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Three Lakes Water‐Quality Model Nutrient Sensitivity Analysis Final Report

January 27, 2014

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Three Lakes Water‐Quality Model Nutrient Sensitivity Analysis

Final Report

January 27, 2014

This report was prepared for the Three Lakes Nutrient Study Technical Committee

and funded by Northern Water and U.S. Bureau of Reclamation.

It was prepared by

Jean Marie Boyer, PhD, PE and Christine Hawley, MS Hydros Consulting Inc.

This report replaces the version

dated December 6, 2012.

Cover Photos: Compliments of Northern Water

Three Lakes Model Nutrient Sensitivity Analysis January 27, 2014 Page i

Hydros Consulting, 1731 15th Street, Suite 103, Boulder, CO 80302

Table of Contents

I. Introduction ............................................................................................................................................... 1

II. Three Lakes Water‐Quality Model and Nutrient Sources ...................................................................... 3

III. Scenarios Considered ............................................................................................................................. 8

IV. Water‐Quality Index Overview .............................................................................................................. 11

V. Overview of Results ................................................................................................................................ 13

VI. Conclusions and Recommendations .................................................................................................... 31

VII. References ........................................................................................................................................... 33

Appendix A ‐ Description of Scenarios Considered ................................................................................. A‐1

Appendix B ‐ Water‐Quality Index Documentation ................................................................................. B‐1

Appendix C ‐ Detailed Results –Reductions in System‐Wide Inflow Loads, Internal Loads, and

Stormwater Loads .................................................................................................................................... C‐1

Appendix D ‐ Detailed Results –Reductions in Loadings by Tributary ................................................... D‐1

Appendix E ‐ Detailed Results –Reductions by Nutrient – System‐Wide and Key Inflow Only ..............E‐1

List of Tables

Table 1. Nutrient Sources by Water Body .................................................................................................. 4

Table 2. Phosphorus and Nitrogen Loads to the Three Lakes System by Source for the Base

Case Model Run ............................................................................................................................. 7

Table 3. Summary of Nutrient Sensitivity Model Runs ............................................................................ 10

Table 4. Additional Metrics Compiled for Each Model Run ..................................................................... 12

Table 5. Summary of Results – Base Case and Ultra‐Clean Scenarios ..................................................... 16

Table 6. Comparison of Results – Significant Reductions in Loading by Type ...................................... 20

Table 7. Percent Load Reductions for Individual Tributary Scenarios, Relative to Base Case ............... 21

Table 8. Summary of Results – Significant Reductions by Reduced Loadings from Individual

Tributaries .................................................................................................................................... 24

Table 9. Summary of Results – Significant Reductions by Reduced Loadings from Pumped

Inflows ......................................................................................................................................... 25

Table 10. Summary of Results – Significant Reductions for All Sources by Nutrient ............................ 29

Three Lakes Model Nutrient Sensitivity Analysis January 27, 2014 Page ii


List of Figures

Figure 1. Box and Whisker Plot Summary of Historical Undepleted Colorado River Flow

Volumes ........................................................................................................................................ 9

Figure 2. 6‐Year Average WQI Results for Base Case and Ultra‐Clean Simulations (2005‐2010) ........... 14

Figure 3. 6‐Year Average WQI Results for Base Case, No Internal‐Loading, Pristine Inflows,

and No Stormwater Loading Simulations (2005‐2010) ............................................................. 18

Figure 4. 6‐Year Average WQI Results for Base Case and Individual Tributary and Pumped

Inflow Pristine Condition Simulations (2005‐2010) .................................................................. 22

Figure 5. 6‐Year Average WQI Results for Base Case and 25%, 50%, and 75% Phosphorus and

Nitrogen Load Reduction Simulations ..................................................................................... 27

List of Acronyms and Abbreviations

%tile ‐ percentile

Arap – Arapaho Creek

Avg ‐ average

C‐BT – Colorado‐Big Thompson

Chl a – chlorophyll a

d‐less – dimensionless

DO – dissolved oxygen

Inf ‐ inflow

Int ‐ internal

m ‐ meter

Mar ‐ March

Max ‐ maximum

mg/L – milligrams per liter

Min ‐ minimum

Mtn ‐ Mountain

N ‐ nitrogen

N/A – not applicable

NFork – North Fork

No. ‐ number

Nov ‐ November

Oct ‐ October

P ‐ phosphorus

Reduc ‐ reduction

SA – sensitivity analysis

Sept ‐ September

Three Lakes Model Nutrient Sensitivity Analysis January 27, 2014 Page iii


List of Acronyms and Abbreviations (Continued)

Std – standard

Stillwtr – Stillwater Creek

SW ‐ stormwater

TN – total nitrogen

TP – total phosphorus

Tribs ‐ tributaries

ug/L – micrograms per liter

WC – Willow Creek pump canal

WG – Windy Gap pipeline

WQI – water‐quality index

Three Lakes Model Nutrient Sensitivity Analysis January 27, 2014 Page 1 of 32


I. Introduction

The Three Lakes Nutrient Study Technical Committee (Technical Committee) embarked on an effort

to conduct nutrient sensitivity analysis model runs using the Three Lakes Water‐Quality Model.

Nutrient sensitivity analysis (SA) model runs involve modifying the amount of nutrient loading to the

Three Lakes system in order to determine the resultant water quality. The scenarios considered are

not necessarily realistic or feasible. They are designed to provide an understanding of bounding or

limits as to how the system might respond under hypothetical conditions and how responsive the

system is to various drivers that influence water quality.

The scenarios investigated were designed to address five key questions. These questions include:

1. What water quality would be anticipated in the Three Lakes if all nutrient loadings were

drastically reduced?

2. What is the relative influence of the different types of nutrient loading (inflow, internal, and

stormwater)1?

3. Of the inflowing tributaries and pumped sources, which one would improve water quality the

most if it were improved to “pristine” conditions?

4. With respect to nutrient loadings from all sources, is it better to focus on phosphorus or

nitrogen loading reductions?

5. Do any of the nutrient reduction scenarios result in improvements to one or more water

body and degradation to another?

In addition, it is understood that the water quality of the Three Lakes system is a function of

numerous types of complex variables and mechanisms. Nutrient loading is just one of several

forcing functions or drivers of in‐lake/reservoir water quality. Conditions such as operations,

weather, and hydrologic year were not varied for the six‐year model runs (2005‐2010). These

assumed conditions also define in‐lake/reservoir water quality and effectively provide limits on

potential improvements. In addition to evaluation of direct model output, model runs were

evaluated and compared using the Three Lakes Water‐Quality Index (WQI).

The remainder of the report is organized as follows:

1 Inflow = loading from all tributaries, pumped sources, and lake/reservoir gains; Internal = internal loading from

the bottom sediment; Stormwater = loads triggered by the timing and magnitude of precipitation events.

Stormwater loads include increased loading delivered via channelized runoff, unchannelized runoff, and/or

groundwater inflows in response to a storm event.



Section II. Three Lakes Water‐Quality Model and Nutrient Sources – This section presents an

overview of the water‐quality model used in this analysis as well as the sources of

nutrients to the Three Lakes, as simulated in the model.

Section III. Scenarios Considered – A summary of the scenarios simulated to conduct the sensitivity analysis is presented.

Section IV. Water‐Quality Index Overview – A brief overview of the index applied to evaluate model results is provided.

Section V. Overview of Results – This section presents a summary of the results of the sensitivity analysis simulations, focusing on the five key questions listed above.

Section VI. Conclusions and Recommendations – In this final section, findings from the sensitivity analysis are listed and discussed.

Additional details regarding the scenarios considered (Appendix A), the water‐quality index

(Appendix B), and model runs results (Appendices C‐E) are located at the end of this report.



II. Three Lakes Water‐Quality Model and Nutrient Sources

The Three Lakes Water‐Quality Model (Boyer and Hawley, anticipated 2014) is a dynamic, mechanistic

model that simulates in‐lake/reservoir water quality for Grand Lake, Shadow Mountain Reservoir, and

Granby Reservoir. Operations of the Colorado‐Big Thompson Project (C‐BT) and the Windy Gap

Project are an integral part of the model. Several constituents are simulated including phosphorus,

nitrogen, chlorophyll a, dissolved oxygen, Secchi depth, and organic carbon. Grand Lake and Granby

Reservoir are represented as three‐layer water bodies and Shadow Mountain Reservoir is

characterized as one well‐mixed layer. The model has been calibrated for the period 2005‐2010 and

represents “base case” conditions for the nutrient sensitivity analysis model runs.

The version of the model used for this study incorporates recent refinements and testing including:

A more accurate quantification of inflows from Stillwater Creek (Hawley and Boyer, 2012a);

Flow adjustments for the Roaring Fork, Columbine Creek, and gains/losses to the system;

Incorporation of water‐quality data recently collected on the Roaring Fork;

Incorporation of internal load release rates for phosphorus and ammonia based on nutrient

profiles collected in Shadow Mountain Reservoir in 2010;

Incorporation of over 50 additional Secchi‐depth observations (for all three water bodies,

mostly in 2008) which had not been received until late 2011;

Validation of the model against 2011 observed conditions (high runoff, 16 week summer Farr

stop‐pump , high Grand Lake clarity);

Water‐quality data modifications based on additional QA/QC of the water‐quality database

(Stephenson, 2013);

Refinements to water‐quality assumptions for gains; and

Refinements to Columbine Creek water‐quality assumptions.

The Three Lakes Water‐Quality Model accounts for the loading of nutrients into the system from

several sources (Table 1).



Table 1. Nutrient Sources by Water Body

Source

Receiving Water Body

Grand Lake

Shadow Mtn Reservoir

Granby Reservoir

North Inlet

East Inlet

North Fork

Arapaho Creek

Stillwater Creek

Windy Gap Pipeline

Willow Creek Pump Canal

Roaring Fork

Columbine Creek

Direct Precipitation onto the Lake/Reservoir

Lake/Reservoir Gains

Internal Loading from the Bottom Sediments

Loads Triggered by the Timing and Magnitude of Stormwater Events

Note that in addition to nutrients, a number of other constituents must be specified as input into the

model for each source listed in Table 1 (internal loading and stormwater loading excepted). These

other constituents include dissolved organic carbon, non‐algal particulate organic carbon,

chlorophyll a, dissolved oxygen, herbivorous zooplankton, carnivorous zooplankton, and inorganic

suspended solids.

Nutrient loads are a function of flow and concentration and are based on measurements, when

available. Nutrient loads for North Inlet, East Inlet, North Fork, Arapaho Creek, Stillwater Creek,

Windy Gap Pipeline, and Willow Creek Pump Canal are based on flow measurements and water‐

quality observations during 2005‐2010. Flows for Roaring Fork and Columbine Creek (both of which

are ungaged2) were estimated based on regressions and historical ratios. Roaring Fork water quality

is characterized based on measurements taken since 2007 while the concentrations in Columbine

Creek are assumed to match those of the Roaring Fork (no samples are analyzed from Columbine

Creek). Precipitation concentrations are based on measurements taken in the early 2000’s during

2 A gage on the Roaring Fork became operational in 2012.



the Three Lakes Clean Lakes Watershed Assessment Study (Hydrosphere Resource Consultants,

2003). Lake and reservoir gains are estimated based on a system‐wide water balance. Gain water

quality is assumed to be that of North Inlet for Grand Lake, the North Fork for Shadow Mountain

Reservoir, and Arapaho Creek for Granby Reservoir. This assumption (using concentrations from the

major tributary for each water body), was made based on the timing of the gains, which dominate

during runoff.

Stormwater loads occur based on the amount of precipitation. When precipitation levels reach 0.2

inches per day, a specified amount of nutrients are added to each water body. On days with over 0.3

inches per day, an increased amount of nutrients are added to reflect higher loading. The amount of

nutrients added was determined during model calibration. Stormwater loading only occurs during

the April through October time period. Additional information regarding major assumptions and

model inputs is located in Boyer and Hawley (anticipated 2014).

Stormwater contributions are incorporated into the model as additional loads based on daily

precipitation patterns. It is important to note that loadings entering the lake/reservoirs during

stormwater events could originate from a variety of sources including 1) significant increases in

surface inflow concentrations (that are not observed during routine monitoring) and 2) increased

sub‐surface loading, due to septic systems or other sources. Auto‐samplers can be used to capture

any increases in concentration during precipitation events – which can be significant. Focused

stormwater monitoring is highly recommended to further investigate this phenomenon for the Three

Lakes system.

Internal loading rates are based on nutrient profiles taken in Shadow Mountain Reservoir in 2010 and

the calibration process. Additional monitoring is also recommended to help ground the assumptions

made based on 2010 measurements. Nutrient loading from the decomposition of macrophytes in

Shadow Mountain Reservoir was accounted for using guidance from the literature (Carpenter, 1980)

and the model calibration process.

Annual average Base Case loadings, are described in Table 2, along with volume‐weighted average

concentrations. The sources listed in Table 2 are system‐wide, and thus do not include loading from

one water body to another (e.g., Farr pumping and channel flows). Note that the combination of

stormwater loading and internal loading accounts for over 50% of the total annual loading for both

nutrients.

Caution needs to be taken when drawing conclusions from the information in Table 2. Loading is

reported on an annual basis for total phosphorus and total nitrogen. One needs to note that there

are differences between the individual sources and based on the magnitude of annual loading, they

cannot be compared directly in terms of water‐quality response. The sources differ by:

Sub‐Species – the response from a reduction in ammonia (readily bioavailable) differ from

the response to a reduction in organic nitrogen (not readily bioavailable);



Location of Entry into the System ‐‐ loading into the epilimnion produces a different response

than loading into the hypolimnion; and

Timing of Loading – loading in August leads to a different response than a loading introduced

in November.

Thus, although loading may be dominated by a particular source, this does not mean that a

significant reduction from that source will cause a greater improvement than reductions from

another source. The development of a follow‐up memorandum to this report has been discussed to

describe these differences in more detail and implications regarding future management strategies.



Table 2. Phosphorus and Nitrogen Loads to the Three Lakes System by Source for the Base Case Model Run (Average Annual Loads for 2005‐2010)

Source

Total Phosphorus Total Nitrogen

Load (kg/year)

Conc* (ug/L)

% of Total Load

Load (kg/year)

Conc* (ug/L)

% of Total Load

Internal Loading 10,091 N/A 37.2% 64,430 N/A 24.9%

Stormwater Loading 6,391 N/A 23.5% 70,552 N/A 27.3%

Windy Gap 2,244 62.8 8.3% 16,633 465 6.4%

Willow Creek 2,006 33.7 7.4% 13,670 230 5.3%

North Fork 1,870 33.9 6.9% 14,884 270 5.8%

Stillwater Creek 1,262 112.1 4.6% 5,265 468 2.0%

Lake/Reservoir Gains 977 16.0 3.6% 16,129 265 6.2%

Arapaho Creek 745 8.3 2.7% 18,075 202 7.0%

North Inlet 722 11.0 2.7% 16,831 257 6.5%

East Inlet 380 8.3 1.4% 10,761 235 4.2%

Direct Precipitation 352 28.0 1.3% 8,822 701 3.4%

Roaring Fork 68 6.6 0.2% 1,644 161 0.6%

Columbine Creek 45 6.6 0.2% 1,103 161 0.4%

SMR Macrophytes 3 N/A 0.0% 25 N/A 0.0%

Total 27,157 N/A 100% 258,823 N/A 100% N/A –Not applicable. Indicates source term for which average, volume‐weighted concentrations cannot be

calculated due to lack of corresponding volume information.

* Concentration computed as a volume‐weighted annual average (2005‐2010).



III. Scenarios Considered

As described in Section I, several key questions guided the design of model sensitivity runs

conducted for this work. Twenty‐four model runs were made, reducing nutrient loading by type of

load (inflow, internal, or stormwater), type of nutrient (nitrogen or phosphorus), or by individual

tributary or pumped inflow. Other than the altered source, all aspects of the model were unchanged

from the Base Case. Thus, all flows (including operations) were assumed to be the same between

runs, reflecting actual conditions from 2005 through 2010. None of the model runs represent pre‐C‐

BT conditions where flow (for Grand Lake) would occur only in the direction of East Inlet and North

Inlet to the Colorado River. In addition, none of the model runs considers conditions where nutrient

loading is completely eliminated. Finally, initial conditions (in‐lake/reservoir concentrations and

lake/reservoir contents at the beginning of the simulation) remained unchanged for each model run.

The 24 model runs conducted for this analysis are listed in Table 3 and specific assumptions can be

found in Appendix A. Runs 1‐11 involve significant reductions in inflow loading, internal loading,

and/or stormwater loading, on a system‐wide basis. Runs 12‐16 focus on large improvements for

major tributaries / pumped inflows. The rest of the runs are focused on reductions in either

phosphorus or nitrogen. In some cases, inflow concentrations were assumed to be “pristine”. A six‐

year time series of concentrations for all input constituents was developed to represent these

conditions. This time series was developed based on the lowest concentrations observed (with the

exception of dissolved oxygen, which was based on the highest concentrations) for all of the

tributaries. Thus, concentrations are low, but not unreasonable for this system. It is recognized that

“pristine” is an imperfect description of these simulated conditions, as truly “pristine” or

unimpacted conditions (anthropogenically) for the Three Lakes watershed no longer exist. The term

is applied throughout the document consistently as a brief descriptor of the select lower

concentration tributary conditions observed within the watershed (described above) that may

reflect more natural/less impacted conditions.

All model runs are compared to a simulation termed “Base Case”. The Base Case refers to the

simulation of actual 2005‐2010 conditions applying observed loads. The term “Base Case” should not

be confused with “Baseline” conditions, as applied in a regulatory sense. The 2005‐2010 simulation

covers a wide range of hydrologic, meteorological and operation conditions; however, these years

were selected due to excellent data availability and are not intended to specifically represent the

range or average of long‐term conditions. For perspective, estimated historical (1954‐2010)

undepleted flows in the Upper Colorado River were compared to 2005‐2010 undepleted flows

(values provided by Northern Water [Vincent, 2012]). A box and whisker plot of the range of

historical undepleted flow volumes for the full calendar year and for the April through July runoff

period is displayed in Figure 1. As shown, 2005 through 2010 hydrologic conditions range from the

25th to 71st percentile, averaging at the 51st percentile. The spring runoff period (April through July)

results show the same pattern, with 2005 through 2010 falling between the 21st and 73rd percentiles,

also averaging at the 51st percentile of the 1954‐2010 record.



Figure 1. Box and Whisker Plot Summary of Historical Undepleted Colorado River Flow Volumes

Although numerous model runs were conducted, the discussion in Section V (Overview of Results)

focuses on a subset of model runs to address each question posed. Detailed results for all scenarios

investigated are available in Appendices C‐E.



Table 3. Summary of Nutrient Sensitivity Model Runs

No. Scenario Name Description of Change from Base Case

1 Ultra‐Clean

All inflows assumed “pristine” All internal loading eliminated

All stormwater loading eliminated

2 Int‐50% All internal loading rates reduced by 50%

3 Int‐Off All internal loading eliminated

4 Inf ‐50% All inflow P and N concentrations reduced by 50%

5 Inf‐Pristine All inflows assumed “pristine”

6 SW‐50% All stormwater loading reduced by 50%

7 SW‐Off All stormwater loading eliminated

8 Inf/Int‐50% All inflow P and N concentrations reduced by 50%

All internal loading rates reduced by 50%

9 Int/SW‐50% All internal loading rates reduced by 50%

All stormwater loading reduced by 50%

10 Inf/SW‐50% All inflow N and P concentrations reduced by 50%


11 Inf/Int/SW 50%

All inflow N and P concentrations reduced by 50%

All internal loading rates reduced by 50%


12 Stillwtr Pristine Stillwater Creek assumed “pristine”

13 Arap Pristine Arapaho Creek assumed “pristine”

14 WC Pristine Willow Creek assumed “pristine”

15 WG Pristine Windy Gap assumed “pristine”

16 NFork Pristine North Fork assumed “pristine”

17 1/2 P ‐ 5 Key Tribs Phosphorus loads reduced by 50% for Key Tribs*

18 1/2 N ‐ 5 Key Tribs Nitrogen loads reduced by 50% for Key Tribs*

19 25% Reduc All P Reduce phosphorus in inflows, internal load, and stormwater load by 25%



22 25% Reduc All N Reduce nitrogen in inflows, internal load, and stormwater load by 25%

23 50% Reduc All N Reduce nitrogen in inflows, internal load, and stormwater load by 50%

24 75% Reduc All N Reduce nitrogen in inflows, internal load, and stormwater load by 75% *Key tributaries = Stillwater Creek, Arapaho Creek, Windy Gap, Willow Creek, and North Fork



IV. Water‐Quality Index Overview

A water‐quality index (WQI) was developed to serve as a tool to compile and rank water‐quality

responses simulated by the Three Lakes Model. Using this type of approach, conditions for the

overall system ‐ encompassing the three water bodies and multiple water‐quality parameters ‐ can be

described using a single index. In addition to simplifying interpretation of model results, the WQI

was needed to align the Technical Committee’s specific objectives with a decision‐making approach

in advance of performing model simulations.

To meet the specific model evaluation needs of the Technical Committee, a site‐specific WQI was

developed for the Three Lakes system (Hawley and Boyer, 2012b – also see Appendix B). A five‐step

process to develop the WQI was defined and utilized, based on review of the literature.

After numerous discussions, the Technical Committee selected three parameters for inclusion in the

WQI: clarity (as measured by Secchi depth), chlorophyll a, and dissolved oxygen (DO). Measures of

these parameters were selected to reflect a combination of the Technical Committee’s water‐quality

concerns and existing/proposed water‐quality standards:

Secchi depth is assessed as the average Secchi depth from July through September 153;

Chlorophyll a is assessed as the average chlorophyll a concentration from March through

November; and

Dissolved Oxygen is assessed as the minimum DO in the epilimnion for each calendar year.

Each metric is converted into subindex scores that range from 1 to 100 and WQI results for each lake

(also ranging from 1 to 100) are generated from those values, by year. Subindex scores from all three

water bodies are added and divided by three to produce a system‐wide score, with a possible range

of 1 to 100. Details of subindex transformations and lake WQI compilation approaches and formulas

are presented in Appendix B. For the nutrient sensitivity simulations, six years are simulated for each

run. System‐wide WQI results for each run are an average of the annual system‐wide WQI results for

each of the six years. Results for each model run are compared to the Base Case (2005‐2010). For

the Base Case run, the system‐wide WQI result is 70 out of a possible 100.

In development of the WQI, the Technical Committee also decided that a table of additional metrics

should be compiled for each modeling run for review in conjunction with numerical index results.

Table 4 presents the list of additional metrics identified by the Technical Committee for development

of each run. For this analysis, all additional metrics results were reviewed, all are provided in

Appendices C through E, and select metrics are presented in the main report.

3 This metric for Secchi depth differs from the metric for the proposed standard (15th percentile assessed from July through

September). It was selected by the Technical Committee for use in computing WQIs as a reflection of average conditions

during the peak tourism season. The metric for the proposed standard is reported for each run/year in the additional

metric table.



Table 4. Additional Metrics Compiled for Each Model Run

Parameter Metric Units

Dissolved Oxygen

Granby Reservoir ‐ DO (epilimnion), # days/yr <6 mg/L days

Shadow Mtn Reservoir ‐ DO, # days/yr <6 mg/L days

Grand Lake – DO (epilimnion) , # days/yr <6 mg/L days

Granby Reservoir – Min DO (mid‐Oct‐ through July) mg/L

Shadow Mtn Reservoir – Min DO (mid‐Oct‐ through July) mg/L

Grand Lake – Min. DO (mid‐Oct‐ through July) mg/L

Chlorophyll a

Granby Res. – Chl a, July‐Sept, # days >8 ug/L days

Shadow Mtn Reservoir – Chl a, July‐Sept, # days >8 ug/L days

Grand Lake – Chl a, July‐Sept, # days >8 ug/L days

Granby Reservoir – Chl a, July‐Sept, Max ug/L

Shadow Mtn Reservoir – Chl a, July‐Sept, Max ug/L

Grand Lake – Chl a, July‐Sept, Max ug/L

Granby Reservoir – Chl a, July‐Sept, Average ug/L

Shadow Mtn Reservoir – Chl a, July‐Sept, Average ug/L

Grand Lake – Chl a, July‐Sept, Average ug/L

Secchi Depth

Grand Lake – Secchi Depth, July‐Sept, # days <4 m days

Grand Lake – Secchi Depth, July‐Sept, Max m

Grand Lake – Secchi Depth, July‐Sept, Min m

Grand Lake – Secchi Depth, July‐Labor Day., 15th %ile m

Grand Lake – Secchi Depth, July‐Sept, 15th %ile (Proposed Std.) m



V. Overview of Results

In this section, we focus on addressing five key questions:

1. What water quality would be anticipated in the Three Lakes if all loadings were drastically

reduced?

2. What is the relative influence of the different types of nutrient loading (inflow, internal, and

stormwater)?

3. Of the inflowing tributaries and pumped sources, which one would improve water quality the

most, if it were improved to “pristine” conditions?

4. With respect to nutrient loadings from all sources, is it better to focus on phosphorus or

nitrogen loading reductions?

5. Do any of the nutrient reduction scenarios result in improvements to one or more water

body and degradation to another?

Model comparisons are based predominantly on the WQI and “additional metrics” developed for this

purpose to reflect the water‐quality concerns of the Technical Committee. As described in Section

IV, the WQI is based on three factors – chlorophyll a, water clarity, and dissolved oxygen.

It is important to understand that there are a number of factors influencing the three variables

included in WQI computations. As such, nutrient loading is not the only factor influencing these

three variables. For example,

Chlorophyll a concentrations are a function of several variables including light, water

temperature, phosphorus concentrations, nitrogen concentrations, the ratio of nitrogen to

phosphorus, zooplankton concentrations and predator–prey relationships, algal respiration,

settling, excretion, inflows, and outflows;

Water clarity is a function of non‐algal organic particulate matter, chlorophyll a

concentrations, inorganic suspended solids concentrations, and dissolved organic carbon;

and

Dissolved oxygen is a function of decomposition of organic matter, nitrification, chlorophyll

a concentrations, zooplankton dynamics, reaeration, and sediment oxygen demand, among

other mechanisms.

Detailed output for all of the model runs, including the additional metrics and individual parameter

results, are presented in Appendices C‐E.

Question 1: How “good” would water quality be if all loadings were drastically reduced?

In order to address this question, the results from the “Ultra‐Clean” model run are compared to the

Base Case. The Ultra‐Clean model run assumes 1) no internal nutrient loading, 2) no stormwater

nutrient loading, and 3) the water quality of all of the inflows (with the exception of precipitation)

matches pristine conditions (see Section III). The Ultra‐Clean simulation corresponds to a net



reduction of 89% of the total phosphorus load and 75% reduction of the total nitrogen load. Note

that the Ultra‐Clean run assumes reductions in more than nutrients – it also assumes reductions in

inorganic suspended solids and non‐algal particulate organic carbon, to simulate a more reasonable

formulation of pristine water quality. Operations and hydrologic conditions were not changed

between scenarios (2005‐2010 actual observations provided inputs). Detailed results for each of

these runs are included Appendix C.

The average 6‐year system WQI scores for the two runs are shown in. Water body‐specific WQI

results and key metrics for these scenarios are presented in Table 5, and discussed below.

Figure 2. 6‐Year Average WQI Results for Base Case and Ultra‐Clean Simulations (2005‐2010)

WQI – The Ultra‐Clean scenario results in an improvement in the 6‐year average, system‐wide WQI

from 70 to 81, out of the maximum achievable system‐wide score of 100. For the individual water

bodies, Grand Lake shows the greatest improvement in WQI (75‐92), followed by Shadow Mountain

Reservoir (44‐57). Granby Reservoir also improves, but less so, reaching a score of 93 (from 91).

Chlorophyll a – Both average and peak chlorophyll a concentrations exhibit large decreases for all

three water bodies under the Ultra‐Clean scenario. Interestingly, the averages drop to similar

concentrations (0.2 – 0.4 ug/L) for each water body. Shadow Mountain Reservoir, with the highest

Base Case averages, shows the largest improvement. Maximum chlorophyll a concentrations exhibit

a similar pattern. It should be noted that the average summer chlorophyll a concentrations for the

Ultra‐Clean scenario drop below 1 ug/L in all three water bodies over the six years, which could result

in a decrease in productivity of the fisheries, though an adverse effect is uncertain. Further, Shadow

Mountain Reservoir and Grand Lake improve from an average of 30 and 13 days per year with

chlorophyll a concentrations greater than 8 ug/L, respectively, to zero days per year greater 8 ug/L.

Overall, the greatest improvement in chlorophyll a concentrations was seen in Shadow Mountain

Reservoir, followed by Grand Lake.



Clarity – All three water bodies exhibit large improvements in average and maximum water clarity

under the Ultra‐Clean scenario. The maximum predicted Secchi depth (July – September) in Grand

Lake for the six‐year period is 8.8 meters (from 6.1 m in the Base Case). Although there are large

improvements in Grand Lake water clarity, it does not meet the proposed 4.0 meter standard on

average using the metric for the proposed clarity standard (15th %ile from July through September).

Looking at the individual years, however, the 4.0 m standard is simulated to be met for 2 of the 6

years considered under Ultra‐Clean conditions.

Dissolved Oxygen – Minimum epilimnetic dissolved oxygen concentrations do not show a significant

change (≤0.1 mg/L) in any water body for the Ultra‐Clean scenario, relative to the Base Case.

Interestingly, the number of days per year of concentrations less than 6 mg/L increases slightly in

Shadow Mountain Reservoir for the Ultra‐Clean scenario (from 51 to 53). This response is the result

of reduced algae concentrations and corresponding reduction in algal photosynthetic production of

dissolved oxygen.

The effect of the Ultra‐Clean scenario on minimum dissolved oxygen concentrations in Shadow

Mountain Reservoir is better understood with consideration of the modeling assumptions and

assessment of what controls dissolved oxygen in that water body. First, key sources of DO to the

epilimnion, such as reaeration and inflowing tributary/pumped source dissolved oxygen

concentrations, do not differ significantly between the model runs. Secondly, rates of sediment

oxygen demand do not differ between the scenarios. It is understood that rates of sediment oxygen

demand may decrease to some extent, based on a decrease in the amount of organic matter

(including algae) that settles to the sediments and subsequently decomposes. This dynamic is not

captured in the current version of the model. Thus, the most significant change to the well‐mixed,

single layer of Shadow Mountain Reservoir with the Ultra‐Clean scenario is a decrease in oxygen

supplied via photosynthesis. The result is a slight decrease to the minimum annual DO and a slight

increase in the number of days when DO is below 6 mg/L. For the stratified water bodies (Grand

Lake and Granby Reservoir), changes in other mechanisms (e.g., reaeration, diffusion with the

metalimnion, algal and zooplankton respiration, advection, decomposition) make up for the

reduction in oxygen due to photosynthesis.



Table 5. Summary of Results – Base Case and Ultra‐Clean Scenarios

Metric Unit Base Case Ultra‐Clean Change

System‐Wide WQI d‐less 70 81 +11

GRAND LAKE

Lake WQI d‐less 75 92 +17

Chl a Avg (Mar‐Nov) ug/L 2.9 0.2 ‐2.7

Chl a Avg (July‐Sept) ug/L 5.1 0.4 ‐4.7

# Days/Yr > 8 ug/L Chl a days 13 0 ‐13

Chl a Max (July‐Sept) ug/L 8.8 0.7 ‐8.1

Secchi Depth 15th %tile (July‐Sept)* m 2.1 (1.6‐2.6) 3.9 (3.6‐4) +1.8

Secchi Depth Avg. (July‐Sept 15) m 3.0 5.4 +2.4

Secchi Depth Maximum** m 6.1 8.8 +2.7

Min Epilimnetic DO mg/L 6.7 6.7 0

# Days/Yr < 6 mg/L Epilimnetic DO days 0 0 0

SHADOW M

TN RESERVOIR




# Days/Yr > 8 ug/L Chl a days 30 0 ‐30


Secchi Depth Avg (July‐Sept 15) m 1.9 3.7 +1.8

Minimum DO mg/L 5.3 5.2 ‐0.1

# Days/Yr < 6 mg/L DO days 51 53 +2

GRANBY RESERVOIR




# Days/Yr > 8 ug/L Chl a days 0 0 0


Secchi Depth Avg (July‐Sept 15) m 5.8 9.0 +3.2

Min Epilimnetic DO mg/L 6.7 6.6 ‐0.1


d‐less – indicates dimensionless All metrics computed for each year, then averaged over the six‐ year period, unless otherwise noted *Six‐year range in parentheses **Maximum daily value over entire six‐year simulation for the period July through September



Summary

Comparison of the Ultra‐Clean scenario to the Base Case was performed to bound potential water‐

quality improvements for all three water bodies in response to significant reductions in nutrients and

other constituents. The results indicate that a drastic reduction in loading would produce major

improvements in water quality in all three water bodies, with the greatest improvements in

chlorophyll a concentrations and clarity. The results from the Ultra‐Clean scenario indicate a

decrease in average March through November chlorophyll a concentrations of 2.4 ug/L (Granby

Reservoir), 2.7 ug/L (Grand Lake), and 4.0 ug/L (Shadow Mountain Reservoir) over the six‐year

simulation. For clarity, results for the Ultra‐Clean scenario indicate improvements in average Secchi

depth (July‐Sept 15) that range from more than 3 m for Granby Reservoir to 1.8 m for Shadow

Mountain Reservoir. The improvement for Grand Lake is 2.4 m over the six‐year simulation.

Although there are large improvements in Grand Lake water clarity, the metric used to evaluate the

proposed clarity standard (15th %ile from July through September) does not meet the proposed 4.0

meter standard on average. Looking at the individual years, however, the 4.0 m standard is

simulated to be met for 2 of the 6 years considered under Ultra‐Clean conditions. For minimum

dissolved oxygen concentrations in the epilimnion, however, these simulations indicate that there

would be no significant changes (≤0.1 mg/L).

Question 2: What is the relative influence of the different types of nutrient loading (inflow, internal, and stormwater)?

To address this question, three sensitivity analysis runs are compared to Base Case. Each run

essentially “turns off” or drastically reduces one type of nutrient loading into the system:

1. Pristine Inflows ‐ For the first run, the water quality of all inflows into the system (including

all tributaries and pumped flows) is set to pristine conditions (see Section III). Note that this

involves reductions on constituents other than nutrients, such as inorganic suspended solids

and non‐algal particulate organic matter, in order to simulate a more reasonable formulation

of pristine water quality. Internal nutrient loading rates and stormwater nutrient loading are

not changed from the Base Case. Nutrient reductions for the Pristine case correspond

roughly to 29% reductions in total phosphorus load and 23% reductions in total nitrogen load,

relative to the Base Case.

2. No Internal Loading ‐ The second run involves running the Base Case without internal

nutrient loading for all three water bodies. All other loading for this scenario is the same as

Base Case. Removing internal loading amounts to a 37% reduction in the total phosphorus

load and a 25% reduction in the total nitrogen load, relative to the Base Case.

3. No Stormwater Loading ‐ The third scenario assumes no stormwater nutrient loading for all

three water bodies. All other loading for this scenario is the same as Base Case. Removing

stormwater loading amounts to a 24% reduction in the total phosphorus load and a 27%

reduction in the total nitrogen load, relative to the Base Case.



Note that, as described earlier, nutrient sub‐species, timing, and spatial distribution (e.g. water‐body

layer introduced) of each of these loading sources vary considerably. This will lead to different types

of water‐quality responses for the same nutrient reduction.

Detailed results for each of these runs are included Appendix C. The average six‐year system WQI

scores for these four runs are displayed in Figure 3. Water body‐specific WQI results and key metrics

for these scenarios are presented in Table 6 and described below.

Figure 3. 6‐Year Average WQI Results for Base Case, No Internal‐Loading, Pristine Inflows, and No Stormwater Loading Simulations (2005‐2010)

WQI – Each run shows improvements in water quality relative to Base Case, as indicated by the

system‐wide WQI results. The greatest system‐wide improvement was simulated for the Pristine

Inflow scenario (system‐wide WQI improvement from 70 to 78). Pristine Inflows also produced the

greatest improvement in lake‐specific WQI scores for all three water bodies, with the largest

improvement in Shadow Mountain Reservoir (Lake WQI improved from 44 to 55). Eliminating

internal loading produces the next biggest improvement (WQI improvement from 70 to 75). The

removal of stormwater loading resulted in a smaller improvement (WQI improvement from 70 to 71).

Chlorophyll a – The elimination of internal loading produces the largest improvement in all of the

chlorophyll a metrics in Grand Lake and Shadow Mountain Reservoir. Pristine inflows resulted in the

largest impact for Granby Reservoir. The reason for the differences in water body response is likely

related to flow patterns, mixing patterns, and the layer in which different sources enter a water

body. Since Shadow Mountain Reservoir is shallow and more mixed, internal nutrient loads in the

reservoir are readily available to algae growing near the surface. In addition, summer‐time internal

nutrient loads in Granby Reservoir’s hypolimnion are typically pumped immediately to Shadow

Mountain Reservoir via the Farr Pumping plant during the summer months. Thus, Shadow Mountain

Reservoir is more directly impacted by its own internal loads and the internal loads in Granby



Reservoir. The water in Shadow Mountain Reservoir then, in turn, predominantly flows into the

epilimnion of Grand Lake during the summer months. Therefore, both Shadow Mountain Reservoir

and the epilimnion of Grand Lake (where most algal growth occurs) are more impacted by internal

nutrient loading than the epilimnion of Granby Reservoir. Nutrient loads from tributary and pumped

inflows (Pristine Inflows) play a larger role for epilimnetic chlorophyll a conditions in Granby

Reservoir in that these loads are greater for Granby Reservoir and they often directly enter the

epilimnion (but are somewhat isolated from the hypolimnion until turnover).

Clarity – The scenario with Pristine Inflows produced the greatest simulated improvements in clarity

in all three water bodies. Improvements in average Secchi depth (July – September 15) ranged from

0.7 m in Shadow Mountain Reservoir to 1.1 m in Grand Lake to 2.1 m in Granby Reservoir.

Additionally, for Pristine Inflows, the maximum Grand Lake Secchi depth (July ‐ September) is

predicted to be 7.9 meters, compared to 6.1 m for the Base Case. The greater improvements to

clarity for the Pristine Inflows may seem counterintuitive, given that the removal of internal loading

produced the greatest decrease in chlorophyll a in Grand Lake and Shadow Mountain Reservoir. It is

important to recall that clarity is determined by more than just algal material, and developing inputs

to simulate a reasonable formulation of pristine water quality involved reducing inorganic suspended

solids and non‐algal particulate organic matter concentrations in addition to nutrient concentrations.

Dissolved Oxygen – No significant changes to minimum dissolved oxygen concentrations were

predicted to occur for any of the simulations (all ≤0.1 mg/L). Reduction of algal growth (and

corresponding decrease of photosynthesis) in Shadow Mountain Reservoir for the Pristine Inflows

scenario resulted in a slight decrease in minimum dissolved oxygen and an increase in the number of

days with concentrations less than 6 mg/L. These results are not surprising for the reasons explained

above for Question 1.



Table 6. Comparison of Results – Significant Reductions in Loading by Type

Metric Unit Base Case Pristine No Internal No Storm

System‐Wide WQI d‐less 70 78 75 71

GRAND LAKE

Lake WQI d‐less 75 85 83 76

Chl a Avg (Mar‐Nov) ug/L 2.9 2.5 0.9 2.6

Chl a Avg (July‐Sept) ug/L 5.1 4.4 1.6 4.8

# Days/Yr > 8 ug/L Chl a days 13 8 0 10

Chl a Max (July‐Sept) ug/L 8.8 7.4 2.4 7.7

Secchi Depth 15th %tile (July‐Sept)* m 2.1 (1.6‐2.6) 2.7 (1.9‐3.2) 2.6 (2.5‐3) 2.2 (1.7‐2.7)

Secchi Depth Avg (July‐Sept 15) m 3.0 4.1 3.7 3.1

Secchi Depth Maximum** m 6.1 7.9 6.8 6.3

Min Epilimnetic DO mg/L 6.7 6.8 6.7 6.7

# Days/Yr < 6 mg/L Epilimnetic DO days 0 0 0 0

SHADOW M

TN RESER

VOIR







Minimum DO mg/L 5.3 5.3 5.2 5.3

# Days/Yr < 6 mg/L DO days 51 50 53 51

GRANBY RESER

VOIR









d‐less – indicates dimensionless. All metrics computed for each year, then averaged over the six‐year period, unless otherwise noted. *Six‐year range in parentheses. **Maximum daily value over entire six‐year simulation for the period July through September.



Summary

Simulations of extreme reductions in loading from inflow sources, internal sources, and stormwater

sources were performed to assess the relative role of each type of loading in determining water

quality in the three water bodies. The results show the greatest system‐wide and lake‐specific water

quality improvements occur with drastic reductions in inflow loading (Pristine Inflows scenario).

These improvements are due to combined improvements in chlorophyll a concentrations and clarity.

Changes to minimum dissolved oxygen in the epilimnion were relatively small across all scenarios.

Removal of internal loading produces the greatest reductions in average chlorophyll a

concentrations in Shadow Mountain Reservoir and Grand Lake. In Granby Reservoir, however, the

Pristine Inflow model run produced greater chlorophyll a improvements in the summer‐time. The

greatest improvements in clarity were simulated for all three water bodies for the Pristine Inflow

scenario.

Question 3: Of the inflowing tributaries and pumped sources, which one would improve water quality the most if it were improved to “pristine” conditions?

To evaluate the relative importance of the nutrient loading associated with the major tributaries and

pumped inflows, model runs were made setting each inflow to pristine conditions (see Section III) –

one inflow at a time. These runs simulate the potential impacts if a particular watershed/inflow

source were targeted for dramatic (and perhaps unrealistic) improvements in water quality. The

inflows investigated are Stillwater Creek, Arapaho Creek, Willow Creek, Windy Gap, and the North

Fork. Nutrient reductions for each of these simulations are summarized in Table 7 in terms of

percent reduction to total inflow TP and TN loads, relative to the Base Case. The largest change in

total nitrogen and phosphorus loading are simulated in the North Fork, Willow Creek, and Windy Gap

pristine simulations. Recall also that changing inputs to simulate pristine water quality included

reducing inorganic suspended solids and non‐algal particulate organic matter concentrations in

addition to nutrient concentrations. Detailed results for each of these runs are included Appendix D.

Table 7. Percent Load Reductions for Individual Tributary Scenarios, Relative to Base Case

Scenario Reduction in Total Phosphorus Load

Reduction in Total Nitrogen Load

Stillwater Creek – Pristine 4.4% 1.5%

Arapaho Creek – Pristine 0.9% 2.7%

Willow Creek – Pristine 6.0% 2.2%

Windy Gap – Pristine 7.5% 4.6%

North Fork – Pristine 5.7% 3.0%

The average 6‐year system WQI scores for these five runs are shown in Figure 4. Water body‐specific

WQI results and key metrics for these scenarios are presented in Table 8 and Table 9 and discussed

below.



Figure 4. 6‐Year Average WQI Results for Base Case and Individual Tributary and Pumped Inflow Pristine Condition Simulations (2005‐2010)

WQI – Each run shows some improvement in water quality relative to Base Case, as indicated by the

system‐wide WQI results. The greatest system‐wide improvement was simulated for the scenario of

pristine inflow conditions for the North Fork (WQI improvement from 69.9 to 72.5). Changing Windy

Gap pump canal inflow water quality to pristine conditions produces the next best improvement in

system water quality, followed by Willow Creek, Stillwater Creek, and Arapaho Creek. The lake‐

specific results for Grand Lake and Shadow Mountain Reservoir also show the greatest

improvements for changes to North Fork inflow concentrations. For Granby Reservoir, results are

slightly better for simulated improvements to Windy Gap, Willow Creek, and Arapaho Creek inflow

water quality. Differences in responses among the water bodies can generally be attributed to the

location and timing of inflows and operations.

Chlorophyll a – For chlorophyll a, predicted changes in average concentrations were small (≤0.2

ug/L) across all simulations for all three water bodies. Predicted changes in maximum

concentrations were slightly larger (≤0.4 ug/L ). Overall, based on the metrics displayed in Tables 8

and 9, Grand Lake and Shadow Mountain Reservoir benefitted the most (with respect to chlorophyll

a) from load reductions in the North Fork. For Granby Reservoir, the largest benefits occur with

improvements from the Willow Creek pump canal.

Clarity – Most simulations show small improvements in clarity relative to the Base Case for all three

water bodies, ranging from 0 m to 0.4 m for the July‐September 15 average. Lake‐specific results

follow similar patterns to those noted for chlorophyll a. Changing North Fork inflows to pristine



conditions produces the greatest improvements to the average July‐September 15 Secchi depths in

Grand Lake and Shadow Mountain Reservoir (0.2 m). For Granby Reservoir, improvements occur for

all five scenarios, although the greatest improvements in average clarity (0.4 m) were simulated for

Willow Creek pump canal and Windy Gap pipeline water‐quality improvements.

Dissolved Oxygen – Minimum dissolved oxygen concentrations are not predicted to change for any

of the simulations. This result fits the pattern of the simulations discussed above for Question 1.



Table 8. Summary of Results – Significant Reductions by Reduced Loadings from Individual Tributaries

Metric Unit Base Case Stillwater Creek

Arapaho Creek

North Fork

System‐Wide WQI d‐less 69.9 70.5 70.4 72.5

GRAND LAKE

Lake WQI d‐less 75.0 75.5 75.3 77.5





Secchi Depth 15th %tile (July‐Sept)* m 2.1 (1.6‐2.6) 2.1 (1.6‐2.6) 2.1 (1.6‐2.6) 2.2 (1.6‐2.7)


Secchi Depth Maximum** m 6.1 6.3 6.2 6.3



SHADOW M

TN RESERVOIR

Lake WQI d‐less 44.0 44.6 44.3 48.7






Minimum DO mg/L 5.3 5.3 5.3 5.3

# Days/Yr < 6 mg/L DO days 51 50 51 50

GRANBY RESERVOIR

Lake WQI d‐less 90.8 91.3 91.5 91.3








d‐less – indicates dimensionless. All metrics computed for each year, then averaged over the six‐ year period, unless otherwise noted. *Six‐year range in parentheses. **Maximum daily value over entire six‐year simulation for the period July through September.



Table 9. Summary of Results – Significant Reductions by Reduced Loadings from Pumped Inflows

Metric Unit Base Case Willow Creek Windy Gap

System‐Wide WQI d‐less 69.9 70.9 71.0

GRAND LAKE

Lake WQI d‐less 75.0 75.8 76.1

Chl a Avg (Mar‐Nov) ug/L 2.9 2.9 2.8

Chl a Avg (July‐Sept) ug/L 5.1 5.1 5.1


Chl a Max (July‐Sept) ug/L 8.8 8.8 8.7

Secchi Depth 15th %tile (July‐Sept)* m 2.1 (1.6‐2.6) 2.2 (1.6‐2.7) 2.2 (1.7‐2.7)

Secchi Depth Avg (July‐Sept 15) m 3.0 3.1 3.1

Secchi Depth Maximum** m 6.1 6.2 6.2

Min Epilimnetic DO mg/L 6.7 6.7 6.7


SHADOW M

TN RESERVOIR







Minimum DO mg/L 5.3 5.3 5.3

# Days/Yr < 6 mg/L DO days 51 50 51

GRANBY RESERVOIR









d‐less – indicates dimensionless. All metrics computed for each year, then averaged over the six‐ year period, unless otherwise noted. *Six‐year range in parentheses. **Maximum daily value over entire six‐year simulation for the period July through September.



Summary

Simulations of reductions in inflow loading for individual tributaries and pumped inflows were

performed to assess the relative role of each inflow in determining water quality in the three water

bodies. The results show the greatest system‐wide water‐quality improvements for the case of

pristine water quality in the North Fork. This case also produces the greatest lake‐specific

improvements in Grand Lake and Shadow Mountain Reservoir. The impacts to Shadow Mountain

Reservoir are the greatest. This makes sense since concentrations in the North Fork are high and

enter Shadow Mountain Reservoir directly. Grand Lake is implicated since loadings through the

channel are significant for this water body. In Granby Reservoir, results were slightly better for the

simulation of pristine Windy Gap, Willow Creek, and Arapaho Creek inflows, reflecting the effects of

inflow locations, timing, and operations. These inflows enter Granby Reservoir directly near the

surface during the period when the reservoir is stratifying, and thus impact the surfaced‐based

constituents considered in the WQI. Note that for the set of scenarios considered in this section,

non‐nutrient reductions were made, in addition to the nutrient reductions listed in Table 7. Thus,

factors that depend on particulate concentrations, such as Secchi depth, are impacted by these non‐

nutrient reductions.

Overall, improved water quality in individual tributaries produces only small changes in summer‐time

chlorophyll a concentrations (≤0.2 ug/L for the six‐year July‐September average). There were no

simulated changes to minimum epilimnetic dissolved oxygen concentrations, reflecting the greater

relative importance of other mechanisms on epilimnetic dissolved oxygen. Average clarity results

(July through September 15) show improvements ranging from 0.2 m in Grand Lake and 0.1 m

Shadow Mountain for the North Fork Pristine scenario to 0.4 m in Granby for Willow Creek Pristine

scenarios. Shadow Mountain Reservoir also shows a 0.1 m improvement with the Windy Gap Pristine

model run. The effect on clarity is due to the combination of changes on inflow concentrations that

included reducing inorganic suspended solids and non‐algal particulate organic matter in addition to

decreases in chlorophyll a.

Question 4: With respect to nutrient loadings from all sources, is it better to focus on phosphorus or nitrogen loading reductions?

To evaluate the relative importance of reductions to nitrogen versus reductions to phosphorus

loading, model runs were made reducing loadings from all sources (inflow, stormwater, and internal

loads) by 75% ‐ first for phosphorus only and then for nitrogen only. Model runs were also made

reducing these terms by 25% and 50%. The discussion in this section focuses on details of the 75% all‐

source reduction runs, since the incremental change runs produced generally corresponding

incremental differences in results. An exception to this occurs for TP reductions in Shadow

Mountain Reservoir where results point to diminishing returns after a 50% TP reduction occurs. The

detailed results for all of these runs are included Appendix E.



The average 6‐year system WQI scores for the 25%, 50%, and 75% nitrogen and phosphorus load

reduction runs are displayed in Figure 5. Water body‐specific WQI results and key metrics for the 75%

phosphorus and nitrogen scenarios are presented in Table 10 and discussed below.

Figure 5. 6‐Year Average WQI Results for Base Case and 25%, 50%, and 75% Phosphorus and Nitrogen Load Reduction Simulations

WQI – Reductions in both phosphorus and nitrogen produce improvements in water quality as

compared to Base Case, as indicated by the system‐wide WQI results. Scenarios of 50% reduction in

phosphorus loading and 50% reduction in nitrogen loading produced similar system‐wide

improvements in WQI scores. The system score improved from 69.9 for the Base Case to 73.3 for the

50% phosphorus and 50% nitrogen reductions. For 25% reductions in nutrients, a slightly higher

system‐wide WQI was computed for TP reductions. For 75% reductions, on the other hand, a slightly

higher WQI was obtained for TN reductions. The same pattern is seen in the lake‐specific WQI results

for Shadow Mountain Reservoir. Results for Grand Lake and Granby Reservoir differ, however.

Grand Lake shows higher lake‐specific scores for TP improvements and Granby Reservoir shows

higher scores for TN improvements.

Chlorophyll a – Average chlorophyll a concentrations, and peak chlorophyll a concentrations all show

the slightly greater improvements for the 75% reductions in phosphorus loading scenario for Grand

Lake. The same is true for Shadow Mountain Reservoir, with the exception of the March –

November average. The effect on chlorophyll a concentrations in Granby Reservoir is the same for

the 755 TN and 75% TP reductions, with the exception of the maximum chlorophyll a, which is better

for the 75% TN reduction. The greatest improvement to March through November average

chlorophyll a concentrations is simulated to occur in Shadow Mountain Reservoir with the 75% TN



reduction (3.1 ug/L decrease). As noted for the Ultra‐Clean scenario results, chlorophyll a average

summer concentrations are predicted to be below 2 ug/L for most years in all three water bodies for

both the 75% phosphorus reduction run and the 75% nitrogen reduction run. At these levels, there is

a potential concern of loss of productivity for the fisheries, though the fishery response is uncertain.

Clarity – Reductions in both phosphorus and nitrogen produced improvements in clarity relative to

the Base Case for all three water bodies, with slightly better improvements predicted for phosphorus

reductions in Grand Lake and nitrogen reductions in Granby Reservoir. Maximum improvements in

six‐year, July‐September 15 average Secchi depth range from 0.5 m in Shadow Mountain, to 0.8 m in

Grand Lake, to 1.3 m in Granby Reservoir.

Dissolved Oxygen – Minimum dissolved oxygen concentrations were not predicted to change much

(≤0.2 mg/L improvement at best) for any of the simulations. This result fits the pattern of the

simulations discussed above for Question 1.



Table 10. Summary of Results – Significant Reductions for All Sources by Nutrient

Metric Unit Base Case Reduce P (75%) All Sources

Reduce N (75%) All Sources

System‐Wide WQI d‐less 70 74 75

GRAND LAKE

Lake WQI d‐less 75 83 83





Secchi Depth 15th %tile (July‐Sept)* m 2.1 (1.6‐2.6) 2.7 (2.6‐3.1) 2.7 (2.5‐3)


Secchi Depth Maximum** m 6.1 7.0 6.5



SHADOW M

TN RESERVOIR







Minimum DO mg/L 5.3 5.1 5.1

# Days/Yr < 6 mg/L DO days 51 54 53

GRANBY RESERVOIR









d‐less – indicates dimensionless. All metrics computed for each year, then averaged over the six‐year period, unless otherwise noted. *Six‐year range in parentheses. **Maximum daily value over entire six‐year simulation for the period July through September.



Summary

Simulations of reductions in phosphorus only or nitrogen only loadings were performed to assess the

relative role of each in determining water quality in the three water bodies. For 75% reductions,

results show slightly greater system‐wide water‐quality improvements when nitrogen is reduced;

however, for 25% reductions, a slightly higher improvement is seen with phosphorus reductions.

Both nutrients are important in determining the water‐quality response of all three water bodies.

These results are consistent across water bodies and parameters. The water‐quality improvements

are apparent in both decreases in chlorophyll a concentrations and increases in Secchi depths, with

minimal responses in minimum epilimnetic dissolved oxygen concentrations for reasons discussed in

Section III.

Question 5: Do any of the nutrient reduction scenarios result in improvements to one or more water body and degradation to another?

Results of all simulations were reviewed to evaluate whether any nutrient reduction scenarios

resulted in improvements to water quality in one water body while causing degradation to another.

None of the results produce a case where one water body suffers at the expense of another over the

course of the entire six years. Improvements occur in all three water bodies for the scenarios

considered. We note that dissolved oxygen in Shadow Mountain Reservoir decreases slightly with

the scenarios that have very low chlorophyll a concentrations. This is a result of simulating this water

body as a well‐mixed system and not coupling sediment oxygen demand with reduced chlorophyll a

concentrations. Future model modifications may include capturing the latter relationship. We also

note that since project operations were assumed to be the same for all scenarios, improvements for

one water body due to operational changes and the resultant effects on the other water bodies, has

not been tested.



VI. Conclusions and Recommendations

A variety of nutrient sensitivity model runs were made to understand in‐lake/reservoir water‐quality

impacts of loading reductions. Key conclusions and recommendations include:

The dramatic water‐quality improvements simulated for the Ultra‐Clean scenario indicate the

importance of nutrient loading to the system water quality.

o Ultra‐Clean scenario results indicate a decrease in average July‐September

chlorophyll a concentrations of 1.5 ug/L for Granby Reservoir, 4.7 ug/L for Grand Lake,

and 6.6 ug/L for Shadow Mountain Reservoir. Peak summer‐time chlorophyll a

concentrations showed even larger improvements, and there were no days in the

Ultra‐Clean scenario with summer‐time chlorophyll a concentrations greater than 8

ug/L in any of the water bodies (down from 30 and 13 average days per year in

Shadow Mountain Reservoir and Grand Lake, respectively).

o For clarity, the Ultra‐Clean scenario indicates improvement in average Secchi depth

(July‐September 15) of at least 1.8 m in each water body over the six‐year simulation.

This finding, related to the effects of nutrients on clarity, should not be confused as a

statement about the relative importance of C‐BT operations on water quality.

Operations were not varied in these simulations. Although there are large

improvements in Grand Lake water clarity under the Ultra‐Clean scenario, including

an increase in maximum Secchi depth (July – September) from 6.1 m to 8.8 m, the

proposed 4.0 meter standard using the proposed metric (15th %ile from July through

September) would not be met on average. Two of the six years would just meet this

4.0 m threshold in the Ultra‐Clean scenario.

While these simulations show marked improvements to clarity and chlorophyll a

concentrations in response to changes in nutrient loading, minimal changes to minimum

epilimnetic dissolved oxygen concentrations are simulated. This result indicates the

importance of other mechanisms on determining epilimnetic dissolved oxygen

concentrations. These include reaeration, advection, diffusion, decomposition, and sediment

oxygen demand.

Greater improvements to overall system water quality are simulated for pristine inflow

conditions, as opposed to the elimination of internal nutrient loading or stormwater nutrient

loading. This primarily reflects the larger improvements in clarity in all three water bodies in

response to pristine inflow conditions, which also included reductions in inorganic suspended

solids concentrations and non‐algal organic particulate matter. The elimination of internal

loading resulted in greater system‐wide improvement than the elimination of stormwater

loads. Removal of internal loading produced the greatest reductions in summer‐time

chlorophyll a concentrations in Grand Lake and Shadow Mountain Reservoir, but not for



Granby Reservoir. For Granby Reservoir, improvements to pristine inflow conditions

produced the greatest improvement in summer‐time chlorophyll a concentrations.

Among the tributaries and pumped inflows, improvement of North Fork water quality to

pristine conditions results in the greatest system‐wide improvements and to Shadow

Mountain Reservoir, in particular (WQI improvement of 4.7). This highlights the importance

of this tributary from a system perspective and to Shadow Mountain Reservoir itself. The

North Fork pristine simulation also produced the greatest lake‐specific improvements in

Grand Lake (WQI improvement of 2.5). In Granby Reservoir, results were slightly better for

the simulation of pristine Windy Gap, Arapaho Creek, and Willow Creek inflows, reflecting the

effects of inflow locations, timing, and operations. These sources enter Granby Reservoir

near the surface and most directly impact the surfaced‐based factors considered in the WQI.

Results of simulations reducing nitrogen only or phosphorus only loading indicate that both

nutrients are important in determining the water‐quality response of all three water bodies.

Water‐quality improvements are apparent in both decreases in chlorophyll a concentrations

and increases in Secchi depths. The results show that for lower reductions (~25%), changes in

total phosphorus loadings may be more important. At larger reductions (~75%), the opposite

conclusion is made. The results are very similar when comparing the same level of reduction

for both nutrients, however.

There are a variety of sources of nutrients to the Three Lakes System which include natural

tributaries, managed inflows, internal loading, direct precipitation, and precipitation‐driven

events. These sources differ not only in magnitude of loading, but also with respect to

timing, the fraction of nutrient sub‐species (for example, the fraction of bioavailable

nutrients), and where the loading occurs (e.g. near the bottom or at the surface).

Operations and stratification patterns also complicate the flow and impact of nutrients

throughout the system. Therefore, although annual nutrient loading budgets are important,

sources with higher annual total nutrient loading may have less of an impact than other

sources.

Focused monitoring during stormwater events is recommended. For example, auto‐

samplers may be used to monitor inflowing water quality during precipitation events. This

information would help to better understand how tributary nutrient concentrations respond

during these periods.



VII. References

Boyer, J.M. and C. M. Hawley. Anticipated 2014. Three Lakes Water‐Quality Model Documentation

Report. In Development.

Carpenter, S.R. 1980. Enrichment of Lake Wingra, Wisconsin, by Submersed Macrophyte Decay.

Ecology. 6(15):1145‐1155.

Hawley, C.M. and J.M. Boyer. 2012a. Revised Methodology for Estimating Stillwater Flows.

Memorandum to Esther Vincent (Northern Water) and Ron Thomasson (USBR). Draft. April

24, 2012.

Hawley, C.M. and J.M. Boyer. 2012b. WQI Development Documentation Memo – Updated October

31. Memorandum to the Three Lakes Nutrient Study Technical Committee. October 31.

Hydrosphere Resource Consultants. 2003. Three Lakes Clean Lakes Watershed Assessment, Final

Report. Submitted to the Three Lakes Technical Advisory Committee. December 5, 2003.

Stephenson, J. 2013. Nutrient Study – Data Review. Prepared by J. Stephenson of Northern Water.

Submitted April 2, 2013.

Vincent, E. 2012. Personal email communication to C. Hawley and J.M. Boyer (Hydros Consulting)

from Esther Vincent (Northern Water). Subject: Hydrology for SA. November 14, 2012.

Three Lakes Model Nutrient Sensitivity Analysis – Appendix A January 27, 2014


Appendix A ‐ Description of Scenarios Considered

Three Lakes Model Nutrient Sensitivity Analysis January 10, 2014

Page A‐1

AppendixA‐DescriptionofScenariosConsidered

Three sets of scenarios were investigated for the nutrient sensitivity analysis runs, for a total of 24

model runs. They include:

Group One: System‐Wide Nutrient Reductions by Type of Loading

Group Two: Nutrient Reductions by Individual Inflow

Group Three: Separate Phosphorus and Nitrogen Reductions

Note that all model runs considered for this analysis assume the same hydrology and operations (i.e.,

actual inflow, outflows, and pumped flows for 2005‐2010). This effort examines the water‐quality

response of the Three Lakes, in its existing configuration, to various types and levels of nutrient

reductions. The purpose of the analysis is not to simulate possible nutrient mitigation strategies, but

rather to understand the extent to which water quality in the system responds to changes in nutrient

inputs. This analysis also informs understanding of the relative importance of various nutrient sources

to the Three Lakes. Note that none of the model runs considers conditions where nutrient loading is

completely eliminated.

Some of the model scenarios described below involve reducing inflow loads to “pristine” conditions.

This “pristine” time series was developed based on the lowest concentrations observed (with the

exception of dissolved oxygen, which was based on the highest concentrations) for all of the tributaries.

Thus, concentrations are low, but not unreasonable for this system.

The three sets of model scenarios are described below. For comparison purposes, a base‐case scenario

was defined and used as an indication of current conditions. The Technical Committee decided to use

the calibrated Three Lakes Water‐Quality Model (2005‐2010) as the base case model run, from which

other modeling scenarios would be compared. Inputs into the calibrated model are based on flow and

water‐quality measurements throughout 2005‐2010 and reflect actual hydrologic, operational, and

water‐quality conditions during the six‐year time period. The three groups of model runs are described

below.

GroupOne:System‐WideNutrientReductions

Several system‐wide nutrient reduction model runs were initially envisioned by the Technical

Committee. These eleven runs and the methodology used to prepare flow and water‐quality inputs for

the model are described in Boyer et al., 2011 (Table 1).

The model runs were designed to vary inflow loading, internal loading, and stormwater loading

systematically and on a system‐wide basis. Each scenario is described below.

Scenario1:Ultra‐CleanScenarioThis scenario represents the upper boundary or absolute best lake/reservoir water quality of the

scenarios considered for this analysis. Constituent concentrations of the inflowing tributaries, gains, and


Page A‐2

the external pumped sources are assumed to be pristine. In addition, all internal and stormwater

loading are eliminated.

Table 1: Description of System‐Wide Nutrient Reduction Model Runs (Modified from Boyer et al.,

2011)

Scenario Description Inflow Loading Internal Loading

Stormwater Loading

1 Ultra-Clean Scenario

Pristine water quality None None

2 Internal – 50% Base Case 50% Rate Reduction

Base Case

3 Internal – Off Base Case None Base Case 4 Inflow– 50% 50% Reduction of Base

Case Base Case Base Case

5 Inflow – Pristine Pristine water quality Base Case Base Case 6 Stormwater – 50% Base Case Base Case 50 % Reduction 7 Stormwater - Off Base Case Base Case None 8 Internal/Inflow –

50% 50% Reduction of Base

Case 50% Rate Reduction

Base Case

9 Internal / Stormwater – 50%

Base Case 50% Rate Reduction

50% Reduction

10 Inflow / Stormwater – 50%

50% Reduction of Base Case

Base Case 50% Reduction

11 All Loading 50% Reduction

50% Reduction of Base Case

50% Rate Reduction

50 % Reduction

Scenario2:InternalLoadingReductionScenario(50%)This scenario helps to understand the impact of reducing internal loading by 50%. Constituent

concentrations of the inflowing tributaries, gains, and the external pumped sources are assumed to be

those observed (2005‐2010). Internal loading rates are reduced by 50%. Stormwater loadings are set to

the loads in the calibrated model.

Scenario3:InternalLoadingReductionScenario(100%)This scenario helps to understand the impact of eliminating internal loading. Constituent concentrations

of the inflowing tributaries, gains, and the external pumped sources are assumed to be those observed

(2005‐2010). Internal loading is eliminated. Stormwater loadings are set to the loads in the calibrated

model.

Scenario4:InflowLoadingReductionScenario(50%)This scenario helps to understand the impact of reducing inflow loading by 50%. Constituent

concentrations of the inflowing tributaries, gains, and the external pumped sources are assumed to be ½

those observed (2005‐2010). Internal loading rates and stormwater loadings are consistent with the

calibrated model.


Page A‐3

Scenario5:InflowLoadingReductionScenario(Pristine)This scenario helps to understand the impact of reducing inflow loading significantly. Constituent


pristine. Internal loading rates and stormwater loadings are consistent with the calibrated model.

Scenario6:StormwaterLoadingReductionScenario(50%)This scenario helps to understand the impact of reducing stormwater loading by 50%. Constituent


those observed (2005‐2010). Internal loading rates are consistent with the calibrated model.

Stormwater loadings are reduced by 50%.

Scenario7:StormwaterLoadingReductionScenario(100%)This scenario helps to understand the impact of eliminating stormwater loading. Constituent


those observed (2005‐2010). Internal loading rates are consistent with the calibrated model.

Stormwater loadings are eliminated.

Scenario8:Internal/InflowLoadingReductionScenario(50%)This scenario helps to understand the impact of reducing internal loading rates and inflow loads by 50%.

Constituent concentrations of the inflowing tributaries, gains, and the external pumped sources are

assumed to be ½ those observed (2005‐2010). Internal loading rates are reduced by 50%. Stormwater

loadings are consistent with the calibrated model.

Scenario9:Internal/StormwaterLoadingReductionScenario(50%)This scenario helps to understand the impact of reducing internal loading rates and stormwater loads by

50%. Constituent concentrations of the inflowing tributaries, gains, and the external pumped sources

are assumed to be those observed (2005‐2010). Internal loading rates are reduced by 50%. Stormwater

loadings are reduced by 50%.

Scenario10:Inflow/StormwaterLoadingReductionScenario(50%)This scenario helps to understand the impact of reducing inflow loading and stormwater loads by 50%.

Constituent concentrations of the inflowing tributaries, gains, and the external pumped sources are

assumed to be ½ those observed (2005‐2010). Internal loading rates are consistent with the calibrated

model. Stormwater loadings are reduced by 50%.

Scenario11:AllLoadingReductionScenario(50%)This scenario helps to understand the impact of reducing internal loading rates and inflow and

stormwater loads by 50%. Constituent concentrations of the inflowing tributaries, gains, and the

external pumped sources are assumed to be ½ those observed (2005‐2010). Internal loading rates and

stormwater loadings are reduced by 50%.


Page A‐4

GroupTwo:NutrientReductionsbyIndividualInflow

The second set of model runs are summarized in Table 2. This set of model runs was designed to vary

specific individual inflow concentrations with the intent of understanding the impacts to overall water

quality.

Table 2. Description of Group Two Model Runs –Nutrient Reduction by Individual Inflow


Stormwater Loading

12 Stillwater - Pristine

Same as Base Case with Stillwater Set at Pristine

Base Case Base Case

13 Arapaho - Pristine

Same as Base Case with Arapaho Set at Pristine

Base Case Base Case

14 Willow Crk - Pristine

Same as Base Case with Willow Crk Set at Pristine

Base Case Base Case

15 Windy Gap - Pristine

Same as Base Case with Windy Gap Set at Pristine

Base Case Base Case

16 North Fork - Pristine

Same as Base Case with North Fork Set at Pristine

Base Case Base Case

Each scenario is described below.

Scenario12:StillwaterCreekWaterQualitySetatPristineWaterQualityThis scenario is the same as the base case except the water quality for Stillwater Creek is set to equal

that assumed for pristine conditions.

Scenario13:ArapahoCreekWaterQualitySetatPristineWaterQualityThis scenario is the same as the base case except the water quality for Arapaho Creek is set to equal that

assumed for pristine conditions.

Scenario14:WillowCreekWaterQualitySetatPristineWaterQualityThis scenario is the same as the base case except the water quality for the Willow Creek Pump Canal is

set to equal that assumed for pristine conditions.

Scenario15:WindyGapWaterQualitySetatPristineWaterQualityThis scenario is the same as the base case except the water quality for the Windy Gap Pump Canal is set

to equal that assumed for pristine conditions.

Scenario16:NorthForkWaterQualitySetatPristineWaterQualityThis scenario is the same as the base case except the water quality for the North Fork is set to equal that

assumed for pristine conditions.


Page A‐5

GroupThree:SeparatePhosphorusandNitrogenReductions

The third group of model runs is summarized in Table 3. This group of model runs was designed to vary

one nutrient at a time with the intent of understanding the impact of reductions in phosphorus from

inflows versus reductions of nitrogen. Note that only a sub‐set of the inflows were considered.

Table 3. Description of Group Three Model Runs –Separate Phosphorus and Nitrogen Reductions


Stormwater Loading

17 P Reduction for 5 Major Inflows

Base Case Except ½ P for 5 Tributaries*

Base Case Base Case

18 N Reduction for 5 Major Inflows

Base Case Except ½ P for 5 Tributaries*

Base Case Base Case

19 25% Reduction – All P

Reduce all inflowing P by 25%

Reduce all internal P loading

rates by 25%

Reduce all stormwater P loads

by 25% 20 50% Reduction

– All P Reduce all inflowing P

by 50% Reduce all

internal P loading rates by 50%



– All P Reduce all inflowing P

by 75%* Reduce all

internal P loading rates by 75%



– All N Reduce all inflowing N

by 25% Reduce all internal N

loading rates by 25%

Reduce all stormwater N loads

by 25%

23 50% Reduction – All N

Reduce all inflowing N by 50%

Reduce all internal N



by 50%

24 75% Reduction – All N

Reduce all inflowing N by 75%*

Reduce all internal N



by 75%

* North Fork, Stillwater Creek, Windy Gap, Willow Creek, and Arapaho Creek

Each scenario is described below.

Scenario17:PhosphorusReduction–FiveMajorInflowsThis scenario is the same as the base case except the inflow organic phosphorus and inorganic

phosphorus concentrations of Stillwater Creek, Arapaho Creek, the Willow Creek Pump Canal, the Windy

Gap Pump Canal, and the North Fork are reduced by 50%. The scenario helps to understand the impacts

of phosphorus reductions from some of the inflows.


Page A‐6

Scenario18:NitrogenReduction–FiveMajorInflowsThis scenario is the same as the base case except the inflow organic nitrogen, nitrate, and ammonia

concentrations of Stillwater Creek, Arapaho Creek, the Willow Creek Pump Canal, the Windy Gap Pump

Canal, and the North Fork are reduced by 50%. The scenario helps to understand the impacts of

nitrogen reductions from some of the inflows.

Scenario19:25%PhosphorusReductionThis scenario is the same as the base case except the inflow organic phosphorus and ortho‐phosphorus

concentrations of all inflows are reduced by 25%. In addition, internal loading rates for phosphorus and

stormwater phosphorus loads are reduced by 25%. The scenario helps to understand the impacts of

phosphorus reductions system‐wide.









Scenario22:25%NitrogenReductionThis scenario is the same as the base case except the inflow organic nitrogen, nitrate, and ammonia

concentrations of all inflows are reduced by 25%. In addition, internal loading rates for nitrogen and

stormwater nitrogen loads are reduced by 25%. The scenario helps to understand the impacts of

nitrogen reductions system‐wide.










Page A‐7

References

Boyer, J.M., C.M. Hawley, R. Thomasson, and E. Vincent. 2011. Draft Hydrology and Water Quality

Inputs for the Three Lakes Water‐Quality Model – Methodology. December 14, 2011.

Three Lakes Model Nutrient Sensitivity Analysis – Appendix B January 27, 2014


Appendix B ‐ Water‐Quality Index Documentation

TECHNICAL MEMORANDUM

TO: The Three Lakes Nutrient Study Technical Committee FROM: Christine Hawley and Jean Marie Boyer, PhD, PE, Hydros Consulting Inc. SUBJECT: Water Quality Index Development Documentation Memo; WQI for Sensitivity

Analysis and Operational Scenarios Application DATE: January 10, 2014 Revision (Minor Editorial Updates to October 31, 2012 Memo)

1 Introduction

The Three Lakes Nutrient Study (TLNS) has undertaken a modeling effort to support operational

forecasting, operational guidelines development, and a nutrient sensitivity analysis of the Three

Lakes System. The objectives of this effort are to better understand the variables that control

water quality response and to support better operational decision‐making. Model runs will

generate daily water quality results for multiple parameters for each of the three water bodies

in the system. A need was identified to develop a tool to compile and rank model run results.

Such a tool could simplify the interpretation steps and unify stakeholders by defining objectives

and decision‐making approaches in advance of modeling. On September 28, 2011, Hydros

Consulting proposed development of a Water Quality Index (WQI) to meet this need.

WQIs have been in use to streamline data analysis and interpretation since the mid‐1960s, when

Horton published a WQI developed for the Ohio River Valley Sanitation Commission (Horton,

1965). Since then, WQIs have been applied to a wide range of systems from rivers and lakes to

estuaries and groundwater, ranging in scale from single streams to international basins.

Significant advancements have been made in development methods and compilation

techniques since early WQIs.

The most widely applied lake‐based water quality index is the Carlson Trophic State Index (TSI),

published in 1977. Early comments on the WQI development effort for this project suggested

use of Carlson’s TSI in lieu of development of a system‐specific index. Application of Carlson’s

TSI is appealing because it is widely accepted and applied; it has the simplicity of a single

parameter index; and it is easy to use and explain. Unfortunately, Carlson’s TSI is not

appropriate for this application because trophic state or relative estimates of algal biomass do

not fully encompass the water quality concern.

To meet the specific model evaluation needs of the TLNS, a system specific WQI has been

developed for the Three Lakes System. Hydros has worked with the TLNS group for over a year

to develop the Three Lakes WQI presented in this memo. It is recognized that performance of

this new tool should be reviewed with each application to ensure that it is continuing to perform

WQI Development Documentation Memo January 10, 2014 Page 2 of 19

Hydros Consulting Inc. 1731 15th St., Suite 103, Boulder, CO 80302

as intended. If the index is found to be inadequate for any particular application, it may be

revised or simply not applied to that particular application. Examples of inadequate WQI

performance include insensitivity to changes in water quality, significant incongruities between

WQI results and the full set of water quality metrics under review, or misleading obfuscation of

poor water quality in one part of the system due to improvements in another part of the

system.

2 WaterQualityIndexDevelopment

A five step process to develop the WQI was defined based on review of literature (e.g., Ferriera,

2000, Cude, 2001, Fernandez, et al., 2004, Boyacioglu, 2007, and Lumb, et al., 2011). This

process is summarized in Figure 1. The path from Step 2 to Step 5 took several iterative loops

through the flow diagram, and the development presented below represents the product of

those iterations.

Figure 1. General Process for Development of the WQI

2.1 Step1:DefineWaterQualityObjectives

For this project, the water quality objective is to improve the health of Grand Lake, Shadow

Mountain Reservoir, and Granby Reservoir through improved system understanding and

optimization of operations. Specific concerns identified as primary water quality concerns by

the TLNS Technical Committee include low clarity, algal growth, and low dissolved oxygen

conditions.

Define WQ

Objectives

Parameter and

Metric Selection

Sub‐Index (SI)

Transform

Development

Define

Compilation

Approach

Apply

Test Method – Does it perform

well on observed data?

Yes

No

1 2 3 4

5



2.2 Step2:ParameterSelection

To evaluate the water quality in accordance with the water quality objective, a set of

parameters was selected. The following guidelines were observed in the parameter selection

process to support generation of a well‐functioning WQI for this application:

Parameters should be measures of response variables. (The WQI is a high level tool that

summarizes the response of the system as simulated by the model. The WQI should not

try to represent all relationships within the model. As such, the WQI should not include

measures of variables that are expected to affect the system response of concern if a

reasonable measure of the system response of concern is available from the model.)

The parameter list should be kept as short as possible while still reflecting the water

quality responses of concern. (Extensive parameter lists could lead to obscuring of

adverse effects to individual parameters.)

There should be minimal overlap/redundancy in parameters. (Overlap or redundancy

can lead to unintentional weighting of parameters in the WQI.)

Selected parameters must be available as output from the model.

After several discussions with the TLNS Technical Committee, clarity (as measured by Secchi

depth), chlorophyll a, and dissolved oxygen (DO), were selected for inclusion in the WQI. Clarity

in Grand Lake has been a key concern of residents since initiation of C‐BT (Colorado Big‐

Thompson Project) operations1. Chlorophyll a was included on the list of response parameters

of concern due to resident concerns about algal concentrations and concerns about meeting the

Colorado interim chlorophyll a standard values, should they be adopted for this system (CDPHE,

2011a). Dissolved oxygen was included as a parameter of concern due to listing of Shadow

Mountain Reservoir on the Colorado 303d List of Impaired Waters for aquatic life due to

dissolved oxygen concentrations (CDPHE, 2012).

The TLNS Technical Committee also discussed inclusion of temperature, pH, total nitrogen, and

total phosphorus concentrations for inclusion. Temperature, total nitrogen, and total

phosphorus were rejected because they did not constitute response variables. pH was rejected

because the pH response of concern in the system (high pH) occurs consistently in response to

algal growth. As such it would be a redundant measure in index.

Measures of these parameters were selected to reflect a combination of the TLNS‐specific water

quality concern and state standards or proposed/interim standards/values. The definition of

each metric is tied to development of the sub‐index transforms in selection of reflected

1 The C‐BT Project pumps water from Granby Reservoir into Shadow Mountain Reservoir. Pumped water then flows

to the Adams Tunnel, a trans‐mountain diversion structure that provides water to the east slope of Colorado for

agricultural, municipal, and industrial uses. C‐BT pumping of water is a reversal of the natural direction of flow

through the system. The CB‐T Project has been fully operational since the 1950’s.



standards and water quality values. Therefore, greater discussion of the metric selection for

each parameter is presented in Section 2.3 and summarized here:

Secchi depth is assessed as the average of observations from July through September

152;

Chlorophyll a is assessed as the average of epilimnion observations from March through

November3; and

Dissolved oxygen is assessed as the minimum annual4 concentration for results

averaged over the depth interval from 0.5 to 2m (epilimnion in model results).

2.3 Step3:Sub‐IndexTransformDevelopment

Before selected parameters can be compiled into the WQI, transforms must be developed for each parameter to normalize results to a common scale. Transforms were designed for each parameter, applying the following consistent rules developed in consultation with the TLNS Technical committee:

A scale of 1 to 100 was set for sub‐index values.

Where available, standards or proposed standards were used as set points to help define

the transforms.

o When applicable water quality standards were available, the standard was set at a

sub‐index value of 90.

o When only proposed or interim standards/values were available, the value was set

at a sub‐index value of 80, reflecting the uncertainty about the eventual adopted

standard value. The shift 80 serves to give more sub‐index resolution and

corresponding WQI sensitivity for that parameter above the proposed or interim

standard/value recognizing the possibility that the final standard value may be more

stringent than the proposed/interim value.

The lower set point for each transform was set to a value determined by the observed range

of data from 2005‐2011.

o Specifically, for each parameter and metric, the range of results for all three water

bodies was calculated, and a lower set point was defined to be 20% below (above

for chlorophyll a) the lowest observation (highest for chlorophyll a).

o This approach was taken to improve the spread of observed results across the index.

As a result, the index is more sensitive over the range of observed results. An earlier

2 This metric for Secchi depth differs from the metric for the proposed standard (15th percentile assessed from July

through September). The reasons for selecting this metric are discussed in Section 2.3.

3 The March through November average is the metric for assessing water bodies designated as direct use water

supplies. The corresponding interim standard value is 5 ug/L. The basis for selecting this metric is discussed in

Section 2.3.

4 This corresponds to the standard metric applicable to the 303d listing of Shadow Mountain Reservoir (the Colorado

cold water lakes aquatic life minimum DO concentration (CDPHE, 2011a)).



approach attempted to define the SI range based on related standard or thresholds

for adverse effects, but consistency in definition of corresponding SI values across

parameters was problematic. Additionally, for this system, those set points created

compression of most of the observed data on the higher end of the scale.

o Minimum observed values were purposefully not set to the bottom of the SI scale to

leave some range for WQI measurement of worse water quality. Specifically, 20% of

the observed range was reserved at the bottom of the scale.

Curves for each transform were set as second order polynomials.

o This shape reflects a value‐decision that greater changes in sub‐index results should

occur for differences in parameter measurements at the lower end of the scale. In

other words, improvements in poorer water quality are valued more highly than

improvements at the higher end (e.g., above standards).

o The use of second order polynomials also allowed for designation of three set points

to define the curves. The third set point in each case was set at an SI value of 100

and was used to define where the scale “maxes out”. All results better than that

value produce an SI result of 100. These “max out” set points are described in the

parameter‐specific transform discussions below.

Chlorophyll a Sub‐Index Transform

The transform to convert chlorophyll a results to SI values was developed by defining a second

order polynomial curve through three chosen set points. First, a standard‐based set point was

placed at an SI value of 80 and a March‐November average chlorophyll a concentration of 5

ug/L. This corresponds to the interim standard value for DUWS lakes5. The chlorophyll a interim

standard value for large, non‐DUWS cold water lakes and reservoirs is 8 ug/L5. While only one of

the three water bodies in the system may be a candidate for designation as a DUWS, there is a

chance that one or both of the other two could achieve this status in the future, given the range

of operational modification alternatives being considered by the U.S. Bureau of Reclamation.

Further, a review of data from 2005 through 2011 shows that exceedance of the 5 ug/L average

from March through November occurs more often than exceedance of the 8 ug/L average

assessed from July through September. Based on all of this, the TLNS group selected a

standards‐based set point of 5 ug/L, and the corresponding metric of the March through

November average.

The lower set point on the curve was set based on the range of observed data from 2005‐2011.

The March through November average chlorophyll a concentrations for the three water bodies

for the 7 years range from 2.4 ug/L to 11.5 ug/L. Taking 20% of this range and adding it to the

11.5 ug/L value gives a set point of 13.3 ug/L at an SI value of 1.

5 These interim values were set during the Colorado Water Quality Division Nutrient Rulemaking Hearing

on March 12, 2012 (CDPHE, 2011b).



The final set point was set to prevent the transform from “maxing out.” A value of 0 ug/L was

set at an SI value of 100. There was some discussion among the TLNS group about fishery

interests and the potential to limit the fishery at very low chlorophyll a concentrations. A higher

max out concentration with a turn down of the curve below that value was considered;

however, ultimately this was not implemented for several reasons. First, for these three water

bodies, the key fishery species are salmonids, which have very low optimum chlorophyll a

concentrations (Oglesby et al., 1987), on the order of 2 ug/L or less. Next, it is recognized that

optimum chlorophyll a concentrations for a fishery are very lake‐specific, and at this time there

is not a good estimate of exactly where such an inflection point should be set (Anthony, 2012,

personal communication). Finally, the State of Colorado’s stated goal of protecting the various

uses as opposed to optimizing each use was a helpful concept. Based on all of this, the set point

was placed at 0 ug/L for the simplest curve. The analysis will specifically note results that

produce average chlorophyll a concentrations below 2 ug/L for consideration of potential

adverse effects to fisheries.

Figure 2 presents the chlorophyll a transform curve, the three set points, and the observed data

from each water body from 2005 through 2011. Review of this figure shows greater chlorophyll

a concentrations in Shadow Mountain Reservoir and Grand Lake, as compared to Granby

Reservoir. This matches the technical system understanding (Hydros, 2012).

Figure 2. Sub-Index Transformation for Chlorophyll a



Dissolved Oxygen Sub‐Index Transform

The transform to convert dissolved oxygen results to SI values was developed by defining a

second order polynomial curve through three chosen set points. First, a standard‐based set

point was placed at an SI value of 90 and an annual minimum (0.5 m to 2 m average) dissolved

oxygen concentration of 7 mg/L. This corresponds to the dissolved oxygen spawning standard

for the Three Lakes. Originally, the set point was placed at 6 mg/L, corresponding to the cold

water lakes dissolved oxygen standard value, which is assessed as an annual minimum (CDPHE,

2011a). It was this standard that was cited in the 303d Listing of Shadow Mountain Reservoir

(CDPHE, 2012). The TLNS group, however, expressed concern that the spawning standard

should be applied, regardless of the fact that the State of Colorado does not mention it in their

assessment. The 303d Listing methodology (CDPHE, 2011c) indicates that the spawning

standard should be assessed against a mid‐October through July minimum. From 2005‐2011,

the annual minimum fails to meet the 6 mg/l value more often than the mid‐October through

July minimum fails to meet the 7 mg/l. Taking a conservative approach, however, it is

recognized that the spawning period for some species may extend back into September. Annual

minimum dissolved oxygen concentrations often occur near the end of September in this

system. Based on all of this, the TLNS group selected a set point of 7 mg/L and a metric of

annual minimum.

The lower set point on the curve was defined based on the range of observed data from 2005‐

2011. The annual minimum dissolved oxygen concentrations (0.5 m to 2 m) for the three water

bodies for the 7 years range from 4.9 mg/L to 7.9 mg/L. Taking 20% of this range and

subtracting it from the 4.9 mg/L value gives a set point of 4.3 mg/L at an SI value of 1.

The final set point was set to a value of 8 mg/L. The annual minimum dissolved oxygen value is

theoretically limited by peak water temperatures and altitude to be below 8 mg/L. Values

above saturation (super‐saturation) are not the concern being evaluated by this metric (i.e., the

aquatic life standard and 303d Listing focused on inadequate dissolved oxygen concentrations).

Further, the Colorado Division of Wildlife indicated that there are no current concerns about

super‐saturation in these water bodies (Anthony, 2012, personal communication).

Figure 3 presents the dissolved oxygen transform curve, the three set points, and the observed

data from each water body for 2005 through 2011. This figure clearly distinguishes the

dissolved oxygen issues in Shadow Mountain Reservoir from those in Grand Lake and Granby

Reservoir, which is a good reflection of the data and related water quality concerns.



Figure 3. Sub-Index Transformation for Dissolved Oxygen

Clarity Sub‐Index Transform

The transform to convert Secchi depth results to SI values was developed by defining a second

order polynomial curve through three chosen set points. First, a standards‐based set point was

placed at an SI value of 80 and a Secchi depth of 4 m (assessed as the average of July through

September 15). This metric for Secchi depth differs from the metric for the proposed standard6

(15th percentile assessed from July through September). The WQI metric was selected by the

TLNS Committee to better reflect the average conditions during the peak tourism season and in

response to findings from 2011. Specifically, the metric for the proposed standard (15th

percentile, July through September) indicated that 2011 clarity was not as good as that of 2009.

This outcome of the 15th percentile metric did not match the TLNS Committee’s perception or

intent in optimizing clarity. Specifically, in 2011, Grand Lake exhibited the greatest (deepest)

summer‐time clarity observed since initiation of C‐BT operations, due to high runoff volumes

6 The Colorado Water Quality Control Commission (Commission) adopted a 4‐meter Secchi depth numerical clarity

standard (assessed as the 15th percentile of July through September observation) to be effective by 2015 if a more

appropriate standard has not been determined (CDPHE, 2011a).



and no Farr pumping in July and August. Note that the use of this July through September 15

metric in the WQI does not indicate any statement by the TLNS group regarding the appropriate

metric to be used in the future for the Grand Lake standard.

The lower set point on the curve was set based on the range of observed data from 2005‐2011.

The July through September 15 average Secchi depths for the three water bodies for the 7 years

range from 1.8 m to 5.9 m. Taking 20% of this range and subtracting it from the 1.8 m value

gives a set point of 1.0 m at an SI value of 1.

For Secchi depth, the “max out” set point (at an SI value of 100) was set to the highest value

possible while applying the other two set points and using a second order polynomial curve. To

achieve this, the set point was set equal to 6.4 m, which corresponds to the vertex of the

parabola. Use of a logarithmic equation was also considered, based on the other two set points;

however, the line would have maxed out lower, at 5.7 m, and the higher max out was preferable

to the TLNS group. The 6.4 m value, assessed as a July through September 15 average, captures

the complete observed range with room for additional improvement in all three water bodies.

Improvements above this value are expected to be difficult to achieve, but would still be

apparent in review of the complete metrics results that will accompany each model run

assessment.

Figure 3 presents the Secchi transform curve, the three set points, and the observed data from

each water body for 2005 through 2011. This figure clearly distinguishes the Shadow Mountain

Reservoir and Grand Lake clarity issues from those in Granby Reservoir. The figure also shows

the one year of exceptional clarity in Grand Lake (at a July through September 15 value of 5.3 m)

that was observed in 2011 in response to high runoff volumes and markedly reduced summer‐

time C‐BT operations. The reflection of these recognized patterns in the transform is a good

indication that the transform is functioning well for this set of observed data.



Figure 4. Sub-Index Transformation for Secchi Depth

2.4 Step4:DefineCompilationApproachA method is needed to compile sub‐index results into a final WQI result for each lake and the

entire Three Lakes System. Two compilation options were originally evaluated. The first

compilation option was termed “Common Indices” and involved development of separate WQI

results for each lake applying the same three sub‐indices. WQI results for each lake would be

averaged to generate the System WQI. This method is appealing because of its consistency in

approach for each water body. This method also allows for comparison of WQI results across

the water bodies and easier communication/explanation of results. Additionally, this method

allows the WQI to capture unexpected water quality deterioration to DO or clarity that is not

included in the more limited key index list defined for the second compilation option. The

Common Indices method is presented in Figure 5.



Figure 5. Compilation Option 1: Common Indices Method

The second compilation option was termed “Lake‐Specific Parameters” and focuses on the

specific parameters of concern for each water body, combining those sub‐index results into the

System WQI. This method is appealing because it focuses on the key parameters of concern

identified by the TLNS Technical Committee, without potential distraction by other parameters

of lesser concern (e.g., clarity in Granby). This method, however, would not allow for direct

comparison of lake‐specific WQI results. The Lake‐Specific Parameter Method is presented in

Figure 6.

Each Lake/Reservoir:

• Secchi • Chl a • DO

WQI ‐ Grand Lake

WQI – Shadow Mountain

R

WQI – Granby Res.

Average = System WQI (1‐100)

Harmonic

Mean for

Each Lake:

WQI (1‐

100)

SI (1‐100)

SI (1‐100)

SI (1‐100)



Figure 6. Compilation Option 2: Lake-Specific Parameters Method

For each method, a harmonic mean (Figure 7) would be used to combine sub‐index results into

the WQI result(s). A harmonic mean was considered superior to arithmetic or geometric

averaging because it more heavily weights the lower values in the series to be averaged, by

nature of the calculation (the reciprocal of the arithmetic mean of the reciprocals). A Smith’s

minimum operator‐type approach (Smith, 1990; the minimum sub‐index value is assigned as the

System WQI) was also considered but identified as inappropriate for this particular application.

Harmonic means have been applied in WQI development elsewhere (e.g., Cude, 2001).

Figure 7. Formula for Harmonic Mean.

Observed data from 2005 through 2011 were used to evaluate the different compilation

methods. System WQI results for each method are plotted in Figure 8.

WQI ‐ Grand Lake

Lake WQI

(1‐100)

• Grand Lake – Secchi • Grand Lake ‐ Chl a • Shadow Mountain ‐ DO • Shadow Mountain ‐ Chl a • Granby Res. – DO • Granby Res. ‐ Chl a

SI (1‐100)

SI (1‐100)

SI (1‐100)

SI (1‐100)

SI (1‐100)

SI (1‐100)

Harmonic

Mean for

System WQI

(1‐100)



Figure 8. Comparison of Results for Two Compilation Methods; Observed Data 2005-2011.

As shown in Figure 8, relative results for the two methods match for the observed record from

2005 through 2011. Both methods rank the years from worst to best as 2007, 2005, 2008, 2006,

2010, 2009, then 2011. Results for the two methods are similar due to the structure of the sub‐

index transformations and the selection of the key indices. In the Common Indices Method,

sub‐index results for measures that are not included in the key indices selected for the Lake‐

Specific Parameter Method generally show high sub‐index values that do not vary much.

Further, because of the use of the harmonic mean in each method, the “worst player” tends to

drive the WQI result in both compilation methods. Because the key indices selected for the

Lake‐Specific Parameter Method include the “worst player” in these years, relative results are

very similar.

In short, the concerns about extra (non‐key) metrics obscuring the System WQI for the Common

Indices Approach appear to be invalid. As such, due to the simplicity of approach, ease of

communication of results, and greater ability to cross‐compare lake WQI results, the Common

Indices Approach was selected by the TLNS Technical Committee for use in evaluation of model

results.

2.5 Step5:EvaluateWQIPerformanceonObservedData

As part of the evaluation of compilation methods, observed data from 2005 through 2011 were

evaluated using the developed WQI approach (Figure 8). The WQI results reflected the TLNS

Technical Committee’s observations and recollections of water quality for the parameters

evaluated. Specifically, the group wanted to make sure that the resultant ranking of observed

years matched their understanding of conditions. Additionally, while recognizing that the scale



is relative, the TLNS group felt it was important, for external communication purposes, that the

actual numeric results reflect their perceptions of water quality. In other words, the group

wanted years with poor water quality to produce a system WQI value that would indicate

“poor” conditions to an outsider without the context of comparison to other years.

The Lake‐Specific and System‐Wide WQI results for 2005‐2011 are presented in Figure 9 and

Figure 10, respectively. A few highlights from these plots are noted below to compare some

key results to technical system understanding and perceptions.

The WQI shows that Shadow Mountain Reservoir consistently exhibits the worst water

quality of the Three Lakes.

The WQI also shows that Grand Lake water quality is the next worst, with the exception

of 2011. In 2011, high runoff volumes and dramatically reduced summer C‐BT

operations resulted in a Grand Lake WQI score of 93. This high score is primarily due to

a sharp increase in the Secchi depth SI score that year, reflecting the large improvement

in clarity.

Granby Reservoir consistently exhibits a relatively high (>80) system score without much

variation from year to year. This matches the technical understanding of how this large

water body behaves (Hydros, 2012).

The 2007 system score is 55 out of 100, which reflects the high algal concentrations,

poor clarity, and low minimum dissolved oxygen concentrations observed during this

very warm year with active C‐BT operations.

The lake/reservoir‐specific results for 2007 reflect the very poor water quality in Shadow

Mountain Reservoir, with a WQI result of 31 out of 100. The effects on Grand Lake are

also apparent with the WQI result of 50 out of 100.

Overall, these values reflect the TLNS group perception of the range of conditions contained

within the 2005 through 2011 dataset. As such, the method passed this observed data review

test and was deemed ready for application to modeling results. It is important to note that the

results presented here are the product of a few rounds of index testing and revisions. As such, a

caution is added to the WQI status that the results from this new WQI tool should be carefully

and critically reviewed with each new application. If the WQI is found to be producing

misleading results for some reason, there may be cause to make modification to the index or

simply to not apply the index to the specific application.



Figure 9. Lake/Reservoir-Specific WQI Results for Observed Data, 2005-2011.

Figure 10. System-Wide WQI Results for Observed Data, 2005-2011.



3 AdditionalMetrics

It was decided that a table of additional metrics should be compiled for each modeling run for

review in conjunction with WQI results. The purpose of the table is to support the following:

Ongoing critical review of modeling results and the WQI method;

Ongoing development of the conceptual understanding of the system, in terms of

responses to operations;

Tie‐breaking (when system WQI results are close for different runs, these additional

metrics can be used to help decide which run actually produced more desirable water

quality); and

Assessing water quality concerns not specifically calculated for the WQI numeric result,

such as:

o The proposed metric for clarity on Grand Lake (CDPHE, 2011a),

o The metric for the interim non‐DUWS chlorophyll a standard (CDPHE, 2011a),

o The 303d Listing Methodology metric for the dissolved oxygen spawning

standard (CDPHE, 2011c).

Table 1 presents the list of additional metrics for development with each run.



Table 1. List of Additional Metrics

Parameter Group Metric Units

Dissolved Oxygen

Granby Res. - DO (0.5 to 2 m), # days/yr <6 mg/L days

Shadow Mountain – DO (0.5 to 2 m), # days/yr <6 mg/L days

Grand Lake – DO (0.5 to 2 m) , # days/yr <6 mg/L days

Granby Res. – Minimum DO (mid-October through July) mg/L

Shadow Mountain – Minimum DO (mid-October through July) mg/L

Grand Lake – Minimum DO (mid-October through July) mg/L

Chlorophyll a

Granby Res. – Chl a, July-Sept., # days >8 ug/L days

Shadow Mountain – Chl a, July-Sept., # days >8 ug/L days

Grand Lake – Chl a, July-Sept., # days >8 ug/L days

Granby Res. – Chl a, July-Sept., Max ug/L

Shadow Mountain – Chl a, July-Sept., Max ug/L

Grand Lake – Chl a, July-Sept., Max ug/L

Grand Lake – Chl a, July-Sept., Average* ug/L

Shadow Mountain – Chl a, July-Sept., Average* ug/L

Granby Res. – Chl a, July-Sept., Average* ug/L

Secchi Depth

Grand Lake – Secchi Depth, July-Sept., # days <4 m days

Grand Lake – Secchi Depth, July-Sept., Max m

Grand Lake – Secchi Depth, July-Sept., Min m

Grand Lake – Secchi Depth, July-Labor Day, 15th %ile m

Grand Lake – Secchi Depth, July-Sept., 15th %ile (Proposed Std.) m

*If the July through September average chlorophyll a concentrations are < 2 ug/L, this result is highlighted for discussion as a potential concern for fishery productivity.



4 Implementation

A macro‐driven tool was developed to compile modeling results into the sub‐indices, lake‐

specific WQIs and system WQIs. The tool also compiles the Additional Metrics table. For model

runs with multiple years of results (nutrient sensitivity runs each simulate 6 years of water

quality), system WQI results for each year are arithmetically averaged to produce the composite

system WQI.

As stated above, it is recognized that performance of the WQI should be reviewed with each

application to ensure that it is continuing to perform as intended. If the index is found to be

inadequate for any particular application, it may be revised or simply not applied to that

particular application. Examples of inadequate WQI performance include insensitivity to

changes in water quality, significant incongruities between WQI results and the full set of water

quality metrics under review, or misleading obfuscation of poor water quality in one part of the

system due to improvements in another part of the system.

5 References

Anthony, J. 2012. Personal Communication. Email exchange between Jamie Anthony of the

Colorado Division of Wildlife and Christine Hawley of Hydros Consulting. October 22,

2012.

Boyacioglu, H. 2007. Development of a Water Quality Index Based on a European Classification

Scheme. Water SA, Vol. 33, No. 1, January, 2007.

Carlson, R.E. 1977. A trophic state index for lakes. Limnology and Oceanography. 22:361‐369.

Colorado Department of Public Health and Environment (CDPHE). 2011a. Classifications and

Numeric Standards for Upper Colorado River Basin and North Platte River (Planning

Region 12). 5 CCR 1002‐33 (Regulation 33). Water Quality Control Commission.

Amended June 13, 2011; Effective January 12, 2012.

CDPHE. 2011b. Notice of Public Rulemaking Hearing before the Water Quality Control

Commission. Letter dated November 21, 2011.

CDPHE. 2011c. Section 303(d) Listing Methodology, 2012 Listing Cycle. Water Quality Control

Commission. March, 2011.

CDPHE. 2012. Colorado’s 303(D) List of Impaired Waters and Monitoring and Evaluation List. 5

CCR 1002‐93 (Regulation 93). Water Quality Control Commission. Amended February 13,

2012; Effective March 30, 2012.



Cude, C.G. 2001. Oregon Water Quality Index: A Tool for Evaluating Water Quality Management Effectiveness. Journal of American Water Resources Association; Vol. 37, No. 1. February 2001.

Fernández, N, A. Ramírez, and F. Solano. 2004. Physico‐chemico Water Quality Indices – A Comparative Review. Bistua: Revista de la Facultad de Ciencias Básicas, Vol. 2, No.001.

Ferriera, J.G. 2000. Development of and Estuary Quality Index based on Key Physical and

Biogeochemical Features. Ocean and Coastal Management, Vol. 33.

Horton, R.K. 1965. An Index‐Number System for Rating Water Quality. Journal of the Water Pollution Control Federation. Vol. 37, No. 3.

Hydros Consulting Inc. 2012. Draft Annual Water Quality Report for the Three Lakes. Prepared for Northern Water. Final document expected December 2012.

Lumb, A., T.C. Sharma, and J.F. Bibeault. 2011. A Review of Genesis and Evolution of Water Quality Index (WQI) and Some Future Directions. Water Quality Expo Health. Vol. 3.

Oglesby. R. T., J. H. Leach, and J. Forney. 1987. Potential Stizostedion yield as a function of chlorophyll concentration with special reference to Lake Erie. Can. J. Fish. Aquat. Sci. 44 (Suppl. 2): 166‐170.

Smith, D.G. 1990. A Better Water Quality Indexing System for Streams and Rivers. Water Research. Vol. 24.

Three Lakes Model Nutrient Sensitivity Analysis – Appendix C January 27, 2014


Appendix C ‐ Detailed Results –Reductions in System‐Wide Inflow Loads, Internal Loads, and Stormwater Loads


Simulation and Year Granby Res. ‐M

in DO (mg/L)

Shadow M

tn.‐Min DO (mg/L)

Grand Lake

‐Min DO (mg/L)

Granby Res. Chl a

(Avg., µg/L)

Shadow M

tn. C

hl a

(Avg., µg/L)

Grand Lake

Chl a

(Avg., µg/L)

Granby Res. ‐Secchi D

epth (Avg., m

)

Shadow M

tn. ‐Secchi D

epth (Avg., m

)

Grand Lake

‐Secchi D

epth (Avg., m

)

Granby Res. ‐M

in DO

Shadow M

tn.‐Min DO

Grand Lake

‐Min DO

Granby Res. Chl a

Shadow M

tn. C

hl a

Grand Lake

Chl a


epth

Shadow M

tn. ‐Secchi D

epth

Grand Lake

‐Secchi D

epth

un Num Granby Res.

Shadow M

tn.

Grand Lake

System

Score

Base Case ‐ 2005 6.6 5.3 6.9 2.6 4.4 2.2 4.7 1.9 4.5 81.8 43.0 87.5 92.2 83.4 93.8 89.7 31.1 87.0 Ru ## 87.7 44.5 89.3 73.8 90.8

Base Case ‐ 2006 6.6 5.4 6.8 2.8 3.9 3.0 6.2 2.0 2.4 82.1 48.8 87.0 91.5 86.1 90.4 99.7 34.2 45.2 ## 90.6 48.9 67.2 68.9 44.0

Base Case ‐ 2007 6.6 4.7 6.4 2.4 6.0 4.0 6.6 1.7 2.4 81.6 20.9 78.8 93.1 73.6 85.8 100.0 24.9 46.1 ## 90.9 29.5 65.2 61.9 75.0

Base Case ‐ 2008 6.7 5.0 6.6 2.8 4.2 2.9 5.7 1.8 2.8 85.1 32.8 82.4 91.4 84.7 90.8 98.0 27.4 56.8 ## 91.2 38.1 73.6 67.6

Base Case ‐ 2009 6.9 5.7 6.8 2.8 4.2 2.6 5.7 2.1 3.4 88.2 59.8 86.7 91.6 84.6 92.0 98.0 36.8 69.9 ## 92.4 53.8 81.7 76.0 Run0

Base Case ‐ 2010 6.7 5.7 6.7 2.5 4.0 2.6 6.0 1.9 2.7 84.4 58.2 85.1 92.7 85.9 92.1 99.4 31.0 53.6 ## 91.8 49.1 72.7 71.2 70

Ultra‐Clean ‐ 2005 6.4 5.1 6.9 0.3 0.3 0.3 8.5 3.5 7.0 78.4 36.4 87.4 99.5 99.3 99.4 100.0 70.3 100.0 Rua‐Cl 91.4 58.0 95.3 81.6 93.5

Ultra‐Clean ‐ 2006 6.6 5.3 6.8 0.2 0.3 0.2 9.4 3.9 4.7 82.3 45.3 86.7 99.6 99.3 99.5 100.0 78.4 89.6 Ultra‐Cl 93.2 66.9 91.6 83.9 56.7

Ultra‐Clean ‐ 2007 6.5 4.5 6.4 0.2 0.3 0.2 9.5 3.9 5.0 80.9 12.4 78.0 99.7 99.4 99.6 100.0 79.2 93.2 Ultra‐Cl 92.6 29.0 89.3 70.3 92.2

Ultra‐Clean ‐ 2008 6.7 4.8 6.5 0.3 0.4 0.2 8.8 3.6 5.2 85.1 23.3 81.2 99.4 99.1 99.5 100.0 73.4 94.3 Ultra‐Cl 94.3 45.1 91.0 76.8

Ultra‐Clean ‐ 2009 6.9 5.6 6.8 0.3 0.6 0.3 8.7 3.5 5.5 87.7 54.0 86.1 99.4 98.8 99.5 100.0 70.7 96.9 Ultra‐Cl 95.3 70.1 93.8 86.4 Run1

Ultra‐Clean ‐ 2010 6.7 5.6 6.7 0.2 0.4 0.2 9.2 3.6 5.0 84.4 54.9 84.5 99.6 99.3 99.6 100.0 73.0 93.0 Ultra‐Cl 94.1 71.4 92.0 85.8 81

Int‐50% ‐ 2005 6.6 5.2 6.8 2.4 3.2 1.5 5.0 2.1 4.8 82.1 40.6 87.4 92.8 89.8 96.2 93.1 36.4 90.4 Ru ‐50 89.0 47.4 91.2 75.9 91.4

Int‐50% ‐ 2006 6.6 5.4 6.8 2.4 2.6 2.0 6.3 2.2 2.6 82.1 47.5 86.7 92.9 92.0 94.6 100.0 40.2 51.6 Int‐50 91.1 52.8 72.3 72.1 47.4

Int‐50% ‐ 2007 6.6 4.7 6.4 2.0 3.9 2.8 6.7 2.1 2.8 81.6 18.0 78.5 94.7 86.2 91.4 100.0 37.6 56.3 Int‐50 91.4 32.0 72.4 65.3 79.0

Int‐50% ‐ 2008 6.7 4.9 6.6 2.5 2.8 2.0 5.7 1.9 3.0 85.1 29.6 81.8 92.7 91.4 94.4 98.3 32.6 61.3 Int‐50 91.7 39.8 76.7 69.4

Int‐50% ‐ 2009 6.9 5.7 6.8 2.4 2.8 1.8 5.8 2.3 3.7 88.2 58.0 86.3 93.1 91.5 95.2 98.3 43.2 74.6 Int‐50 93.0 58.4 84.5 78.7 RunB

Int‐50% ‐ 2010 6.7 5.7 6.7 2.0 2.6 1.7 6.1 2.1 2.9 84.3 57.2 84.7 94.5 92.4 95.5 99.6 36.9 59.4 Int‐50 92.3 54.2 76.7 74.4 73

Int‐Off ‐ 2005 6.6 5.2 6.8 2.3 1.9 0.9 5.0 2.3 5.1 81.6 38.7 87.0 93.2 94.8 97.9 92.8 43.5 94.0 Rut‐Of 88.9 50.5 92.8 77.4 91.7

Int‐Off ‐ 2006 6.6 5.4 6.8 2.1 1.5 0.9 6.2 2.4 2.9 82.2 46.8 86.4 94.3 96.1 98.0 99.8 45.9 58.2 C Int‐Of 91.5 56.0 77.0 74.8 50.4

Int‐Off ‐ 2007 6.6 4.6 6.4 1.7 1.6 0.9 6.6 2.7 3.5 81.6 16.3 77.9 95.7 95.9 97.9 100.0 54.4 70.4 C Int‐Of 91.7 33.3 80.5 68.5 83.2

Int‐Off ‐ 2008 6.7 4.9 6.5 2.4 1.5 1.1 5.7 2.1 3.3 85.1 26.7 81.3 93.1 96.1 97.5 98.1 38.7 67.6 C Int‐Of 91.8 40.7 80.3 70.9

Int‐Off ‐ 2009 6.9 5.6 6.8 2.0 1.3 0.9 5.8 2.6 4.0 88.1 55.7 85.9 94.4 96.7 97.8 98.6 50.9 80.1 C Int‐Of 93.5 62.6 87.3 81.1 RunC

Int‐Off ‐ 2010 6.7 5.6 6.7 1.6 1.2 0.7 6.1 2.3 3.3 84.3 56.0 84.3 96.0 97.2 98.5 99.7 44.0 66.9 C Int‐Of 92.8 59.0 81.2 77.7 75

Summary Values (Year‐Round for DO; Jul‐Sept15

Secchi; Mar‐Nov for Chl a) SUB‐INDEX RESULTS (1‐100, unitless) WQI (1‐100, unitless)

Page C‐1



in DO (mg/L)

Shadow M

tn.‐Min DO (mg/L)

Grand Lake

‐Min DO (mg/L)

Granby Res. Chl a

(Avg., µg/L)

Shadow M

tn. C

hl a

(Avg., µg/L)

Grand Lake

Chl a

(Avg., µg/L)


epth (Avg., m

)

Shadow M

tn. ‐Secchi D

epth (Avg., m

)

Grand Lake

‐Secchi D

epth (Avg., m

)

Granby Res. ‐M

in DO

Shadow M

tn.‐Min DO

Grand Lake

‐Min DO

Granby Res. Chl a

Shadow M

tn. C

hl a

Grand Lake

Chl a


epth

Shadow M

tn. ‐Secchi D

epth

Grand Lake

‐Secchi D

epth

un Num Granby Res.

Shadow M

tn.

Grand Lake

System

Score



Inf ‐50% ‐ 2005 6.5 5.3 6.9 2.1 3.8 2.0 5.4 1.9 4.6 81.1 42.5 87.5 94.2 86.8 94.6 96.3 32.7 88.5 Ru ‐50 90.0 45.7 90.1 75.3 91.9

Inf ‐50% ‐ 2006 6.6 5.4 6.8 2.1 3.4 2.7 6.8 2.0 2.5 82.0 47.9 86.7 94.0 88.6 91.8 100.0 36.1 48.1 Inf ‐50 91.4 50.1 69.4 70.3 44.6

Inf ‐50% ‐ 2007 6.6 4.7 6.4 1.9 5.6 3.8 7.1 1.7 2.5 81.5 19.1 78.3 94.7 76.3 86.5 100.0 26.3 47.9 Inf ‐50 91.4 29.0 66.4 62.2 76.4

Inf ‐50% ‐ 2008 6.7 5.0 6.6 2.1 3.8 2.6 6.2 1.8 3.0 84.8 30.9 81.9 94.1 86.8 92.3 99.8 28.3 60.2 Inf ‐50 92.5 37.9 75.7 68.7

Inf ‐50% ‐ 2009 6.9 5.7 6.8 2.2 3.8 2.4 6.2 2.1 3.6 87.8 58.6 86.6 94.0 86.8 93.1 99.8 38.2 72.3 Inf ‐50 93.6 54.8 83.1 77.2 RunD

Inf ‐50% ‐ 2010 6.7 5.7 6.7 2.0 3.6 2.4 6.5 1.9 2.8 84.2 57.7 84.8 94.5 87.9 93.1 100.0 31.8 55.7 Inf ‐50 92.4 49.9 74.1 72.1 71

Inf‐Pristine ‐ 2005 6.5 5.2 6.9 1.6 3.3 1.7 7.3 2.6 5.8 81.1 41.8 88.1 95.8 89.3 95.7 100.0 52.0 98.6 RuPrist 91.6 55.2 93.9 80.2 92.6

Inf‐Pristine ‐ 2006 6.6 5.5 6.9 1.9 3.1 2.5 8.1 2.9 3.4 82.5 50.4 87.8 94.7 89.9 92.6 100.0 57.3 70.1 nf‐Prist 91.8 62.0 82.3 78.7 55.5

Inf‐Pristine ‐ 2007 6.6 4.8 6.5 1.4 5.2 3.8 8.6 2.2 3.1 81.9 23.4 80.1 96.6 78.5 86.8 100.0 39.1 63.1 nf‐Prist 92.1 37.0 75.3 68.1 85.3

Inf‐Pristine ‐ 2008 6.7 5.0 6.6 1.6 3.5 2.4 8.0 2.7 4.1 85.2 33.5 83.5 95.7 88.4 93.0 100.0 53.9 81.5 nf‐Prist 93.2 50.2 85.7 76.4

Inf‐Pristine ‐ 2009 6.9 5.8 6.9 1.9 3.5 2.2 7.4 2.6 4.5 88.1 61.0 87.8 94.8 88.3 93.9 100.0 52.0 87.3 nf‐Prist 94.0 63.9 89.6 82.5 RunE

Inf‐Pristine ‐ 2010 6.7 5.8 6.8 1.7 3.3 2.3 8.0 2.7 3.8 84.6 60.1 86.5 95.5 89.0 93.5 100.0 53.5 77.1 nf‐Prist 92.9 64.4 85.1 80.8 78

SW‐50% ‐ 2005 6.6 5.2 6.9 2.4 4.2 2.0 5.1 1.9 4.6 81.6 42.1 87.5 93.1 84.5 94.7 94.1 32.3 88.9 RuW‐50 89.2 45.1 90.3 74.9 91.4

SW‐50% ‐ 2006 6.6 5.4 6.8 2.3 3.7 2.9 6.5 2.0 2.4 82.1 48.6 87.2 93.2 87.1 91.0 100.0 35.3 46.5 SW‐50 91.2 49.7 68.2 69.7 44.3

SW‐50% ‐ 2007 6.6 4.7 6.4 2.1 5.8 4.0 6.7 1.7 2.4 81.6 20.2 78.7 94.2 74.6 85.9 100.0 25.7 46.7 SW‐50 91.3 29.4 65.6 62.1 75.5

SW‐50% ‐ 2008 6.7 5.0 6.6 2.5 4.1 2.8 5.8 1.8 2.9 85.0 31.9 82.2 92.5 85.3 91.2 98.7 27.7 57.2 SW‐50 91.7 37.9 73.9 67.8

SW‐50% ‐ 2009 6.9 5.7 6.8 2.4 4.1 2.6 5.9 2.1 3.5 88.0 59.4 86.8 92.9 85.3 92.4 99.0 37.2 70.3 SW‐50 93.1 54.1 82.0 76.4 RunF

SW‐50% ‐ 2010 6.7 5.7 6.7 2.1 3.8 2.6 6.2 1.9 2.7 84.3 58.6 85.0 94.0 86.6 92.3 99.8 31.5 53.8 SW‐50 92.2 49.7 72.8 71.6 70

SW‐Off ‐ 2005 6.5 5.2 6.8 2.0 3.9 1.7 5.3 2.0 4.8 80.4 40.7 87.3 94.4 86.1 95.6 95.3 33.6 91.1 RuW‐O 89.5 45.5 91.2 75.4 91.9

SW‐Off ‐ 2006 6.6 5.4 6.8 1.9 3.5 2.7 6.7 2.1 2.5 82.1 49.5 86.9 94.7 88.1 91.9 100.0 36.3 47.7 G SW‐O 91.6 50.7 69.2 70.5 44.8

SW‐Off ‐ 2007 6.6 4.7 6.4 1.8 5.6 3.8 6.9 1.7 2.5 81.6 19.6 79.1 95.3 76.1 86.7 100.0 27.0 48.3 G SW‐O 91.6 29.6 66.9 62.7 76.2

SW‐Off ‐ 2008 6.7 5.0 6.6 2.2 3.9 2.7 6.0 1.8 2.9 84.9 31.0 82.0 93.6 86.1 91.7 99.2 28.0 57.6 G SW‐O 92.2 37.7 74.2 68.0

SW‐Off ‐ 2009 6.9 5.7 6.8 2.1 3.9 2.5 6.2 2.1 3.5 87.8 59.0 87.2 94.1 86.0 92.7 99.7 37.8 70.7 G SW‐O 93.6 54.5 82.4 76.9 RunG

SW‐Off ‐ 2010 6.7 5.7 6.8 1.8 3.6 2.5 6.5 1.9 2.7 84.2 59.6 85.5 95.1 87.5 92.7 100.0 32.3 54.4 G SW‐O 92.6 50.7 73.5 72.3 71

Page C‐2



in DO (mg/L)

Shadow M

tn.‐Min DO (mg/L)

Grand Lake

‐Min DO (mg/L)

Granby Res. Chl a

(Avg., µg/L)

Shadow M

tn. C

hl a

(Avg., µg/L)

Grand Lake

Chl a

(Avg., µg/L)


epth (Avg., m

)

Shadow M

tn. ‐Secchi D

epth (Avg., m

)

Grand Lake

‐Secchi D

epth (Avg., m

)

Granby Res. ‐M

in DO

Shadow M

tn.‐Min DO

Grand Lake

‐Min DO

Granby Res. Chl a

Shadow M

tn. C

hl a

Grand Lake

Chl a


epth

Shadow M

tn. ‐Secchi D

epth

Grand Lake

‐Secchi D

epth

un Num Granby Res.

Shadow M

tn.

Grand Lake

System

Score



Inf/Int‐50% ‐ 2005 6.5 5.2 6.8 1.7 2.5 1.3 5.5 2.1 4.9 80.6 39.2 87.2 95.4 92.8 96.7 96.7 38.1 92.2 Runt‐5 90.3 48.0 91.9 76.7 92.3

Inf/Int‐50% ‐ 2006 6.6 5.4 6.8 1.8 2.1 1.7 6.9 2.2 2.7 82.0 46.6 86.4 95.4 94.0 95.6 100.0 41.8 54.1 nf/Int‐5 91.8 53.6 74.0 73.1 47.4

Inf/Int‐50% ‐ 2007 6.6 4.6 6.4 1.5 3.4 2.6 7.2 2.2 2.9 81.5 16.0 77.9 96.1 88.5 92.3 100.0 39.1 58.6 nf/Int‐5 91.8 30.2 73.7 65.2 80.3

Inf/Int‐50% ‐ 2008 6.7 4.9 6.5 1.7 2.3 1.7 6.3 2.0 3.2 84.8 27.6 81.3 95.4 93.3 95.6 99.9 33.6 65.0 nf/Int‐5 92.9 39.1 78.6 70.2

Inf/Int‐50% ‐ 2009 6.9 5.7 6.8 1.8 2.4 1.5 6.3 2.4 3.8 87.8 56.7 86.0 95.3 93.1 96.0 99.9 44.6 77.0 nf/Int‐5 94.1 59.1 85.7 79.6 RunH

Inf/Int‐50% ‐ 2010 6.7 5.6 6.7 1.5 2.2 1.5 6.5 2.1 3.0 84.2 56.4 84.4 96.0 93.9 96.3 100.0 37.8 61.7 nf/Int‐5 92.9 54.7 78.0 75.2 73

Int/SW‐50% ‐ 2005 6.5 5.2 6.8 2.2 3.1 1.4 5.1 2.1 4.9 81.1 40.4 87.2 93.7 90.3 96.6 94.1 37.6 92.0 RuW‐5 89.2 48.0 91.8 76.3 91.8

Int/SW‐50% ‐ 2006 6.6 5.4 6.8 2.0 2.5 1.8 6.5 2.2 2.7 82.1 47.3 86.7 94.6 92.5 95.1 100.0 40.8 52.3 t/SW‐5 91.6 53.1 72.9 72.5 47.5

Int/SW‐50% ‐ 2007 6.6 4.7 6.4 1.7 3.7 2.6 6.8 2.1 2.9 81.6 17.5 78.4 95.5 87.0 92.1 100.0 38.4 57.4 t/SW‐5 91.7 31.7 73.1 65.5 79.4

Int/SW‐50% ‐ 2008 6.7 4.9 6.6 2.3 2.7 2.0 5.9 1.9 3.0 85.0 28.8 81.7 93.4 91.6 94.7 98.8 32.9 61.6 t/SW‐5 92.0 39.5 76.8 69.4

Int/SW‐50% ‐ 2009 6.9 5.7 6.8 2.1 2.7 1.7 6.0 2.3 3.7 88.0 57.4 86.2 94.3 91.9 95.5 99.2 43.5 75.0 t/SW‐5 93.6 58.5 84.7 78.9 RunI

Int/SW‐50% ‐ 2010 6.7 5.7 6.7 1.7 2.4 1.6 6.3 2.1 3.0 84.3 56.7 84.5 95.6 92.8 95.8 100.0 37.3 59.8 t/SW‐5 92.8 54.4 76.9 74.7 73

Inf/SW‐50% ‐ 2005 6.5 5.2 6.8 1.8 3.6 1.8 5.6 2.0 4.8 80.1 41.1 87.3 95.3 87.7 95.2 97.4 33.8 90.3 RuW‐5 90.2 45.9 90.8 75.7 92.2

Inf/SW‐50% ‐ 2006 6.6 5.4 6.8 1.8 3.3 2.6 7.0 2.1 2.5 82.0 47.7 86.7 95.3 89.2 92.2 100.0 36.7 48.7 f/SW‐5 91.8 50.5 69.9 70.7 44.8

Inf/SW‐50% ‐ 2007 6.6 4.7 6.4 1.7 5.4 3.8 7.2 1.7 2.5 81.5 18.3 78.3 95.7 77.2 86.5 100.0 27.0 48.3 f/SW‐5 91.7 28.7 66.6 62.3 76.8

Inf/SW‐50% ‐ 2008 6.7 4.9 6.6 1.8 3.7 2.5 6.4 1.8 3.0 84.7 30.0 81.7 95.1 87.3 92.6 100.0 28.6 60.6 f/SW‐5 92.8 37.6 75.9 68.8

Inf/SW‐50% ‐ 2009 6.9 5.7 6.8 1.8 3.6 2.3 6.5 2.1 3.6 87.7 58.2 87.0 95.1 87.5 93.5 100.0 38.8 72.7 f/SW‐5 94.0 55.1 83.4 77.5 RunJ

Inf/SW‐50% ‐ 2010 6.7 5.7 6.7 1.7 3.4 2.3 6.7 1.9 2.8 84.1 58.4 85.2 95.6 88.7 93.3 100.0 32.4 55.9 f/SW‐5 92.7 50.6 74.3 72.6 71

Inf/Int/SW 50% ‐ 2005 6.5 5.2 6.8 1.4 2.3 1.2 5.6 2.2 5.1 79.4 39.0 87.0 96.5 93.4 97.2 97.8 39.2 93.9 Ru/SW 90.4 48.5 92.5 77.1 92.6

Inf/Int/SW 50% ‐ 2006 6.6 5.4 6.8 1.4 2.0 1.6 7.1 2.3 2.8 81.9 46.2 86.3 96.5 94.4 96.0 100.0 42.5 54.9 /Int/SW 92.1 53.8 74.6 73.5 47.4

Inf/Int/SW 50% ‐ 2007 6.6 4.6 6.4 1.2 3.3 2.4 7.4 2.2 2.9 81.5 15.3 78.0 97.1 89.3 92.9 100.0 39.9 59.4 /Int/SW 92.1 29.5 74.2 65.3 80.7

Inf/Int/SW 50% ‐ 2008 6.7 4.9 6.5 1.5 2.2 1.6 6.5 2.0 3.2 84.7 26.6 81.1 96.3 93.7 95.9 100.0 34.0 65.4 /Int/SW 93.2 38.6 78.9 70.2

Inf/Int/SW 50% ‐ 2009 6.9 5.6 6.8 1.4 2.2 1.5 6.6 2.4 3.8 87.6 56.1 86.0 96.4 93.6 96.3 100.0 45.1 77.4 /Int/SW 94.4 59.2 85.9 79.8 RunK

Inf/Int/SW 50% ‐ 2010 6.7 5.6 6.7 1.2 2.0 1.4 6.8 2.1 3.1 84.1 55.9 84.2 97.1 94.3 96.6 100.0 38.3 62.1 /Int/SW 93.2 54.9 78.3 75.5 74

Page C‐3


Simulation and Year Granby Res. ‐ DO (ep

ilim., # days/yr <6

mg/L)

Shadow M

tn. ‐ DO (# days/yr <6 m

g/L)

Grand Lake

‐ DO (ep

ilim., # days/yr <6

mg/L)

Granby Res. ‐ Min DO (mid‐Oct through

July)

Shadow M

tn ‐ M

in DO (mid‐Oct through

July)

Grand Lake

‐ M


July)

Granby Res. Lake

Chl a

(# days >8 µg/L)

Shadow M

tn. C

hl a

(# days >8 µ

g/L)

Grand Lake

Chl a

(# days >8 µg/L)

Granby Res. Chl a

(Jul‐Sept, Avg., µg/L);

Results <2

ug/l highlighted for potential

fishery

concern

Shad

ow M

tn. C

hl a


Results <2


fishery

concern

Grand Lake Chl a

(July‐Sep

t, Avg., µg/L);

Results <2 ug/l highlighted for potential

fishery

concern

Granby Res. Chl a

(max, µg/L)

Shadow M

tn. C

hl a

(max, µ

g/L)

Grand Lake

Chl a

(max, µg/L)

Grand Lake

Chl a

(Avg. M

ar.‐Nov., µ

g/L)

Grand Lake

‐Secchi D

epth (# days <4, m

)

Grand Lake

‐Secchi D

epth (max, m

)

Grand Lake

‐Secchi D

epth (min, m

)

Grand Lake

‐Secchi D

epth (15th %ile, July

through

Labor Day, m

)

Grand Lake

‐Secchi D


through

Sep

t, m

)

Base Case ‐ 2005 0 59 0 6.6 5.5 7.0 0 12 0 1.9 6.2 3.0 3.2 8.4 5.0 2.2 38 6.1 2.2 3.9 2.6

Base Case ‐ 2006 0 46 0 6.7 5.6 6.9 0 25 17 1.5 5.6 5.3 3.5 10.3 8.5 3.0 92 3.4 1.9 2.0 2.0

Base Case ‐ 2007 0 59 0 6.6 5.0 7.0 0 62 50 1.2 11.6 8.4 2.4 18.9 15.1 4.0 78 5.6 1.5 1.6 1.6

Base Case ‐ 2008 0 60 0 6.8 5.1 7.0 0 28 12 2.0 6.3 4.8 4.1 10.3 8.8 2.9 79 4.6 1.9 2.2 2.1

Base Case ‐ 2009 0 47 0 7.0 5.9 6.9 0 26 0 2.1 6.3 4.1 4.1 9.9 7.7 2.6 68 5.3 2.0 2.7 2.1

Base Case ‐ 2010 0 33 0 6.9 6.1 7.0 0 28 0 1.5 6.2 4.8 2.9 10.3 7.6 2.6 88 4.2 2.2 2.3 2.2

Ultra‐Clean ‐ 2005 0 60 0 6.4 5.4 7.3 0 0 0 0.2 0.4 0.5 0.6 1.0 0.9 0.3 16 8.8 3.5 6.2 3.8

Ultra‐Clean ‐ 2006 0 46 0 6.7 5.5 7.3 0 0 0 0.2 0.3 0.4 0.4 0.6 0.7 0.2 4 6.9 3.8 4.1 4.0

Ultra‐Clean ‐ 2007 0 60 0 6.5 4.9 7.0 0 0 0 0.1 0.3 0.3 0.4 0.6 0.6 0.2 9 8.3 3.9 4.2 4.0

Ultra‐Clean ‐ 2008 0 60 0 6.8 5.0 7.0 0 0 0 0.3 0.4 0.4 0.8 1.0 0.6 0.2 21 7.2 3.9 4.4 3.9

Ultra‐Clean ‐ 2009 0 57 0 6.9 5.8 7.3 0 0 0 0.4 0.5 0.5 0.9 1.4 0.8 0.3 31 7.8 3.5 4.6 3.6

Ultra‐Clean ‐ 2010 0 34 0 6.7 6.1 7.2 0 0 0 0.3 0.4 0.4 0.6 1.0 0.7 0.2 26 7.3 3.7 4.1 3.8

Int‐50% ‐ 2005 0 59 0 6.6 5.4 7.1 0 0 0 2.0 4.1 2.5 3.2 5.8 4.5 1.5 31 6.5 2.4 4.2 2.8

Int‐50% ‐ 2006 0 46 0 6.7 5.6 6.9 0 0 0 1.5 3.3 3.4 3.1 5.7 5.2 2.0 92 3.5 2.2 2.3 2.3

Int‐50% ‐ 2007 0 60 0 6.6 4.9 7.0 0 44 38 1.1 7.0 6.1 2.2 11.3 10.8 2.8 76 5.8 1.9 2.0 2.0

Int‐50% ‐ 2008 0 60 0 6.8 5.1 7.0 0 0 0 1.9 3.8 3.4 3.9 5.9 5.6 2.0 75 4.7 2.2 2.4 2.3

Int‐50% ‐ 2009 0 50 0 7.0 5.9 6.9 0 0 0 2.1 3.9 2.8 3.8 5.7 4.5 1.8 64 5.7 2.3 3.0 2.3

Int‐50% ‐ 2010 0 34 0 6.9 6.1 7.0 0 0 0 1.5 3.6 3.2 2.5 5.7 4.7 1.7 88 4.3 2.4 2.6 2.4

Int‐Off ‐ 2005 0 60 0 6.6 5.4 7.0 0 0 0 1.9 1.6 1.6 3.4 4.3 3.0 0.9 21 6.8 2.5 4.5 3.0

Int‐Off ‐ 2006 0 46 0 6.7 5.6 6.8 0 0 0 1.5 1.3 1.5 2.6 1.5 1.8 0.9 92 3.7 2.5 2.6 2.6

Int‐Off ‐ 2007 0 60 0 6.6 4.9 6.9 0 0 0 1.1 1.5 1.8 2.7 2.1 2.6 0.9 74 6.2 2.7 2.7 2.7

Int‐Off ‐ 2008 0 60 0 6.8 5.0 6.9 0 0 0 1.9 1.3 1.7 3.6 2.0 2.5 1.1 72 5.2 2.4 2.7 2.5

Int‐Off ‐ 2009 0 55 0 7.0 5.8 6.9 0 0 0 2.0 1.2 1.5 3.4 2.9 2.3 0.9 57 6.0 2.4 3.4 2.5

Int‐Off ‐ 2010 0 34 0 6.8 6.1 7.0 0 0 0 1.4 1.0 1.4 2.2 1.7 2.0 0.7 88 4.3 2.5 3.0 2.6

Additional Metrics

Page C‐4



ilim., # days/yr <6

mg/L)

Shadow M


g/L)

Grand Lake

‐ DO (ep

ilim., # days/yr <6

mg/L)


July)

Shadow M

tn ‐ M


July)

Grand Lake

‐ M


July)

Granby Res. Lake

Chl a

(# days >8 µg/L)

Shadow M

tn. C

hl a

(# days >8 µ

g/L)

Grand Lake

Chl a

(# days >8 µg/L)

Granby Res. Chl a


Results <2


fishery

concern

Shad

ow M

tn. C

hl a


Results <2


fishery

concern

Grand Lake Chl a

(July‐Sep

t, Avg., µg/L);


fishery

concern

Granby Res. Chl a

(max, µg/L)

Shadow M

tn. C

hl a

(max, µ

g/L)

Grand Lake

Chl a

(max, µg/L)

Grand Lake

Chl a

(Avg. M

ar.‐Nov., µ

g/L)

Grand Lake

‐Secchi D

epth (# days <4, m

)

Grand Lake

‐Secchi D

epth (max, m

)

Grand Lake

‐Secchi D

epth (min, m

)

Grand Lake

‐Secchi D


through

Labor Day, m

)

Grand Lake

‐Secchi D


through

Sep

t, m

)

Additional Metrics

Inf ‐50% ‐ 2005 0 59 0 6.5 5.4 7.1 0 12 0 1.4 5.8 3.0 2.5 8.7 5.0 2.0 35 6.3 2.3 4.0 2.6

Inf ‐50% ‐ 2006 0 46 0 6.7 5.6 6.9 0 23 0 1.1 5.3 4.8 3.1 10.1 7.9 2.7 92 3.6 2.0 2.1 2.1

Inf ‐50% ‐ 2007 0 59 0 6.6 4.9 7.0 0 61 50 0.9 11.4 8.2 1.9 18.4 14.9 3.8 77 5.8 1.6 1.6 1.6

Inf ‐50% ‐ 2008 0 60 0 6.8 5.1 7.0 0 26 4 1.3 5.9 4.1 2.8 9.9 8.2 2.6 74 5.2 1.9 2.3 2.1

Inf ‐50% ‐ 2009 0 48 0 6.9 5.9 6.9 0 19 0 1.5 5.9 3.6 3.1 9.6 6.9 2.4 65 5.7 2.0 2.9 2.2

Inf ‐50% ‐ 2010 0 33 0 6.9 6.1 7.0 0 27 0 1.1 5.9 4.3 2.2 9.7 7.2 2.4 88 4.3 2.2 2.3 2.3

Inf‐Pristine ‐ 2005 0 59 0 6.5 5.5 7.4 0 10 0 0.9 5.1 2.2 1.7 8.4 3.8 1.7 26 7.9 2.9 4.7 3.2

Inf‐Pristine ‐ 2006 0 46 0 6.7 5.6 7.3 0 2 0 0.8 5.1 4.5 2.0 8.1 7.0 2.5 78 6.5 2.6 2.7 2.7

Inf‐Pristine ‐ 2007 0 59 0 6.6 5.0 7.2 0 60 50 0.4 10.9 8.2 1.0 17.4 14.6 3.8 76 7.6 1.9 1.9 1.9

Inf‐Pristine ‐ 2008 0 59 0 6.8 5.1 7.1 0 13 0 0.7 5.5 3.7 1.4 8.6 7.0 2.4 59 6.7 2.6 3.0 2.8

Inf‐Pristine ‐ 2009 0 45 0 7.0 5.9 7.4 0 7 0 1.2 5.6 3.3 2.2 8.6 5.4 2.2 45 7.4 2.6 3.3 2.8

Inf‐Pristine ‐ 2010 0 31 0 6.9 6.1 7.3 0 16 0 0.9 5.6 4.3 1.6 8.6 6.6 2.3 63 7.0 2.7 2.7 2.7

SW‐50% ‐ 2005 0 59 0 6.6 5.4 7.1 0 0 0 1.8 5.9 2.9 3.0 7.3 4.5 2.0 35 6.2 2.3 4.1 2.7

SW‐50% ‐ 2006 0 46 0 6.7 5.6 6.9 0 24 13 1.3 5.5 5.2 2.7 9.8 8.2 2.9 92 3.5 2.0 2.0 2.0

SW‐50% ‐ 2007 0 59 0 6.6 4.9 7.0 0 62 51 1.1 11.4 8.5 2.0 17.2 13.9 4.0 77 5.6 1.5 1.6 1.6

SW‐50% ‐ 2008 0 60 0 6.8 5.1 7.0 0 26 9 1.8 6.1 4.7 3.6 10.2 8.7 2.8 78 4.6 1.9 2.2 2.1

SW‐50% ‐ 2009 0 47 0 7.0 5.9 6.9 0 21 0 1.8 6.1 4.0 3.2 9.7 7.2 2.6 67 5.4 2.0 2.8 2.1

SW‐50% ‐ 2010 0 33 0 6.9 6.1 7.0 0 27 0 1.3 6.0 4.8 2.3 9.3 7.5 2.6 88 4.2 2.2 2.3 2.2

SW‐Off ‐ 2005 0 59 0 6.5 5.5 7.1 0 0 0 1.6 5.3 2.4 2.8 6.6 3.6 1.7 31 6.3 2.4 4.3 2.7

SW‐Off ‐ 2006 0 46 0 6.7 5.6 6.9 0 16 0 1.0 5.2 4.8 1.8 8.9 7.9 2.7 92 3.5 2.0 2.0 2.1

SW‐Off ‐ 2007 0 59 0 6.6 4.9 7.0 0 63 52 0.9 11.1 8.2 1.9 15.3 12.4 3.8 77 5.7 1.6 1.7 1.7

SW‐Off ‐ 2008 0 60 0 6.8 5.1 7.0 0 26 8 1.6 6.0 4.6 3.0 10.0 8.6 2.7 78 4.6 1.9 2.2 2.1

SW‐Off ‐ 2009 0 47 0 7.0 5.9 6.9 0 11 0 1.4 5.9 4.0 2.4 8.9 6.7 2.5 66 5.4 2.0 2.8 2.1

SW‐Off ‐ 2010 0 33 0 6.8 6.1 7.0 0 12 0 1.0 5.6 4.7 1.7 8.7 6.8 2.5 88 4.3 2.2 2.3 2.3

Page C‐5



ilim., # days/yr <6

mg/L)

Shadow M


g/L)

Grand Lake

‐ DO (ep

ilim., # days/yr <6

mg/L)


July)

Shadow M

tn ‐ M


July)

Grand Lake

‐ M


July)

Granby Res. Lake

Chl a

(# days >8 µg/L)

Shadow M

tn. C

hl a

(# days >8 µ

g/L)

Grand Lake

Chl a

(# days >8 µg/L)

Granby Res. Chl a


Results <2


fishery

concern

Shad

ow M

tn. C

hl a


Results <2


fishery

concern

Grand Lake Chl a

(July‐Sep

t, Avg., µg/L);


fishery

concern

Granby Res. Chl a

(max, µg/L)

Shadow M

tn. C

hl a

(max, µ

g/L)

Grand Lake

Chl a

(max, µg/L)

Grand Lake

Chl a

(Avg. M

ar.‐Nov., µ

g/L)

Grand Lake

‐Secchi D

epth (# days <4, m

)

Grand Lake

‐Secchi D

epth (max, m

)

Grand Lake

‐Secchi D

epth (min, m

)

Grand Lake

‐Secchi D


through

Labor Day, m

)

Grand Lake

‐Secchi D


through

Sep

t, m

)

Additional Metrics

Inf/Int‐50% ‐ 2005 0 60 0 6.5 5.4 7.1 0 0 0 1.3 3.5 2.1 2.2 5.3 3.8 1.3 27 6.6 2.5 4.4 2.8

Inf/Int‐50% ‐ 2006 0 46 0 6.7 5.6 6.9 0 0 0 1.0 3.0 2.9 2.5 5.4 4.6 1.7 92 3.7 2.3 2.3 2.4

Inf/Int‐50% ‐ 2007 0 60 0 6.6 4.9 7.0 0 41 36 0.8 6.7 5.6 1.5 10.8 9.7 2.6 76 6.0 2.0 2.1 2.1

Inf/Int‐50% ‐ 2008 0 60 0 6.8 5.0 7.0 0 0 0 1.2 3.4 2.7 2.6 5.5 4.8 1.7 72 5.4 2.2 2.5 2.3

Inf/Int‐50% ‐ 2009 0 53 0 6.9 5.9 6.9 0 0 0 1.4 3.5 2.4 2.8 5.2 4.2 1.5 63 6.0 2.3 3.2 2.4

Inf/Int‐50% ‐ 2010 0 34 0 6.8 6.1 7.0 0 0 0 1.0 3.3 2.7 1.8 5.4 4.2 1.5 88 4.3 2.4 2.7 2.5

Int/SW‐50% ‐ 2005 0 60 0 6.5 5.4 7.1 0 0 0 1.7 3.8 2.2 3.1 4.8 3.5 1.4 27 6.5 2.4 4.4 2.8

Int/SW‐50% ‐ 2006 0 46 0 6.7 5.6 6.9 0 0 0 1.2 3.2 3.3 2.1 5.4 5.0 1.8 92 3.6 2.2 2.3 2.3

Int/SW‐50% ‐ 2007 0 60 0 6.6 4.9 7.0 0 39 26 1.0 6.7 5.7 2.1 10.5 9.5 2.6 76 5.8 2.0 2.0 2.0

Int/SW‐50% ‐ 2008 0 60 0 6.8 5.1 7.0 0 0 0 1.7 3.6 3.3 3.3 5.7 5.5 2.0 75 4.7 2.2 2.4 2.3

Int/SW‐50% ‐ 2009 0 52 0 7.0 5.9 6.9 0 0 0 1.7 3.7 2.8 2.9 5.4 4.4 1.7 64 5.7 2.3 3.1 2.3

Int/SW‐50% ‐ 2010 0 34 0 6.8 6.1 7.0 0 0 0 1.2 3.5 3.1 1.9 5.5 4.5 1.6 88 4.3 2.4 2.6 2.4

Inf/SW‐50% ‐ 2005 0 59 0 6.5 5.4 7.1 0 0 0 1.2 5.3 2.6 1.9 7.1 4.0 1.8 31 6.3 2.3 4.2 2.7

Inf/SW‐50% ‐ 2006 0 46 0 6.7 5.6 6.9 0 21 0 0.9 5.1 4.7 2.2 9.5 7.8 2.6 92 3.6 2.0 2.1 2.1

Inf/SW‐50% ‐ 2007 0 59 0 6.6 4.9 7.0 0 61 50 0.7 11.2 8.3 1.5 17.0 13.9 3.8 77 5.8 1.6 1.6 1.6

Inf/SW‐50% ‐ 2008 0 60 0 6.8 5.1 7.0 0 26 1 1.1 5.7 4.0 2.3 9.7 8.0 2.5 74 5.2 2.0 2.3 2.1

Inf/SW‐50% ‐ 2009 0 49 0 6.9 5.9 6.9 0 12 0 1.2 5.7 3.6 2.2 9.0 6.3 2.3 65 5.7 2.1 2.9 2.2

Inf/SW‐50% ‐ 2010 0 33 0 6.8 6.1 7.0 0 25 0 0.8 5.6 4.3 1.7 8.8 6.9 2.3 88 4.3 2.2 2.3 2.3

Inf/Int/SW 50% ‐ 2005 0 60 0 6.5 5.4 7.1 0 0 0 1.1 3.2 1.8 1.9 4.2 2.8 1.2 24 6.6 2.5 4.6 2.9

Inf/Int/SW 50% ‐ 2006 0 46 0 6.7 5.6 6.9 0 0 0 0.7 2.9 2.8 1.6 5.2 4.4 1.6 92 3.7 2.3 2.4 2.4

Inf/Int/SW 50% ‐ 2007 0 60 0 6.6 4.9 7.0 0 37 23 0.6 6.4 5.4 1.2 10.1 9.1 2.4 76 6.0 2.0 2.1 2.1

Inf/Int/SW 50% ‐ 2008 0 60 0 6.8 5.0 7.0 0 0 0 1.0 3.3 2.6 2.0 5.3 4.7 1.6 72 5.4 2.3 2.5 2.4

Inf/Int/SW 50% ‐ 2009 0 54 0 6.9 5.8 6.9 0 0 0 1.1 3.3 2.3 1.9 5.1 3.8 1.5 63 6.0 2.3 3.2 2.4

Inf/Int/SW 50% ‐ 2010 0 34 0 6.8 6.1 7.0 0 0 0 0.8 3.2 2.6 1.2 5.1 4.1 1.4 88 4.3 2.5 2.7 2.5

Page C‐6


Run

Composite 6yr

System WQI

1 Base Case 70

2 Ultra‐Clean 81

3 Int‐50% 73

4 Int‐Off 75

5 Inf ‐50% 71

6 Inf‐Pristine 78

7 SW‐50% 70

8 SW‐Off 71

9 Inf/Int‐50% 73

10 Int/SW‐50% 73

11 Inf/SW‐50% 71

12 Inf/Int/SW 50% 74

13

14

15

Annual System WQI

Run 2005 2006 2007 2008 2009 2010

1 Base Case 74 69 62 68 76 71

7 Ultra‐Clean 82 84 70 77 86 86

13 Int‐50% 76 72 65 69 79 74

19 Int‐Off 77 75 69 71 81 78

25 Inf ‐50% 75 70 62 69 77 72

31 Inf‐Pristine 80 79 68 76 82 81

37 SW‐50% 75 70 62 68 76 72

43 SW‐Off 75 71 63 68 77 72

49 Inf/Int‐50% 77 73 65 70 80 75

55 Int/SW‐50% 76 73 65 69 79 75

61 Inf/SW‐50% 76 71 62 69 78 73

67 Inf/Int/SW 50% 77 74 65 70 80 75

70

81

7375

71

78

70 7173 73

7174

6567697173757779818385

System

WQI

Composite 6yr System WQI

0

10

20

30

40

50

60

70

80

90

100

System

WQI

System WQI by Year

2005

2006

2007

2008

2009

2010

Page C‐7)


6‐Year Composite WQIs

Grand Lake Avg Shadow Mtn Avg Granby Res Avg

1 Base Case 75.0 44.0 90.8

2 Ultra‐Clean 92.2 56.7 93.5

3 Int‐50% 79.0 47.4 91.4

4 Int‐Off 83.2 50.4 91.7

5 Inf ‐50% 76.4 44.6 91.9

6 Inf‐Pristine 85.3 55.5 92.6

7 SW‐50% 75.5 44.3 91.4

8 SW‐Off 76.2 44.8 91.9

9 Inf/Int‐50% 80.3 47.4 92.3

10 Int/SW‐50% 79.4 47.5 91.8

11 Inf/SW‐50% 76.8 44.8 92.2

12 Inf/Int/SW 50% 80.7 47.4 92.6

13

14

15

16

17

75

92

7983

76

85

75 7680 79

7781

40

50

60

70

80

90

100

System

WQI

Grand Lake

44

57

4750

45

55

44 4547 48

4547

40

50

60

70

80

90

100

System

WQI

Shadow Mountain Reservoir

9193 91 92 92 93 91 92 92 92 92 93

40

50

60

70

80

90

100

System

WQI

Granby Reservoir

Page C‐8)


Grand Lake WQIRun 2005 2006 2007 2008 2009 2010

1 Base Case 89 67 65 74 82 73

7 Ultra‐Clean 95 92 89 91 94 92

13 Int‐50% 91 72 72 77 85 77

19 Int‐Off 93 77 81 80 87 81

25 Inf ‐50% 90 69 66 76 83 74

31 Inf‐Pristine 94 82 75 86 90 85

37 SW‐50% 90 68 66 74 82 73

43 SW‐Off 91 69 67 74 82 73

49 Inf/Int‐50% 92 74 74 79 86 78

55 Int/SW‐50% 92 73 73 77 85 77

61 Inf/SW‐50% 91 70 67 76 83 74

67 Inf/Int/SW 50% 92 75 74 79 86 78

20

30

40

50

60

70

80

90

100

Base Case Ultra‐Clean Int‐50% Int‐Off Inf ‐50% Inf‐Pristine SW‐50% SW‐Off Inf/Int‐50% Int/SW‐50% Inf/SW‐50% Inf/Int/SW 50%

System

WQI

Grand Lake WQI by Year

2005

2006

2007

2008

2009

2010

Page C‐9)


Shadow Mountain Reservoir WQIRun 2005 2006 2007 2008 2009 2010

1 Base Case 45 49 30 38 54 49

7 Ultra‐Clean 58 67 29 45 70 71

13 Int‐50% 47 53 32 40 58 54

19 Int‐Off 51 56 33 41 63 59

25 Inf ‐50% 46 50 29 38 55 50

31 Inf‐Pristine 55 62 37 50 64 64

37 SW‐50% 45 50 29 38 54 50

43 SW‐Off 46 51 30 38 55 51

49 Inf/Int‐50% 48 54 30 39 59 55

55 Int/SW‐50% 48 53 32 39 59 54

61 Inf/SW‐50% 46 50 29 38 55 51

67 Inf/Int/SW 50% 48 54 30 39 59 55

20

30

40

50

60

70

80

90

100


System

WQI

Shadow Mountain Reservoir WQI by Year

2005

2006

2007

2008

2009

2010

Page C‐10)


Granby Reservoir WQIRun 2005 2006 2007 2008 2009 2010

1 Base Case 88 91 91 91 92 92

7 Ultra‐Clean 91 93 93 94 95 94

13 Int‐50% 89 91 91 92 93 92

19 Int‐Off 89 91 92 92 94 93

25 Inf ‐50% 90 91 91 92 94 92

31 Inf‐Pristine 92 92 92 93 94 93

37 SW‐50% 89 91 91 92 93 92

43 SW‐Off 89 92 92 92 94 93

49 Inf/Int‐50% 90 92 92 93 94 93

55 Int/SW‐50% 89 92 92 92 94 93

61 Inf/SW‐50% 90 92 92 93 94 93

67 Inf/Int/SW 50% 90 92 92 93 94 93

20

30

40

50

60

70

80

90

100


System

WQI

Granby Reservoir WQI by Year

2005

2006

2007

2008

2009

2010

Page C‐11)


Grand Lake Chl a ‐ Subindex ResultsRun 2005 2006 2007 2008 2009 2010

1 Base Case 94 90 86 91 92 92

7 Ultra‐Clean 99 99 100 99 99 100

13 Int‐50% 96 95 91 94 95 95

19 Int‐Off 98 98 98 98 98 98

25 Inf ‐50% 95 92 87 92 93 93

31 Inf‐Pristine 96 93 87 93 94 93

37 SW‐50% 95 91 86 91 92 92

43 SW‐Off 96 92 87 92 93 93

49 Inf/Int‐50% 97 96 92 96 96 96

55 Int/SW‐50% 97 95 92 95 95 96

61 Inf/SW‐50% 95 92 87 93 93 93

67 nf/Int/SW 50% 97 96 93 96 96 97

Grand Lake Chl a ‐ Metric Values (ug/L)Run 2005 2006 2007 2008 2009 2010

1 Base Case 2.2 3.0 4.0 2.9 2.6 2.6

7 Ultra‐Clean 0.3 0.2 0.2 0.2 0.3 0.2

13 Int‐50% 1.5 2.0 2.8 2.0 1.8 1.7

19 Int‐Off 0.9 0.9 0.9 1.1 0.9 0.7

25 Inf ‐50% 2.0 2.7 3.8 2.6 2.4 2.4

31 Inf‐Pristine 1.7 2.5 3.8 2.4 2.2 2.3

37 SW‐50% 2.0 2.9 4.0 2.8 2.6 2.6

43 SW‐Off 1.7 2.7 3.8 2.7 2.5 2.5

49 Inf/Int‐50% 1.3 1.7 2.6 1.7 1.5 1.5

55 Int/SW‐50% 1.4 1.8 2.6 2.0 1.7 1.6

61 Inf/SW‐50% 1.8 2.6 3.8 2.5 2.3 2.3

67 nf/Int/SW 50% 1.2 1.6 2.4 1.6 1.5 1.4

75

80

85

90

95

100

Chla

Subindex Value

Grand Lake Chl a Subindex Results

2005

2006

2007

2008

2009

2010

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Chl a

Metric Value (ug/L)

Grand Lake Chl aMetric Values

2005

2006

2007

2008

2009

2010

Page C‐12)


Grand Lake Secchi ‐ Subindex ResultsRun 2005 2006 2007 2008 2009 2010

1 Base Case 87 45 46 57 70 54

7 Ultra‐Clean 100 90 93 94 97 93

13 Int‐50% 90 52 56 61 75 59

19 Int‐Off 94 58 70 68 80 67

25 Inf ‐50% 88 48 48 60 72 56

31 Inf‐Pristine 99 70 63 82 87 77

37 SW‐50% 89 46 47 57 70 54

43 SW‐Off 91 48 48 58 71 54

49 Inf/Int‐50% 92 54 59 65 77 62

55 Int/SW‐50% 92 52 57 62 75 60

61 Inf/SW‐50% 90 49 48 61 73 56

67 nf/Int/SW 50% 94 55 59 65 77 62

Grand Lake Secchi ‐ Metric Values (m)Run 2005 2006 2007 2008 2009 2010

1 Base Case 4.5 2.4 2.4 2.8 3.4 2.7

7 Ultra‐Clean 7.0 4.7 5.0 5.2 5.5 5.0

13 Int‐50% 4.8 2.6 2.8 3.0 3.7 2.9

19 Int‐Off 5.1 2.9 3.5 3.3 4.0 3.3

25 Inf ‐50% 4.6 2.5 2.5 3.0 3.6 2.8

31 Inf‐Pristine 5.8 3.4 3.1 4.1 4.5 3.8

37 SW‐50% 4.6 2.4 2.4 2.9 3.5 2.7

43 SW‐Off 4.8 2.5 2.5 2.9 3.5 2.7

49 Inf/Int‐50% 4.9 2.7 2.9 3.2 3.8 3.0

55 Int/SW‐50% 4.9 2.7 2.9 3.0 3.7 3.0

61 Inf/SW‐50% 4.8 2.5 2.5 3.0 3.6 2.8

67 nf/Int/SW 50% 5.1 2.8 2.9 3.2 3.8 3.1

73

79

85

91

97

0

10

20

30

40

50

60

70

80

90

100

Secchi Subindex Result

Grand Lake Secchi Subindex Results

2005

2006

2007

2008

2009

2010

0

1

2

3

4

5

6

7

8Secchi M

etric Value (m)

Grand Lake Secchi Metric Values

2005

2006

2007

2008

2009

2010

Page C‐13)


Grand Lake DO ‐ Subindex ResultsRun 2005 2006 2007 2008 2009 2010

1 Base Case 88 87 79 82 87 85

7 Ultra‐Clean 87 87 78 81 86 85

13 Int‐50% 87 87 78 82 86 85

19 Int‐Off 87 86 78 81 86 84

25 Inf ‐50% 88 87 78 82 87 85

31 Inf‐Pristine 88 88 80 83 88 87

37 SW‐50% 87 87 79 82 87 85

43 SW‐Off 87 87 79 82 87 86

49 Inf/Int‐50% 87 86 78 81 86 84

55 Int/SW‐50% 87 87 78 82 86 85

61 Inf/SW‐50% 87 87 78 82 87 85

67 nf/Int/SW 50% 87 86 78 81 86 84

Grand Lake DO ‐ Metric Values (mg/L)Run 2005 2006 2007 2008 2009 2010

1 Base Case 6.9 6.8 6.4 6.6 6.8 6.7

7 Ultra‐Clean 6.9 6.8 6.4 6.5 6.8 6.7

13 Int‐50% 6.8 6.8 6.4 6.6 6.8 6.7

19 Int‐Off 6.8 6.8 6.4 6.5 6.8 6.7

25 Inf ‐50% 6.9 6.8 6.4 6.6 6.8 6.7

31 Inf‐Pristine 6.9 6.9 6.5 6.6 6.9 6.8

37 SW‐50% 6.9 6.8 6.4 6.6 6.8 6.7

43 SW‐Off 6.8 6.8 6.4 6.6 6.8 6.8

49 Inf/Int‐50% 6.8 6.8 6.4 6.5 6.8 6.7

55 Int/SW‐50% 6.8 6.8 6.4 6.6 6.8 6.7

61 Inf/SW‐50% 6.8 6.8 6.4 6.6 6.8 6.7

67 nf/Int/SW 50% 6.8 6.8 6.4 6.5 6.8 6.7

72

74

76

78

80

82

84

86

88

90

DO Subindex Result

Grand Lake DO Subindex Results

2005

2006

2007

2008

2009

2010

0

1

2

3

4

5

6

7DO M

etric Value (mg/L)

Grand Lake DO Metric Values

2005

2006

2007

2008

2009

2010

Page C‐14)


Shadow Mountain Res. Chl a ‐ Subindex ResultsRun 2005 2006 2007 2008 2009 2010

1 Base Case 83 86 74 85 85 86

7 Ultra‐Clean 99 99 99 99 99 99

13 Int‐50% 90 92 86 91 91 92

19 Int‐Off 95 96 96 96 97 97

25 Inf ‐50% 87 89 76 87 87 88

31 Inf‐Pristine 89 90 78 88 88 89

37 SW‐50% 85 87 75 85 85 87

43 SW‐Off 86 88 76 86 86 87

49 Inf/Int‐50% 93 94 88 93 93 94

55 Int/SW‐50% 90 93 87 92 92 93

61 Inf/SW‐50% 88 89 77 87 88 89

67Inf/Int/SW 50% 93 94 89 94 94 94

Shadow Mountain Res. Chl a ‐ Metric Values (ug/L)Run 2005 2006 2007 2008 2009 2010

1 Base Case 4.4 3.9 6.0 4.2 4.2 4.0

7 Ultra‐Clean 0.3 0.3 0.3 0.4 0.6 0.4

13 Int‐50% 3.2 2.6 3.9 2.8 2.8 2.6

19 Int‐Off 1.9 1.5 1.6 1.5 1.3 1.2

25 Inf ‐50% 3.8 3.4 5.6 3.8 3.8 3.6

31 Inf‐Pristine 3.3 3.1 5.2 3.5 3.5 3.3

37 SW‐50% 4.2 3.7 5.8 4.1 4.1 3.8

43 SW‐Off 3.9 3.5 5.6 3.9 3.9 3.6

49 Inf/Int‐50% 2.5 2.1 3.4 2.3 2.4 2.2

55 Int/SW‐50% 3.1 2.5 3.7 2.7 2.7 2.4

61 Inf/SW‐50% 3.6 3.3 5.4 3.7 3.6 3.4

67Inf/Int/SW 50% 2.3 2.0 3.3 2.2 2.2 2.0

60

65

70

75

80

85

90

95

100

Chla

Subindex Value

SMR Chl a Subindex Results

2005

2006

2007

2008

2009

2010

0

1

2

3

4

5

6

7Chl a

Metric Value (ug/L)

SMR Chl aMetric Values

2005

2006

2007

2008

2009

2010

Page C‐15)


Shadow Mountain Res. Secchi ‐ Subindex ResultsRun 2005 2006 2007 2008 2009 2010

1 Base Case 31 34 25 27 37 31

7 Ultra‐Clean 70 78 79 73 71 73

13 Int‐50% 36 40 38 33 43 37

19 Int‐Off 44 46 54 39 51 44

25 Inf ‐50% 33 36 26 28 38 32

31 Inf‐Pristine 52 57 39 54 52 54

37 SW‐50% 32 35 26 28 37 31

43 SW‐Off 34 36 27 28 38 32

49 Inf/Int‐50% 38 42 39 34 45 38

55 Int/SW‐50% 38 41 38 33 44 37

61 Inf/SW‐50% 34 37 27 29 39 32

67Inf/Int/SW 50% 39 42 40 34 45 38

Shadow Mountain Res. Secchi ‐ Metric Values (m)Run 2005 2006 2007 2008 2009 2010

1 Base Case 1.9 2.0 1.7 1.8 2.1 1.9

7 Ultra‐Clean 3.5 3.9 3.9 3.6 3.5 3.6

13 Int‐50% 2.1 2.2 2.1 1.9 2.3 2.1

19 Int‐Off 2.3 2.4 2.7 2.1 2.6 2.3

25 Inf ‐50% 1.9 2.0 1.7 1.8 2.1 1.9

31 Inf‐Pristine 2.6 2.9 2.2 2.7 2.6 2.7

37 SW‐50% 1.9 2.0 1.7 1.8 2.1 1.9

43 SW‐Off 2.0 2.1 1.7 1.8 2.1 1.9

49 Inf/Int‐50% 2.1 2.2 2.2 2.0 2.4 2.1

55 Int/SW‐50% 2.1 2.2 2.1 1.9 2.3 2.1

61 Inf/SW‐50% 2.0 2.1 1.7 1.8 2.1 1.9

67Inf/Int/SW 50% 2.2 2.3 2.2 2.0 2.4 2.1

0

10

20

30

40

50

60

70

80

90


SMR Secchi Subindex Results

2005

2006

2007

2008

2009

2010

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Secchi M

etric Value (m)

SMR Secchi Metric Values

2005

2006

2007

2008

2009

2010

Page C‐16)


Shadow Mountain Res. DO ‐ Subindex ResultsRun 2005 2006 2007 2008 2009 2010

1 Base Case 43 49 21 33 60 58

7 Ultra‐Clean 36 45 12 23 54 55

13 Int‐50% 41 47 18 30 58 57

19 Int‐Off 39 47 16 27 56 56

25 Inf ‐50% 43 48 19 31 59 58

31 Inf‐Pristine 42 50 23 33 61 60

37 SW‐50% 42 49 20 32 59 59

43 SW‐Off 41 49 20 31 59 60

49 Inf/Int‐50% 39 47 16 28 57 56

55 Int/SW‐50% 40 47 18 29 57 57

61 Inf/SW‐50% 41 48 18 30 58 58

67Inf/Int/SW 50% 39 46 15 27 56 56

Shadow Mountain Res. DO ‐ Metric Values (mg/L)Run 2005 2006 2007 2008 2009 2010

1 Base Case 5.3 5.4 4.7 5.0 5.7 5.7

7 Ultra‐Clean 5.1 5.3 4.5 4.8 5.6 5.6

13 Int‐50% 5.2 5.4 4.7 4.9 5.7 5.7

19 Int‐Off 5.2 5.4 4.6 4.9 5.6 5.6

25 Inf ‐50% 5.3 5.4 4.7 5.0 5.7 5.7

31 Inf‐Pristine 5.2 5.5 4.8 5.0 5.8 5.8

37 SW‐50% 5.2 5.4 4.7 5.0 5.7 5.7

43 SW‐Off 5.2 5.4 4.7 5.0 5.7 5.7

49 Inf/Int‐50% 5.2 5.4 4.6 4.9 5.7 5.6

55 Int/SW‐50% 5.2 5.4 4.7 4.9 5.7 5.7

61 Inf/SW‐50% 5.2 5.4 4.7 4.9 5.7 5.7

67Inf/Int/SW 50% 5.2 5.4 4.6 4.9 5.6 5.6

0

10

20

30

40

50

60

70

DO Subindex Result

SMR DO Subindex Results

2005

2006

2007

2008

2009

2010

0

1

2

3

4

5

6

7

DO M

etric Value (mg/L)

SMR DO Metric Values

2005

2006

2007

2008

2009

2010

Page C‐17)


Granby Res. Chl a ‐ Subindex ResultsRun 2005 2006 2007 2008 2009 2010

1 Base Case 92 92 93 91 92 93

7 Ultra‐Clean 99 100 100 99 99 100

13 Int‐50% 93 93 95 93 93 94

19 Int‐Off 93 94 96 93 94 96

25 Inf ‐50% 94 94 95 94 94 95

31 Inf‐Pristine 96 95 97 96 95 95

37 SW‐50% 93 93 94 92 93 94

43 SW‐Off 94 95 95 94 94 95

49 Inf/Int‐50% 95 95 96 95 95 96

55 Int/SW‐50% 94 95 96 93 94 96

61 Inf/SW‐50% 95 95 96 95 95 96

67Inf/Int/SW 50% 96 97 97 96 96 97

Granby Res. Chl a ‐ Metric Values (ug/L)Run 2005 2006 2007 2008 2009 2010

1 Base Case 2.6 2.8 2.4 2.8 2.8 2.5

7 Ultra‐Clean 0.3 0.2 0.2 0.3 0.3 0.2

13 Int‐50% 2.4 2.4 2.0 2.5 2.4 2.0

19 Int‐Off 2.3 2.1 1.7 2.4 2.0 1.6

25 Inf ‐50% 2.1 2.1 1.9 2.1 2.2 2.0

31 Inf‐Pristine 1.6 1.9 1.4 1.6 1.9 1.7

37 SW‐50% 2.4 2.3 2.1 2.5 2.4 2.1

43 SW‐Off 2.0 1.9 1.8 2.2 2.1 1.8

49 Inf/Int‐50% 1.7 1.8 1.5 1.7 1.8 1.5

55 Int/SW‐50% 2.2 2.0 1.7 2.3 2.1 1.7

61 Inf/SW‐50% 1.8 1.8 1.7 1.8 1.8 1.7

67Inf/Int/SW 50% 1.4 1.4 1.2 1.5 1.4 1.2

73

79

85

91

97

86

88

90

92

94

96

98

100

Chla

Subindex Value

Granby Chl a Subindex Results

2005

2006

2007

2008

2009

2010

0.0

0.5

1.0

1.5

2.0

2.5

3.0Chl a

Metric Value (ug/L)

Granby Chl aMetric Values

2005

2006

2007

2008

2009

2010

Page C‐18)


Granby Res. Secchi ‐ Subindex ResultsRun 2005 2006 2007 2008 2009 2010

1 Base Case 90 100 100 98 98 99

7 Ultra‐Clean 100 100 100 100 100 100

13 Int‐50% 93 100 100 98 98 100

19 Int‐Off 93 100 100 98 99 100

25 Inf ‐50% 96 100 100 100 100 100

31 Inf‐Pristine 100 100 100 100 100 100

37 SW‐50% 94 100 100 99 99 100

43 SW‐Off 95 100 100 99 100 100

49 Inf/Int‐50% 97 100 100 100 100 100

55 Int/SW‐50% 94 100 100 99 99 100

61 Inf/SW‐50% 97 100 100 100 100 100

67Inf/Int/SW 50% 98 100 100 100 100 100

Granby Res. Secchi ‐ Metric Values (m)Run 2005 2006 2007 2008 2009 2010

1 Base Case 4.7 6.2 6.6 5.7 5.7 6.0

7 Ultra‐Clean 8.5 9.4 9.5 8.8 8.7 9.2

13 Int‐50% 5.0 6.3 6.7 5.7 5.8 6.1

19 Int‐Off 5.0 6.2 6.6 5.7 5.8 6.1

25 Inf ‐50% 5.4 6.8 7.1 6.2 6.2 6.5

31 Inf‐Pristine 7.3 8.1 8.6 8.0 7.4 8.0

37 SW‐50% 5.1 6.5 6.7 5.8 5.9 6.2

43 SW‐Off 5.3 6.7 6.9 6.0 6.2 6.5

49 Inf/Int‐50% 5.5 6.9 7.2 6.3 6.3 6.5

55 Int/SW‐50% 5.1 6.5 6.8 5.9 6.0 6.3

61 Inf/SW‐50% 5.6 7.0 7.2 6.4 6.5 6.7

67Inf/Int/SW 50% 5.6 7.1 7.4 6.5 6.6 6.8

84

86

88

90

92

94

96

98

100


Granby Secchi Subindex Results

2005

2006

2007

2008

2009

2010

2.5

3.5

4.5

5.5

6.5

7.5

8.5

9.5

10.5

Secchi M

etric Value (m)

Granby Secchi Metric Values

2005

2006

2007

2008

2009

2010

Page C‐19)


Granby Res. DO ‐ Subindex ResultsRun 2005 2006 2007 2008 2009 2010

1 Base Case 82 82 82 85 88 84

7 Ultra‐Clean 78 82 81 85 88 84

13 Int‐50% 82 82 82 85 88 84

19 Int‐Off 82 82 82 85 88 84

25 Inf ‐50% 81 82 82 85 88 84

31 Inf‐Pristine 81 82 82 85 88 85

37 SW‐50% 82 82 82 85 88 84

43 SW‐Off 80 82 82 85 88 84

49 Inf/Int‐50% 81 82 81 85 88 84

55 Int/SW‐50% 81 82 82 85 88 84

61 Inf/SW‐50% 80 82 82 85 88 84

67Inf/Int/SW 50% 79 82 81 85 88 84

Granby Res. DO ‐ Metric Values (mg/L)Run 2005 2006 2007 2008 2009 2010

1 Base Case 6.6 6.6 6.6 6.7 6.9 6.7

7 Ultra‐Clean 6.4 6.6 6.5 6.7 6.9 6.7

13 Int‐50% 6.6 6.6 6.6 6.7 6.9 6.7

19 Int‐Off 6.6 6.6 6.6 6.7 6.9 6.7

25 Inf ‐50% 6.5 6.6 6.6 6.7 6.9 6.7

31 Inf‐Pristine 6.5 6.6 6.6 6.7 6.9 6.7

37 SW‐50% 6.6 6.6 6.6 6.7 6.9 6.7

43 SW‐Off 6.5 6.6 6.6 6.7 6.9 6.7

49 Inf/Int‐50% 6.5 6.6 6.6 6.7 6.9 6.7

55 Int/SW‐50% 6.5 6.6 6.6 6.7 6.9 6.7

61 Inf/SW‐50% 6.5 6.6 6.6 6.7 6.9 6.7

67Inf/Int/SW 50% 6.5 6.6 6.6 6.7 6.9 6.7

55

60

65

70

75

80

85

90

95

100

DO Subindex Result

Granby DO Subindex Results

2005

2006

2007

2008

2009

2010

0

1

2

3

4

5

6

7

DO M

etric Value (mg/L)

Granby DO Metric Values

2005

2006

2007

2008

2009

2010

Page C‐20)

Three Lakes Model Nutrient Sensitivity Analysis – Appendix D January 27, 2014


Appendix D ‐ Detailed Results –Reductions in Loadings by Tributary


Simulation and Year Granby Res. ‐Min DO (mg/L)

Shad

ow M

tn.‐Min DO (mg/L)

Grand Lake‐M

in DO (mg/L)

Granby Res. Chl a (Avg., µg/L)

Shad

ow M

tn. C

hl a (Avg., µg/L)

Grand Lake Chl a (Avg., µg/L)


epth (Avg., m

)*

Shad

ow M

tn. ‐Secchi D

epth (Avg., m

)*

Grand Lake ‐Secchi D

epth (Avg., m

)*

Granby Res. ‐Min DO

Shad

ow M

tn.‐Min DO

Grand Lake‐M

in DO

Granby Res. Chl a

Shad

ow M

tn. C

hl a

Grand Lake Chl a


epth

Shad

ow M

tn. ‐Secchi D

epth


epth

un Nu Granby Res.

Shad

ow M

tn.

Grand Lake

System Score

Base Case ‐ 2005 6.6 5.3 6.9 2.6 4.4 2.2 4.7 1.9 4.5 81.8 43.0 87.5 92.2 83.4 93.8 89.7 31.1 87.0 Ru # 87.7 44.5 89.3 73.8 90.8

Base Case ‐ 2006 6.6 5.4 6.8 2.8 3.9 3.0 6.2 2.0 2.4 82.1 48.8 87.0 91.5 86.1 90.4 99.7 34.2 45.2 # 90.6 48.9 67.2 68.9 44.0

Base Case ‐ 2007 6.6 4.7 6.4 2.4 6.0 4.0 6.6 1.7 2.4 81.6 20.9 78.8 93.1 73.6 85.8 100.0 24.9 46.1 # 90.9 29.5 65.2 61.9 75.0

Base Case ‐ 2008 6.7 5.0 6.6 2.8 4.2 2.9 5.7 1.8 2.8 85.1 32.8 82.4 91.4 84.7 90.8 98.0 27.4 56.8 # 91.2 38.1 73.6 67.6

Base Case ‐ 2009 6.9 5.7 6.8 2.8 4.2 2.6 5.7 2.1 3.4 88.2 59.8 86.7 91.6 84.6 92.0 98.0 36.8 69.9 # 92.4 53.8 81.7 76.0 Run0

Base Case ‐ 2010 6.7 5.7 6.7 2.5 4.0 2.6 6.0 1.9 2.7 84.4 58.2 85.1 92.7 85.9 92.1 99.4 31.0 53.6 # 91.8 49.1 72.7 71.2 70

Stillwtr Pristine ‐ 2005 6.6 5.3 6.9 2.5 4.3 2.1 5.2 1.9 4.6 81.8 43.0 87.6 92.6 83.9 94.3 95.0 31.7 87.9 Rur Pr 89.4 44.9 89.8 74.7 91.3

Stillwtr Pristine ‐ 2006 6.6 5.4 6.8 2.6 3.9 3.0 6.5 2.0 2.4 82.1 49.1 87.3 92.1 86.4 90.6 100.0 36.1 46.9 lwtr Pr 90.8 50.3 68.5 69.8 44.6

Stillwtr Pristine ‐ 2007 6.6 4.7 6.4 2.2 6.0 4.0 6.9 1.7 2.4 81.6 21.0 78.9 93.9 73.8 85.7 100.0 25.8 46.8 lwtr Pr 91.2 30.0 65.6 62.3 75.5

Stillwtr Pristine ‐ 2008 6.7 5.0 6.6 2.7 4.1 2.9 6.0 1.8 2.9 85.1 32.9 82.4 91.8 84.9 90.9 99.1 28.1 57.4 lwtr Pr 91.6 38.6 74.0 68.1

Stillwtr Pristine ‐ 2009 6.9 5.7 6.8 2.7 4.2 2.6 5.9 2.1 3.5 88.1 59.9 86.8 91.9 84.7 92.1 98.9 37.2 70.2 lwtr Pr 92.8 54.1 81.9 76.3 Run1

Stillwtr Pristine ‐ 2010 6.7 5.7 6.7 2.3 3.9 2.6 6.3 1.9 2.7 84.3 58.3 85.1 93.5 86.0 92.1 100.0 31.6 54.0 lwtr Pr 92.1 49.6 72.9 71.6 70

Arap Pristine ‐ 2005 6.6 5.3 6.9 2.5 4.4 2.1 5.2 1.9 4.5 82.8 43.1 87.8 92.7 83.5 94.0 95.1 31.2 87.1 RuPri 89.9 44.6 89.5 74.7 91.5

Arap Pristine ‐ 2006 6.6 5.4 6.8 2.5 3.8 3.0 6.6 2.0 2.4 82.3 48.7 87.0 92.5 86.5 90.5 100.0 36.1 47.0 ap Pri 91.0 50.2 68.4 69.9 44.3

Arap Pristine ‐ 2007 6.6 4.7 6.4 2.3 6.0 4.0 6.9 1.7 2.4 81.7 20.7 78.8 93.6 73.6 85.7 100.0 25.1 46.3 ap Pri 91.1 29.5 65.3 62.0 75.3

Arap Pristine ‐ 2008 6.7 5.0 6.6 2.5 4.2 2.9 6.0 1.8 2.8 85.2 32.8 82.4 92.4 84.7 90.8 99.3 27.8 57.2 ap Pri 91.9 38.3 73.8 68.0

Arap Pristine ‐ 2009 6.9 5.7 6.8 2.6 4.2 2.6 5.9 2.1 3.4 88.3 59.8 86.7 92.1 84.6 92.1 99.1 37.0 70.1 ap Pri 92.9 54.0 81.8 76.3 RunB

Arap Pristine ‐ 2010 6.7 5.7 6.7 2.4 4.0 2.6 6.2 1.9 2.7 84.5 58.2 85.1 93.0 85.9 92.1 99.8 31.1 53.7 ap Pri 92.0 49.2 72.8 71.3 70

WC Pristine ‐ 2005 6.6 5.3 6.9 2.5 4.3 2.1 5.4 1.9 4.5 82.0 42.9 87.6 92.6 83.9 94.2 96.5 32.1 87.7 RuPris 89.9 45.2 89.7 75.0 91.5

WC Pristine ‐ 2006 6.6 5.4 6.8 2.6 3.8 3.0 6.5 2.1 2.5 82.2 49.1 87.3 92.1 86.5 90.6 100.0 37.5 48.2WC Pris 90.8 51.2 69.4 70.5 45.3

WC Pristine ‐ 2007 6.6 4.7 6.4 2.2 6.0 4.0 6.8 1.7 2.4 81.6 21.0 78.9 93.6 73.8 85.7 100.0 25.8 46.8WC Pris 91.1 30.0 65.6 62.3 75.8

WC Pristine ‐ 2008 6.7 5.0 6.6 2.7 4.1 2.9 6.1 1.8 2.9 85.2 33.0 82.4 91.9 84.9 90.9 99.5 29.3 58.1WC Pris 91.8 39.3 74.4 68.5

WC Pristine ‐ 2009 6.9 5.8 6.8 2.6 4.2 2.6 6.0 2.1 3.5 88.2 60.0 87.0 92.1 84.8 92.2 99.3 38.1 70.7WC Pris 93.0 54.8 82.2 76.7 RunC

WC Pristine ‐ 2010 6.7 5.7 6.7 2.2 3.9 2.6 6.5 1.9 2.8 84.4 58.8 85.2 93.6 86.1 92.1 100.0 33.1 55.0WC Pris 92.2 51.0 73.6 72.3 71



Page D‐1



Shad

ow M

tn.‐Min DO (mg/L)

Grand Lake‐M

in DO (mg/L)


Shad

ow M

tn. C

hl a (Avg., µg/L)



epth (Avg., m

)*

Shad

ow M

tn. ‐Secchi D

epth (Avg., m

)*


epth (Avg., m

)*


Shad

ow M

tn.‐Min DO

Grand Lake‐M

in DO

Granby Res. Chl a

Shad

ow M

tn. C

hl a

Grand Lake Chl a


epth

Shad

ow M

tn. ‐Secchi D

epth


epth

un Nu Granby Res.

Shad

ow M

tn.

Grand Lake

System Score



WG Pristine ‐ 2005 6.6 5.3 6.9 2.5 4.3 2.1 5.3 1.9 4.5 82.1 42.6 87.6 92.7 83.9 94.2 95.3 32.2 87.6 RuPris 89.7 45.1 89.7 74.8 91.5

WG Pristine ‐ 2006 6.6 5.4 6.8 2.5 3.8 2.9 6.6 2.1 2.5 82.2 49.3 87.3 92.5 86.7 90.8 100.0 37.8 48.5WG Pris 91.0 51.5 69.7 70.7 45.4

WG Pristine ‐ 2007 6.6 4.7 6.5 2.0 5.9 4.0 7.1 1.8 2.5 81.6 21.2 79.3 94.4 74.3 85.6 100.0 28.4 48.9WG Pris 91.3 31.3 67.1 63.3 76.1

WG Pristine ‐ 2008 6.7 5.0 6.6 2.5 4.1 2.8 6.1 1.9 2.9 85.1 32.6 82.4 92.4 85.3 91.2 99.5 30.6 59.0WG Pris 92.0 40.0 74.9 68.9

WG Pristine ‐ 2009 6.9 5.7 6.8 2.6 4.1 2.6 6.0 2.1 3.5 88.2 59.9 86.9 92.3 85.0 92.3 99.2 38.5 70.9WG Pris 93.0 55.1 82.3 76.8 RunD

WG Pristine ‐ 2010 6.7 5.7 6.7 2.4 3.9 2.6 6.1 1.9 2.7 84.4 58.3 85.1 93.1 86.0 92.2 99.6 31.6 54.1WG Pris 91.9 49.7 73.0 71.6 71

NFork Pristine ‐ 2005 6.6 5.3 6.9 2.6 4.0 2.1 5.2 2.2 4.6 82.8 43.4 87.8 92.1 85.8 94.2 94.4 40.1 88.5 Ru Pr 89.5 50.3 90.1 76.6 91.3

NFork Pristine ‐ 2006 6.6 5.4 6.8 2.7 3.6 2.9 6.4 2.2 2.6 82.2 49.0 87.1 91.9 87.6 90.8 100.0 40.5 51.5 ork Pr 90.8 53.1 71.6 71.8 48.7

NFork Pristine ‐ 2007 6.6 4.7 6.4 2.4 5.8 4.0 6.7 1.7 2.5 81.7 21.6 79.0 93.2 74.6 85.8 100.0 27.2 47.5 ork Pr 91.0 31.1 66.1 62.7 77.5

NFork Pristine ‐ 2008 6.7 5.0 6.6 2.8 4.0 2.9 5.9 2.2 3.1 85.1 33.4 82.6 91.6 85.9 91.1 98.8 39.2 63.9 ork Pr 91.5 44.7 77.4 71.2

NFork Pristine ‐ 2009 6.9 5.8 6.8 2.7 4.0 2.6 5.9 2.2 3.5 88.2 60.0 87.1 91.8 85.7 92.2 98.8 40.7 71.8 ork Pr 92.8 56.7 82.8 77.4 RunE

NFork Pristine ‐ 2010 6.7 5.7 6.7 2.4 3.8 2.6 6.3 2.2 3.0 84.4 58.7 85.3 93.1 86.7 92.1 99.9 40.5 60.9 ork Pr 92.0 56.4 76.9 75.1 72

1/2 P ‐ 5 Key Tribs ‐ 2005 6.5 5.2 6.8 2.4 4.3 2.0 5.1 1.9 4.5 80.8 41.5 87.4 93.0 84.3 94.4 93.4 32.4 87.8 Ru5 Ke 88.6 44.9 89.7 74.4 91.3

1/2 P ‐ 5 Key Tribs ‐ 2006 6.6 5.4 6.8 2.4 3.8 2.8 6.4 2.0 2.4 82.1 49.5 86.9 93.1 86.5 91.2 100.0 34.9 46.1 P ‐ 5 Ke 91.1 49.6 68.0 69.6 45.1

1/2 P ‐ 5 Key Tribs ‐ 2007 6.5 4.8 6.4 1.9 6.0 4.0 6.9 1.7 2.5 81.4 22.8 79.1 94.9 73.8 85.7 100.0 27.2 47.9 P ‐ 5 Ke 91.4 31.8 66.4 63.2 75.5

1/2 P ‐ 5 Key Tribs ‐ 2008 6.7 5.0 6.6 2.7 4.3 2.9 5.8 1.8 2.8 84.9 33.9 83.0 91.9 83.9 90.8 98.5 27.7 57.0 P ‐ 5 Ke 91.4 38.7 73.9 68.0

1/2 P ‐ 5 Key Tribs ‐ 2009 6.9 5.8 6.8 2.5 4.1 2.6 5.8 2.1 3.5 87.9 61.2 87.1 92.8 85.1 92.4 98.4 37.7 70.3 P ‐ 5 Ke 92.8 54.9 82.1 76.6 RunF

1/2 P ‐ 5 Key Tribs ‐ 2010 6.7 5.7 6.7 2.1 3.8 2.5 6.1 1.9 2.7 84.2 59.1 85.4 94.1 86.7 92.5 99.6 32.1 54.0 P ‐ 5 Ke 92.2 50.3 73.1 71.9 71

1/2 N ‐ 5 Key Tribs ‐ 2005 6.6 5.2 6.9 2.4 4.3 2.2 5.3 1.9 4.4 82.9 41.9 87.9 93.0 84.0 93.8 95.2 30.8 85.9 Ru5 Ke 90.0 43.9 89.1 74.3 91.7

1/2 N ‐ 5 Key Tribs ‐ 2006 6.6 5.4 6.8 2.3 3.7 2.9 6.6 2.0 2.4 82.1 48.1 86.9 93.2 87.3 90.9 100.0 35.5 46.4 N ‐ 5 Ke 91.2 49.7 68.1 69.7 43.9

1/2 N ‐ 5 Key Tribs ‐ 2007 6.6 4.7 6.4 2.1 5.9 3.9 6.9 1.7 2.4 81.6 19.6 78.6 94.0 74.4 86.0 100.0 24.7 45.8 N ‐ 5 Ke 91.2 28.6 64.9 61.6 75.2

1/2 N ‐ 5 Key Tribs ‐ 2008 6.7 5.0 6.6 2.2 4.0 2.8 6.1 1.8 2.9 84.9 31.3 82.1 93.6 85.9 91.3 99.6 27.9 57.4 N ‐ 5 Ke 92.3 37.8 74.0 68.0

1/2 N ‐ 5 Key Tribs ‐ 2009 6.9 5.7 6.8 2.3 4.1 2.5 6.0 2.1 3.5 88.0 58.9 86.5 93.3 85.3 92.5 99.4 37.1 70.2 N ‐ 5 Ke 93.3 53.9 81.9 76.4 RunG

1/2 N ‐ 5 Key Tribs ‐ 2010 6.7 5.7 6.7 2.2 3.8 2.6 6.3 1.9 2.7 84.3 57.8 84.9 93.6 86.6 92.3 99.9 31.4 53.9 N ‐ 5 Ke 92.2 49.4 72.9 71.5 70

Page D‐2


Simulation and Year Granby Res. ‐ DO (epilim

., # days/yr <6 m

g/L)

Shad

ow M


g/L)

Grand Lake ‐ DO (epilim

., # days/yr <6 m

g/L)

Granby Res. ‐ M


July)

Shad

ow M

tn ‐ M


July)

Grand Lake ‐ M


July)

Granby Res. Lake Chl a

(# days >8

µg/L)

Shad

ow M

tn. C

hl a

(# days >8

µg/L)

Grand Lake Chl a

(# days >8

µg/L)

Granby Res. Chl a

(Jul‐Sept, Avg., µg/L); R

esults <2

ug/L highlighted for potential fishery concern

Shad

ow M

tn. C

hl a


esults <2


Grand Lake Chl a

(July‐Sept, Avg., µg/L); R

esults <2


Granby Res. Chl a

(max, µg/L)

Shad

ow M

tn. C

hl a

(max, µ

g/L)

Grand Lake Chl a

(max, µg/L)


epth (# days <4, m

)


epth (max, m

)


epth (min, m

)


epth (15th %ile, July through

Labor Day, m

)



Sept, m

)

Base Case ‐ 2005 0 59 0 6.6 5.5 7.0 0 12 0 1.9 6.2 3.0 3.2 8.4 5.0 38 6.1 2.2 3.9 2.6

Base Case ‐ 2006 0 46 0 6.7 5.6 6.9 0 25 17 1.5 5.6 5.3 3.5 10.3 8.5 92 3.4 1.9 2.0 2.0

Base Case ‐ 2007 0 59 0 6.6 5.0 7.0 0 62 50 1.2 11.6 8.4 2.4 18.9 15.1 78 5.6 1.5 1.6 1.6

Base Case ‐ 2008 0 60 0 6.8 5.1 7.0 0 28 12 2.0 6.3 4.8 4.1 10.3 8.8 79 4.6 1.9 2.2 2.1

Base Case ‐ 2009 0 47 0 7.0 5.9 6.9 0 26 0 2.1 6.3 4.1 4.1 9.9 7.7 68 5.3 2.0 2.7 2.1

Base Case ‐ 2010 0 33 0 6.9 6.1 7.0 0 28 0 1.5 6.2 4.8 2.9 10.3 7.6 88 4.2 2.2 2.3 2.2

Stillwtr Pristine ‐ 2005 0 59 0 6.6 5.5 7.1 0 13 0 1.9 6.2 3.1 3.2 8.7 5.3 38 6.3 2.3 3.9 2.6






Arap Pristine ‐ 2005 0 59 0 6.6 5.5 7.1 0 17 0 1.7 6.3 3.3 3.4 9.0 5.6 39 6.2 2.3 3.8 2.6

Arap Pristine ‐ 2006 0 46 0 6.7 5.6 6.9 0 25 16 1.4 5.6 5.4 4.0 10.4 8.5 92 3.5 2.0 2.0 2.0

Arap Pristine ‐ 2007 0 59 0 6.6 5.0 7.0 0 62 51 1.0 11.6 8.4 2.4 18.3 14.8 78 5.6 1.5 1.6 1.6

Arap Pristine ‐ 2008 0 60 0 6.8 5.1 7.0 0 28 12 1.7 6.3 4.8 4.0 10.3 8.8 78 4.6 1.9 2.2 2.1

Arap Pristine ‐ 2009 0 47 0 7.0 5.9 6.9 0 28 0 2.0 6.4 4.1 4.0 9.9 7.8 67 5.4 2.0 2.8 2.2

Arap Pristine ‐ 2010 0 33 0 6.9 6.1 7.0 0 28 0 1.4 6.2 4.8 2.9 10.3 7.6 88 4.2 2.2 2.3 2.2

WC Pristine ‐ 2005 0 59 0 6.6 5.5 7.1 0 13 0 1.9 6.2 3.2 3.1 8.7 5.4 38 6.2 2.3 3.9 2.7

WC Pristine ‐ 2006 0 45 0 6.7 5.6 6.9 0 25 16 1.4 5.6 5.3 3.2 9.8 8.4 92 3.6 2.0 2.1 2.1

WC Pristine ‐ 2007 0 59 0 6.6 5.0 7.0 0 62 51 1.1 11.5 8.5 2.1 18.9 15.2 77 5.6 1.5 1.6 1.6

WC Pristine ‐ 2008 0 59 0 6.8 5.1 7.0 0 28 12 1.8 6.2 4.8 3.7 10.2 8.8 78 4.6 2.0 2.3 2.1

WC Pristine ‐ 2009 0 45 0 7.0 5.9 6.9 0 21 0 2.0 6.3 4.1 3.7 9.8 7.1 67 5.4 2.1 2.8 2.2

WC Pristine ‐ 2010 0 33 0 6.9 6.1 7.0 0 28 0 1.4 6.1 4.9 2.4 9.8 7.7 88 4.3 2.2 2.3 2.3

Additional Metrics

Page D‐3


Simulation and Year Granby Res. ‐ DO (epilim

., # days/yr <6 m

g/L)

Shad

ow M


g/L)

Grand Lake ‐ DO (epilim

., # days/yr <6 m

g/L)

Granby Res. ‐ M


July)

Shad

ow M

tn ‐ M


July)

Grand Lake ‐ M


July)


(# days >8

µg/L)

Shad

ow M

tn. C

hl a

(# days >8

µg/L)

Grand Lake Chl a

(# days >8

µg/L)

Granby Res. Chl a


esults <2


Shad

ow M

tn. C

hl a


esults <2


Grand Lake Chl a

(July‐Sept, Avg., µg/L); R

esults <2


Granby Res. Chl a

(max, µg/L)

Shad

ow M

tn. C

hl a

(max, µ

g/L)

Grand Lake Chl a

(max, µg/L)


epth (# days <4, m

)


epth (max, m

)


epth (min, m

)



Labor Day, m

)



Sept, m

)

Additional Metrics

WG Pristine ‐ 2005 0 59 0 6.6 5.5 7.1 0 13 0 1.8 6.1 3.2 3.0 8.7 5.5 38 6.2 2.3 3.9 2.7

WG Pristine ‐ 2006 0 46 0 6.7 5.6 6.9 0 24 14 1.3 5.5 5.2 3.0 9.5 8.2 92 3.6 2.1 2.1 2.1

WG Pristine ‐ 2007 0 59 0 6.6 5.0 7.0 0 63 51 0.9 11.3 8.6 1.9 18.0 14.9 77 5.6 1.6 1.7 1.7

WG Pristine ‐ 2008 0 60 0 6.8 5.1 7.0 0 26 10 1.7 6.1 4.7 3.6 10.2 8.7 78 4.6 2.0 2.3 2.2

WG Pristine ‐ 2009 0 46 0 7.0 5.9 6.9 0 24 0 2.0 6.2 4.1 3.8 9.8 7.2 67 5.4 2.1 2.8 2.3

WG Pristine ‐ 2010 0 33 0 6.9 6.1 7.0 0 28 0 1.5 6.1 4.8 2.7 10.0 7.6 88 4.3 2.2 2.3 2.3

NFork Pristine ‐ 2005 0 59 0 6.6 5.5 7.1 0 10 0 2.0 6.0 3.2 3.2 8.4 5.4 36 6.3 2.4 4.0 2.7

NFork Pristine ‐ 2006 0 46 0 6.7 5.6 6.9 0 25 15 1.5 5.6 5.3 3.6 10.3 8.5 88 4.2 2.1 2.1 2.1

NFork Pristine ‐ 2007 0 59 0 6.6 5.0 7.0 0 62 50 1.2 11.5 8.5 2.3 19.1 15.2 77 5.6 1.6 1.6 1.6

NFork Pristine ‐ 2008 0 59 0 6.8 5.1 7.0 0 27 12 1.9 6.2 4.8 4.0 10.3 8.8 74 4.8 2.0 2.4 2.2

NFork Pristine ‐ 2009 0 45 0 7.0 5.9 6.9 0 22 0 2.1 6.2 4.1 3.9 9.8 7.2 66 5.4 2.1 2.9 2.3

NFork Pristine ‐ 2010 0 32 0 6.9 6.1 7.0 0 28 0 1.5 6.1 4.9 2.7 9.7 7.7 82 4.6 2.3 2.4 2.4

1/2 P ‐ 5 Key Tribs ‐ 2005 0 59 0 6.5 5.5 7.1 0 4 0 1.7 5.6 3.0 3.5 8.2 5.3 38 6.2 2.3 3.9 2.7

1/2 P ‐ 5 Key Tribs ‐ 2006 0 46 0 6.7 5.6 6.9 0 2 0 1.2 5.4 5.1 2.3 8.1 7.3 92 3.4 2.0 2.1 2.1

1/2 P ‐ 5 Key Tribs ‐ 2007 0 59 0 6.6 5.0 7.0 0 62 51 0.8 11.1 8.5 1.8 17.5 14.7 77 5.6 1.6 1.6 1.6

1/2 P ‐ 5 Key Tribs ‐ 2008 0 59 0 6.8 5.1 7.0 0 24 0 1.5 6.1 4.7 2.7 9.3 8.0 79 4.6 1.9 2.2 2.0

1/2 P ‐ 5 Key Tribs ‐ 2009 0 44 0 7.0 6.0 6.9 0 11 0 1.8 5.9 4.0 2.6 8.7 6.0 68 5.3 2.1 2.7 2.1

1/2 P ‐ 5 Key Tribs ‐ 2010 0 27 0 6.8 6.1 7.0 0 6 0 1.3 5.7 4.7 2.3 8.4 6.6 88 4.2 2.2 2.3 2.2

1/2 N ‐ 5 Key Tribs ‐ 2005 0 59 0 6.6 5.4 7.1 0 19 0 1.7 6.4 3.5 3.3 9.4 6.1 43 6.1 2.3 3.7 2.5

1/2 N ‐ 5 Key Tribs ‐ 2006 0 46 0 6.7 5.6 6.9 0 24 13 1.4 5.5 5.2 4.0 10.2 8.4 92 3.5 2.0 2.0 2.0

1/2 N ‐ 5 Key Tribs ‐ 2007 0 59 0 6.6 4.9 7.0 0 61 50 1.0 11.5 8.3 2.4 18.6 15.0 78 5.6 1.5 1.6 1.6

1/2 N ‐ 5 Key Tribs ‐ 2008 0 60 0 6.8 5.1 7.0 0 26 9 1.4 6.1 4.7 3.2 10.2 8.6 78 4.6 1.9 2.2 2.1

1/2 N ‐ 5 Key Tribs ‐ 2009 0 49 0 7.0 5.9 6.9 0 27 0 1.7 6.2 4.0 3.4 10.2 7.5 67 5.4 2.1 2.7 2.2

1/2 N ‐ 5 Key Tribs ‐ 2010 0 34 0 6.9 6.1 7.0 0 27 0 1.3 6.0 4.8 2.8 10.2 7.5 88 4.2 2.2 2.3 2.3

Page D‐4


Run Composite 6yr System WQI

1 Base Case 70

2 Stillwtr Pristine 70

3 Arap Pristine 70

4 WC Pristine 71

5 WG Pristine 71

6 NFork Pristine 72

7 1/2 P ‐ 5 Key Tribs 71

8 1/2 N ‐ 5 Key Tribs 70

9

10

11

12

13

14

15

16

17

Annual System WQI

Run 2005 2006 2007 2008 2009 2010

1 Base Case 74 69 62 68 76 71

7 Stillwtr Pristine 75 70 62 68 76 72

13 Arap Pristine 75 70 62 68 76 71

19 WC Pristine 75 70 62 69 77 72

25 WG Pristine 75 71 63 69 77 72

31 NFork Pristine 77 72 63 71 77 75

37 1/2 P ‐ 5 Key Tribs 74 70 63 68 77 72

43 1/2 N ‐ 5 Key Tribs 74 70 62 68 76 71

69.970.5 70.4

70.9 71.0

72.5

70.670.2

65

66

67

68

69

70

71

72

73

System W

QI


0

10

20

30

40

50

60

70

80

90

Base Case Stillwtr Pristine Arap Pristine WC Pristine WG Pristine NFork Pristine 1/2 P ‐ 5 Key Tribs 1/2 N ‐ 5 Key Tribs

System W

QI

System WQI by Year

2005

2006

2007

2008

2009

2010

Page D‐5)




1 Base Case 75.0 44.0 90.8

2 Stillwtr Pristine 75.5 44.6 91.3

3 Arap Pristine 75.3 44.3 91.5

4 WC Pristine 75.8 45.3 91.5

5 WG Pristine 76.1 45.4 91.5

6 NFork Pristine 77.5 48.7 91.3

7 1/2 P ‐ 5 Key Tribs 75.5 45.1 91.3

8 1/2 N ‐ 5 Key Tribs 75.2 43.9 91.7

75.0 75.5 75.3 75.8 76.177.5

75.5 75.2

55

60

65

70

75

80

Base Case StillwtrPristine

ArapPristine

WCPristine

WGPristine

NForkPristine

1/2 P ‐ 5Key Tribs

1/2 N ‐ 5Key Tribs

System

WQI

Grand Lake

44.044.6 44.3

45.3 45.4

48.7

45.1

43.9

41

42

43

44

45

46

47

48

49

50


ArapPristine

WCPristine

WGPristine

NForkPristine



System

WQI


90.8 91.3 91.5 91.5 91.5 91.3 91.3 91.7

55

60

65

70

75

80

85

90

95


ArapPristine

WCPristine

WGPristine

NForkPristine



System

WQI

Granby Reservoir

Page D‐6)



1 Base Case 89 67 65 74 82 73


13 Arap Pristine 90 68 65 74 82 73

19 WC Pristine 90 69 66 74 82 74

25 WG Pristine 90 70 67 75 82 73

31 NFork Pristine 90 72 66 77 83 77

37 1/2 P ‐ 5 Key Tribs 90 68 66 74 82 73

43 1/2 N ‐ 5 Key Tribs 89 68 65 74 82 73

20

30

40

50

60

70

80

90

100


System

WQI


2005

2006

2007

2008

2009

2010

Page D‐7)



1 Base Case 45 49 30 38 54 49


13 Arap Pristine 45 50 30 38 54 49

19 WC Pristine 45 51 30 39 55 51

25 WG Pristine 45 51 31 40 55 50

31 NFork Pristine 50 53 31 45 57 56

37 1/2 P ‐ 5 Key Tribs 45 50 32 39 55 50

43 1/2 N ‐ 5 Key Tribs 44 50 29 38 54 49

20

30

40

50

60

70

80

90

100


System

WQI


2005

2006

2007

2008

2009

2010

Page D‐8)



1 Base Case 88 91 91 91 92 92


13 Arap Pristine 90 91 91 92 93 92

19 WC Pristine 90 91 91 92 93 92

25 WG Pristine 90 91 91 92 93 92

31 NFork Pristine 89 91 91 91 93 92

37 1/2 P ‐ 5 Key Tribs 89 91 91 91 93 92

43 1/2 N ‐ 5 Key Tribs 90 91 91 92 93 92

20

30

40

50

60

70

80

90

100


System

WQI


2005

2006

2007

2008

2009

2010

Page D‐9)



1 Base Case 94 90 86 91 92 92


13 Arap Pristine 94 91 86 91 92 92

19 WC Pristine 94 91 86 91 92 92

25 WG Pristine 94 91 86 91 92 92

31 NFork Pristine 94 91 86 91 92 92

37 1/2 P ‐ 5 Key Tribs 94 91 86 91 92 93

43 1/2 N ‐ 5 Key Tribs 94 91 86 91 92 92


1 Base Case 2.2 3.0 4.0 2.9 2.6 2.6

7 Stillwtr Pristine 2.1 3.0 4.0 2.9 2.6 2.6

13 Arap Pristine 2.1 3.0 4.0 2.9 2.6 2.6

19 WC Pristine 2.1 3.0 4.0 2.9 2.6 2.6

25 WG Pristine 2.1 2.9 4.0 2.8 2.6 2.6

31 NFork Pristine 2.1 2.9 4.0 2.9 2.6 2.6

37 1/2 P ‐ 5 Key Tribs 2.0 2.8 4.0 2.9 2.6 2.5

43 1/2 N ‐ 5 Key Tribs 2.2 2.9 3.9 2.8 2.5 2.6

80

82

84

86

88

90

92

94

96


ArapPristine

WC PristineWG Pristine NForkPristine



Chla

Subindex Value


2005

2006

2007

2008

2009

2010

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5


ArapPristine




Chl a

Metric Value (ug/L)


2005

2006

2007

2008

2009

2010

Page D‐10)



1 Base Case 87 45 46 57 70 54


13 Arap Pristine 87 47 46 57 70 54

19 WC Pristine 88 48 47 58 71 55

25 WG Pristine 88 49 49 59 71 54

31 NFork Pristine 88 52 48 64 72 61

37 1/2 P ‐ 5 Key Tribs 88 46 48 57 70 54

43 1/2 N ‐ 5 Key Tribs 86 46 46 57 70 54


1 Base Case 4.5 2.4 2.4 2.8 3.4 2.7


13 Arap Pristine 4.5 2.4 2.4 2.8 3.4 2.7

19 WC Pristine 4.5 2.5 2.4 2.9 3.5 2.8

25 WG Pristine 4.5 2.5 2.5 2.9 3.5 2.7

31 NFork Pristine 4.6 2.6 2.5 3.1 3.5 3.0

37 1/2 P ‐ 5 Key Tribs 4.5 2.4 2.5 2.8 3.5 2.7

43 1/2 N ‐ 5 Key Tribs 4.4 2.4 2.4 2.9 3.5 2.7

0

10

20

30

40

50

60

70

80

90

100


ArapPristine

WC Pristine WGPristine

NForkPristine





2005

2006

2007

2008

2009

2010

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0


ArapPristine




Secchi M

etric Value (m

)


2005

2006

2007

2008

2009

2010

Page D‐11)



1 Base Case 88 87 79 82 87 85


13 Arap Pristine 88 87 79 82 87 85

19 WC Pristine 88 87 79 82 87 85

25 WG Pristine 88 87 79 82 87 85

31 NFork Pristine 88 87 79 83 87 85

37 1/2 P ‐ 5 Key Tribs 87 87 79 83 87 85

43 1/2 N ‐ 5 Key Tribs 88 87 79 82 86 85


1 Base Case 6.9 6.8 6.4 6.6 6.8 6.7


13 Arap Pristine 6.9 6.8 6.4 6.6 6.8 6.7

19 WC Pristine 6.9 6.8 6.4 6.6 6.8 6.7

25 WG Pristine 6.9 6.8 6.5 6.6 6.8 6.7

31 NFork Pristine 6.9 6.8 6.4 6.6 6.8 6.7

37 1/2 P ‐ 5 Key Tribs 6.8 6.8 6.4 6.6 6.8 6.7

43 1/2 N ‐ 5 Key Tribs 6.9 6.8 6.4 6.6 6.8 6.7

72

74

76

78

80

82

84

86

88

90


ArapPristine




DO Subindex Result


2005

2006

2007

2008

2009

2010

0

1

2

3

4

5

6

7


ArapPristine

WC Pristine WG Pristine NForkPristine



DO M

etric Value (m

g/L)


2005

2006

2007

2008

2009

2010

Page D‐12)



1 Base Case 83 86 74 85 85 86 1

7 Stillwtr Pristine 84 86 74 85 85 86 7

13 Arap Pristine 84 86 74 85 85 86 13

19 WC Pristine 84 86 74 85 85 86 19

25 WG Pristine 84 87 74 85 85 86 25

31 NFork Pristine 86 88 75 86 86 87 31

37 1/2 P ‐ 5 Key Tribs 84 87 74 84 85 87 37

43 1/2 N ‐ 5 Key Tribs 84 87 74 86 85 87 43

49

55

61

67

73

79

85

91


1 Base Case 4.4 3.9 6.0 4.2 4.2 4.0 1

7 Stillwtr Pristine 4.3 3.9 6.0 4.1 4.2 3.9 7

13 Arap Pristine 4.4 3.8 6.0 4.2 4.2 4.0 13

19 WC Pristine 4.3 3.8 6.0 4.1 4.2 3.9 19

25 WG Pristine 4.3 3.8 5.9 4.1 4.1 3.9 25

31 NFork Pristine 4.0 3.6 5.8 4.0 4.0 3.8 31

37 1/2 P ‐ 5 Key Tribs 4.3 3.8 6.0 4.3 4.1 3.8 37

43 1/2 N ‐ 5 Key Tribs 4.3 3.7 5.9 4.0 4.1 3.8 43

65

70

75

80

85

90


ArapPristine




Chla

Subindex Value


2005

2006

2007

2008

2009

2010

0

1

2

3

4

5

6

7


ArapPristine




Chl a

Metric Value (ug/L)


2005

2006

2007

2008

2009

2010

Page D‐13)



1 Base Case 31 34 25 27 37 31 1


13 Arap Pristine 31 36 25 28 37 31 13

19 WC Pristine 32 37 26 29 38 33 19

25 WG Pristine 32 38 28 31 38 32 25

31 NFork Pristine 40 41 27 39 41 41 31

37 1/2 P ‐ 5 Key Tribs 32 35 27 28 38 32 37

43 1/2 N ‐ 5 Key Tribs 31 36 25 28 37 31 43


1 Base Case 1.9 2.0 1.7 1.8 2.1 1.9 1


13 Arap Pristine 1.9 2.0 1.7 1.8 2.1 1.9 13

19 WC Pristine 1.9 2.1 1.7 1.8 2.1 1.9 19

25 WG Pristine 1.9 2.1 1.8 1.9 2.1 1.9 25

31 NFork Pristine 2.2 2.2 1.7 2.2 2.2 2.2 31

37 1/2 P ‐ 5 Key Tribs 1.9 2.0 1.7 1.8 2.1 1.9 37

43 1/2 N ‐ 5 Key Tribs 1.9 2.0 1.7 1.8 2.1 1.9 43

0

5

10

15

20

25

30

35

40

45


ArapPristine






2005

2006

2007

2008

2009

2010

0.0

0.5

1.0

1.5

2.0

2.5


ArapPristine




Secchi M

etric Value (m

)


2005

2006

2007

2008

2009

2010

Page D‐14)



1 Base Case 43 49 21 33 60 58 1


13 Arap Pristine 43 49 21 33 60 58 13

19 WC Pristine 43 49 21 33 60 59 19

25 WG Pristine 43 49 21 33 60 58 25

31 NFork Pristine 43 49 22 33 60 59 31

37 1/2 P ‐ 5 Key Tribs 42 49 23 34 61 59 37

43 1/2 N ‐ 5 Key Tribs 42 48 20 31 59 58 43


1 Base Case 5.3 5.4 4.7 5.0 5.7 5.7 1


13 Arap Pristine 5.3 5.4 4.7 5.0 5.7 5.7 13

19 WC Pristine 5.3 5.4 4.7 5.0 5.8 5.7 19

25 WG Pristine 5.3 5.4 4.7 5.0 5.7 5.7 25

31 NFork Pristine 5.3 5.4 4.7 5.0 5.8 5.7 31

37 1/2 P ‐ 5 Key Tribs 5.2 5.4 4.8 5.0 5.8 5.7 37

43 1/2 N ‐ 5 Key Tribs 5.2 5.4 4.7 5.0 5.7 5.7 43

0

10

20

30

40

50

60

70


ArapPristine




DO Subindex Result


2005

2006

2007

2008

2009

2010

0

1

2

3

4

5

6

7


ArapPristine




DO M

etric Value (m

g/L)


2005

2006

2007

2008

2009

2010

Page D‐15)



Base Case 92 92 93 91 92 93

Stillwtr Pristine 93 92 94 92 92 93

Arap Pristine 93 93 94 92 92 93

WC Pristine 93 92 94 92 92 94

WG Pristine 93 93 94 92 92 93

NFork Pristine 92 92 93 92 92 93

1/2 P ‐ 5 Key Tribs 93 93 95 92 93 94

1/2 N ‐ 5 Key Tribs 93 93 94 94 93 94


Base Case 2.6 2.8 2.4 2.8 2.8 2.5

Stillwtr Pristine 2.5 2.6 2.2 2.7 2.7 2.3

Arap Pristine 2.5 2.5 2.3 2.5 2.6 2.4

WC Pristine 2.5 2.6 2.2 2.7 2.6 2.2

WG Pristine 2.5 2.5 2.0 2.5 2.6 2.4

NFork Pristine 2.6 2.7 2.4 2.8 2.7 2.4

1/2 P ‐ 5 Key Tribs 2.4 2.4 1.9 2.7 2.5 2.1

1/2 N ‐ 5 Key Tribs 2.4 2.3 2.1 2.2 2.3 2.2

89

90

91

92

93

94

95

96


ArapPristine


NForkPristine



Chla

Subindex Value


2005

2006

2007

2008

2009

2010

0.0

0.5

1.0

1.5

2.0

2.5

3.0


ArapPristine


NForkPristine



Chl a

Metric Value (ug/L)


2005

2006

2007

2008

2009

2010

Page D‐16)



Base Case 90 100 100 98 98 99


Arap Pristine 95 100 100 99 99 100

WC Pristine 97 100 100 100 99 100

WG Pristine 95 100 100 100 99 100

NFork Pristine 94 100 100 99 99 100

1/2 P ‐ 5 Key Tribs 93 100 100 99 98 100

1/2 N ‐ 5 Key Tribs 95 100 100 100 99 100


Base Case 4.7 6.2 6.6 5.7 5.7 6.0


Arap Pristine 5.2 6.6 6.9 6.0 5.9 6.2

WC Pristine 5.4 6.5 6.8 6.1 6.0 6.5

WG Pristine 5.3 6.6 7.1 6.1 6.0 6.1

NFork Pristine 5.2 6.4 6.7 5.9 5.9 6.3

1/2 P ‐ 5 Key Tribs 5.1 6.4 6.9 5.8 5.8 6.1

1/2 N ‐ 5 Key Tribs 5.3 6.6 6.9 6.1 6.0 6.3

84

86

88

90

92

94

96

98

100


ArapPristine


NForkPristine





2005

2006

2007

2008

2009

2010

0

1

2

3

4

5

6

7

8


ArapPristine




Secchi M

etric Value (m

)


2005

2006

2007

2008

2009

2010

Page D‐17)



Base Case 82 82 82 85 88 84


Arap Pristine 83 82 82 85 88 84

WC Pristine 82 82 82 85 88 84

WG Pristine 82 82 82 85 88 84

NFork Pristine 83 82 82 85 88 84

1/2 P ‐ 5 Key Tribs 81 82 81 85 88 84

1/2 N ‐ 5 Key Tribs 83 82 82 85 88 84


Base Case 6.6 6.6 6.6 6.7 6.9 6.7


Arap Pristine 6.6 6.6 6.6 6.7 6.9 6.7

WC Pristine 6.6 6.6 6.6 6.7 6.9 6.7

WG Pristine 6.6 6.6 6.6 6.7 6.9 6.7

NFork Pristine 6.6 6.6 6.6 6.7 6.9 6.7

1/2 P ‐ 5 Key Tribs 6.5 6.6 6.5 6.7 6.9 6.7

1/2 N ‐ 5 Key Tribs 6.6 6.6 6.6 6.7 6.9 6.7

76

78

80

82

84

86

88

90


ArapPristine




DO Subindex Result


2005

2006

2007

2008

2009

2010

0

1

2

3

4

5

6

7


ArapPristine




DO M

etric Value (m

g/L)


2005

2006

2007

2008

2009

2010

Page D‐18)

Three Lakes Model Nutrient Sensitivity Analysis – Appendix E January 27, 2014


Appendix E ‐ Detailed Results –Reductions by Nutrient – System‐Wide and Key Inflow Only



Shad

ow M

tn.‐Min DO (mg/L)

Grand Lake‐Min DO (mg/L)


Shad

ow M

tn. C

hl a (Avg., µg/L)



epth (Avg., m

)

Shad

ow M

tn. ‐Secchi D

epth (Avg., m

)


epth (Avg., m

)


Shad

ow M

tn.‐Min DO

Grand Lake‐Min DO

Granby Res. Chl a

Shad

ow M

tn. C

hl a

Grand Lake Chl a


epth

Shad

ow M

tn. ‐Secchi D

epth


epth

imula Granby Res.

Shad

ow M

tn.

Grand Lake

System Score

Base Case ‐ 2005 6.6 5.3 6.9 2.6 4.4 2.2 4.7 1.9 4.5 81.8 43.0 87.5 92.2 83.4 93.8 89.7 31.1 87.0 Ru # 87.7 44.5 89.3 73.8 90.8

Base Case ‐ 2006 6.6 5.4 6.8 2.8 3.9 3.0 6.2 2.0 2.4 82.1 48.8 87.0 91.5 86.1 90.4 99.7 34.2 45.2 # 90.6 48.9 67.2 68.9 44.0

Base Case ‐ 2007 6.6 4.7 6.4 2.4 6.0 4.0 6.6 1.7 2.4 81.6 20.9 78.8 93.1 73.6 85.8 100.0 24.9 46.1 # 90.9 29.5 65.2 61.9 75.0

Base Case ‐ 2008 6.7 5.0 6.6 2.8 4.2 2.9 5.7 1.8 2.8 85.1 32.8 82.4 91.4 84.7 90.8 98.0 27.4 56.8 # 91.2 38.1 73.6 67.6

Base Case ‐ 2009 6.9 5.7 6.8 2.8 4.2 2.6 5.7 2.1 3.4 88.2 59.8 86.7 91.6 84.6 92.0 98.0 36.8 69.9 # 92.4 53.8 81.7 76.0 Run0

Base Case ‐ 2010 6.7 5.7 6.7 2.5 4.0 2.6 6.0 1.9 2.7 84.4 58.2 85.1 92.7 85.9 92.1 99.4 31.0 53.6 # 91.8 49.1 72.7 71.2 70

25% Reduc All P ‐ 2005 6.5 5.2 6.8 2.5 3.7 1.6 4.8 2.0 4.8 80.5 40.4 87.1 92.8 87.4 96.0 91.3 35.6 91.1 Ruedu 87.8 46.6 91.2 75.2 91.0

25% Reduc All P ‐ 2006 6.6 5.4 6.8 2.1 3.4 2.3 6.3 2.1 2.5 82.1 48.4 86.6 94.0 88.9 93.3 100.0 36.3 48.5% Redu 91.4 50.4 70.0 70.6 46.3

25% Reduc All P ‐ 2007 6.6 4.7 6.4 1.8 4.8 3.3 6.8 2.0 2.7 81.4 20.2 78.5 95.1 81.0 89.3 100.0 33.5 53.6% Redu 91.5 32.7 70.5 64.9 77.7

25% Reduc All P ‐ 2008 6.7 5.0 6.6 2.8 4.1 2.5 5.4 1.8 3.0 85.1 34.1 82.8 91.2 85.2 92.5 96.3 29.1 59.6% Redu 90.6 39.8 75.6 68.7

25% Reduc All P ‐ 2009 6.9 5.7 6.8 2.4 3.6 2.0 5.6 2.2 3.6 87.9 59.6 86.6 93.2 87.7 94.4 97.2 39.4 72.5% Redu 92.6 56.0 83.5 77.4 RunD

25% Reduc All P ‐ 2010 6.7 5.7 6.7 2.0 3.3 1.9 5.9 2.0 2.9 84.2 57.8 84.8 94.5 89.1 95.0 98.9 34.4 57.5% Redu 92.1 52.1 75.6 73.2 72

50% Reduc All P ‐ 2005 6.4 5.1 6.8 1.7 2.5 1.1 5.4 2.2 5.1 78.2 37.7 86.8 95.5 92.7 97.4 96.0 39.6 94.1 Ruedu 89.1 47.9 92.5 76.5 92.0

50% Reduc All P ‐ 2006 6.6 5.4 6.8 1.4 2.3 1.6 6.9 2.2 2.7 81.8 46.4 86.2 96.5 93.5 95.9 100.0 41.0 53.8 Redu 92.0 53.0 73.8 72.9 47.1

50% Reduc All P ‐ 2007 6.5 4.6 6.4 1.2 3.3 2.3 7.2 2.2 3.0 80.4 15.6 77.5 97.0 89.2 93.5 100.0 41.0 60.5 Redu 91.6 30.1 74.8 65.5 80.7

50% Reduc All P ‐ 2008 6.7 4.9 6.5 1.9 3.3 1.7 5.9 2.0 3.2 84.8 27.3 81.4 94.7 89.0 95.7 99.0 33.3 65.1 Redu 92.5 38.5 78.7 69.9

50% Reduc All P ‐ 2009 6.9 5.6 6.8 1.6 2.5 1.4 6.1 2.3 3.8 87.5 56.3 85.8 95.9 92.4 96.5 99.7 43.9 77.0 Redu 94.1 58.4 85.7 79.4 RunE

50% Reduc All P ‐ 2010 6.7 5.6 6.7 1.3 2.3 1.3 6.5 2.1 3.1 83.9 55.9 84.1 96.7 93.5 96.9 100.0 38.3 62.3 Redu 93.0 54.8 78.4 75.4 73

75% Reduc All P ‐ 2005 6.3 5.1 6.8 0.9 1.3 0.7 5.9 2.3 5.5 75.6 35.2 86.5 97.8 96.7 98.5 99.0 43.7 96.7 Ruedu 89.4 48.7 93.6 77.2 92.3

75% Reduc All P ‐ 2006 6.6 5.3 6.8 0.7 1.2 0.9 7.6 2.4 2.9 81.5 44.2 85.6 98.4 97.1 98.0 100.0 46.1 59.5 Redu 92.5 54.9 77.5 75.0 47.0

75% Reduc All P ‐ 2007 6.4 4.5 6.3 0.7 1.7 1.3 7.7 2.5 3.4 78.6 10.8 76.5 98.5 95.4 97.0 100.0 49.8 68.4 Redu 91.3 24.3 79.0 64.8 83.3

75% Reduc All P ‐ 2008 6.7 4.7 6.5 1.0 2.1 0.9 6.6 2.1 3.5 84.4 21.8 80.2 97.6 94.2 97.9 100.0 37.8 70.4 Redu 93.5 36.2 81.3 70.3

75% Reduc All P ‐ 2009 6.8 5.5 6.7 0.8 1.4 0.8 6.9 2.5 4.1 85.6 52.6 85.1 98.2 96.5 98.1 100.0 49.4 81.4 Redu 94.1 60.5 87.7 80.7 RunF

75% Reduc All P ‐ 2010 6.6 5.6 6.6 0.7 1.2 0.7 7.1 2.3 3.3 82.5 53.6 83.4 98.5 97.2 98.5 100.0 42.5 67.2 Redu 93.0 57.2 81.0 77.1 74

25% Reduc All N ‐ 2005 6.6 5.2 6.9 2.2 3.5 1.9 5.3 2.0 4.4 82.6 39.7 87.5 93.7 88.4 94.8 95.2 33.9 86.4 Ruduc 90.1 45.5 89.4 75.0 91.9

25% Reduc All N ‐ 2006 6.6 5.4 6.8 2.1 3.0 2.3 6.6 2.1 2.6 82.1 47.4 86.6 94.2 90.6 93.3 100.0 38.4 49.9 Reduc 91.5 51.6 70.9 71.3 45.6

25% Reduc All N ‐ 2007 6.6 4.7 6.4 1.9 4.9 3.4 6.9 1.8 2.6 81.6 18.0 78.3 94.7 80.6 88.5 100.0 29.5 50.2 Reduc 91.4 29.4 68.2 63.0 77.3

25% Reduc All N ‐ 2008 6.7 4.9 6.6 2.1 3.2 2.3 6.1 1.9 3.0 84.9 29.7 81.8 94.1 89.7 93.5 99.4 30.5 60.9 Reduc 92.4 38.7 76.2 69.1

25% Reduc All N ‐ 2009 6.9 5.7 6.8 2.1 3.3 2.1 6.1 2.2 3.6 88.0 58.0 86.3 94.2 89.3 94.3 99.5 40.6 73.5 Reduc 93.6 56.5 83.8 78.0 RunG

25% Reduc All N ‐ 2010 6.7 5.7 6.7 1.9 3.0 2.0 6.4 2.0 2.9 84.3 57.2 84.7 94.7 90.5 94.4 100.0 34.5 57.6 Reduc 92.5 52.1 75.5 73.4 72

50% Reduc All N ‐ 2005 6.5 5.1 6.8 1.5 2.4 1.4 5.6 2.1 4.7 80.7 38.0 87.1 96.0 93.0 96.4 97.6 38.2 89.7 Rudu 90.8 47.4 90.9 76.4 92.6

50% Reduc All N ‐ 2006 6.6 5.3 6.8 1.4 2.0 1.6 7.1 2.3 2.7 82.0 46.1 86.3 96.4 94.4 95.8 100.0 42.5 54.6 Redu 92.1 53.8 74.4 73.4 47.1

50% Reduc All N ‐ 2007 6.6 4.6 6.4 1.3 3.4 2.5 7.3 2.1 2.8 81.5 15.2 77.8 96.7 88.5 92.5 100.0 37.6 56.8 Redu 92.0 28.9 72.7 64.5 80.1

50% Reduc All N ‐ 2008 6.7 4.9 6.5 1.5 2.2 1.6 6.5 2.0 3.2 84.7 26.6 81.1 96.3 93.7 95.9 100.0 34.0 65.3 Redu 93.2 38.6 78.8 70.2

50% Reduc All N ‐ 2009 6.9 5.6 6.8 1.4 2.3 1.5 6.5 2.4 3.8 87.7 56.1 85.9 96.4 93.5 96.2 100.0 44.9 77.3 Redu 94.4 59.1 85.8 79.7 RunH

50% Reduc All N ‐ 2010 6.7 5.6 6.7 1.3 2.1 1.4 6.8 2.1 3.1 84.1 55.9 84.2 96.7 94.3 96.5 100.0 38.2 62.1 Redu 93.1 54.9 78.2 75.4 73

75% Reduc All N ‐ 2005 6.4 5.1 6.8 0.9 1.3 0.9 6.0 2.3 5.2 78.5 36.3 86.8 98.1 96.8 98.0 99.3 42.8 94.4 Ruduc 90.9 49.0 92.8 77.6 93.0

75% Reduc All N ‐ 2006 6.6 5.3 6.8 0.8 1.1 0.9 7.6 2.4 3.0 81.9 44.8 86.0 98.3 97.4 97.9 100.0 47.0 60.0 Reduc 92.6 55.7 77.9 75.4 48.0

75% Reduc All N ‐ 2007 6.5 4.5 6.4 0.7 1.8 1.4 7.8 2.5 3.2 81.1 12.4 77.2 98.4 95.1 96.5 100.0 47.7 65.9 Reduc 92.3 26.8 78.0 65.7 83.1

75% Reduc All N ‐ 2008 6.7 4.8 6.5 0.8 1.2 0.9 6.9 2.1 3.5 84.6 23.4 80.5 98.2 97.0 97.9 100.0 37.9 70.2 Reduc 93.7 37.7 81.3 70.9

75% Reduc All N ‐ 2009 6.8 5.6 6.7 0.8 1.3 0.9 7.1 2.5 4.1 87.4 53.8 85.4 98.2 96.9 98.0 100.0 49.7 81.3 Reduc 94.9 61.2 87.7 81.3 RunI

75% Reduc All N 2010 6.7 5.6 6.7 0.7 1.1 0.8 7.2 2.3 3.3 84.0 54.5 83.8 98.5 97.4 98.3 100.0 42.5 67.0 % Redu 93.6 57.5 81.0 77.4 75



Page E‐1


Simulation Granby Res. ‐ DO (epilim., # days/yr <6 m

g/L)

Shad

ow M


g/L)

Grand Lake ‐ DO (epilim., # days/yr <6 m

g/L)

Granby Res. ‐ M


July)

Shad

ow M

tn ‐ M


July)

Grand Lake ‐ Min DO (mid‐Oct through

July)


(# days >8

µg/L)

Shad

ow M

tn. C

hl a

(# days >8

µg/L)

Grand Lake Chl a

(# days >8

µg/L)

Granby Res. Chl a

(Jul‐Sept, Avg., µ

g/L); Results

<2 ug/L highlighted for potential fishery concern

Shad

ow M

tn. C

hl a


Results <2

ug/L highlighted for potential fishery

concern

Grand Lake Chl a

(July‐Sept, Avg., µg/L); Results

<2 ug/L highlighted for potential fishery concern

Granby Res. Chl a

(max, µg/L)

Shad

ow M

tn. C

hl a

(max, µ

g/L)

Grand Lake Chl a

(max, µg/L)

Grand Lake Chl a

(Avg. M

ar.‐Nov., µ

g/L)


epth (# days <4, m

)


epth (max, m

)


epth (min, m

)



Labor Day, m

)



Sept, m

)

Base Case ‐ 2005 0 59 0 6.6 5.5 7.0 0 12 0 1.9 6.2 3.0 3.2 8.4 5.0 2.2 38 6.1 2.2 3.9 2.57

Base Case ‐ 2006 0 46 0 6.7 5.6 6.9 0 25 17 1.5 5.6 5.3 3.5 10.3 8.5 3.0 92 3.4 1.9 2.0 1.99

Base Case ‐ 2007 0 59 0 6.6 5.0 7.0 0 62 50 1.2 11.6 8.4 2.4 18.9 15.1 4.0 78 5.6 1.5 1.6 1.57

Base Case ‐ 2008 0 60 0 6.8 5.1 7.0 0 28 12 2.0 6.3 4.8 4.1 10.3 8.8 2.9 79 4.6 1.9 2.2 2.06

Base Case ‐ 2009 0 47 0 7.0 5.9 6.9 0 26 0 2.1 6.3 4.1 4.1 9.9 7.7 2.6 68 5.3 2.0 2.7 2.14

Base Case ‐ 2010 0 33 0 6.9 6.1 7.0 0 28 0 1.5 6.2 4.8 2.9 10.3 7.6 2.6 88 4.2 2.2 2.3 2.24

25% Reduc All P ‐ 2005 0 60 0 6.5 5.5 7.1 0 0 0 1.8 4.4 2.3 4.5 6.2 3.9 1.6 29 6.4 2.4 4.3 2.8

25% Reduc All P ‐ 2006 0 46 0 6.7 5.6 6.8 0 0 0 1.2 4.7 4.1 2.4 6.5 5.7 2.3 92 3.4 2.2 2.2 2.2

25% Reduc All P ‐ 2007 0 60 0 6.6 4.9 7.0 0 58 45 0.9 8.7 7.0 2.2 13.7 12.1 3.3 77 5.8 1.8 1.8 1.8

25% Reduc All P ‐ 2008 0 59 0 6.8 5.1 7.0 0 0 0 1.7 5.2 3.9 3.5 6.7 5.9 2.5 77 5.0 2.1 2.3 2.162789

25% Reduc All P ‐ 2009 0 47 0 7.0 5.9 6.9 0 0 0 1.8 4.8 3.2 3.3 6.1 4.8 2.0 66 5.5 2.2 2.9 2.242229

25% Reduc All P ‐ 2010 0 31 0 6.8 6.1 7.0 0 0 0 1.4 4.4 3.5 3.5 5.6 4.7 1.9 88 4.3 2.4 2.6 2.383975

50% Reduc All P ‐ 2005 0 60 0 6.4 5.5 7.1 0 0 0 1.3 2.9 1.6 3.2 4.1 2.7 1.1 23 6.7 2.5 4.6 2.9

50% Reduc All P ‐ 2006 0 46 0 6.7 5.5 6.9 0 0 0 0.8 3.2 2.9 1.7 4.4 3.9 1.6 92 3.6 2.4 2.4 2.4

50% Reduc All P ‐ 2007 0 60 0 6.5 4.9 7.0 0 20 5 0.6 5.9 4.9 1.6 9.2 8.3 2.3 76 6.0 2.1 2.1 2.2

50% Reduc All P ‐ 2008 0 60 0 6.8 5.0 7.0 0 0 0 1.2 3.3 2.5 3.1 4.0 3.6 1.7 73 5.6 2.3 2.5 2.374471

50% Reduc All P ‐ 2009 0 53 0 6.9 5.8 6.9 0 0 0 1.3 3.3 2.2 2.6 5.2 3.2 1.4 64 5.9 2.4 3.2 2.398433

50% Reduc All P ‐ 2010 0 34 0 6.7 6.1 7.0 0 0 0 0.9 3.0 2.4 2.4 3.8 3.2 1.3 88 4.3 2.5 2.8 2.526961

75% Reduc All P ‐ 2005 0 60 0 6.3 5.4 7.1 0 0 0 0.7 1.5 1.0 1.8 2.0 1.6 0.7 20 7.0 2.7 5.0 3.1

75% Reduc All P ‐ 2006 0 47 0 6.6 5.5 6.8 0 0 0 0.4 1.7 1.6 0.9 2.2 2.1 0.9 92 3.9 2.6 2.6 2.6

75% Reduc All P ‐ 2007 0 60 0 6.4 4.9 6.9 0 0 0 0.3 3.0 2.6 0.9 4.6 4.2 1.3 74 6.5 2.5 2.5 2.6

75% Reduc All P ‐ 2008 0 60 0 6.7 5.0 6.9 0 0 0 0.6 1.6 1.3 1.7 2.0 1.8 0.9 70 6.1 2.5 2.7 2.576716

75% Reduc All P ‐ 2009 0 59 0 6.8 5.8 6.9 0 0 0 0.6 1.7 1.3 1.4 2.8 1.8 0.8 52 6.4 2.5 3.5 2.550969

75% Reduc All P ‐ 2010 0 35 0 6.6 6.1 7.0 0 0 0 0.5 1.6 1.3 1.2 2.0 1.7 0.7 88 4.4 2.6 3.0 2.673333

25% Reduc All N ‐ 2005 0 59 0 6.6 5.4 7.1 0 0 0 1.7 5.1 3.3 3.2 7.9 6.1 1.9 47 6.1 2.4 3.7 2.7

25% Reduc All N ‐ 2006 0 46 0 6.7 5.6 6.9 0 0 0 1.3 4.3 4.1 3.6 7.8 6.5 2.3 92 3.5 2.1 2.2 2.2

25% Reduc All N ‐ 2007 0 59 0 6.6 4.9 7.0 0 61 52 1.0 9.9 7.4 2.3 14.5 11.3 3.4 78 5.6 1.8 1.8 1.8

25% Reduc All N ‐ 2008 0 60 0 6.8 5.1 7.0 0 0 0 1.5 4.8 3.7 3.1 7.8 6.8 2.3 75 5.0 2.1 2.3 2.199111

25% Reduc All N ‐ 2009 0 50 0 7.0 5.9 6.9 0 0 0 1.6 4.9 3.2 3.1 7.7 5.7 2.1 65 5.7 2.2 2.9 2.270585

25% Reduc All N ‐ 2010 0 34 0 6.9 6.1 7.0 0 0 0 1.2 4.7 3.7 2.5 7.8 5.9 2.0 88 4.3 2.4 2.4 2.371255

50% Reduc All N ‐ 2005 0 60 0 6.5 5.4 7.1 0 0 0 1.2 3.5 2.5 2.1 5.4 4.8 1.4 30 6.1 2.5 4.1 2.9

50% Reduc All N ‐ 2006 0 46 0 6.7 5.5 6.9 0 0 0 0.9 2.9 2.8 2.4 5.2 4.4 1.6 92 3.7 2.3 2.4 2.4

50% Reduc All N ‐ 2007 0 60 0 6.6 4.9 7.0 0 57 11 0.7 6.9 5.5 1.5 9.9 8.3 2.5 77 5.6 2.0 2.1 2.1

50% Reduc All N ‐ 2008 0 60 0 6.8 5.0 7.0 0 0 0 1.0 3.3 2.6 2.1 5.3 4.7 1.6 72 5.4 2.3 2.5 2.371277

50% Reduc All N ‐ 2009 0 54 0 6.9 5.8 6.9 0 0 0 1.1 3.4 2.3 2.0 5.2 4.0 1.5 63 6.1 2.4 3.2 2.408226

50% Reduc All N ‐ 2010 0 34 0 6.8 6.1 7.0 0 0 0 0.8 3.2 2.6 1.6 5.3 4.0 1.4 88 4.3 2.5 2.7 2.508026

75% Reduc All N ‐ 2005 0 60 0 6.4 5.4 7.1 0 0 0 0.7 1.9 1.5 1.1 2.8 2.7 0.9 21 6.4 2.6 4.7 3.0

75% Reduc All N ‐ 2006 0 47 0 6.7 5.5 6.9 0 0 0 0.5 1.5 1.5 1.1 2.7 2.3 0.9 92 3.9 2.6 2.6 2.6

75% Reduc All N ‐ 2007 0 60 0 6.5 4.9 7.0 0 0 0 0.4 3.6 3.0 0.7 5.2 4.3 1.4 76 5.9 2.4 2.5 2.5

75% Reduc All N ‐ 2008 0 60 0 6.8 5.0 6.9 0 0 0 0.6 1.7 1.5 1.0 2.7 2.5 0.9 70 6.0 2.5 2.7 2.573553

75% Reduc All N ‐ 2009 0 56 0 6.9 5.8 6.9 0 0 0 0.6 1.8 1.4 1.0 2.7 2.1 0.9 51 6.5 2.5 3.5 2.554001

75% Reduc All N 2010 0 35 0 6.7 6.1 7.0 0 0 0 0.4 1.6 1.4 0.7 2.7 2.2 0.8 88 4.4 2.6 3.0 2.663883

Additional Metrics

Page E‐2


Run Composite 6yr System WQI

1 Base Case 70

5 25% Reduc All P 72



8 25% Reduc All N 72



Annual System WQI

Run 2005 2006 2007 2008 2009 2010

1 Base Case 74 69 62 68 76 71

7 25% Red All N&P 70 67 58 62 72 76

13 50% Red All N&P 71 70 62 66 76 80

19 75% Red All N&P 73 73 65 71 80 83

25 25% Reduc All P 75 71 65 69 77 73

31 50% Reduc All P 77 73 65 70 79 75

37 75% Reduc All P 77 75 65 70 81 77

43 25% Reduc All N 75 71 63 69 78 73

49 50% Reduc All N 76 73 65 70 80 75

55 75% Reduc All N 78 75 66 71 81 77

69.971.7

73.374.2

71.673.3

74.7

65

67

69

71

73

75

77

79

System

WQI


0

10

20

30

40

50

60

70

80

90

Base Case 25% RedAll N&P

50% RedAll N&P

75% RedAll N&P

25% ReducAll P

50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

System

WQI

System WQI by Year

2005

2006

2007

2008

2009

2010

Page E‐3)




1 Base Case 75.0 44.0 90.8

5 25% Reduc All P 77.7 46.3 91.0

6 50% Reduc All P 80.7 47.1 92.0

7 75% Reduc All P 83.3 47.0 92.3

8 25% Reduc All N 77.3 45.6 91.9

9 50% Reduc All N 80.1 47.1 92.6

10 75% Reduc All N 83.1 48.0 93.0 75.077.7

80.783.3

77.380.1

83.1

68

73

78

83

88

93

98

Base Case 25% ReducAll P

50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

System W

QI

Grand Lake

44.0

46.347.1 47.0

45.647.1

48.0

40

42

44

46

48

50

52

54

56

58

60


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

System W

QI


90.8 91.0 92.0 92.3 91.9 92.6 93.0

50

55

60

65

70

75

80

85

90

95

100


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

System W

QI

Granby Reservoir

Page E‐4)



1 Base Case 89 67 65 74 82 73

25 25% Reduc All P 91 70 70 76 84 76

31 50% Reduc All P 93 74 75 79 86 78

37 75% Reduc All P 94 78 79 81 88 81

43 25% Reduc All N 89 71 68 76 84 75

49 50% Reduc All N 91 74 73 79 86 78

55 75% Reduc All N 93 78 78 81 88 81

20

30

40

50

60

70

80

90

100

Base Case 25% Reduc All P 50% Reduc All P 75% Reduc All P 25% Reduc All N 50% Reduc All N 75% Reduc All N

System W

QI


2005

2006

2007

2008

2009

2010

Page E‐5)



1 Base Case 45 49 30 38 54 49

25 25% Reduc All P 47 50 33 40 56 52

31 50% Reduc All P 48 53 30 39 58 55

37 75% Reduc All P 49 55 24 36 60 57

43 25% Reduc All N 45 52 29 39 57 52

49 50% Reduc All N 47 54 29 39 59 55

55 75% Reduc All N 49 56 27 38 61 57

20

30

40

50

60

70

80

90

100


System W

QI


2005

2006

2007

2008

2009

2010

Page E‐6)



1 Base Case 88 91 91 91 92 92

25 25% Reduc All P 88 91 91 91 93 92

31 50% Reduc All P 89 92 92 92 94 93

37 75% Reduc All P 89 92 91 93 94 93

43 25% Reduc All N 90 91 91 92 94 93

49 50% Reduc All N 91 92 92 93 94 93

55 75% Reduc All N 91 93 92 94 95 94

20

30

40

50

60

70

80

90

100


System W

QI


2005

2006

2007

2008

2009

2010

Page E‐7)



1 Base Case 94 90 86 91 92 92

25 25% Reduc All P 96 93 89 93 94 95

31 50% Reduc All P 97 96 93 96 96 97

37 75% Reduc All P 99 98 97 98 98 98

43 25% Reduc All N 95 93 89 94 94 94

49 50% Reduc All N 96 96 93 96 96 96

55 75% Reduc All N 98 98 97 98 98 98


1 Base Case 2.2 3.0 4.0 2.9 2.6 2.6

25 25% Reduc All P 1.6 2.3 3.3 2.5 2.0 1.9

31 50% Reduc All P 1.1 1.6 2.3 1.7 1.4 1.3

37 75% Reduc All P 0.7 0.9 1.3 0.9 0.8 0.7

43 25% Reduc All N 1.9 2.3 3.4 2.3 2.1 2.0

49 50% Reduc All N 1.4 1.6 2.5 1.6 1.5 1.4

55 75% Reduc All N 0.9 0.9 1.4 0.9 0.9 0.8

75

80

85

90

95

100


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

Chla

Subindex Value


2005

2006

2007

2008

2009

2010

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

Chl a

Metric Value (ug/L)


2005

2006

2007

2008

2009

2010

Page E‐8)



1 Base Case 87 45 46 57 70 54

25 25% Reduc All P 91 49 54 60 73 58

31 50% Reduc All P 94 54 61 65 77 62

37 75% Reduc All P 97 59 68 70 81 67

43 25% Reduc All N 86 50 50 61 73 58

49 50% Reduc All N 90 55 57 65 77 62

55 75% Reduc All N 94 60 66 70 81 67


1 Base Case 4.5 2.4 2.4 2.8 3.4 2.7

25 25% Reduc All P 4.8 2.5 2.7 3.0 3.6 2.9

31 50% Reduc All P 5.1 2.7 3.0 3.2 3.8 3.1

37 75% Reduc All P 5.5 2.9 3.4 3.5 4.1 3.3

43 25% Reduc All N 4.4 2.6 2.6 3.0 3.6 2.9

49 50% Reduc All N 4.7 2.7 2.8 3.2 3.8 3.1

55 75% Reduc All N 5.2 3.0 3.2 3.5 4.1 3.3

0

1020

3040

5060

7080

90100


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N



2005

2006

2007

2008

2009

2010

0.0

1.0

2.0

3.0

4.0

5.0

6.0


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

Secchi M

etric Value (m)


2005

2006

2007

2008

2009

2010

Page E‐9)



1 Base Case 88 87 79 82 87 85

25 25% Reduc All P 87 87 78 83 87 85

31 50% Reduc All P 87 86 78 81 86 84

37 75% Reduc All P 86 86 77 80 85 83

43 25% Reduc All N 87 87 78 82 86 85

49 50% Reduc All N 87 86 78 81 86 84

55 75% Reduc All N 87 86 77 81 85 84


1 Base Case 6.9 6.8 6.4 6.6 6.8 6.7

25 25% Reduc All P 6.8 6.8 6.4 6.6 6.8 6.7

31 50% Reduc All P 6.8 6.8 6.4 6.5 6.8 6.7

37 75% Reduc All P 6.8 6.8 6.3 6.5 6.7 6.6

43 25% Reduc All N 6.9 6.8 6.4 6.6 6.8 6.7

49 50% Reduc All N 6.8 6.8 6.4 6.5 6.8 6.7

55 75% Reduc All N 6.8 6.8 6.4 6.5 6.7 6.7

70

7274

7678

8082

8486

8890


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

DO Subindex Result


2005

2006

2007

2008

2009

2010

6.0

6.1

6.2

6.3

6.4

6.5

6.6

6.7

6.8

6.9


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

DO M

etric Value (mg/L)


2005

2006

2007

2008

2009

2010

Page E‐10)



1 Base Case 83 86 74 85 85 86

25 25% Reduc All P 87 89 81 85 88 89

31 50% Reduc All P 93 94 89 89 92 93

37 75% Reduc All P 97 97 95 94 97 97

43 25% Reduc All N 88 91 81 90 89 90

49 50% Reduc All N 93 94 88 94 93 94

55 75% Reduc All N 97 97 95 97 97 97


1 Base Case 4.4 3.9 6.0 4.2 4.2 4.0

25 25% Reduc All P 3.7 3.4 4.8 4.1 3.6 3.3

31 50% Reduc All P 2.5 2.3 3.3 3.3 2.5 2.3

37 75% Reduc All P 1.3 1.2 1.7 2.1 1.4 1.2

43 25% Reduc All N 3.5 3.0 4.9 3.2 3.3 3.0

49 50% Reduc All N 2.4 2.0 3.4 2.2 2.3 2.1

55 75% Reduc All N 1.3 1.1 1.8 1.2 1.3 1.1

60

65

70

75

80

85

90

95

100


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

Chla

Subindex Value


2005

2006

2007

2008

2009

2010

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

Chl a

Metric Value (ug/L)


2005

2006

2007

2008

2009

2010

Page E‐11)



1 Base Case 31 34 25 27 37 31

25 25% Reduc All P 36 36 34 29 39 34

31 50% Reduc All P 40 41 41 33 44 38

37 75% Reduc All P 44 46 50 38 49 43

43 25% Reduc All N 34 38 29 31 41 34

49 50% Reduc All N 38 42 38 34 45 38

55 75% Reduc All N 43 47 48 38 50 42


1 Base Case 1.9 2.0 1.7 1.8 2.1 1.9

25 25% Reduc All P 2.0 2.1 2.0 1.8 2.2 2.0

31 50% Reduc All P 2.2 2.2 2.2 2.0 2.3 2.1

37 75% Reduc All P 2.3 2.4 2.5 2.1 2.5 2.3

43 25% Reduc All N 2.0 2.1 1.8 1.9 2.2 2.0

49 50% Reduc All N 2.1 2.3 2.1 2.0 2.4 2.1

55 75% Reduc All N 2.3 2.4 2.5 2.1 2.5 2.3

0

10

20

30

40

50

60


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N



2005

2006

2007

2008

2009

2010

0.0

0.5

1.0

1.5

2.0

2.5

3.0


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

Secchi M

etric Value (m)


2005

2006

2007

2008

2009

2010

Page E‐12)



1 Base Case 43 49 21 33 60 58

25 25% Reduc All P 40 48 20 34 60 58

31 50% Reduc All P 38 46 16 27 56 56

37 75% Reduc All P 35 44 11 22 53 54

43 25% Reduc All N 40 47 18 30 58 57

49 50% Reduc All N 38 46 15 27 56 56

55 75% Reduc All N 36 45 12 23 54 54


1 Base Case 5.3 5.4 4.7 5.0 5.7 5.7

25 25% Reduc All P 5.2 5.4 4.7 5.0 5.7 5.7

31 50% Reduc All P 5.1 5.4 4.6 4.9 5.6 5.6

37 75% Reduc All P 5.1 5.3 4.5 4.7 5.5 5.6

43 25% Reduc All N 5.2 5.4 4.7 4.9 5.7 5.7

49 50% Reduc All N 5.1 5.3 4.6 4.9 5.6 5.6

55 75% Reduc All N 5.1 5.3 4.5 4.8 5.6 5.6

0

10

20

30

40

50

60

70


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

DO Subindex Result


2005

2006

2007

2008

2009

2010

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

DO M

etric Value (mg/L)


2005

2006

2007

2008

2009

2010

Page E‐13)



1 Base Case 92 92 93 91 92 93

25 25% Reduc All P 93 94 95 91 93 95

31 50% Reduc All P 96 96 97 95 96 97

37 75% Reduc All P 98 98 99 98 98 98

43 25% Reduc All N 94 94 95 94 94 95

49 50% Reduc All N 96 96 97 96 96 97

55 75% Reduc All N 98 98 98 98 98 98


1 Base Case 2.6 2.8 2.4 2.8 2.8 2.5

25 25% Reduc All P 2.5 2.1 1.8 2.8 2.4 2.0

31 50% Reduc All P 1.7 1.4 1.2 1.9 1.6 1.3

37 75% Reduc All P 0.9 0.7 0.7 1.0 0.8 0.7

43 25% Reduc All N 2.2 2.1 1.9 2.1 2.1 1.9

49 50% Reduc All N 1.5 1.4 1.3 1.5 1.4 1.3

55 75% Reduc All N 0.9 0.8 0.7 0.8 0.8 0.7

86

88

90

92

94

96

98

100


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

Chla

Subindex Value


2005

2006

2007

2008

2009

2010

0.0

0.5

1.0

1.5

2.0

2.5

3.0


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

Chl a

Metric Value (ug/L)


2005

2006

2007

2008

2009

2010

Page E‐14)



1 Base Case 90 100 100 98 98 99

25 25% Reduc All P 91 100 100 96 97 99

31 50% Reduc All P 96 100 100 99 100 100

37 75% Reduc All P 99 100 100 100 100 100

43 25% Reduc All N 95 100 100 99 100 100

49 50% Reduc All N 98 100 100 100 100 100

55 75% Reduc All N 99 100 100 100 100 100


1 Base Case 4.7 6.2 6.6 5.7 5.7 6.0

25 25% Reduc All P 4.8 6.3 6.8 5.4 5.6 5.9

31 50% Reduc All P 5.4 6.9 7.2 5.9 6.1 6.5

37 75% Reduc All P 5.9 7.6 7.7 6.6 6.9 7.1

43 25% Reduc All N 5.3 6.6 6.9 6.1 6.1 6.4

49 50% Reduc All N 5.6 7.1 7.3 6.5 6.5 6.8

55 75% Reduc All N 6.0 7.6 7.8 6.9 7.1 7.2

84

86

88

90

92

94

96

98

100


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N



2005

2006

2007

2008

2009

2010

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

Secchi M

etric Value (m)


2005

2006

2007

2008

2009

2010

Page E‐15)



1 Base Case 82 82 82 85 88 84

25 25% Reduc All P 80 82 81 85 88 84

31 50% Reduc All P 78 82 80 85 87 84

37 75% Reduc All P 76 81 79 84 86 83

43 25% Reduc All N 83 82 82 85 88 84

49 50% Reduc All N 81 82 82 85 88 84

55 75% Reduc All N 78 82 81 85 87 84


1 Base Case 6.6 6.6 6.6 6.7 6.9 6.7

25 25% Reduc All P 6.5 6.6 6.6 6.7 6.9 6.7

31 50% Reduc All P 6.4 6.6 6.5 6.7 6.9 6.7

37 75% Reduc All P 6.3 6.6 6.4 6.7 6.8 6.6

43 25% Reduc All N 6.6 6.6 6.6 6.7 6.9 6.7

49 50% Reduc All N 6.5 6.6 6.6 6.7 6.9 6.7

55 75% Reduc All N 6.4 6.6 6.5 6.7 6.8 6.7

687072747678808284868890


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

DO Subindex Result


2005

2006

2007

2008

2009

2010

6.0

6.16.2

6.36.4

6.56.6

6.76.8

6.97.0


50% ReducAll P

75% ReducAll P

25% ReducAll N

50% ReducAll N

75% ReducAll N

DO M

etric Value (mg/L)


2005

2006

2007

2008

2009

2010

Page E‐16)

water quality model sensitivity analysis · 1/27/2014 · three lakes model nutrient sensitivity...

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