Detailed estimation of desalination system cost using computerized cost
projection tools
Robert P. Huehmer
CH2M HILL, Desalination Global Technology Leader, Englewood, Colorado, USA
Abstract
For planners of new desalination plants, evaluating the potential capital and operating costs
associated with the plant is a major concern. There exists a large volume of empirical data in
the published literature. This data possesses significant scatter in terms of the costs of on a
regional, capacity and year of construction. Several commercially available and/or non-
proprietary desalination cost models currently exist in the desalination market. The cost
models most frequently quoted in the grey literature are WTCost© and cost curves contained
in the USBR publication entitled “Desalting Handbook for Planners”. Other models include
Global Water Intelligence Desalination SWRO Cost Estimator, Desalination Economic
Evaluation Program (DEEP), AUDESSY, WRA models and the Kawamura model. In this
paper, the authors conduct a comparison of the results of WTCost II, GWI SWRO Cost
Estimator and CH2M HILL’s proprietary cost model to identify the similarities, weaknesses
and strengths of the models. The capital cost of several recent desalination plants, over a
range of capacities, are compared to the cost projects made by the models. In general, the
authors conclude that the models are adequate for a Class 5 cost estimate as defined by the
Association for the Advancement of Cost Estimating (AACE). The author also presents
insights into the future of cost estimating.
1. Introduction
In developing business cases for desalination, project planners and desalination engineers are
required to provide cost estimates on a regular basis.There is signific-ant variability in the
costs provided, depending upon the approach utilized. Of particular concern, is the lack of
standardization in the reporting of both CAPEX and OPEX associated with seawater
desalination plants. In the generation of capital cost estimates, one of several approaches is
typically utilized, as illustrated in Table 1.
Table 1. Cost Estimating Approaches utilized in seawater desalination
The “swag” – a value provided by a knowledgeable individual. Often surprisingly accurate, it
is based upon experience and historical costs.
Type Tool
“The Swag” Call an expert
Empirical Models
Desalination Handbook for Planners
Literature Cost Curves
Cost data bases
Parametric Models
GWITM
WT Cost IITM
CH2M HILL CPESTM
Factored Cost Models Material take-offs for major items, with factors applied
Material Take-Off Detailed material take-off of design drawings using Timberline
TM or
other software and experienced estimators
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Empirical Cost Models – Empirical cost models are based on statistical analysis and curve-
fitting of historical data, typically with capacity utilized as the key variable.
Parametric Cost Models – A parametric model utilizes a number of variables to provide, using
typically a multivariate empirical or hybrid empirical/factored approached, to provide greater
specificity for various applications than a parametric cost model.
Factored Cost Models – A factored cost model typically utilizes capital cost estimates for the
major equipment, and then adds factors to account for the remainder of the capital costs.Very
commonly used in water treatment and in oil and gas sectors. Requires some design
development in order to conduct, and typically requires vendor quotations.
Material Take-off – Once significant design activity has occurred, estimators can begin
counting components and provide schedules of materials, along with typical costs or
quotations for each line item on the schedules. While most accurate, the design must be well
developed. Most commonly used in early stage development are empirical and parametric
models. The Association for the Advancement of Cost Engineering (AACE) provides
recommendations on the level of accuracy that may be assigned to an estimate at any given
stage of a project. Figure 1 provides details of estimate uncertainty, as well as the typical level
of design detail provided.
1.1 Estimating Desalination Cost
There are three types of costs associated with desalination typically mentioned in the
literature. These include the capital cost (CAPEX), operating cost (OPEX) and the Total
Water Cost (TWC). Each are described below:
1.1.1 Capital Cost
Often referred to as Capital Expenditure or CAPEX, it describes the capital expenditures
required to complete the project. Capital costs for a desalination plant typically are associated
with the construction of the over-all infrastructure, and include the following cost
components:
• Intake construction (may include wells, open intakes, sub-surface intakes)
• Brine disposal (may include outfall, injection wells, blending, evaporation ponds)
• Raw water conveyance
• Pretreatment
• Desalination (including pumping, membrane racks, energy recovery etc.)
• Post-treatment
• Pretreatment residuals management
• Water storage and conveyance
• Procurement of land
• Obtaining right-of-ways
• Permitting
• Engineering
• Escalation
• Contractor overhead and profit
• Taxes
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Fig. 1. Construction Cost Estimate Accuracy Ranges (adapted from [1]).
1.1.2 Operating Cost
Operating costs, which are recurring costs, typically on an annual- or annual allotment-basis
include, but are not limited to, the following cost components
• Operating and Maintenance (O&M) Labor
• Energy Consumption
• Chemicals for pre-treatment, scale inhibitors, cleaning etc.
• Maintenance parts
• Insurance
• Membrane replacement (typically annualized)
• Cartridge filter replacement
• Laboratory analysis and monitoring
• Regulatory compliance
1.1.3 Total Water Cost
Total Water Cost (TWC) is frequently quoted in desalination industry literature as a common
comparison between projects. TWC has been defined as the annual operating cost + the
annualized capital cost (or debt service).
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2. Desalination cost modelling
2.1 Seawater desalination
Numerous researchers have published capital cost figures for seawater desalination
plants with associated empirical cost models. These figures are typic-ally used to develop
empirical cost estimates typically utilized during the planning stage of a project. One of the
most commonly cited cost models was developed as part of United States Bureau of
Reclamation funding and is reported on by Watson et al. [2]. The model, published in the
“Desalting Handbook for Planners” provides cost curves for nanofiltration, brackish reverse
osmosis and seawater reverse osmosis desalination systems, based on historical data.
Additionally, the model contains empirical curves for thermal processes. A number of
alternative empirical cost models have been reported in the literature [3], [4], [5] and [6].
These models generally use either a polynomial equation, log-log or semi-log model for the
regression analysis.
Wittholz et al. [4] analyzed desalination cost data collected from a wide variety of sources
including surveys, reports, and published journals spanning a period of 35 years. Cost data
was normalized to 2006 using cost indices. Using 90 sets of BWRO data and 112 sets of
SWRO data, linear regression using least squares was completed to fit data to power law. The
resulted empirical correlation is shown in Equation 1.
ln ( Capital cost) = m x ln (Capacity) + constant Equation 1
Other researchers have used similar regression analyses to evaluate costs of reverse osmosis
desalination plants. Zhou and Tol [3] used regression analysis to construct a total water cost
(TWC) model from 2,514 data points.The model derived was in general form:
F(Unit Cost) = G(Capacity, Year, Type) Equation 2
Both log-log and semi-log forms were analyzed. For a log-log model, the regression analysis
accomplished a fit with a R2 of 0.72. The final model form developed was:
ln(cost) = alpha x ln(capacity) + constant + dummies Equation 3
Kawamura [5] has developed a series of cost correlations for estimating capital cost of various
water treatment processes, including desalination. The cost figures utilize simple correlations
based upon historical data. A capital and construction cost curves are provided for SWRO;
O&M cost curves. The source of the data is not detailed by the author, but is understood to
represent his personal experience. Dore [6] used an auto-aggressive integrated moving
average model (ARIMA) to forecast the change in desalination unit costs over time. The
model was applied to historical desalination unit cost data. It was concluded that the 2004
total water cost for desalinated water is between $0.25/m3 and $0.71/m3. A comparison of
these models is presented in Table 2.
Typical comparison of several of these models, along with the GWI SWRO Cost Estimator
are shown in Figure 2 for seawater applications.
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Table 2. Empirical Capital Cost Models for Reverse Osmosis.
Zhou and Tol [3]
(Seawater)
Watson et al [2]
(SWRO)
Wittholz et al.
[4] (SWRO)
Dore [6] Kawamura
[5]
Type Log-log Power Log-log ARIMA Power
Year 2005 2003 2008 2005 2009
Equation ln(cost) = m x
ln(capacity) +
constant + dummies Cost = M(capacity)
B
ln(cost) = m x
ln(capacity) +
constant
(1 – B)Yi = -
0.31149899 + vi
– 0.80700050 vi-1
Cost =
M(capacity)B
Units m
3/d m
3/d m
3/d m
3/d MGD
N 1514 Not reported 112
R2
n.a. 0.907 n.a.
M Not reported 0.81
Constant Not reported 4.07
B n.a. -
Fig. 2. Capital Cost Curves for Seawater Reverse Osmosis Plants.
2.3 Total Water Cost Estimates
Many of the desalination projects located around the world are delivered as Build-Own-
Operate with a set cost for water delivered. In many instances, the capital cost and operating
cost breakdowns are not reported for these facilities. Cost data is commonly published,
particularly for seawater desalination, in terms of the Total Water Cost (TWC) which includes
that annualized capital cost and the annual operating cost. The TWC is typically reported in
terms of cost per unit volume (for instance $/m3) of finished water produced. As a result of
local factors, such as cost of labor, materials and energy, proponents may elect to increase or
decrease capital cost expenditures, and offset that change with adjustments to annual
operating cost. It is less common to publish total water cost data on brackish water,
nanofiltration or tertiary reuse desalination systems. This is largely a factor of the differences
in delivery methods utilized. Seawater desalination systems are much more likely to be
delivered using an at risk approach.
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A recent analysis, conducted using data published in Water Desalination Report, was
conducted.
Table 3. Total Water Cost (TWC) for seawater desalination facilities [8].
Total Water Cost Capacity
Plant Year $/m3 $/kgal
m3/d mgd Process
Santa Barbara California 1991 $1.22 $4.62 25,360 6.7 SWRO
Bahamas 1996 $1.28 $4.84 9,840 2.6 SWRO
Dhekelia Cyprus 1997 $1.19 $4.50 40,000 10.6 SWRO
Larnaca Cyprus 1999 $0.76 $2.88 54,000 14.3 SWRO
Taweelah C UAE 2000 $0.72 $2.73 325,000 85.9 SWRO
Ashkelon Israel 2001 $0.52 $1.97 326,144 86.2 SWRO
Carboneras Spain 2002 $0.57 $2.16 120,000 31.7 SWRO
Point Lisas Trinidad 2002 $0.71 $2.69 119,000 31.4 SWRO
Tuas Singapore 2003 $0.48 $1.82 136,360 36 SWRO
Tampa Bay Florida 2004 $0.55 $2.08 95,000 25.1 SWRO
Arzew Algeria 2005 $0.90 $3.41 86,000 22.7 SWRO
Beni Saf Algeria 2005 $0.70 $2.65 150,000 39.6 SWRO
Cap Djinet Algeria 2005 $0.73 $2.76 100,000 26.4 SWRO
Douaouda Algeria 2005 $0.75 $2.84 120,000 31.7 SWRO
Fukuoka Japan 2005 $1.84 $6.96 50,000 13.2 SWRO
Hamma Algeria 2005 $0.82 $3.10 200,000 52.8 SWRO
Los Angeles California 2005 $0.82 $3.10 94,625 25 SWRO
Palmachim Israel 2005 $0.78 $2.95 110,000 29.1 SWRO
Skikda Algeria 2005 $0.74 $2.80 100,000 26.4 SWRO
West Basin California 2005 $0.64 $2.42 37,850 10 SWRO
Blue Hills Bahamas 2006 $1.30 $4.92 27,250 7.2 SWRO
Perth Australia 2006 $0.75 $2.84 143,700 38 SWRO
Shuqaiq Saudi Arabia 2006 $1.03 $3.90 213,475 56.4 SWRO
Tampa Bay Florida 2006 $0.84 $3.18 95,000 25.1 SWRO
Carlsbad California 2007 $0.77 $2.91 189,250 50 SWRO
Chennai India 2007 $1.10 $4.16 100,000 26.4 SWRO
Dhekelia Cyprus 2007 $0.88 $3.33 40,000 10.6 SWRO
Gold Coast Australia 2007 $1.09 $4.13 133,000 35.1 SWRO
Santa Barbara California 1991 $1.22 $4.62 25,360 6.7 SWRO
Hadera Israel 2007 $0.60 $2.27 330,000 87.2 SWRO
Malta 2007 $0.72 $2.73 20,000 5.3 SWRO
Sur Oman 2007 $1.20 $4.54 80,200 21.2 SWRO
Tianjin China 2007 $0.95 $3.60 150,000 39.6 SWRO
Ad Dur Bahrain 2008 $0.93 $3.52 218,000 57.6 SWRO
Ashkelon Israel 2008 $0.78 $2.95 326,144 86.2 SWRO
El Tarf Algeria 2008 $0.89 $3.37 50,000 13.2 SWRO
Hadera Israel 2008 $0.86 $3.26 330,000 87.2 SWRO
Jeddah Barge Saudi Arabia 2008 $2.27 $8.59 52,000 13.7 SWRO
Mactaa Algeria 2008 $0.56 $2.12 500,000 132.1 SWRO
Oued Sebt Algeria 2008 $0.68 $2.57 100,000 26.4 SWRO
Palmachim Israel 2008 $0.86 $3.26 83,270 22 SWRO
Ras Azzour Saudi Arabia 2008 $1.09 $4.13 1,000,000 264.2 Hybrid
Taunton Massachusetts 2008 $1.53 $5.79 18,925 5 SWRO
Tenes Algeria 2008 $0.59 $2.23 200,000 52.8 SWRO
Tuas Singapore 2008 $0.57 $2.16 136,360 36 SWRO
The total water cost data is plotted in Figure 3. The data clearly indicates a decrease in Unit
Total Water Cost as the capacity of the facility increases.
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Fig. 3. Unit Total Water Cost upon published data in [8].
3. Parametric cost estimating
3.1 Commercially Available Desalination Cost Estimating Models
Several commercially available and/or non-proprietary desalination cost models currently
exist in the market place. The cost models most frequently quoted in the grey literature are
WTCost© and cost curves contained in the USBR publication entitled “Desalting Handbook
for Planners”. Other models include Global Water Intelligence Desalination SWRO Cost
Estimator, Desalination Economic Evaluation Program (DEEP), AUDESSY, WRA models
and the Kawamura model. Additionally, USEPA is currently working on new cost estimating
guidelines to replace the guidelines developed in 1979 and updated in 1992; it has not yet
been released to the public. This section focuses on capital cost comparisons between
WTCost II, GWI SWRO Cost Estimator and CH2M HILL’s proprietary cost model
WTCost II is based upon research funding provided by the United States Bureau of
Reclamation, where a desalination cost model was developed using Microsoft Excel as the
platform. The model was subsequently commercialized as WTCost II, by I. Moch &
Associates, in conjunction with W. R. Querns & Associates and Boulder Research
Enterprises. The model permits the evaluation and comparison of processes employing
reverse osmosis/nanofiltration, multi stage flash evaporation, multi-effect distillation, vapor
compression, microfiltration/ ultrafiltration, electrodialysis and ion exchange. This program,
utilizing proprietary code is, according to USBR documentation, based upon 1979 USEPA
water treatment cost estimates (1978 dollars) and the 1992 Quasim updates to the 1979 costs
as the basis. Processes not included in the 1979 or 1992 updates are estimated from the
authors’ experience and manufacturers’ estimates. The majority of the program is based on
applicable flows between 1 and 200 MGD. There has been some recent work incorporating
smaller flows of 2,500 gpd to 1 MGD.
Global Water Intelligence (GWI) has released a web-based cost model called the
Global Water Intelligence Desaldata.com SWRO cost estimator. This online tool is a
proprietary model utilized to estimate the capital cost of a SWRO desalination plant. The
model includes no documentation regarding the specific correlations utilized. The model uses
data from real projects, which was then normalised prior to factoring in capex options such as
intake and permitting. It does not account for product water storage and distribution costs.The
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model uses the following user inputs seawater TDS, seawater temperature, degree of
pretreatment required, intake/outfall requirements, second pass, remineralization, permitting
effort and country.
GWI reports that it is valid over a range of flows between 250 m3/d to 250,000 m3/d. No
representation is made regarding the confidence interval for the capital cost estimate.
CH2M HILL has developed a model known as CH2M HILL Parametric Cost Estimating
System or CPES. The model consists of a mass balance tool and series of approximately 60
different unit process parametric models. The outputs of the appropriate parametric models
and then utilized in a factored approach to develop the final capital cost values.
A comparison of the functionality of the models is contained in Table 4. While all three
models are capable of providing CAPEX estimates, greater functionality is provided by
WTCost II and CPES over the GWI SWRO Cost Estimator.
On order to compare the cost estimating tools, cost estimates for a 30,000 m3/d seawater
desalination plants using beach-wells and waste injection wells were prepared. Prior to
beginning the estimate, the cost databases for WTCost II and CPES were updated for the
latest Engineering News Record indices. Table 5 summarizes the results. The values range
between $1066 to $1400 per metre cubed of capacity.
On review of the key differences in the model, GWI Cost Estimator does not provide
estimates for wells, and instead assumes open intakes and outfalls. As a result, it does not
provide accurate costs for pretreatment, and likely underestimates the cost of the injection
wells in particular. These values seem to offset each other. While the model remains a black-
box housed on the GWI servers, it is difficult to determine the specifics of the estimate.
Likewise, as no materials list is provided by WTCost II, it is difficult to delve into the specific
details of the cost estimate. Nor does the model allow us to readily adjust costs for location
factors etc. The costs associated with well development do appear to be low which may result
in the low cost estimate. CPES generates detailed piping calculations, layout and materials
lists, permitting estimating professionals the ability to check and confirm the bottom up cost
estimate as design progresses.
Based upon a recently completed project, the unit capital cost for a 30,000 m3/d plant was
approximately $36,000,000 or a unit cost of $1200/m3. All three tools provided a cost
estimate within +30%; -20% bounds, corresponding with a Class 3 estimate using AACE
guidelines. Under AACE, approximately 35 to 45% of the design development is completed
prior to a Class 3 estimate. These tools, and the inevitable progressions anticipated in the
future, are good tools in predicting costs associated with seawater desalination projects.
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Table 4. Comparison of Computerized Cost Model Features.
Model Features GWI SWRO
Cost Estimator WTCost II CH2M HILL CPES
Type Parametric
Model
Hybrid
Parametric/
Factored
Hybrid
Parametric/
Factored
Computer Based No. Web-based Yes Yes
Applicability
Brackish Water
Seawater
Tertiary Reuse
No
Yes
No
Yes
Yes
Yes
Yes
Yes
Yes
Adjustable Permeate Quality No No Yes
Input data from Projections No Yes Yes
Location Adjustment Factors Yes No Yes
Configurable Cost Database No Yes Yes
Variability Raw Water Quality Yes Yes Yes
Preliminary Equipment List No No Yes
Motor Schedule No No Yes
Intake/Outfall Yes Yes Yes
Different process trains No Yes Yes
Area Estimate No No Yes
Capital Cost Estimate Yes Yes Yes
Operating Cost Estimate No Yes Yes
Total Water Cost Estimate No Yes Yes
Publicly Available Yes Yes Proprietary
Table 5. Comparison of CAPEX estimates using computerized Cost Estimating Tools.
GW
I
WTCost II CH2M HILL CPES
Capacity 30,000 30,000 30,000
CAPEX ($) $41,000,000 $32,000,000 $42,000,000
Unit Cost ($/m3) $1366/m
3 $1066/m
3 $1400/m
3
Platform Web-based MS Access w/VB MS Excel w/VB
4. CH2M HILL Parametric Cost Estimating System (CPES)
CPES is a cost estimating system that interfaces reverse osmosis projection software, mass-
balance generator, cost data base and Computer Aided Design (CAD) software into a system
to provide conceptual cost estimates. Based on an EXCEL platform, users set-up the basic
plant configuration and conduct RO projections using the embedded Visual Basic code, which
includes modules for energy recovery devices. The resultant mass-balances and design criteria
are used for the basis of generating a high-level material take-off and cost estimates. A basic
schematic of the work-flow is shown in Figure 4.
Dimensions of the entire system, including pipe length, pipe diameters and other major
components are calculated. These dimensions are then exported to a CAD platform to develop
plant lay-out (Figure 5) and isometric drawings (Figure 6).
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Fig. 4. Flow-chart for the CPES estimating system.
Fig. 5. Plant layout for a Reverse Osmosis system generated by CPES.
Fig. 6. Isometric drawing for a Reverse Osmosis system generated by CPES.
Cost estimates created by CPES have been benchmarked against bid prices for a number of
projects. The estimates, shown in Table 6, show that cost estimates generated by CPES are
well within the AACE Class 4 cost estimate uncertainty (as shown in Figure 1), with most
values corresponding to a Class 2 cost estimate – with significantly lower investment into
engineering for each project to determine the projected cost.
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Table 6. Comparison of CAPEX estimates using CPES versus bid prices.
5. Design Driven Cost Estimating System
The development and accuracy of CPES provides insight into the total power of future cost
estimating systems. A number of companies have developed internal proprietary programs for
the rapid design development of water treatment systems. USFILTER created an early
prototype of a mass balance solution that selected standard equipment from their product line
to incorporate into their process.
While this program could not conduct balance of plant cost estimating, it did incorporate RO
projection capability and permit rapid development of costs for major process/mechanical
equipment.
Developed independently of USFilter, Glegg Water Conditioning created the Reference
Design program in the 1990s. This program included the functionality of USFilter’s program,
but also was able to automatically generate process & instrumentation drawings, process
mechanical drawings and create accurate material take-offs.
Such tools were developed within the platforms of the era. Figures 7 through 9 shows a
system developed within an AutoCAD platform. Using the tool, very rapid development of a
custom engineered process could be developed. Figure 6 shows a typical input page for an ion
exchange vessel.
With new software such as ASPEN and SmartPlant suite, implementation of Design Driven
estimating systems has become easier and easier, as material take-offs are directly exported
into cost estimating packages. Cost estimates that historically took many weeks to conduct,
with hundreds of engineering hours, can be automated to conduct similar estimates in mere
hours. To date, efforts in seawater desalination have been limited to proprietary developments
within individual organizations. The community would be well-served with a publically
available package to eliminate uncertainty of scope used in current and convention cost
estimates.
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Fig. 7. Input page for an ion exchange vessel as part of an ultrapure water solution.
Fig. 8. P&ID automatically developed from user inputs and system modelling.
References [1] AACE 18-R-87 accessed 8/8/2011 http://www.aacei.org/
[2] Watson et al. (2003). “Desalting Handbook for Planners, 3rd Edition” U.S. Department of the Interior,
Bureau of Reclamation Technical Service Center Water Treatment Engineering and Research Group
Cooperative Assistance Agreement Number: 98-PG-81-0366, Desalination Research and Development Program
Report No. 72 http://www.usbr.gov/pmts/water/media/pdfs/report072.pdf
[3] Zhou, Y., and R. S. J. Tol (2005), Evaluating the costs of desalination and water transport, Water Resour.
Res., 41, W03003, doi:10.1029/2004WR003749
[4] Wittholz, M.K., B.K. O'Neill, et al. (2008). "Estimating the cost of desalination plants using a cost database."
Desalination 229(1-3): 10-20.
[5] Kawamura, S and McGivney, W (2008). Cost Estimating Manual for Water Treatment Facilities. Wiley.
[6] Dore, M.H.I. (2005). "Forecasting the economic costs of desalination technology." Desalination 172(3): 207-
214
[7] Nicot et al (2005) A Desalination Database for Texas Prepared for Texas Water Development Board Under
Contract No. 2004-483-021 Jean-Philippe Nicot, Steven Walden1, Lauren Greenlee2, and John Els
[8] Pankratz, Tom. Water Desalination Report (2010).
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