Prepared in cooperation with the Bureau of Reclamation

Review of Revised Klamath River Total Maximum Daily 

Load Models from Link River Dam to Keno Dam, Oregon

By Stewart A. Rounds and Annett B. Sullivan

Open-File Report 2013–1136

(Reissue of an Administrative Report prepared for the Bureau of Reclamation, 2010)

U.S. Department of the Interior

U.S. Geological Survey
ii

U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia 2013

For more information on the USGS—the Federal source for science about the Earth,

its natural and living resources, natural hazards, and the environment:

World Wide Web: http://www.usgs.gov

Telephone: 1-888-ASK-USGS

Suggested citation:

Rounds, S.A., and Sullivan, A.B., 2013, Review of revised Klamath River total maximum daily load models from Link 

River Dam to Keno Dam, Oregon: U.S. Geological Survey Open-File Report 2013-1136, 31 p.

http://pubs.usgs.gov/of/2013/1136/ (Reissue of an Administrative Report prepared for the Bureau of Reclamation, 2010)

Any use of trade, product, or firm names is for descriptive purposes only and does not imply 

endorsement by the U.S. Government. 

Although this report is in the public domain, permission must be secured from the individual 

copyright owners to reproduce any copyrighted material contained within this report.
iii

Contents

Executive Summary....................................................................................................................................................... 1

Introduction and Background......................................................................................................................................... 3

Description of Study Area .......................................................................................................................................... 5

Purpose and Scope ................................................................................................................................................... 7

Review of Revised Models ............................................................................................................................................ 7

Model Changes.......................................................................................................................................................... 7

Boundary Conditions .............................................................................................................................................. 8

Model Source Code................................................................................................................................................ 8

Model Parameters.................................................................................................................................................. 8

Model Results........................................................................................................................................................13

Natural Conditions Scenario..................................................................................................................................14

Remaining Issues .....................................................................................................................................................21

Boundary Conditions .............................................................................................................................................21

Model Source Code...............................................................................................................................................22

Model Parameters.................................................................................................................................................22

Model Results........................................................................................................................................................24

Natural Conditions Scenario..................................................................................................................................26

Perspectives on Water-Quality Modeling ..................................................................................................................27

Acknowledgments ........................................................................................................................................................28

References Cited..........................................................................................................................................................28

Appendix A.Qualifications of Reviewers .......................................................................................................................31

Figures

Figure 1. Map showing the Klamath River, its major tributaries, and locations of dams on the upper river, Oregon

and California. .............................................................................................................................................................. 4

Figure 2. Map showing Link River Dam to Keno Dam reach of the Klamath River, Oregon ......................................... 6

Figure 3. Graphs showing dependence of the rate of sediment oxygen demand (SOD) on water temperature for the 

original and revised Lake Ewauna to Keno Dam Klamath River TMDL models........................................................... 10

Figure 4. Graph showing dependence of the oxygen rate multiplier on the dissolved oxygen concentration for the 

Lake Ewauna to Keno Dam Klamath River TMDL model. ........................................................................................... 12

Figure 5. Graph showing upstream boundary algae concentrations in the original and revised natural conditions 

models......................................................................................................................................................................... 15

Figure 6. Graph showing upstream boundary labile organic matter concentrations (LDOM + LPOM) in the original

and revised natural conditions models........................................................................................................................ 16

Figure 7. Graph showing upstream boundary organic matter concentrations (LDOM and LPOM) in the original and 

revised natural conditions scenarios............................................................................................................................ 17

Figure 8. Graph showing sum of organic matter and algae boundary input concentrations in the original and revised 

natural conditions models............................................................................................................................................ 17

Figure 9. Graph showing total phosphorus boundary inflow concentrations in the original and revised natural 

conditions models........................................................................................................................................................ 18

Figure 10. Graph showing dissolved inorganic phosphorus concentrations at the downstream outflow (Keno reef) in 

the original and revised natural conditions models. ..................................................................................................... 19
iv

Figure 11. Graphs showing total phosphorus mean and 1- and 2-standard deviations for the eutrophic and 

mesotrophic OECD lake classifications. ...................................................................................................................... 20

Figure 12. Graph showing simulated conversion rates from “healthy” to “unhealthy” algae (K1) and back (K2) for 

phytoplankton and epiphyton in the Klamath River TMDL model for Lake Ewauna to Keno Dam, Oregon................. 23

Figure 13. Graphs showing measured and simulated nitrate concentrations in the Klamath River at Keno 

(Highway 66) ............................................................................................................................................................... 25

Figure 14. Graphs showing simulated withdrawal rates for the North and Ady Canals for the natural conditions 

scenario and the year 2000 current conditions scenario.............................................................................................. 26

Tables

Table 1. Goodness-of-fit statistics for the original and revised Lake Ewauna to Keno Dam models of the Klamath 

River, Oregon, using results from May 1 through October 31...................................................................................... 13

Table 2. Annual and summer average total phosphorus concentrations in the major inflows and the downstream 

outflow of the original and revised natural conditions models...................................................................................... 19

Conversion Factors, Datums, and Abbreviations and Acronyms

Inch/Pound to SI

Multiply By To obtain

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

SI to Inch/Pound 

Multiply By To obtain

gram (g) 0.03527 ounce, avoirdupois (oz)

meter (m) 3.281 foot (ft) 

square meter per day (m2/d) 10.76 square foot per day (ft2/d)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows: °F=(1.8×°C)+32.

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

Datums

Vertical coordinate information is referenced to the Upper Klamath Lake Vertical Datum (UKLVD), a local datum established by 

the Bureau of Reclamation. For purposes of this report, UKLVD – 1.78 ft = NGVD 29. “Elevation,” as used in this report, refers to 

distance above the vertical datum. 

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

Acronyms and Abbreviations

DO dissolved oxygen 

DOC dissolved organic carbon 

DOM dissolved organic matter

EPA U.S. Environmental Protection Agency 

ESP elevation of spillway

FSOD fraction of user-specified sediment oxygen demand 

ISS inorganic suspended solids 

LDOM labile dissolved organic matter

LPOM labile particulate organic matter

N nitrogen 

ODEQ Oregon Department of Environmental Quality 

OM organic matter

P phosphorus 

POM particulate organic matter

RDOM refractory dissolved organic matter

RPOM refractory particulate organic matter

SDK sedimentary organic matter decomposition rate

SOD sediment oxygen demand 

TDS total dissolved solids

TMDL total maximum daily load

TN total nitrogen

TP total phosphorus 

UKL Upper Klamath Lake

USGS U.S. Geological Survey
vi

This page is intentionally blank.
1

Review of Revised Klamath River Total Maximum Daily 

Load Models from Link River Dam to Keno Dam, Oregon

By Stewart A. Rounds and Annett B. Sullivan

Executive Summary

Flow and water-quality models are being used to support the development of Total Maximum Daily 

Load (TMDL) plans for the Klamath River downstream of Upper Klamath Lake (UKL) in south-central 

Oregon. For riverine reaches, the RMA-2 and RMA-11 models were used, whereas the CE-QUAL-W2 

model was used to simulate pooled reaches. The U.S. Geological Survey (USGS) was asked to review 

the most upstream of these models, from Link River Dam at the outlet of UKL downstream through the 

first pooled reach of the Klamath River from Lake Ewauna to Keno Dam. Previous versions of these 

models were reviewed in 2009 by USGS. Since that time, important revisions were made to correct

several problems and address other issues. This review documents an assessment of the revised models, 

with emphasis on the model revisions and any remaining issues.

The primary focus of this review is the 19.7-mile Lake Ewauna to Keno Dam reach of the Klamath 

River that was simulated with the CE-QUAL-W2 model. Water spends far more time in the Lake 

Ewauna to Keno Dam reach than in the 1-mile Link River reach that connects UKL to the Klamath 

River, and most of the critical reactions affecting water quality upstream of Keno Dam occur in that 

pooled reach. This model review includes assessments of years 2000 and 2002 current conditions 

scenarios, which were used to calibrate the model, as well as a natural conditions scenario that was used 

as the reference condition for the TMDL and was based on the 2000 flow conditions. The natural 

conditions scenario included the removal of Keno Dam, restoration of the Keno reef (a shallow spot that 

was removed when the dam was built), removal of all point-source inputs, and derivation of upstream 

boundary water-quality inputs from a previously developed UKL TMDL model. 

This review examined the details of the models, including model algorithms, parameter values, and 

boundary conditions; the review did not assess the draft Klamath River TMDL or the TMDL 

allocations. Attention to the details of a model is one of the best ways to identify potential problems, 

correct them if possible, and begin to assess the magnitude of potential model errors and uncertainty. 

Model users need to determine the level of acceptable uncertainty associated with their objectives, 

identify all sources of potential uncertainty (model uncertainty, data uncertainty, etc.), and assess their 

approach and results accordingly. In the draft Klamath River TMDL, the Oregon Department of 

Environmental Quality identified the upstream boundary conditions as the largest source of uncertainty 

for both the current and natural conditions scenarios, not the model algorithms or choice of model 

parameters. We agree that the upstream boundary conditions are one of the largest, if not the largest, 

source of model uncertainty; therefore, the derivation of upstream boundary conditions may be more 

important to the TMDL than some other model-related issues identified in this review.

The revised models contain a number of changes, some of which were done to solve small 

problems and are largely inconsequential to model results, but others of which are important and affect 

model predictions of instream concentrations. A consistent version of the model is now applied to all 
2

scenarios, and an error in the source code was corrected that had inadvertently discarded 20 percent of 

the incoming solar radiation in the original model. The baseline light-extinction coefficient for water 

was decreased and set to a consistent and defensible value across all models of reservoir reaches. 

Inconsistencies among the values of certain parameters in the original models, such as the ammonia 

nitrification rate and the decomposition rates of organic matter, have been eliminated, although the 

reasoning behind the final selections was not documented. The dependence of the rate of sediment 

oxygen demand (SOD) on temperature was modified such that the SOD rate was substantially decreased 

at temperatures less than 20°C, causing the model to predict higher dissolved oxygen (DO) 

concentrations in spring, autumn, and winter. Although that change to the temperature dependence 

function was done to make the function more similar to the model’s default, this change was not 

accompanied by any documentation of recalibration or sensitivity exercises. The maximum SOD rate 

for the 2002 current conditions scenario was decreased from 3.0 grams per square meter per day 

(g/m2/d) in the original model to 2.0 g/m2/d in the revised model, a considerable adjustment that appears 

to have been needed to offset effects of a change to another variable (O2LIM) that would have resulted 

in a substantial increase in the effective SOD rate for 2002. A 50-percent decrease in the SOD rate over 

a 2-year period, however, is not likely to be mirrored by field measurements, so this change may be 

compensating for some process that is not represented correctly in the DO budget for the current 

conditions scenarios. 

Several important changes were made to the natural conditions scenario. First, the elevation of the 

Keno reef was corrected; the elevation specified in the original model was 1 foot too high, which 

affected the volume of the pooled reach and the travel time through it. The most important changes to 

this scenario were to the upstream boundary inputs of organic matter and algae, which affect incoming 

fluxes of nitrogen and phosphorus. Algal biomass inputs were increased by approximately 60 percent 

during summer because of a change in the way those inputs were derived from results of the UKL 

TMDL model. Non-algal organic matter inputs were decreased, particularly in summer to correct a 

problem attributed to double-counting of phosphorus in the original inputs. The distribution of non-algal 

organic matter was changed from 20 percent dissolved in the original model to 90 percent dissolved in 

the revised model in response to review comments and published data. The overall sum of algal biomass 

and non-living organic matter was decreased, which resulted in lower inputs of total phosphorus and 

nitrogen. Total phosphorus inputs were less than 0.03 mg/L, and although the inputs were derived from 

selected results of the UKL TMDL model, these concentrations seem too low to be representative of a 

historically eutrophic system surrounded by extensive wetlands, peat soils, and a groundwater system 

high in phosphorus. The draft TMDL states that the upstream boundary conditions are the greatest 

source of uncertainty, greater than any uncertainty associated with the models. Efforts to improve 

existing models of algal growth and nutrient cycling in UKL, therefore, would provide a substantial 

benefit to downstream modeling efforts on the Klamath River. 

Although many improvements were made in revising the Klamath River TMDL models, some 

issues and uncertainties remain. Several errors in the model source code remain, but do not affect model 

results for this application as long as certain options and rates are not changed; future users of these 

models should be aware of these issues. Although the distribution of dissolved and particulate organic 

matter was modified for the natural conditions scenario, that distribution was not changed for the current 

conditions scenarios. Recent data on that distribution and the likely rates of organic matter 

decomposition could be used to improve these models in the future. Nitrate predictions at Keno 

(Highway 66) still are too high for the current conditions scenarios; future efforts should re-evaluate the 

model’s denitrification rates and the release rate of ammonia from anoxic sediments. Possibly the most 

important of the remaining issues are tied to the two-state (healthy/unhealthy) hypothesis for the algae 
3

population that was coded into the model. Some of the rates and conversion functions could be refined 

to make them more acceptable; currently, the published literature does not support the concept of 

moderately low dissolved-oxygen concentrations as a stressor of algae in the ranges used by the model. 

More research is needed before these algorithms can be truly tested. The algorithms currently appear to 

help the model fit the patterns in the available data, and that is useful and perhaps sufficient for some 

purposes, but those algorithms are not truly predictive or reliable for certain purposes until they can be 

tested through well-designed experiments and research.

In summary, the TMDL models used to simulate Link and Klamath Rivers from Link River Dam to 

Keno Dam were revised to fix several problems and address various issues. The resulting models are an 

improvement over those that were reviewed by USGS in 2009, and represent a useful advance in the 

simulation of a complex system that is difficult to model. However, several issues remain that cause 

increased uncertainty in the model results. Depending on the objectives of the modeling, now or in the 

future, these remaining issues could be more or less important. For the Klamath River TMDL, the 

upstream boundary conditions may be a larger source of uncertainty than the concerns with model 

algorithms and model parameters identified in this review. Efforts to re-evaluate the available models of 

algal growth and nutrient cycling in UKL would be highly beneficial to downstream modeling efforts in 

the Klamath River.

Introduction and Background

The Klamath River flows from Upper Klamath Lake (UKL) in south-central Oregon past a series of 

dams into northern California, where the river eventually empties into the Pacific Ocean near the town 

of Klamath (fig. 1). The Klamath River does not meet certain water-quality standards as specified by the 

States of Oregon and California, and both States have placed the Klamath River on their list of impaired 

water bodies. As required by the Federal Clean Water Act, these States and the U.S. Environmental 

Protection Agency (EPA) are in the process of creating Total Maximum Daily Load (TMDL) plans in 

an effort to bring the water quality of the river into compliance with standards. In Oregon, TMDL issues 

for the Klamath River are temperature, ammonia toxicity, dissolved oxygen, pH, and algae 

(chlorophyll). In California, the TMDL issues in the Klamath River are temperature, nutrients, organic 

enrichment, dissolved oxygen, sedimentation, and algal toxins, depending on the specific reach. 

Water-quality models are being used to form the foundation of Oregon’s TMDL program for the 

Klamath River. The models of Link and Klamath Rivers upstream of Keno Dam were originally 

developed by Dr. Michael Deas of Watercourse Engineering, Inc. (Watercourse) for the relicensing of a 

series of PacifiCorp dams (Watercourse Engineering, Inc., 2004). For the Lake Ewauna to Keno Dam 

reach of the Klamath River, Dr. Deas built on a previous model by CH2M-Hill and Dr. Scott Wells of 

Portland State University (CH2M-Hill and Wells, 1995). The Watercourse models then were modified 

for the purpose of TMDL development by Tetra Tech, Inc., under contract to the Oregon Department of 

Environmental Quality (ODEQ), the California North Coast Regional Water Quality Control Board, and 

EPA (Tetra Tech, Inc., 2009a). 
4

Figure 1. Map showing the Klamath River, its major tributaries, and locations of dams on the upper river, 

Oregon and California. (Map from Risley and Rounds, 2006.) 

The development of TMDLs often relies on a historical, reference, or hypothetical condition that 

helps regulators identify an acceptable level of anthropogenic impact under the applicable water-quality 

standards. Because such a reference condition may not exist at present and historical data may not be 

available, models typically are used to estimate the characteristics of the reference condition. For the 

Klamath River TMDL, a “natural conditions” scenario was constructed to simulate water quality in the 

river under a condition without dams and with improved upstream water-quality conditions. The natural 

conditions scenario relied on results from models used previously for the UKL TMDL (Walker, 2001). 

This natural conditions scenario is important because it forms part of the foundation of the TMDL; this 

and related model scenarios typically are used as the basis for regulatory actions or goals, such as 

establishment of limits on point-source nutrient discharges or restoration of a more natural flow, channel 

shape, or riparian condition. 
5

Description of Study Area

This model review includes the two most upstream models used in the Klamath River TMDL: (1) 

Link River from Link River Dam to Lake Ewauna and (2) Lake Ewauna to Keno Dam. The Link River 

Dam to Keno Dam reach is approximately 21 mi long and has an annual average flow of about 1,600 

ft3/s at the streamflow-gaging station 1.4 mi downstream of Keno Dam. The Lake Ewauna to Keno Dam 

reach is a 19.7-mi reservoir-like reach that runs from Link River (the outlet of UKL) to Keno Dam (fig. 

2). That reach has a typical width of 330-1,300 ft, a typical depth of 10-20 ft, and undergoes periodic 

thermal stratification. The Klamath River upstream of Keno Dam is greatly affected by water-quality 

conditions in UKL, where large populations of blue-green algae dominate the water quality of the lake 

in summer (Hoilman and others, 2008). This reach of the river has been classified as having “very poor” 

water quality during summer, as quantified by the Oregon Water Quality Index (Mrazik, 2006). A 

water-quality investigation of this reach was initiated by the Bureau of Reclamation in 2006 in 

partnership with the U.S. Geological Survey (USGS) and Watercourse; selected data from the study are 

available online (Sullivan and others, 2008, 2009; see 

http://or.water.usgs.gov/proj/keno_reach/data.html).
6

Figure 2. Map showing Link River Dam to Keno Dam reach of the Klamath River, Oregon. Sites shown 

are the locations of data-collection stations used by the Bureau of Reclamation and the U.S. Geological 

Survey. 
7

Purpose and Scope

The purpose of this report is to document a review of revised flow and water-quality models 

constructed for the 21-mi Link River Dam to Keno Dam reach of the Klamath River, just downstream of 

UKL in south-central Oregon (fig. 2). The 1-mi Link River reach was simulated with the RMA-2 and 

RMA-11 models (King, 2002; 2003). Output from those models provided upstream boundary conditions 

for a CE-QUAL-W2 model (Cole and Wells, 2002) of the 19.7-mi Lake Ewauna to Keno Dam reach. 

Earlier versions of these models were reviewed previously by USGS (Rounds and Sullivan, 2009), but 

the models have since been revised to correct certain problems and address issues raised during the 

June–August 2009 and December 2009–February 2010 public comment period for the California 

Klamath River TMDL.

The objective of this review was to assess the technical merit of the revised models and determine 

whether any issues remain unaddressed from the 2009 USGS review of the original models. This review 

does not assess the draft Klamath River TMDL, the draft TMDL allocations, or the methodology used 

to determine those allocations. Although the models are being used to help construct TMDL plans for 

the Klamath River, this assessment was of the models, not the draft TMDL.

The Lake Ewauna to Keno Dam CE-QUAL-W2 model of the Klamath River is the primary focus 

of this review for several reasons. The reach simulated by that model includes the great majority of the 

length of the UKL to Keno Dam reach and accounts for most of the travel time. It also is the reach 

where the most important water-quality problems and processes occur—the travel time in Link River is 

short enough that fewer of the critical changes occur there. The models reviewed included several 

scenarios: 

• Current conditions, year 2000

• Current conditions, year 2002

• Natural conditions 

The current (existing) conditions models were developed for calendar years 2000 and 2002. The 

natural conditions model was based on the current conditions year 2000 model, with adjustments to 

remove Keno Dam and point-source inflows, restore the Keno reef (a shallow spot removed when Keno 

Dam was built), and set boundary inputs to median loading conditions from the 1995 UKL TMDL 

model. Models, documentation, and model source code for this review were provided to USGS by Tetra 

Tech and ODEQ. 

Review of Revised Models 

This review is divided into several sections. First, the late-2009 revisions made to the models are 

identified and discussed. Second, a selection of remaining issues from the original model review are 

described along with the reasons these issues remain important and potential opportunities for 

improvement. Lastly, some perspective on the issues raised in this and the original model review is 

provided so that readers might better understand how to interpret the information in this review. 

Model Changes

Several important revisions were made to the Link-to-Keno Klamath River TMDL models to 

address issues that were identified during the June–August 2009 public comment period for the 

California TMDL and to refine the model scenarios. This section of the model review identifies the 

changes that were made and assesses the potential effects of those changes. 
8

Boundary Conditions

• Boundary temperatures. The 2009 USGS model review suggested that it might be wise to 

incorporate some seasonal variation into the distributed tributary, stormwater, and point-source 

accretion temperature inputs, where such variation was not already present (comment A2—Rounds 

and Sullivan, 2009). Seasonal variation has been incorporated into the revised model’s distributed 

tributary temperatures for the year 2000 current conditions scenario; seasonal variation already was 

present in the 2002 distributed tributary. The stormwater and point-source accretion temperature 

inputs, however, remain at a constant 12oC all year. These inputs can be large at certain times of the 

year, and some variation in the temperatures of these sources is likely, so it would be helpful to 

incorporate some amount of seasonal variation into those inputs. Although the stormwater and pointsource accretion temperatures are constant, this setting is likely to have only a minor effect on model 

results in mid-summer because those inputs are small at that time.

Model Source Code

• Version control and documentation. The 2009 USGS model review noted that different versions 

of the model source code were used for the current conditions and natural conditions scenarios 

(comment C3—Rounds and Sullivan, 2009). This inconsistency has been corrected, and all revised 

model scenarios were run with the same model code and program. 

• SC10 error. The Lake Ewauna to Keno Dam CE-QUAL-W2 model source code was revised to 

remove a problem that was identified in the 2009 USGS model review (comment C4—Rounds and 

Sullivan, 2009). In that review, it was discovered that 20 percent of the incoming short-wave solar 

radiation was discarded through a change in the model source code embodied in a variable named 

SC10. Errors in the application of this change to the model source code caused additional 

inconsistencies in the handling of the vertical heat flux associated with light penetration, among other 

problems.

This problem has been corrected in the revised model. The SC10 variable and all FORTRAN 

statements related to this error have been removed from the model source code used for the Lake 

Ewauna to Keno Dam model. The existence of this coding error apparently had been an oversight; 

therefore, its removal was appropriate. 

Although the correction of this error is an important change, the implication of this change on 

simulated water temperatures is difficult to assess because other revisions affecting the heat budget

also were made, such as changes in the value of the baseline light-extinction coefficient. The overall 

performance of the model with respect to water temperature is assessed and discussed in the section 

“Model Results.” 

Model Parameters

• Algae. Both the original and revised models simulate algae and epiphyton in two different states—

“healthy” and “unhealthy”—where the unhealthy fraction is stressed by exposure to low dissolved 

oxygen (DO) concentrations and is modeled with rates of growth, respiration, excretion, and 

mortality that are different from those used for the healthy algae fraction. The 2009 USGS review 

commented on several aspects of the representation of healthy/unhealthy algae in the model

(comment D1—Rounds and Sullivan, 2009). 

The model allows algae in the healthy group to become stressed and the stressed algae to recover 

(Tetra Tech, Inc., 2009a). Healthy algae in the model are converted to an unhealthy state at a user-
9

specified rate that depends on the simulated DO concentration, with a greater rate of conversion at 

lower DO concentrations. Similarly, the unhealthy algae are converted to a healthy state at a different

user-specified rate that increases at higher DO concentrations. The 2009 USGS model review noted 

that the healthy/unhealthy conversion rates and their functional dependence on DO were different for 

phytoplankton as opposed to epiphyton, but that no justification was provided for the different 

conversion rates. In the revised model, the conversion rates and their DO dependence for epiphyton 

were changed to make them identical to those specified for phytoplankton (other than the healthy-tounhealthy cut-off at a DO of 6 mg/L, which is implemented for phytoplankton but not for epiphyton). 

The original review comment was not meant to suggest that these rates and DO dependencies should 

be identical; it is entirely possible that if this sort of stress actually occurs in the river, it might be 

manifested differently for epiphyton as compared to phytoplankton. 

Discussions with the TMDL modeling team indicated that these changes to the 

healthy/unhealthy conversion rates for epiphyton were made for the sake of consistency. The 

healthy/unhealthy hypothesis and the details of its implementation are relatively new and untested, 

with little research or field data to set the values of model parameters other than through model 

calibration. Data on epiphyton were not available for the Lake Ewauna to Keno Dam reach for the 

years modeled, and the effect of epiphyton on overall model results is minimal. Using a consistent set 

of healthy/unhealthy conversion rates for phytoplankton and epiphyton, therefore, seems a 

reasonable choice. If epiphyton play a minimal role in affecting water quality in this reach of the 

Klamath River, which seems likely based on best available information, then these changes to the 

DO/epiphyton relation should have little effect on overall model results. 

• Sediment oxygen demand. The 2009 USGS model review pointed out that the zero-order rate of 

sediment oxygen demand (SOD) used in the original model, 3.0 g/m2

/d, was significantly higher than 

the SOD rate measured in-situ by USGS in this reach of the Klamath River (median = 1.8 g/m2/d at

20°C, Doyle and Lynch, 2005; comment D2—Rounds and Sullivan, 2009). Laboratory 

measurements of SOD rates from cores collected in the Lake Ewauna reach of the Klamath River 

have varied greatly and include relatively moderate rates (0.97-1.96 g/m2/d, Raymond and Eilers, 

2004) as well as relatively high rates (2.68-3.61 g/m2

/d, Eilers and Raymond, 2005). 

In the revised model, the year 2000 current conditions scenario retained a maximum SOD rate of 

3.0 g/m2

/d (SOD=3.0, FSOD=1.0), but the year 2002 current conditions scenario was revised to 

decrease the maximum SOD rate to 2.0 g/m2

/d (SOD=3.0, FSOD=0.667). The natural conditions 

SOD rate remained at 1.42 g/m2/d (SOD=3.0, FSOD=0.473). In addition, the value of the SODK1 

parameter, one of several that specify the temperature dependence of the SOD rate, was decreased for 

all revised models from 0.5 to 0.1, resulting in a greatly decreased SOD rate at temperatures less than 

about 20°C (fig. 3).
10

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34

0.0

0.5

1.0

1.5

2.0

2.5

3.0

SOD Rate (g/m2/d)

original, current conditions 2000/2002

revised, current conditions 2000

revised, current conditions 2002

original, natural conditions

revised, natural conditions

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34

Water Temperature (degrees Celsius)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

SOD Temperature Function Multiplier

original SOD rate multiplier

revised SOD rate multiplier

Lake Ewauna to Keno Dam

Klamath River model

Lake Ewauna to Keno Dam

Klamath River model

Figure 3. Graphs showing dependence of the rate of sediment oxygen demand (SOD) on water 

temperature for the original and revised Lake Ewauna to Keno Dam Klamath River TMDL models. 

Water temperatures in this reach of the Klamath River range from 0 to 26°C during the year. 

Discussions with the TMDL modeling team indicated that the change in the SODK1 parameter 

was done to make the temperature dependence of the SOD rate more consistent with the default 

functionality of the model, where the suggested value is 0.1 (Cole and Wells, 2002). The value used 

in the original version of the model (0.5) apparently was a remnant of calibration testing. Few 

measurements of the SOD rate have been made in the Klamath River at temperatures well below 
11

20°C, so the temperature dependence of this process is largely left to model calibration and 

information gleaned from published literature. The large decrease in the temperature rate multiplier 

for SOD at temperatures less than 20°C should result in higher simulated DO concentrations outside 

of the warm summer period, which is exactly what the model results show. It would be useful to 

perform a sensitivity analysis to determine an optimal temperature dependence for SOD for the 

cooler spring, autumn, and winter seasons. 

The decreased SOD rate for the revised 2002 current conditions scenario was explained as used

to reflect potential interyear variability (California North Coast Regional Water Quality Control 

Board, 2010), but no justification was provided for retaining the relatively high SOD rate of 3.0 

g/m2

/d for the year 2000 current conditions scenario. Measurements and published research suggest 

that SOD rates typically do not decrease by one-third (3.0 to 2.0 g/m2/d) over a 2-year period, but 

tend to be more constant over time in the absence of large changes in environmental conditions 

(Rounds and Doyle, 1997). Variation in the loading of OM from UKL might indeed have an effect 

on the SOD rate just downstream in Lake Ewauna. Measurements of the SOD rate in the Lake 

Ewauna to Keno Dam reach in 2003 (Doyle and Lynch, 2005), however, were similar to rates 

measured in UKL in spring and summer of 1999 (Wood, 2001), indicating that significant year-toyear variation in the SOD rate is unlikely. If the 2002 SOD rate had to be decreased by a factor of 

one-third to achieve an acceptable DO calibration, then perhaps the SOD rate is inadvertently 

compensating for some other poorly represented DO-related process in the model. Through 

additional analyses and model calibration, it should be possible to determine a set of interannually 

consistent DO-related model parameters that achieve a reasonable calibration for both 2000 and 

2002. 

• Parameter value consistency among models. The 2009 USGS model review identified several 

parameters for which inconsistent values were specified for the year 2000 and 2002 current 

conditions scenarios and the natural conditions scenario (comment D3—Rounds and Sullivan, 2009). 

These inconsistencies existed for the nitrification rate (NH4DK), dissolved oxygen half-saturation 

constant (O2LIM), labile dissolved organic matter (DOM) and particulate organic matter (POM) 

decomposition rates (LDOMDK, LPOMDK), and the POM settling rate (POMS). The revised

models have been changed to use consistent values for all these parameters. The only remaining 

inconsistency among the revised model parameters is the maximum SOD rate, as described in the 

previous comment. 

Documentation was not provided for the (now consistent) values selected for NH4DK, O2LIM, 

LDOMDK, LPOMDK, and POMS in the revised models. All these parameters are relatively 

important to the simulation of ammonia, DO, and OM; therefore, it seems reasonable that a set of 

sensitivity analyses or model calibration exercises should have been conducted and documented to 

determine the best set of final values for these parameters.

The change in the value of O2LIM (from 2.0 to 0.1 mg/L) for the 2002 current conditions model 

has important ramifications for the simulation of many processes in the model, including DO, 

ammonia, and nitrate. A multiplier based on O2LIM is used in the model to determine how oxygendependent rate processes vary as a function of the DO concentration. Reactions that consume 

oxygen, for example, become inactive under low-DO conditions because the O2LIM-dependent rate 

multiplier approaches zero as the DO concentration approaches zero (fig. 4). The rate multiplier in 

figure 4 can be viewed as the fractional value of a temperature-adjusted reaction rate. At a DO 

concentration of 2.0 mg/L, for example, the SOD rate would be one-half of its temperature-adjusted 

value if O2LIM were set to 2.0 mg/L, but would be about 95 percent of its temperature-adjusted 
12

value if O2LIM were set to 0.1 mg/L. The use of an O2LIM of 2.0 mg/L in the original 2002 current 

conditions scenario was an oversight; a value of 0.1 mg/L is far more reasonable and is the 

recommended value from the CE-QUAL-W2 user manual (Cole and Wells, 2002). The result, 

however, is that many oxygen-dependent reaction rates in the 2002 current conditions scenario are 

noticeably higher in the revised model. This change results in a higher effective SOD rate, which 

might explain the apparent need to decrease the maximum SOD rate from 3.0 to 2.0 g/m2

/d for 2002. 

A higher ammonia nitrification rate, which results from the decreased O2LIM value, also explains 

the increase in simulated nitrate concentrations in mid-summer for the 2002 scenario relative to the 

previous version of the model. Ensuring a consistent O2LIM value of 0.1 mg/L for all scenarios is an 

important model revision and has a large effect on many modeled rates. Additional analyses to 

document these effects and assess the potential need for additional model calibration seem warranted. 

0 1 2 3 4 5 6 7 8 9 10

Dissolved Oxygen Concentration (mg/L)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Rate Multiplier

O2LIM = 2.0

O2LIM = 0.1

Figure 4. Graph showing dependence of the oxygen rate multiplier on the dissolved oxygen 

concentration for the Lake Ewauna to Keno Dam Klamath River TMDL model. A value of 0.1 mg/L is 

used for the revised models and was used for the original models except for the 2002 current 

conditions scenario, which used a value of 2.0 mg/L. 

• Light extinction. The baseline light-extinction coefficient for water was decreased from 0.60/m in 

the original Lake Ewauna to Keno Dam model to 0.45/m in the revised model. This revision was 

done to address a consistency issue identified in the original Klamath River TMDL models, in which 

this baseline extinction coefficient was given different values in the several reservoir models 

(comment Db—Rounds and Sullivan, 2009). A value of 0.45/m for the baseline light-extinction 

coefficient is within the range of acceptable values for this parameter (Cole and Wells, 2002). A 

smaller baseline light-extinction coefficient allows more of the short-wave light energy to penetrate 

deeper into the water column, thus altering the temperature distribution in the epilimnion and the 

depth of the thermocline at times. 
13

Model Results

• Error statistics. The 2009 USGS model review recommended that goodness-of-fit statistics be 

reported because such statistics can be useful as one means of assessing model performance

(comment E2—Rounds and Sullivan, 2009). The documentation for the revised model now includes 

goodness-of-fit statistics in addition to graphical comparisons of modeled and measured values 

(Tetra Tech, Inc., 2009a). 

The mean error statistics in the revised model documentation appear to have been computed as 

measured minus modeled, although this is not stated in the documentation (Tetra Tech, Inc., 2009a, 

appendix E). This convention is the reverse of the typical method; it is more common to compute the 

mean error as modeled minus measured so that the sign of the result gives an indication of the mean 

bias of the model. Therefore, when a mean error of 0.15°C is reported for the revised year 2000 

current conditions scenario at Miller Island, it means that the model has a slight negative bias on the 

order of 0.15°C (see Tetra Tech, Inc., 2009a, appendix E). It would be more intuitive for the reader if 

the signs of the mean errors were reversed; regardless, the convention (modeled minus measured, or 

measured minus modeled) should be stated in the documentation. 

In order to examine changes in model performance, goodness-of-fit statistics for water 

temperature and DO were calculated as part of this review for both the original and revised models 

for May 1 through October 31 at two sites (table 1). Results show a slight improvement in the mean 

absolute error for the simulation of water temperature, but a slight degradation in the mean absolute 

error for the simulation of DO at Keno for 2000 and 2002. The mean absolute error can be thought of 

as the magnitude of typical model uncertainty for any data point.

Table 1. Goodness-of-fit statistics for the original and revised Lake Ewauna to Keno Dam models of the 

Klamath River, Oregon, using results from May 1 through October 31.

[Model results were compared to measurements taken from 1 meter below the river surface. Site locations are shown in

figure 2. Mean error is defined as modeled minus measured. Abbreviations: °C = degrees Celsius; mg/L = milligrams 

per liter] 

Parameter Site Year

Original model Revised model

Mean 

Error

Mean 

Absolute 

Error

Root 

Mean 

Square 

Error

Mean 

Error

Mean 

Absolute 

Error

Root 

Mean 

Square 

Error

Water

temperature

(°C)

Miller 

Island

2000 0.1 1.1 1.5 -0.2 1.1 1.5

2002 0.4 1.1 1.5 0.2 0.9 1.4

Keno 2000 0.4 0.8 1.0 0.2 0.7 0.9

2002 0.8 0.9 1.1 -0.6 0.8 1.0

Dissolved

oxygen

(mg/L)

Miller 

Island

2000 -0.5 1.9 2.5 -0.1 1.9 2.6

2002 0.4 2.1 2.7 -0.1 2.2 2.9

Keno 2000 -0.7 1.6 2.1 -0.1 1.8 2.4

2002 0.0 2.1 2.7 -0.5 2.4 3.1
14

It is not entirely straightforward to interpret these goodness-of-fit statistics in light of the 

revisions made to the models. For example, several important changes were made to the heat budget 

formulation. The original model had a higher baseline light extinction coefficient, which would tend 

to convert short-wave solar energy into heat closer to the water surface. In contrast, the original 

model also had an error that discarded 20 percent of the incoming short-wave solar energy, which 

would tend to keep the river surface cooler. The result is that the revised model produces 1-m 

temperatures that are slightly cooler than those of the original model—thus the slightly lower mean 

errors for water temperature. The mean error is a measure of overall model bias—positive if model 

predictions tend to be greater than the measured data. The original mean errors show a slight positive 

bias, indicating that the river was simulated to be slightly too warm near the surface—these 

goodness-of-fit statistics were computed from measurements and model simulations at 1-m below the 

surface. 

The goodness-of-fit statistics for DO also are difficult to interpret. Given the decreased SOD 

rates in the revised model at lower temperatures, one might expect simulated DO concentrations in

the revised model to be larger outside of the warm summer period, if all other influences were 

similar. The mean errors for DO indicate that the revised model produces slightly higher DO 

concentrations in 2000 than the original model, but lower concentrations overall in 2002. Simulated 

DO concentrations are the result of many influences, however, and many processes affecting DO 

were changed in the revised models.

Natural Conditions Scenario

• Keno reef flows. The original natural conditions scenario specified an incorrect value (1,244.82 m) 

for the spillway elevation (ESP) of the Keno reef. Derivation of the spillway equation showed that 

the reef elevation should have been 1,244.5 m (comment F2—Rounds and Sullivan, 2009). This 

discrepancy apparently was due to the use of a feet-to-meters conversion factor with an insufficient 

number of significant digits. The revised natural conditions scenario uses the correct spillway 

elevation, 1,244.5 m. This change should allow the model to more accurately simulate stage, 

velocity, and travel time in the Lake Ewauna to Keno reach.

• Natural conditions initial concentrations. In the original natural conditions scenario, the initial 

water-quality concentrations were set higher than the initial boundary inputs, closer to concentrations 

in the current conditions scenarios (comment Fa—Rounds and Sullivan, 2009). This was not a 

particularly important concern because the initial conditions are rapidly replaced by effects of 

incoming boundary conditions in these model scenarios. Regardless, the revised model was adjusted 

so that the initial water-quality concentrations were more similar to the boundary conditions of the 

natural conditions scenario. 

• Natural conditions inflow TDS. Boundary condition concentrations for total dissolved solids 

(TDS) for the Lost River Diversion Channel and the Klamath Straits Drain were set to zero in the 

original natural conditions scenario. This was identified as an unrealistic condition in the 2009 USGS 

model review (comment F3—Rounds and Sullivan, 2009). In the revised natural conditions scenario, 

the TDS boundary condition concentration for these inflows was changed to 100 mg/L, which is 

more consistent with the expected range of TDS concentrations for these inflows. TDS 

concentrations in the model have a minor effect on water density and pH computations; this change 

should not greatly affect model predictions of water temperature, nutrients, DO, algae, or OM. 
15

• Natural conditions ISS. Boundary condition concentrations for inorganic suspended solids (ISS) 

were decreased in the revised natural conditions scenario (3 mg/L) compared to the original natural 

conditions scenario (15 mg/L). The implications of this change are not readily apparent, other than a 

reduced light extinction where the ISS remain suspended. Effects on more important water-quality 

constituents such as temperature, nutrients, DO, algae, and OM are likely to be minimal or 

inconsequential. 

• Natural conditions OM, N, and P. For the natural conditions scenario, concentrations of organic 

matter (OM), nitrogen (N), phosphorus (P), and other water-quality constituents for inflows from 

Link River, Lost River Diversion Channel, and Klamath Straits Drain were derived from results of 

the UKL TMDL model. The 2009 USGS model review suggested that the concentrations of DOM, 

N, and P in those inflows were lower than one might expect based on the historically eutrophic 

conditions in UKL and its surrounding wetlands (comments F4 and F5—Rounds and Sullivan, 

2009). 

In the revised natural conditions scenario, concentrations of most of the dissolved inflow 

constituents, such as dissolved P, ammonia, nitrate, DO, dissolved inorganic carbon, and alkalinity 

were unchanged from the original natural conditions scenario. Concentrations of algae, labile 

particulate organic matter (LPOM), and labile dissolved organic matter (LDOM), however, all of 

which contain N and P, were changed. These changes were done to make the TP inputs to the revised 

model consistent with results from the UKL TMDL model. These changes affect the total incoming 

flux of nutrients and the simulated downstream concentrations of DO, algae, OM, and nutrients. 

The general seasonal pattern of inputs for algae was retained, but higher concentrations were 

specified in the revised model (range: 0.9–4.0 mg/L) than in the original model (range: 0.5–2.5 

mg/L) (fig. 5). In the original model, incoming algae concentrations were calculated from 

chlorophyll results of the UKL TMDL model using an algae:chlorophyll a mass ratio of 67 (Tetra 

Tech, Inc., written commun., 2009). For the revised model, incoming algae concentrations were

derived from algal P results of the UKL TMDL model using an algal biomass:P mass ratio of 180 

(Tetra Tech, Inc., 2009b). 

0

1

2

3

4

5

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

2000

Algal biomass (mg/L)

original model

revised model

Figure 5. Graph showing upstream boundary algae concentrations in the original and revised natural 

conditions models. 
16

With respect to OM boundary inputs in the natural conditions scenario, the sum of LDOM and 

LPOM was decreased in the revised model (range: 0.1–3.0 mg/L) compared to that in the original 

model (range: 2.1–3.8 mg/L) (fig. 6). The refractory OM inputs (RDOM and RPOM) were set to zero 

in both the original and revised models. Documentation for the original (Tetra Tech, Inc., written 

commun., 2009) and revised (Tetra Tech, Inc., 2009b) models both state that these OM 

concentrations were derived from UKL TMDL model results for organic P, using an OM:OP mass 

ratio of 180. Discussions with the TMDL modeling team indicated that part of this change in OM 

loading was to correct a mistake in the original boundary conditions, the derivation of which may 

have double-counted a portion of the P load. The result, however, is that the seasonal pattern in OM 

was changed greatly, with little OM present in mid-summer at the same time that algal biomass 

concentrations are highest. Patterns in the data from recent years do not show low concentrations of 

OM in Link River in mid-summer when algal biomass concentrations are highest (Sullivan and 

others, 2008, 2009), and it seems strange that the seasonal pattern in non-living OM should be 

opposite to the pattern in the algae. 

0

1

2

3

4

5

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

2000

Labile organic matter (mg/L)

original model

revised model

Figure 6. Graph showing upstream boundary labile organic matter concentrations (sum of LDOM 

and LPOM) in the original and revised natural conditions models. 

Total OM concentrations in the revised model are composed of both particulate (LPOM, range: 

0–0.3 mg/L) and dissolved (LDOM, range: 0.1–2.7 mg/L) forms, with roughly 90 percent of the OM 

in the dissolved fraction (fig. 7), based on information from Thurman (1985). The 2009 USGS model 

review noted that inflow DOM concentrations for the original natural conditions scenario were less 

than 0.8 mg/L (0.4 mg/L as dissolved organic carbon [DOC], using a DOC:DOM mass ratio of 0.45), 

and that those concentrations were less than what one might expect in a system with extensive 

surrounding wetlands (comment F4—Rounds and Sullivan, 2009). In the revised model, the annual 

average inflow DOM concentration was increased in winter, spring, and autumn, up to a maximum 

of 2.7 mg/L (1.2 mg/L as DOC). Increasing the natural conditions inflow DOM concentration is an 

improvement in simulating the historical Klamath River, but the maximum model inflow 

concentration of 1.2 mg/L as DOC is still well below the range of values cited by Thurman (1985) 

for rivers and lakes (2–10 mg/L as DOC) and wetlands (10–60 mg/L as DOC). 
17

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

2000

OM concentration (mg/L)

original LPOM

revised LPOM

original LDOM

revised LDOM

Figure 7. Graph showing upstream boundary organic matter concentrations (LDOM and LPOM) in 

the original and revised natural conditions scenarios. 

The revised OM concentrations in the natural conditions scenario have a different seasonal 

pattern from the original natural conditions scenario, and a pattern that does not seem consistent with 

expected patterns. The revised POM and DOM concentrations are low in summer, both with 

concentrations less than 0.1 mg/L. As mentioned previously, these concentrations are lower than

those that might be expected in a system such as UKL. Considering all types of OM inputs (algae 

plus LDOM and LPOM), the revised natural conditions scenario has lower input concentrations 

compared to the original natural conditions scenario (fig. 8), which should result in higher DO 

concentrations downstream because of decreased decomposition of OM. 

0

1

2

3

4

5

6

7

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

2000

Algae plus OM (mg/L)

original model

revised model

Figure 8. Graph showing sum of organic matter and algae boundary input concentrations in the 

original and revised natural conditions models.
18

By decreasing OM inputs and keeping dissolved nutrient fluxes the same, the overall boundary 

fluxes of N, P, and carbon were decreased in the revised natural conditions model. Total P 

concentrations are easily calculated as the sum of dissolved orthophosphate and P in algae and OM, 

where the latter two components were computed from upstream boundary algae, LDOM, and LPOM 

concentrations and the P:algae and P:OM mass ratios specified in the model. The TP concentrations 

in the boundary inflows of the revised model are lower than those in the original model (fig. 9).

0.00

0.01

0.02

0.03

0.04

0.05

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

2000

Total phosphorus (mg/L) 

original model

revised model

Figure 9. Graph showing total phosphorus boundary inflow concentrations in the original and 

revised natural conditions models.

Largely because of the decreased boundary input concentrations, simulated TP concentrations at 

the downstream end of the model at Keno reef are lower in the revised natural conditions scenario 

than in the original natural conditions scenario (table 2). Similarly, lower inputs of OM and higher 

inputs of algae, along with instream processes within the Link-to-Keno reach, combine to produce 

differences in dissolved nutrient concentrations at the downstream outflow. Dissolved inorganic P 

concentrations, for example, did not change in the upstream inflow but are lower at Keno reef in the 

revised natural conditions scenario compared to the original natural conditions scenario (fig. 10).
19

Table 2. Annual and summer average total phosphorus concentrations in the major inflows and the 

downstream outflow of the original and revised natural conditions models.

[Abbreviation: mg/L = milligrams per liter] 

Original natural conditions 

model

Revised natural conditions 

model 

Time period Total P (mg/L) Total P (mg/L)

Major Inflows

(Link River, Lost River Diversion Channel, Klamath Straits Drain)

annual average (Jan-Dec) 0.028 0.023

summer average (June-Aug) 0.037 0.026

Outflow

(at Keno reef)

annual average (Jan-Dec) 0.024 0.016

summer average (June-Aug) 0.028 0.012

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

2000

Dissolved PO4 (mg/L as P)

original model

revised model

Figure 10. Graph showing dissolved inorganic phosphorus concentrations at the downstream 

outflow (Keno reef) in the original and revised natural conditions models.

The natural conditions inflow concentrations of TP (table 2) were based on UKL TMDL model 

results for 1995 (Tetra Tech, Inc., 2009b) that simulated a 40-percent reduction in P loading (Walker, 

2001). Other years, 1992–98, also were simulated for the UKL TMDL, but results for 1995 were

selected for the Klamath River TMDL model inputs (Tetra Tech, Inc., 2009b). The rationale for that 

decision is explained in the draft TMDL (Oregon Department of Environmental Quality, 2010). 

Phosphorus concentrations from the 1995 UKL TMDL model along with ratios such as TN:TP and 

OM:OP were used to derive concentrations of other constituents such as N species and OM for the 

Klamath River upstream boundary. 
20

Upper Klamath Lake is commonly accepted to be historically eutrophic (Eilers and others, 2003; 

Bradbury and others, 2004). Total P concentrations commonly are used to classify the trophic status 

of a lake, and many classification criteria are based on results from an Organization for Economic 

Co-Operation and Development (OECD) study of more than 200 lakes (OECD, 1982; Wetzel, 1983, 

2001; Reynolds, 2006). The annual average TP concentration from the 1995 UKL TMDL model 

(0.023 mg/L) would be classified as mesotrophic using the OECD fixed-boundary classification 

criteria (mesotrophic: 0.010–0.035 mg/L; eutrophic 0.035–0.100 mg/L), but near the 

mesotrophic/eutrophic boundary according to a classification scheme by Welch and Jacoby (2004). 

Using an alternate OECD classification scheme with overlapping categories, the annual average TP 

concentrations from the UKL TMDL model indicate a lake in the mesotrophic to eutrophic range

(fig. 11). The trophic classification, however, is less important than the loads of OM, algae, and 

nutrients predicted by the UKL TMDL model and used as upstream boundary conditions for the 

Klamath River TMDL models. 

Eutrophic Mesotrophic

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

Total phosphorus, 

mg/L

UKL TMDL model, 1992-1998

UKL TMDL model, 1995

mean P for category

1 std. dev.

2 std. dev.

Eutrophic Mesotrophic

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

Total phosphorus, 

mg/L

UKL TMDL model, 1992-1998

UKL TMDL model, 1995

mean P for category

1 std. dev.

2 std. dev.

Figure 11. Graphs showing total phosphorus mean and 1- and 2-standard deviations for the 

eutrophic and mesotrophic OECD lake classifications (Organization for Economic Co-Operation and 

Development, 1982). The annual average total phosphorus outflow concentration from the 1995

Upper Klamath Lake (UKL) TMDL model’s 40-percent load reduction scenario, used to develop the 

boundary condition for the Klamath River TMDL model, is plotted along with values from the model 

for 1992–98 (Walker, 2001).

Total P and OM concentrations used as the upstream boundary conditions for the natural 

conditions scenario seem too low, relative to what might be expected from a lake system with 

extensive surrounding wetland systems, peat soils, and a regional groundwater system containing 
21

high concentrations of P. It is beyond the scope of this review, however, to evaluate the accuracy, 

uncertainties, strengths, or limitations of the UKL TMDL model from which these boundary 

conditions were derived, or to develop an alternative estimate. The UKL TMDL model was

identified by ODEQ as the largest source of uncertainty to the natural conditions model scenario—

larger than uncertainties inherent to the river model and its various algorithms and parameters 

(Oregon Department of Environmental Quality, 2010). Given the low TP concentrations and the 

strange seasonal pattern in OM that result, we concur that the upstream boundary conditions are a 

large source of uncertainty to the natural conditions scenario. To address this increased uncertainty, 

additional model scenarios could be run to assess the effects of different upstream boundary 

conditions for the natural conditions scenario, thus providing useful insights for downstream water 

quality and for assessing other implications, such as the effect on TMDL allocations. In addition, 

future efforts to create an updated model of algal growth and nutrient cycling in UKL, in light of the 

data collection and research that has been performed in the last decade, would be beneficial to

downstream water-quality planning and management efforts for the Klamath River. 

Remaining Issues

Although many changes were made to the Link-to-Keno Klamath River TMDL models, some 

important issues identified in the 2009 USGS model review by Rounds and Sullivan (2009) remain. 

This report does not include new discussions of all remaining issues that were identified in the 2009 

model review, such as the number of years simulated, any concerns about the model bathymetry, or the 

ammonia inputs in the year 2000 current conditions scenario. Several remaining issues are sufficiently 

important or noteworthy, however, to be included in this review of the revised models, and are the 

subject of this section of the report. 

Boundary Conditions

• Organic matter. The current conditions models still specify an upstream boundary condition for 

OM from UKL such that 20 percent was assumed to be dissolved and 80 percent was assumed to be 

particulate (comment A5—Rounds and Sullivan, 2009). Both forms were given identical 

decomposition rates, but a substantial fraction of the particulate form will settle out downstream, 

leaving a smaller load of OM to be transported through the remainder of the model reach. 

Recent data indicate that a large fraction of the incoming OM load (other than live algae) is in 

the dissolved form (Sullivan and others, 2008, 2009). Although those data were not collected during 

the years of interest (2000 and 2002), they do provide useful information that could be used to revise 

the assumptions used to partition the model OM inputs into dissolved and particulate fractions. The 

draft TMDL document states that this sort of information could be used to refine the model and 

reduce uncertainties in the upstream boundary conditions in the future (Oregon Department of 

Environmental Quality, 2010). Organic matter is a large and important input to the Klamath River 

from UKL, and is a critical constituent affecting DO concentrations, nutrient loads, and light 

extinction. 

• TDS inputs. The TDS boundary input for the Klamath Straits Drain for the current conditions 

scenarios is still set to a constant 0 mg/L (comment A3—Rounds and Sullivan, 2009). This is not a 

particularly important concern, as this problem would have only a minor effect on water density and 

pH computations. Still, it seems inconsistent that the TDS boundary conditions for this tributary were 

revised for the natural conditions scenario (increased from 0 to 100 mg/L) but not for the current 

conditions scenarios. 
22

Model Source Code

• Code version. Version 3.12 of CE-QUAL-W2, originally dated August 15, 2003, was used as the 

basis for the Lake Ewauna to Keno Dam model of the Klamath River for this TMDL effort. Tetra 

Tech modified portions of the code to add new capabilities and customize outputs. A detailed 

examination of the model source code was included in the 2009 USGS model review (section C—

Rounds and Sullivan, 2009). 

It is important to note, for the benefit of future model users, that errors are present in this version 

of the model source code, which was originally developed by the Corps of Engineers and Portland 

State University (Cole and Wells, 2002). Most, if not all, of the errors identified in the 2009 USGS 

model review do not affect the model results as long as the model user does not choose to use certain 

model options that currently are unused. Should the model be altered for another purpose, however, a 

user might unknowingly select and attempt to use a piece of the model that is broken. To that end, 

here is an abbreviated list of “knobs that should not be turned” in the model: 

• Do not use, or do not increase the amount of, P sorption (PARTP, currently 0.001). 

• Do not turn on ice calculations without correcting problems associated with the WINTER 

variable.

• Do not increase the sedimentary OM decomposition rate (SEDK or SDK) from its current value 

of zero, as parts of the SEDIMENTS subroutine are broken. 

• The flux output computations currently are turned off and should not be trusted if they were to 

be turned on, as that part of the model code is broken. This does not affect the model 

simulations—just one means of extracting information from the model.

The presence of these errors in the code, as well as the fact that it is easy to make mistakes in 

setting up and using these models, means that if these models are to be modified or used for other 

purposes, it would be prudent to have the altered models run by, or reviewed by, modelers that have 

experience with these tools. 

Model Parameters

• Algae. The revised model retained the depiction of one type of algae that is split into two groups—a 

“healthy” group and an “unhealthy” group that is stressed as a result of exposure to low DO 

conditions. The only revision to this part of the model was that the user-specified rates at which 

members of the healthy group become unhealthy, and vice versa, and the dependence of those rates 

on the DO concentration, were changed for epiphyton so that the rates and functions would be 

identical to those used for phytoplankton (discussed previously in section “Model Changes”). The 

rest of the healthy/unhealthy depiction of the algal communities remains the same as in the original 

models. 

This healthy/unhealthy representation of the algal community continues to raise questions and 

concerns relative to (a) its validity with regard to instream processes, (b) the number of calibration 

parameters, and (c) the values selected for some of the required model parameters (comment D1—

Rounds and Sullivan, 2009). These issues do not mean that the model did not or cannot reproduce 

some of the more important patterns in the data, nor do these issues mean that the model cannot be 

used for certain purposes. From the perspective of scientists trying to understand the details of 

instream processes that occur in the Klamath River and simulate those processes with models, 

however, this healthy/unhealthy representation is both intriguing and troubling. Although it is 

interesting to postulate that the algal community might respond differently when exposed to low 
23

concentrations of DO, no published research is available to indicate that algae are stressed by DO 

concentrations in the range of 3–6 mg/L. Some variation in the response of the algal community 

could be modeled by breaking the algae into several groups corresponding to the different types of 

algae present in the river (blue-greens, diatoms, etc.), but algal speciation data were not available for 

2000 and 2002. The growth, respiration, excretion, and mortality rates of the modeled algae already 

are dependent on water temperature, and the growth rate depends on factors such as light intensity 

and the concentrations of N and P. It is an interesting, but still unproven, hypothesis that the algae 

change their response as a function of the DO concentration. To determine whether that is actually

happening, detailed research to quantify that response and incorporate it into models would be 

needed. 

Whether it is physiologically accurate to model the current condition of the algal community in 

the Klamath River with the postulated healthy/unhealthy approach is subject to debate and future 

research. In the meantime, however, several issues could be addressed to make the approach more 

reasonable. For example, the unhealthy algae were simulated with growth and respiration rates of 

zero, even during oxic conditions. This does not seem plausible; small nonzero rates would be more 

reasonable. In addition, the rate of conversion of phytoplankton (but not epiphyton) from healthy to 

unhealthy still has a cut-off at 6 mg/L that is set in the model source code (fig. 12). The reason for 

this cut-off, as well as its absence for epiphyton, has not been adequately explained. Furthermore, the 

DO dependence of the healthy to unhealthy conversion rate allows for a significant health-status 

conversion at relatively high DO concentrations. No published research was found during the course 

of this review to suggest that some fraction of the algae community should become stressed at a DO 

concentration of 5 or 4 mg/L. The healthy/unhealthy hypothesis might be more reasonable if the 

conversion thresholds were set at lower DO concentrations.

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Dissolved Oxygen Concentration (mg/L)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

Conversion Rate (day-1)

Healthy to Unhealthy: K 1 = 1.2 * (1.5 / (1.5 + [DO])) -- for epiphyton

Healthy to Unhealthy: K 1 = 1.2 * (1.5 / (1.5 + [DO])) -- for phytoplankton

Unhealthy to Healthy: K 2 = 0.15 * ([DO] / (3.0 + [DO]))

Figure 12. Graph showing simulated conversion rates from “healthy” to “unhealthy” algae (K1) and 

back (K2) for phytoplankton and epiphyton in the Klamath River TMDL model for Lake Ewauna to 

Keno Dam, Oregon. The K1 rate for phytoplankton is zero when the dissolved oxygen concentration 

is greater than 6 mg/L.
24

• Organic matter decomposition rates. Most of the OM in the Lake Ewauna to Keno Dam model is 

in the form of either labile DOM or labile POM, and the specified decomposition rates for those 

groups were identical (comment D3—Rounds and Sullivan, 2009). Recent research indicates that 

DOM in the Klamath River probably is more refractory (decomposes more slowly) than POM 

(Sullivan and others, 2010). The TMDL modeling effort may not have had sufficient data to add this 

level of complexity, but future modeling efforts definitely should make use of this recent research. 

This need is recognized in the draft TMDL document (Oregon Department of Environmental 

Quality, 2010). 

Model Results

• Nitrate calibration. The 2009 USGS review noted that nitrate concentrations from the year 2000 

current conditions scenario at Keno had an unexpected seasonal pattern relative to other years, with 

modeled summer concentrations approaching 1 mg/L (comment E3—Rounds and Sullivan, 2009). In 

contrast, the long-term ODEQ dataset from that site, including year 2000, shows consistently low 

summer nitrate concentrations. The year 2000 dataset used for model calibration did include nitrate 

data at Keno approaching 2 mg/L in summer, but those data may not have been reliable—the revised 

model documentation notes that those nitrate data are suspected to be incorrect (Tetra Tech, Inc., 

2009a). The available nitrate data at Keno during 2002 showed low concentrations during summer, 

more similar to the historical datasets.

The revised model still predicts relatively high mid-summer nitrate concentrations at Keno in 

2000 and 2002 (fig. 13). The increased nitrate concentrations in July–September 2002 for the revised 

model as compared to the original model are a direct result of the change in O2LIM from 2.0 to 0.1 

mg/L, which caused a large increase in the rate of nitrification (conversion of ammonia to nitrate). 

An important fraction of the ammonia in the river during July–September 2002 probably was being 

released from sediments as a result of low DO conditions—the model was set up to release nutrients 

(ammonia and dissolved P) from the sediments as a fraction of the zero-order SOD rate when DO 

concentrations in the overlying water are near zero. If modeled nitrate concentrations are too high 

compared to measured concentrations, one or more processes likely are not being accurately 

modeled. The release rate of ammonia from sediments under low DO conditions may be too high, the 

rate of denitrification may be too low, and/or the rate of N uptake by algae may be too low. The 

model includes two mechanisms to remove nitrate through denitrification, and only one of those 

mechanisms was being used in the model. Future model refinements might benefit from a reexamination and adjustment of these processes in the model. 
25

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Nitrate (mg/L as N)

ODEQ. 1981-2007

USGS. 2007-2008

original model - 2000

revised model - 2000

TetraTech calib, 2000

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Nitrate (mg/L as N)

ODEQ. 1981-2007

USGS. 2007-2008

original model - 2002

revised model - 2002

TetraTech calib, 2002

Figure 13. Graphs showing measured and simulated nitrate concentrations in the Klamath River at 

Keno (Highway 66). ODEQ data were collected approximately six times per year, and only data 

reported in units of mg/L as nitrogen are plotted. USGS data were collected weekly from April to 

November during 2007 and 2008. Measured concentrations labeled “Tetra Tech calib” were used for 

model calibration.

Note that the revised nitrate model results at Keno (Highway 66) for 2002 in the previous figure 

were extracted from the model results, but are not the same as results included in the revised model 

documentation (Tetra Tech, Inc., 2009a, fig. E-58, p. E-25). Apparently, that figure in the model 

documentation, as well as a few others (fig. E-55 on p. E-24, for one), still show results from the 

original model rather than from the revised model.
26

Natural Conditions Scenario

• Natural conditions boundary flows. Withdrawals through the North and Ady Canals were retained 

in the natural conditions scenario, but at slightly different flow rates compared to the year 2000 

conditions on which the scenario was based. The 2009 USGS model review questioned why these 

withdrawal rates were different from those in the current conditions scenario (comment F1—Rounds 

and Sullivan, 2009). The boundary inflows for the natural conditions scenario from Link River, the 

Lost River Diversion Channel, and the Klamath Straits Drain all were identical to the flows used in 

the year 2000 current conditions scenario, but the flows for the North and Ady Canal withdrawals 

were not (fig. 14). This point is not particularly important relative to other choices made for the 

natural conditions scenario, and the discrepancy might be unintentional; regardless, better 

documentation would be useful. 

0

2

4

6

8

10

12

14

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Withdrawal Rate (m3/s)

North Canal, revised current conditions 2000

North Canal, revised natural conditions

0

2

4

6

8

10

12

14

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan

Withdrawal Rate (m3/s)

Ady Canal, revised current conditions 2000

Ady Canal, revised natural conditions

Figure 14. Graphs showing simulated withdrawal rates for the North and Ady Canals for the natural 

conditions scenario and the year 2000 current conditions scenario.
27

Perspectives on Water-Quality Modeling

Water-quality models are simplified representations of real-world systems that are used to provide 

insights and help answer questions related to the management, regulation, or inner workings of those 

systems. For every question asked, a certain amount of uncertainty can be tolerated in the answer. 

Uncertainty is inherent in all model predictions, and an evaluation of that uncertainty is an important 

step in the modeling process. Simple questions may require only simple models. For more detailed and 

demanding questions, the acceptable level of uncertainty may decrease, often compelling the use or 

construction of more accurate, and often more complex, models. Increasing the capability and utility of 

a model, and decreasing its predictive uncertainty begins with ensuring that (a) the model includes 

algorithms describing the most important physical, chemical, and biological processes occurring in the 

waterbody of interest and (b) those mathematical algorithms are as accurate and robust as possible (or 

necessary). These assurances are particularly important when studying the details of instream processes 

or asking questions that are likely to include an extrapolation to conditions that are at or beyond the 

limits of model calibration. 

Uncertainty in model predictions derives from many sources, such as incomplete or inaccurate or 

overly simplistic model algorithms, unrealistic or otherwise incorrect values for model parameters, and 

measurement or other errors in boundary conditions that propagate through the model, among others. 

Quantifying model uncertainty becomes increasingly difficult as the number of model parameters 

increases and the time required to run the model increases. A series of simulations demonstrating the 

sensitivity of model predictions to a few model parameters or selected boundary conditions is useful, but 

a full quantification of potential uncertainty for a model with hundreds of input parameters, even if only 

a handful are particularly important, may be impractical. Because model uncertainty is so difficult to 

quantify for complex models, an assessment of model algorithms, model parameter values, and 

boundary conditions often is the best means of assessing predictive uncertainty. For these reasons, this 

model review focused on the details of model algorithms, the values of model parameters, and the 

choice or derivation of boundary conditions. Any application of the model then must evaluate the level 

of acceptable uncertainty in light of the likely model error and other sources of uncertainty.

The goals and perspectives of the USGS reviewers might be different from those who developed 

and used the model for the Klamath River TMDL. Insights and quantitative assessments required from 

the models by the TMDL team have an associated tolerance for uncertainty, just as they would for any 

other purpose. If the perceived level of uncertainty was sufficiently high, then the Clean Water Act 

requires TMDLs to account for that uncertainty by choosing options that were more protective of 

aquatic life through a margin of safety. The draft TMDL document recognizes many sources of 

uncertainty, but the greatest source of uncertainty was attributed not to the models but to the upstream 

boundary conditions, either because of insufficient data for the current conditions scenarios, or 

uncertainties derived from the UKL TMDL model for the natural conditions scenario (Oregon 

Department of Environmental Quality, 2010). Although the model results for the TMDL may have been 

primarily driven by the boundary conditions, the details of the model remain important. First, the model 

processes those boundary conditions, simulating changes in water quality as water traverses the system. 

Those changes can be simulated accurately only if the model is well calibrated and its algorithms are 

sufficiently robust to handle some level of extrapolation. Second, the TMDL models could be used for 

other purposes; if so, the model must represent the most critical instream processes as accurately as 

possible, and all known weaknesses and uncertainties must be well documented. For both of these 

reasons, this review focused on some of the finer details of the Klamath River models, despite the fact 

that some uses of the models might be less reliant on the model parameter values and algorithms and 

more reliant on the choice of upstream boundary conditions. 
28

Acknowledgments

The authors thank Jon Hicks, Jason Cameron, and Rick Carlson of the Bureau of Reclamation for 

helpful discussions and feedback on the report. For providing the models, source code, and 

documentation, and for participating in useful discussions pertaining to this review, the authors thank 

Dan Turner and Steve Kirk of the Oregon Department of Environmental Quality; Mark Filippini, Ben 

Cope, and Sue Keydel of the U.S. Environmental Protection Agency; Clayton Creager of the California 

North Coast Regional Water Quality Control Board; and Andrew Parker and Rui Zou of Tetra Tech, 

Inc. Acknowledgment of any of these participants in discussions related to this review does not imply

their agreement with the conclusions stated by USGS in this review.

References Cited

Bradbury, J.P., Colman, S.M., and Reynolds, R.L., 2004, The history of recent limnological changes 

and human impact on Upper Klamath Lake, Oregon: Journal of Paleolimnology, no. 31, p. 151–165. 

California North Coast Regional Water Quality Control Board, 2010, Appendix 10—Public comments 

and responses on the staff report, appendices to the staff report, and basin plan amendment language: 

Santa Rosa, California North Coast Regional Water Quality Control Board, [variously paged], 

accessed May 12, 2010, at 

http://www.waterboards.ca.gov/northcoast/water_issues/programs/tmdls/klamath_river/100427/Appe

ndix_10_IntroductionToRTC.pdf

CH2M-Hill and Wells, S.A., 1995, Water quality model of the Klamath River between Link River and 

Keno Dam: Draft report for the Oregon Department of Environmental Quality, [variously paged]. 

Cole, T.M., and Wells, S.A., 2002, CE-QUAL-W2—A two-dimensional, laterally averaged, 

hydrodynamic and water-quality model, version 3.1: U.S. Army Corps of Engineers, Instruction 

Report EL-02-1, [variously paged]. 

Doyle, M.C., and Lynch, D.D., 2005, Sediment oxygen demand in Lake Ewauna and the Klamath 

River, Oregon, June 2003: U.S. Geological Survey Scientific Investigations Report 2005–5228, 14 p., 

accessed April 5, 2010, at http://pubs.usgs.gov/sir/2005/5228/pdf/sir2005-5228.pdf

Eilers, J., Kann, J., Cornett, J., Moser, K., and St. Amand, A., 2003, Paleolimnological evidence of 

change in a shallow hypereutrophic lake—Upper Klamath Lake, Oregon, USA: Hydrobiologia, v. 

520, p. 7–18. 

Eilers, J.M., and Raymond, R., 2005, Sediment oxygen demand in selected sites of the Lost River and 

Klamath River—Prepared for Tetra Tech, Inc., by MaxDepth Aquatics, Inc., 17 p., accessed April 5, 

2010, at 

http://www.deq.state.or.us/WQ/TMDLs/docs/klamathbasin/uklost/KlamathLostDraftAppendixE.pdf

Hoilman, G.R., Lindenberg, M.K., and Wood, T.M., 2008, Water quality conditions in Upper Klamath 

and Agency Lakes, Oregon, 2005: U.S. Geological Survey Scientific Investigations Report 2008-

5026, 44 p., accessed April 5, 2010, at http://pubs.usgs.gov/sir/2008/5026/. 

King, I.P., 2002, RMA2—A two-dimensional finite element model for flow in estuaries and streams, 

update documentation, version 7.0a: Fairfield, California, Resource Management Associates, October 

2002, 70 p. 

King, I.P., 2003, RMA11—A three-dimensional finite element model for water quality in estuaries and 

streams, update documentation, version 4.0a: Fairfield, California, Resource Management Associates, 

January 2003, 90 p. 
29

Mrazik, S., 2006, Oregon water quality index summary report, water years 1996–2005: Oregon 

Department of Environmental Quality, DEQ06-LAB-0029-TR, 13 p. 

Oregon Department of Environmental Quality, 2010, Draft Upper Klamath and Lost River subbasins 

Total Maximum Daily Load (TMDL) and water quality management plan (WQMP): Oregon 

Department of Environmental Quality, [variously paged], accessed April 5, 2010, at 

http://www.deq.state.or.us/WQ/TMDLs/docs/klamathbasin/uklost/KlamathLostTMDLWQMP.pdf

Organization for Economic Co-Operation and Development, 1982. Eutrophication of waters—

Monitoring, assessment and control: Report of the OECD Cooperative Programme on Eutrophication, 

Prepared by Vollenweider, R.A. & J. Kerekes, OECD, Paris, 154 p. 

Raymond, R., and Eilers, J.M., 2004, Sediment oxygen demand and nutrient release from sites in Lake 

Ewauna and Keno Reservoir—Prepared for PacifiCorp by MaxDepth Aquatics, Inc., 18 p. 

Reynolds, C.S., 2006, Ecology of phytoplankton: Cambridge University Press, New York, 550 p. 

Risley, J.C., and Rounds, S.A., 2006, Evaluation and review of recent Klamath River water-temperature 

modeling studies: U.S. Geological Survey Administrative Letter, 27 p. 

Rounds, S.A., 2007, Temperature effects of point sources, riparian shading, and dam operations on the 

Willamette River, Oregon: U.S. Geological Survey Scientific Investigations Report 2007-5185, 34 p., 

accessed April 5, 2010, at http://pubs.usgs.gov/sir/2007/5185/. 

Rounds, S.A., and Doyle, M.C., 1997, Sediment oxygen demand in the Tualatin River Basin, Oregon, 

1992-1996: U.S. Geological Survey Water-Resources Investigations Report 97-4103, 19 p, accessed 

April 5, 2010, at http://pubs.er.usgs.gov/usgspubs/wri/wri974103. 

Rounds, S.A., and Sullivan, A.B., 2009, Review of Klamath River total maximum daily load models 

from Link River Dam to Keno Dam, Oregon: U.S. Geological Survey Administrative Report, 37 p., 

accessed April 5, 2010, at 

http://or.water.usgs.gov/proj/keno_reach/download/klamath_river_model_review_final.pdf

Rounds, S.A., and Wood, T.M., 2001, Modeling water quality in the Tualatin River, Oregon, 1991–

1997: U.S. Geological Survey Water-Resources Investigations Report 01-4041, 53 p., accessed April 

5, 2010, at http://or.water.usgs.gov/pubs_dir/Online/Pdf/01-4041.pdf

Sullivan, A.B., Deas, M.L., Asbill, J., Kirshtein, J.D., Butler, K., and Vaughn, J., 2009, Klamath River 

water quality data from Link River to Keno Dam, Oregon, 2008: U.S. Geological Survey Open-File 

Report 2009-1105, 25 p., accessed April 5, 2010, at http://pubs.usgs.gov/of/2009/1105/. 

Sullivan, A.B., Deas, M.L., Asbill, J., Kirshtein, J.D., Butler, K., Wellman, R.W., Stewart, M.A., and 

Vaughn, J., 2008, Klamath River water quality and acoustic Doppler current profiler data from Link 

River Dam to Keno Dam, 2007: U.S. Geological Survey Open-File Report 2008-1185, 24 p., accessed 

April 5, 2010, at http://pubs.usgs.gov/of/2008/1185/. 

Sullivan, A.B., and Rounds, S.A., 2005, Modeling hydrodynamics, temperature and water quality in 

Henry Hagg Lake, Oregon, 2000–2003: U.S. Geological Survey Scientific Investigations Report 

2004-5261, 38 p., accessed April 5, 2010, at http://pubs.usgs.gov/sir/2004/5261/. 

Sullivan, A.B., and Rounds, S.A., 2006, Modeling water-quality effects of structural and operational 

changes to Scoggins Dam and Henry Hagg Lake, Oregon: U.S. Geological Survey Scientific 

Investigations Report 2006-5060, 36 p., accessed April 5, 2010, at 

http://pubs.usgs.gov/sir/2006/5060/. 

Sullivan, A.B., Rounds, S.A., Sobieszczyk, S., and Bragg, H.M., 2007, Modeling hydrodynamics, water 

temperature, and suspended sediment in Detroit Lake, Oregon: U.S. Geological Survey Scientific 
30

Investigations Report 2007-5008, 40 p., accessed April 5, 2010, at 

http://pubs.usgs.gov/sir/2007/5008/.

Sullivan, A.B., Snyder, D.M., and Rounds, S.A., 2010, Controls on biochemical oxygen demand in the 

upper Klamath River, Oregon: Chemical Geology, v. 269, no. 1-2, p. 12-21, doi: 

10.1016/j.chemgeo.2009.08.007, accessed April 5, 2010, at 

http://dx.doi.org/10.1016/j.chemgeo.2009.08.007. 

Tetra Tech, Inc., 2009a, Model configuration and results—Klamath River model for TMDL 

development: Prepared for U.S. Environmental Protection Agency Region 9 and 10, North Coast 

Regional Water Quality Control Board, Oregon Department of Environmental Quality, Fourth 

revision, December 2009, [variously paged], accessed April 5, 2010, at 

http://www.deq.state.or.us/WQ/TMDLs/docs/klamathbasin/uklost/KlamathLostDraftAppendixC.pdf

Tetra Tech, Inc., 2009b, Modeling scenarios—Klamath River model for TMDL development: Prepared 

for U.S. Environmental Protection Agency Region 9 and 10, North Coast Regional Water Quality 

Control Board, Oregon Department of Environmental Quality, December 2009, [variously paged], 

accessed April 5, 2010, at 

http://www.deq.state.or.us/WQ/TMDLs/docs/klamathbasin/uklost/KlamathLostDraftAppendixD.pdf

Thurman, E.M., 1985, Organic geochemistry of natural waters: Durdrecht, The Netherlands, 

Nijhoff/Junk Publishers, 497 p. 

Walker, W.W., Jr., 2001, Development of a phosphorus TMDL for Upper Klamath Lake, Oregon: 

Prepared for Oregon Department of Environmental Quality, March 7, 2001, accessed April 5, 2010, at 

http://www.deq.state.or.us/wq/TMDLs/docs/klamathbasin/ukldrainage/devphostmdl.pdf

Watercourse Engineering, Inc., 2004, Klamath River modeling framework to support the PacifiCorp 

Federal Energy Regulatory Commission Hydropower Relicensing Application, March 9, 2004. 

Welch, E.B., and Jacoby, J.M., 2004, Pollutant effects in freshwater—Applied limnology, 3rd edition: 

Spon Press, New York, 520 p. 

Wetzel, R.G., 1983, Limnology: Saunders College Publishing, Philadelphia, 860 p. 

Wetzel, R.G., 2001, Limnology—Lake and river ecosystems: Academic Press, San Diego, 1006 p. 

Wood, T.M., 2001, Sediment oxygen demand in Upper Klamath and Agency Lakes, Oregon, 1999: U.S. 

Geological Survey Water-Resources Investigations Report 01–4080, 13 p, accessed April 5, 2010, at 

http://or.water.usgs.gov/pubs_dir/WRIR01-4080/wri014080.pdf
31

Appendix A. Qualifications of Reviewers

USGS is the Nation's largest water, earth, and biological science and civilian mapping agency. The 

USGS collects, monitors, analyzes, and provides scientific data and interpretations about natural 

resource conditions, issues, and problems. With no regulatory or resource management mission, USGS 

provides unbiased and impartial research and scientific information to resource managers, planners, and 

other customers. 

A detailed model review of this type is best performed by scientists who have extensive waterquality modeling expertise, experience with the specific models under review, and knowledge of the 

water body being modeled. The two USGS hydrologists who performed this review meet these criteria 

and are currently working with the CE-QUAL-W2 model and the reach of interest of the Klamath River. 

Dr. Stewart Rounds has been using CE-QUAL-W2 to model water quality in the rivers and lakes of 

Oregon for 18 years, including models that have formed the foundation of TMDL regulations in the 

Tualatin and Willamette Rivers (Rounds and Wood, 2001; Rounds, 2007). Dr. Rounds is well versed 

with the CE-QUAL-W2 source code and has collaborated with the model developers on model 

improvements. Dr. Rounds’ professional page may be viewed at https://profile.usgs.gov/sarounds/. 

Dr. Annett Sullivan currently leads a project designed to better understand instream water-quality 

processes in the Link River Dam to Keno Dam reach of the Klamath River and improve upon existing 

models of that reach. She has more than 8 years of experience working with CE-QUAL-W2 on river and 

reservoir systems in Oregon, and has published detailed USGS modeling reports using CE-QUAL-W2 

on Detroit Lake, Henry Hagg Lake, and the Santiam and North Santiam River systems in Oregon 

(Sullivan and Rounds, 2005, 2006; Sullivan and others, 2007). Dr. Sullivan’s professional page may be 

viewed at https://profile.usgs.gov/annett.