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1
2Sandia National Laboratory 3Assistant Professor, College of Tech. and Innovation
Senior Sustainability Scientist, Global Inst. of Sustainability 1Arizona State University
480-727-5123
Benjamin L. Ruddell 1,3
Acknowledging:
Elizabeth A. Adams1
Seth Herron1
Yueming Qiu1
Vincent C. Tidwell2
Sandia National Laboratories Staff & Data
Water Resource Impacts Embedded in the Western US Electrical Energy Trade; Current Patterns and Adaptation to Future Drought
WRRC
University of Arizona
10 October 2013
Dalin et al., 2012
(change in) Global Virtual Water Trade
A Signature of (increasingly)
Complex Water-Economy Interactions
Hoekstra and Chapagain (2007)
Virtual Water is THE major
adaptive mechanism to water
scarcity worldwide… just at
trade in products derived with
the service of scarce resources
is the major adaptive
mechanism to ALL types of
resource scarcity. This is a
hydrologist’s way of
understanding economic trade.
Net Systemic Impact (footprint) of a Process, E: the sum of the
Direct (U) and indirect (V) network impacts of a process on a stock
of interest, conditioned on a local/external (l/x) boundary
“Virtual Water” (Allan, 1993) is a special single-type network case of
ERA. ERA is related to Input-Output and Life Cycle Analysis, which
are also network concepts.
The foundation of ERA is the partial
embedded resource impact Vp ; the
sum across intermediaries k and rk
is the net indirect impact V
Embedded Resource Impact Accounting (ERA): A network theory for complex CNH’s (Liu et al., 2007)
l x l l x x
IN OUT IN OUTE U U V V V V
Western Power Grid: State Level Data
•High prices = high demand, limited supply, high costs of electricity generation •Low water consumption intensity = water scarcity/conservation
Water Intensity
(gal/MWh)
Price
($/MWh)
New Mexico 437.25 $103.56
Utah 411.77 $81.35
Wyoming 384.17 $85.57
Colorado 352.66 $100.26
Nevada 349.23 $80.10
Montana 297.32 $81.57
Arizona 183.81 $86.23
California 129.69 $125.26
Idaho 83.31 $62.91
Oregon 82.04 $67.65
Washington 52.52 $61.65
4
Water intensities calculated using Sandia National Laboratory Energy/Water Nexus Group data, for year 2009, of total electricity production reported by plants and estimated net water consumption at each power plant within each state (Tidwell et al. 2012, EPA 2010, EIA 2005, Kenny et al. 2009, Macknick et al. 2011, Solley et al.1995) Prices are 2009 averages of retail electric utility prices for all utilities within each state obtained from US Energy Information Administration (EIA 2011a)
Net Interstate Trade,
(MWh)
Gross Export,
(MWh)
Gross Export
Coefficient, (%)
Arizona 31,685,245 31,685,245 31.3%
Montana 5,775,543 5,775,543 5.7%
New Mexico 15,700,958 15,700,958 15.5%
Nevada 1,655,392 1,655,392 1.6%
Oregon 5,079,110 5,079,110 5.0%
Utah 12,389,184 12,389,184 12.2%
Washington 2,117,039 2,117,039 2.1%
Wyoming 26,882,529 26,882,529 26.5%
Gross Import,
(MWh)
Gross Import
Coefficient, (%)
California (84,137,000) 84,137,000 83.1%
Colorado (4,815,000) 4,815,000 4.8%
Idaho (12,333,000) 12,333,000 12.2%
5
•Trade data is for 2009
using EIA data tables
•Net Trade is taken as
production –
consumption within
each state
•Total exports must
equal total imports
summed across
network
•Assumed 1%
reduction in exports
due to export to
neighboring grid(s)
(EIA 2011a, EIA 2011b)
Scott and Pasqualetti (2010) Reported Gross export of electricity from Arizona = 30,750,700 MWh.
Transfer quantities between states = (Exporting state Net Trade) * (Importing state Import Coeff)
Western Power Grid: Interstate Trade Estimation
Virtual Water Embedded in the Electrical Power Grid in the Western USA: Outsourcing Water Impact via Power
Ruddell et al., in review
CO 5 Mgal
WY 6,363 Mgal
ID
CO CA
MT 3,353 Mgal
ID
CA
CO
CO 16,230 Mgal
CA 20,289 Mgal
868 Mgal
3,713 Mgal
4,476 Mgal
UT 11,359 Mgal
NM 9,465 Mgal AZ
13,498 Mgal
11,445 Mgal
ID 14Mgal
CA
ID CO
CA
CO
ID CA ID
CA
CO
ID
CO CA
CO ID
CA
92 Mgal
WA
OR
346 Mgal
51 Mgal
20 Mgal
ID
82 Mgal 1,426 Mgal
209 Mgal
1,258 Mgal
8,579 Mgal
491 Mgal
480 Mgal
70 Mgal
27 Mgal
NV
621 Mgal
243 Mgal
4,238 Mgal
709 Mgal
277 Mgal 4,838
Mgal
836 Mgal
326 Mgal
5,703 Mgal
Em
bed
ded
Wat
er (
Mga
l)
7
A systematic shift of water impacts (and emissions) from California to energy exporters like WY and NM
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
External water embedded in imported electricity (Million embedded gallons)
Internal water embedded in exported electricity (Million embedded gallons)
Internal water embedded in locally consumed electricity (Million embedded gallons)
34%
42%
10% 2%
62% 31%
5%
30% 8%
56%
81%
𝜔𝐿𝑂𝐶𝐴𝐿 𝜔𝐸𝑋𝑃𝑂𝑅𝑇 𝜔𝐼𝑀𝑃𝑂𝑅𝑇
Martin and Ruddell [2012]
A risky strategy for CA, given
the CO river drought and
Suppliers’ junior water rights.
USBR, 2012
Water Savings through trade in electricity on the power grid
8
U (Mgal) V (Mgal) E (Mgal) U' (Mgal) RS (Mgal) RS (%) Actual Actual U + V If-local U' - E RS/U' Arizona 19322 -5824 13498 13498 0 0
California 20289 25703 45992 31200 -14792 -47%
Colorado 16230 1471 17701 17928 227 1%
Idaho 868 3768 4636 1896 -2740 -145%
Montana 5070 -1717 3353 3353 0 0
New 16330 -6865 9465 9465 0 0
Nevada 12023 -578 11445 11445 0 0
Oregon 4129 -417 3713 3713 0 0
Utah 16461 -5102 11359 11359 0 0
Washington 4587 -111 4476 4476 0 0
Wyoming 16690 -10328 6363 6363 0 0
System 132000 0 132000 114695 -17304 -15%
40%
48%
81%
84%
92%
84%
Q=1 for California water resources only
Q=1 for all global water resources
100%
How does the water footprint of California’s energy use change as the network boundaries change?
Adams et al., in review
DI =
Making Sense of Multitype CNH Networks (or, Why Does Virtual Water Flow?)
A derivative of ERA, Dollar Intensities, DI, are defined by the
intersection of three types of networks at a node in the process network:
• Economic Trade in a Good or Service (input/output)
• Exchange of Currency (Dollars) for said Goods and Services
• Water Resource Consumption
This gives systemic impacts (E) and indirect socio-economic valuation
of outsourced impacts (DI) using multitype CNH network analysis
Imagine other types of CNH intersections, like the production of a social
benefit or value instead of electricity…
hint: it’s not gravity…
11
What Explains This Virtual Flow: Dollar Intensity
Retail electricity price.
Function of the
economic market.
Water efficiency
of electricity
generation.
Function of the
current
technology.
Dollar intensity
of the embedded
water
(exists where money flow, trade flow, and resource flow
networks connect at a node in a multitype CNH network)
0.00
50.00
100.00
150.00
200.00
250.00
300.00
350.00
400.00
450.00
500.00
$0.00
$0.50
$1.00
$1.50
$2.00
$2.50 D
oll
ar
Inte
ns
ity o
f W
ate
r E
mb
ed
de
d i
n E
lec
tric
ity (
$U
SD
/ga
l)
Wate
r Inte
nsity
of E
lectric
ity P
rod
uctio
n (g
al/M
Wh
)
89%
-58%
72%
-73%
35% 15% 43%
12% 45%
36% 43%
(Virtual) water flows uphill toward value, in this case $$$
Higher dollar
intensities are
generally associated
with States that have
lower local water
intensities per MWh
Importers generally
see a decrease in
dollar intensity
compared with local
value intensity, and
Exporters generally
see an increase in
dollar intensity
compared with local
value intensity
Water intensity
of electricity
production
(gal/MWh)
DILocal ($/gal)
DIImport ($/gal)
DIExport($/gal)
Figure adapted from Martin and Ruddell [2012]
Kumar and Singh,
2005 found that
arable land
availability, not
water availability
drove production
patterns for water
embedded in
international
agricultural trade.
Modeling Virtual Water Trade: Future Demands and Droughts
Plants grouped into three categories for response to drought
(Harto & Yan, 2011)
– Low risk thermoelectric
– At risk thermoelectric
– Hydroelectric
0
10
20
30
40
50
60
70
AZ CA CO ID MT NM NV OR UT WA WY
exi
stin
g ge
ne
rati
on
cap
acit
y (t
ho
usa
nd
MW
)
Hydro
At Risk
Low Risk
Herron et al., in review
Methods and Assumptions: Generation Options
Import In-state
At risk
Coal NG
Single Cycle
NGCC Nuclear Geothermal
Existing
As is
Surface Water
Potable Ground Water
Agriculture Water
Brackish Ground Water
Waste Water
Effluent
Retrofit
New
Biomass Hydro Wind PV
Low risk
Export
At risk Low risk
Methods and Assumptions: Scenarios
• Maximum Likely scenarios – Current demands vs 2040
projected demands (US EIA, 2013)
– No drought vs full duration and intensity in all states
• Intermediate scenarios – Varying drought duration and
intensity in all states
• Spatially varied scenarios – Drought in Pacific Northwest,
California, Great Basin (NW) vs drought in Upper/Lower Colorado, Rio Grande, Missouri (SE) (Harto & Yan, 2011)
– Varying drought duration and intensity in NW basins, with no drought in SE basins, and vice versa
HUC-2 Basins (Harto & Yan, 2011)
Current Generation Mix
NGCC is most cost effective source. Model replaces expensive natural gas single-cycle plants with NGCC.
NWPP states have
competitive advantage
in NGCC prices
Herron et al., in review
Results: Production MWh
States with high in-state electricity prices and high costs to build new NGCC import (AZ, CA, CO, NV). States with low costs to build new NGCC export (MT, OR, UT, WA).
NGCC power is
increasingly exported
under drought and high
demand
1. Current demand, no drought
2. Current demand, severe drought
3. 2040 demand, no drought
4. 2040 demand, severe drought
Herron et al., in review
Results: Consumption MWh
NGCC or importing always most cost-effective options, regardless of scenario
AZ becomes a
net importer
under drought
and increasing
demand
According to the
model, no new
transmission
capacity is required
to meet these loads
(the model
considers average
not peak loads)
States do not choose to
build renewables in this
model because they are
expensive relative to
NGCC
1. Current demand, no drought
2. Current demand, severe drought
3. 2040 demand, no drought
4. 2040 demand, severe drought
Herron et al., in review
Results: Water Intensity of Power
Drought increases water intensity of in-state power due to hydropower loss. Exported power becomes less water-intense because of expansion of NGCC.
Grid Water
Intensity
Decreases
Herron et al., in review
Results: Water Savings from Trade in Power
Importers save water via states with water efficient production. Savings increase under drought and demand pressure.
1. Current demand, no drought
2. Current demand, severe drought
3. 2040 demand, no drought
4. 2040 demand, severe drought
This current number is
actually negative. In reality CA
buys power from water
inefficient AZ rather than
water efficient OR and WA.
Herron et al., in review
Modeled Dollar Intensity
1. Current demand, no drought
2. Current demand, all drought
3. 2040 demand, no drought
4. 2040 demand, all drought
0
500
1000
1500
2000
2500
CA ID NV CO AZ NM MT UT WY WA OR
Po
we
r C
on
sum
ed
(m
illio
n M
Wh
)
Imports PV Wind Biofuel Geothermal Hydro Nuclear NGCC Natural Gas Coal
Results: Extreme Demand Scenarios 1. 4x demand, no drought
2. 4x demand, severe drought
3. 10x demand, no drought
4. 10x demand, severe drought
By the time demand gets to 4x or 10x of
current, hydropower and at-risk water are
a tiny fraction of generation and the
system is no longer vulnerable to this risk.
NGCC (and renewables?)
dominates, and use little
enough water that no States
run out of local water
resources for power
CA builds locally
instead of
transmitting for
10X
• Interstate trade is primarily West to East, indicating a flow of
embedded water from drier to wetter areas (except KS and OR)
• Local trade is primarily imports of raw materials and agricultural
Network based on the 2007 US
Commodity Flow Survey; watershed
color indicates water stress
(Hoekstra and Mekonnen, 2011)
Virtual Water Trade Network for Flagstaff, AZ
Cities are the hubs of the water
network and they use/outsource water
to obtain what they value (next slide)
Value Intensity of Combined Direct and Indirect Water Use of
Phoenix Area Cities
1
10
100
1000
10000
100000
Core-A Core-B Core-C Core-D Sub-A Sub-BSub-C
Sub-DSub-E
Sub-FFringe-A
Fringe-BFringe-C
Value Intensity of Cities: Total Water Allocation
Population (people/ ac-ft) Gross Revenue ($/ac-ft) Payroll ($/ac-ft)
[#/ac-ft] Population Payroll Revenue
‘Core’ cities are massive net importers
of VW and use far more water than it
appears, including via labor from
bedroom communities. But they
produce even more value because
they specialize in high-value tertiary
and quaternary economic sectors.
Conclusions
• This helps us understand SYSTEM LEVEL sustainability and resilience, and the interaction of economics with water resources.
• Every connection is both a vulnerability and an opportunity.
• Water use is currently increased and shifted to drier and junior water rights States by the electrical power system as a whole
• Large fractions of California’s (and Idaho’s) water use is outsourced
• Most of California’s outsourcing is to CO basin, a built-in conflict
• Future drought and demand will drive a shift to NGCC in locations with relatively low costs; electrical trade and transmission totals increase
• It is possible to handle even large demand increases and severe droughts through system level trade
• Shift to NGCC will dramatically reduce systemic water consumption, with embedded water reductions concentrated in traded power
• We have enough water, and transmission capacity for VW trade, if we use low-cost and low-water generation technologies.
26
References Allan, T. (1993), Fortunately there are substitutes for water: Otherwise our hydropolitical futures would be impossible, paper
presented at Conference on Priorities for Water Resources Allocation and Management, Overseas Dev. Admin., London. Dalin, C., M. Konar, N. Hanasaki, A. Rinaldo, and I. Rodriguez-Iurbe (2012), Evolution of the global virtual water trade network,
PNAS, V.109, No.21, 8353, doi/10.1073/pnas.1203176109. Harto, C. B., & Yan, Y. E. (2011). Analysis of drought impacts on electricity production in the western and Texas interconnections
of the United States. Argonne National Laboratory, Environmental Science Division. Oak Ridge, TN: U.S. Department of Energy.
Hoekstra, A.Y. and A.K. Chapagain (2007), Water footprints of nations: Water use by people as a function of their consumption pattern, Water Resour. Manage., 21, 35-48, doi:10.1007/s11269-006-9039-x.
Hoekstra, A.Y. and Mekonnen, M.M. (2011) Global water scarcity: monthly blue water footprint compared to blue water availability for the world’s major river basins, Value of Water Research Report Series No.53, UNESCO-IHE, Delft, the Netherlands
Konar, M, C. Dalin, N. Hanasaki, A. Rinaldo, and I. Rodriguez-Iturbe (2012), Temporal dynamics of blue and green virtual water trade networks. Water Resour. Res., 48,W07509, doi:10.1029/2012WR011959.
Jianguo Liu , Thomas Dietz, Stephen R. Carpenter, Marina Alberti, Carl Folke, Emilio Moran, Alice N. Pell, Peter Deadman, Timothy
Kratz, Jane Lubchenco, Elinor Ostrom, Zhiyun Ouyang, William Provencher, Charles L. Redman, Stephen H. Schneider, and
William W. Taylor (2007), Science, 1513-1516. [DOI:10.1126/science.1144004]
Martin, E.A. and B.L. Ruddell (2012), Value intensity of water used for electrical energy generation in the Western U.S.; An application of embedded resource accounting. IEEE International Symposium of Systems and Technology, Conference paper. Boston, Mass.
Ruddell, B., E.A. Adams, R. Rushforth, and V.C. Tidwell (2013), Embedded Resource Impact Accounting for Water Resources
Applications, Part 1 and 2, in review.
USBR (2012), Colorado River Basin Water Supply and Demand Study, U.S. Bureau of Reclamation, December 2012.
Water resources are a key element in the global coupled natural-human (CNH) system, because they are tightly coupled with the world’s social, environmental, and economic subsystems, and because water resources are under increasing pressure worldwide. A fundamental adaptive tool used especially by cities to overcome local water resource scarcity is the outsourcing of water resource impacts through substitutionary economic trade. This is generally understood as the indirect component of a water footprint, and as ‘virtual water’ trade.
The presented work employs generalized CNH methods, Embedded Resource Impact Accounting (ERA), to reveal the trade in water resource impacts embedded in electrical energy within the Western US power grid, and the relationship of these impacts to the human economy’s structure. We then utilize a general equilibrium economic trade model combined with drought and demand growth constraints to estimate the future status of this trade. Trade in embedded water resource impacts currently increases total water used for electricity production in the Western US and shifts water use to more water-limited States. Extreme drought and large increases in electrical energy demand increase the need for embedded water resource impact trade, while motivating a shift to more water-efficient generation technologies and more water-abundant generating locations. Cities are the largest users of electrical energy, and in the 21st Century will outsource a larger fraction of their water resource impacts through trade. This trade exposes cities to risks associated with disruption of long-distance transmission and distant hydrological droughts.
Such as time allows, a more detailed introduction to the general concepts and methods of Embedded Resource Impact Accounting and its applications to urban and watershed systems in the US will be presented. Municipalities are connected to each other and to surrounding landscapes through trade and the attendant embedded water impacts form a rich network of interactions between the human and natural system. These interactions have important implications for economics and resilience, as well as for achieving system-level solutions to environmental problems in the 21st century.