Risk Governance Research Workshop
Lisbon, Instituto Superior Tecnico, June 25, 2014
Quantifying WEF Interdependencies for
Mitigating Resource Uncertainties in
Developing Countries
Afreen Siddiqi, Ph.D.
Research Scientist, MIT
Visiting Scholar, Harvard Kennedy School
Increased demands and new technologies have
created the ‘water-energy-food’ nexus

Food, water, and energy are increasingly interlinked across different segments of their value
chains




water is used in extracting and processing fossil
fuel, and cooling electric power plants
energy is needed for pumping ground water,
desalination, distribution, and treatment
energy is used to power agricultural machinery,
process and transport food
adoption of bio-fuel has raised concerns for
adequate food supply and use of water
Understanding and accounting for these interconnections is
important for resource use-efficiency, socio-economic growth, and
long term sustainability
1
World Economic Forum: Global Risks Assessment 2011
The water-food-energy nexus
A cluster of risks within 37 selected global
risks as seen by members of the World
Economic Forum’s Global Agenda Councils
and supported by a survey of 580 global leaders
and decision-makers
Source: Global Risks 2011, World Economic Forum.

Demand for water, food and energy is
expected to rise by 30-50% in the next two
decades

Economic disparities incentivize short-term
responses in production and consumption
that undermine long term sustainability

Shortages could cause social and political
instability, geopolitical conflict and
irreparable environmental damage.

Any strategy that focuses on one part of
the water-energy-food nexus without
considering its interconnections risks
serious unintended consequences
2
Journal publication trends in Compendex database show
emergence of ‘nexus’ research on water, energy, and food
45
40
25
South
Africa
4%France
4%
Sweden
4%
China
4%
20
Japan Spain
4%
5%
35
# of publications
Greece India
3%
3%
30
water OR energy
OR food AND nexus
US
38%
Germany
5%
15
Others
5%
UK Turkey
8%
5%
Australia
8%
10
water AND energy
AND nexus
5
0
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
3
Indus River Basin in Pakistan
KPK
AGRICULTURE
20.1%
INDUSTRY
Punjab
Balochistan
SERVICES
54.4%
GDP
25.5%
Sindh
POPULATION: 180 MILLION
POPULATION GROWTH RATE: 1.8%
82% URBAN
Siddiqi, A., Wescoat, J. L., (2013), “Energy use in large-scale irrigated agriculture in the Punjab province
of Pakistan”, Water International, 38 (5), pp 571-586. (*Editors Choice Article)
4
Research Q: What is the energy intensity in large-scale
irrigated agriculture in Pakistan?

We base our analysis on the Indus basin in Pakistan
 a country of 180 million people intimately dependent on the Indus
river for water, food, and energy
 human impact

acute shortage of energy and water, and insufficient access to
nutrition
 necessary conditions present for action

major institutional re-structuring and infrastructure planning
under-way
 finite possibility of implementing solutions
5
Global Map of Irrigation
Source: FAO http://www.fao.org/nr/water/aquastat/irrigationmap/index10.stm
6
The Indus Basin
length (km) :
3,180
annual flow (km3) :
207
Avg. Discharge (m3/s) : 6600
Basin Area (km2) :
1,005,786
Total Population (Million) : 237
Basin Precipitation (mm/yr): 423
Source: Laghari et al. Hydrol. Earth Syst.
Sci., 16, 2012: 1063-1083.
7
Large part of the Indus Basin is arid

Low precipitation and high ET
render the region largely arid.

Rain fed agriculture is limited.
Ref: Laghari et al. Hydrol. Earth Syst.
Sci., 16, 2012: 1063-1083.
8
Despite the aridity, the area is a major agricultural
region through irrigation
Image by James Wescoat
9
Indus basin irrigation system is among the world’s largest
network of surface canals

~129 km3 of water is diverted annually to the
canal network for irrigating 44 million acres

There are large delivery losses (40% – 60%)
in the surface system that has led to
expansion of pumped irrigation
Key Features of Surface Irrigation System
10
Canal water availability has declined over past decades
(largely during the winter cropping season)
Canal Withdrawal in Punjab
80.000
70.000
Total (annual)
Billion Cubic Meters
60.000
50.000
Kharif (summer)
40.000
30.000
Rabi (winter)
20.000
10.000
0.000
The linear trend for Rabi is an average decrease of 252 Billion CM per year
The overall trend is a decrease of 182 Billion Cubic meters each year for canal withdrawals in Punjab
11
A conjunctive irrigation system has emerged with surface
and ground water use that now depends on energy
Dot Density:
1 dot = 500 Tubewells
Tubewells in 1995
Tubewells in 2010
Using district level tubewell installation data, we used GIS Mapping to
map pumping density in Punjab
12
Acute energy shortages are impacting all sectors of the
economy
Energy Shortage Context in Pakistan
Estimated Electricity Deficit in 2011
Industrial
Agricultural
Electricity Use [GWh]
3000
2500
2000
1500
1000
500
0
2006-07
2007-08
2008-09
2009-10
2010-11
MEPCO
Siddiqi, et. al, “An empirical analysis of the hydropower portfolio in Pakistan”, Energy Policy, Vol. 50, 2012
13
800,000
0
1970-71
1971-72
1972-73
1973-74
1974-75
1975-76
1976-77
1977-78
1978-79
1979-80
1980-81
1981-82
1982-83
1983-84
1984-85
1985-86
1986-87
1987-88
1988-89
1989-90
1990-91
1991-92
1992-93
1993-94
1994-95
1995-96
1996-97
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
Tube wells in Punjab
A massive pumping system draws water from the ground
to augment surface water supplies for agriculture
Total Electric Tubewells
Total Diesel Tubewells
1,000,000
900,000
off-grid distributed system
700,000
600,000
500,000
400,000
300,000
200,000
100,000
14
Reported data of energy use in agriculture provides only
partial information of total energy used in the sector
Energy Use in Agriculture in Pakistan
Agri Sector
LDO [kTOE]
Agri Electricity in Pakistan [kTOE]
900.00
800.00
700.00
k TOE
600.00
500.00
400.00
300.00
200.00
100.00
1980-81
1981-82
1982-83
1983-84
1984-85
1985-86
1986-87
1987-88
1988-89
1989-90
1990-91
1991-92
1992-93
1993-94
1994-95
1995-96
1996-97
1997-98
1998-99
1999-00
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06
2006-07
2007-08
2008-09
2009-10
2010-11
2011-12
-
Data Source: Energy Year Book, HDIP (2010, 2012)
15
Top down data coupled with bottom up calculations
were used to estimate energy use in agriculture
Fuel Type
Farm Machinery
Farm Operations
direct
energy use
Tractors
(< 55 HP)
High Speed
Diesel (HSD)
Tractors
(> 55 HP)
Field Operations
HSD Tube wells
Light Diesel Oil
(LDO)
LDO Tube wells
Electricity
Electric Tube wells
Natural Gas
Fertilizer
Production
Water Pumping
Fertilizer
Application
in- direct
energy use
16
Pumping system and farming machinery stock levels
used for bottom up estimation of HSD consumption

Annual fuel use volume (Vkfuel) for
each type of element (power level
and fuel use type) was estimated
as:
k
V fuel
 S k  c fuel  U k
Total Electric Tubewells
Total Diesel Tubewells
1,000,000
900,000
800,000
700,000
600,000
500,000
400,000
300,000
200,000
100,000
0
1970-71
1972-73
1974-75
1976-77
1978-79
1980-81
1982-83
1984-85
1986-87
1988-89
1990-91
1992-93
1994-95
1996-97
1998-99
2000-01
2002-03
2004-05
2006-07
2008-09
Operation and usage data obtained
from Punjab Agricultural Machinery
Census of 1994 and 2004
Tube wells in Punjab

U td
where:
Sk: stock level of machinery in year k

cfuel: fuel consumption /hr
U: annual utilization
t: operating hours per day
d: number of operating days per year
Number of Tractors in
Punjab
500,000
450,000
400,000
350,000
300,000
250,000
200,000
150,000
100,000
50,000
-
17
Benchmarking of the results showed reasonable
agreement with reported data
Punjab Agri LDO Use


The ratio of HSD motors used for water
pumping changes from 24% (of total
installed base) in 1994 census to 80% in the
2004 census.
This shift in fuel type contributes to steady
decline of LDO sales
300.00
250.00
200.00
k TOE

bottom-up estimate of LDO use
150.00
100.00
We compared country-level results of PakIEM model (which is MARKAL adapted for
Pakistan)
50.00
0.00
Source: Pakistan Integrated Energy
Model (Pak-IEM) – Final Report Vol. I, 2010
Agriculture
Energy Use
(2007)
Pak-IEM
Estimate
(Pakistan)
Pak-IEM derived
estimate for
Punjab
MIT
Study
data and
results
Electricity
0.8 Mtoe
0.8 X 0.47 =
370 ktoe
312 ktoe
LDO
0.1 Mtoe
0.1 X 0.9 =
90 ktoe
81 ktoe
HSD
2.7 Mtoe
-
2.4 Mtoe
LDO
Electricity
HSD
18
Water pumping is estimated to account for 61% of direct
energy use in 2010 in farm-level operations
Energy Use by Application and Fuel Type in Punjab Agriculture
Electricity
(pumping)
LDO
(pumping)
HSD
(pumping)
HSD
(Farm Ops)
1600
HSD TW pumping
1400
1200
field (HSD tractor)
operations
800
600
Electric pumping
400
2009-10
2008-09
2006-07
2005-06
2004-05
2003-04
2002-03
2001-02
2000-01
1999-00
1998-99
1997-98
1996-97
1995-96
0
2007-08
LDO TW pumping
200
1994-95
k TOE
1000
19
Reported estimates for agriculture (that exclude HSD) show only
a 3% share in total energy use in the province in 2010
Reported Energy Use in
Sectors (Punjab) [kToe]
Estimation Adjusted Energy Use in
Sectors (Punjab) [kToe]
Domestic:
Industry:
Agriculture:
Commercial:
Transport:
Power:
Other:
Domestic:
Industry:
Agriculture:
Commercial:
Transport:
Power:
Other:
Other
2%
Govt.
2%
1764
1785
467
287
5265
5305
366
Commercial Domestic
2%
12%
Industry
12%
Power
35%
Domestic
12%
Industry
12%
Power
35%
Agriculture
3%
Transport
34%
1764
1785
3118
287
2634
5305
366
Agriculture
20%
Commercial
2%
Transport
17%
20
Water, food, and energy security is about human welfare –
the resource-use efficiency needs to be improved
At the provincial level in Punjab (between 1995-2010):
 Direct energy intensity has risen 80% (from 1 to 1.8 MJ per kg of
crop produced)
 Fertilizer use intensity has risen 85% from 99 kg/ha to 184 kg/ha
 Total crop production has increased only 31%
“Due to declining performance of the sector, as well as increased
cost of inputs and inflation, the cost of food per head in the province
has gone beyond Rs.3000 [$30] per month” (DAWN, March 25, 2013)
21
Future work: Integrated modeling of water, energy, crop production,
for water, food, and energy security
22
Summary

In principle, policy makers acknowledge importance of integrated planning; in
practice it has been hard to do so due to technical and institutional hurdles

Knowledge gap in resource inter-linkages is a major impediment towards
improved policy

Strategic organizational linkages, and enhanced rules for infrastructure planning
and resource policy can be easy first steps towards improving decision-making
“The vast gains in human welfare from improved provision of
food, energy and water – and the spectre of losing this access
through shortsighted policies that fail to recognize the complex
interactions of these three issues – suggest that the Energy
Water Food nexus must be prioritized both by the analytical
policy-support community and policy-makers”
(Bazilian et al, Energy Policy, 2011)
23
QUESTIONS?
24
HSD and LDO
 Two main grades of diesel fuel are marketed in India and Pakistan,
High Speed Diesel (HSD) and Light diesel oil (LDO).
 HSD is a 100% distillate fuel while LDO is a blend of distillate fuel
with a small proportion of residual fuel.
 HSD is normally used as a fuel for high speed diesel engines
operating above 750 rpm i.e. buses, lorries, generating sets,
locomotives, pumping sets etc. Gas turbine requiring distillate fuels
normally make use of HSD as fuel.
 LDO is used for diesel engines, generally of the stationery type
operating below 750 rpm
Ref: http://www.petroleumbazaar.com/hsd/hsdappli1.htm
25
Energy estimates for agriculture show that the sector accounted
for 20% of total energy use in Punjab in 2010
Other
2%
Energy Use in Sectors (Punjab) [kToe]
Domestic:
Industry:
Agriculture:
Commercial:
Transport:
Power:
Other:
1764
1785
3118
287
2634*
5305
366
Total:
15259
Water pumping (~1909 kToe) is 12%
of total energy use in the province in
2010.
Farm operations with tractors
(~ 1209 kToe) is 8% of total energy
use in 2010.
Domestic
12%
Industry
12%
Power
35%
Agriculture
20%
Commercial
2%
Transport
17%
*HSD use estimate for agriculture was subtracted from
official HSD transport numbers keeping the reported
total energy use for the province
26
Energy, water, food policy have interwoven concerns from
ensuring access to price volatility to environmental impacts

Benefits of more holistic policy & regulatory design would likely be:





economic efficiency
resource efficiency
improved livelihood options
and public health
Negative consequences can include




impacts on communities
commodity prices
sub-optimal infrastructure design
environmental degradation
27
Surface irrigation system serves to redistribute
meltwaters as ground water recharge
Snow and icemelt from glaciers
Extensive distribution network
1. http://earthobservatory.nasa.gov/Features/Monsoon/printall.php
Large surface storage
28
Energy, water, food policy have interwoven concerns from
ensuring access to price volatility to environmental impacts
All three areas :

have many billions of people without access
(quantity or quality or both)

have rapidly growing global demand

have resource constraints
Benefits of more holistic policy &
regulatory design would likely be:






have different regional availability, supply, and
demand
operate in heavily regulated markets
are ‘‘global goods’’, involve international trade
and have global implications





have deep security issues as they are
fundamental to the functioning of society
require the explicit identification and treatment
of risks
Negative consequences can include




have strong interdependencies with climate
change and the environment
economic efficiency
resource efficiency
improved livelihood options
and public health

impacts on communities
commodity prices
sub-optimal infrastructure design
environmental degradation
Bazilian et al., “Considering the energy, water and food nexus: Towards an integrated modelling approach”,
Energy Policy, 2011
29
Background

70% of global freshwater use is in the agricultural sector

Rainfed agriculture covers 80% of cultivated land globally, and
produces 60% of crops

Irrigated agriculture represents 20% of cultivated land and accounts
for 40% of crop production
 irrigated agriculture grew 1.5% annually from 1950s-1990s

Un-reliable surface water supplies increasingly replaced with
ground water withdrawals – a shift that requires more energy
The shift from gravity-fed, surface water to pumped ground water
and pressurized field application systems has increased the
coupling between water and energy in large-scale irrigation
30
30
Future Work:
Incorporating Water Availability Uncertainties

Planning for uncertainty in water availability
Glacier Area
Glacier Area %
% change
Glacier Area [km2]
– shifts from historical norms – Indus is considered one of the most vulnerable
rivers to climate change
– decreases in surface water supplies will likely further increase pumped
irrigation
Decade
in the
future
Expected shifts in annual influx in the Indus
River [2]
[1] Himalayan Glaciers, National Research Council, 2012
[2] Pakistan’s Water Economy: Running Dry, John Briscoe, Oxford Univ. Press, 2006
31
31
World Economic Forum: Global Risks
32
Quantitative Modeling and Analysis of Complex Systems
for Data-driven Planning and Decision-Making
Investigating interactions between large-scale, critical
infrastructure systems (such as that of water, energy, and
agriculture) with the aim of informing policy, planning, and
design for improving resource use efficiency and enabling
long-term sustainability
Modeling and Computation
Decision Analysis
Dependency Structure Mapping
Graph Theory &
Networks Analysis
Systems Dynamics
Stakeholders Analysis
33
Urban Water-Energy Couplings
Problem
Approach
Impact
Quantifying water-energy couplings at
urban-scale
Building-level temporal computation of
water use and related energy
consumption
Synergies for water and energy
infrastructure planning, higher
efficiencies, improved architectural
decisions
Uncertainty Drivers:
Population Growth
Climate Change
Factors:
Urban Form
Water Scarcity
System Architecture
34
34
Urban Water Cycle: Masdar City, UAE
Siddiqi, A., de Weck, O.L., (2013) “Quantifying End-Use Energy Intensity of the Urban Water
Cycle”, ASCE Journal of Infrastructure Systems, 19 (4), pp 474-485
35
Building level water sources modeled in the study include
municipal water, rainwater, and recycled grey water
36
36
Energy needs for Building-level Water Use
1. Energy for Water Heating
EH 




Ep  ep VM  maxF  1  fM , 0  V{ RW F 
VWW F 
123
1 4 4 44 2 4 4 4 43
rainwater

recycled
wastewater 
building height


VH cT
h
A
VH  hi vi
i 1
2. Energy for On-site Pumping

 hF 1   l 
ep 
p
3. Energy for On-site Recycling
Ag
Er  er  vi

i 1
4. Building-level Energy for Water Use:
ET  EH  EP  Er
VH : volume of heated water
ρ : density of water
c : specific heat capacity
ΔT : temperature difference
αhi : ith application hot water fraction
vi : ith application water use volume
er : energy intensity of recycling
hF : floor height
αl : pipe losses
F : total number of floors in building
37
37
Computational Framework
38
38
Sample Outputs
39
39
Case Study: Masdar City

Masdar City is in the outskirts of Abu Dhabi, United
Arab Emirates

It is 6 km2 , planned to house
50,000 people, 1500
businesses, and a technical
university.

Initial cost estimates were at
$22 billion and development
time was ~10 years

It was originally targeted to be
the world’s first zero-carbon
city
40
40
Masdar City: Plot-level Master Plan
41
41
Energy for all Water Segments
Estimated Energy for Water Cycle [GWh]
Estimate for Masdar City
ΔE
Annual Water Demand [Million m3]
42
42
Energy by Water Segment
GWh
Estimated Annual Energy Requirement In Water Cycle for Masdar
Water Demand Scenario
43
43
Comparative Analysis
Comparison of Energy Intensity of Masdar Water Cycle
Across the range of water demand scenarios considered, the
energy intensity for Masdar City is ~5-7 kWh/m3
44
44
Summary
 End-use segment compares almost equally in energy intensity with
production segment (in case of Masdar)
 Water heating – even in hot climates- makes up a large share of waterrelated energy use in buildings
 Water efficiency in end-use segment is a high-impact lever for influencing
energy consumption in the urban water cycle
– water efficiency in end-use has largest multiplier effect for energy
– water conservation measures can be incentivized from an energy and financial
savings perspectives
 Water-sector energy efficiency incentives should be targeted for both
utilities and end-users
45
45
Energy for Large-Scale Irrigation
IBIS – Distributory
Network
Indus Basin Irrigation
System (IBIS)
Problem
Approach
Impact
Quantifying energy intensity of largescale irrigation.
Water and energy stocks and flows in
natural and engineered system; relating
water efficiency and energy efficiency.
Application to IBIS investment decisions
and infrastructure planning ($30 billion
currently planned)
Major Reservoirs: 3
No. of Barrages:
16
No. of Inter-link Canals:
12
No. of Canal Systems:
44
No. of Water Courses:
107,000
Avg. Canal Diversions:
104.7 MAF
Groundwater Abstraction: 42 MAF
No. of Wells:
> 750,000
Canal Command: 36 M acres
46
46
Research Q: How are energy intensity and water use
efficiency coupled in large-scale irrigated agriculture?

Large-scale irrigated agriculture is at the
core of this nexus

We base our analysis on the Indus basin
in Pakistan

a country of 180 million people
intimately dependent on the Indus
river for water, food, and energy

human impact

acute shortage of energy and water,
and in-sufficient access to nutrition
 necessary conditions
present for action

major institutional re-structuring and
infrastructure planning under-way

finite possibility of
implementing solutions
http://www.fao.org/nr/water/aquastat/irrigationmap/index10.stm
length (km) :
3,180
3
annual flow (km ) :
207
3
Avg. Discharge (m /s) :
6600
Basin Area (Million km2) : 1
Total Population (Million) : 237
Precipitation (mm/yr):
423
Ref: Laghari et al. Hydrol. Earth Syst. Sci., 16, 2012: 1063-1083.
47