Earth Systems Engineering and Management CEE 400 Week 5: Complex Systems Earth Systems Engineering and Management * Complex Systems: TermsSystems are groups of interacting, interdependent parts linked together by exchanges of energy, matter and informationComplex systems are characterized by:Strong (usually non-linear) interactions between the partsComplex feedback loops that make it difficult to distinguish cause from effectSignificant time and space lags, discontinuities, thresholds, and limitsOperation far from equilibrium in a state of constant adaptation to changing conditions (at the edge of deterministic chaos) Adapted from R. Costanza, L. Wainger, C folk, and K. Maler, “Modeling Complex Ecological Economic,” BioScience 43(8): 545-55 Four Types of ComplexityStatic complexity (or just complicated): many nodes and links (a 747 sitting on the ground)Dynamic complexity: system operating through time (747 in flight, controlled by air traffic control)Wicked complexity: integrates human systems (global air transport as a system)Earth systems complexity: integrated built/natural/human systems at regional and global scale (e.g., effect of 747 on disease patterns, and on eco-touorism) Evolution of Complex Adaptive Systems All complex systems evolve in response to changing boundary conditions and internal dynamics – so known as “Complex Adaptive Systems”. Evolution occurs as the result of three mechanisms linked in complicated ways: Information storage and transmission Mutation (generation of new alternatives for system agents Selection among alternative based on performance given internal states and external boundary conditions Where Complex Adaptive Systems LiveIf too many strong linkages among parts of a system, it cannot adapt; any mutation is rapidly damped out.If not enough linkages, also cannot adapt; mutation can’t be preserved in new system state.Therefore, CASs live between stasis and randomness Human Systems vs. Non-Human Systems (The “Wicked” vs. The “Tame”) Wicked Systems: 1. Policy problems cannot be definitively described 2. There is nothing like an indisputable public good 3. There are no objective definitions of equity 4. Policies for social problems cannot be meaningfully correct or false 5. There are no “solutions”in the sense of definitive, objective answers 6. There is no optimality Source: H.W.J. Rittel and M. M.Webber, “Dilemmas in a General Theory Planning,” Policy Scenes 4 (1973), pp. 155-169 Policy Implications of Simple (S) vs Complex (C) Systems Function as Displayed by System Information Centralized command-and-control feasible System management by adjusting forcing behavior; command-and-control contraindicated Causality Centralized command-and-control to endpoint (effect) feasible Function Type Policy Implication S Centralized; system is “knowable” C Information diffused throughout the system; some embedded in system structure; system too complex to be “known” S Linea ...

1. Earth Systems Engineering and Management
CEE 400
Week 5: Complex Systems
Earth Systems Engineering and Management
*
Complex Systems: TermsSystems are groups of interacting,
interdependent parts linked together by exchanges of energy,
matter and informationComplex systems are characterized
by:Strong (usually non-linear) interactions between the
partsComplex feedback loops that make it difficult to
distinguish cause from effectSignificant time and space lags,
discontinuities, thresholds, and limitsOperation far from
equilibrium in a state of constant adaptation to changing
conditions (at the edge of deterministic chaos)
Adapted from R. Costanza, L. Wainger, C folk, and K. Maler,
“Modeling Complex Ecological Economic,” BioScience 43(8):
545-55
Four Types of ComplexityStatic complexity (or just
complicated): many nodes and links (a 747 sitting on the
ground)Dynamic complexity: system operating through time

2. (747 in flight, controlled by air traffic control)Wicked
complexity: integrates human systems (global air transport as a
system)Earth systems complexity: integrated
built/natural/human systems at regional and global scale (e.g.,
effect of 747 on disease patterns, and on eco-touorism)
Evolution of Complex Adaptive Systems All complex systems
evolve in response to changing boundary conditions and internal
dynamics – so known as “Complex Adaptive Systems”.
Evolution occurs as the result of three mechanisms linked in
complicated ways:
Information storage and transmission Mutation (generation of
new alternatives for system agents Selection among alternative
based on performance given internal states and external
boundary conditions
Where Complex Adaptive Systems LiveIf too many strong
linkages among parts of a system, it cannot adapt; any mutation
is rapidly damped out.If not enough linkages, also cannot adapt;
mutation can’t be preserved in new system state.Therefore,
CASs live between stasis and randomness
Human Systems vs. Non-Human Systems
(The “Wicked” vs. The “Tame”)
Wicked Systems:
1. Policy problems cannot be definitively described
2. There is nothing like an indisputable public good
3. There are no objective definitions of equity

3. 4. Policies for social problems cannot be meaningfully
correct or false
5. There are no “solutions”in the sense of definitive,
objective answers
6. There is no optimality
Source: H.W.J. Rittel and M. M.Webber, “Dilemmas in a
General Theory Planning,” Policy Scenes 4 (1973), pp. 155-169
Policy Implications
of Simple (S) vs Complex (C) Systems
Function as Displayed by System
Information
Centralized command-and-control feasible
System management by adjusting forcing behavior; command-
and-control contraindicated
Causality
Centralized command-and-control to endpoint (effect) feasible
Function
Type
Policy Implication
S
Centralized; system is “knowable”
C
Information diffused throughout the system; some embedded in
system structure; system too complex to be “known”
S
Linear; cause and effect east to determine
C
Causes and effects cannot be linked in most cases
Cannot be sure of actual impact on system of any policy
initiative

4. Policy Implications
of Simple (S) vs Complex (C) Systems (Cont)
Function
Type
Policy Implication
S
Predictable and relatively linear
C
Highly non-linear and may be discontinuous; not predictable a
priori
S
Rational centralized control is possible and effective
C
Causes and effects cannot be linked in most cases
Single, fully responsible entity with authoritarian power can
control system (e.g., U.S. EPA)
Response to Forcing
Rigid regulatory structures both o.k. (because out come
predictable) and politically preferable (because can’t be gamed)
Policy once in place must be very flexible, so can be changed as
systems response dictates: arbitrariness and gaming avoided by
adherence to appropriate set of metrics
Responsible management entity adjusts forcing functions (e.g.,
taxes or fees) and monitor results; direct control of system
towards endpoint eschewed metrics
Function as Displayed by System
Control Mechanisms
Policy Implications
of Simple (S) vs Complex (C) Systems (Cont)

5. S
May not be necessary because performance measured by
attaining endpoint, not system state
C
Defined in process or performance terms, and not fixed because
the constantly evolving nature of the system
Endpoints are metrics
Manage process to improve performance against metrics;
metrics critical to public/political acceptance of management
process; choice of appropriate set of metrics essential to policy
evaluate and subject to improvement as well
Metrics
Function
Type
Policy Implication
S
Defined as static terms, and achievable, not path dependent
C
Defined in process or performance terms, and not fixed because
of constantly evolving nature of systems
Endpoint
Command-and-control management to endpoint o.k.
No defined endpoint; manage system to achieve desired
emergent behavior
Function as Displayed by System
Policy Implications
of Simple (S) vs Complex (C) Systems (Cont)
Function
Type
Policy Implication
S

6. Produce endpoint
C
Maintain system stability and integrity over time
Existence
Can minimize specific insult (e.g., lead dispersion from use in
gasoline); cannot lead to or support achievability of
sustainability
Policy focus as a whole must be on system, not arbitrary
components; metrics focus on stability and systems dynamics,
not throughput
Function as Displayed by System
Complex System Case Study:
Water
Water as Earth System:
What is it?It is a materialIt is a commodity (a material that can
be owned)It is a legal construct – “water rights”It is a cultural
construct – “water as human right”It is a technological construct
(technology makes “potable water” from “sewage”)
*
Water as Earth SystemIt is transport (in Roman empire,
estimates that moving a given load 1 mile by oxcart = 5.7 miles
by river = 57 miles by sea) Development economics theorizes

7. that inland countries are disadvantaged because of lack of
access to ocean shippingThe railroad made up for this later in
some countries It is energyIt is political power (cf. water wars)
Essential for life (critical environmentally)
Dada from A. Beattie, 2009, False Economy, London: Penguin))
*
Water as Earth SystemIt is something that can be used, but not
used up (form and quality matter)
Availability in a particular circumstance is a matter of
pricepoint, infrastructure and power, not “natural” constraints.
Distribution challenges arise from transitional regimes (e.g.,
climate change, technology and infrastructure design and
construction) and cultural regimes (e.g., water as “human right”
must be economically free)
Traditional definitions fail (e.g., factory beef from stem cells as
“water technology”)
*
Water as Earth SystemLike all critical earth systems, it can be
weaponized (cf: food as weapon in Darfur)
It is provided, traded, and sold both as a material (“water”) and
as embedded in other products (“virtual water”)

8. *
Embedded Water Content of Selected Items
Based on Gradel and Allenby, Industrial Ecology and
Sustainable Engineering, 2010, Prentice-Hall; A.Y. Hoekstra
and A.K. Chapagain, Water footprints of nations: Water use by
people as a function of their consumption pattern, Water
Resources Management, 21, 35–48, 2007ProductEmbedded
water content (liters)1 microchip (2 g) 321 sheet of A4-size
paper (80 g/m2) 101 slice of bread (30 g)401 potato
(100 g)251 cup of coffee (125 ml)1401 bag of potato crisps
(190 g)1851 hamburger (150 g)2,400Embedded Water Content,
liters per gram16.125 (liters/m2)1.33.251.12 (l/ml).9716

9. *
Embedded Water80% of embedded water in global trade is in
agricultural goods¾ in crops¼ in animal productsBut beef is
single largest component of virtual water flow at 13% of global
VW, compared with 11% for soybeans and 9% for wheat,
because . . .To produce:1 ton of vegetables requires about 1,000
cubic meters of water1 ton of wheat requires about 1,450 cubic
meters1 ton of beef requires 42,500 cubic meters
*
Water as Earth System
WATER SYSTEMS
Production Technologies
Nitrogen Cycle
Carbon Cycle

10. Phosphorous Cycle
Biodiversity
Recycling Technologies
Treatment Technologies
Efficient Use Options
Agriculture
Global Trade
WATER ECONOMICS
Culture/Law
OTHER TECHNOLOGY SYSTEMS
EARTH SYSTEMS
USUAL
FOCUS
OF
WATER
POLICY
Human Health
*
Institutional Time/Population Space

11. (log/log scales)
0
3
-1
1
2
-1
-2
Time
1
10
5
15
20
Small Group or Individual Decisions
Policy, Contract
Law
Constitution
Culture
Religion-Technology Systems (coupled vs uncoupled)
Traditions and Values
Fads
Population Involved
Source: Based on L.H. Gunderson, C. S. Holling, and S. S.
Light, “Barriers broken and bridges built”, in L. H. Gunderson,
C.S. Holling, and S. S. Light, eds., Barriers and Bridges (New
York, Columbia University Press: 1995), p. 521

12. Human Psychology and Natural Systems Scale
102
104
106
108
1010
1012
10-1
100
101
102
103
104
105
106
107
108
1 hour
1 day
1 month
1 year
1 century
1 millennium
Wind Velocity
Human Transportation
Person
House
Livermore
United States
Circ of earth

13. Personal garbage
Tornados
The Tides
Thunderstorms
Dump
Faults
Aquifers
Ponds, Lakes
Storms
Jet streams
Meters
Seconds
Human psychological horizon
System Structure Over Different Time Scales
Time Scale
Endogenous

14. Exogenous
Principal Implementation Mechanism
Principal R&D Component
Integration of Natural and Artifactual Systems
Short Term (ca. 5 years)
Medium Term (ca. 5-10 years)
Long Term (ca. 10-100 years)
Incremental technology evolution within existing major
technology systems
Evolution of product and process technology systems, marginal
cultural change
Significant evolution of major technology systems; link between
quality of life and material consumption; population levels;
most aspects of culture
Population level, cultural change
Population level, significant cultural change
Almost nothing
Policy
Changes in legal structures, disciplinary assumptions, based on
industrial ecology
Metrics, changes in fundamental conservative cultural systems
(e.g., religion)
Short term industrial ecology R&D (e.g., Design for
Environment, Integrated Pest Management)
Industrial ecology infrastructure (e.g., environmentally
preferable materials database)
Industrial ecology systems (e.g., resource and energy
maps of communities and regions)
Experimental stage involving small systems (e.g., bioreactors,
drug production in genetically engineered sheep)
Partial integration of biological and engineered systems (e.g.,
commercial energy from biomass; engineered wetlands for
flood, pollution control, and waste processing)
Management of integrated regional and global systems (e.g.,
water cycles in Yellow River watershed or Southwestern United
States); Earth Systems Engineering