Prepared in cooperation with the Bureau of Reclamation

Dissolved Oxygen Analysis, TMDL Model Comparison, and 

Particulate Matter Shunting: Preliminary Results from 

Three Model Scenarios for the Klamath River Upstream of 

Keno Dam, Oregon

U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2012–1101

Dissolved Oxygen Analysis, TMDL Model Comparison, 

and Particulate Matter Shunting: Preliminary Results from 

Three Model Scenarios for the Klamath River Upstream of 

Keno Dam, Oregon

By Annett B. Sullivan and Stewart A. Rounds, U.S. Geological Survey; Michael L. Deas and I. Ertugrul Sogutlugil, 

Watercourse Engineering, Inc.

Prepared in cooperation with the Bureau of Reclamation

Open-File Report 2012–1101

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

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

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

visit http://www.usgs.gov or call 1–888–ASK–USGS.

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visit http://www.usgs.gov/pubprod

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Suggested citation:

Sullivan, A.B., Rounds, S.A., Deas, M.L., and Sogutlugil, I.E., 2012, Dissolved oxygen analysis, TMDL model 

comparison, and particulate matter shunting—Preliminary results from three model scenarios for the Klamath 

River upstream of Keno Dam, Oregon: U.S. Geological Survey Open-File Report 2012-1101, 30 p. 

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

Significant Findings ........................................................................................................................................................1

Background....................................................................................................................................................................3

Purpose and Scope........................................................................................................................................................5

Model Description...........................................................................................................................................................5

Model Scenarios ............................................................................................................................................................6

Scenario 3. Compliance with Dissolved Oxygen Standards, Before and After TMDL Implementation. ......................7

Dissolved Oxygen Standards..................................................................................................................................7

Natural Conditions Dissolved Oxygen.....................................................................................................................8

Scenario Setup .......................................................................................................................................................9

Results of Scenario 3 Analyses ............................................................................................................................10

Depth-Averaged vs. Volume-Averaged Dissolved Oxygen Concentrations ......................................................10

Natural Conditions Dissolved Oxygen Effect on the Standard...........................................................................11

Comparison to the Dissolved Oxygen Standard................................................................................................13

Representativeness of the Seven ODEQ Compliance Locations......................................................................16

Scenario 4. Comparison of the USGS and TMDL Models Using 2006–09 Data ......................................................17

Scenario Setup .....................................................................................................................................................17

Results of Scenario 4 Analyses ............................................................................................................................18

Scenario 5. Shunting Particulate Material from Diversion Canals into the Klamath River.........................................21

Particulate Shunting..............................................................................................................................................22

Changes to Return-Flow Concentrations ..............................................................................................................23

Results of Scenario 5 Analyses ............................................................................................................................24

Acknowledgments ........................................................................................................................................................27

References Cited .........................................................................................................................................................27

Appendix—Code Changes to CE-QUAL-W2 ...............................................................................................................29

A. Natural Conditions Code Changes.......................................................................................................................29

B. Particulate Matter Shunting Code Changes .........................................................................................................30
iv

Figures

Figure 1. Map showing location of the study area, streamflow-gaging stations, and point-source inputs in the 

upper Klamath River, Oregon...........................................................................................................................4

Figure 2. Graph showing Upper Klamath Lake and Link River total phosphorus TMDL targets and natural 

conditions Link River total phosphorus for the USGS and TMDL models. ........................................................9

Figure 3. Graphs showing comparison of volume-averaged and depth-averaged dissolved oxygen concentration 

for calendar year 2008 at model segment 38, the Miller Island monitoring site...............................................11

Figure 4. Graphs showing base case [3(1a)] and natural conditions [3(nc)] scenarios for 2008 dissolved oxygen 

concentration at Miller Island (model segment 38) in the Link River to Keno reach of the Klamath River, 

and the relevant dissolved oxygen standards. ................................................................................................12

Figure 5. Graphs showing (A) minimum 30-day mean dissolved oxygen concentration at each modeled location 

during 2007 for scenario 3 model runs and (B) the difference between that minimum 30-day mean 

dissolved oxygen and the dissolved oxygen standard relevant for that location and day................................15

Figure 6. Graph showing number of days dissolved oxygen concentrations at all modeled locations in the Link 

River to Keno Dam reach violated the dissolved oxygen standard in the 2007 base case (scenario 1a)........17

Figure 7a. Graphs showing comparison of year 2007 measured algae, total nitrogen, particulate nitrogen, nitrate, 

and ammonia data, calibrated model results, and scenario 4 (2007 inputs applied to TMDL model setup) 

results for sites in the Klamath River upstream of Keno Dam, Oregon. ..........................................................19

Figure 7b. Graphs showing comparison of year 2007 measured total phosphorus, orthophosphorus, particulate 

organic carbon, dissolved organic carbon, and dissolved oxygen data, calibrated model results, and 

scenario 4 (2007 inputs applied to TMDL model setup) results for sites in the Klamath River upstream of 

Keno Dam, Oregon. ........................................................................................................................................20

Figure 8. Graph showing flows for A Canal, Lost River Diversion Channel, North Canal, Ady Canal, and Klamath 

Straits Drain for 2007. .....................................................................................................................................22

Figure 9. Graph showing particulate organic load (particulate organic material + algae) at Link River for 2006 

under current conditions and under A Canal particulate shunting. ..................................................................23

Figure 10. Graph showing 30-day mean dissolved oxygen concentrations at model segment 78 (site KRS12a) 

for the base case and scenarios 5a, 5b, 5c, and 5d in 2008.. .........................................................................26

Tables

Table 1. Model scenarios for the Link River to Keno Dam reach of the Klamath River, Oregon....................................6

Table 2. Number of days the Klamath River would violate dissolved oxygen standards at the seven ODEQ 

compliance locations for base case and TMDL compliance scenarios for years 2006–09..............................13

Table 3. Number of days the Klamath River would violate dissolved oxygen standards at the seven ODEQ 

compliance locations in the base case and particulate shunting scenarios for years 2006–09.......................25
v

Conversion Factors, Datums, and Abbreviations and Acronyms

Conversion Factors

Inch/Pound to SI

Multiply By To obtain

foot (ft) 0.3048 meter (m)

mile (mi) 1.609 kilometer (km)

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

SI to Inch/Pound

Multiply By To obtain

meter (m) 3.281 foot (ft) 

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

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius (μS/cm at 25 °C).

Concentrations of chemical constituents in water are given in milligrams per liter (mg/L), which is approximately equivalent 

to parts per million (ppm), or micrograms per liter (μg/L), which is approximately equivalent to parts per billion (ppb).

Datums

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

of Reclamation. For this report, the conversion is UKLVD – 1.78 ft = National Geodetic Vertical Datum of 1929 (NGVD29).

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

“Elevation” refers to distance above the vertical datum. 
vi

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1

Dissolved Oxygen Analysis, TMDL Model Comparison, 

and Particulate Matter Shunting: Preliminary Results from 

Three Model Scenarios for the Klamath River Upstream of 

Keno Dam, Oregon

By Annett B. Sullivan and Stewart A. Rounds, U.S. Geological Survey; Michael L. Deas and I. Ertugrul Sogutlugil, 

Watercourse Engineering, Inc.

Significant Findings

Efforts are underway to identify actions that 

would improve water quality in the Link River to 

Keno Dam reach of the Upper Klamath River in 

south-central Oregon. To provide further insight 

into water-quality improvement options, three 

scenarios were developed, run, and analyzed using previously calibrated CE-QUAL-W2 

hydrodynamic and water-quality models. Additional scenarios are under development as part of 

this ongoing study. Most of these scenarios evaluate changes relative to a “current conditions”

model, but in some cases a “natural conditions” 

model was used that simulated the reach without 

the effect of point and nonpoint sources and set

Upper Klamath Lake at its Total Maximum Daily Load (TMDL) targets. These scenarios were 

simulated using a model developed by the U.S. 

Geological Survey (USGS) and Watercourse Engineering, Inc. for the years 2006–09, referred to 

here as the “USGS model.” Another model of 

the reach was developed by Tetra Tech, Inc. for 

years 2000 and 2002 to support the Klamath 

River TMDL process; that model is referred to 

here as the “TMDL model.”

The three scenarios described in this report 

included (1) an analysis of whether this reach of 

the Upper Klamath River would be in compliance with dissolved oxygen standards if 

sources met TMDL allocations, (2) an application of more recent datasets to the TMDL model

with comparison to results from the USGS model, and (3) an examination of the effect on 

dissolved oxygen in the Klamath River if particulate material were stopped from entering Klamath Project diversion canals. Updates and 

modifications to the USGS model are in

progress, so in the future these scenarios will be 

reanalyzed with the updated model and the interim results presented here will be superseded.

Significant findings from this phase of the investigation include:

• The TMDL analysis used depth-averaged

dissolved oxygen concentrations from model 

output for comparison with dissolved oxygen 

standards. The Oregon dissolved oxygen 

standards do not specify whether the numeric 

criteria are based on depth-averaged dissolved oxygen concentration; this was an 

interpretation of the standards rule by the 

Oregon Department of Environmental Quality (ODEQ). In this study, both depthaveraged and volume-averaged dissolved 

oxygen concentrations were calculated from 

model output. Results showed that modeled 

depth-averaged concentrations typically were 

lower than volume-averaged dissolved oxygen concentrations because depth-averaging 

gives a higher weight to small volume areas 

near the channel bottom that often have lower dissolved oxygen concentrations. Results 

from model scenarios in this study are reported using volume-averaged dissolved 

oxygen concentrations.
2

• Under all scenarios analyzed, violations of 

the dissolved oxygen standard occurred most 

often in summer. Of the three dissolved oxygen criteria that must be met, the 30-day 

standard was violated most frequently. Under 

the base case (current conditions), fewer violations occurred in the upstream part of the 

reach. More violations occurred in the downstream direction, due in part to oxygen 

demand from the decay of algae and organic 

matter from Link River and other inflows.

• A condition in which Upper Klamath Lake

and its Link River outflow achieved Upper 

Klamath Lake TMDL water-quality targets 

was most effective in reducing the number of 

violations of the dissolved oxygen standard

in the Link River to Keno Dam reach of the 

Klamath River. The condition in which point 

and nonpoint sources within the Link River 

to Keno Dam reach met Klamath River 

TMDL allocations had no effect on dissolved 

oxygen compliance in some locations and a 

small effect in others under current conditions. On the other hand, meeting TMDL 

allocations for nonpoint and point sources 

was predicted to be important in meeting dissolved oxygen criteria when Upper Klamath 

Lake and Link River also met Upper Klamath TMDL water-quality targets.

• The location of greatest dissolved oxygen

improvement from nutrient and organic matter reductions was downstream from point 

and nonpoint source inflows because time

and distance are required for decay to occur 

and for oxygen demand to be exerted.

• After assessing compliance with dissolved 

oxygen standards at all 102 model segments 

in the Link River to Keno Dam reach, it was 

determined that the seven locations used by 

ODEQ appear to be a representative subset of 

the reach for dissolved oxygen analysis.

• The USGS and TMDL models were qualitatively compared by running both models for 

the 2006–09 period but preserving the essential characteristics of each, such as organic 

matter partitioning, bathymetric representation, and parameter rates. The analysis 

revealed that some constituents were not 

greatly affected by the differing algorithms, 

rates, and assumptions in the two models.

Conversely, other constituents, especially organic matter, were simulated differently by 

the two models. Organic matter in this river 

system is best represented by a mixture of 

relatively labile particulate material and a 

substantial concentration of refractory dissolved material. In addition, the use of a firstorder sediment oxygen demand, as in the 

USGS model, helps to capture the seasonal 

and dynamic effect of settled organic and algal material.

• Simulation of shunting (diverting) particulate 

material away from the intake of four Klamath Project diversion canals, so that the 

material stayed in the river and out of the 

Project area, caused higher concentrations of 

particulate material to occur in the river. In 

all cases modeled, the increase in in-river 

particulate material also produced decreased 

dissolved oxygen concentrations and an increase in the number of days when dissolved 

oxygen standards were violated.

• If particulate material were shunted back into 

the river at the Klamath Project diversion 

canals, less organic matter and nutrients 

would be taken into the Klamath Project area 

and the Lost River basin, resulting in return 

flows to the Klamath River via Lost River 

Diversion Channel that may have reduced 

nutrient concentrations. Model scenarios 

bracketing potential end-member nutrient 

concentrations showed that the composition 

of the return flows had little to no effect on 

dissolved oxygen compliance under simulated conditions.
3

Background

The Klamath River flows about 255 mi (410 

km) from the outlet of Upper Klamath Lake 

through southern Oregon and northern California 

to the Pacific Ocean. The first 21 mi of the river, 

just downstream of Upper Klamath Lake, are 

bounded by Link River Dam and Keno Dam (fig. 

1). Water quality in this reach has been classified 

as “very poor” by the State of Oregon (Mrazik, 

2007) and was designated as “water quality limited” on Oregon’s 303(d) list for exceeding 

ammonia toxicity and dissolved oxygen criteria 

year-round, and pH and chlorophyll a criteria in 

summer (Oregon Department of Environmental 

Quality, 2007). A TMDL for the Klamath River 

was submitted to the Environmental Protection 

Agency (EPA) in December 2010 (Oregon Department of Environmental Quality, 2010). In the

TMDL, load reductions of total nitrogen, total 

phosphorus, and biochemical oxygen demand 

(BOD) were specified for the nonpoint sources 

Lost River Diversion Channel and Klamath 

Straits Drain and for point sources Klamath Falls 

wastewater treatment plant and South Suburban 

wastewater treatment plant. For example, the

TMDL would require greater than 80-percent

reductions in total nitrogen, total phosphorus, 

and BOD in the Lost River Diversion Channel 

and Klamath Straits Drain.

As a foundation for the TMDL process,

ODEQ and Tetra Tech, Inc. developed a waterquality model for the Klamath River, including 

the Link River to Keno Dam (Link to Keno)

reach, based on a model previously developed 

for a dam-relicensing process by Watercourse 

Engineering, Inc. (Watercourse Engineering, 

Inc., 2004). For the Link to Keno reach, a modified CE-QUAL-W2 model was constructed and 

calibrated for the years 2000 and 2002 (Tetra 

Tech, Inc., 2009). The datasets used to drive the 

model, however, did not include direct measurements of organic matter concentrations, 

organic matter partitioning, or algae species. The 

technical basis of the TMDL model for the Link

to Keno reach was reviewed and evaluated by 

the USGS (Rounds and Sullivan, 2009 and 

2010).

Beginning in 2006, the USGS began a collaboration with the Bureau of Reclamation 

(Reclamation) and Watercourse Engineering, 

Inc. (Watercourse) to collect detailed datasets, 

conduct research, and develop a new waterquality model for the Link to Keno reach of the 

Klamath River. The goal was to produce a model 

that accurately represented the most important 

instream processes affecting water quality so that 

potential management strategies could be evaluated and prioritized. The result was a CEQUAL-W2 model calibrated for 2006–09 conditions that simulated three separate algal groups 

and relied on recent research and measurements 

to characterize the instream processes controlling 

water quality in the Klamath River (Sullivan and 

others, 2011). The model simulates water velocity, streamflow, stage, temperature, and a wide 

range of water-quality constituents including algae, nutrients, organic matter, suspended 

sediment, and dissolved oxygen. Based on extensive field data (Sullivan and others, 2008, 2009)

and experimental studies on flow, suspendedmatter settling, and dissolved oxygen and organic matter dynamics (Sullivan and others, 2010; 

Poulson and Sullivan, 2010; Deas and Vaughn, 

2011), the USGS-Watercourse-Reclamation

model (henceforth simply called the USGS model) of the Link to Keno reach has a sound 

technical basis for the exploration of a range of 

management strategies.
4

Figure 1. Map showing location of the study area, streamflow-gaging stations, and point-source inputs in the 

upper Klamath River, Oregon.
5

Purpose and Scope

The purpose of this report is to present the results of using the USGS and TMDL CE-QUALW2 models of the Link to Keno reach of the 

Klamath River to analyze three new model scenarios (numbered 3 through 5). Two model 

scenarios (numbered 1 and 2) were run and analyzed previously (Sullivan and others, 2011). 

Those two scenarios investigated Klamath River 

water-quality changes that might occur if UpperKlamath Lake and Upper Klamath River 

point and nonpoint inflows were to meet their 

respective TMDL allocations. The three model 

scenarios run and evaluated for this report include:

3. Compliance with dissolved oxygen standards, before and after TMDL 

implementation (USGS model).

4. Comparison of the USGS and TMDL models using 2006–09 data (simulations of 

current conditions).

5. Shunting particulate material from Klamath 

Project diversion canals into the Klamath 

River, such that particulate material that 

normally would be withdrawn remains instead in the Klamath River (USGS model).

The USGS model for years 2006–09 for this 

reach is currently being refined in two ways: (1)

incorporation of dissolved organic matter, phosphoric acid, and ammonia buffering into the pH 

subroutine and (2) inclusion of macrophytes 

(rooted aquatic plants) in the model based on data collected in summer 2011. Thus, the scenarios 

presented in this report are interim results because all model scenarios will be rerun with the 

updated model when those modifications are finalized. Additional model scenarios, currently in 

development, will also be run with the updated 

model. The purpose of this report is to publish 

some of these interim results in a timely manner 

so that the results can be considered as part of an 

ongoing resource management and planning 

process.

Model Description

The concentration of a constituent in a river 

can be affected by hydrology, atmospheric conditions, tributary inputs, withdrawals, chemical 

reactions, and biochemical reactions and 

processes. Mechanistic, sometimes called physically based, computer models include many of 

these processes and are regularly used to make 

predictions about effects on water quality in response to system changes. The models used in 

this study were built with the mechanistic model 

CE-QUAL-W2, a two-dimensional, laterally averaged, hydrodynamic, water temperature, and 

water-quality model (Cole and Wells, 2008). CEQUAL-W2 has been applied to hundreds of 

lakes, reservoirs, and rivers around the world

with good success.

The USGS-constructed Upper Klamath River CE-QUAL-W2 model for 2006–09 simulates

flow, water temperature, specific conductance, 

dissolved and suspended solids, dissolved oxygen, total nitrogen, ammonia, nitrate, total 

phosphorus, orthophosphate, dissolved and particulate organic matter, and three algal groups: 

blue-greens, diatoms, and other algae (Sullivan 

and others, 2011). A similar set of constituents 

was included in the TMDL model. Both the 

USGS and TMDL models can simulate these 

constituents from the mouth of Link River to 

Keno Dam. The USGS model grid is formed 

from 102 segments that connect together in the 

direction of flow. Segments average 1,009 ft

(308 m) in length and each segment represents a 

cross-sectional shape with stacked rectangular

layers of varying width from the river surface to 

the channel bottom. Grid layers were all 0.61 m 

in height; since CE-QUAL-W2 allows for a variable water surface elevation, water in the 

uppermost layer may be lower than the maximum layer height. The model produces output 

for all constituents for each layer of each segment at a chosen time interval, often hourly.
6

Although the models were constructed and 

calibrated for current conditions, the mechanistic 

nature of the models allows them to make useful 

predictions of hydrodynamic, thermal, and water-quality changes resulting from altered 

conditions. It is important to remember, however, that all model predictions have some 

uncertainty. Model scenario results are most useful in providing insights regarding changes to the 

system, rather than providing high certainty regarding the values of predicted concentrations; 

for example, model results can be used to evaluate decisions about which treatment or 

restoration processes might be most effective at 

improving water quality by assessing the predicted changes in key constituent concentrations.

Model Scenarios

The calibrated Link-Keno model was used 

to set up, run, and analyze three scenarios (table

1, scenarios 3 to 5). All scenarios were run for 

model years 2006–09 to examine a range of 

possible effects under different flow, meteorological, and water-quality conditions. Previously

run scenarios 1 and 2 examined changes in Upper Klamath River water quality under 

conditions in which Upper Klamath River point 

and nonpoint sources met Klamath River TMDL 

allocations, and/or Upper Klamath Lake and its 

Link River outflow achieved water-quality targets of the Upper Klamath Lake TMDL 

(Sullivan and others, 2011). Outlined herein are 

scenario assumptions, conditions, and associated 

information as well as results for scenarios 3 

through 5.

Table 1. Model scenarios for the Link River to Keno Dam reach of the Klamath River, Oregon—continued

[Scenarios were run for calendar years 2006–09. Scenario 3 is based upon further analyses of Scenarios 1 and 2. Abbreviations: TMDL, Total Maximum Daily Load; LRDC, Lost River Diversion Channel; KSD, Klamath Straits Drain; DO, 

dissolved oxygen; OM, organic matter]

Scenario 

Number Description Results presented

Scenario 1: point and nonpoint tributary sources at TMDL compliance

1a Base case (current conditions) Sullivan and others, 2011

1b TMDL tributaries Sullivan and others, 2011

Scenario 2: Link River at TMDL compliance

2a TMDL Link River Sullivan and others, 2011

2b TMDL Link River and TMDL tributaries Sullivan and others, 2011

Scenario 3: compliance with dissolved oxygen standards analysis

3(nc) Natural conditions, without anthropogenic impact This report

3(1a) Base case (current conditions) This report

3(1b) TMDL tributaries This report

3(2a) TMDL Link River This report

3(2b) TMDL Link River and tributaries This report

Scenario 4: comparison to TMDL model

4 Apply 2006-09 data to TMDL model This report
7

Table 1. Model scenarios for the Link River to Keno Dam reach of the Klamath River, Oregon—continued

[Scenarios were run for calendar years 2006–09. Scenario 3 is based upon further analyses of Scenarios 1 and 2. Abbreviations: TMDL, Total Maximum Daily Load; LRDC, Lost River Diversion Channel; KSD, Klamath Straits Drain; DO, 

dissolved oxygen; OM, organic matter]

Scenario 

Number Description Results presented

Scenario 5: particulate matter shunting

5a Shunt, LRDC and KSD current This report

5b Shunt, LRDC and KSD intermediate This report

5c Shunt, LRDC and KSD zero OM, nutrients, and algae, with DO at saturation This report

Scenario 3. Compliance with Dissolved 

Oxygen Standards, Before and After TMDL 

Implementation.

Scenario 3 extends scenario 1 and 2 analyses

further, and compares predicted instream dissolved oxygen concentrations to Oregon 

dissolved oxygen standards under various 

TMDL attainment conditions.

Dissolved Oxygen Standards

For the Link-Keno reach of the Upper Klamath River, classified as cool-water aquatic 

habitat, the relevant Oregon dissolved oxygen 

standard states “...the dissolved oxygen may not 

fall below 6.5 mg/L as a 30-day mean minimum, 

5.0 mg/L as a 7-day minimum mean, and may 

not fall below 4.0 mg/L as an absolute minimum” (Oregon Department of Environmental 

Quality, 2011). The “30-day mean minimum” is 

defined as the minimum of the 30 consecutiveday floating averages of the calculated daily 

mean, and the “7-day minimum mean” is defined 

as the minimum of the 7 consecutive-day floating average of the daily minimum concentration.

These numeric criteria are superseded if natural 

conditions are determined to have lower levels of 

dissolved oxygen; in that case, the natural conditions dissolved oxygen concentration becomes 

the standard. Additional applicable rule language

for this reach states that “no measurable reduction of dissolved oxygen” shall occur when the 

numeric criteria are violated, where “measurable 

reduction” is defined as “...no more than 0.20 

mg/L for all anthropogenic activity.” This 0.20 

mg/L rule was one of the primary measures used 

during the determination of allocations for point 

and nonpoint sources for the Klamath River 

TMDL (Daniel Turner, ODEQ, oral commun.).

Modeled compliance with these dissolved oxygen standards is checked by ODEQ at seven 

locations within the Link-Keno reach: at the inflows of the Klamath Falls wastewater treatment 

plant (USGS model segment 4), South Suburban 

wastewater treatment plant (segment 8), Lost 

River Diversion Channel (segment 19), and 

Klamath Straits Drain (model segment 69), as 

well as at monitoring sites Miller Island (segment 38), KRS12a (segment 78), and Keno

(segment 95) (fig. 1).

For TMDL dissolved oxygen analysis in this 

reach, depth-averaged dissolved oxygen concentrations from model output were calculated in 

order to compare to dissolved oxygen standards 

(oral commun., Daniel Turner, ODEQ). The 

Oregon dissolved oxygen standards rules do not 

specify any type of depth- or volume-averaging 

to be used in rivers that are not vertically well 

mixed; the depth-averaging model output was an 

interpretation of the dissolved oxygen standards 

rules by ODEQ. In this study, model depthaveraged dissolved oxygen concentrations were 

compared to another type of averaging, volumeaveraged concentrations. Calculation of depthaveraged dissolved oxygen concentrations from 

model output assigns equal weight to layers near 

the channel bottom and near the surface, despite 

the fact that the wider widths near the water surface contain more water volume than do the 

bottom layers. Volume-averaged concentrations, 
8

on the other hand, account for the cross-sectional 

width of each layer in the calculation. Both calculations took into account the fact that the total 

water depth varied over time in the grid.

The instantaneous criterion (4.0 mg/L) was 

compared to hourly average dissolved oxygen 

concentrations. The 7-day minimum mean criterion (5.0 mg/L) was compared to the average of 

the daily minimum of the previous 7 days. For 

the 30-day mean criterion (6.5 mg/L), the Oregon rules state that “... for the purpose of 

calculating the mean, concentrations in excess of 

100 percent of saturation are valued at the saturation concentration...”, so any supersaturated 

hourly average dissolved oxygen concentrations 

were set to saturation, and then the average of 

the daily mean of the previous 30 days was compared to the 6.5 mg/L criterion.

Natural Conditions Dissolved Oxygen

Because the natural conditions dissolved

oxygen concentration becomes the dissolved 

oxygen standard if it is lower than any of the 

three numeric criteria, it was necessary to set up 

and run a natural conditions model scenario.

ODEQ defines natural conditions as “conditions 

or circumstances affecting the physical, chemical, or biological integrity of a water of the state 

that are not influenced by past or present anthropogenic activities” (Oregon Department of 

Environmental Quality, 2011). Anthropogenic 

activity that modified flow began in this basin 

before 1900; for instance, the connection between the historical Lower Klamath Lake and the 

Lost River Slough was closed with a dike in 

1890 (Bureau of Reclamation, 2005). Although 

observational information exists on the nature of 

flow before anthropogenic activity (Bureau of 

Reclamation, 2005), some of those observational 

reports conflict (Weddell, 2000), and little quantitative flow data and no nutrient or organic 

matter concentration data exist from the time before anthropogenic activity.

Natural conditions models were constructed 

for both the TMDL modeling and the USGS 

modeling reported here. In general, both were 

constructed considering some level of improved 

water quality imported from Upper Klamath 

Lake, and limited effects from point and nonpoint source water quality. There were, however, 

differences in the details of the construction and 

implementation of the TMDL and USGS natural 

conditions models.

The construction of the natural conditions 

TMDL model has been documented and reviewed elsewhere (Oregon Department of 

Environmental Quality, 2010 [Appendix D];

Rounds and Sullivan, 2009, 2010). Briefly, that 

natural conditions model set Link River water 

quality on the basis of results from an Upper 

Klamath Lake model in which the Upper Klamath Lake TMDL was implemented. The same 

water-quality conditions for Link River were 

used as natural conditions water quality for the 

Lost River Diversion Channel and the Klamath 

Straits Drain. Point sources were removed from 

the natural conditions TMDL model. Keno Dam 

was left in place because historically a natural 

basalt structure was there (Oregon Department of 

Environmental Quality, 2010).

For the natural conditions model used in 

USGS modeling, instead of using output from an

Upper Klamath Lake model to form the Upper 

Klamath Lake and Link River inflow conditions, 

Link River existing concentrations of orthophosphorus, algae, and organic matter for 2006–09 

were decreased until the Upper Klamath Lake 

TMDL total phosphorus targets were met (Sullivan and others, 2011, p. 60). This is the same 

Link River boundary condition used in model 

scenarios 2 and 3(2a) and 3(2b), with the latter 

two described in this report. The total phosphorus inflow from this natural conditions model 

was higher than that of the TMDL natural conditions model in summer but still below the Upper 

Klamath Lake TMDL targets (fig. 2).

Rather than remove point sources for USGS 

natural conditions modeling, which would affect

the residence time and complicate comparisons 

to scenarios that include the point sources, we 

retained those sources but set the concentration 

of all point-source inputs to the same concentra-
9

tion as the Klamath River where each inflow entered the river. The same was done for 

“nonpoint” tributaries such as the Klamath 

Straits Drain. To allow tributary inputs to be given concentrations that match those simulated in 

the river at their discharge location, the CEQUAL-W2 code was modified, specifically in 

the wqconstituents.f90 source file (see appendix). A similar code change was made for water 

temperature in the temperature.f90 source file. 

Finally, the natural conditions scenario was set 

up so that tributaries would distribute flow 

equally into all layers of the receiving stream 

(input TRC=“DISTR”) instead of weighted depending on water density in the layer; with the 

same temperature and concentration in the tributary and segment, water density would be the 

same and water would enter all layers equally. 

This modified CE-QUAL-W2 code was used to 

run only the natural conditions scenario.

Figure 2. Graph showing 

Upper Klamath Lake and Link 

River total phosphorus TMDL 

targets and natural conditions 

Link River total phosphorus 

for the USGS and TMDL 

models.

Scenario Setup

Scenario 3 consists of the natural conditions 

scenario 3(nc) as well as model runs 3(1a), 

3(1b), 3(2a), and 3(2b) that are identical to those 

completed for scenarios 1 and 2 (table 1). Those 

model runs were constructed as described in Sullivan and others (2011). To summarize, model 

runs for this scenario set included:

3(nc) Natural conditions

Upper Klamath Lake at Upper Klamath Lake

TMDL targets; point and nonpoint tributary 

sources set equal to Klamath River concentrations

3(1a) Base case (same as scenario 1a)

All inflows at current conditions

3(1b) TMDL tributaries (same as scenario 1b)

Link River at current conditions; point and nonpoint tributary sources at Klamath River TMDL 

allocations

3(2a) TMDL Link River (same as scenario 2a)

Link River at Upper Klamath Lake TMDL targets; point and nonpoint tributary sources at 

current conditions

3(2b) TMDL Link River and tributaries (same 

as scenario 2b)

Link River at Upper Klamath Lake TMDL targets; point and nonpoint tributary sources at 

Klamath River TMDL allocations
10

All scenarios were run with the USGS model for calendar years 2006–09 and the nonnatural scenario results were compared to the 

relevant dissolved oxygen standard. Standards 

compliance was checked at the seven ODEQ 

compliance locations for all years. A compliance 

analysis also was conducted for the entire Link 

to Keno reach for year 2007 to determine whether the seven compliance locations were a 

representative subset of the entire reach.

Results of Scenario 3 Analyses

Depth-Averaged vs. Volume-Averaged Dissolved Oxygen

Concentrations

During the winter and early spring, when little vertical variation in dissolved oxygen was 

present in the water column, depth-averaged and 

volume-averaged dissolved oxygen concentrations were almost identical (fig. 3). During late 

spring, summer, and fall, when vertical variations in dissolved oxygen concentrations in the 

water column were more common, differences 

between the depth-averaged and volumeaveraged dissolved oxygen concentration were 

apparent, with the depth-averaged concentrations 

typically less than the volume-averaged concentrations. The differences occurred in the hourly 

values as well as the 7-day and 30-day values. 

At the seven ODEQ compliance locations, 

differences between depth-averaged and volumeaveraged concentrations were greatest at the 

most upstream compliance location (model segment 4) for all 4 years, up to a maximum of 

about 4 mg/L for hourly values in summer. At 

that location in summer, large algal populations 

produced supersaturated oxygen conditions near 

the water surface, and organic matter decomposition led to low dissolved oxygen concentrations 

near the bottom. The notable difference between 

surface and bottom dissolved oxygen concentrations led to the associated differences in results 

from the two calculation methods. Crosssectional segment geometries also play a role in 

the difference between depth-averaged and volume-averaged concentrations. In addition to 

segment 4, summer differences in depthaveraged and volume-averaged concentrations at 

other compliance locations also occurred, ranging from near zero to 2 mg/L (for example, 

fig. 3).

Depth-averaged concentrations typically 

were lower than volume-averaged concentrations 

of dissolved oxygen, mainly because the depthaveraged method gives more weight to layers 

near the channel bottom, which most often had 

the lowest concentrations of dissolved oxygen. 

Only for limited times and a few locations did 

the depth-averaged calculation method produce 

higher dissolved oxygen concentrations than the 

volume-averaged calculation method. This occurred under the specific condition when a 

tributary inflow had both higher dissolved oxygen and a higher water density (based on 

temperature and concentration) compared to the 

river. Because of the higher density, the high dissolved oxygen tributary water would plunge to 

the channel bottom at the inflow segment; this 

unusual condition was an anomaly in the comparison of the two averaging methods.
11

Figure 3. Graphs showing comparison of volume-averaged and depth-averaged dissolved oxygen concentration 

for calendar year 2008 at model segment 38, the Miller Island monitoring site.

Based on the comparative analysis, volumeaveraged concentrations were used through the 

rest of this study because that calculation method

provides a more appropriate representation of the 

average dissolved oxygen concentration when 

the entire cross section is considered. This may 

change in future analyses, and vertical profile 

measurements in the field may be easier to compare to results from the depth-averaged method.

In any case, the differences between the averaging methods are notable and the selected method 

should be documented when comparisons to the 

dissolved oxygen standard are made.

Natural Conditions Dissolved Oxygen Effect on the

Standard

In general, the natural conditions dissolved 

oxygen concentrations were greater than the 

hourly, 7-day minimum mean, or 30-day mean

dissolved oxygen standards. However, there 

were certain periods in summer, at certain locations, where the dissolved oxygen concentration 
12

from the natural conditions run was lower than 

the numeric criteria. For example, at Miller Island the natural conditions dissolved oxygen 

concentration was less than all three criteria for 

certain periods in summer (fig. 4). When this occurred, the natural conditions dissolved oxygen

concentration was set as the dissolved oxygen 

standard, with the applicable compliance metric 

set to the new standard with an additional reduction of 0.20 mg/L to account for the 0.20 mg/L 

anthropogenic allowance.

Figure 4. Graphs showing base case [3(1a)] and natural conditions [3(nc)] scenarios for 2008 dissolved oxygen 

concentration at Miller Island (model segment 38) in the Link River to Keno reach of the Klamath River, and the 

relevant dissolved oxygen standards.
13

Comparison to the Dissolved Oxygen Standard

For all scenario 3 model runs, for all years, 

the simulated Link to Keno dissolved oxygen 

concentration was above the dissolved oxygen 

standard for most of the winter and early spring

(for example, fig. 4). At that time of year, the 

river contains less decomposable (oxygenconsuming) material, temperature-dependent decay rates are slower, and the cold water 

temperatures were able to retain higher levels of 

dissolved oxygen (higher solubility). However, 

during summer, the opposite condition occurred, 

with elevated levels of labile particulate organic 

matter, higher decay rates from temperaturedependent processes, and warmer temperatures 

decreasing the solubility of oxygen in water. The 

result was that during summer, violations of the 

dissolved oxygen standard occurred more frequently.

Of the three dissolved oxygen standards (instantaneous (hourly), 7-day minimum mean, 30-

day mean), the hourly standard was violated least 

often, and the 30-day standard was violated most 

often. The maximum number of days that any of 

the three standards were violated, for a specific 

location and year, are presented in table 2; this 

was most often the number of days that the 30-

day standard was violated. This summary table 

does not show how close the value was to the 

standard, only whether it was violated. In some 

cases, the value was close to the standard, but 

still in violation. 

Table 2. Number of days the Klamath River would violate dissolved oxygen standards at the seven ODEQ compliance locations for base case and TMDL compliance scenarios for years 2006–09—continued

[Abbreviations: KF, Klamath Falls wastewater treatment plant; SSSD, South Suburban wastewater treatment plant; LRDC, 

Lost River Diversion Channel; KSD, Klamath Straits Drain; seg, model segment; TMDL, total maximum daily load]

Scenario number and description

Days violating dissolved oxygen standard at compliance locations

Total for the 

7 compliance locations

KF 

inflow

SSSD 

inflow

LRDC 

inflow

Miller 

Island

KSD 

inflow KRS12a Keno

seg 4 seg 8 seg 19 seg 38 seg 69 seg 78 seg 95

2006

3(1a) Base case (current conditions) 676 24 75 89 120 122 122 124

3(1b) TMDL tributaries 664 24 74 88 119 119 119 121

3(2a) TMDL Link River 246 0 0 0 0 82 80 84

3(2b) TMDL Link River and tributaries 117 0 0 0 0 65 48 4

2007

3(1a) Base case (current conditions) 729 53 89 105 119 121 122 120

3(1b) TMDL tributaries 707 53 89 104 116 117 117 111

3(2a) TMDL Link River 147 0 0 0 0 68 64 15

3(2b) TMDL Link River and tributaries 113 0 0 0 0 67 46 0
14

Table 2. Number of days the Klamath River would violate dissolved oxygen standards at the seven ODEQ compliance locations for base case and TMDL compliance scenarios for years 2006–09—continued

[Abbreviations: KF, Klamath Falls wastewater treatment plant; SSSD, South Suburban wastewater treatment plant; LRDC, 

Lost River Diversion Channel; KSD, Klamath Straits Drain; seg, model segment; TMDL, total maximum daily load]

Scenario number and description

Days violating dissolved oxygen standard at compliance locations

Total for the 

7 compliance locations

KF 

inflow

SSSD 

inflow

LRDC 

inflow

Miller 

Island

KSD 

inflow KRS12a Keno

seg 4 seg 8 seg 19 seg 38 seg 69 seg 78 seg 95

2008

3(1a) Base case (current conditions) 833 67 92 113 134 141 142 144

3(1b) TMDL tributaries 828 67 92 113 133 140 141 142

3(2a) TMDL Link River 152 0 0 0 19 20 37 76

3(2b) TMDL Link River and 

tributaries 38 0 0 0 19 19 0 0

2009

3(1a) Base case (current conditions) 854 80 102 120 133 139 139 141

3(1b) TMDL tributaries 850 80 102 120 133 138 138 139

3(2a) TMDL Link River 245 0 0 0 1 68 86 90

3(2b) TMDL Link River and 

tributaries 80 0 0 0 1 62 16 1

Base case conditions, scenario 3(1a), violated the dissolved oxygen standard for some 

period of days at all seven ODEQ compliance

locations for all 4 years that were simulated. For 

the same locations, 2006 and 2007 had the fewest violation days, and 2008 and 2009 had the 

most. A distinct spatial trend also was evident in 

the base case scenarios, with the fewest violation 

days on the upstream end and the highest number 

of violation days on the downstream end of the 

reach. This spatial trend is also illustrated in figure 5 (top), which shows the lowest 30-day mean 

dissolved oxygen concentration for year 2007 for

all of the 102 modeled segments. This trend is

likely due to the fact that inflowing water from 

Link River generally has dissolved oxygen concentrations above 6.5 mg/L, but as waters move

downstream, concentrations decrease because of

oxygen demand from settling and decomposing 

algae, organic matter, and sediment oxygen demand. Further, there are additional inputs of 

oxygen-demanding material and/or low dissolved oxygen water from point and nonpoint 

sources throughout the reach.
15

Figure 5. Graphs showing (A) minimum 30-day mean dissolved oxygen concentration at each modeled location 

during 2007 for scenario 3 model runs and (B) the difference between that minimum 30-day mean dissolved oxygen and the dissolved oxygen standard relevant for that location and day.

Setting the four point and nonpoint sources 

to their TMDL allocations in scenario 3(1b) by 

reducing inflowing concentrations of orthophosphate, organic matter, and algae by 59 to 95

percent (with some additional reductions in nitrate and ammonia) (Sullivan and others, 2011) 

did not substantially reduce the number of violation days compared to the base case 3(1a) at any 

of the seven ODEQ compliance locations (table 2). Compared to the base case, the point of 

greatest improvement in 30-day mean dissolved 

oxygen was downstream of the point and nonpoint inflows (table 2; fig. 5, top). Considering 

the compliance locations, the greatest improvement was only nine fewer violation days at Keno 

in 2007 (8 percent). For all compliance locations 

and depending on the year, the number of dissolved oxygen violation days for scenario 3(1b) 

decreased 1 to 3 percent from current conditions.
16

Setting the Link River inflow to meet the 

Upper Klamath Lake TMDL water-quality targets in scenario 3(2a) had the largest effect of 

any of the scenario-3 model runs on Upper Klamath River dissolved oxygen concentrations

(fig. 5), decreasing the number of violation days 

by 24 to 132 days compared to the base case

3(1a), depending on location (table 2). The improvement in meeting dissolved oxygen 

standards occurred throughout the reach, but was 

most notable in the upstream part of the reach.

The most upstream compliance locations (segments 4, 8, and 19) had zero days violating the 

dissolved oxygen standard in this scenario for all 

years; segments farther downstream also had far 

fewer violation days. Considering all compliance 

locations and depending on the year, the number 

of dissolved oxygen violation days in scenario 

3(2a) decreased 64–82 percent from current conditions.

Under conditions where Link River met its 

TMDL allocation 3(2a), the additional condition 

of setting nonpoint and point sources to meet 

their Klamath River TMDL allocations in scenario 3(2b) had a greater effect for downstream 

segments than the model runs in which Link 

River was set to current conditions (scenario 

3(1b) versus 3(1a)) (table 2, fig. 5). With Link 

River at Upper Klamath Lake TMDL waterquality targets, dissolved oxygen through the 

reach was much closer to the standard, so small 

improvements could more easily move dissolved 

oxygen concentrations above the standard. With 

Link River at current conditions, the river was 

well below the standard, so small improvements

from the point and nonpoint sources had a much 

smaller effect towards meeting the standard 

(fig. 5, bottom). Considering all compliance locations and depending on the year, the number of 

dissolved oxygen violation days in scenario 

3(2b) decreased 83–95 percent from current conditions.

Several conclusions can be drawn from thes 

scenario results. First, assuming Link River to 

meet Upper Klamath Lake TMDL targets in scenarios 3(2a) and 3(2b) goes a long way towards 

meeting dissolved oxygen standards in the Link 

to Keno reach. None of the other actions tested 

in scenario 3 could pull the river into compliance 

with the dissolved oxygen standard if the Link 

River inflow was allowed to remain at its current 

condition (scenarios 3(1a) and 3(1b)). The importance of the Upper Klamath Lake and Link 

River boundary on the water quality of this reach 

has been documented previously (Oregon Department of Environmental Quality, 2010;

Sullivan and others, 2011). Second, point and 

nonpoint sources meeting TMDL allocations had 

the greatest effect when the Link River inflow 

was already meeting Upper Klamath Lake waterquality targets. Finally, these scenarios also show 

that the effect of setting the Link River input to

Upper Klamath Lake TMDL water-quality targets may have the greatest effect not at the 

inflow point, but further downstream (fig. 5).

The point of maximum impact from these 

changes may even be downstream of Keno Dam.

The downstream improvement arises from the 

fact that organic matter, algae, ammonia, and 

other oxygen demanding substances take time to 

decay, and the location of greatest change depends on decay rates, water velocity, travel time,

and other factors.

Representativeness of the Seven ODEQ Compliance 

Locations

A comparison of the maximum number of 

days violating the dissolved oxygen standard for 

all model segments as well as the seven ODEQ 

compliance segments are shown in figure 6.

These results indicate that the seven compliance 

locations selected by ODEQ appear to be a representative subset of dissolved oxygen 

compliance conditions in this reach of the Upper 

Klamath River. As with other analyses in this 

report, this will be re-examined after model updates for pH buffering and macrophyte growth 

are finalized. Although these segment locations 

appear to be representative for dissolved oxygen, 

similar analyses to determine the representativeness of these locations will be completed for 

other constituents and measures, such as ammonia toxicity and pH, which currently are out of 

compliance with water-quality standards.
17

Figure 6. Graph showing number of days dissolved oxygen concentrations at all modeled locations in the Link 

River to Keno Dam reach violated the dissolved oxygen standard in the 2007 base case (scenario 1a). The seven 

segments where the Oregon Department of Environmental Quality monitors compliance with water-quality standards are noted.

Scenario 4. Comparison of the USGS and 

TMDL Models Using 2006–09 Data

In addition to the USGS model of the Link 

to Keno reach, an earlier CE-QUAL-W2 model 

was constructed by Tetra Tech and used as the 

technical basis for the Klamath River TMDL allocations (Tetra Tech, Inc., 2009). The 

development of the TMDL model for the years

2000 and 2002 did not have the benefit of the 

extensive field data and experimental research 

conducted in this reach for the USGS model in 

2006–09. Reviews of the TMDL model questioned the concentration and partitioning of 

organic matter used in that model as well as other assumptions (Rounds and Sullivan, 2009, 

2010). The TMDL model and the USGS model

of this reach cannot be compared directly because the models were set up to simulate 

different years. To assess qualitative differences 

between output from the two models and evaluate the effects of several important model factors, scenario 4 was developed wherein the 

TMDL model executable, control file parameters 

and rates, bathymetry, and organic matter partitioning assumptions were applied with the 2006–

09 flow, water quality, and meteorological input 

files. The 2006–09 dataset was selected for the 

main comparison because it is more extensive 

than the 2000 and 2002 datasets used by the 

TMDL model.

Scenario Setup

To apply the TMDL model for this scenario, 

the 2006–09 model input files were used, including flow, temperature, water quality, and 

meteorology, with some adjustments to make 

those inputs consistent with the assumptions 

built into the TMDL model. The partitioning of 

organic matter in the water-quality input files, 

for example, was changed to match that of the 

TMDL model. While the 2006–09 input files for 
18

the USGS model included both labile (quickly

decaying) and refractory (slowly decaying) organic matter, the TMDL model inputs had zero 

refractory organic matter and had low concentrations of dissolved organic matter (Rounds and 

Sullivan, 2009, 2010). To change the organic 

matter partitioning in the 2006–09 input files so 

it was consistent with the rates and assumptions 

built into the TMDL model, a total organicmatter concentration was calculated from the 

sum of labile and refractory, dissolved and particulate organic matter concentrations 

(LDOM+RDOM+LPOM+RPOM). Then, the 

organic matter was partitioned according to the 

partitioning assumptions used by the TMDL 

model. For example, Link River organic matter

inputs were partitioned into 20 percent labile dissolved organic matter and 80 percent labile 

particulate organic matter, with no refractory organic matter, either dissolved or particulate.

Several other changes were made to the 

2006–09 input files in this scenario so that they 

more closely matched the setup of the TMDL 

model input files. The separate 2006–09 sluice, 

fish ladder, and spill gate outflows at Keno Dam 

were added together to produce only one outflow. Further, the TMDL model did not 

differentiate between algal groups, so the concentration of diatoms, blue-green algae, and 

“other” algae used by the USGS model were 

added together to produce one algae input. In 

addition, precipitation input files were used for 

both the USGS and TMDL models in this scenario to keep hydrologic inputs the same.

Precipitation had not been explicitly used in the 

earlier 2000 and 2002 TMDL model simulations, 

but were used in the USGS model.

The TMDL model executable, graph file, 

shade file, bathymetry file, and control files were 

used without substantive modification to preserve the rates, parameters, shading, and river 

geometry of the original TMDL model. The 

TMDL model executable was a modified version 

of CE-QUAL-W2 version 3.12, whereas the 

USGS model used CE-QUAL-W2 version 3.6.

Most of the TMDL control file parameters were

not changed; however, the wind height parameter 

was changed to 10 m to match the height of the 

wind sensor where the 2006–09 meteorological 

data were measured. In addition, evaporation as 

part of the water budget (not the heat budget) had 

been turned off in the TMDL model, but was 

turned on for these scenarios; this change is 

small and unimportant to the results, but is more 

consistent with the water balance used for the 

2006–09 datasets.

The results of this application of the TMDL 

model to the 2006–09 inputs were compared to 

measured data and to results from the calibrated 

USGS models. This comparison provides a qualitative means to examine the effect of 

differences in organic matter partitioning (labile 

versus refractory, dissolved versus particulate), 

algae algorithms, model parameter values, bathymetry, and the nature of the sediment oxygen 

demand (zero order only in the TMDL model 

versus a combination of zero and first order in 

the USGS model). This comparison is not meant 

to provide a means to criticize either the TMDL 

model or the USGS model, but simply to evaluate how different approaches to formulating 

certain boundary conditions and different methods of simulating certain river processes can 

result in different model predictions. In this way, 

the comparison is best used to highlight which 

processes or assumptions have a large effect on 

model results so that our understanding of the 

importance of these factors and the sensitivity of 

models to them can be improved. However, it is 

important to remember that this scenario is only 

a partial comparison and this analysis focuses on

base case, current condition models; it does not 

compare the setup of the natural conditions model for the TMDL process, which included 

different assumptions than the natural conditions 

USGS model, as noted in scenario 3.

Results of Scenario 4 Analyses

Qualitative comparison of the scenario 4 

TMDL model to the calibrated 2006–09 USGS 

model and measured data (figs. 7a, 7b) shows 

large differences for certain constituents and only minor differences for others. Because the 

general nature of the differences was similar be-
19

tween years, only year 2007 results are included 

in this report. Despite the different algorithms 

used to simulate algae in the TMDL model and 

the USGS model, the spatial and temporal patterns in the modeled algae populations were 

similar between the two models (fig. 7a). Total 

nitrogen and ammonia concentrations were underpredicted in summer from Miller Island to 

Keno in the TMDL model, and nitrate concentrations were overpredicted compared to data in 

summer from KRS12 to Keno. The overprediction of nitrate in the downstream end of the reach 

had been noted during reviews of the TMDL 

model (Rounds and Sullivan, 2009, 2010).

Figure 7a. Graphs showing comparison of year 2007 measured algae, total nitrogen, particulate nitrogen, nitrate, 

and ammonia data, calibrated model results, and scenario 4 (2007 inputs applied to TMDL model setup) results 

for sites in the Klamath River upstream of Keno Dam, Oregon.
20

Figure 7b. Graphs showing comparison of year 2007 measured total phosphorus, orthophosphorus, particulate 

organic carbon, dissolved organic carbon, and dissolved oxygen data, calibrated model results, and scenario 4 

(2007 inputs applied to TMDL model setup) results for sites in the Klamath River upstream of Keno Dam, Oregon.

Spatial and temporal patterns of orthophosphorus and total phosphorus concentrations were 

similar between the TMDL and USGS models, 

with perhaps a slight overprediction of orthophosphorus by the TMDL model in summer at 

KRS12a and Keno and slight overprediction of 

total phosphorus by the USGS model at the same 

locations and times (fig. 7b). Particulate carbon 

in the scenario 4 TMDL model was notably high 

in winter compared to measured data at the upstream end of the Link-Keno reach (fig. 7b); 

differences decreased in the downstream direction. The disappearance of particulate matter 

from upstream to downstream was due in part to 
21

the fact that all organic matter in the TMDL 

model was classified as labile (quickly decaying). Dissolved organic matter concentrations 

showed large differences between the two models, with concentrations greatly underpredicted 

by the scenario 4 TMDL model, but this is understandable because the data collected in 2006–

09 indicate a different organic matter partitioning 

than the assumptions used by the TMDL model 

in 2000 and 2002, which did not have the benefit 

of a more robust organic matter dataset.

The implications of the TMDL model representations of particulate organic matter were 

manifest in the dissolved oxygen concentrations.

The oxygen demand associated with particulate 

organic matter in the TMDL model application

that was classified as completely labile also led 

to dissolved oxygen concentrations that were too 

low during spring in the scenario 4 TMDL model. Recovery of dissolved oxygen in the fall also 

was sooner than measured data or the USGS 

model with the scenario 4 TMDL model. This is 

likely because the TMDL model uses only a zero-order sediment oxygen demand that does not 

keep track of demand from settled organic material and, as a result, is not responsive to 

seasonal changes other than that from water temperature; the USGS model represents part of the 

sediment oxygen demand with a first-order 

process that includes the effect of that seasonally 

deposited material. On the other hand, the 

TMDL model was able to more accurately capture the low dissolved oxygen concentrations at

the Railroad Bridge site in summer. It is hoped 

that further model comparisons for other years 

will reveal more opportunities to learn from 

models that were calibrated with different datasets and different sets of assumptions.

This analysis revealed several constituents 

where different algorithms, rates, and assumptions did not make a notable difference in model 

predictions for 2006–09. For example, both 

models predicted algae, orthophosphorus, and 

total phosphorus concentrations to have similar 

magnitudes and seasonal patterns at many locations. On the other hand, the analysis also 

confirmed several issues that are critical to understanding and representing the dynamics and 

patterns of Klamath River water quality. In particular, organic matter in this system is best 

represented by a mixture of relatively labile particulate material and a substantial concentration 

of relatively refractory dissolved material, and a 

zero-order-only sediment oxygen demand does 

not capture the seasonal and relatively dynamic 

effect of settled algal and particulate organic material. To assess the effect of future management 

activity, models should aim to capture the pertinent processes as accurately as possible. The 

USGS model will continue to be used for this 

ongoing scenario work.

Scenario 5. Shunting Particulate Material from 

Diversion Canals into the Klamath River

Scenario 5 examined the effects on Klamath 

River water quality under conditions where particulate material was “shunted,” or diverted,

from Klamath Project withdrawal points back to 

the river such that particulate material stayed in 

the Klamath River system and out of the canals.

Another goal of this particulate shunting analysis

is to understand whether keeping particulate matter out of the Klamath Project diversion canals 

and the Lost River basin would decrease nutrient 

and organic matter in the Lost River Diversion 

Channel and Klamath Straits Drain enough to

move them towards their TMDL allocations. Future analyses will examine the second question 

more closely. Results presented here focus on

how particulate shunting might affect Klamath 

River dissolved oxygen concentrations and compliance with dissolved oxygen standards.

Under current operations, four Klamath 

Project diversion canals take water from Link 

River and the Upper Klamath River upstream of 

Keno Dam; the withdrawn water is routed into 

Reclamation’s Klamath Project and the Lost 

River basin. These diversion canals are the A 

Canal, the Lost River Diversion Channel, North 

Canal, and Ady Canal (fig. 1). The Lost River 

Diversion Channel typically withdraws water to 

the Lost River in summer and returns flow to the 

Klamath River during the rest of the year. The 

other three diversion canals act only as with-
22

drawals (fig. 8); the A Canal withdrew the largest amount of water during 2006–09 compared to 

the other three canals. The particulate material 

under consideration included all three types of 

algae, labile and refractory particulate organic 

matter, and inorganic suspended sediment.

Withdrawals in this scenario were essentially 

filtered within the model to keep particulate matter out of the diversion canals. Flows were not 

altered in this scenario. Scenarios were run for 

all 4 years, 2006–09.

Figure 8. Graph showing flows for A 

Canal, Lost River Diversion Channel, 

North Canal, Ady Canal, and Klamath 

Straits Drain for 2007. Diversions 

away from the Klamath River system 

are shown as negative flows; flows to 

the Klamath River from the Lost River 

basin are shown as positive flows.

For comparison, flows at the upstream end of this Klamath River 

reach, at Link River, averaged 1,165 

cubic feet per second in 2007.

Particulate Shunting

The shunting of particulate material from A 

Canal was accomplished outside the model, as 

the A Canal takes water from upstream of the 

model’s upper boundary. The A Canal technically withdraws water from a southern lobe of 

Upper Klamath Lake upstream of Link River 

Dam. Because the A Canal intake is fairly close 

to the dam, which is the main outlet of the lake, 

it was assumed that the water quality at the A 

Canal intake was similar to water quality at the 

mouth of Link River. The shunted mass of inorganic suspended sediment, labile particulate 

organic matter, refractory particulate organic 

matter, blue-green algae, diatoms, and other algae were individually calculated based on concentrations at the mouth of Link River and 

A Canal flows. For the years modeled, A Canal 

diversions only occurred between late March and 

mid-October (for example, fig. 8). It was assumed that all particulates shunted from the A 

canal intake flowed into Link River, and that travel time was negligible between the A Canal 

intake and the Link River model boundary. For 

each type of particulate material, the shunted 

mass of A Canal particulates was added to the 

mass of particulates used in base-case model 

scenarios at Link River, and new Link River particulate concentrations were calculated from the

masses and the Link River flow. For example, 

the sum of the particulate organic load

(LPOM+RPOM+BlueGreen algae+Diatoms+

Other algae) at Link River with and without

shunting in 2006 is shown in figure 9.
23

Figure 9. Graph showing particulate organic load (particulate organic material + 

algae) at Link River for 2006 under current 

conditions and under A Canal particulate 

shunting.

For the three in-reach diversions (Lost River 

Diversion Channel, North Canal, and Ady Canal), particulate shunting was accomplished 

within the model by changing the CE-QUALW2 code so all that particles remained in the 

Klamath River at selected diversions (see appendix). Mass balance calculations during code 

development checked that the increase in particulate matter at the relevant Klamath River 

segments matched the decrease in particulate 

matter in the diversion outflow.

Changes to Return-Flow Concentrations

Return flows in the Link-Keno reach were 

dominated by contributions from the Lost River

basin. The Lost River system is a complex 90-

mile series of riverine segments, reservoirs, 

drains, canals, and wetlands (Tetra Tech, Inc., 

2005). Water returns from the Lost River basin

to the Upper Klamath River via the Lost River 

Diversion Channel (part of the year) and the 

Klamath Straits Drain (fig. 8). If particulate material did not enter the Lost River basin from the 

Klamath Project diversion canals, it is possible 

that return flows to the Klamath River from the 

Lost River basin would have lower concentrations of particulate matter and possibly dissolved 

material because forms of nutrients and organic 

matter could be transformed within the Lost River system. Due to the complexity of the Lost 

River system, which also includes Tule Lake and 

the Lower Klamath National Wildlife Refuge, it 

is difficult to estimate precisely how Lost River 

Diversion Channel and Klamath Straits Drain 

return-flow concentrations might change. Given 

this uncertainty, a bracketing approach was applied, with two end members and an intermediate 

condition for the return-flow concentrations.

Model runs for this scenario included:

5a. Particulates shunted at diversions. No 

change to Lost River Diversion Channel or Klamath Straits Drain return concentrations. (End 

member)

5b. Particulates shunted at diversions. Intermediate change to Lost River Diversion Channel 

and Klamath Straits Drain nutrients, algae, and 

organic matter concentrations.

5c. Particulates shunted at diversions. Dissolved oxygen concentrations set to saturation, 

and zeroed out concentrations of particulate and

dissolved nutrients, algae, and organic matter for

the Lost River Diversion Channel and Klamath 

Straits Drain returns. (End member)

Each of the end member runs (5a, 5c) is unlikely to occur individually, but their inclusion 

allows for the examination of the entire range of 

possible results.
24

The intermediate condition (5b) for Lost 

River Diversion Channel return-flow concentrations was estimated by reducing Lost River 

Diversion Channel algae, nutrients, and organic 

matter concentrations (both dissolved and particulate) by 0–50 percent, depending on how much 

the organic mass load was reduced at A Canal by 

particulate shunting; a 0-percent reduction was 

applied when no particulate shunting was occurring, and a 50-percent reduction was applied at 

maximum shunting. Concentrations were proportionately reduced for intermediate shunting 

values. The 50 percent maximum was an estimate for this scoping exercise. Due to the 

configuration of the Lost River–Upper Klamath 

River systems, Lost River Diversion Channel 

return flows would only be affected by changes 

to the A Canal diversions, as the other three diversions are further downstream. Both 

particulate and dissolved concentrations were 

reduced in the return-flow concentrations because Aphanizomenon flos-aquae (AFA), which 

makes up most of the Upper Klamath Lake algae 

in summer, has been found to decay quickly in 

the Klamath River (Sullivan and others, 2010); 

decay releases dissolved nutrients and organic 

matter, so removal of AFA would likely decrease 

dissolved nutrients and organic matter also.

The intermediate condition (5b) for Klamath 

Straits Drain return-flow concentrations was estimated by reducing Klamath Straits Drain algae, 

nutrients, and organic matter concentrations 

(both dissolved and particulate) by up to 50 percent, depending on how much the organic mass 

load was reduced at A Canal, as described above.

In addition, a minimum 10-percent reduction 

was instituted throughout each calendar year.

The Klamath Straits Drain is farther downstream 

from the A Canal diversion; however, water 

quality would also be affected by reduced particulate loading from the Lost River Diversion 

Channel, North Canal, and Ady Canal, the latter 

two of which withdraw water throughout the 

year (fig. 8).

The formulation of the intermediate condition for this scenario is only an estimate and 

subject to a great deal of uncertainty. To accurately formulate an intermediate reduction scenascenario, more information would be needed 

about travel time as well as the spatial and temporal dynamics of organic matter and nutrient 

transformations within the Lost River basin, including Tule Lake and the Lower Klamath 

National Wildlife Refuge. Collecting such data is 

outside the scope of this study, so only estimates 

were formulated for the intermediate scenario 

(5b). Should more information become available, 

it could be combined with existing knowledge 

about the system (for example, Risley and Gannett, 2006), and the formulation of this 

intermediate scenario could be revised.

Results of Scenario 5 Analyses

In all years, and at all seven ODEQ compliance locations, shunting particulate material 

away from the Klamath Project diversion canal 

intakes and into the Klamath River (scenarios 5a, 

5b, 5c) led to more days where dissolved oxygen 

standards in the Klamath River were violated 

compared to the current conditions base case (table 3). The number of days during which 

dissolved oxygen standards would be violated 

increased from an additional 10 to an additional 

78 days, depending on location, year, and scenario details. Considering all compliance locations 

and depending on the year, the number of dissolved oxygen violation days in scenario 5a, 5b, 

and 5c increased 24 to 32 percent from current 

conditions.
25

Table 3. Number of days the Klamath River would violate dissolved oxygen standards at the seven ODEQ compliance locations in the base case and particulate shunting scenarios for years 2006–09.

[Abbreviations: KF, Klamath Falls wastewater treatment plant; SSSD, South Suburban wastewater treatment plant; LRDC, Lost River Diversion Channel; KSD, Klamath Straits Drain; seg, model segment; TMDL, total maximum daily load; OM, organic matter; DO dissolved 

oxygen]

Scenario number and description

Days violating dissolved oxygen standard at compliance locations

Total for 

the 7 

compliance locations

KF 

inflow

SSSD 

inflow

LRDC 

inflow

Miller 

Island

KSD 

inflow KRS12a Keno

seg 4 seg 8 seg 19 seg 38 seg 69 seg 78 seg 95

2006

Base case (current conditions) 676 24 75 89 120 122 122 124

5a Shunt, LRDC and KSD current 894 102 120 126 131 137 138 140

5b Shunt, LRDC and KSD intermediate 894 102 120 126 131 137 138 140

5c

Shunt, LRDC and KSD zero OM, 

nutrients, and algae, with DO at 

saturation

883 102 120 126 130 134 135 136

2007

Base case (current conditions) 729 53 89 105 119 121 122 120

5a Shunt, LRDC and KSD current 949 98 119 130 141 151 153 157

5b Shunt, LRDC and KSD intermediate 948 98 119 130 141 151 153 156

5c

Shunt, LRDC and KSD zero OM, 

nutrients, and algae, with DO at 

saturation

930 98 119 128 139 146 148 152

2008

Base case (current conditions) 833 67 92 113 134 141 142 144

5a Shunt, LRDC and KSD current 1065 95 123 144 165 179 179 180

5b Shunt, LRDC and KSD intermediate 1065 95 123 144 165 179 179 180

5c

Shunt, LRDC and KSD zero OM, 

nutrients, and algae, with DO at 

saturation

1051 95 123 142 162 175 176 178

2009

Base case (current conditions) 854 80 102 120 133 139 139 141

5a Shunt, LRDC and KSD current 1100 100 123 137 157 192 193 198

5b Shunt, LRDC and KSD intermediate 1100 100 123 137 157 192 193 198

5c

Shunt, LRDC and KSD zero OM, 

nutrients, and algae, with DO at 

saturation

1060 100 123 136 155 180 180 186
26

The formulation of the Lost River Diversion 

Channel and Klamath Straits Drain return-flow 

concentrations (5a, 5b, 5c) had little effect on 

Upper Klamath River dissolved oxygen compliance in this scenario. Even between the end 

members, with unchanged water quality (5a) or

zero organic matter, nutrients, algae, and dissolved oxygen at saturation (5c), the numbers of 

days violating the dissolved oxygen standard only increased by 1 to 5 percent, depending on the 

year. The difference in simulated dissolved oxygen concentrations between the end member 

scenarios was more striking on a seasonal basis

in winter (fig. 10); however, dissolved oxygen 

concentrations were well above the standard at 

that time.

Figure 10. Graph showing 30-day mean dissolved oxygen concentrations at model segment 78 (site KRS12a) for 

the base case and scenarios 5a, 5b, 5c, and 5d in 2008. The relevant dissolved oxygen standard is also shown.

Several factors contribute to the lack of effect of the return-flow composition on Upper 

Klamath River dissolved oxygen compliance.

First, the Lost River Diversion Channel returnflow concentration was only affected by A Canal 

particulate shunting for a short period of time

during conditions when both the Lost River Diversion Channel flowed towards the Klamath 

River (mostly in winter) and the A Canal was 

withdrawing (summer) (fig. 8). Also, while the 

other return-flow canal, Klamath Straits Drain,

did flow into the Klamath River all year, it was 

noted in the scenario 3 analysis that changes to 

point and nonpoint sources had relatively small 

effects on Upper Klamath River dissolved oxygen concentrations when Link River loads were 

high. In any case, even though the differences 

between runs 5a and 5c can be quantified and 

might be important under some circumstances, 

the effects are small in terms of the dissolved 

oxygen budget under scenario 5 conditions.

This scenario demonstrates the importance 

of the diversion canal operation on Upper Klamath River water quality. If particulate matter is 

not withdrawn and the particulate is shunted 

back to the Klamath River, then dissolved oxygen conditions in the river would worsen. It is of 

course possible that shunted material could be 

removed from the river as part of the shunting 

process; in this case there would be no change to

Klamath River particulate loading at the diversion locations during shunting, but some 

improvements in Klamath River dissolved oxygen conditions might result from improved water 

quality in the return flows.
27

Future model scenarios will examine the effects of not only changing water quality in the 

diversion canals, but the effect of changing flows

as well. Future runs will also include an analysis 

of the effects of particulate shunting on compliance with water-quality standards for 

parameters other than dissolved oxygen.

Acknowledgments

Funds for this study were provided by the 

Bureau of Reclamation. Discussions with Jason 

Cameron, Rick Carlson, and Jessica Asbill-Case 

(Reclamation) were helpful at various stages of 

the project. The authors are grateful to Dan 

Turner (Oregon Department of Environmental 

Quality) for his helpful discussions of the dissolved oxygen standard and sharing ideas for 

post-processing of model output.

References Cited

Bureau of Reclamation, 2005, Natural flow of 

the Upper Klamath River—Phase I: Accessed 

March 22, 2012, at http://www.usbr.gov/mp/

kbao/docs/undepleted_klam_fnl_rpt.pdf.

Cole, T.M., and Wells, S.A., 2008, CE-QUALW2—A two-dimensional, laterally averaged, 

hydrodynamic and water-quality model, version 3.6: U.S. Army Corps of Engineers, 

Instruction Report EL-08-1 [variously paged].

Deas, M.L., and Vaughn, J., 2011, Keno Reservoir particulate study 2008—Technical 

memorandum, Prepared for the Bureau of Reclamation, Klamath Basin Area Office, April 

2011: Davis, Calif., Watercourse Engineering, 

Inc., 38 p.

Mrazik, S., 2007, Oregon water quality index 

summary report, water years 1997–2006: Oregon Department of Environmental Quality, 

DEQ07-LAB-007-TR, 13 p.

Oregon Department of Environmental Quality, 

2007, Oregon’s 2004/2006 integrated report: 

Accessed November 16, 2007, at 

http://www.deq.state.or.us/wq/assessment/rpt0

406.htm.

Oregon Department of Environmental Quality, 

2010, Upper Klamath and Lost River subbasins total maximum daily load (TMDL) and 

water quality management plan (WQMP): Accessed March 22, 2012, at

http://www.deq.state.or.us/WQ/TMDLs/

klamath.htm.

Oregon Department of Environmental Quality, 

2011, Oregon Administrative Rules OAR 340-

041: Oregon Secretary of State Archives, accessed October 21, 2011, at 

http://arcweb.sos.state.or.us/pages/rules/oars_

300/oar_340/340_041.html.

Poulson, S.R., and Sullivan, A.B., 2010, Assessment of diel chemical and isotopic 

techniques to investigate biogeochemical 

cycles in the Upper Klamath River, Oregon, 

USA: Chemical Geology, v. 269, no. 1–2, p. 

3–11.

Risley, J.C., and Gannett, M.W., 2006, An evaluation and review of water-use estimates and 

flow data for the Lower Klamath and Tule 

Lake National Wildlife Refuges, Oregon and 

California: U.S. Geological Survey Scientific 

Investigations Report 2006–5036, 18 p. (Also 

available at http://pubs.er.usgs.gov/

publication/sir20065036.)

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 13, 2012, at 

http://or.water.usgs.gov/proj/keno_reach/down

load/klamath_river_model_review_final.pdf.

Rounds, S.A., and Sullivan, A.B., 2010, Review 

of revised Klamath River total maximum daily 

load models from Link River Dam to Keno 

Dam, Oregon: U.S. Geological Survey Administrative Report, 32 p., accessed April 13, 

2012, at http://or.water.usgs.gov/proj/

keno_reach/download/

klamath_model_rereview_final.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 

Dam to Keno Dam, Oregon, 2008: U.S. Geological Survey Open-File Report 2009–1105, 

25 p. (Also available at http://pubs.er.usgs.gov

/publication/ofr20091105.)
28

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. (Also available at 

http://pubs.er.usgs.gov/publication/

ofr20081185.)

Sullivan, A.B., Rounds, S.A., Deas, M.L., Asbill, 

J.R., Wellman, R.E., Stewart, M.A., Johnston, 

M.W., and Sogutlugil, I.E., 2011, Modeling 

hydrodynamics, water temperature, and water 

quality in the Klamath River upstream of Keno 

Dam, Oregon, 2006–09: U.S. Geological Survey Investigations Report 2011–5105, 70 p.

(Also available at http://pubs.er.usgs.gov/

publication/sir20115105.)

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.

Tetra Tech, Inc., 2005, Model configuration and 

results Lost River model for TMDL development—Prepared for U.S. Environmental 

Agency Regions 9 and 10, Oregon Department 

of Environmental Quality, and North Coast 

Regional Water Quality Control Board: Portland, Oregon [variously paged], accessed April 

13, 2012, at 

http://www.epa.gov/region9/water/tmdl/lostriver/AppendixATmdlModelReport-8-29-

05.pdf.

Tetra Tech, Inc., 2009, Klamath River model for 

TMDL development—Prepared for U.S. Environmental Agency Regions 9 and 10, Oregon 

Department of Environmental Quality, and 

North Coast Regional Water Quality Control 

Board: 196 p., accessed May 20, 2011, at 

http://www.deq.state.or.us/wq/tmdls/docs/klam

athbasin/uklost/KlamathLostAppendixC.pdf.

Watercourse Engineering, Inc., 2004, Klamath 

River modeling framework to support the PacifiCorp Federal Energy Regulatory 

Commission Hydropower Relicensing Application, March 9, 2004: Davis, California, 291 

p.

Weddell, B.J., 2000, Relationship between flows 

in the Klamath River and Lower Klamath Lake

prior to 1910—Report to U.S. Fish and Wildlife Service, Klamath Basin National Wildlife 

Refuges, Tulelake, California: Pullman, Washington, 12 p. 
29

Appendix—Code Changes to CE-QUAL-W2

To formulate the executable for the natural conditions and particulate shunting model runs, the following changes were made to the CE-QUAL-W2 source code (version 3.6 from the November 2010 

release). The original source code can be downloaded at http://or.water.usgs.gov/proj/keno_reach/

models.html

All code was compiled as described in the CE-QUAL-W2 manual (Cole and Wells, 2008) with the 

addition of the /fp:precise switch to force consistency in floating-point calculations.

A. Natural Conditions Code Changes

1. Changed code in temperature.f90 for tributary inputs

IF (TRIBUTARIES) THEN

DO JT=1,JTT

 IF (JB == JBTR(JT)) THEN

 I = ITR(JT)

 IF (I < CUS(JB)) I = CUS(JB)

 DO K=KTTR(JT),KBTR(JT)

 IF (QTR(JT) < 0) THEN

 TSS(K,I) = TSS(K,I) +T2(K,I)*QTR(JT)*QTRF(K,JT)

 TSSTR(JB) = TSSTR(JB)+T2(K,I)*QTR(JT)*QTRF(K,JT)*DLT

 ELSE

 TSS(K,I) = TSS(K,I) +T2(K,I)*QTR(JT)*QTRF(K,JT) ! SR 9/08/11

 TSSTR(JB) = TSSTR(JB)+T2(K,I)*QTR(JT)*QTRF(K,JT)*DLT ! SR 9/08/11

 ! TSS(K,I) = TSS(K,I) +TTR(JT)*QTR(JT)*QTRF(K,JT) ! SR 9/08/11

 ! TSSTR(JB) = TSSTR(JB)+TTR(JT)*QTR(JT)*QTRF(K,JT)*DLT ! SR 9/08/11

 END IF

 END DO

 VOLTRB(JB) = VOLTRB(JB)+QTR(JT)*DLT

 END IF

END DO

END IF

2. Changed code in wqconstituents.f90 for tributary inputs

IF (TRIBUTARIES) THEN

DO JT=1,JTT

 IF (JB == JBTR(JT)) THEN

 I = ITR(JT)

 IF (I < CUS(JB)) I = CUS(JB)

 DO K=KTTR(JT),KBTR(JT)

 IF (QTR(JT) < 0.0) THEN

 CSSB(K,I,JC) = CSSB(K,I,JC)+C1(K,I,JC)*QTR(JT)*QTRF(K,JT)

 ELSE

 CSSB(K,I,JC) = CSSB(K,I,JC)+C1(K,I,JC)*QTR(JT)*QTRF(K,JT) ! SR 08/26/11

 ! CSSB(K,I,JC) = CSSB(K,I,JC)+CTR(JC,JT)*QTR(JT)*QTRF(K,JT) ! SR 08/26/11

 END IF

 END DO

 END IF

END DO

END IF
30

B. Particulate Matter Shunting Code Changes

1. Changed code in endsimulation.f90 to accommodate FILTER_PARTICLES variable

DEALLOCATE (HYDRO_PLOT, SEDIMENT_RESUSPENSION, FILTER_PARTICLES)

2. Changed code in input.f90 to handle the new FILTER_PARTICLES variable

ALLOCATE (IWD(NWDT), KWD(NWDT), QWD(NWDT), EWD(NWDT), KTW(NWDT), KBW(NWDT), 

FILTER_PARTICLES(NWDT))

FILTER_PARTICLES = IWD < 0 ! SR 08/08/11

IWD = ABS(IWD) ! SR 08/08/11

3. Changed code in outputa.f90 to show filtered withdrawals correctly

IF (.NOT. FILTER_PARTICLES(JWD) .OR. &

 ( CN(JC) /= NPSI .AND. CN(JC) /= NLPOM .AND. CN(JC) /= NRPOM .AND. &

 CN(JC) /= NLPOMP .AND. CN(JC) /= NRPOMP .AND. CN(JC) /= NLPOMN .AND. CN(JC) /= NRPOMN .AND. &

 (CN(JC) < NSSS .OR. CN(JC) > NSSE ) .AND. &

 (CN(JC) < NAS .OR. CN(JC) > NAE ) .AND. &

 (CN(JC) < NZOOS .OR. CN(JC) > NZOOE) )) THEN ! SR 08/10/11

CSUM(CN(JC)) = CSUM(CN(JC))+C2(K,IWD(JWD),CN(JC))*QSW(K,JWD)

END IF ! SR 08/10/11

IF (.NOT. FILTER_PARTICLES(JWD) .OR. &

 ( CDN(JC,JWWD) == 1 .OR. CDN(JC,JWWD) == 4 .OR. CDN(JC,JWWD) == 9 .OR. &

 CDN(JC,JWWD) == 16 .OR. CDN(JC,JWWD) >= 19 )) THEN ! SR 08/11/11

CDSUM(CDN(JC,JWWD)) = CDSUM(CDN(JC,JWWD))+CD(K,IWD(JWD),CDN(JC,JWWD))*QSW(K,JWD)

ELSE IF (CDN(JC,JWWD) == 3) THEN ! filtered TOC = DOC ! SR 08/11/11

CDSUM(3) = CDSUM(3)+CD(K,IWD(JWD),1)*QSW(K,JWD) ! SR 08/11/11

ELSE IF (CDN(JC,JWWD) == 6) THEN ! filtered TON = DON ! SR 08/11/11

CDSUM(6) = CDSUM(6)+CD(K,IWD(JWD),4)*QSW(K,JWD) ! SR 08/11/11

ELSE IF (CDN(JC,JWWD) == 7) THEN ! filtered TKN = DON + NH4 ! SR 08/11/11

CDSUM(7) = CDSUM(7)+(CD(K,IWD(JWD),4)+C2(K,IWD(JWD),NNH4))*QSW(K,JWD) ! SR 08/11/11

ELSE IF (CDN(JC,JWWD) == 8) THEN ! filtered TN = DON + NO3 + NH4 ! SR 08/11/11

CDSUM(8) = CDSUM(8)+(CD(K,IWD(JWD),4)+C2(K,IWD(JWD),NNO3)+C2(K,IWD(JWD),NNH4))*QSW(K,JWD) ! SR 

08/11/11

ELSE IF (CDN(JC,JWWD) == 11) THEN ! filtered TOP = DOP ! SR 08/11/11

CDSUM(11) = CDSUM(11)+CD(K,IWD(JWD),9)*QSW(K,JWD) ! SR 08/11/11

ELSE IF (CDN(JC,JWWD) == 12) THEN ! filtered TP = DOP + PO4 ! SR 08/11/11

CDSUM(12) = CDSUM(12)+(CD(K,IWD(JWD),9)+C2(K,IWD(JWD),NPO4))*QSW(K,JWD) ! SR 08/11/11

END IF ! SR 08/11/11

4. Changed code in w2modules.f90 to declare FILTER_PARTICLES variable

LOGICAL, ALLOCATABLE, DIMENSION(:) :: FLUX, EVAPORATION, ZERO_SLOPE, FILTER_PARTICLES 

5. Changed code in wqconstituents.f90 to do particulate shunting

IF (WITHDRAWALS) THEN

DO JWD=1,JWW

 IF (.NOT. FILTER_PARTICLES(JWD) .OR. &

 ( JC /= NPSI .AND. JC /= NLPOM .AND. JC /= NRPOM .AND. &

 JC /= NLPOMP .AND. JC /= NRPOMP .AND. JC /= NLPOMN .AND. JC /= NRPOMN .AND. &

 (JC < NSSS .OR. JC > NSSE ) .AND. &

 (JC < NAS .OR. JC > NAE ) .AND. &

 (JC < NZOOS .OR. JC > NZOOE) )) THEN ! SR 08/08/11

 IF (QWD(JWD) /= 0.0) THEN

 IF (JB == JBWD(JWD)) THEN

 I = MAX(CUS(JBWD(JWD)),IWD(JWD))

 FORALL(K=KTW(JWD):KBW(JWD))

 CSSB(K,I,JC) = CSSB(K,I,JC)-C1S(K,I,JC)*QSW(K,JWD)

 END FORALL

 END IF

 END IF

 END IF ! SR 08/08/11

END DO

END IF
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Sullivan and others— Preliminary Results from Three Model Scenarios for the Klamath River Upstream of Keno Dam, Oregon—Open-File Report 2012–1101