USDA

Lake Waco-Bosque River Initiative

Nutrient Targets for Lake Waco

and North Bosque River:

Developing Ecosystem

Restoration Criteria

Richard L. Kiesling, Anne M.S. McFarland, and Larry M. Hauck

TR0107

August 2001

Texas Institute for Applied Environmental Research

Tarleton State University • Box T0410, Tarleton Station • Stephenville, Texas

(254) 968-9567 • Fax (254) 968-9568 info@tiaer.tarleton.edu
Nutrient Targets for Lake Waco and North Bosque River

2

Acknowledgments

The United States Department of Agriculture Lake Waco-Bosque River Initiative supported 

this study, with additional funding provided by the State of Texas. The authors wish to 

acknowledge the support and dedicated work of the many field personnel and laboratory 

chemists involved with the monitoring program. Special thanks are due Dr. Owen Lind and 

Dr. Laura Dávalos-Lind of Baylor University and Dr. Marty Matlock of the University of 

Arkansas for their guidance and participation in the project. Further thanks are due to 

members of the Bosque River Advisory Committee (BRAC) who assisted in the public review 

of the proposed targets as well as to members of the Technical Work Group that provided 

technical overview of the Initiative including the efforts to develop nutrient targets.

Mention of trade names or equipment manufacturers does not represent endorsement of these 

products or manufacturers by TIAER.

Authors

Richard Kiesling, Research Scientist, TIAER, kiesling@usgs.gov

Anne McFarland, Research Scientist, TIAER, mcfarla@tiaer.tarleton.edu

Larry Hauck, Assistant Director of Environmental Research, TIAER, hauck@tiaer.tarleton.edu

USDA2.7
 Nutrient Targets for Lake Waco and North Bosque River

3

Abstract

The State of Texas has identified a number of water bodies as having potential water quality 

problems as a result of nutrient enrichment from point and nonpoint sources (TNRCC, 1996). 

In the Bosque River watershed, elevated levels of chlorophyll-α (CHLA) and nutrients have 

prompted the state to classify portions of the watershed as water quality impaired, and to 

place selected water quality segments on the Clean Water Act Section 303(d) list. In response 

to the listing of the Upper North Bosque River (Segment 1255) and the North Bosque River 

(Segment 1226) and in cooperation with stakeholders in the basin, water quality monitoring 

data and in situ nutrient bioassays were used to develop nutrient targets by answering the 

following questions: 

1. What nutrient or nutrients limit aquatic primary production in the watershed?

2. What functional relationship(s), if any, exists between the limiting nutrient and primary 

production?

3. How do degraded water bodies compare to reference sites?

A series of in situ stream bioassays were performed to develop a predictive relationship 

between nutrient supply and algal production and growth. Stream bioassays were performed 

using a recently developed periphytometer that supplies specific nutrient treatments to an 

artificial substrate (Matlock et al., 1998). The Matlock periphytometer is capable of estimating 

stream trophic status as the ratio of control production to nutrient saturated production. This 

ratio is referred to as the Lotic Ecosystem Trophic Status Index (LETSI). Individual glass-fiber 

filters were supplied with nitrogen (N), phosphorus (P), or N and P in combination and 

deployed in the stream in a replicated design to test for nutrient limitation in algal biomass 

production. Eight stream sites within the watershed were tested seasonally using this method. 

Growth and production responses to the treatments were estimated from CHLA production.

Laboratory-based bioassays measured the algal growth potential of Lake Waco waters from 

three reservoir monitoring sites. Natural phytoplankton collected from the lacustrine area of 

the reservoir and Selenastrum capricornutum from laboratory cultures were used to measure the 

growth response to ambient nutrient concentrations as well as to additions of N, P, or N and P 

in combination. Soluble reactive P (PO4-P) dose-response bioassays were performed in the 

lake once phosphorus was identified as the dominant limiting nutrient. Growth responses 

were assessed daily using in vivo fluorescence (IVF), and growth rates were determined by 

applying an exponential growth model to the IVF data. Bioassay results were compared to 

field data collected at two-week or monthly intervals at all of the bioassay sites. Comparisons 

were made between biomass production or algal growth rates and ambient nutrient 

concentrations.

Bioassay results indicated that aquatic primary production in the watershed was limited by 

phosphorus availability. For stream sites, over 40 percent of the in situ bioassays showed 

phosphorus limitation or co-limitation with nitrogen. In-stream primary production, 

measured as the ratio of control to nutrient sufficient production (aka LETSI), was a significant 

function of in situ P concentrations. North Bosque River sites showed a decrease of LETSI 

values as you moved downstream from site BO040 to BO100. Sites showing little or no P 

limitation (BO020 and BO040) had LETSI values very close to unity. For reservoir sites, over 90 

percent of the bioassays showed phosphorus limitation. Dose-response bioassay experiments 

using P as the limiting nutrient established predictive relationships between phosphorus 

nutrient supply and experimental natural phytoplankton biomass. Maximum growth rate 
Nutrient Targets for Lake Waco and North Bosque River

4

estimates from these dose-response bioassays declined over an order of magnitude 

throughout the summer.

Stream and reservoir bioassay results were used to develop provisional nutrient targets by 

comparison of in situ and laboratory experimental data with contemporaneous monitoring 

data. Provisional nutrient targets were derived from maximum growth responses of both 

stream and reservoir algae to saturating nutrient supply and from half-saturation constants 

for reservoir algae population growth or biomass production. These provisional nutrient 

targets were compared to the results of other analyses. Additional targets were developed 

based upon statewide screening criteria for algal biomass and within-basin reference sites or 

historical averages.
5

Contents

Chapter 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

The Role of Nutrient Targets in Restoring Water Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Nutrient Enrichment in the Bosque River Ecosystem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Chapter 2 Target Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Restoration Targets for Eutrophic Water Bodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Fundamental Basis of Reservoir Targets. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Fundamental Basis of River Targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Assumptions of Mass Balance Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Lake Waco Restoration Targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Determining Limiting Nutrient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Developing a Predictive Relationship. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Lake Waco Target Estimates From Bioassay Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Lake Waco Target Estimates From Monitoring Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Technical Work Group Target Recommendations For Lake Waco . . . . . . . . . . . . . . . . . . . 28

North Bosque River Restoration Targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

AGP Bioassay Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Periphytometer Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

In-stream Limiting Nutrient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Target Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Statistical Relationships From Monitoring Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Summary of Potential Stream Targets. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Chapter 3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Reference List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Appendix A Bosque River-Lake Waco Sampling Sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Sites on the North Bosque River . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Sites on Major Tributaries to Lake Waco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

Sites on Lake Waco . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

Appendix B Bosque River-Lake Waco Watershed Technical Work Group . . . . . . . . . . . 51
Nutrient Targets for Lake Waco and North Bosque River

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7

Tables

Table 1 Comparison of classified segments to TNRCC (1998) screening criteria.. . . . . . . . . . . . . . . . 15

Table 2 Summary of Lake Waco bioassay results: December 1996 to November 1998. . . . . . . . . . . 21

Table 3 Potential nutrient restoration targets for Lake Waco. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Table 4 Algal growth potential (AGP) bioassay results for tributaries of Lake Waco. . . . . . . . . . . . 31

Table 5 Summary of nutrient limitation for tributaries of Lake Waco. . . . . . . . . . . . . . . . . . . . . . . . . 31

Table 6 Summary of nutrient limitation results for Matlock periphytometers. . . . . . . . . . . . . . . . . . 32

Table 7 Summary of basic statistics for monthly chlorophyll and biweekly PO4-P samples. . . . . . 36

Table 8 Potential nutrient restoration targets for North Bosque River. . . . . . . . . . . . . . . . . . . . . . . . . 38
Nutrient Targets for Lake Waco and North Bosque River

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9

Figures

Figure 1 Lake Waco-Bosque River Watershed with boundaries of classified water segments. . . . . . 14

Figure 2 Location of major sampling sites in Lake Waco. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Figure 3 Lake Waco bioassay dose-response curves. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Figure 4 Lake Waco bioassay results: Monod parameters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Figure 5 Lake Waco PO4-P dose-response experiments, 1998. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Figure 6 Lake Waco bioassay productivity ratio as a function of in-lake PO4-P concentration. . . . . 25

Figure 7 Regression analysis of CHLA with PO4-P concentrations for all Lake Waco sites. . . . . . . . 27

Figure 8 Regression analysis of CHLA with PO4-P concentrations for Lake Waco dam sites.. . . . . . 28

Figure 9 Lake Waco segmentation map from CE-QUAL-W2 model.. . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Figure 10 Bosque River watershed map with location of major stream sampling sites. . . . . . . . . . . . . 30

Figure 11 Annual average algal biomass as a function of grab sample PO4-P concentration. . . . . . . . 34

Figure 12 In-stream algal biomass as a function of time-weighted PO4-P concentration.. . . . . . . . . . . 34

Figure 13 In-stream algal biomass as a function of flow-weighted PO4-P concentration.. . . . . . . . . . . 35

Figure 14 Summary of Matlock periphytometer bioassay results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
Nutrient Targets for Lake Waco and North Bosque River

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11

CHAPTER 1

Introduction

The Role of Nutrient Targets in Restoring Water Quality

Restoration of polluted aquatic ecosystems has been a topic of concern among aquatic 

ecologists since the 1970s. Early efforts to identify the causative agents of aquatic ecosystem 

degradation focused on the obvious impacts associated with accelerated eutrophication 

(sometimes referred to as cultural eutrophication) of lakes and reservoirs. Excessive loadings 

of nutrients and organic wastes from point sources into these water bodies were shown to 

enhance and promote algal growth, leading to the accumulation of algal biomass and to 

whole-scale changes in lake and reservoir metabolism. In response to these observations, 

numerous attempts were made to restore the affected water bodies through practical means, 

such as diversion of known point sources away from lakes and reservoirs (e.g., Edmondson 

1972). At the same time, a number of research projects were initiated to define acceptable 

baseline nutrient conditions to serve as restoration endpoints for lake and reservoir managers. 

The most well known of these efforts was a literature and data review compiled by R. A. 

Vollenweider (1968) for the Organization for Economic Cooperation and Development 

(OCDE). His review concluded that the previously identified critical nutrient levels of 300μg/

L inorganic nitrogen and 10μg/L inorganic phosphorus from the work by Sawyer (1947) were 

reasonable benchmarks for temperate lakes and reservoirs.

Vollenweider’s analysis affirming Sawyer’s recommendations initiated efforts to define 

appropriate nutrient management criteria for water quality impaired lakes and reservoirs 

based, in part, on mass-loading models. Numerous empirical relationships between average 

nutrient loads and in-lake nutrient concentrations were developed, leading to a series of 

published mass balance equations as well as statistical models capable of predicting algal 

biomass from nutrient loads (see Meeuwig and Peters 1996 for a review). The underlying 

assumption in these models was tested with a series of whole-lake fertilization experiments 

that provided dramatic evidence of nutrient limitation in general, and limitation by 

phosphorus in particular (Schindler, 1977), in freshwater lakes. With the fundamental 

importance of phosphorus affirmed by Schindler’s whole-lake experiments and by 

Vollenweider’s pattern analysis, restoration efforts turned towards building a more 

mechanistic understanding of the eutrophication process.

Similar efforts aimed at exploring the implications of nutrient enrichment in rivers and 

streams were initiated within the same time frame as the studies focused on lakes and 

reservoirs. The early work of Odum (1956) and King and Ball (1967) illustrated how stream 

productivity was enhanced by nutrient addition. Experimental manipulations involving 

nutrient additions to streams documented the role of phosphorus in limiting periphyton 

accumulation in streams (Stockner and Shortreed, 1976; Peterson et al., 1983) while work by 

Hornberger et al. (1977) developed methods to assess eutrophication potential using 

productivity (P) measurements and productivity to respiration ratios (P/R). Nutrient 

enrichment of experimental streams (Horner et al., 1983) provided estimates of critical 

phosphorus levels as well as algal biomass criteria indicative of eutrophy. According to 

Horner’s experiments, soluble reactive phosphorus (SRP) supply rates of 15 to 25μg /L 
Nutrient Targets for Lake Waco and North Bosque River

12

produced nuisance levels of periphyton biomass in excess of 150mg chlorophyll-α (CHLA)/

m2. Maximum algal biomass for the same experiments was observed at supply rates between 

50 and 80μg/L SRP. These results are in general agreement with field-based estimates of 

critical total phosphorus levels for the filamentous alga Cladophora. Using maximum relative 

photosynthesis as the measure of growth and performance, Wong and Clark (1976) estimated 

the critical total phosphorus requirement at 60μg/L.

Although these reports established a direct link between nutrient availability and 

eutrophication of streams and reservoirs, development of federal numeric water quality 

criteria for nutrients in freshwater did not take place. Despite the lack of federal criteria, a 

number of states moved forward to address eutrophication and adopted numeric phosphorus 

criteria for the protection of specific water bodies or classes of water bodies including streams 

and lakes. A 1988 summary of nutrient criteria found 13 states with some form of numeric 

criteria for phosphorus (USEPA, 1988). USEPA recently initiated an effort to develop 

ecoregion-based nutrient criteria for the entire United States (USEPA, 1998b). The underlying 

goal of this effort is to have numeric nutrient criteria adopted by the individual states as part 

of their respective water quality standards before 2003. Part of the motivation for this effort 

stems from the importance of nutrient enrichment as the suspected causative agent in water 

quality impairment across the nation. A 1998 assessment of the nation's water quality 

identified nutrients as a major source of impairment to lakes and reservoirs as well as rivers 

and streams (USEPA, 2000). Forty-four percent of the impaired surface acres from lakes and 

reservoirs were attributed to nutrient pollution as were 29 percent of the impaired river and 

stream miles. In this same assessment, agricultural activities were identified as major potential 

sources of water quality impairment for 31 percent of impaired lake acres and 59 percent of 

impaired river miles (USEPA, 2000). No direct measure of the agricultural contribution to 

nutrient impairment was available from the EPA (2000) report, but basin-level studies of 

nutrient levels in streams and rivers from across the United States have identified significant 

associations between agricultural land uses and elevated nutrient concentrations (USGS, 

1999). Results from the United States Geological Survey (USGS) National Water Quality 

Assessment (NAWQA) Program have documented significant increases in total phosphorus 

and total nitrogen concentrations in streams draining watersheds with high levels of 

agricultural and urban land uses. This result is not surprising as significant nutrient loading 

from agricultural sources has been documented since the late 1960s (e.g., Loehr, 1967). 

Systematic studies of the importance of agricultural nutrient loading to surface water (e.g., 

Lennox et al., 1997) and its management (e.g., Daniels et al., 1994; Pionke et al., 1997) have 

only recently become commonplace.

Resource managers must understand how land-use decisions interact with the specific 

characteristics of streams and reservoirs if they hope to reduce the number of aquatic 

ecosystems at risk for developing cultural eutrophication. Land-use based assessments of 

potential nutrient sources like those performed under the NAQWA program highlight 

linkages between activities in the watershed and the response of aquatic ecosystems to 

nutrient enrichment. Detailed studies of how land use affects nutrient loading for watersheds 

in Minnesota (Brezonik, personal communication), Wisconsin (Bennett et al., 1999) and Texas 

(McFarland and Hauck, 1999a&b) have pinpointed the specific role played by agriculture in 

elevating nutrient loads to streams and lakes. Current research on land use and its effect on 

the export of limiting nutrients to water bodies have highlighted the importance of integrated 

watershed management to implementing long-term solutions of cultural eutrophication. 

Preventing or reversing accelerated eutrophication associated with agricultural nonpoint 

source loading will require watershed-based solutions that address entire drainage basins.

Development of restoration targets is the first step in the restoration of basins with impaired 

water quality from excessive nutrient loading. The Lake Waco-Bosque River watershed is an 

example of a basin with water quality problems that stem from excessive nutrient loading 
 Chapter 1 Introduction

13

from urban point sources and agricultural nonpoint sources. Previous studies have 

determined that substantial point and nonpoint source loads of nitrogen (N) and phosphorus 

(P) have elevated ambient concentrations of these two nutrients in the North Bosque River 

and in Lake Waco (e.g., McFarland and Hauck, 1998a, 1998b, 1999a, 1999b). These elevated 

nutrient levels are associated with increases in algal biomass (McFarland and Hauck 1998a, 

1999a; McFarland et al., 2001), which has placed portions of the North Bosque River on the 

State of Texas list of impaired water bodies.

Nutrient Enrichment in the Bosque River Ecosystem

The Lake Waco-Bosque River watershed encompasses 1,660 square miles in north central 

Texas, all draining into Lake Waco (Figure 1). Major tributaries within the Bosque River 

watershed include the North Bosque River, Hog Creek, Middle Bosque River and South 

Bosque River, of which the North Bosque River basin covers about 74 percent of the total 

drainage area. 

From a regulatory perspective, the classified stream segments in the watershed are segments 

1226 (North Bosque River), 1246 (Middle Bosque and South Bosque River), and 1255 (Upper 

North Bosque River). Lake Waco is classified segment 1225 of the Brazos River Basin. Segment 

1225 includes Lake Waco dam to the North Bosque River arm in McLennan county to the 

confluence of the Middle Bosque River on the South Bosque River arm in McLennan county. 

Segment 1226 includes the North Bosque River from Lake Waco, up to a point immediately 

above the confluence of Indian Creek. Segment 1255 includes the North Bosque River from 

Indian Creek to the confluence of the North Fork and South Fork above Stephenville. Segment 

1246 includes the Middle and South Bosque Rivers located in McLennan county, as well as a 

small portion of the Middle Bosque in Coryell county up to the confluence of Cave Creek and 

Middle Bosque River. The state of Texas has designated the following uses for these four 

classified segments (TNRCC, 1996):

Segment 1225 (Lake Waco)

• Contact recreation 

• High aquatic life

• Public water supply

Segment 1226 (North Bosque River)

• Contact recreation

• High aquatic life

• Public water supply

Segment 1246 (Middle Bosque and South Bosque River)

• Contact recreation

• High aquatic life

Segment 1255 (Upper North Bosque River)

• Contact recreation

• Intermediate aquatic life

The two North Bosque River segments (1226 and 1255) are also included on the State of Texas 

1992, 1994, 1996, 1998, and 2000 list of impaired water quality segments, otherwise known as 

the Section 303(d) list. Nutrient enrichment in the form of elevated nutrient concentrations 
Nutrient Targets for Lake Waco and North Bosque River

14

and excessive algal growth is the major reason for the listing of these classified segments 

comprising the North Bosque River.

Figure 1 Lake Waco-Bosque River Watershed with boundaries of classified water segments.

The Texas Institute for Applied Environmental Research (TIAER) has been performing water 

quality monitoring in the Lake Waco-Bosque River watershed since the early 1990s. Until 

1996, the monitoring was focused on the watershed above the North Bosque River at Hico, 

Texas, and in that year the monitoring was expanded to the entire watershed. The monitoring 

has focused on sample collection during base flow and storm events on tributaries and rivers, 

measurement of stream flow at several sites, sample collection in Lake Waco, and sample 

analysis for nutrient forms and related constituents, such as total suspended solids, dissolved 

oxygen, and chlorophyll-a. Additional information on the monitoring program may be found 

in journal articles, e.g., McFarland and Hauck (1999a, 2001), and technical reports, e.g., 

McFarland and Hauck (1998a, 1998b, 1999b). Principal sampling site locations are described in 

Appendix A. The monitoring program is further described in semiannual data analysis 

reports to the Texas Natural Resource Conservation Commission, e.g., Pearson and McFarland 

(1999).

Analysis of TIAER monitoring data largely corroborates the section 303(d) listing of the two 

segments of the North Bosque River and provides additional insight into nutrient enrichment 

issues in the entire watershed. By first grouping sites by location in classified water body 
 Chapter 1 Introduction

15

segments, the monitoring data from June 1993 through May 1998 were analyzed according to 

protocol in TNRCC (1998) to provide an assessment of water quality parameters associated 

with nutrient enrichment. The assessment parameters include dissolved oxygen (DO), nitritenitrogen plus nitrate-nitrogen (NO2-N+NO3-N), ammonia-nitrogen (NH3-N), dissolved 

reactive phosphorus (PO4-P), total phosphorus (total-P), and chlorophyll-α (CHLA). In this 

assessment data collected from riverine automated samplers during storm water flows were 

analyzed separately from samples collected by routine grab sampling. Based on the 

percentage of data exceeding numeric water quality criteria (TNRCC, 1998), each parameter 

was assessed as fully supporting (FS), partially supporting (PS), or not supporting (NS) the 

numeric criterion. Texas has responded to the lack of numeric criteria by using nutrient 

screening levels derived from statistical distributions of statewide water quality monitoring 

data for specific categories of surface water (TNRCC, 1998). Screening levels exist for all water 

quality nutrient parameters reported in Table 1, and the percentage of data exceeding a 

screening level was assessed for each parameter as no concern (NC), potential concern (PC) or 

concern (C).

The assessment of TIAER data indicated that suspended algae (CHLA) were a concern in Lake 

Waco and both North Bosque River segments (Table 1). The various nutrient forms were 

assessed as being a concern or potential concern in some segments, and DO was assessed as a 

partially supporting in the Upper North Bosque River. This assessment indicates nutrient 

enrichment is a water quality issue in the North Bosque River and Lake Waco.

The outcome of the analysis presented in Table 1 coupled with the section 303(d) listing for the 

North Bosque River indicate that excessive amounts of nutrients and suspended algae exist in 

the North Bosque River and Lake Waco. These and other problems prompted the listing of the 

North Bosque River as a nonpoint source impaired water from nutrient loadings (TNRCC and 

TSSWCB, 1999). 

This report presents the results of an effort to develop numeric nutrient targets for the North 

Bosque River and Lake Waco. The purpose of nutrient target development is to provide 

restoration endpoints in the North Bosque River and Lake Waco for the USDA Lake WacoBosque River watershed Initiative Project. Attaining these endpoints should reduce the 

occurrence of algal blooms and long-term average concentrations of algae. Within the 

Table 1 Comparison of classified segments to TNRCC (1998) screening criteria.

Results of comparing TIAER water quality data to TNRCC (1998) segment-specific criteria or 

screening level. FS = fully supporting; PS = partially supporting; C= concern; PC = potential 

concern; NC = no concern

Segment Sample Type DO NO2-N+NO3-N NH3-N PO4-P Total-P CHLA

Lake Waco 

(1225)

Surface 

Grab FS C NC NC PC C

North 

Bosque 

(1226)

Grab FS NC NC NC NC C

Storm - NC NC NC NC -

Middle & 

South 

Bosque 

(1246)

Grab FS C NC NC NC NC

Storm - C NC NC NC -

Upper 

North 

Bosque 

(1255)

Grab PS C PC PC PC C

Storm - PC C NC PC -
Nutrient Targets for Lake Waco and North Bosque River

16

initiative, research efforts are being conducted to address several aspects of nutrient 

enrichment, its impacts, and its control. Further a stakeholder group, the Bosque River 

Advisory Committee (BRAC), which is comprised of various concerned citizens of the 

watershed, has been instrumental in development of the nutrient targets. Equally important in 

target development has been the Technical Work Group that provides technical overview of 

the initiative monitoring program and serves in an advisory role to the BRAC. 
17

CHAPTER 2

Target Development

Restoration Targets for Eutrophic Water Bodies

Fundamental Basis of Reservoir Targets

The long history of lake eutrophication research has provided a wealth of theoretical, 

experimental, and applied investigations into how lakes and reservoirs respond to nutrient 

enrichment. For example, numerous simple mass-balance models have been derived from 

statistical descriptions of reservoirs and lakes of different trophic status (see Meeuwig and 

Peters, 1996, for a review). The most sophisticated of these approaches have been used to 

derive restoration endpoints for severely impaired water bodies (e.g., Lathrop et al., 1998). 

However, in order to develop these models or to use them to predict reservoir responses to 

changes in loading, very large data sets are required. In the early development of the loading 

models, Vollenweider (1976) used data from a modest sample of lakes and reservoirs to 

develop a predictive relationship between phosphorus loading and average summer algal 

biomass measured as chlorophyll-α (CHLA). Through numerous refinements and 

improvements to Vollenweider’s simple mass-balance model by a large number of authors 

(e.g., Meeuwig and Peters, 1996), larger and larger data sets have been used to explore the 

predictive capabilities of these statistical mass-balance models. Analysis of a large set of North 

American lakes by Smith and Shapiro (1981) found that the predictive capabilities of these 

statistical mass-balance models were acceptable for understanding how the average lake 

might respond to a given level of loading, however, specific lakes were found to be capable of 

individualistic responses to changes in nutrient loading. Inter-annual variability in the CHLAnutrient load relationship was great enough in some lakes to call into question the usefulness 

of statistical, mass balance models for management purposes. In response to the shortcomings 

of simple mass-balance relationships, more complex, mechanistic mass-balance models were 

developed that included food-web components and consumer-resource interactions (e.g., 

Canale, DePalma, and Vogel, 1976; Larsen, Mercier, and Malueg, 1974). These efforts 

culminated in the production of mechanistic water quality models like WASP (DiToro, 

Fitzpatrick, and Thomann, 1983) and CE-QUAL-W2 (USACOE, 1986) capable of modeling 

lake and reservoir ecosystems. The two approaches illustrate the trade-off inherent in 

modeling strategies between generality and precision (Levins, 1966). Despite the loss in 

precision associated with simple nutrient loading-algal biomass models, they continue to be 

used as management tools.

The usefulness of simple, statistical mass-balance models to target development for a specific 

lake or reservoir is limited by two factors. The first is the size of the database required to apply 

the model to an individual lake and the time and expense required to collect the information. 

Five to ten years of focused monitoring may be required to establish a reliable productivitynutrient loading relationship for a reservoir. This amount of time and effort may not be 

available if previous monitoring data have indicated that excessive nutrient loading is already 

occurring. Water quality managers may have limited time or funds available to collect new 

information. The second factor is the lack of specificity and precision in the underlying cause 
Nutrient Targets for Lake Waco and North Bosque River

18

and effect relationship between the target variable (e.g., CHLA) and the water quality 

parameter to be controlled (e.g., phosphorus) in these models. This detailed linkage is 

required to ensure the proposed target is relevant to the goal of maintaining or restoring water 

quality for the water body of concern. 

Fundamental Basis of River Targets

Riverine eutrophication research faced similar challenges in the 1970s, but the initial solutions 

developed to meet these challenges differed from those that developed for lakes and 

reservoirs. Up until the late 1960s, mathematical models of river ecosystems focused on 

dissolved oxygen mass balance (Sandoval, Verhoff, and Cahill, 1976). Early work like that of 

Chen (1970) introduced the concept of mass balance approaches for elements other than 

oxygen. By 1972, modelers were incorporating the effects of nutrients into models of river 

systems as part of a generalized mass balance approach to predicting riverine responses to 

nutrient enrichment (Chen and Orlob, 1972; Sandoval, 1974). By 1976, this procedure was 

commonplace. Further model development through the 1970s and 1980s produced standard 

water quality simulation models like WASP (DiToro, Fitzpatrick, and Thomann, 1983) and CEQUAL-W2 (USACOE, 1986). These advanced models included explicit functional 

relationships between nutrient availability and phytoplankton growth and could be applied 

to reservoirs and lakes as well as rivers and estuaries. These more complex models unified the 

water quality modeling framework for freshwater ecosystems, but differences in the way 

these models were applied remained. Although rivers tended to be evaluated using complex 

models, the data required to run simulations were extensive. In addition to the data 

requirements, the need to test the specific assumptions inherent in these complex models was 

also prohibitive because of the time and effort involved. 

The common solution to this problem was and still is the extensive use of calibration and 

verification data sets (Thomann and Mueller, 1987). By using a calibration data set to develop 

a hypothetical model of complex riverine ecosystems, modelers side-step the need to test each 

specific mechanism in the model proper. This approach works well to predict short-term 

dynamics of riverine systems but can fail to predict long-term dynamics. For example, the 

Potomac Estuary Model was unable to predict the magnitude of a massive algal bloom in 

1983. Despite this failure, the model was an important investigative tool in determining the 

most likely cause of this bloom (Thomann and Mueller, 1987).

Assumptions of Mass Balance Models

What steps need to be taken to ensure the target is relevant to the goal? In the case of 

eutrophication associated with excessive phosphorus loading, additional data are required to 

establish how phosphorus reductions or other planned management actions will affect 

productivity. Additional information may be necessary to be certain that reducing phosphorus 

loads will decrease algal productivity on an acceptable time schedule and with an acceptable 

level of confidence in the predictive statistical relationship or mathematical function. Even 

when precise models are used, they may fail to make accurate predictions when specific 

assumptions are not met. In the case of nutrient target development, an assumption is made 

that the target parameter will track the water quality variable of interest (e.g., algal biomass). 

If this assumption is not met, the target parameter (e.g., phosphorus) is not relevant to the 

process of restoring water quality in the water body of interest.

One approach to addressing both of these concerns is to apply the tenants of resourceconsumer theory as it relates to algae (Tilman, 1982; Grover, 1997) to the problem of endpoint 

definition. While nutrient resources such as nitrogen and phosphorus are consumed by all 
 Chapter 2 Target Development

19

algae, algal growth, and therefore algal biomass accumulation, must be controlled by nutrient 

supply rates before algal populations are in fact nutrient limited. Nutrient limitation, or 

control, of algal biomass accumulation is an assumption and prerequisite of all nutrient 

loading models that seek to predict algal biomass, or its surrogate, CHLA. Nutrient limitation 

is also an inherent assumption of any attempt to restore a highly productive water body 

through control of nutrient loading. Therefore, it is critical to restoration efforts to know that 

nutrients limit algal growth and biomass accumulation, and it is also necessary to know which 

nutrient is limiting to growth so that appropriate management action plans can be developed.

Once it has been established that a specific nutrient limits algal growth, further work must 

establish the functional relationship between increases in algal population size and external 

nutrients. Current understanding of nutrient-limited algal growth and reproduction suggests 

this functional relationship is the culmination of a two step process: nutrient uptake followed 

by cell division. Although two-step algal growth models are available (e.g., Kilham, 1978), 

simpler models exist that relate external nutrient concentrations directly to population growth 

(Monod, 1950). The Monod function has been useful in describing the nutrient-dependent 

growth of algae in culture and in predicting the outcome of nutrient competition (Tilman, 

1982). More importantly, it is the only available model that predicts population growth rate 

based solely upon the external concentration of the limiting nutrient. This makes the Monod 

model a much more simple, if somewhat less reliable, alternative than a two-step growth 

model when dealing with natural algae communities (Grover, 1997). Despite its limitations, 

the Monod model has been incorporated into most mechanistic water quality models like CEQUAL-W2 (Cole and Buchak, 1995) as an algal-growth subroutine.

Identifying the limiting nutrient and using the Monod model to predict algal growth 

responses to the supply rate are the first two steps in establishing a recovery objective for the 

water body of interest or in modeling the water body’s response. A third condition is field 

evidence that the water quality variable of interest, in this case algal biomass measured as 

CHLA, responds to changes in the loading or supply rate of the limiting nutrient. For 

example, in a phosphorus-limited system, correlation between annual total phosphorus (totalP) load, annual-average spring orthophosphate (PO4-P) concentration, or annual-average 

growing season total-P and CHLA would provide evidence in support of the functional 

relationship between the potential target variable (e.g., total-P load) and the water quality 

parameter of interest (CHLA).

In the context of cultural eutrophication, re-establishing ecosystem function is best thought of 

as restoring natural biogeochemical cycling of nutrients and carbon. Simply put, this means 

reducing productivity to levels produced by background nutrient loading associated with 

minimal human impact. Unfortunately, historical data are often inadequate for this task, 

making the development of a target that meets this standard difficult. In the Lake WacoBosque River watershed, historical data do exist but these data are generally inadequate to the 

task of applying simple models for reservoirs such as those developed by Vollenweider or 

complex models for rivers and reservoirs like CE-QUAL-W2. Data simply do not exist for 

enough years and in sufficient detail to estimate the annual average response of algal biomass 

to changing levels of annual loading. In response to the lack of adequate data, an alternative 

approach to mass-balance productivity models was followed to develop nutrient restoration 

targets. The following series of tasks were performed to achieve the objective of nutrient target 

identification for both Lake Waco and the North Bosque River:

• Determine what nutrient limits algal biomass production

• Develop predictive relationships between algal biomass measure and putative target 

variable

• Identify reference conditions for feasible endpoints or targets
Nutrient Targets for Lake Waco and North Bosque River

20

Lake Waco Restoration Targets

Determining Limiting Nutrient

The first task was accomplished by performing a series of algal growth bioassays following 

standard EPA bioassay methods (APHA, 1995). Standard algal bioassays were conducted at 

the limnology laboratory at Baylor University in Waco (see Dávalos-Lind and Lind, 1999). 

These bioassays were similar in design to experiments performed in other Texas reservoirs to 

determine nutrient limitation patterns (e.g., Sterner, 1994). Bioassay methods and the detail of 

their application to Lake Waco sites are available elsewhere (Dávalos-Lind and Lind, 1999; 

McFarland et al., 2001). Growth responses of a native phytoplankton community from Lake 

Waco site LW013 (Figure 2) and a standard bioassay species Selenastrum capricornutum Printz. 

were assessed during the bioassays. Nitrogen and phosphorus were added separately and in 

combination to water collected at three Lake Waco sites (LW013 near the dam, LW015 near the 

State Highway 6 bridge, and LW070 near the Bosque Bend Clubhouse in Speegleville I Park) 

to test for nutrient-dependent growth. Growth of algal biomass in nutrient addition 

treatments was compared to results for control groups with no added nutrients. Bioassays 

were run at least once a month from December 1996 to November 1998. All bioassays used an 

acclimated growth rate method and tracked changes in biomass using in vivo fluorescence 

(IVF) of CHLA. Results from the three Lake Waco sites strongly indicate that phosphorus 

limits algal biomass growth during the study period (Table 2). Ninety-four percent of the 

experiments show some level of phosphorus limitation, with 92 percent showing only 

phosphorus limitation. All phosphorus was added as orthophosphate (PO4-P).

Developing a Predictive Relationship

The nutrient-limitation bioassay data clearly illustrate the importance of phosphorus to algal 

population growth and biomass accumulation. However, this importance does not establish a 

functional relationship between in-lake phosphorus concentration or some other measure of 

availability of the limiting nutrient and algal growth or productivity. To test for this 

relationship, a second set of bioassays were performed during 1998 to test the predictive 

capabilities of the Monod model. Native phytoplankton communities from lake site LW013 

were subjected to an enrichment PO4-P gradient in the laboratory to establish a dose-response 

relationship. Each treatment group was enriched with a specific concentration of phosphorus 

as PO4-P, the presumptive limiting nutrient. PO4-P was added because measurements of Lake 

Waco and Bosque River bioavailable phosphorus (Sharpley, 1993) were dominated by PO4-P 

measured as soluble reactive phosphorus (TIAER, unpublished data).

Biomass-based algal growth rates were calculated using a simple exponential growth model. 

Details of this analysis are available in McFarland et al. (2001). Growth rate data were fit to a 

Monod function shown below using the SAS statistical package. 

In the Monod model, observed growth rate (μ) is a function of the maximum nutrient 

sufficient growth rate (μmax), the external nutrient concentration (S), and the half-saturation 

constant for growth (Ks). For the Lake Waco bioassays, resulting growth rates were reported 

on a per day basis (day-1), and S and Ks were in μg/L. The resulting Monod curves were 

significant for all spring and summer months, April through August, as well as for September 

μ μmax • S Ks = ⁄ ( ) + S
 Chapter 2 Target Development

21

and November (e.g., Figure 3). Comparisons between Ks estimates from all of the doseresponse experiments reveal a strong seasonal decline between May and September (Figure 4). 

Figure 2 Location of major sampling sites in Lake Waco.

Table 2 Summary of Lake Waco bioassay results: December 1996 to November 1998.

Summary of algal growth potential results for native algae communities (native) and Selenastrum 

capricornutum Printz. Ninety-four percent of all of the replicated bioassays exhibit some level of 

phosphorus limitation. 

Population P-Limited N-Limited Co-Limited Other Total

Native 71 3 1 0 75

Selenastrum 67 5 2 1 75

Totals 138 8 3 1 150

Percent 92 5 2 1 100
Nutrient Targets for Lake Waco and North Bosque River

22

Figure 3 Lake Waco bioassay dose-response curves.

Examples of dose-response curves for natural phytoplankton communities collected at site LW013 in 

Lake Waco. Monod model parameter estimates and function are illustrated for an early (May) and midgrowing season (July) experiment. Maximum growth rates (μmax) and half-saturation constants (Ks) 

were estimated using the SAS statistical program.

3a. Lake Waco bioassay results from May 17, 1998 

3b. Lake Waco bioassay results from July 1, 1998.

PO4-P-based maximum growth rates show a slightly altered pattern, with elevated values in 

May and November and a flat response in the intervening months. The maximum growth rate 

in May was much larger than in September, which appears to be a transition month away 

from PO4-P limitation. Unlike September, October data do not conform to a Monod function, 

while November again demonstrates a significant relationship between PO4-P as the limiting 

nutrient and algal biomass.

0

0.5

1

1.5

2

2.5

0 100 200 300 400

PO4-P Concentration (μg/L)

Growth Rate (day-1)

Monod parameters:

Ks = 31.01

μmax - 2.25

0

0.2

0.4

0.6

0.8

1

0 100 200 300 400

PO4-P Concentration (μg/L)

Growth Rate (day-1)

Monod parameters:

Ks = 27.82

μmax = 0.86
 Chapter 2 Target Development

23

Figure 4 Lake Waco bioassay results: Monod parameters.

Monod parameter estimates for dose-response bioassays of natural phytoplankton communities from 

LW013 in Lake Waco, which include phosphorus-dependent μmax and Ks. Ks decreases over the course of 

the summer, indicating nutrient uptake rates increase while growth rates decline.

The dose-response bioassays have shown that PO4-P elicits a population growth effect 

consistent with the Monod algal growth model. Using Ks as a benchmark, and assuming that 

algal population growth rate and algal biomass accumulation rate are directly proportional in 

Lake Waco, it is possible to identify an ambient PO4-P concentration that will reduce current 

algal biomass by up to 50 percent. Scaling the result of each bioassay-derived Monod curve to 

μmax and plotting the results on one graph makes it possible to derive a composite Monod 

function for the family of growth-rate curves produced by the bioassays. Applying the Monod 

model to the relative growth data in Figure 5 results in a composite Ks for relative growth of 

28μg/L.

Upon further inspection, some additional patterns emerge from the bioassay results. The 

strong seasonal decrease in Ks suggests an increase in the competitive ability for PO4-P among 

the algae community. However, there appears to be a trade-off between this increase in 

efficiency of nutrient-dependent growth and maximum attainable biomass growth rates 

(Figure 4). This trend could reflect a change in species composition, species-specific nutrient 

limitation, average cell size, or a combination of all three alternatives.

Lake Waco Target Estimates From Bioassay Data

In contrast to the majority of conventional statistical models that predict CHLA from total-P 

concentrations (Meeuwig and Peters, 1994), PO4-P appears to be the controlling variable in 

this system. McFarland et al. (2001) have documented high phosphorus loading to the Lake 

Waco system during 1996-1998. A large portion of this load entered the lake as PO4-P, and 

subsequent nutrient dynamics maintained a large pool of this phosphorus species. Unlike 

most low to moderately productive lakes (e.g., Dillon and Rigler, 1974), the PO4-P pool in Lake 

Waco was generally indicative of instantaneous bioavailable phosphorus during this time 

0

10

20

30

40

50

60

70

80

5/18/1998 6/17/1998 7/17/1998 8/16/1998 9/15/1998 10/15/1998

Date

Half Saturation Constant (Ks ) in μg/L

0.00

0.50

1.00

1.50

2.00

2.50

Maximum Growth Rate (umax), day-1

Ks 31 18 28 10 4 72

μmax 2.25 0.76 0.86 0.75 0.69 1.34

5/18/98 6/16/98 7/1/98 8/18/98 9/4/98 11/3/98
Nutrient Targets for Lake Waco and North Bosque River

24

period. The predictive relationship developed from the dose-response bioassay can be used to 

identify nutrient targets based on the importance of this PO4-P pool in Lake Waco. For 

example, a target designed to reduce relative algal growth rate by 50 percent can be developed 

using Ks as a benchmark. A composite Ks value from relative growth rates gives a potential 

nutrient target of 28μg/L PO4-P for Lake Waco (Figure 5). Under the assumptions of the 

Monod model as applied under resource-consumer theory, this target approximates the 

nutrient supply that would sustain the selected 50 percent relative growth rate. 

Figure 5 Lake Waco PO4-P dose-response experiments, 1998.

Relative growth rates for PO4-P dose-response bioassays. Monod fit (μrel) to entire relative growth rate 

data set yields a Ks of 28 μg/L.

The time period over which this target can be applied is also a point of concern. Given that the 

Ks for relative growth rate was derived from bioassays performed over the entire growing 

season, it appears reasonable to apply the target to an average condition over the same time 

period. Furthermore, estimates of average nutrient supply rates in lakes and reservoirs may be 

approximated by early growing season average concentrations (e.g., Linsley Pond in 1938 

reported by Hutchinson, 1944; Shagawa Lake in 1972 reported by Larsen, Mercier, Malueg, 

1974). Models of average summer algal biomass have been based on total nutrient 

concentrations at spring turnover in north temperate lakes (Dillon and Rigler, 1974) and in 

Florida lakes (Baker, Brezonick, and Kratzer, 1981). Results from a CE-QUAL-W2 simulation 

for Lake Waco have documented a significant relationship between mean summer PO4-P 

concentrations and mean summer CHLA concentration (R2 = 0.71; p < 0.05; Flowers et al., in 

prep.). 

Assuming this relationship is appropriate for Lake Waco, this target should be evaluated as a 

seasonal annual average PO4-P concentration. Limitations of this target include the 

assumption that the supply rate of PO4-P to summer algal populations is predicted by average 

ambient nutrient concentration over the same period. The impact of internal resupply of 

nutrients on algal biomass accumulation must also be reflected through changes in the 

seasonal average concentration of PO4-P.

Other bioassay results are also useful in developing potential nutrient target values for Lake 

Waco. Results from the nutrient bioassays can be combined with monitoring data to establish 

a reference condition for nutrient-dependent biomass accumulation. Figure 6 shows the 

relationship between the relative maximum biomass from the bioassay control groups and 

PO4-P concentrations from Lake Waco. PO4-P data were collected along temporal and spatial 

nutrient gradients in Lake Waco, with sampling occurring at least monthly over a two year 

period at three locations. The relationship in Figure 6 establishes how biomass accumulation, 

measured in the control treatments from the bioassays, are a function of in-lake PO4-P 

0.0

0.3

0.5

0.8

1.0

1.3

0 50 100 150 200 250 300 350

PO4-P Concentration (μg/L)

Relative Growth Rate (μrel)

May

June

July

August

September

November

μrel

Composite Ks is 28 μg/L PO4-P

μrel = [PO4-P]/(28+[PO4-P])

R2

 = 0.41; p < 0.05
 Chapter 2 Target Development

25

concentrations. The lowest observed biomass accumulation occurs within a range of 

minimum PO4-P concentrations, suggesting a potential reference condition. Figure 6 

illustrates that a clear threshold in maximum biomass production response to increasing 

nutrient availability occurs at 16μg/L PO4-P. Below this level, algal biomass does not 

significantly respond to increasing PO4-P concentrations. Above this level, biomass becomes 

elevated in response to increased availability of the limiting nutrient. 

Figure 6 Lake Waco bioassay productivity ratio as a function of in-lake PO4-P concentration.

Relative maximum biomass for control treatment from nutrient bioassays as a function of in-lake PO4-P 

concentrations. Simple linear regression is significant at p<0.05. Dashed line at 16μg/L PO4-P identifies 

hypothesized threshold for PO4-P stimulation of algal growth. Biomass measured as in vivo fluorescence 

(IVF) units.

Biomass responses above the 16μg/L threshold are also much more variable, suggesting the 

increasing importance of additional controlling factors at higher ambient concentrations. This 

threshold response provides a second potential nutrient target of 16μg/L PO4-P. A simple 

linear regression provides a significant estimate of how the bioassay control growth rates 

changed as a function of in-lake phosphorus availability, but the linear trend explains less than 

30 percent of the variation in biomass response. Targets could be derived from the regression 

relationship, but the threshold response appears to provide a stronger alternative. Using the 

bioassay data and recognizing seasonal effects, it appears that two targets can be suggested: a 

composite Ks from bioassay work yielding 28μg/L PO4-P and a 16μg/L PO4-P from threshold 

growth response found within lab monitoring (Table 3).

Lake Waco Target Estimates From Monitoring Data

Bioassays were used to identify the limiting nutrient and to develop predictive relationships 

between the limiting nutrient and algal biomass. Unfortunately, bioassays are not a direct 

measure of Lake Waco's response to changes in nutrient loading or in-lake nutrient supply 

rates. Furthermore, bioassays of this type may not account for complex limitation patterns 

(Sterner and Grover, 1998). Direct analysis of lake monitoring data will test for further 

associations between these variables and confirm the functional relationship between the 

presumptive limiting nutrient and our water quality response variable, CHLA. As discussed 

earlier, limited historical data prevent the application of mass-balance loading models to Lake 

Waco as a whole, however, it is possible to construct a predictive relationship between in-lake 

LETSI = 0.004x + 0.08

R2

 = 0.30; p<0.05

0

0.2

0.4

0.6

0.8

0 20 40 60 80 100

In-lake PO4-P Concentration (μg/L)

Maximum Control IVF/Maximum N+P IVF

P-limited sites only; N and co-limited sites removed
Nutrient Targets for Lake Waco and North Bosque River

26

algal biomass and in-lake phosphorus concentrations using data for each station averaged by 

year. For this analysis, average summer PO4-P concentrations were calculated for the springsummer growing period of April through September by year for each sampling site in the lake 

(Sterner, 1994; Lathrop et al., 1998). Simple linear regression analysis was performed on these 

calculated mean values for all years and sites. A more restricted analysis was also performed 

for sites near the dam because of their proximity to the City of Waco drinking water supply 

intake. The specific dam sites were chosen a priori based upon the segmentation schematics 

for application of the CE-QUAL-W2 reservoir model (see Flowers et al. In prep). Subsequent 

statistical analysis has suggested that these dam sites are not significantly different from a 

number of open lake sites (McFarland et al., 2001). However, the original analysis as presented 

to the Technical Workgroup and the Bosque River Advisory Committee in winter and spring 

of 1999 has been preserved for this report.

Table 3 Potential nutrient restoration targets for Lake Waco.

Potential nutrient targets to be used a restoration criteria and their sources. All targets are in terms of 

average annual summer values as defined in the text.

Figure 7 and 8 present the results of regression analysis of TIAER monitoring data and 

historical data supplied by Dr. Owen Lind (Lind, 1979). Figure 7 includes all available data for 

all sampling sites in Lake Waco. The analysis in Figure 8 is limited to data collected from 

sampling sites located in the lacustrine area of the reservoir near the dam. Both regressions 

produce significant, predictive relationships between the PO4-P and CHLA. The historical 

data from 1977 and 1978 anchor both relationships. Mean algal summer biomass for 1977 and 

1978 falls below the TNRCC screening level for CHLA in Texas reservoirs (TNRCC, 1998). In 

contrast, for a majority of the sites sampled in 1997 and 1998 mean CHLA exceeded the 

TNRCC screening level (Pearson and McFarland, 1999).

These significant, linear relationships provide the basis for establishing numerical nutrient 

targets. First, the historical data collected by Dr. Lind provide a temporal reference condition 

against which we can judge future productivity because their collection predates many of the 

recent changes in agricultural practices and urban growth thought to be responsible for 

increased phosphorus loading. The overall, grand mean summer CHLA concentration for the 

1977 and 1978 data is 11μg/L. This level of algal biomass is associated with a grand mean 

Target Source Target Value (μg/L) Time Frame Spatial Distribution

Relative algal growth rate 

average Ks

28 Summer annual average Central body of reservoir

Relative maximum biomass 

threshold

16 Instantaneous grab Entire reservoir

Mean relationship from 

1977-1978

8 Annual summer average Entire reservoir

Mean relationship for all 

data

14 Annual summer average Entire reservoir

TNRCC CHLA screening 

level and Figure 7

13 Annual summer average Central body of reservoir

Mean relationship from 

1977-1978

6 Annual summer average Dam sites in reservoir

TNRCC CHLA screening 

level and Figure 7

14 Annual summer average Dam sites in reservoir

Final Technical Workgroup 

recommendation

10 Annual summer average Central body of reservoir
 Chapter 2 Target Development

27

summer PO4-P concentration of 8μg/L, providing our third potential nutrient target. In 

contrast to the historical data, the grand summer means from the entire available data set 

provide a potential target representative of the long-term average condition in the lake during 

the summer season. Grand mean summer CHLA and PO4-P values for all sites and years 

included in this target evaluation are 20μg/L and 14μg/L, respectively, providing the fourth 

potential PO4-P target concentration of 14μg/L (Table 3).

Figure 7 Regression analysis of CHLA with PO4-P concentrations for all Lake Waco sites.

Regression analysis of annual summer average CHLA concentration and annual summer average PO4-P 

concentration for all Lake Waco sites. Analysis based on surface grab samples including historic data 

from Lind (1979) and TIAER monitoring data from 1997 through 1998. PO4-P outlier from 6 Sept. 1977 

removed from analysis. Triangles = 1977 and 1978 values from Lind and squares = 1997 and 1998 values. 

Further target comparisons are possible with this regression analysis. For example, a potential 

nutrient target can be developed based upon the TNRCC CHLA screening level and the 

associated PO4-P concentrations. The TNRCC screening level is based on the 85th percentile of 

all CHLA measurements made in Texas reservoirs. As such, the screening level represents a 

broad regional standard. Using the approximate screening value of 20μg/L CHLA as the 

benchmark, the regression equation in Figure 7 yields the fifth potential PO4-P target 

concentration of 13μg/L (Table 3).

These first five potential targets depend upon data collected at multiple sites within Lake 

Waco. These sites have been positioned along a known physical and chemical gradient that 

spans the riverine to lacustrine areas of the lake (McFarland et al., 2001). The presence of this 

gradient enhances the range of the analysis presented in Figure 7 but also introduces the 

potential confounding factor of physical variation between sites in the reservoir. Although 

these sites exhibited phosphorus limitation in the nutrient bioassays, the physical conditions 

along this gradient are significantly different from those observed in the main body of the lake 

(McFarland et al., 2001). Target development for a more lacustrine area of the reservoir, based 

upon field data collected from sites located near the dam, was analyzed separately using the 

regression analysis presented in Figure 8. 

y = 0.89x + 8.19

R2

 = 0.68; p<0.05

0

10

20

30

40

50

0 8 16 24 32 40

Annual Summer Average PO4-P Concentration (μg/L)

Annual Summer Average CHLA (μg/L)
Nutrient Targets for Lake Waco and North Bosque River

28

Figure 8 Regression analysis of CHLA with PO4-P concentrations for Lake Waco dam sites.

Regression analysis of summer annual average CHLA concentration (April-September; 1977-78; 1997-98) 

and summer annual average PO4-P concentration for Lake Waco dam sites. Analysis was based on 

surface grab samples including historic data from Lind (1979) and TIAER routine monitoring data. Sites 

were taken from Lake Waco Model (Flowers et al,. In prep). PO4-P outlier from 6 Sept. 1977 removed 

from analysis. Symbols as in Figure 7. 

All of these sites fall within the boundaries of segment 8 of the CE-QUAL-W2 model 

implementation for Lake Waco (Figure 9; Flowers et al., in prep.). All of the sites also fall into a 

single group with uniform physical and chemical characteristics (McFarland et al. 2001). 

Qualitatively, the regression analysis results for sites located in segment 8 (Figure 8) are very 

similar to those for all Lake Waco sites combined (Figure 7). Significant linear relationships 

exist between algal biomass and PO4-P in both cases, but the slopes of these relationships 

differ. The regression for the sites in segment 8 has a steeper slope and lower y intercept than 

the relationship for all of the sites. Despite these differences, the potential targets based upon 

this more restricted analysis are very similar to targets developed from the comprehensive 

analysis of all sampling sites in Lake Waco. Using the relationship in Figure 8, the potential 

PO4-P target based on historical field data dropped from 8μg/L to 6μg/L in this analysis, 

providing the sixth potential target. In contrast, the seventh suggested PO4-P target based on 

the TNRCC screening level has increased from 13μg/L to 14μg/L.

Table 3 summarizes the potential targets presented in the text, providing an overview of the 

temporal and spatial characteristics of each alternative. The overall range of targets from 8 to 

28μg/L PO4-P span averaging periods of from a few months to a few years. The strongest 

relationship with the most relevance to the goal of target development appears to be the 

annual summer average targets derived from Figure 7 and 8.

Technical Work Group Target Recommendations For Lake Waco

The potential PO4-P nutrient targets were presented to the project Technical Work Group 

(TWG) convened for the purpose of reviewing and approving both the methods and results of 

this phase of target development in the Lake Waco-Bosque River watershed. The composition 

of the workgroup, including affiliations, is presented in Appendix B, ”Bosque River-Lake 

Waco Watershed Technical Work Group.” Workgroup members received detailed 

presentations and interim work products during target development. Final deliberations by 

the members focused on the alternatives presented in Table 3. After careful consideration, a 

y = 1.26x + 3.48

R2

 = 0.90; p<0.05

0

10

20

30

0 4 8 12 16 20

Annual Summer Average PO4-P Concentration (μg/L)

Annual Average CHLA (μg/L)
 Chapter 2 Target Development

29

target range of between 8 and 14μg/L was identified as desirable. A single numeric PO4-P

target of 10μg/L was also identified to facilitate comparisons between the target and the 

outcome of analytical modeling and load allocation exercises. All of these targets were 

generated after lengthy discussions of the scientific merits of the analyses as well as the level 

of effort to gather the appropriate data. In the end, the targets represented a consensus of the 

TWG members.

Figure 9 Lake Waco segmentation map from CE-QUAL-W2 model.

North Bosque River Restoration Targets

The approach to developing potential nutrient targets for the North Bosque River followed the 

same overall approach as that applied to Lake Waco. Algal growth potential bioassays (AGP; 

USEPA, 1978; APHA, 1995) were performed on water collected at downstream sites on the 

major tributaries to Lake Waco: South Bosque River (SB060), Middle Bosque River (MB070), 

Hog Creek (HC065), and North Bosque River (BO100; Figure 10). Monthly bioassays were run 

using Selenastrum capricornutum Printz. as inoculum over a two-year period. The standard 

algal bioassays were conducted at the limnology laboratory at Baylor University in Waco (see 

Dávalos-Lind and Lind, 1999).
Nutrient Targets for Lake Waco and North Bosque River

30

Figure 10 Bosque River watershed map with location of major stream sampling sites.

In addition to these AGP bioassays, a series of in situ stream bioassays were performed to 

determine the pattern of nutrient limitation. These same bioassays were then used to develop 

a predictive relationship between nutrient supply and algal production and growth. In-stream 

bioassays were performed using a recently developed periphytometer technique that supplies 

specific nutrient treatments to an artificial substrate (Matlock et al., 1998, 1999). Matlock 

periphytometers are capable of estimating stream trophic status using the ratio of control 

production to nutrient saturated production. This ratio is referred to as the Lotic Ecosystem 

Trophic Status Index (LETSI). A similar ratio was used in the Lake Waco target development 

in Figure 6.

The Matlock periphytometer bioassay is based on substrate colonization and growth in 

response to nutrient availability. The method integrates water column influences on substratespecific processes through the use of artificial substrates. Suspended algae capable of a 

periphytic growth habitat colonize the artificial substrates. Growth-rates on the artificial 

substrate are regulated by the availability of the limiting nutrient as supplied by the 

periphytometer, and corresponding rates of biomass accumulation provide estimates of 

primary productivity. Recent tests have confirmed a correlation between biomass 

accumulation on the glass fiber filters and primary productivity measured using radiometric 
 Chapter 2 Target Development

31

methods (Rodriguez and Matlock, personal communication). In these bioassays, individual 

glass-fiber filters were supplied with nitrogen (N), phosphorus (P), or N and P in combination 

and deployed in the stream in a replicated design to test for nutrient limitation in algal 

biomass production. Control filters were used to assess in-stream baseline production over the 

deployment period. Growth and production responses to the treatments were estimated from 

CHLA production on the respective filters. 

A total of eight stream sites within the watershed were tested seasonally using this method. 

The in-stream periphytometers were deployed at five sites along the North Bosque River 

(BO020, BO040, BO070, BO090, BO100), one site each on the Middle Bosque River (MB060), 

Hog Creek (HC065), and at a reference site along Neils Creek (NC060). Data collected 

represents three different time periods at each site (Matlock and Rodriguez, 1999).

AGP Bioassay Results

Phosphorus was the element limiting growth of S. capricornutum Printz. for all tributary sites 

as indicated from the standard algal growth potential (AGP) bioassay evaluations. The 

addition of nitrogen to the bioassays produced a very limited growth response above that 

observed in the bioassay controls (Table 4). In contrast, the addition of phosphorus produced 

large growth responses in S. capricornutum Printz. The fraction of trials at each site exhibiting 

phosphorus-stimulated growth (i.e., significant growth responses to P addition) exceeded 80 

percent for all sites tested by the bioassays (Table 5). All sites indicated a strong general trend 

towards increased growth under phosphorus additions as compared to control treatments. 

Assuming the bioassay algae are indicative of in-stream algae responses, all major tributaries 

to Lake Waco are phosphorus limited immediately downstream of sampling locations.

Table 4 Algal growth potential (AGP) bioassay results for tributaries of Lake Waco.

Mean and standard deviation (n=25) of Selenastrum capricornutum Printz. growth response in 

fluorescence units to phosphorus and nitrogen additions (fluorescence of treatment minus control) for 

samples collected December 1996 through November1998 (Dávalos-Lind and Lind, 1999).

Table 5 Summary of nutrient limitation for tributaries of Lake Waco.

Percent of treatment means showing a significant growth response of Selenastrum capricornutum Printz. 

to phosphorus and nitrogen additions (fluorescence of treatment minus control) for samples collected 

between December 1996 and November 1998 (Dávalos-Lind and Lind, 1999).

Site Treatment Selenastrum capricornutum Printz.

AGP in Fluorescence Units

HC065 P Addition 136 + 103

N Addition 2 + 4

SB060 P Addition 188 + 122

N Addition 6 + 20

MB070 P Addition 124 + 118

N Addition 2 + 5

BO100 P Addition 102 + 85

N Addition 3 + 6

Site Selenastrum capricornutum Printz. Limitation

P-Limited (percent) N-Limited (percent)

HC065 90 5

SB060 87 13

MB070 90 10

BO100 84 12
Nutrient Targets for Lake Waco and North Bosque River

32

Periphytometer Results

The periphytometer results were used to compare growth potential between control 

treatments and nutrient added treatments for a number of sites (Table 6). In summary, trials at 

the reference site on Neils Creek (NC060) indicated phosphorus as the limiting nutrient. The 

North Bosque River sites (BO020, BO040, BO070, BO090, BO100) indicated phosphorus 

limitation more often than nitrogen limitation, although in the nutrient-enriched environment 

of the upper North Bosque (i.e., BO020 and BO040), the in situ trials indicated that other 

factors limited algal growth more than either nitrogen or phosphorus. The North Bosque 

River sites show a downstream trend of increasing frequency of nutrient limitation (Table 6). 

Downstream sites have a higher frequency of significant limitation as do reference sites, 

corresponding with a pattern of higher nutrient concentrations in the Upper North Bosque 

River watershed (above BO070) as a result of higher nutrient loadings (McFarland and Hauck, 

1999b).

Table 6 Summary of nutrient limitation results for Matlock periphytometers.

Table 6 displays the number of experiments showing significant nutrient limitation results for Matlock 

periphytometer deployments in tributaries of Lake Waco. Fifty-three percent of the replicated 

experiments showed some form of nutrient limitation, with the majority being phosphorus limited.

In-stream Limiting Nutrient

Taken together, the AGP and periphytometer bioassays indicate phosphorus in the form of 

PO4-P limits algal growth and production of suspended and attached algae throughout the 

Bosque River drainage. The effects of enrichment are more pronounced along the Upper 

North Bosque River, while the reference site on Neils Creek exhibits the most consistent 

pattern of phosphorus limitation. Downstream sites on the North Bosque River also appear to 

be phosphorus limited with some regularity.

Summary of Stream Bioassay Results: 1997-1998

Site P-Limited N-Limited Co-Limited Other Total

North Bosque River Sites

BO020 0 0 0 3 3

BO040 1 0 0 2 3

BO070 0 1 1 1 3

BO090 1 0 1 0 2

BO100 2 0 0 1 3

NC060 2 0 0 0 2

Other Lake Waco Tributary Sites

MB060 0 1 0 1 2

HC060 0 0 0 1 1

Totals 6 2 2 9 19

Percent 32 11 11 47 100
 Chapter 2 Target Development

33

Some contradictions are present between the results of the two bioassays. While AGP 

bioassays are phosphorus limited for Hog Creek and the Middle Bosque River water, 

periphytometers at these sites did not respond to experimental additions of PO4-P. Analysis of 

control growth rates for periphytometers from the Middle Bosque River did indicate a growth 

rate response to ambient phosphorus levels (see analysis and discussion below). This was not 

the case for Hog Creek.

Target Development

As was the case with Lake Waco target development, a number of alternative analyses were 

undertaken to develop target estimates for the Bosque River drainage with an emphasis on the 

North Bosque River. Four separate general approaches were used to develop a predictive 

relationship between in-stream phosphorus and CHLA concentrations for target 

development. The first method evaluated statistical relationships from monitoring data 

between annual average CHLA versus phosphorus concentrations from routine grab 

sampling data from sites throughout the Lake Waco Bosque River watershed. The second 

approach compared TNRCC screening levels for CHLA with the predictive relationships 

developed with the first method. The third used the Neils Creek reference site to set a 

benchmark for ecosystem functions from a minimally impacted watershed. The fourth 

comparison evaluated the relationship of in situ productivity compared to maximum 

potential productivity. Matlock’s LETSI measure was plotted as a function of 

contemporaneous in-stream phosphorus concentrations and fit to the Monod population 

growth model.

Statistical Relationships From Monitoring Data

In evaluating the stream target, PO4-P was again chosen as the independent variable driving 

algal productivity and growth. Unlike total-P, PO4-P is not confounded with the dependent 

variable algal biomass (i.e., algae contain significant amounts of organic phosphorus). 

Secondly, PO4-P has been shown to predict algal population growth rates according to an 

external-substrate Monod model (Monod, 1950; Kilham, 1978). Third, aquatic ecosystems 

enriched through cultural eutrophication are known to have elevated, measurable levels of 

PO4-P, and this is especially true for the Upper North Bosque River (Pearson and McFarland 

1999). In contrast, less productive natural systems have ambient PO4-P concentrations that are 

often hard to measure because of very low concentrations and very high flux rates between 

PO4-P and other forms of phosphorus (e.g., Dillon and Rigler, 1974). Fourth, PO4-P had 

greater predictive power than total-P in explaining observed patterns in the distribution of 

algal biomass in the field. Finally, PO4-P was the largest component of bioavailable 

phosphorus in the North Bosque River as measured by the Sharpley (1993) method (TIAER 

unpublished data).

Monitoring data from January 1997 through December 1998 collected at eight main stem sites 

along the North Bosque River were compared to TNRCC screening levels for CHLA, PO4-P 

and total-P (Pearson and McFarland, 1999). While 54 percent of CHLA samples exceeded the 

screening level of 16.5μg/L, only 2 percent of all samples exceeded the PO4-P screening level 

of 1400μg/L. 

Figure 11, 12, and 13 illustrate three separate relationships between annual average ambient 

CHLA concentrations and annual average PO4-P concentrations for data collected 1993 

through 1998. Analysis was restricted to sites where annual average PO4-P concentrations 

were less than 500μg/L because primary productivity is nutrient-saturated at in-stream PO4-P 

concentrations between 70-150μg/L (Figure 11). All three of these figures support the 
Nutrient Targets for Lake Waco and North Bosque River

34

conclusion that portions of the North Bosque River experience concentrations of PO4-P 

sufficient to saturate algal biomass growth and accumulation. Figure 11 summarizes annual 

average data from biweekly grab sampling for all stream-monitoring sites in the Lake Waco 

Bosque watershed. This includes sites from all of the tributaries to Lake Waco, mainstem sites 

from the North Bosque River as well as sites on tributaries of the North Bosque.

Figure 11 Annual average algal biomass as a function of grab sample PO4-P concentration.

Annual average algal biomass as a function of ambient PO4-P concentrations < 500μg/L for all grab 

samples from Lake Waco-Bosque River watershed stream sites. Monod model fit to data is significant at 

p<0.05 level. 

Figure 12 In-stream algal biomass as a function of time-weighted PO4-P concentration.

Annual average algal biomass as an exponential function of time-weighted PO4-P concentration for all 

North Bosque River and tributary sites except BO020, BO040 and SB050. Analysis limited to sites with 

PO4-P concentration < 500μg/L. Relationship is significant at the p<0.05 level. 

0

25

50

75

0 50 100 150 200 250 300 350 400 450

Annual Average PO4-P Concentration (μg/L); Grab Samples Only

Annual Average CHLA (μg/L)

CHLA = 32.12 * [PO4-P] / (0.041 + [PO4-P])

R2

 = 0.17; p < 0.01

y = 12.38Ln(x) - 28.6

R2

 = 0.65; p<0.01

0

10

20

30

40

50

60

0 50 100 150 200 250 300

Annual Average PO4-P Concentration (μg/L)

Annual Average CHLA (μg/L)
 Chapter 2 Target Development

35

Figure 13 In-stream algal biomass as a function of flow-weighted PO4-P concentration.

Annual average algal biomass as an exponential function of flow-weighted PO4-P concentration for all 

North Bosque River and tributary sites except BO020, BO040, and SB050. Analysis limited to sites with 

PO4-P concentrations < 500μg/L. Relationship is significant at p<0.05 level.

The annual average CHLA concentration was determined as the simple arithmetic mean of 

samples collected on a routine monthly basis for all three figures. The annual average PO4-P 

calculation for Figure 11 was made more complex because of the availability of biweekly grab 

samples and temporally intense storm water samples that were collected at intervals less than 

daily. For monitoring sites with stream flow records, mean daily concentrations were 

estimated by dividing each annual hydrograph into intervals based on the date and time 

when water quality samples were taken, applying a midpoint rectangular integration method 

(Stein, 1977) and appropriate aggregation to calculate a daily PO4-P mass, and dividing the 

mass by corresponding daily stream flow volume to give a concentration. The annual average 

PO4-P concentration is then determined as the arithmetic average of all the daily 

concentrations for each site and year. For sites without stream flow data and storm water 

sampling, the annual PO4-P concentration was determined by first calculating an average 

monthly concentration from biweekly sampling (either two or three samples per month) and 

then averaging the mean concentrations for the 12 months of the year. 

For Figure 11, a Monod function has been fit to the data. This model was chosen based on the 

assumption that algal biomass sampled at a fixed point in a continuously flowing system with 

a constant resource supply will conform to a simple external nutrient growth model. The Ks of 

approximately 40μg/L PO4-P from the Monod fit to the ambient concentration data in Figure 

11 provides the first potential nutrient target for the North Bosque River. Derived from a 

watershed-wide response curve, this estimate is anchored on one end by reference sites with 

minimal production and on the other by enriched sites at near maximum productivity. A 

threshold level is also visible in Figure 11. As annual average PO4-P reaches 50μg/L, a major 

discontinuity appears in the data set that provides the second potential target. This 

discontinuity is also well below the asymptote of the graphical relationship between CHLA 

and PO4-P.

The robustness of the relationship in Figure 11 was explored using two alternative calculations 

of average in-stream nutrient concentration. In Figure 12, time-weighted data were used to 

calculate an annual average PO4-P concentration from monthly flow-weighted concentration 

data. In Figure 13, annual PO4-P concentration was calculated as the ratio of total annual load 

divided by total annual flow. Annual average CHLA was fit to these two alternative measures 

y = 13.14Ln(x) - 35.9

R2

 = 0.71; p<0.05

0

10

20

30

40

50

60

0 50 100 150 200 250 300 350

Annual Flow-Weighted PO4-P Concentration (μg/L)

Annual Average CHLA (μg/L)
Nutrient Targets for Lake Waco and North Bosque River

36

of PO4-P concentration using an exponential model (Figure 12 and 13). Both relationships 

illustrate the dependence of annual average in-stream CHLA levels on in-stream PO4-P 

concentrations. These significant predictive relationships illustrate the functional dependence 

of primary production on the average availability of the limiting nutrient in this system. Algal 

biomass responds to the limiting nutrient in a predictable manner regardless of how average 

in-stream concentration is approximated, illustrating the robust nature of the target 

development methodology employed in this study.

The third source of a potential target comes from analysis of the watershed reference sites. 

Reference sites represent sustainable ecosystem function under minimal impacts from 

anthropogenic sources and provide benchmarks against which we can judge the feasibility of 

proposed targets. They are a source of real life best-case scenarios in the watershed of interest.

The TNRCC Water Quality Monitoring Program has established Neils Creek as an ecoregion 

reference in the Lake Waco Bosque River watershed. Analysis of fish communities (Jones, 

2000), macrobenthic invertebrate communities (Hendon et al., 1998), and in-stream habitat 

(Hendon et al., 1998) have established Neils Creek as a site free from major water quality 

problems. Compared to values for sites located along the North Bosque River, values from 

Neils Creek for mean CHLA and PO4-P were much lower than those from sites along the 

North Bosque River (Table 7). In general, the highest concentrations of CHLA and PO4-P are 

found in the upper reaches of the North Bosque River with decreasing concentrations from 

upstream to downstream locations (McFarland and Hauck, 1998a; Pearson and McFarland, 

1999). Using Neils Creek as a reference site, and based on data collected from 1996 through 

1998, an annual mean CHLA of 4μg/L could be expected at a PO4-P concentration of 15μg/L 

as a benchmark within this ecoregion.

Table 7 Summary of basic statistics for monthly chlorophyll and biweekly PO4-P samples.

Basic statistic from eight monitoring sites along the North Bosque River compared to reference site data 

on Neils Creek for January 1996 through December 1999

The fourth approach involves use of the Lotic Ecosystem Trophic Status Index (LETSI) to 

develop a predictive relationship between the ecosystem function of interest and the potential 

target variable. The LETSI is defined as the ratio of baseline primary productivity (BPP) to 

maximum potential productivity (MPP) where BPP is represented by the control treatment 

containing no added nutrients and MPP is represented by the N plus P treatment from the 

periphytometer bioassay method (Matlock et. al., 1999). LETSI should vary between zero and 

one with a value of one indicating that the stream is at MPP. LETSI values from the bioassay 

treatments were compared to in-stream PO4-P concentrations at the time of the 

periphytometer deployments (Figure 14). Sites BO020, BO040, BO070, BO090, and BO100 

represent a gradient of decreasing ambient PO4-P and CHLA concentrations as water flows 

downstream, away from major point and nonpoint sources of nutrient loading (McFarland 

CHLA (μg/L)

Mean Median Std. Min. Max # Obs.

North Bosque 27 16 34 0.5 290 430

Neils Creek 4 3 3 0.6 15 48

PO4-P (μg/L)

Mean Median Std. Min. Max # Obs.

North Bosque 340 100 610 2 4510 767

Neils Creek 14 9 14 2 80 86
 Chapter 2 Target Development

37

and Hauck, 1999a; 1999b). Figure 14 includes LETSI values calculated from bioassay results 

for all tributary sites and main stem sites from the Lake Waco Bosque River watershed that 

exhibited phosphorus limitation or that occurred along the North Bosque River nutrient 

supply gradient.

Figure 14 Summary of Matlock periphytometer bioassay results.

Functional relationship between LESTI bioassay results and in-stream PO4-P concentrations. Mean 

LETSI responses from individual deployments are plotted as a function of average in-stream PO4-P 

concentration measured during the deployment. Monod function is significant at the p<0.05 level.

In situ stream production, measured as the ratio of control to nutrient sufficient production, 

was a significant function of in situ PO4-P concentrations (Figure 14). Bosque River sites 

showed a decrease of LETSI values as you moved downstream from site BO040 to BO100. 

Sites BO020 and BO040 were at nutrient saturated production or MPP. Baseline productivity 

was saturated at PO4-P concentrations above 200μg/L. The reference site NC060 had a LETSI 

of 0.4 at a PO4-P concentration of 15μg/L. Sites showing little or no P limitation (BO020 and 

BO040) had LETSI values very close to unity, consistent with the predictions of the method 

(Matlock et al., 1998). Dose-response PO4-P treatments show reference-site nutrient sufficient 

growth at 50μg/L. A Monod equation was fit to the data using the Lineweaver-Burk 

parameter estimation method to calculate the Ks (Lehninger, 1975). LETSI attains 50 percent of 

its asymptote at a PO4-P concentration of 40μg/L, providing the last potential nutrient target.

Summary of Potential Stream Targets

Table 8 summarizes the potential PO4-P target values based upon the various assessment 

methods. As was the case with Lake Waco, all potential targets are defined in terms of the 

putative limiting nutrient in the system, PO4-P. Targets were derived from analysis of ambient 

monitoring data, reference site comparisons, and in situ experimental results. Targets were 

developed from the relationships discussed above and summarized in Table 8.

MB060

MB060 BO070

NC060

BO090

BO100 BO100

BO070

NC060 BO090 MB060

BO020 BO020

BO020 BO040

BO040

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

0 200 400 600 800 1,000 1,200

PO4-P (μg/L)

LETSI

LETSI=(0.98*[PO4-P]/(37.73+[PO4-P])

R2

 = 0.72; p < 0.05
Nutrient Targets for Lake Waco and North Bosque River

38

Table 8 Potential nutrient restoration targets for North Bosque River.

Potential nutrient targets to be used as restoration criteria and their sources. All targets are in terms of 

average annual summer values as defined in the text. Values are derived from various approaches 

described in the text.

From these relationships, a summary of potential PO4-P targets was presented to the Technical 

Work Group that also reviewed Lake Waco targets. An initial consensus target range of 15 to 

50μg/L PO4-P as an annual average was set for the North Bosque River at Meridian (BO085), 

Clifton (BO090), and Valley Mills (BO100). This recommendation was reviewed and modified 

to 30μg/L PO4-P as an annual average by a subcommittee of the Bosque River Advisory 

Committee for the Lake Waco-Bosque River watershed. The approved target was forwarded 

to additional subcommittees of the BRAC for incorporation into a recovery plan for the 

watershed.

Target Source PO4-P Target Value (μg/L) Time Frame Spatial Distribution

Ks from the Monod fit to the 

annual average grab sample data 40 Annual average Entire basin

Threshold level from the Monod 

fit to the annual average grad 50 Annual average Entire basin

Reference site annual mean 15 Annual average North Bosque River

Ks from the Monod fit to the 

dose-response / LETSI data 40 Grab average

North and Middle 

Bosque Rivers
39

CHAPTER 3

Discussion

The major challenge to achieving watershed-based solutions through integrated basin 

management is understanding how linkages between terrestrial and aquatic ecosystem 

components drive water quality. Aquatic and terrestrial components of basins are tightly 

coupled by nutrient and carbon cycles (e.g., Hynes, 1975). When these natural ecosystem 

functions are disrupted or overwhelmed by pollutants such as nutrients that originate from 

point and nonpoint sources, restoring water quality becomes an exercise in re-establishing 

these cycles. By focusing on watersheds, integrated basin management can design and test 

selective management actions, which aim to restore specific, degraded ecosystem functions 

like nutrient cycling and carbon assimilation. Once implemented, individual management 

actions need to be evaluated for success, and one critical measure of that success is the 

attainment of specific targets or indicators of ecosystem function. Evaluation for success is 

especially important for basins degraded by nonpoint source pollution known to originate 

from land-use conversions and inadequate management practices. 

Measurable targets are necessary to monitor the success or failure of best management 

practices or other nutrient management efforts. By definition, a nutrient management 

program that meets its target(s) is a programmatic success. If the correct target value was 

chosen, attainment of the target should also indicate the end of the water quality problem in 

the basin, which is the more relevant measure of a successful target. In order for this water 

quality measure to be met, the assessment variable used as the target must either have a cause 

and effect (i.e., mechanistic) relationship with the water quality impairment or have a well 

known correlation (i.e., co-linearity) with the water quality problem of concern. If either of 

these conditions is true, then a change in target variable value will have a high probability of 

indicating a meaningful change in the water quality of receiving waters.

Our analysis has demonstrated that in-lake and in-stream algal biomass varies as a function of 

ambient PO4-P concentrations. Additional tests of this functional relationship for both the 

Lake Waco and North Bosque River ecosystems have also revealed that algal biomass 

accumulates according to a predictive, mechanistic model of resource-dependent growth with 

PO4-P as the limiting resource. Given the level of documentation presented supporting a 

cause and effect relationship between phosphorus availability and algal biomass, PO4-P 

concentrations are a reasonable indicator of ecosystem function and health for the Lake WacoBosque River watershed. Specific targets defined in terms of average PO4-P concentrations 

have a high probability of tracking ecosystem response to any future restoration activities in 

the watershed.

The actual numeric values of the targets presented in Chapter 2, “Target Development”, 

compare favorably with the literature values discussed in Chapter 1, “Introduction”. The Lake 

Waco consensus target of 10μg/L is identical to past suggestions from Vollenweider (1968) 

and Sawyer (1947). The 30μg/L target for the North Bosque River is also well within the range 

of the published in-stream limits reviewed in Chapter 1, “Introduction”.

The targets developed here are directly related to the water quality problems identified by 

previous studies. Each target is based on a mechanistic link between the limiting nutrient and 
Nutrient Targets for Lake Waco and North Bosque River

40

algal growth and production. This link is the basis of a predictive relationship between the 

target (P) and the measure of impairment subject to control during implementation (CHLA). 

However, these relationships are limited by two factors: the short duration of the study (two 

years) and the use of in-lake and in-stream spatial gradients to predict future water body 

responses to changes in loading and runoff. Because of these limitations, targets for Lake Waco 

and the North Bosque River should continue to be reviewed and refined on a regular basis.

The proposed targets have already been used in the evaluation of proposed best-management 

practices (BMPs) within the Lake Waco-Bosque River watershed. Watershed-loading (SWAT) 

and reservoir simulation (CE-QUAL-W2) modeling have been applied to evaluate the 

effectiveness of BMPs in meeting the proposed targets. As part of this process, the 

management practices available have been modeled to determine the feasibility of meeting 

these proposed targets through nonpoint and point source load allocation/reduction in the 

Lake Waco-Bosque River watershed. The results of these modeling studies will help guide the 

development and implementation of watershed restoration plans based in large part on the 

targets developed in this report. The success of specific management actions will be judged by 

future water quality conditions in the component water bodies. Nutrient targets or other 

numeric benchmarks must be a part of the measurement of this success if the process is to be 

credible.
41

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Nutrient Targets for Lake Waco and North Bosque River

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47

APPENDIX A

Bosque River-Lake Waco

Sampling Sites

Sites on the North Bosque River

Sampling on the North Bosque River was conducted at eight sites, beginning upstream at 

BO020 above Stephenville and continuing downstream to BO100 near Valley Mills. Routine 

grab samples were collected at all eight sites on the North Bosque River, while storm event 

samples were taken at sites BO020, BO040, BO070, BO090 and BO100.

The land uses above the North Bosque River sites do not vary greatly from site to site. Of note, 

however, is a general decrease in percentage of permanent pasture and dairy waste 

application fields and a general increase in percentage of land designated as woodland, range 

and cropland from upstream sites to downstream sites.

Six cities are located along the North Bosque River. These cities, listed upstream to 

downstream, are Stephenville (16,000), Hico (1,500), Iredell (370), Meridian (1,500), Clifton 

(3,600) and Valley Mills (1,200).

North Bosque River above Stephenville (site BO020): Site BO020 is located on the North 

Bosque River, at the crossing of State Highway 8 on the northeast boundary of Stephenville. 

BO020, an automated sampler site, is located just below the confluence of the North and South 

Forks of the North Bosque River. The drainage area for BO020 is primarily rural but does 

contain a small portion of the city of Stephenville.

North Bosque River below Stephenville Wastewater Treatment Plant (site BO040): Automated 

sampler site BO040, located on the North Bosque River approximately one quarter mile below 

the Stephenville wastewater treatment plant (WWTP), is the only North Bosque River site 

located directly below a municipal WWTP discharge. The site is located at the crossing of CR 

454; about five miles below site BO020. Although the WWTP is a dominant influence on the 

water quality at BO040 during low flow conditions, the drainage area includes storm water 

runoff from the city of Stephenville and from many of the rural land areas above and around 

Stephenville.

North Bosque River near Green Creek (site BO060): Site BO060, a grab sampling site, is located 

on the North Bosque River about 14 miles downstream of site BO040 at the crossing of CR 248. 

Tributaries entering the river between site BO060 and BO040 include Indian and Sims Creeks.

North Bosque River at Hico, Texas (site BO070): Automated sampler site BO070 is located near 

U.S. Geological Survey (USGS) station 08094800 on the North Bosque River at the crossing of 

U.S. Highway 281 in Hico, Texas. The drainage area of this site is referred to as the upper 

North Bosque River watershed in most TIAER data analysis reports. BO070 is located about 

seven river miles downstream of site BO060 and about one mile above the WWTP discharge 

for the city of Hico.
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North Bosque River at Iredell (site BO080): Site BO080 is located on the North Bosque River 

below the confluence of Duffau Creek with the North Bosque River. Monitoring is limited to 

biweekly physical measurements and grab sample analysis. BO080 is located about 14 river 

miles downstream of site BO070 and above the city of Iredell WWTP discharge.

North Bosque River at Meridian (site BO085): This monitoring site is located on FM Road 

2840, west of Meridian. Monitoring is limited to biweekly physical measurements and grab 

sample analysis. BO085 is located about 17 river miles downstream of site BO080 and above 

the city of Meridian WWTP discharge.

North Bosque River at Clifton (site BO090): Automated sampler site BO090 is located near 

USGS station 08095000 on the North Bosque River near the crossing of FM Road 219, about 

half a mile northeast of Clifton, Texas. BO090 is located approximately 14 river miles 

downstream of BO085 and above the city of Clifton WWTP discharge.

North Bosque River at Valley Mills (site BO100): Automated sampler site BO100 is located 

south of the USGS station 08095200 on the North Bosque River near the crossing of FM Road 

56 northeast of Valley Mills. BO100 is located about 12 river miles downstream of BO090 and 

about 28 river miles upstream from the mouth of the North Bosque River at Lake Waco. The 

discharge for the Valley Mills WWTP is located below site BO100.

Sites on Major Tributaries to Lake Waco

The North, Middle and South Bosque Rivers, and Hog Creek represent the major tributaries to 

Lake Waco. Each tributary is monitored using automatic storm samplers and routine manual 

grab samples. BO100 is included both in this category and in the North Bosque River category 

because it is the nearest North Bosque River site to Lake Waco.

The land uses within the watersheds of these four tributaries vary considerably. Range and 

woodland dominate the North Bosque River watershed, with considerable dairy activity, 

while the South and Middle Bosque and Hog Creek watersheds contain more cropland. Site 

BO100, on the North Bosque River, is the only one of the four sites on major tributaries to Lake 

Waco having substantial dairy activity within its drainage area. One dairy is located in the 

Middle Bosque River watershed, but it is located downstream of the MB060 sampling site. 

About three percent of the drainage area above BO100 is designated as dairy waste 

application fields, almost all of which occurs in the upper portion of the North Bosque River 

watershed above site BO070 (McFarland and Hauck, 1998). The drainage area above BO100 

contains over 746,000 acres, while the drainage areas above sites HC060, MB060, SB050 and 

SB060 each contain less than 77,000 acres.

North Bosque River at Valley Mills (site BO100).

Hog Creek (site HC060): An automated sampler is located on Hog Creek at the crossing of FM 

Road 185 near USGS station 08095400 about 6 miles east of Crawford, Texas. Site HC060 is 

about 10 miles upstream from Lake Waco. The majority of the land area above the Hog Creek 

site is characterized as either cropland or range, with no influence from dairy operations.

Middle Bosque River (sites MB060 and MB070): An automated sampler is located on the 

Middle Bosque River MB060 site, located east of Crawford at the crossing of FM Road 185, 

approximately 12 miles upstream from Lake Waco. The city of Crawford (700) is located below 

site MB060. Site MB070 is located approximately 1.5 miles north of US Highway 84 on 

Speegleville cutoff near the McGregor Municipal Airport. The land area above the Middle 
 Appendix A Bosque River-Lake Waco Sampling Sites

49

Bosque site is dominated by cropland, with the remaining land characterized primarily as 

wood and range.

South Bosque River (sites SB050 and SB060): Site SB060 is located on the South Bosque River at 

FM Road 2837, south of US Highway 84. Site SB050 is located on private property on Church 

Road, about 3⁄4 miles south of US Highway 84. The automatic sampler installed in January 

1997 was moved upstream to site SB050 in July 1997 due to backwater impacts from Lake 

Waco. The location of the site SB050, however, presented safety hazards for personnel trying 

to obtain grab samples. Therefore, grab samples representing the South Bosque River are 

taken at site SB060, while storm samples are taken at Site SB050. The city of McGregor (4,800) 

is located within the South Bosque River watershed, about 10 miles above sampling sites 

SB050 and SB060. The land area above the South Bosque sites is dominated by cropland, with 

no influence from dairy operations. Because of their proximity and the complementary nature 

of the sampling regimes, the data from the two sites are combined for this report.

Sites on Lake Waco

Lake Waco covers about 7,270 acres and a longitudinal distance of 14 miles in McLennan 

County (TNRCC, 1996). The City of Waco originally constructed Lake Waco in 1929 as a 

municipal water supply. The lake was enlarged in 1964 by the U.S. Army Corps of Engineers 

for flood control, conservation storage, and recreation. Lake Waco is formed by a rolled 

earthfill dam. As part of the TIAER Lake Waco sampling program, grab samples are generally 

collected 1 foot below the surface, 1 foot above the bottom of the lake and at a mid-depth 

between the surface and bottom depth. Hydrolab readings are also generally taken at 1-meter 

(3.28 feet) intervals for DO, pH and conductivity to profile the lake’s water quality 

characteristics with depth.

Lake Waco N. Bosque Arm (site LW010): LW010 is located in the upper reservoir arm near the 

North Bosque River midchannel upstream from FM 185 Bridge.

Lake Waco mouth of N. Bosque (site LW011): LW011 is located at the mouth of the North 

Bosque River. The site is marked by a buoy at the confluence of the river with the reservoir.

Lake Waco N. Bosque Arm (site LW012): LW012 is at midchannel at the lower end of the 

original North Bosque River channel. The site is midchannel between Reynolds Creek and 

Airport Park.

Lake Waco at structure of dam (site LW013): LW013 is located at the structure of the dam 

approximately 30 yards to the southwest of the structure.

Lake Waco Middle & South Bosque arm (site LW015): LW015 is located between the State 

Highway 6 bridge and a buoy to the north of the bridge approximately midchannel.

Lake Waco near mouth of Hog creek (site LW016): LW016 is located at the white buoy near the 

south shore just inside the mouth of Hog Creek.

Lake Waco at S. Bosque arm (site LW017): LW017 is located near the mouth of the South 

Bosque River on the north side of the channel.

Lake Waco at Langdon Branch arm (site LW020): LW020 is located at the center buoy that 

marks the confluence of Langdon Branch with the reservoir. Langdon Branch enters the 

reservoir at the dam.
Nutrient Targets for Lake Waco and North Bosque River

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Lake Waco at body of lake (site LW030): LW030 is located in the body of the reservoir just 

south of the dam.

Lake Waco between dam and retainer gates (site LW040): LW040 is located at a point between 

the dam and the retainer gates.

Lake Waco at body of lake (site LW050): LW050 is located in the body of the reservoir 

southwest of the spillway at the north end of the dam.

Lake Waco between bridge and dam (site LW060): LW060 is located approximately midway 

between the State Highway 6 bridge and the dam. The site is midchannel between the boat 

launch off Overflow Road and the boat launch on Lake Shore Drive (south shore).

Lake Waco at Speegleville I Park (LW070): LW070 is located at a white buoy directly in front of 

the Bosque Bend Clubhouse at Speegleville I park on the west shore of the lake.
51

APPENDIX B

Bosque River-Lake Waco

Watershed Technical Work Group

(Participants during nutrient target discussions)

Agency Representatives

Texas Natural Resource Conservation Commission Clyde Bohmfalk (Chair)

Jim Davenport

Larry Koenig

Allison Woodall

Mel Vargas

Larry Mitchell

Marie Knipfer

Hari Krishna

Charles Maddox

Texas State Soil and Water Conservation Board James Moore

Beade Northcut

City of Waco Richard Garrett

Mike Jones

Natural Resources Conservation Service Allan Colwick

University of Texas George Ward

Brazos River Authority Mike Meadows 

Tom Conry

Texas Parks & Wildlife Joan Glass

EPA Region VI Shawneille Campbell
Nutrient Targets for Lake Waco and North Bosque River

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