigations 

Report 03–4174, 33 p. 

Patton, C.J., and Kryskalla, J.R., 2011, Colorimetric determination of nitrate plus nitrite in water by enzymatic reduction, automated discrete analyzer methods: U.S. Geological 

Survey Techniques and Methods, book 5, chap. B8, 34 p. 

[Also available at https://pubs.usgs.gov/tm/05b08/.] 

Peterson, B.J., Wollheim, W.M., Mulholland, P.J., Webster, 

J.R., Meyer, J.L., Tank, J.L., Martí, E., Bowden, W.B., 

Valett, H.M., Hershey, A.E., and McDowell, W.H., 2001, 

Control of nitrogen export from watersheds by headwater 

streams: Science, v. 292, no. 5514, p. 86–90. 

Porterfield, George, 1972, Computation of fluvial-sediment 

discharge: Techniques of Water-Resources Investigations 

of the United States Geological Survey, book 3, chap. C3, 

66 p., accessed October 6, 2016, at http://pubs.usgs.gov/ 

twri/twri3-c3/. 

Powell, G. L., Matsumoto, Junji, and Brock, D. A., 2002, 

Methods for determining minimum freshwater inflow 

needs of Texas bays and estuaries: Estuaries, v. 25, no. 6, 

p. 1262–1274, accessed December 9, 2016, at http://link. 

springer.com/article/10.1007/BF02692223. 

Rantz, S.E., and others, 1982a, Measurement and computation 

of streamflow—Volume 1 measurement of stage and discharge: U.S. Geological Survey Water-Supply Paper 2175, 

284 p., accessed December 9, 2016, at http://pubs.usgs.gov/ 

wsp/wsp2175/pdf/WSP2175_vol1a.pdf. 

Rantz, S.E., and others, 1982b, Measurement and computation of streamflow—Volume 2 computation of discharge: 

U.S. Geological Survey Water-Supply Paper 2175, 631 p., 

accessed December 9, 2016, at http://pubs.usgs.gov/wsp/ 

wsp2175/pdf/WSP2175_vol2a.pdf. 

References Cited 

Rasmussen, P.P., Gray, J.R., Glysson, G.D., and Ziegler, A.C., 

2009, Guidelines and procedures for computing time-series 

suspended-sediment concentrations and loads from instream turbidity-sensor and streamflow data: U.S. Geological Survey Techniques and Methods book 3, chap. C4, 

53 p., accessed October 12, 2016, at http://pubs.usgs.gov/ 

tm/tm3c4/. 

Rus, D.L., Patton, C.J., Mueller, D.K., and Crawford, C.G., 

2013, Assessing total nitrogen in surface-water samples— 

Precision and bias of analytical and computational methods: 

U.S. Geological Survey Scientific Investigations Report 

2012–5281, 38 p. 

Sauer, V.B., and Turnipseed, D.P., 2010, Stage measurement 

at gaging stations: U.S. Geological Survey Techniques 

and Methods, book 3, chap. A7, 45 p., accessed October 3, 

2016, at http://pubs.usgs.gov/tm/tm3-a7/. 

Seitzinger, S. P., Harrison, J. A., Dumont, Egon, Beusen, A. 

H.W., and Bouwman, A. F., 2005, Sources and delivery 

of carbon, nitrogen, and phosphorus to the coastal zone— 

An overview of Global Nutrient Export from Watersheds 

(NEWS) models and their application: Global Biogeochemical Cycles, v. 19, accessed November 28, 2016, at http:// 

onlinelibrary.wiley.com/doi/10.1029/2005GB002606/epdf. 

Sharpley, A.N., Menzel, R.G., Smith, S.J., Rhoades, E.D., and 

Olness, A.E., 1981, The sorption of soluble phosphorus by 

soil material during transport in runoff from cropped and 

grassed watersheds: Journal of Environmental Quality, 

v. 10, no. 2, p. 211–215. 

Sklar, F.H., and Browder, J.A., 1998, Coastal environmental 

impacts brought about by alterations to freshwater flow in 

the Gulf of Mexico: Environmental Management, v. 22, 

no. 4, p. 547–562. 

Smith, V.H., Tilman, G.D., and Nekola, J.C., 1999, Eutrophication—Impacts of excess nutrient inputs on freshwater, 

marine, and terrestrial ecosystems: Environmental Pollution, v. 100, no. 1, p. 179–196. 

Texas Parks and Wildlife Department, 1974, An analysis of 

Texas waterways—A report on the physical characteristics 

of rivers, streams, and bayous in Texas, accessed October 

3, 2016, at http://tpwd.texas.gov/publications/pwdpubs/ 

pwd_rp_t3200_1047/index.phtml. 

Texas Water Development Board, 2016, 2017 State water plan, 

water for Texas, 164 p., accessed September 21, 2016, at 

http://www.twdb.texas.gov/waterplanning/swp/2017/. 

Topping, D.J., and Wright, S.A., 2016, Long-term continuous 

acoustical suspended-sediment measurements in rivers— 

Theory, application, bias, and error: U.S. Geological Survey 

Professional Paper 1823, 98 p., accessed November 28, 

2016, at http://dx.doi.org/10.3133/pp1823. 
28 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 28 

Trinity River Authority of Texas, 2012, Trinity River Basin 

master plan, 58 p., accessed September 21, 2016, at http:// 

www.trinityra.org/downloads/Master_Plan_2012.pdf. 

U.S. Environmental Protection Agency, 1993, Method 365.1 

determination of phosphorus by semi-automated colorimetry, revision 2.0, in O’Dell, J.W., ed., Methods for the determination of inorganic substances in environmental samples: 

U.S. Environmental Protection Agency EPA/600/R–93/100. 

U.S. Fish and Wildlife Service, 2016, National Wetlands 

Inventory website, accessed September 21, 2016, at http:// 

www.fws.gov/wetlands/. 

U.S. Geological Survey, variously dated, National field manual for the collection of water-quality data: U.S. Geological 

Survey Techniques of Water-Resources Investigations, book 

9, chaps. A1–A10, accessed October 17, 2016, at http:// 

water.usgs.gov/owq/FieldManual/index.html. 

U.S. Geological Survey, 2016, U.S. Geological Survey 

National Water Information System, accessed September 

21, 2016, at http://dx.doi.org/10.5066/F7P55KJN. 

Withers, P.J.A., and Jarvie, H.P., 2008, Delivery and cycling 

of phosphorus in rivers—A review: Science of the Total 

Environment, v. 400, no. 1, p. 379–395. 

Wood, M.S., and Teasdale, G.N., 2013, Use of surrogate 

technologies to estimate suspended sediment in the Clearwater River, Idaho, and Snake River, Washington, 2008–10: 

U.S. Geological Survey Scientific Investigations Report 

2013–5052, 30 p. 

Xylem Analytics, 2016, YSI—Monitor, analyze, and protect 

the world’s natural resources, accessed November 1, 2016, 

at http://www.sontek.com/. 

Yang, S.L., Milliman, J. D., Li, P., and Xu, K., 2011, 50,000 

Dams later—Erosion of the Yangtze River and its delta: 

Global and Planetary Change, v. 75, no. 1 p. 14–20. 
Appendix 1 29 

Appendix 1. Model Archival Summary for Suspended-Sediment Concentration 

at U.S. Geological Survey Streamflow-Gaging Station 08067252 Trinity River at 

Wallisville, Texas
 

This model archival summary documents the suspendedsediment concentration (SSC) model developed to compute 

15-minute suspended-sediment concentration from May 16, 

2014, at U.S. Geological Survey (USGS) streamflow-gaging 

station 08067252 Trinity River at Wallisville, Tex. The methods follow USGS guidance documented in USGS Techniques 

and Methods, book 3, chapter C5 (Landers and others, 2016). 

Site and Model Information 

Wallisville site (USGS streamflow-gaging station 08067252 

Trinity River at Wallisville, Tex.) 

Location: Latitude 29°49’52.71”, longitude 94°45’14.89”W 

NAD 27 

Chambers County, Tex., Hydrologic Unit 12030203, at the 

Index Velocity gage approximately 2.5 miles upstream from 

a river-stage gage at the U.S. Army Corps of Engineers river 

lock and dam structure in the Trinity River, 3.9 river miles 

upstream from where the Trinity River enters Galveston Bay. 

Drainage area: 17,796 square miles 

Contributing drainage area: 17,796 square miles 

Date rating model was created: 05/18/2016 

Model calibration data period: 05/16/2014–12/09/2015 

Model application date: Starting 05/16/2014 

Computed by: Zulimar Lucena, USGS, Houston, Tex. 

(zlucena@usgs.gov) 

Reviewed by: Mark Landers, USGS, Office of Surface Water, 

Atlanta, Ga. 

Approved by: Robert Joseph, USGS, Texas Water Science 

Center Director, Austin, Tex. 

Physical Sampling Equipment and Sampling 

Details 

Suspended-sediment samples are collected bimonthly 

during the first year of model development and monthly during the second year of model calibration. After model calibration, samples are collected at least quarterly during low-flow 

conditions. During high-flow events, samples are collected 

at a higher frequency depending on the duration of the event. 

Samples are collected within each of five vertical sections in a 

cross section. The location of each vertical section is detervelocities exceed 1.5 feet per second (ft/s), the cross section 

is divided using the equal discharge increment method, and 

samples are collected using a US DH–2 sampler. When water 

velocities are below 1.5 ft/s, grab samples are collected along 

the cross section using a weighted bottle sampler. Samples are 

analyzed for suspended-sediment concentrations (SSC) in the 

USGS Kentucky Water Science Center Sediment Laboratory. 

Surrogate Equipment and Setup Details 

A 1.5-megahertz (MHz) SonTek Argonaut-Side-Looker 

(SL) Acoustic Doppler velocity meter (ADVM) is installed 

at the site to compute discharge in cubic feet per second and 

obtain sediment backscatter data (table 1–1). The ADVM is 

bolted to a Cupronickel 2-inch diameter pipe that is pinned in 

place to a steel bracket welded onto the stream bulkhead on 

the right bank of the river. The Acoustic Doppler beams are 

horizontal and perpendicular to flow. The gage house, containing a battery, solar panel, Data Collection Platform, and regulator, is located on the right bank, approximately 10 feet from 

the ADVM. The ADVM configuration settings are provided 

(table 1–2). 

Model Calibration Dataset 

All data were collected using USGS protocols and are 

available on the USGS National Water Information System 

(NWIS) database (U.S. Geological Survey, 2016). The dataset 

used to develop the regression model consisted of 35 measurements of SSC (equal discharge increment and grab samples) 

and ADVM data collected from May 16, 2014, to December 9, 

2016. Two samples were excluded because of missing acoustic 

backscatter data. Two samples were removed based on outlier 

diagnostic indicators and further evaluation of the data. From 

the 35 samples, 31 were used in the model calibration dataset. 

The 31 samples were collected over the range of continuously observed streamflow conditions as shown in the duration 

curves below. The duration curves were developed for streamflow and sediment corrected backscatter () data collected in 

May 2014–December 2015 (fig. 1–1). Summary statistics for 

SSC data used in the model calibration dataset are provided 

mined based on discharge and water velocity. When water (table 1–3). 
30 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River

Table 1–1. Acoustic Doppler velocity meter (ADVM) specifications. 

Effective trans- Frequency Slant beam angle Echo intensity Make Model Serial number ducer diameter (MHz) (degrees) factor (meters) 

SonTek Argonaut SL 1.5 E3902 0.03 25 0.43 

Table 1–2. Acoustic Doppler velocity meter (ADVM) configuration settings. 

Blanking Number Cell size Measurement averaging period Measurement interval Date distance of cells (meters) (seconds) (seconds) installed (meters) 

3.05 5 3.05 600 (from 5/16/2014 to 1/15/2015) 900 (from 5/16/2014 to 1/15/2015) 5/16/2014 

60 (from 1/16/2015 to 8/5/2015) 60 (from 1/16/2015 to 8/5/2015) 

30,000 100 Sediment corrected backscatter (SCB), in decibels

EXPLANATION EXPLANATION 25,000

Streamflow, in cubic feet per second 

Model calibration sample 90 Model calibration sample 

Period of record flow duration Period of record SCB duration 

curve 

80 

70 

60 

50 

40 

0 20 40 60 80 100 

20,000 curve 

15,000 

10,000 

5,000 

0 

-5,000

0 20 40 60 80 100 

Frequency of exceedance, in percent 

Figure 1–1. Streamflow and sediment corrected backscatter duration curves at U.S. Geological Survey streamflowgaging station 08067252 Trinity River at Wallisville, Texas, May 2014–December 2015. 

Table 1–3. Summary statistics for suspended-sediment concentration 

data collected at U.S. Geological Survey streamflow-gaging station 

08067252 Trinity River at Wallisville, Texas, May 2014–December 2015. 

Suspended sediment concentration Summary statistic (milligrams per liter) 

Minimum 5.0 

Maximum 453 

Median 65.0 

Mean 11.3 

Count 31 
Appendix 1 31

Suspended-sediment particles smaller than 0.0625 millimeter (mm) were measured for 27 samples and ranged from 

37 to 100 percent, with a median of 85.5. The percentage of 

fine-sized particles decreased as discharge increased. Full-size 

analysis was also performed for six samples between April 3, 

2015, and June 10, 2015 (table 4). For these samples, the fraction of sediment particles smaller than fine sand (smaller than 

0.25 mm) ranged from 96 to 100 percent.

Model Development

Suspended-sediment concentrations at the site are computed from a calibrated regression model between streamflow, 

SSCs, and continuously measured surrogates. The model was 

developed by the evaluation of mean sediment corrected backscatter ( ), sediment attenuation coefficient (SAC), and 

streamflow as explanatory variables for SSC. 

By using the Surrogate Analysis and Index Developer 

(SAID) tool (version 1.0), SCB was calculated from measured 

backscatter following the methods described in Landers and 

others (2016). The processing settings used in the SAID tool 

are shown (table 1–4).

The SAID tool was also used to develop an ordinary least 

squares linear regression analysis, which examined streamflow, SAC, and SCB as explanatory variables for estimating 

SSC. Combinations of these three variables were evaluated to 

determine the best explanatory variables for SSC. A multiple 

linear regression model with a combination of streamflow and 

SCB as explanatory variables was determined to be the best 

model based on adjusted coefficient of determination (R2

a

), 

significance tests, model root mean square error, residual 

plots, and correlation of explanatory variables. All considered 

models were evaluated using these statistical measures and are 

included (table 1–5). 

SCB

Table 1–4. Acoustic Doppler velocity meter settings used to process backscatter data with the Surrogate Analysis and Index 

Developer tool.

[Avg., average calculated from the two Acoustic Doppler beams; WCB, water corrected backscatter; SNR, signal to noise ratio]

Acoustic Doppler 

beam used

Moving average 

span

Backscatter values 

(SNR or amplitude) Cells used Near field correction WCB profile adjustment

Avg. 1 SNR 1–5 Yes Yes

Table 1–5. Alternative models considered for estimating suspended-sediment concentrations at U.S. Geological Survey streamflowgaging station 08067252 Trinity River at Wallisville, Texas.

[R2, coefficient of determination; SSC, suspended-sediment concentration; , mean sediment corrected backscatter; –, not applicable; log10, base-10 

logarithm; Q, discharge; SAC, sediment attenuation coefficient]

Response 

variable

Explanatory 

variables Root mean square error R2 Adjusted R2 Variance inflation factor

SSC 82.0 0.58 0.57 –

log10SSC 0.229 0.87 0.87 –

log10SSC log10Q 0.281 0.79 0.79 –

log10SSC Q 0.276 0.81 0.80 –

log10SSC SAC 0.590 0.14 0.11 –

log10SSC , SAC 0.223 0.88 0.87 1.0, 1.0

log10SSC , log10Q 0.209 0.89 0.88 1.6,1.6

log10SSC , Q, SAC 0.213 0.89 0.87 2.5, 2.4, 3.9

SCB

SCB

SCB

SCB

SCB

SCB
 

 

 

 

32 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

Model Summary 

The model of SSC for USGS streamflow-gaging station 

08067252 Trinity River at Wallisville, Tex., has an adjusted 

coefficient of determination of 0.92 and is its equation in 

linear form is: 

log10SSC = -1.57 + 0.416SCB+ 0.000031Q 

where 

SSC is the suspended-sediment concentration, in 

milligrams per liter; 

SCB is the mean sediment corrected backscatter, in 

decibels; and 

Q is the computed discharge, in cubic feet per 

second. 

The SSC was transformed before regression analysis, and 

the predicted mean of the variable may be biased. To account 

for this bias, a nonparametric smearing bias correction factor 

(BCF) of 1.09 was applied to the predicted variable (table 1–6). 

Detailed statistical information for the selected model and 

statistical measures useful for evaluating the model are summarized (table 1–7). 

Table 1–6. Suspended-sediment regression model and nonparametric smearing bias correction factor for U.S. Geological Survey 

streamflow-gaging station 08067252 Trinity River at Wallisville, Texas. 

[BCF, nonparametric smearing bias correction factor; SSC, suspended-sediment concentration; SCB, sediment corrected backscatter; Q, discharge] 

Start date End date Linear regression model BCF 

0.0416SCB+0.000031Q 05/16/2014 – SSC = 0.0269 ×10 × BCF 1.09
 

Appendix 1 33 

Table 1–7. Summary statistics for the selected model and statistical measures to evaluate the suspended-sediment regression model for 

U.S. Geological Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas. 

[SSC, suspended-sediment-concentration; SCB, sediment corrected backscatter; Q, discharge; dB, decibels; mg/L, milligrams per liter; R2, coefficient of determination; ft3

/s, cubic feet per second; E, exponential; Cook’s D, Cook’s distance; DFFITS, difference in fit statistic] 

Rating equation form 

log SCB 10SSC = -1.57 + 0.000031Q + 0.0416 

Explanatory and response variable summary statistics 

Q (ft3

/s) SCB (dB) log10(SSC) SSC (mg/L) 

Minimum –691 55.1 0.699 5 

1st quartile 1,050 62.3 1.089 12.5 

Median 10,600 74.7 1.813 65 

Mean 9,730 71.8 1.711 113 

3rd quartile 17,000 78.7 2.257 181 

Maximum 23,700 86.5 2.656 453 

Rating calibration 

Number of 31 

observations 

Error degrees of freedom 28 

Root mean square error 0.181 

R2 0.92 

Adjusted R2 0.92 

F-statistic vs. constant model 163 

p-value 3.87E-16 

Variance inflation factor (Q, ) 2.41, 2.41 

Estimated coefficients 

Estimate Standard error of 

coefficients Student’s t-value p-value 

Lower value of 

90 percent confidence interval 

Upper value of 

90 percent confidence interval 

(Intercept) -1.57 0.410 -3.8206 0.0007 -2.26 -0.870 

Q 3.01E-05 7.11E-06 4.2374 0.0002 0.0000 0.0000 

SCB 0.0416 0.00650 6.4312 0.0000 0.0306 0.0526 

Nonparametric smearing 1.088 

bias 

correction factor 

Probability plot correlation 0.983 

coefficient 

Variance-covariance matrix 

(Intercept) Discharge SCB

(Intercept) 0.168 2.23E-06 -0.00260 

Discharge 2.23E-06 5.06E-11 -3.79E-08 

-0.00260 -3.79E-08 4.18E-05 

Test Criteria 

High leverage 0.290 

Extreme outlier (Standardized residual) 3 

(absolute value) 

High influence (Cook’s D) 2.12 

High influence (DFFITS) 0.622 
34 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

Residual plots showing distribution of residuals throughout the period of the calibration dataset and the range of 

predicted log transformed SSC concentrations and a normal 

quantile plot are provided (fig. 1–2), along with a scatter plot 

of observed and computed SSC values (fig. 1–3). Model calibration data, SSC predicted values, and selected statistics for 

individual observations are provided (table 1–8). 

Suspended-Sediment Concentration Record 

The continuous time-series SSC record is computed 

using the regression model from May 16, 2014, through 

December 31, 2015. Data are computed at 15-minute intervals. 

The continuous SSC record at the Wallisville site from January 

to December 2015 is depicted in figure 1–4. 

0.6 

0.4 

0.2 

0 

-0.2 

-0.4 -0.4 

-0.2 

0 

0.2 

0.4 

0.6 

Residuals 

0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 

Residuals

05-14

06-14

07-1408-1409-14

10-14

11-14

12-14

01-15

02-1503-15

04-15

05-15

06-15

07-1508-15

09-15

10-15

11-15

12-15 

Predicted log10 of suspended-sediment concentration Month-year 

0.6 

0.4 

0.2 

-3 -2 -1 0 1 2 3 

Residuals

0.0 

-0.2 

-0.4 

-0.6 

Normal quantiles 

Figure 1–2. Diagnostics plots for selected regression model developed for U.S. Geological Survey streamflow-gaging 

station 08067252 Trinity River at Wallisville, Texas. 
 

Suspended-sediment sample Explanatory variables Model results 

Date and 

time Measured SSC 

(24hr) 

(CST) (mg/L) log10 

5/16/2014 

Computed SCB Discharge 

(dB) (ft3

/s) 

Predicted 

(mg/L) log10 

Residuals 

log10 

Standard­ Normal ized residu­ quantiles als 

Leverage Cook’s D DFFITS 

11:35 453 2.656 81.73 12,900 180 2.219 0.437 2.538 2.070 0.100 0.239 0.948 

6/19/2014 

12:40 17 1.230 62.68 1,960 14 1.097 0.133 0.759 0.801 0.067 0.014 0.203 

7/30/2014 

11:45 7 0.845 57.40 -310 7 0.809 0.036 0.210 0.243 0.117 0.002 0.075 

8/6/2014 

11:13 9 0.954 59.61 -337 9 0.900 0.054 0.312 0.413 0.094 0.003 0.099 

8/26/2014 

11:38 5 0.699 60.28 132 10 0.942 -0.243 -1.402 -1.633 0.088 0.063 -0.443 

9/10/2014 

12:13 6 0.778 59.13 943 9 0.919 -0.141 -0.817 -0.695 0.098 0.024 -0.268 

9/22/2014 

14:00 19 1.279 61.20 2,190 12 1.042 0.236 1.355 1.383 0.078 0.052 0.401 

10/10/2014 

11:46 8 0.903 55.06 469 6 0.735 0.168 1.009 0.917 0.163 0.066 0.445 

Appendix 1 35

0 100 200 300 400 500 

0 

100 

200 

300 

400 

500

Predicted suspended-sediment concentration, in milligrams per liter

1:1 line 

Measured suspended-sediment concentration, in milligrams per liter 

Figure 1–3. Model predicted and measured suspended-sediment concentrations at U.S. 

Geological Survey streamflow-gaging station 08067252 Trinity River at Wallisville, Texas 

Table 1–8. Calibration data used for suspended-sediment model development at U.S. Geological Survey streamflow-gaging station 

08067252 Trinity River at Wallisville, Texas, and selected statistical results.—Continued 

[hr, hour; CST, central standard time; SSC, suspended-sediment concentration; mg/L, milligrams per liter; SCB, mean sediment corrected backscatter; dB, decibels; ft3

/s, cubic feet per second; mg/L, milligrams per liter; log10, base-10 logarithm, Cook’s D, Cook’s distance; DFFITS, difference in fit statistic] 
Table 1–8. Calibration data used for suspended-sediment model development at U.S. Geological Survey streamflow-gaging station 

08067252 Trinity River at Wallisville, Texas, and selected statistical results.—Continued 

[hr, hour; CST, central standard time; SSC, suspended-sediment concentration; mg/L, milligrams per liter; SCB , mean sediment corrected backscatter; dB, deci

bels; ft3/s, cubic feet per second; mg/L, milligrams per liter; log10, base-10 logarithm, Cook’s D, Cook’s distance; DFFITS, difference in fit statistic] 

Suspended-sediment sample Explanatory variables Model results 

Date and Standard­ Computed Residuals Normal time Measured SSC Predicted ized residu­ Leverage Cook’s D DFFITS Discharge log10 quantiles (24hr) als 

(CST) (mg/L) log10 (dB) (ft3

/s) (mg/L) log10 

10/15/2014 

12:27 11 1.041 62.13 770 12 1.039 0.003 0.016 0.080 0.075 0.000 0.005 

11/3/2014 

11:24 9 0.954 62.68 81 12 1.040 -0.086 -0.494 -0.413 0.078 0.007 -0.142 

12/12/2014 

11:35 9 0.954 60.78 1,370 11 1.000 -0.046 -0.265 -0.243 0.082 0.002 -0.078 

1/7/2015 

12:22 380 2.580 80.55 14,700 182 2.224 0.356 2.029 1.633 0.067 0.099 0.579 

1/12/2015 

11:29 65 1.813 73.71 11,400 75 1.840 -0.027 -0.152 -0.080 0.034 0.000 -0.028 

1/14/2015 

13:12 65 1.813 78.87 10,600 117 2.031 -0.218 -1.252 -1.047 0.083 0.047 -0.380 

1/16/2015 

11:06 84 1.924 78.33 11,100 115 2.023 -0.099 -0.565 -0.502 0.069 0.008 -0.151 

1/20/2015 

12:20 38 1.580 74.76 8,550 68 1.798 -0.218 -1.234 -1.198 0.053 0.029 -0.296 

1/23/2015 

11:42 39 1.591 76.37 6,670 70 1.808 -0.217 -1.263 -0.917 0.105 0.062 -0.438 

2/15/2015 

15:20 17 1.230 68.00 -691 19 1.238 -0.008 -0.047 0.000 0.126 0.000 -0.017 

3/12/2015 

12:10 359 2.555 83.44 14,900 244 2.350 0.205 1.193 1.198 0.107 0.057 0.415 

3/20/2015 

12:24 244 2.387 86.54 17,000 379 2.542 -0.155 -0.920 -0.801 0.142 0.047 -0.374 

4/3/2015 

10:55 49 1.690 73.24 5,290 47 1.636 0.054 0.309 0.327 0.080 0.003 0.089 

5/4/2015 

12:50 225 2.352 84.42 17,000 310 2.454 -0.102 -0.594 -0.596 0.104 0.014 -0.200 

5/18/2015 

13:00 201 2.303 76.76 20,400 188 2.238 0.065 0.381 0.596 0.116 0.006 0.136 

5/22/2015 

11:45 236 2.373 79.13 20,500 238 2.340 0.033 0.193 0.161 0.097 0.001 0.062 

5/30/2015 

11:30 169 2.228 77.35 20,200 196 2.257 -0.029 -0.167 -0.161 0.106 0.001 -0.056 

6/10/2015 

14:15 185 2.267 75.44 21,300 177 2.210 0.057 0.340 0.502 0.158 0.007 0.145 

6/26/2015 

12:57 78 1.892 74.76 20,600 158 2.161 -0.269 -1.607 -2.070 0.151 0.153 -0.697 

7/16/2015 

12:59 165 2.217 75.72 17,000 135 2.092 0.125 0.714 0.695 0.067 0.012 0.190 

8/5/2015 

12:20 32 1.505 71.77 4,920 40 1.564 -0.059 -0.338 -0.327 0.067 0.003 -0.089 

36 Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River 

­
Appendix 1 37 

Table 1–8. Calibration data used for suspended-sediment model development at U.S. Geological Survey streamflow-gaging station 

08067252 Trinity River at Wallisville, Texas, and selected statistical results.—Continued 

[hr, hour; CST, central standard time; SSC, suspended-sediment concentration; mg/L, milligrams per liter; , mean sediment corrected backscatter; dB, deci SCB -

bels; ft3/s, cubic feet per second; mg/L, milligrams per liter; log10, base-10 logarithm, Cook’s D, Cook’s distance; DFFITS, difference in fit statistic] 

Suspended-sediment sample Explanatory variables Model results 

Date and 

time 

(24hr) 

Measured SSC Computed 

Discharge Predicted Residuals 

log10

Standardized residuals

Normal 

quantiles Leverage Cook’s D DFFITS

(CST) (mg/L) log10 (dB) (ft3

/s) (mg/L) log10 

11/13/2015 

12:45 162 2.210 78.95 23,700 292 2.429 -0.219 -1.322 -1.383 0.167 0.117 -0.600 

12/9/2015 

11:55 168 2.225 75.22 16,300 122 2.051 0.175 0.992 1.047 0.062 0.022 0.254 

1,400 30,000 

Suspended-sediment concentration, in millirgams per liter 1,200
 25,000
 

1,000
 20,000
 

800 15,000 

600 10,000 

400 5,000 

200 0 

-5,000 

Jan. Feb. Mar. Apr. May June July Aug. Sept. Oct. Nov. Dec. Jan.

2015 

0 

EXPLANATION 

90 percent prediction interval Predicted suspended-sediment 

concentration 

Sample suspended-sediment 

concentration Streamflow

Figure 1–4. Continuous suspended-sediment concentration record at U.S. Geological Survey 

streamflow-gaging station 08067252 Trinity River at Wallisville, Texas, January–December 2015. 

Streamflow, in cubic feet per second 
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Texas Water Science Center 

1505 Ferguson Lane 

Austin, TX 78754-4733 

(512) 927-3500 

Or visit the Texas Water Science Center Web site at: 

http://tx.water.usgs.gov/ 
Lucena and Lee—Characterization of Streamflow, Suspended Sediment, and Nutrients Entering Galveston Bay from the Trinity River—Scientific Investigations Report 2016–5177

Printed on recycled paper 

ISSN 2328-031X (print) 

ISSN 2328-0328 (online)

https://doi.org/10.3133/sir20165177