IFPRI
IFU-IMK
INIA
ISSER
UfZ
UHOH
UTalca
WRI
Challenge Program
Integrating
Governance &
Modeling
Multi-Agent System Modeling:
An Application to Water
Resource Management
Thomas Berger
University of Hohenheim
Governance
&
Modeling
Challenge Program
CGIAR Challenge Program
Global challenge: provision of food and
environmental security
First cycle of competitive grant funding: program
budget US$ 30 - 40 million
342 concept notes, 98 full proposals, 50 approved
projects, 16 immediately funded
IFPRI/UHOH are co-leading the project
'Integrating Governance and Modeling' (1 of 16)
Governance
&
Modeling
Challenge Program
Benchmark Basins
Project sites of Integrating Governance & Modeling
Governance
&
Modeling
Challenge Program
Project Website
Governance
&
Modeling
Key Questions
Challenge Program
Improve process understanding of water
resource systems?
Contribution of Multi-Agent Systems
Models?
Integrating Governance and Modeling?
Governance
&
Modeling
Simulation Models in Agriculture
Type of scenario
Aggregated Approach
Independent Farms
Not profit-maximizing
Challenge Program
Imperfect markets
MAS
++
MAS
+++
Adjustment processes
Interdependencies at sector level
Spatial set-up
Based on Hazell/Norton (1986) and Hanf (1989)
Governance
&
Modeling
Challenge Program
Scales of Simulation Models
Aggregated Regional
Models
MP-based
Multi-Agent Models
Kraichgau
(Dabbert et al.)
1.500 km2
Uganda
(UHOH)
12 km2
25.000
km2
Chile
(UHOH)
670 km2
28.000
km2
Hohenlohe
(Happe)
734 km2
Regflud
(RAUMIS)
Danubia
(GLOWA)
Governance
&
Modeling
Challenge Program
Here: Class of Problems
Technical and institutional innovations in smallerscale water resource systems
Spatial externalities, property rights,
distributional effects
Compensation mechanisms, viability,
implementation
Potential for collective action, participation of
resource users and managers
Governance
&
Modeling
Structure of Talk
Management of water resource systems
– Social Ecological Systems
– CGIAR Challenge Program on Water & Food
Challenge Program
MAS as part of policy-relevant monitoring
systems
– Parameterization and model coupling
– Use of legacy models
Outlook
– Possible contributions of simulation models
– Challenges ahead
Governance
&
Modeling
Social Ecological Systems #1
Water resource systems are a subset of Social Ecological
Systems (Walker et al., 2002)
Interdependencies among actors through interactions
with biophysical and biological entities
Challenge Program
– Irrigation systems
– Fishing, Hunting
Resource users invested in physical and institutional
infrastructure
– Resource managers, providers of public infrastructure
– Potential for collective action
Governance
&
Modeling
Social Ecological Systems #2
Wittmer et al. (2006)
1 Water availability
7
2 Election of directorate
Contribution of users
Resource
users
2
Challenge Program
1
6
Infrastructure
providers
5
Resource
4
3 Establishing/Maintaining
infrastructure
Public
infrastructure
3
4 Reduction of water
availability
5 Maintenance,
Monitoring,
Sanctioning
6 Rainfall variability
Water contamination
7 Change in water code
6
Based on Janssen/Ostrom (2006)
Governance
&
Modeling
Challenge Program
Social Ecological Systems #3
Important Research Issues
Self-organization and cultural adaptation, robustness of
social ecological systems
Dynamics in ecological subsystem, linking of model
approaches to effective monitoring systems
Common-pool resources, linkages between resource
users and providers of infrastructure, institutional
“memory“
Establishment of multi-stakeholder platforms for local
resource management (action research, collaborative
learning)
Governance
&
Modeling
Requirements for Policy-Relevant
Modeling Systems (PRMS)
informative
– provide information on changing resource use
conditions and give early warnings
Challenge Program
intelligent
– identify causes and suggest solutions
interactive
– bring key stakeholders together to obtain consensus
on management problems and to assign
responsibilities for agreed solutions
Hazell et al. (2001)
Governance
&
Modeling
Challenge Program
Research Questions related to PRMS
Identify functions and frictions within multistakeholder governance structures
Develop actor-centered and knowledge-based
tools for planning support
Assess impacts of using these tools on
decision/policymaking
Suggest appropriate institutional solutions for
using tools
Collaborative research and learning framework
Governance
&
Modeling
Project Integrating Governance &
Modeling
Analysis of multi-stakeholder governance structures
– Policy Pilot Studies in cooperation with stakeholders
Challenge Program
Identification of stakeholders' problems, policy options
and criteria for evaluation of the policy options
Extension of integrated modeling system
– Incorporate impact of climate change on resource use decisions
– Evaluation of policy options, as identified by stakeholders
Development of decision-support tools
– Present and visualize outputs of modeling systems in a form that
is useful for the stakeholders, and
Actual use of the decision-support tools in negotiation
and planning processes
– Up-scaling of pilot project experiences
Governance
&
Modeling
Policy Background in Chile
General political system
– Unitary state, centralized
– “Model” for far-reaching privatization
– Limited role of NGOs
Challenge Program
Advanced stage of basin development
–
–
–
–
Water user rights privatized
Management of infrastructure devolved to user associations
State subsidies for irrigation infrastructure
Concessions to private sector for large-scale infrastructure
Problems
– Security of water flow (storage capacity)
– Maintenance of infrastructure
Governance
&
Modeling
Wittmer et al. (2006)
Challenge Program
Institutional Analysis
Governance
&
Modeling
Challenge Program
Interactions of Actors
GIS: Plan Director Cuenca Maule
Governance
&
Modeling
Collaborative Research & Learning
Framework
1. First round contacts, introductions
Inform stakeholders, contribute to understanding governance
structures
2. Demonstrations of the model
Challenge Program
Elicit feed-back on problems, needs and potential solutions and
evaluation criteria (use cases, scenarios); may involve another
workshop
3. Organizing feed-back, esp. regarding front-end
More workshops and evaluation of workshops, may also involve
smaller working groups/interviews
4. Practical use of the model by stakeholders
Identification of people who to train, training - training version of
the model
5. Monitoring/evaluating the use of models by stakeholders
Establishing the use potential of the model
Wittmer et al. (2006)
&
Stakeholder Workshop, Casa Pehuenche, Chile
22-23 Nov. 2005
Challenge Program
Governance
Modeling
Options Perceived by Stakeholders
Governance
&
Modeling
Priorities of Stakeholders
Water resources management
– Environmental impacts (water quality)
– Quantification of return-flows
Implications of medium/large-size reservoirs
Challenge Program
– Water availabilty, water price, income
– Regulations concerning concessions
Options for infrastructure improvement
– Project / investment analysis
– Impacts on return-flows
Impacts of government programs
– Social effects (distribution of benefits, poverty alleviation)
– Analysis of cost efectiveness
Governance
&
Modeling
Challenge Program
Multi-Agent Systems (MAS)
Layers
Components
Networks
Communication model
Land markets
Auction model
Land use
MILP
CropWat
Factor endowment
Household survey
Property rights
Land registry
Soil quality
GIS/DEM
Water run-off
WaSiM-ETH
Berger et al. (2006)
Governance
&
Modeling
Challenge Program
Demo Version and Manual
http://www.uni-hohenheim.de/mas/software/
Governance
&
Modeling
Empirical Parameterization (1)
Challenge Program
Land tenure based on data of
CIREN-CORFO
Agricultural and forestry plots
Governance
&
Modeling
Empirical Parameterization (2)
Actors
Data processing
Agents
11 1111 11
01 0011 10
Challenge Program




Estimate distribution
functions
Apply Monte Carloapproach
Assign characteristics
to computational
agents
Validate statistical
consistency
11 0101 01
01 0101 01
01 0110 00
11 0111 11
01 0111 11
01 0011 11
N = 5400
n = 250
N = 5400
Governance
&
Modeling
Empirical Parameterization (3)
Challenge Program
Monte-Carlo Data Generator
Objective:
Automated generation
of possible
agent populations
Procedure:
Sequential assignment
following distribution functions
Agent No. 1
1. Area of land
2. # plots
3. # hh members
4. Educational level
4. Age of members
5. # cows
6. # goats
7. # chicken
Governance
&
Modeling
Empirical Parameterization (4)
Challenge Program
Empirical distribution over all farm households
Berger/Schreinemachers (2006)
Governance
&
Modeling
Empirical Parameterization (5)
Berger/Schreinemachers (2006)
Challenge Program
Empirical distribution in household clusters
Governance
&
Modeling
Empirical Parameterization (6)
Challenge Program
Family composition (survey vs. model results)
Berger/Schreinemachers (2006)
Governance
&
Modeling
Agent Behavior
Household
agent
performance
last year
Off-farm;
migration
Expectations
for next year
Recursive agent decision model
prices, water
Agent decision
making
Agent
interactions
Investments
Communication
networks
Tenure
Resource
markets
Challenge Program
yes
no
Continue
farming?
land, labor, water
Production
Production &
marketing
results
Irrigation
Water return
flows
Governance
&
Modeling
Modeling Agent Decision-Making
Maximization of expected household income
Consumption side
Production side
1.Savings
1.Mitscherlich yield response
(Quadratic savings model)
2.Food expenditures
(Working-Leser model)
3.Food item expenditures
(LA/AIDS model)
(TSPC)
2.Labor reduction factor
(Cobb-Douglas production function)
Schreinemachers/Berger (in print)
Challenge Program
implemented with mixed-integer mathematical programming (MIP)
Governance
&
Modeling
Challenge Program
Validation of WASIM-ETH
Leemhuis (2006)
Governance
&
Modeling
Graphical User Interface
1. Environmental indicators
– Land use
– Nutrient balances
– Water return-flows
Challenge Program
2. Socioeconomic indicators
–
–
–
–
Cash-flow
On-farm capital
On-farm labor
Relative factor payment
Thanks to T. Arnold (UHOH)
Governance
&
Modeling
Preliminary Simulation Results
Effect of technical change on
average household income
Effect of technical change on
average water use efficiency
0.5
1400
1200
0.4
800
600
400
0.3
0.2
ideal technical change
0.1
market solution
200
without innovation
0
0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
Years [1 = 1997]
1 2 3 4 5 6
7 8 9 10 11 12 13 14 15 16 17 18 19
Years [1 = 1997]
Berger et al. (2006)
On-field water use efficiency
$ [10,000 Chilean Pesos]
Challenge Program
1000
Governance
&
Modeling
Why Integration?
“Value Added“ of bridging knowledge domains
– Feedback loops, thresholds and irreversibilities
Biophysical and socioeconomic data sets becoming
available
Challenge Program
– Geo-referencing, merging
Participatory approaches in water management
– Integrated water resources management
– Water directive of European Union
„Frontier“ of applied basic research
– Funding by NSF, DFG and others
– Funding by EU (e.g. OpenMI)
Governance
&
Modeling
Challenge Program
Expected Contributions of Integrated
Model Systems
Resolving basic information problem if process of
integration succeeds
Quantification of temporal and spatial
externalities, ex ante analysis of policy options,
exploring scope for collective action
MAS as part of policy-relevant monitoring
systems could serve platform for exploration of
alternative management rules and compensation
mechanisms
Governance
&
Modeling
Challenge Program
Challenges Ahead
Model sensitivity analysis
Data analysis and interpretation
Representation of social interactions
Practical use of PRMS
Knowledge representation and knowledge
engineering
Governance
&
Modeling
Challenge Program
Model Team at UHOH
Alexandra Theune
Groundwater and Water Quality
Arnélida Gorrín
Satellite imagery, remote sensing, classification of land use change in Chile
Chris Schilling
Gross Margin Analysis, calibration of MIP, updating of MAS input data set in Chile
Constanze Leemhuis
Calibration of WASIM using Richards Equations in Chile; Proposal for extension of
fine-scale WASIM model in Ghana (Atankwidi+)
Florian Bruns
Programming of GIS structure and TDT for MAS-WASIM model coupling
Hamil Uribe
WASIM irrigarion sections, GIS input data in Chile; Use-Case Analysis
Hannes König
WASIM (Top Soil model) in Chile plus Gross Margin Calculations
Jingtao Wang
Computer Programming; Solver for Mixed-Integer Programming
Marco Huigen
Use-Case Analysis; Advice on options for model coupling
Markus Mast
Coupling of MAS and WASIM; programming of WASIM interface
Paul Fuentes
Compilation of model input data in Chile
Pepijn Schreinemachers
MAS Teaching Module; programming of Visual Basic Macros for MAS input data set
Sascha Holzauer
MAS Teaching Module; Project Website
Thomas Berger
Programming of MAS source code
Thorsten Arnold
Coupling of MAS and WASIM; programming of MAS interface; programminng of User
Front End, data input and output processing routines
Tsegaye Yilma
Fieldwork in Ghana (Household and Market Survey), Use-Case Analysis