IRWP Seasonal Storage Project Water Reuse System Storage Model

RDD/070330003 (SYSTEM_STORAGE.DOC) WB012007008RDD 1
T E C H N I C A L M E M O R A N D U M
IRWP Seasonal Storage Project
Water Reuse System Storage Model
PREPARED FOR: City of Santa Rosa
PREPARED BY: Rob Tull/CH2M HILL
Jason Lillywhite/CH2M HILL
REVIEWED BY: Doug Smith/CH2M HILL
Ted Whiton/Winzler & Kelly
Marc Soloman/Winzler & Kelly
COPIES: Dave Smith/Merritt Smith Consulting
Pat Collins/Winzler & Kelly
Mark Millan/Data Instincts
DATE: November 29, 2007
Background and Purpose
The existing Water Balance Model (WBM) utilized during the Incremental Recycled Water
Program (IRWP) feasibility study and master planning work identified the need for addi-
tional seasonal storage to support additional reuse projects. However, a more detailed
simulation was still needed to better define the operational interaction between existing and
potential future storage ponds within the envelope of the IRWP demand and discharge
scenarios developed in the IRWP. The Seasonal Storage Project (SSP), therefore, included a
Storage Planning Model (SPM), as described in this technical memorandum (TM).
The purpose of this TM is to document the data collection, model approach, assumptions,
and operational rules used to build the SPM for the Santa Rosa Subregional Water Reuse
System (Subregional System). This TM also summarizes the model results for the
seven storage and five demand scenarios evaluated in the storage analysis.
The SPM was developed to conduct a screening-level evaluation of the Subregional
System’s seasonal storage options under alternative future storage location, sizing, and
demand scenarios. The results of the model show how alternative storage site locations
perform if integrated into the existing Subregional System. The model simulates the existing
and future system response to changes in urban demands, agricultural demands, flows to
the Geysers, and discharge disposal strategies.
The model was applied to potential additional storage sites, including the following sites:
x Alpha Pond
x Brown Pond
x Kelly Pond
x West College Pond

IRWP SEASONAL STORAGE PROJECT
WATER REUSE SYSTEM STORAGE MODEL
x Alexander Valley Road Pond
x Petaluma Hill Road Pond
The West College and Alexander Valley Road Sites are not considered further because of
findings from the geotechnical investigations indicating uncertainty related to potential
impacts from liquefaction, fault zones, and/or landslides and the appropriate measures to
mitigate for these potential hazards. Based on the geotechnical findings at these sites, both
are considered infeasible as defined by CEQA Guidelines, as described in the TM
Geotechnical Evaluation, November 2007.
This TM covers the following topics:
x Background and Purpose
x Conclusions and Recommendations
x Study Area and Modeling Approach
x Analytical Approach
x Existing System Data and Pond Operations
x Existing Conditions Model Formulation and Verification
x Future Model Formulation
x Future Conditions Model Results
Conclusions and Recommendations
The following conclusions are based on evaluation of the results from the future conditions
model:
x Location of Future Ponds: Through simulations of all pond location scenarios, it was
found that storage location does not affect the volume of future total system storage
capacity needed nor the ability to discharge.
x Additional Volume Requirement: The range of additional storage volume required for
the scenarios run in the future conditions model (under five different hydrologic water
years ranging from dry to wet, where a water year is defined as starting on October 1
and ending on September 30) is between 200 and 650 million gallons (MG). The
additional volume required is based on an existing maximum operational storage
volume of 1,436 MG.
x Pipe and Pump Capacities: Increasing the capacity of the pipeline from Meadow Lane
Pond to Delta Pond could reduce the discharge from Meadow Lane Pond complex to the
Laguna de Santa Rosa (Laguna). Some other minor facility upgrades might be required
as part of pond enlargements under a given pond scenario, such as piping for draining
ponds.

Study Area and Modeling Approach
Study Area
The study area for the SPM includes the Laguna Subregional Water Reuse Facility (Laguna
Plant), all existing reuse storage ponds, major transmission pipelines, pump stations, and
the Geysers supply pipeline to the point of delivery.
The system is divided into five zones (used for flowmeter reading) where recycled water is
applied for irrigation from the Laguna Plant. The Rohnert Park urban reuse areas are in
addition to these five zones. Figure 1 is a map showing the study area, including major
conveyance facilities and the five demand zones. Recycled water in the Subregional System
comes from the Laguna Plant and is delivered to irrigated areas shown on Figure 1. Water
that is not immediately used for irrigation is stored in ponds located throughout the system.
Water can be discharged into the Laguna from Meadow Lane Pond complex and Delta Pond
at certain times of the year under given discharge constraints.
Summary of General Approach
The SPM was built in two phases, with the first consisting of an existing conditions model
and the second, a future scenario model. The SPM was built on information provided by the
City of Santa Rosa and an existing simulation model called the WBM. Some of the results of
the SPM related to operational and hydraulic constraints will be used in coordination with a
separate reuse system Hydraulics Model, which will then provide input to the Urban Reuse
Hydraulics Model. Figure 2 illustrates how these models work together.
The following steps were taken in building the SPM:
1. Develop an understanding of the existing system.
2. Collect hydrologic, physical system, and operations data.
3. Develop a daily time-step existing conditions model to verify the SPM’s ability to
adequately simulate the operation of the storage ponds from October 2003 through
October 2006.
4. Modify the existing conditions model with logic used in the WBM to allow simulation of
alternative future pond storage and demand scenarios.
5. Conduct simulations of five different hydrologic years for each alterative future pond
storage and system demand scenario.
GoldSim Pro Software
The SPM needed a flexible software platform or tool to simulate multiple decision processes
and operational rules for a complex system of ponds connected by pipelines and pump
stations. This tool also needed to provide output that would allow for easy evaluation of
alternative storage and demand scenarios.
GoldSim was the chosen software because it provides a highly effective and flexible simula-
tion platform for visualizing and dynamically simulating physical, financial, or organiza-
tional systems. This software allows models to be built in an intuitive manner by literally

drawing a picture (an influence diagram) of the system. The user can graphically create and
manipulate data and equations within a series of linked elements or dashboards.

Rohnert
Park
Pump
Station
Laguna
Subregional
Water
Reclamation
Facility
FIGURE 1
SANTA ROSA SUBREGIONAL
WATER REUSE SYSTEM
WB012007018RDD_01 (2/27/07)
High/Low Pressure
Reuse Pipeline
Geysers Pipeline
Irrigation Areas

FIGURE 2
Illustration of Overall Model Coordination
WBM
x Rules for allowable discharge and required
storage
x Plant flows
x Hydrology
x Irrigation demand patterns
x Future reuse demands, schedules, priorities
Storage Planning
Model
Hydraulics
Modela
x Pipeline peak capacities
x Pump curves
x Pressures and elevations
x Simulates pond volume transfers and flow
rates between ponds
x Incorporates rules governing transfers
x Includes all ponds in system
x Include existing users and associated
demand patterns
x Does not calculate river flows or plant
outflows
x Future reuse demands, schedules, priorities
Urban Reuse
Hydraulics Modelb
Confirmscapacity
available
x Required storage under
various operations or
geographic scenariosCoordinate
Major Coordination ComponentsModel Relationships
Check results and logic
Notes:
aThe Hydraulics Model simulates the pipe network system that interconnects all of the ponds. This model will be used
to evaluate and confirm pump and pipe capacities and also to check pressure requirements.
bThe Urban Reuse Hydraulics Model will be similar in function to the Hydraulic Model, but it is focused on the proposed
Urban Reuse system. This model will be built using the Hydraulics Model as the foundation and will be supported by
the results of the Storage Planning Model.

Analytical Approach
The following steps were taken in building the SPM:
1. Develop an Understanding of the Existing System.
The first step in building the SPM was to develop an understanding of the existing system.
This step included formulating a general layout of the existing system based on previously
created schematic diagrams. This general layout includes flow directions from the Laguna
Plant to the ponds and from ponds to demands. This basic understanding was developed
through discussions with Reclamation Superintendent Randy Piazza.
2. Collect Hydrologic, Physical System, and Operational Data.
The next step was to gather the pertinent hydrologic, physical system, and operational data
critical to building the model of the existing system. The data obtained was for the period
October 2003 through October 2006 and was the basis for the existing conditions model run.
3. Develop Existing Conditions Model.
The purpose of the existing conditions model was to verify the model’s ability to adequately
simulate the system. During this step, some inconsistencies in the data were noted for
operations in the years 2003 through 2006. These inconsistencies were taken into account in
the model verification process and, in some cases, the model results did not exactly match
historical operations. However, on an overall basis, the results from the existing conditions
model matched historical operations of the system very closely for the period 2003 through
2006. This demonstrates the model’s ability to simulate the complex operations of the
Subregional System.
4. Develop Future Conditions Model.
The existing conditions model was modified to incorporate the capability to simulate the
operation of alternative future conditions. This includes simulation of proposed storage site
locations and pond volumes, changes in operations, increased demands, changes in
receiving water quality constraints, and increased Laguna Plant production. To simulate the
ponds, dynamic storage rule curves were developed to control and balance simulated pond
inflows, pond outflows, and discharges to reuse activities or the Laguna. These storage rule
curves are made up of multiple volume or level target points that change seasonally to help
“guide” the operations of a storage facility. In general, these curves are used to guide
decisions regarding storage facility operations, such as increasing storage or outflows. The
dynamic storage rule curves used in the SPM adjust, depending on the hydrology, and
provide a continuous target storage level for each pond that triggers when to begin storing
water, controls discharge timing, and allocates water to demands.
5. Conduct Future Scenario Simulations.
The future conditions model was used to evaluate multiple demand and storage scenarios.
Scenarios included six different future pond configurations (one of which includes no
increase to overall storage capacity), and five future demand levels. Each scenario was
simulated for five years representing a range of driest to wettest hydrologic conditions (as
established by the WBM).

Existing System Data and Pond Operations
A meeting was held with Randy Piazza on October 10, 2006, to discuss operational parame-
ters and practices used to operate and maintain the reuse system. A field visit to the major
Subregional System facilities was also conducted. The following section briefly describes the
operations and physical facilities of the system as they relate to the development of the
existing conditions SPM.
Summary of Data Obtained for the Existing Conditions Model
1. Physical characteristics of the existing ponds (storage volume, fill/drain rates)
2. Demand scenarios, priorities, categories (zones and ponds), and patterns
3. Operational rules and criteria for filling and draining storage ponds
Table 1 summarizes all of the data collected for the existing conditions model.
TABLE 1
List of Data Obtained for the Existing Conditions Model
IRWP Seasonal Storage Project – Water Reuse System Storage Model
Type Description Dates in Set
Time-
Step
Total pond storage volumes with lower, upper, and maximum
boundaries
Jan 1, 2004 –
Oct 10, 2006
Daily
Stage-volume curves for each pond N/A N/A
Pond storage volumes for Meadow Lane, Delta, West College,
and small ponds (combined smaller ponds)
Oct 1, 2003 –
Sep 30, 2006
Daily
Storage
Summary of operational ranges of storage at individual ponds N/A N/A
Geysers flow data Oct 1, 2003 –
Sep 30, 2006
Daily
Irrigation water use separated by zones and ponds
(accumulation of many files)
Sep 1, 2003 –
Sep 30, 2006
Monthly
Crop ET (Bennett Valley) Oct 1, 2001 –
Sep 30, 2006
Daily
Demands
Typical demands on Delta Pond system N/A Monthly
River discharge Oct 1, 2003 –
Sep 30, 2006
Daily
Russian River flows at Guerneville Oct 1, 2003 –
Oct 16, 2006
Daily
Pond discharge flows (including Alpha, Brown, Kelly, Laguna de
Santa Rosa [Laguna], Delta)
Jan 1, 2000 –
May 3, 2006
Daily
Documentation of how 2005-2006 Laguna flows at Delta were
estimated
N/A N/A
Laguna flows near Delta Pond Oct 1, 2003 –
Sep 30, 2006
Daily
Laguna water surface elevation near Delta Pond Oct 1, 2003 –
Sep 30, 2006
Daily
River &
Discharge
Russian River Flows at Hacienda Gage Oct 1, 2003 –
Sep 30, 2006
Daily

TABLE 1
List of Data Obtained for the Existing Conditions Model
Type Description Dates in Set
Time-
Step
Climate Precipitation and pan evaporation measured at the Laguna
Plant (includes temperature data)
Oct 1, 2003 –
Oct 13, 2006
Daily
Water Balance data (summary data – current typical and
historical maximum)
N/A Monthly
Five year types used in Legacy Model (WBM) Varies Daily
Water
Balance
Documentation of Legacy Model setup N/A N/A
Other Maps of Subregional System N/A N/A
Documentation of 2004 Sonoma County Water Authority
(SCWA) water usage
2004 Monthly
Documentation of 2005 SCWA water usage 2005 Monthly
Documentation of 2006 SCWA water usage 2006 Monthly
SCWA transfer in water usage summary Oct 1, 2003 –
Sep 30, 2006
Monthly
Flow In
Laguna Plant effluent flow data Aug 1, 2003 –
Oct 16, 2006
Daily
Existing Operating Information and Rules
The following is a summary of information and general rules that were applied in operating
the existing pond system:
x Total system storage goal at the end of the irrigation season is about 120 MG.
x The total system storage goal at the beginning of the irrigation season is around
1,350 MG. The total maximum operational storage volume is 1,436 MG.
x In pre-Geysers years (before 2003), an average of four cuttings of hay were made on City
farms during the irrigation season. In the post-Geysers period, there was only enough
water to provide for two cuttings on City farms, resulting in an abbreviated irrigation
season in which water deliveries end around July 1.
x Typically, the system storage target for March 1 is 1 billion gallons. The amount of rain
after this date will determine whether the operator will continue storing or discharging
water.
x The drawdown operations of Meadow Lane Pond and Delta Pond, which occurs late in
the irrigation season, is coordinated so that the volumes of both ponds are
approximately equal between August 1 and October 1.
Year 2005 was considered by operations staff to be more of a typical (or average) year for
operating the system. Year 2004 was considered drier than normal with a very dry spring,
and year 2006 was considered to be a very wet year. The last 3 years provided a good range
of hydrologic conditions. The Geysers Pipeline did not come into operation until the end of

2003, which needs to be considered when analyzing this information, because the Geysers
Pipeline has a significant impact on total recycled water usage.
Laguna Plant Production and System Discharges
Laguna Plant daily production was obtained directly from Supervisory Control and Data
Acquisition (SCADA) records. Figure 3 is a plot of these data from October 2003 through
September 2006.
0
10
20
30
40
50
60
70
2004 2005 2006
WWTPProduction(MGD)
Time (Years)
FIGURE 3
Laguna Plant Flows (Oct 2003 – Oct 2006)
Daily system discharge flow rate records from October 2003 through September 2006 are
shown on Figure 4. Values shown represent total discharge from the Subregional System.
0
20
40
60
80
100
120
140
160
2004 2005 2006
Discharge(mgd)
Time (Years)
FIGURE 4
Recorded Discharge (Oct 2003 – Oct 2006)
Hydrology
Hydrology data collected for the existing conditions model include daily flow records in the
Russian River at the Hacienda Gage from October 2003 through September 2006. This
information was obtained from Merritt Smith Consulting and is shown on Figure 5.

0
10
20
30
40
50
60
70
80
90
2004 2005 2006
Flow(1,000cfs)
Time (day)
FIGURE 5
Russian River Flow at Hacienda Gage (Oct 2003 – Sept 2006)
Climatic Data
Climatic data used for the existing conditions model include evaporation and precipitation.
This information was obtained from Laguna Plant records and was used to calculate the net
loss or gain at each pond as a result of evaporation and precipitation. Pan evaporation data
recorded at the Laguna Plant was converted to pond evaporation using a pan coefficient of
0.7 (typical range is 0.65 to 0.85). Evaporation and precipitation are applied in inches to the
pond water surface to estimate the volume of net loss or gain. Figure 6 is a graph of the
daily net sum of precipitation and evaporation used in the existing conditions model.
-20
-10
0
10
20
30
2004 2005 2006
NetEvaporation/Precipitation(in)
Time (day)
FIGURE 6
Net Evaporation and Precipitation (Oct 2003 – Sept 2006)
Data Validation
A monthly systemwide water balance was conducted using existing recorded field data by
accounting for flow into the system minus flow out of the system and comparing that net
flow volume to the change in total system storage. The existing data used in this procedure
included irrigation demands, Laguna Plant production, discharge rates, and storage
volumes for water years 2004 through 2006. The water balance results are shown on

Figure 7, where inflow minus outflow is compared to monthly changes in total system
storage. The results indicate reasonable agreement with some expected variation, likely
caused by the relative accuracy of the various data collection methods and typical data
measurement uncertainty associated with flowmeter error, accuracy of pond depth/storage
rating curves, measured evaporation/precipitation rates, and pond level measurements. No
evidence exists of any particular bias in the data, indicating that the data error is generally
balanced and does not accumulate over time. The months with the greatest deviation occur
in December 2003 and January of 2004, which coincide with the approximate time that the
Geysers Pipeline first became operational.
The results of the water balance analysis provided an adequate data set for developing and
verifying the existing conditions SPM. The observed data for October 2003 through
September 2006 were used as the basis for evaluating the SPM’s ability to simulate the
general operations of the existing system. The October 2003 through September 2006 data
set was not used in the future conditions analysis, which incorporated hydrologic
information from the WBM for five specific year types representing a range of different
hydrologic conditions.
-600
-400
-200
0
200
400
600
800
Oct-2003
Oct-2004
Oct-2005
Date
MillionGallons
Qin-Qout
Change in Storage
FIGURE 7
Existing Water Balance Comparison
Existing Conditions Model Formulation and Verification
A model verification process was conducted for the existing conditions model based on
system storage and discharge data for water years 2004, 2005, and 2006. Water years used in

the SPM start on October 1 and end on September 30. This process confirmed the existing
conditions model’s ability to simulate the existing system.
Existing System Configuration
Figure 8 shows a schematic diagram of the existing reuse system. Water from the Laguna
Plant flows directly into the Meadow Lane Pond complex, which includes the pumps
feeding the agricultural and urban reuse systems (EA and EB pumps) and the pumps
feeding the Geysers (Llano Pump Station). Water from the plant can either be distributed
using these pump stations, or stored in the Meadowlane Ponds. From the Meadow Lane
Pond complex, water is sent in the following three directions:
1. To Zones 2 and 3, then to the Delta/West College System and Zones 4 and 5
2. Geysers
3. Rohnert Park System and Zone 1
The EB pumps are used to lift water to the irrigation demand zones within the Subregional
System (and Delta Pond), including the south end of Zone 1 and Rohnert Park demands.
Within the Rohnert Park system, the Rohnert Park Pump Station lifts water to Rohnert Park
high-pressure demands and to Gallo Pond. The EB pumps also pump water north of Meadow
Lane Pond to Alpha, Brown, Kelly, and Lafranconi Ponds and to Zone 1, 2, and 3 demands.
Delta Pond supplies water to the Delta/West College system and is lifted through the Delta
Pump Station to Ambrosini Pond, Place to Play, West College Ponds and Zones 4 and
5 demands. Currently, some water from the Sonoma County Water Agency transfers into
the system, but it is anticipated that this will not continue in the future. The Delta Pump
Station is operated to maintain target water levels in West College Pond. The North Pump
Station is located to the north of Delta Pond and supplies water to several private farmers.
The demands supplied by this pump station were included in the model, but the actual
operations of this pump station were not simulated.
Existing Conditions Model Logic
The existing conditions model runs on a daily time-step for 3 consecutive water years
starting on October 1, 2003, and ending on September 30, 2006.
At each pond, the model flow logic is as follows: outflow from the pond is the given irriga-
tion demand plus pond evaporation, inflows are calculated according to controls that
change throughout the year, and the controls are intended to provide a certain amount of
storage in the pond that is similar to historical operations. The historical operations are
summarized in the next section. Precipitation on the ponds is added to the inflow. A storage
element in GoldSim is used to calculate the change in storage given the inflows and out-
flows. GoldSim uses the following reservoir routing equation to calculate change in storage:
)()( tOtIS ''' )(
2
)(
)(
2
)( 2121
12 t
OO
t
II
SS '»¼
º
«¬
ª
'»¼
º
«¬
ª
(1)
Where S = Storage, I = Inflow, O = Outflow, and t = time.

FIGURE 8
Existing Conditions Model Schematic
Figure 9 illustrates Alpha Pond model logic as an example of how the mass balance of each
pond is calculated. “AP” is the storage element that simulates change in storage volume (for
Alpha Pond). “Qin” is the sum of precipitation and controlled inflows to the pond, and
“Qout” is a sum of evaporation and irrigation demands that pull water from the pond.
The pond operation rules at Meadow Lane and Delta Ponds are similar to those of the other
ponds except that these ponds may be drained by discharging to the Laguna or by sending
water back into the system to meet demands. For the existing conditions model, discharge is
calculated as a percentage of Russian River flow. Discharge rates in Meadow Lane and Delta
Ponds are controlled by meeting target volumes in the respective ponds at different times of
the year. Discharge rules and criteria become more complex in the future conditions model.

FIGURE 9
Typical Pond Mass Balance Flow Diagram
Existing Pond Operations
The following discussion summarizes the status and current operational parameters for
each pond in the Subregional System. Table 2 summarizes the basic operating parameters
for each pond in the system.
Gallo
This pond is currently a one-way pond, receiving inflow from the Rohnert Park Pump
Station. Flow cannot be returned to the system from this pond. The piping could potentially
be modified to turn this into a two-way pond, benefiting the overall system. The volume of
this pond is not counted as part of total system storage. The total pond capacity is estimated
to be up to 90 MG, but the maximum usable capacity is equal to the amount that is supplied
to irrigation (approximately 60 MG), since Gallo is currently operating as a one-way pond.

TABLE 2
Summary of Pond Operating Parameters – Initial Conditions
Pond
Two-way
Pond?
c
Dead Storage
Volume
(MG)
Maximum
Operating
Volume
b
(MG)
Emergency
Overflow
Volume
(MG)
Maximum
Fill/Drain Rate
(mgd)
Alpha no 5 31 37 5
Ambrosini no 5 18 24 4
Browna no 30b 128 145 10
Delta yes 20 572 632 25d
Kelly no 2 23 29 7
Lafranconi no 3 5 6 1
Meadow Lane yes 13 564 600 N/A
Place to Play no 10 20 27 1.5
West College no 10 75 106 20
Total 98 1,436 1,606
Gallo no 5 90 100 7
Total w/Gallo 103 1,526 1,706
aBrown Pond dead storage can drop below 30 MG during non-irrigation season.
bMaximum operating volume is defined as 2 feet below the overflow level at all ponds except for Meadow Lane
Pond, where it is 1.5 feet below the overflow at C and D Ponds and equal to the overflow level at B Pond.
c
This means that the pond is capable of a two-way filling and draining operation rather than just a one-way filling
operation, which does not have the ability to drain water back into the main supply system.
d
The fill rate for Delta Pond includes flow only from Meadow Lane Pond
Brown
This pond is currently a one-way pond, which means water flows into this pond from the
existing recycled water system pipeline (main supply system), but water from the pond
cannot return to the same pipeline system. This pond is filled during April with a target fill
date of May 1. Throughout summer, this pond is slowly filled as-needed for irrigators
connected to this pond, which include both City and private demands. The current initial fill
rate is 15 mgd. Typically, about 10 MG is added twice per summer to this pond after initial
filling. Currently, this pond cannot be filled to its design capacity because when the water
level in the pond exceeds the ground level at the onfarm pump station, water leaks around
the base of the pump station. If the pump station was elevated above the maximum design
water level of Brown Pond, 30 to 35 MG could be added to the usable capacity of the pond.
An additional 30 MG of dead storage exists in the bottom of this pond because, if the water
level is drawn down farther, private irrigators would be cut off from supply. However, the
pond could be completely pumped out in the off season. Mechanical/structural improve-
ments to the onfarm pump station at this pond could increase the maximum operating
volume to 160 MG.

Alpha
There are two ponds at Alpha that were simulated as one pond in the SPM. An automated
control valve opens to fill this pond twice per year (typically), with the first filling occurring
by May 1.
Meadow Lane
For the purposes of this model, the storage volumes for Ponds B, C, and D were simulated
as a single pond. Pond A acts as a wet well for the pump station, with a storage volume too
small to have significant impact on the overall operations of the system. Ponds B, C, and D
all interact with each other as independent facilities, but will be combined to simplify the
SPM. The operating target for filling Ponds C and D is 530 MG, which is 18 inches below the
overflows. Pond B overflows into Pond C; therefore, a maximum operating level at Pond B
is unnecessary.
Lafranconi
This is a relatively small pond that is typically filled three times per year (filled monthly as it
is used for irrigation). Fill time is less than 1day.
Kelly
This pond is also known as Kelly #1 Pond. Kelly #2 Pond was converted to a wetlands,
which does not hold storage that benefits the system. Currently, Kelly #1 Pond is not filled
to maximum design capacity of 25 MG because of a bank failure. If the bank around the
pond was fixed, 10 MG could be added. A valve is used to fill the pond at a rate of about
2 mgd during the irrigation season.
Delta
Delta Pond is typically filled by May 15. Currently, the water is used to supply the West
College system, including areas north and east of Delta Pond and the areas served by the
North Pump Station. Sometimes, late in the irrigation season, some users just to the south of
Delta Pond will be served from Delta Pond. The goal, late in the irrigation season, is to
empty Delta and Meadow Lane Ponds simultaneously. For example, if the Delta Pond water
level is significantly higher than that of Meadow Lane Pond in August, water from Delta
Pond would be sent southward to supply demands that would have been supplied by
Meadow Lane Pond. In this example, Delta Pond could be drained at a faster rate than
Meadow Lane Pond for a period of time so that the volumes of the two ponds could come
closer to equilibrium. Any water transferred from SCWA is prevented from entering Delta
Pond (for water quality reasons) as it continues east into Zone 4 (the West College system).
SCWA transfers water from its Oceanview Pond, which can have up to 90 or 100 MG
available. The water is transferred in July and August. The transfer in 2006 was 60 to 70 MG,
and the rate was about 1.5 mgd. The transfer from SCWA is not considered to be a reliable,
long-term supply and is, therefore, not included in the model simulations.
Ambrosini
This pond fills in less than 1 day, and an automatic valve actuator is used to maintain the
water level in this pond. The valve closes when the volume reaches 17 MG, and opens when

it reaches 5 MG. The normal operating range of this pond is 9 to 14 MG. Four users draw
water from this pond for irrigation.
Place to Play (Old 1A)
Historically, these ponds have been referred to as Ponds 1A, 1B, and 1C. Ponds 1B and 1C
are no longer used. Pond 1A is planned to become part of a City park (called Place to Play)
by summer 2007. See Table 2 for operating parameters.
West College (Pond 2)
West College Pond consists of Ponds 1 and 2. Pond 1 is no longer used. The level in Pond 2
“floats” on the system and is used as a buffer for peak demands in Zones 4 and 5. When
demand in this area is low, there is positive flow into the pond. When demand is high,
water will flow out of the pond into the system. The pond is drained at the end of the
irrigation season. Water is fed to this pond from Delta Pond, but can also be supplied from
Meadow Lane Pond.
Storage Pond Rule Curves
For the existing conditions model, each pond is operated based on a target storage rule
curve that prescribes storage volumes as a function of time of year based on existing
operational logic. The basic logic for the operation of all ponds is the same except for
individual fill rates and timing. The basic logic for pond operations (except for Meadow
Lane and Delta Ponds) is described below.
Starting on October 1 of each year, target pond storage is maintained at or near minimum
storage until the fill period begins (usually occurring between the months of March through
May. Pond filling is typically short in duration and high in flow rate so that the pond can fill
completely in anticipation of irrigation demands through the summer. The filling stops
when a target pond volume is reached. Target pond volumes for filling the ponds are listed
in Table 2, under “Maximum Operating Volume.”
When the simulated volume of the pond reaches the Maximum Operating Volume, the
initial high inflow rate is reduced and the model switches to a sustaining inflow rate, which
is intended to maintain approximately the same pond volume through about the end of
July. After July, irrigation demands begin to decrease, so the model switches to a “drain
period,” which refers to a volume slightly higher than the year-end minimum target
volume. The minimum target volume is the dead storage level of the pond shown in
Table 2. In the existing conditions model, there are actually no mechanisms to physically
drain one-way ponds back into the main supply system. However, the ponds are inherently
drained to an extent by supplying irrigation demands. Meadow Lane, Delta, and West
College Ponds are two-way ponds and are able to drain back into the main supply system to
reduce pond volume to minimum pool by the end of the irrigation season. Figure 10 shows
how the storage volume in Brown Pond (a typical one-directional fill pond) rises early in
spring, sustains through summer, and drops back to just above minimum storage in late
summer.

FIGURE 10
Maximum Operating Volume in Brown Pond (Oct 2003 – Sept 2006)
Existing Demands
Figure 11 is a plot of actual recorded irrigation deliveries and Geysers flows between
October 2003 and September 2006. The “Pond Demands” line represents demands that pull
directly from ponds and the “Zone Demands” line represents zone demands (Zones 1
through 5 and Rohnert Park). The irrigation deliveries data were provided in monthly time-
steps, and the Geysers flows were provided in daily time-steps.
FIGURE 11
Irrigation Deliveries and Geysers Flows
Verification of Results
Results from the existing conditions model were compared against historical pond level
records and discharge rates. Figure 12 is a graph of total system storage volumes compared
with recorded values for the 3 years of simulation. Also shown on this graph are minimum
and maximum storage rule curves that help the operators make decisions regarding desired
storage volume levels at different times of the year.

FIGURE 12
Simulated Total Pond Storage Volume Compared with Recorded Volume
As shown on Figure 12, the simulated storage volume closely matches recorded values in
2005 and 2006, but deviates from the observed storage volume in 2004. The difference in
storage volume in year 2004 may be the result of differences in the operations strategies in
each of the 3 years of record. Specifically, the actual total system storage volume in late 2003
was allowed to rise to a higher volume than the total system storage in late 2004 and 2006.
Another difference is that in January 2004, system storage was only reduced to about
600 MG, the volume in January 2005 was reduced to 770 MG, and volume in January 2006
was reduced to 400 MG. These changes in operation are likely the result of real-time
operations in response to rainfall events or in anticipation of forecasted high rainfall events.
The existing conditions simulation does not reflect these real-time changes in operations
because the model logic is based on general system rules designed to approximate
operations.
A comparison of actual recorded discharge with simulated discharge was evaluated during
verification of the existing conditions model (Figure 13). Discharge rules were developed to
mimic actual discharge timing and flow rates. Initially, the model was set to begin discharg-
ing when the total storage volume reached specific target values. These target values were
developed by analyzing the actual recorded storage volume as compared with actual
recorded discharge rates for the 3 years of actual operation. Total storage volume target
values were estimated and allowed to change throughout the winter season.
These target values were used in the model to simulate discharge rates that depended on
total system volume. For example, on October 15 of each year, discharge would begin if the
storage pond volume of Delta Pond exceeded 300 MG; on January 1 of each year, discharge
would begin if storage pond volume of Delta Pond exceeded 400 MG; and on March 1 of
each year, discharge would begin if Delta Pond storage exceeded 500 MG. Based on actual
recorded discharge rates, discharge rates appeared to follow this pattern. However, it was
also found that discharge rates on January 1 of each year varied significantly. These changes
in operation are attributed to previously experienced (and anticipations of future) variations
in winter rainfall patterns. An attempt was made to mimic this change of operation in the

existing conditions model based on analysis completed with the WBM, wherein cumulative
Russian River flows at the Hacienda Gage between October 1 and January 1 of each year
were tracked and discharge managed accordingly. If, by January 1, the cumulative volume
of flow in Russian River exceeded approximately 600,000 acre-feet (AF), discharge would
begin when Delta Pond exceeded 200 MG instead of 400 MG.
FIGURE 13
Simulated Discharge Compared with Recorded Discharge
Because of inconsistencies in the observed data, there are some differences between the
simulated storage volumes and the observed storage values. The complex operational
scheme used in the existing conditions model helped to simulate the amount of actual
recorded discharge, but some real-time decisions made by the pond operators are difficult
to capture within the model’s generalized logic.
Summary of Model Comparison of Existing System
The above simulation was performed to demonstrate that the model was capable of
simulating existing operational decisions reasonably well. This was accomplished by the
following steps:
x Comparison of the overall mass balance
x Comparison of simulated to actual pond volumes
x Comparison of simulated and actual discharge volumes
x Confirmation that the model achieves closure from a mass balance perspective
The verification demonstrates that the model is adequate for planning purposes and
provides a reasonable simulation of existing operations.
Future Conditions Model Formulation
General Approach
The existing conditions model was modified to incorporate the capability to simulate the
operation of alternative future conditions. This includes simulation of proposed storage site

locations and pond volumes, changes in operations, increased demands/reuse, changes in
receiving water quality constraints, and increased Laguna Plant production. To simulate the
ponds, dynamic storage rule curves were developed to control and balance simulated pond
inflows, outflows, and discharges. The rule curves provide a continuous target storage level
for each pond that triggers when to begin storing water, control discharge quantity and
timing, and allocate water to irrigation and other demands.
The future conditions model was used to evaluate multiple demand and storage scenarios.
These scenarios included 6 different future pond configurations (one of which includes no
increase to overall storage capacity), and five future demand levels, which were simulated
for five historical years (from the WBM) representing a range of critical dry to wet hydro-
logic conditions. The future conditions model simulates 365 days starting on October 1 and
ending on September 30 for a given time series of water production and demand conditions.
Data Collection
The data used for future scenario runs are listed in Table 3. The source of the data was the
original WBM, Randy Piazza, and the California Irrigation Management Information System
(CIMIS) website. To simulate future scenarios, the system representation in the future
conditions model must be as consistent as possible with the data assumptions used in the
WBM.
TABLE 3
List of Data Obtained for the Future Conditions Model
Type Description Source
Time-
Step File Name
Total Storage volume (used only for comparison) WBM Daily 5-year types.xls
Stage-volume curves for each pond Randy Piazza N/A Pond reading chart.xls
Storage
Summary of operational ranges of storage at
individual ponds
Randy Piazza N/A SR5.xls
Geysers flow data WBM Daily 5-year types.xls
Tier priorities for demands N/A SR5.xls
Urban demand patterns WBM Monthly SR5.xls
Demands
Laguna T1 T2 and Rohnert Park demand patterns WBM, Randy
Piazza
Monthly Irrigation_Summary.xls
River discharge (for comparison only) WBM Daily 5-year types.xls
Russian River flows at Guerneville WBM Daily 5-year types.xls
Laguna Plant flows near Delta Pond WBM Daily 5-year types.xls
Laguna Plant water surface elevation near
Delta Pond
WBM Daily 5-year types.xls
River and
Discharge
Russian River Flows at Hacienda Gage WBM Daily 5-year types.xls
Climate Precipitation and lake evaporation CIMIS Daily SR5.xls
Inflow Laguna Plant effluent flow data WBM Daily 5-year types.xls
Figure 14 shows the layout of ponds in the future conditions model, which includes the
potential Petaluma Hill Road site and urban demands.

FIGURE 14
Future Conditions Model Schematic
Petaluma Hill Road Pond
For the scenarios that include adding Petaluma Hill Road (PHR) Pond, water will be sent
from the EB pumps at Meadow Lane Complex to the new pond, where water will be
distributed to irrigation demands, including those of South Santa Rosa Urban Reuse and
additional Rohnert Park Reuse. If PHR Pond needs to be drained, and there is not enough
demand to drain the pond, excess water in the pond will be returned to other demands of
the Rohnert Park system and will reduce the flow through the Rohnert Park Pump Station
and the EB pumps.
Future Demands
Demands in the future conditions model are categorized into two tiers and are separated
into six priorities within these tiers. Table 4 summarizes how these demands are prioritized.

Demands are reduced if the total storage is insufficient to meet the full demands through
the end of the irrigation season. Lowest priority demands are reduced first; subsequently,
the next higher priority demand is reduced, if needed. The next higher priority demand is
only reduced if the lower priority demand has been reduced to zero. Laguna Tier 2
demands are treated differently because reductions to these demands affect harvesting
operations and, therefore, must be turned off for the remainder of the season if they are to
be reduced. Baseline demands are outlined herein based on potential future scenarios, but
can be modified to explore various levels and priorities of reuse.
TABLE 4
Summary of Demand Priorities
Demand Name Tier Level Priority
Geysers Tier 1 1 1
Urban Tier 1 1 2
Laguna Tier 1 1 3
North County Tier 1 1 4
Geysers Tier 2 2 5
Laguna Tier 2 2 6
Note:
Geysers Tier 1, Laguna Tier 1, and Laguna Tier 2 are existing demands,
while the others are possible future demands.
Urban and Geysers demand patterns were obtained directly from the WBM. All agricultural
demand patterns (included in Laguna Tier 1, North County Tier 1, and Laguna Tier 2) in the
model are based on a demand pattern developed from actual recorded data for the existing
Laguna Tier 1 and 2 demands for 2003 through 2006. The average of these 3 years of record
was used to develop the agricultural demand pattern, and the total annual volume of
demand was obtained from the TM, Laguna Agricultural Demands – Tier 1 and 2 Demand Levels,
November 2006. Agricultural demands in the WBM typically do not begin until at least May 1
of each water year. For the future conditions model to be consistent with the WBM, the
historical agricultural demands were modified to begin May 1 and use the same springtime
demand reductions as the WBM. Figure 15 is a graph of Zone 1, Tier 1 agricultural demands
used in the future conditions model. Reductions in the spring/early summer occur as a result
of increased precipitation.

FIGURE 15
Example of Agricultural Demands for Different Years
Total annual demands used for various scenarios analyzed in the future conditions model
are summarized in Table 5.
TABLE 5
Demand Scenario Summary
Demands in (MG) for Each Demand Scenario
Demand Scenario 1
b
2 3 4 5
Conservation 0 300 300 300 300
GeysersT1 4,000 4,000 4,000 4,000 4,400
Urban T1 (North) 0 500 500 500 500
Urban T1 (South) 0 500 700 700 500
Laguna T1 1,720 1,720 1,720 1,720 1,720
North County T1 0 100 100 100 400
Geysers T2 0 700 700 2,930a 0
Laguna T2 720 720 720 720 720
Total 6,440 8,540 8,740 10,970 8,540
aDepends on hydrologic year and how much storage is available. Geysers Tier 2 demand
goal = 19 mgd – Geysers Tier 1 flow rate, but only to the extent that supply is available.
bDemand scenario 1 represents existing conditions.
Geysers Tier 1 Demand
The Geysers Tier 1 demand is the highest priority demand in the system and typically
fluctuates only slightly through the year. This demand is supplied through the Geysers
Pump Station and Pipeline. Figure 16 is a plot of a typical monthly flow pattern for Geysers
Tier 1 demands, which is specified in the existing agreement with Calpine.

0
2
4
6
8
10
12
14
Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct
GeysersTier1Flow(MGD)
Time (day)
FIGURE 16
Typical Demand Pattern for Geysers Tier 1 Demand (Driest Year)
Urban Demand
The urban demand is the second highest priority demand in the system and typically
continues through the year with minimal demands in the winter and significantly higher
demands through the summer. Figure 17 is a plot of a typical monthly demand pattern for
the Urban Reuse System, which is based on historical urban reuse demand patterns.
FIGURE 17
Typical Demand Pattern for Urban Demand (Driest Year)
Laguna Tier 1 Demand
The Laguna Tier 1 demand is the third highest priority demand in the system and typically
does not start until May 1 each year. This demand is typically supplied through the EB
Pump Station and from various ponds throughout the system. The pattern for this demand
is based on historical agricultural irrigation demands in the Laguna system. Figure 18 is a
plot of a typical monthly demand pattern for Laguna Tier 1.

FIGURE 18
Typical Demand Pattern for Laguna Tier 1 Demand (Driest Year)
Rohnert Park demands are included in the same tier priority as Laguna Tier 1 demands, but
are characterized by a different demand pattern. The Rohnert Park demand pattern is based
on the average demands of the last 3 years of recorded Rohnert Park water use data.
Figure 19 is a graph showing the Rohnert Park demand pattern used for Rohnert Park high-
pressure demands.
FIGURE 19
Typical Demand Pattern for Rohnert Park Demand (Driest Year)
North County Demand
The North County demand is the fourth highest priority demand in the system and
typically does not start until May 1 each year. The monthly pattern for this demand is based
on the demand pattern used for Laguna Tier 1 demands. This demand is supplied through
the Geysers Pump Station and Pipeline. Figure 20 is a plot of a typical monthly pattern for
North County demands.

FIGURE 20
Typical Demand Pattern for North County Demand (Driest Year)
Geysers Tier 2 Demand
The Geysers Tier 2 demand is the fifth priority demand in the system and typically
fluctuates only slightly through the year. This demand is supplied through the Geysers
Pump Station and Pipeline. Typical monthly flow for Geysers Tier 2 is constant at 1.9 mgd
(except for Demand Scenario 4, where it increases to as much as 7 to 8 mgd).
Laguna Tier 2 Demand
The Laguna Tier 2 demand is the lowest priority demand in the system and typically does
not start until May 1 each year. This demand is usually supplied through the EB Pump
Station and from various ponds throughout the system. Figure 21 is a plot of a typical
monthly demand pattern for Laguna Tier 2.
FIGURE 21
Typical Demand Pattern for Laguna Tier 2 Demand (Driest Year)
Demands are physically distributed through the system into categories as shown in Table 6.
Spatial distribution of demands is based on records obtained from Randy Piazza. These

records are categorized into Demand Zones 1 through 5, Rohnert Park, and Tier 2 demands
at Alpha, Brown, and Kelly Ponds.
TABLE 6
Spatial Demand Distribution
IRW P Seasonal Storage Project – Water Reuse System Storage Model
Zone or Pond
Demand Priority
Name
Annual Demand Volume (median
year, demand scenario 3)
(MG)
Zone 1 (north of EB pumps) Laguna T1 105
Zone 1 (south of EB pumps) Laguna T1 160
Zone 2 Laguna T1 175
Zone 4 Laguna T1 90
Zone 5 (north of Delta Pond) Laguna T1 201
Rohnert Park Low Pressure Laguna T1 163
Rohnert Park High Pressure Laguna T1 216
North County North County T1 104
Alpha Pond Laguna T2 216
Ambrosini Pond Laguna T1 65
Broun Pond (Tier 1) Laguna T1 52
Brown Pond (Tier 2) Laguna T2 200
Gallo Pond Laguna T1 50
Kelly Pond Laguna T2 304
Lafranconi Pond Laguna T1 86
Place to Play Pond Laguna T1 8
West College Pond Laguna T1 5
West College Pond Urban T1 (North) 500
Rohnert Park System (May include
PHR and/or Gallo Ponds)
Urban T1 (South)
700
Geysers Geysers T1 and T2 4,700
Conservation N/A 300
Total 8,745
Five Year Types Used in Future Simulations
The future conditions model is run for each of five hydrologic year types for each pond and
demand scenario. These five years represent a range of critical dry to wet hydrologic
conditions. The data for these five years are part of a larger dataset used in the WBM and
include demand patterns, Laguna Plant effluent flow rates, and Russian River flows.
Simulation results from the WBM, such as total storage volume and discharge flows, were
used for model verification to check the consistency of the results between the future

conditions model and the WBM. Table 7 shows the average Laguna Plant flow and Russian
River flow for each of these five years.
TABLE 7
Five Year Types Used in Future Conditions Simulations
Year Type
Year of Source
Data
Average Laguna
Plant Flow
(mgd)
Average Russian
River Flow
(cfs)
Driest Year 1977 25.1 48
Dry Year 1972 26.7 500
Median Year 1917 29.3 1,191
Wet Year 1914 31.8 2,718
Wettest Year 1983 34.5 3,884
The assumed future base flow (dry weather flow) from Laguna Plant is 25.1 mgd after
accounting for 300 MG of conservation, which is equal to a flow rate of approximately
0.8 mgd. During rain events, the Laguna Plant production rate increases above the base flow
as shown on the graph of production rates for the five years used in the model (Figure 22).
FIGURE 22
Future Laguna Plant Production for the Five Years
Russian River flows for the five years are shown on Figure 23. This graph shows that the
median year flow was greater than wet year flow in the spring.

FIGURE 23
Russian River Flow for the Five Years
Dynamic Storage Rule Curves
Storage rule curves are the primary method of controlling storage and discharge from
storage. The rule curves used in this model were developed such that Tier 1 demands must
be met, while Tier 2 demands are to be supplied only if excess water exists (i.e., in excess of
specified operational storage). Storage rule curves are used to manage flows into and out of
ponds in the system to maintain desired storage.
The dynamic concept and general shape of the rule curves are derived from the curves used
in the WBM. The general shape of the curve is shown on Figure 24. The volume under the
initial portion of the rule curve stays at minimum total system dead storage to provide
discharge management to meet temperature objectives or minimize discharge violations.
The peak of the curve, which occurs between May 1 and June 1, is a function of Tier 1
demands that must be met through the end of September. To store enough water to meet
potential future demands and attain the target storage level on June 1, the rule curve must
start to rise early in the spring. However, this timing depends on the year-to-date hydrology
and annual Tier 1 demand level. In wet years (as indicated by November through March
hydrology), the rising limb of the rule curve is steeper, and might not start rising until
April 1. In a dry year (as indicated by year-to-date hydrology), the rising limb of the rule
curve will be flatter and could start rising as early as March 1 or even February 1, depending
on the annual Tier 1 demands being imposed on the system.

0
200
400
600
800
1000
1200
1400
Storage(mgal)
Time (Month)
FIGURE 24
Example Total System Storage Rule Curve
Three different types of rule curve sets are used, depending on the demand scenario in the
model. Each of these sets of curves allow for changes in the start date when storage begins
to fill (i.e., post-fill date). Table 8 summarizes the peak volume required to meet Tier 1
demands.
TABLE 8
Minimum Tier 1 Demand Storage Requirements
Demand
Scenario Minimum Storage Requirement to Meet Tier 1 Demands
2 Minimum June 1 storage = 1,000 MG
3 and 4 Minimum June 1 storage = 1,200 MG
5 Minimum June 1 storage = 1,400 MG
The logic used to create the sets of rule curves was based on available Russian River flow
and Laguna Plant production data provided for the five years and the various demand
options. A minimum total system-wide dead storage volume of 100 MG is assumed for all
model runs. This is the target volume in the late winter or early spring before the storage fill
date occurs; however, storage may increase above minimum pool in response to wet
weather events. The minimum June 1 storage shown in Table was determined as the
approximate amount required to serve all Tier 1 demands through September with a buffer
of 100 MG. This buffer is used to ensure that demands are met and storage does not fall
below the minimum storage in September. The different hydrologies of the five water years
affects the ability to meet the June 1 storage requirement. For example, in a dry year,
initiation of increasing storage from dead storage level must begin at an earlier date than a
wet year to meet the June 1 requirement.
Based on WBM analyses using flow through February as an indicator of hydrologic year
type, the decision process in the model allows the rule curve to shift based on the current

hydrology. Figure 25 presents a probability distribution of 90 years of Russian River flow
data to show the cumulative volume between October 1 and February 28.
FIGURE 25
Cumulative Flows in Russian River at Hacienda Gage (Oct – Feb)
It was assumed that if the cumulative flow volume in Russian River at Hacienda Gage
exceeded the value shown on the graph at the 80 percent probability, or was above approxi-
mately 400,000 AF by March 1, the year was considered to be a normal to wet year on
March 1. If by March 1, the cumulative flow was found to be less than 400,000 AF (or greater
than 80 percent probability), the year was considered to be a drier than normal year.
The decision process outlined above is used for all demand scenarios to determine the point
of initializing a storage increase from dead pool on March 1. The date that this increase in
storage begins is shifted in the model based on whether the year is considered dry by
March 1.
For demand scenarios 3 and 4, it was necessary to add another decision point at February 1
to ensure that the minimum storage requirement of 1,200 MG is achieved by June 1 for all
water years. In drier years, it might not be possible to meet the required 1,200 MG by June 1
if the determination of whether or not it was a dry year was not made until March 1. To
make the decision on February 1, the same process was used to determine a dry year (using
80 percent probability exceedance criteria), but using a dataset for October through January
instead of October through February. See Figure 26 for a graph of probability of exceedance
for the October through January timeframe.

FIGURE 26
Cumulative Flows in Russian River at Hacienda Gage (Oct – Jan)
For demand scenarios 3 and 4, it was assumed that if the cumulative flow volume in
Russian River at Hacienda Gage exceeded the value shown on the graph at the 80 percent
probability by February 1, the year was considered to be a normal to wet year. If by
February 1 the cumulative flow volume was greater than 80 percent probability, the year
was considered to be a drier than normal year.
For demand scenario 5, the minimum storage requirement for June 1 is 1,400 MG. To ensure
that this storage can be obtained under all five water years, storage must begin to accumu-
late on February 1. But on March 1, the decision process discussed above was used to
determine whether or not the year was dry. If it was found to be a wet to normal year on
March 1, the rule curve shifts accordingly on March 1.
Figures 27 through 29 illustrate the decision process and resultant rule curves used to target
storage requirements for all water years and the various demand scenarios. The figures
illustrate the various permutations that could occur depending on the decisions made on
February 1 and March 1.

0
200
400
600
800
1000
1200
1400
Time (Month)
Storage(MG)
Normal to Wet
Dry
FIGURE 27
Demand Scenario 2 – March 1 Decision Only
0
200
400
600
800
1000
1200
1400
Time (Month)
Storage(MG)
Normal to Wet
Dry
Dry Feb
FIGURE 28
Demand Scenarios 3 and 4 – February 1 and March 1 Decision

0
200
400
600
800
1000
1200
1400
Time (Month)
Storage(MG)
Normal to Wet
Dry
FIGURE 29
Demand Scenario 5 – March 1 Decision Only
Pond Operations Logic
Pond operations logic was developed for all the ponds (future and existing) within the
Subregional System. The logic is used to provide a means to simulate water that is moved
from Laguna Plant to various ponds, then supplied to areas for irrigation or discharged to
the Laguna, and to maintain proportionate pond volumes given certain constraints of each
pond.
Meadow Lane Pond to Delta Pond Flow Logic
The operational rules to control flow from Meadow Lane Pond to Delta Pond are as follows:
1. Pumping capacity at EB Pump Station is 25 mgd minus any additional flows in the main
pipeline between Brown Pond and Delta Pond.
2. Maintain a volume in Meadow Lane Pond that is 30 to 40 MG less than that of Delta
Pond to provide a storage buffer in Meadow Lane Pond while Laguna Plant production
rates continue to fluctuate through the wet season.
3. Decrease pumping to Delta Pond if Meadow Lane Pond volume drops to 5 MG or less.
4. Increase pumping to Delta Pond by a factor of 2 (up to 25 mgd) if the storage volume in
Meadow Lane Pond approaches the maximum operating volume.
5. If Delta Pond volume is more than 40 MG higher than Meadow Lane Pond in August
and September, release water from Delta Pond back into the Meadow Lane Pond system
to drain storage to help meet the minimum fall carryover target.
This logic is used for all scenarios, and the goal is to maintain a balanced operation between
Meadow Lane and Delta Ponds, as shown for pond scenario 6, demand scenario 3 on
Figure 30.

FIGURE 30
Meadow Lane and Delta Pond Storage and Flow Rate to and from the Ponds
Individual Pond Rule Curves
The pond logic used for all ponds (except Lafranconi, Ambrosini, and Place to Play) in the
future conditions model follows a rule curve that is the same shape as the overall system
rule curve described in the section, Dynamic Storage Rule Curves. The rule curve used for
each pond is a scaled-down version of the overall system rule curve. These curves are
calculated as a proportion of total system storage equal to the difference in maximum
storage volume of the individual pond divided by the total maximum system storage
volume as shown in the following equation:
Pond Rule Curve = (Pond Max Volume / Total System Volume) * Total System Rule Curve (2)
Where Pond Max Volume is the maximum operating volume for each pond, and Total
System Volume is the total combined maximum operating volumes of all the ponds.
The future conditions model includes the ability to drain some ponds back into the system,
and to meet demands from the pond. This means that the ponds are capable of a two-way
filling and draining operation rather than just a one-way filling operation. Refer to Table 9
for a summary of ponds that allow proposed two-way operations in the future conditions
SPM. Refer to Table 2 for a summary of pond operational volumes (including dead storage,
maximum operating volume, and emergency overflow volumes) and fill/drain rates used
for the initial conditions of the model. The values shown in Table 2 reflect initial conditions
in the future conditions model and do not show changes in storage volumes for other pond
scenarios that were analyzed. For a comparison of the storage volumes of each pond for all
scenarios evaluated, refer to Table 11.

TABLE 9
Summary of Ponds that Allow Two-way Drain-fill Operation
Pond Two-way Pond?
Alpha yes
Ambrosini no
Brown yes
Delta Yes
Kelly Yes
Lafranconi No
Meadow Lane Yes
Place to Play No
West College Yes
PHR Yes
Gallo No
The fill and drain rates used for PHR were estimated by determining the rate required to fill
the pond to the maximum operating volume, if needed, and to drain the pond before
October 1.
In the future conditions model, simulated pond volumes will generally follow the rule curve
and stay within the bounds of dead storage and maximum operating volume. When total
system storage volume is high, pond operational rules allow storage to slightly exceed the
maximum operating volume when discharge is limited, but storage is never allowed to
exceed the emergency overflow volume. If any pond volume exceeds the emergency volume
or drops below 0.0 MG, the user is notified during the simulation, and a warning message is
sent to the results file. In model runs of the future conditions SPM, appropriate iterative
adjustments were made to the model to prevent these occurrences in the simulations.
As shown on Figure 31, inflows to and outflows from the pond are controlled so that the
simulated volume of the pond follows the rule curve for Alpha Pond. The controls in the
model will cause water to be released from Meadow Lane Pond and Delta Pond for storage
in other ponds if Meadow Lane Pond and Delta Pond storage is within 200 to 300 MG below
their maximum operating levels.

FIGURE 31
Alpha Pond Volume with Inflows and Outflows (Wet Year)
As shown on Figure 32, water is sent to Alpha Pond in May when discharge is no longer
possible at Meadow Lane Pond or Delta Pond. Later in the summer when irrigation
demands are high, this water can be drained from Alpha Pond to serve demands in other
ponds and areas.
FIGURE 32
Alpha Pond Volume with Inflows and Outflows (Wettest Year)
Water transfers from Meadow Lane Pond or Delta Pond to other ponds in the system may
be limited when smaller ponds become too full. To limit these flows, a lookup table was
used that is based on storage levels and emergency pond storage levels. The lookup table
creates a ratio between 0 and 1, with 0 indicating that this pond is full, and 1 indicating that
it is not full.

Discharge Controls
Discharge can occur from Meadow Lane Pond and Delta Pond subject to certain rules and
limitations, which include seasonal timing, physical limitations, dilution requirements,
temperature criteria, and pond capacity.
Discharge rates from Meadow Lane Pond and Delta Pond are controlled using the overall
storage rule curves for each pond. Figure 33 shows that discharge is triggered when the total
storage volume rises above the rule curve. The magnitude of discharge increases as the total
storage volume continues to rise above the rule curve.
FIGURE 33
Total Discharge vs. Total Storage Volume
Discharge from Delta Pond
To avoid impacts of discharge, discharge from Delta Pond has a higher priority than
discharge from Meadow Lane Pond, which causes Delta Pond discharge to begin before
Meadow Lane Pond discharge, and to discharge more volume than at Meadow Lane Pond.
The following factors are used at Delta Pond to control discharge:
1. Discharge Season: Discharge is allowed beginning October 1 and ending May 14.
2. Hydraulic Capacity Limitation: Discharge at Delta Pond is sometimes restricted
hydraulically by the difference in water levels in Delta Pond and in the Laguna. The
following logic is used to calculate the hydraulic capacity to discharge from Delta Pond:
Discharge occurs when the water surface (WS) elevation in Delta Pond exceeds the WS
elevation in the Laguna, and the following equation is used to calculate discharge:
QDP = 21 * ( ElevDP – ElevL_DP) ^ 0.5 (3)
Where QDP = discharge from Delta Pond, ElevL_DP = WS elevation in the Laguna at
Delta Pond, and ElevDP = WS elevation in Delta Pond.
Backflow from the Laguna to Delta Pond could occur, and is calculated using the
following logic:
a. Backflow occurs when WS elevation in the Laguna exceeds the WS elevation in Delta
Pond.

b. Russian River flow at Hacienda Gage exceeds 15,000 cfs.
c. Backflow rate into Delta Pond is calculated as follows:
QDP = 21 * ( ElevL_DP – ElevDP) ^ 0.5 (4)
Where QDP = backflow rate into Delta Pond, ElevL_DP = WS elevation in Laguna at
Delta Pond, ElevDP = WS elevation in Delta Pond.
3. Total System Discharge is Limited to 5 Percent of Russian River Flow at Hacienda
Gage: The sum of the total discharge from Delta Pond and Meadow Lane Pond is
limited to an equivalent flow equal to 5 percent of the flow in the Russian River at the
Hacienda Gage. The 5 percent rule is applied to Delta Pond as follows:
If simulated total system storage minus the desired storage value from the system rule
curve is less than 50 MG, then discharge is 0 mgd. If total system storage minus the
system rule curve is between 50 MG and 70 MG, then discharge ramps up from 0 to
4.99 percent of Russian River flows. If the system storage minus the system rule curve is
between 70 MG and 1,300 MG, then the discharge will be 5 percent. If the variance is
greater than 1,300 MG, then the discharge will be greater than 5 percent. This forces the
model to restrict discharges greater than 5 percent to extreme circumstances in which
the total storage is approaching maximum capacity.
4. Discharge is Limited by Biological Temperature Criteria: These criteria (described in
the Laguna Water Temperature Criteria section below) will control discharge from Delta
Pond unless the volume at Delta Pond rises to within 50 MG of its maximum operating
volume level. The temperature criteria are further discussed in the following section.
5. Emergency Discharge: If the storage volume of the pond exceeds the emergency
volume, the model automatically allows up to 100 mgd discharge, regardless of other
limitations.
Discharge from Meadow Lane Pond
The basic discharge logic at Meadow Lane Pond is the same as that of Delta Pond except
there is no hydraulic backwater limitation. The following factors are used to control
discharge at Meadow Lane Pond:
1. Discharge Season: Discharge is allowed beginning October 1 and ending May 14.
2. Hydraulic Capacity Limitation: Discharge from Meadow Lane Pond is limited to a
maximum of 50 mgd.
3. Discharge Limited to 5 Percent of Russian River Flow: Combined discharge at
Meadow Lane and Delta Ponds is limited to an equivalent flow equal to 5 percent of the
flow in the Russian River at the Hacienda Gage. The 5 percent rule is applied in the
model as follows:
If the simulated storage in Meadow Lane Pond minus the desired storage value from the
Meadow Lane Pond rule curve is less than 210 MG, then discharge is 0 mgd. If Meadow
Lane Pond volume minus the Meadow Lane Pond rule curve is between 210 MG and
500 MG, then discharge ramps up so the combined discharge of Meadowlane and Delta

Ponds will not exceed 5 percent of total Russian River flow. If Meadow Lane Pond
volume minus the Meadow Lane Pond rule curve is greater than 500 MG, then the
combined discharge will be greater than 5 percent. If the variance is greater than
1,300 MG, then the combined discharge will be greater than 5 percent. This logic forces
the model to restrict combined discharges greater than 5 percent to extreme circum-
stances in which the Meadow Lane Pond storage is approaching maximum capacity.
Water may be pumped from Meadow Lane Pond to Delta Pond through the EB Pump
Station according to the pond operations logic discussed in the Pond Operations Logic
section of this TM. This transfer reduces the need to discharge from Meadow Lane Pond
because it reduces the volume of storage to less than 210 MG above the rule curve
during the driest and dry years.
4. Discharge is Limited by Biological Temperature Criteria: These criteria will control the
discharge from Meadow Lane Pond unless the volume in the pond rises above the
emergency overflow volume level. The temperature criteria are further discussed in the
following section.
5. Emergency Discharge: If the storage volume of the pond exceeds the emergency
volume, then the model automatically allows up to 100 mgd discharge, regardless of
other limitations.
As shown on Figure 34, the discharge from Delta Pond occurs more frequently than from
Meadow Lane Pond. This figure shows model simulation results for pond scenario 6,
demand scenario 2, for a median water year.
FIGURE 34
Meadow Lane Discharge vs. Delta Pond Discharge
Laguna Water Temperature Criteria
The Laguna water temperature limitations on discharge are based on biological receiving
water temperature criteria, which were provided by Merritt Smith Consulting. Figure 35 is a
graph of the monthly biological temperature criteria. To assess temperature criteria in the
SPM, a simplified set of thermal criteria were developed based on existing discharge permit

conditions. Although existing permit language has detailed requirements on allowable
increases based on receiving water temperatures, for planning level analysis, a range of
representative values based on time of year and salmon life stage were developed as
screening criteria (M. Fawcett, pers. comm.) (Figure 35)
FIGURE 35
Biological Temperature Criteria
A series of mass balance equations calculate the change in temperature in the Laguna as
reuse water is discharged from Meadow Lane and Delta Ponds. Figure 36 is a schematic
diagram showing the mass balance calculated at each point in the Laguna.
The flow in the Laguna at point A (QA) is input to the model daily, and the flows vary by
water year. The assumed Laguna and pond discharge water temperature values at points A,
M, and D are input to the model. To calculate the flow and temperature at point B in the
Laguna, the following mass balance equations are used.
QB = QA + QM (5)
And
TB = (QA * TA + QM * TM) / QB (6)
QB and TB are flow and temperature calculated at point B in the Laguna.
Some additional contributing flows enter the Laguna between points B and E. This flow
contribution is calculated by comparing the known flow at point A and the known flow just
upstream of Delta Pond, both of which are provided by Merritt Smith Consulting. This flow
contribution between points B and E is referred to as QX. The temperature of QX is assumed
to be equal to TA. To calculate the flow and temperature at point E in the Laguna, the
following mass balance equations are used:
QE = QB + QX (7)
And
TE = (QB * TB + QX * TX) / QX (8)

FIGURE 36
Schematic of Mass Balance Temperature Equations in Laguna
QE and TE are flow and temperature calculated at point E in the Laguna.
Discharge from Delta Pond enters the Laguna between points E and F and the following
mass balance equations are used to calculate flow and temperature at point F.
QF = QE + QD (9)

And
TF = (QE * TE + QD * TD) / QF (10)
QF and TF are flow and temperature calculated at point F in the Laguna.
Allowable discharge based on temperature is calculated as the flow rate allowed before
discharge causes an increase in the Laguna temperature above the biological criteria by
more than 0.5 degree Fahrenheit (°F). The equation for maximum discharge from Meadow
Lane Pond is as follows:
Allowable Discharge = QA * (TA – [TBC + 0.5°F]) / ([TBC + 0.5°F] – TM) (11)
The equation for maximum discharge from Delta Pond is as follows:
Allowable Discharge = QE * (TE – [TBC + 0.5 °F]) / ([TBC + 0.5°F] – TD) (12)
TBC is equal to the biological temperature criteria.
These equations calculate the allowable discharge rate that would not increase water
temperature in the Laguna above the biological temperature criteria.
The allowable discharge based on temperature is used as a soft constraint at Delta Pond and
a hard constraint at Meadow Lane Pond. Delta Pond discharge is constrained to the
maximum temperature discharge rate until the volume in Delta Pond comes to within
50 MG of the maximum operating volume. Discharge at Meadow Lane Pond is restricted to
temperature-based discharge unless the emergency pond level is reached. Figure 37 shows
the water temperature downstream of Delta Pond as compared with the biological criteria.
FIGURE 37
Temperature Downstream of Delta Pond vs. Temperature Criteria
Future Pump Operations
The specific assumptions used in the model for each pump station are described below.
Table 10 summarizes assumed maximum pump station and pipeline capacities.

Delta Pump Station
Delta Pump Station operates according to the rule curve for West College Pond using the
methodology described in the section, Individual Pond Logic. The pump station has a
capacity of 20 mgd and will shut down if storage in Delta Pond drops below a minimum
threshold value.
TABLE 10
Assumed Maximum Operating Pump and Pipeline Capacities
Description Capacity
Pipe from Laguna Plant to Meadow Lane Pond No limit in model
Pipe from EB pumps to as far north as Brown Pond 30 mgd
Pipe from as far north as Brown Pond to Delta Pond 25 mgd
Pipe from Delta Pump Station to West College Pond 20 mgd
Pipe from EB pumps to Rohnert Park System 23 mgd
EB Pump Station 30 mgd
Geysers Pump Station 40 mgd
Rohnert Park Pump Station 23 mgd
Delta Pump Station 20.2 mgd
EB Pump Station
The flow at the EB Pump Station is the sum of all the irrigation demands and flows into the
ponds north and south of the pump station plus the flows needed to fill Delta Pond. The
capacity of the pump station is 30 mgd. The pipeline to Delta Pond is limited to a capacity of
25 mgd, so the pipeline reaches maximum flow capacity before the pump station.
Geysers Pump Station
The Geysers Pump Station has a capacity of 40 mgd, and the required pump flow rate is
calculated as the sum of Geysers Tiers 1 and 2, and North County demands.
Rohnert Park Pump Station
Rohnert Park Pump Station has a capacity of 23 mgd, and the required pump flow rate is
calculated as the sum of flow entering Gallo Pond and Rohnert Park high-pressure zone,
plus flows to PHR Pond if it is included in the scenario.
Future Conditions Model Results
The future conditions model simulates the Subregional System under combinations of
different pond size/location alternatives and demand scenarios. Table 11 summarizes the
pond scenarios analyzed in the future conditions model and the combinations of demand
scenarios simulated under each scenario (shown on bottom row of the table). Shaded entries
indicate scenarios with pond improvements/enlargements or incorporation of new ponds
to augment existing storage. Scenarios 3, 4, 7, 8, and 9 have been removed because some
pond configurations being eliminated from the analysis prior to completion of this TM.

WATER REUSE SYSTEM STORAGE MODEL WATER REUSE SYSTEM STORAGE MODEL
TABLE 11
Pond Storage Scenario Summary
Pond Operating Volumes for Seven Storage Scenarios
(MG)
Pond 1 2 5 6 10 11 12
Alpha 30 30 230 230 30 30 30
Ambrosini 18 18 18 18 18 18 18
Brown 128 128 128 378 128 158 558
Delta 572 572 572 572 572 572 572
Gallo 90 90 90 90 90 90 90
Kelly 23 23 23 273 23 503 23
Lafranconi 5 5 5 5 5 5 5
Meadow Lane 564 564 564 564 564 564 564
Place to Play (old 1A) 20 20 20 20 20 20 20
West College 75 75 75 75 75 75 75
PHR 0 0 500 0 500 0 0
Total 1,525 1,525 2,225 2,225 2,025 2,035 1,955
Laguna Plant Base Flow (mgd) 16.5 25.9 25.9 25.9 25.9 25.9 25.9
Demand Scenario(s) Analyzed 1 2-4 2-4 2-5 2-5 2-4 2-4
Note:
Shaded entries represent pond improvements/enlargements or incorporation of new ponds to augment existing
storage (refer to “Future Pond Operations” section).
All of the scenario combinations were simulated for each of the five water years. The model
results of each scenario combination are automatically exported to a Microsoft Excel file
called “SR5.xls” after each scenario run. The summary table showing all of the scenario
results is included in Attachment 1 of this TM.
The following conclusions are based on evaluation of the results from the future conditions
model:
Location of Future Ponds: Through simulations of all the different pond location scenarios,
storage location does not affect the volume of future total system storage capacity needed
nor the ability to discharge.
Additional Volume Requirement: The range of additional storage volume required for all
of the scenarios run in the future conditions model is between 200 and 650 MG. The
additional volume required is assumed to be the peak storage minus the existing maximum
operating volume of all the ponds in the system, which is 1,436 MG. As shown in Table 12,
for pond Scenario 6, the wettest and driest years require the largest volumes of additional
storage. In the driest year, Russian River flows are very low, and discharge to the Laguna is

extremely limited, requiring more storage. In the wettest year, Laguna Plant production is
very high during wet weather events, and discharge to the Laguna may be limited by
backwater effects from the Russian River. Extra storage needed in the wettest year type over
that needed in the driest year type could be avoided or reduced if the discharge capacity
under high flow conditions was increased by using a pump station to overcome the
backwater limitation. Additional analysis would be required to determine whether
additional storage or pumping is more economical. The summary table of results in
Attachment 1 shows that the driest and wettest year simulations require the highest
additional storage volumes for all of the pond size, location, and demand scenarios.
TABLE 12
Summary of Additional Storage Requirements (MG) – Pond Scenario 6, Demand Scenarios 2 through 5
IRWP Seasonal Storage Project– Water Reuse System Storage Model
Demand Scenario
Representative
Year 2 3 4 5
Driest 416 360 0 555
Dry 0 0 0 0
Median 151 276 30 298
Wet 0 0 0 25
Wettest 441 546 203 650
The different demand scenarios also have a direct impact on the additional volume
requirement. As shown in Table 12, the additional volume requirement for a median year
increases from demand scenario 2 to scenario 3. This increase is because demand scenario 3
includes an additional 200 MG of urban demand, which requires more seasonal storage and
raises the storage rule curve by 200 MG in May and June. This higher urban demand forces
a reduction in Geysers Tier 2 demand during the month of April when the Laguna Plant
production is relatively high. The net effect is that more storage is required under demand
scenario 3 in the median year.
The additional storage required for demand scenario 4 is much less than for other demand
scenarios because demand scenario 4 includes higher Geysers Tier 2 demands. For example,
under the median year, approximately 200 MG of Geysers Tier 2 demand is applied during
the month of May in demand scenario 4, which reduces the required peak storage
significantly.
River Discharge: The results of the future conditions simulations show that the different
demand scenarios have an effect on discharge volume. Table 13 shows that scenarios with
higher demands have lower total discharge volumes to the Laguna.

TABLE 13
Summary Total Discharge (MG) – Pond Scenario 6, Demand Scenarios 2 through 5
Demand Scenario
Representative
Year 2 3 4 5
Driest 304 299 243 303
Dry 1,819 1,761 1,130 1,579
Median 2,533 2,381 1,632 2,527
Wet 3,845 3,733 3,006 3,888
Wettest 4,270 4,098 3,324 4,240
Development of Rule Curves: Rule curves based on Tier 1 demands provide a dynamic
approach to storage evaluation. As discussed in the Dynamic Storage Rule Curves section of
this TM, rule curves were developed according to Tier 1 demands that occur between June 1
and September 30. It was found that this method produced a set of dynamic rule curves that
can be applied to all five water years.
Pipe and Pump Capacities: The results of the future conditions model indicate that most of
the existing conveyance facilities have adequate capacity to move water through the system
under the future scenarios. Some minor facility upgrades might be required as part of pond
enlargements under a given pond scenario, such as piping for draining the pond. Increasing
the capacity of the pipeline from Meadow Lane Pond to Delta Pond could allow reduced
discharge from Meadow Lane Pond.
Additional Simulation Results: Graphs showing total system storage volume and total
discharge for the following pond and demand scenarios are included in Attachment 2 of
this TM.
x Pond Scenario 2, Demand Scenario 2, all five years
Also included in Attachment 2 are plots showing demand reductions for pond scenario 6,
demand scenario 2, and for all five years.
References
CH2M HILL. 2006. Laguna Agricultural Demands – Tier 1 and 2 Demand Levels. November 10.
Piazza, Randy. 2006. Personal communication regarding storage pond operating
parameters. October 10.

Attachment 1
Summary Table of Results

TABLE 1-1
Incremental Recycled Water Program – Water Reuse System Storage Model
PondVolume
Scenario
Demand
Scenario
YearType
DPVolume
MLPVolume
DPDays5%
DPandMLP
Days5%
DPVolume
Temp
MLPVolume
Temp
DPDays
Temp
MLPDays
Temp
GeysersT1
Demands
UrbanDemands
LagunaT1
Demands
NorthCounty
Demands
GeysersT2
Demands
LagunaT2
Demands
CarryOver
Storage(MG)
PeakStorage
(MG)
TotalDischarge
(MG)
volumeover5%
Additional
Storage
Required(MG)
2 2 Driest 661 55 3 36 356 0 51 0 4,000 1,000 1,833 114 683 574 86 1,515 716 460 79
2 2 Dry 1,820 0 0 0 0 0 0 0 4,000 1,000 1,833 114 592 148 127 1,155 1,820 0 0
2 2 Median 2,586 74 1 0 130 0 2 0 4,000 1,000 1,721 104 675 462 87 1,538 2,660 100 102
2 2 Wet 3,101 720 0 0 0 0 0 0 4,000 1,000 1,819 112 656 138 255 1,278 3,820 0 0
2 2 Wettest 3,849 851 4 0 400 50 4 1 4,000 1,000 1,634 97 700 625 69 1,557 4,700 400 121
5 2 Driest 304 0 0 0 0 0 0 0 4,000 1,000 1,833 114 700 875 163 1,852 304 0 416
5 2 Dry 1,827 0 0 0 0 0 0 0 4,000 1,000 1,833 114 592 148 109 1,153 1,827 0 0
5 2 Median 2,444 91 0 0 0 0 0 0 4,000 1,000 1,721 104 681 543 119 1,590 2,535 0 154
5 2 Wet 3,081 784 0 0 0 0 0 0 4,000 1,000 1,819 112 649 138 218 1,257 3,865 0 0
5 2 Wettest 3,425 871 0 0 0 0 0 0 4,000 1,000 1,634 97 700 642 465 1,878 4,296 0 442
6 2 Driest 304 0 0 0 0 0 0 0 4,000 1,000 1,833 114 700 875 179 1,852 304 0 416
6 2 Dry 1,818 0 0 0 0 0 0 0 4,000 1,000 1,833 114 593 148 128 1,156 1,818 0 0
6 2 Median 2,445 88 0 0 0 0 0 0 4,000 1,000 1,721 104 676 543 132 1,587 2,533 0 151
6 2 Wet 3,080 766 0 0 0 0 0 0 4,000 1,000 1,819 112 649 138 237 1,260 3,845 0 0
6 2 Wettest 3,424 848 0 0 0 0 0 0 4,000 1,000 1,634 97 700 642 478 1,876 4,272 0 440
10 2 Driest 304 0 0 0 0 0 0 0 4,000 1,000 1,833 114 700 875 162 1,851 304 0 415
10 2 Dry 1,829 0 0 0 0 0 0 0 4,000 1,000 1,833 114 591 148 108 1,152 1,829 0 0
10 2 Median 2,449 88 0 0 0 0 0 0 4,000 1,000 1,721 104 679 538 124 1,589 2,537 0 153
10 2 Wet 3,087 781 0 0 0 0 0 0 4,000 1,000 1,819 112 648 138 216 1,255 3,868 0 0
10 2 Wettest 3,433 865 0 0 0 0 0 0 4,000 1,000 1,634 97 700 642 462 1,876 4,298 0 440
11 2 Driest 305 0 0 0 0 0 0 0 4,000 1,000 1,833 114 700 875 179 1,852 305 0 416
11 2 Dry 1,818 0 0 0 0 0 0 0 4,000 1,000 1,833 114 593 148 128 1,156 1,818 0 0
11 2 Median 2,450 86 0 0 0 0 0 0 4,000 1,000 1,721 104 676 543 130 1,585 2,536 0 149
11 2 Wet 3,083 764 0 0 0 0 0 0 4,000 1,000 1,819 112 649 138 235 1,258 3,847 0 0
11 2 Wettest 3,432 842 0 0 0 0 0 0 4,000 1,000 1,634 97 700 642 476 1,874 4,274 0 438
12 2 Driest 322 3 0 1 17 0 18 0 4,000 1,000 1,833 114 700 875 158 1,833 325 7 397
12 2 Dry 1,819 0 0 0 0 0 0 0 4,000 1,000 1,833 114 592 148 127 1,155 1,819 0 0
12 2 Median 2,452 85 0 0 0 0 0 0 4,000 1,000 1,721 104 676 543 129 1,584 2,537 0 148
12 2 Wet 3,086 763 0 0 0 0 0 0 4,000 1,000 1,819 112 648 138 235 1,258 3,848 0 0
12 2 Wettest 3,438 837 0 0 0 0 0 0 4,000 1,000 1,634 97 700 642 475 1,873 4,275 0 437
RDD/070370001 (NLH2187.xls)

TABLE 1-1
PondVolume
Scenario
Demand
Scenario
YearType
DPVolume
MLPVolume
DPDays5%
DPandMLP
Days5%
DPVolume
Temp
MLPVolume
Temp
DPDays
Temp
MLPDays
Temp
GeysersT1
Demands
UrbanDemands
LagunaT1
Demands
NorthCounty
Demands
GeysersT2
Demands
LagunaT2
Demands
CarryOver
Storage(MG)
PeakStorage
(MG)
TotalDischarge
(MG)
volumeover5%
Additional
Storage
Required(MG)
2 3 Driest 656 0 3 0 353 0 51 0 4,000 1,200 1,833 114 700 322 180 1,552 656 304 116
2 3 Dry 1,760 0 0 0 0 0 0 0 3,974 1,188 1,825 113 525 143 107 1,230 1,760 0 0
2 3 Median 2,525 86 1 0 230 0 4 0 4,000 1,200 1,721 104 633 82 353 1,573 2,611 100 137
2 3 Wet 3,020 715 0 0 0 0 0 0 4,000 1,200 1,819 112 590 138 208 1,361 3,734 0 0
2 3 Wettest 3,804 795 3 1 400 100 4 2 4,000 1,200 1,634 97 700 475 122 1,590 4,599 350 154
5 3 Driest 299 0 0 0 0 0 0 0 4,000 1,200 1,833 114 700 698 145 1,799 299 0 363
5 3 Dry 1,769 0 0 0 0 0 0 0 3,972 1,188 1,825 113 514 143 98 1,227 1,769 0 0
5 3 Median 2,282 106 0 0 0 0 0 0 4,000 1,200 1,721 104 633 521 136 1,714 2,387 0 278
5 3 Wet 2,970 780 0 0 0 0 0 0 4,000 1,200 1,819 112 590 138 193 1,362 3,750 0 0
5 3 Wettest 3,358 757 0 0 0 0 0 0 4,000 1,200 1,634 97 700 642 446 1,990 4,115 0 554
6 3 Driest 299 0 0 0 0 0 0 0 4,000 1,200 1,833 114 700 703 156 1,796 299 0 360
6 3 Dry 1,761 0 0 0 0 0 0 0 3,973 1,188 1,825 113 524 143 107 1,230 1,761 0 0
6 3 Median 2,273 109 0 0 0 0 0 0 4,000 1,200 1,721 104 633 527 143 1,712 2,381 0 276
6 3 Wet 2,970 763 0 0 0 0 0 0 4,000 1,200 1,819 112 590 138 209 1,363 3,733 0 0
6 3 Wettest 3,369 729 0 0 0 0 0 0 4,000 1,200 1,634 97 700 642 454 1,982 4,098 0 546
10 3 Driest 300 0 0 0 0 0 0 0 4,000 1,200 1,833 114 700 698 144 1,798 300 0 362
10 3 Dry 1,771 0 0 0 0 0 0 0 3,974 1,188 1,825 113 510 143 98 1,223 1,771 0 0
10 3 Median 2,284 102 0 0 0 0 0 0 4,000 1,200 1,721 104 634 521 137 1,716 2,385 0 280
10 3 Wet 2,971 777 0 0 0 0 0 0 4,000 1,200 1,819 112 591 138 195 1,364 3,748 0 0
10 3 Wettest 3,362 762 0 0 0 0 0 0 4,000 1,200 1,634 97 700 642 437 1,981 4,124 0 545
11 3 Driest 300 0 0 0 0 0 0 0 4,000 1,200 1,833 114 700 703 155 1,796 300 0 360
11 3 Dry 1,759 0 0 0 0 0 0 0 3,974 1,188 1,825 113 525 143 107 1,230 1,759 0 0
11 3 Median 2,268 110 0 0 0 0 0 0 4,000 1,200 1,721 104 633 527 146 1,715 2,378 0 279
11 3 Wet 2,966 760 0 0 0 0 0 0 4,000 1,200 1,819 112 592 138 214 1,368 3,726 0 0
11 3 Wettest 3,359 738 0 0 0 0 0 0 4,000 1,200 1,634 97 700 642 455 1,983 4,097 0 547
12 3 Driest 300 0 0 0 0 0 0 0 4,000 1,200 1,833 114 700 703 155 1,795 300 0 359
12 3 Dry 1,759 0 0 0 0 0 0 0 3,974 1,188 1,825 113 525 143 107 1,230 1,759 0 0
12 3 Median 2,278 103 0 0 0 0 0 0 4,000 1,200 1,721 104 633 527 143 1,712 2,380 0 276
12 3 Wet 2,984 759 0 0 0 0 0 0 4,000 1,200 1,819 112 588 138 200 1,353 3,743 0 0
12 3 Wettest 3,398 717 0 0 0 0 0 0 4,000 1,200 1,634 97 700 642 436 1,964 4,115 0 528
RDD/070370001 (NLH2187.xls)

TABLE 1-1
PondVolume
Scenario
Demand
Scenario
YearType
DPVolume
MLPVolume
DPDays5%
DPandMLP
Days5%
DPVolume
Temp
MLPVolume
Temp
DPDays
Temp
MLPDays
Temp
GeysersT1
Demands
UrbanDemands
LagunaT1
Demands
NorthCounty
Demands
GeysersT2
Demands
LagunaT2
Demands
CarryOver
Storage(MG)
PeakStorage
(MG)
TotalDischarge
(MG)
volumeover5%
Additional
Storage
Required(MG)
2 4 Driest 247 0 0 0 0 0 0 0 4,000 1,200 1,833 114 1,453 148 10 1,229 247 0 0
2 4 Dry 1,132 0 0 0 0 0 0 0 3,952 1,180 1,820 113 1,283 143 10 1,228 1,132 0 0
2 4 Median 1,634 53 0 0 49 0 1 0 4,000 1,200 1,721 104 1,901 82 10 1,430 1,687 0 0
2 4 Wet 2,583 412 0 0 0 0 0 0 3,964 1,188 1,816 112 1,609 138 -2 1,331 2,995 0 0
2 4 Wettest 3,054 357 1 0 100 0 1 0 4,000 1,200 1,634 97 2,207 341 -22 1,572 3,411 100 136
5 4 Driest 244 0 0 0 0 0 0 0 4,000 1,200 1,833 114 1,442 148 8 1,224 244 0 0
5 4 Dry 1,140 0 0 0 0 0 0 0 3,949 1,181 1,821 113 1,267 143 9 1,227 1,140 0 0
5 4 Median 1,593 48 0 0 0 0 0 0 4,000 1,200 1,721 104 1,842 188 8 1,464 1,641 0 28
5 4 Wet 2,559 465 0 0 0 0 0 0 3,960 1,188 1,816 112 1,591 138 -4 1,331 3,023 0 0
5 4 Wettest 2,932 405 0 0 0 0 0 0 4,000 1,200 1,634 97 2,263 373 -23 1,644 3,336 0 208
6 4 Driest 243 0 0 0 0 0 0 0 4,000 1,200 1,833 114 1,457 148 10 1,229 243 0 0
6 4 Dry 1,130 0 0 0 0 0 0 0 3,951 1,181 1,820 113 1,284 143 10 1,228 1,130 0 0
6 4 Median 1,582 50 0 0 0 0 0 0 4,000 1,200 1,721 104 1,962 82 10 1,466 1,632 0 30
6 4 Wet 2,551 454 0 0 0 0 0 0 3,957 1,188 1,816 112 1,609 138 -2 1,332 3,006 0 0
6 4 Wettest 2,932 392 0 0 0 0 0 0 4,000 1,200 1,634 97 2,264 373 -22 1,639 3,324 0 203
10 4 Driest 245 0 0 0 0 0 0 0 4,000 1,200 1,833 114 1,441 148 8 1,224 245 0 0
10 4 Dry 1,141 0 0 0 0 0 0 0 3,948 1,181 1,821 113 1,266 143 9 1,227 1,141 0 0
10 4 Median 1,594 50 0 0 0 0 0 0 4,000 1,200 1,721 104 1,944 82 8 1,466 1,644 0 30
10 4 Wet 2,567 457 0 0 0 0 0 0 3,958 1,188 1,816 112 1,591 138 -4 1,331 3,024 0 0
10 4 Wettest 2,937 397 0 0 0 0 0 0 4,000 1,200 1,634 97 2,265 373 -23 1,645 3,334 0 209
11 4 Driest 244 0 0 0 0 0 0 0 4,000 1,200 1,833 114 1,456 148 10 1,229 244 0 0
11 4 Dry 1,131 0 0 0 0 0 0 0 3,951 1,181 1,820 113 1,283 143 10 1,228 1,131 0 0
11 4 Median 1,582 47 0 0 0 0 0 0 4,000 1,200 1,721 104 1,963 82 10 1,466 1,630 0 30
11 4 Wet 2,553 449 0 0 0 0 0 0 3,958 1,188 1,816 112 1,610 138 -2 1,331 3,003 0 0
11 4 Wettest 2,922 384 0 0 0 0 0 0 4,000 1,200 1,634 97 2,275 379 -22 1,644 3,307 0 208
12 4 Driest 245 0 0 0 0 0 0 0 4,000 1,200 1,833 114 1,456 148 10 1,229 245 0 0
12 4 Dry 1,132 0 0 0 0 0 0 0 3,952 1,180 1,820 113 1,283 143 10 1,228 1,132 0 0
12 4 Median 1,592 51 0 0 0 0 0 0 4,000 1,200 1,721 104 1,950 82 10 1,464 1,643 0 28
12 4 Wet 2,565 446 0 0 0 0 0 0 3,955 1,187 1,815 112 1,604 138 -2 1,332 3,011 0 0
12 4 Wettest 2,959 382 0 0 0 0 0 0 4,000 1,200 1,634 97 2,246 373 -22 1,635 3,341 0 199
RDD/070370001 (NLH2187.xls)

TABLE 1-1
PondVolume
Scenario
Demand
Scenario
YearType
DPVolume
MLPVolume
DPDays5%
DPandMLP
Days5%
DPVolume
Temp
MLPVolume
Temp
DPDays
Temp
MLPDays
Temp
GeysersT1
Demands
UrbanDemands
LagunaT1
Demands
NorthCounty
Demands
GeysersT2
Demands
LagunaT2
Demands
CarryOver
Storage(MG)
PeakStorage
(MG)
TotalDischarge
(MG)
volumeover5%
Additional
Storage
Required(MG)
6 5 Driest 303 0 0 0 0 0 0 0 4,400 1,000 1,833 455 0 875 139 1,991 303 0 555
6 5 Dry 1,579 0 0 0 0 0 0 0 4,400 1,000 1,833 455 0 148 218 1,425 1,579 0 0
6 5 Median 2,359 168 0 0 0 0 0 0 4,400 1,000 1,721 416 0 82 559 1,734 2,527 0 298
6 5 Wet 3,053 835 0 0 0 0 0 0 4,342 981 1,788 441 0 105 259 1,461 3,888 0 25
6 5 Wettest 3,416 825 0 0 0 0 0 0 4,400 1,000 1,634 389 0 642 526 2,086 4,240 0 650
10 5 Driest 328 0 0 0 25 0 25 0 4,400 1,000 1,833 455 0 839 134 1,966 328 0 530
10 5 Dry 1,589 0 0 0 0 0 0 0 4,400 1,000 1,833 455 0 148 198 1,421 1,589 0 0
10 5 Median 2,373 149 0 0 0 0 0 0 4,400 1,000 1,721 416 0 82 556 1,747 2,522 0 311
10 5 Wet 3,025 866 0 0 0 0 0 0 4,354 981 1,788 442 0 110 243 1,460 3,891 0 24
10 5 Wettest 3,388 883 0 0 0 0 0 0 4,400 1,000 1,634 389 0 642 511 2,086 4,271 0 650
RDD/070370001 (NLH2187.xls)

Attachment 2
Volume and Discharge Plots

WB012007018RDD_02 (2/22/07)
TOTAL STORAGE AND DISCHARGE - POND SCENARIO 2, DEMAND SCENARIO 2, DRIEST YEAR TYPE
TOTAL STORAGE AND DISCHARGE - POND SCENARIO 2, DEMAND SCENARIO 2, DRY YEAR TYPE
TOTAL STORAGE AND DISCHARGE - POND SCENARIO 2, DEMAND SCENARIO 2, MEDIAN YEAR TYPE

WB012007018RDD_02 (2/22/07)
TOTAL STORAGE AND DISCHARGE - POND SCENARIO 2, DEMAND SCENARIO 2, WET YEAR TYPE
TOTAL STORAGE AND DISCHARGE - POND SCENARIO 2, DEMAND SCENARIO 2, WETTEST YEAR TYPE

WB012007018RDD_02 (2/22/07)
DEMAND REDUCTIONS - POND SCENARIO 6, DEMAND SCENARIO 2, DRIEST YEAR TYPE
DEMAND REDUCTIONS - POND SCENARIO 6, DEMAND SCENARIO 2, DRY YEAR TYPE

WB012007018RDD_02 (2/22/07)
DEMAND REDUCTIONS - POND SCENARIO 6, DEMAND SCENARIO 2, MEDIAN YEAR TYPE

WB012007018RDD_02 (2/22/07)
DEMAND REDUCTIONS - POND SCENARIO 6, DEMAND SCENARIO 2, WET YEAR TYPE
DEMAND REDUCTIONS - POND SCENARIO 6, DEMAND SCENARIO 2, WETTEST YEAR TYPE

WB012007018RDD_02 (2/22/07)

IRWP Seasonal Storage Project Water Reuse System Storage Model

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