UHOH

1. ISSER UTalca WRI UfZ UHOH IFPRI INIA IFU-IMK

2. Multi-Agent System Modeling:An Application to Water Resource Management Thomas BergerUniversity of Hohenheim

3. 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)

4. Benchmark Basins Project sites of Integrating Governance & Modeling

5. Project Website

6. Key Questions • Improve process understanding of water resource systems? • Contribution of Multi-Agent Systems Models? • Integrating Governance and Modeling?

7. Simulation Models in Agriculture Aggregated Approach Independent Farms Type of scenario Not profit-maximizing MAS ++ Imperfect markets Adjustment processes Interdependencies at sector level Spatial set-up MAS +++ Based on Hazell/Norton (1986) and Hanf (1989)

8. Scales of Simulation Models

9. Here: Class of Problems • Technical and institutional innovations in smaller-scale water resource systems • Spatial externalities, property rights, distributional effects • Compensation mechanisms, viability, implementation • Potential for collective action, participation of resource users and managers

10. Structure of Talk • Management of water resource systems • Social Ecological Systems • CGIAR Challenge Program on Water & Food • MAS as part of policy-relevant monitoring systems • Parameterization and model coupling • Use of legacy models • Outlook • Possible contributions of simulation models • Challenges ahead

11. 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 • Irrigation systems • Fishing, Hunting • Resource users invested in physical and institutional infrastructure • Resource managers, providers of public infrastructure • Potential for collective action

12. Wittmer et al. (2006) 7 1 2 3 4 5 6 7 Water availability Election of directorate Contribution of users Establishing/Maintaining infrastructure Reduction of water availability Maintenance, Monitoring, Sanctioning Rainfall variability Water contamination Change in water code 2 1 5 6 4 3 6 Social Ecological Systems #2 Resource users Resource Infrastructureproviders Public infrastructure Based on Janssen/Ostrom (2006)

13. 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)

14. Requirements for Policy-Relevant Modeling Systems (PRMS) • informative • provide information on changing resource use conditions and give early warnings • 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)

15. Research Questions related to PRMS • Identify functions and frictions within multi-stakeholder 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

16. Project Integrating Governance & Modeling • Analysis of multi-stakeholder governance structures • Policy Pilot Studies in cooperation with stakeholders • 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

17. Policy Background in Chile • General political system • Unitary state, centralized • “Model” for far-reaching privatization • Limited role of NGOs • 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

18. Institutional Analysis Wittmer et al. (2006)

19. Interactions of Actors GIS: Plan Director Cuenca Maule

20. Collaborative Research & Learning Framework • First round contacts, introductions Inform stakeholders, contribute to understanding governance structures • Demonstrations of the model Elicit feed-back on problems, needs and potential solutions and evaluation criteria (use cases, scenarios); may involve another workshop • Organizing feed-back, esp. regarding front-end More workshops and evaluation of workshops, may also involve smaller working groups/interviews • Practical use of the model by stakeholders Identification of people who to train, training - training version of the model • Monitoring/evaluating the use of models by stakeholders Establishing the use potential of the model Wittmer et al. (2006)

21. Options Perceived by Stakeholders Stakeholder Workshop, Casa Pehuenche, Chile22-23 Nov. 2005

22. Priorities of Stakeholders • Water resources management • Environmental impacts (water quality) • Quantification of return-flows • Implications of medium/large-size reservoirs • 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

23. Networks Communication model Auction model Land markets MILP CropWat Land use Land registry Property rights Factor endowment Household survey Water run-off WaSiM-ETH Soil quality GIS/DEM Multi-Agent Systems (MAS) Layers Components Berger et al. (2006)

24. Demo Version and Manual http://www.uni-hohenheim.de/mas/software/

25. Empirical Parameterization (1) • Land tenure based on data of CIREN-CORFO • Agricultural and forestry plots

26. Estimate distribution functions Apply Monte Carlo-approach Assign characteristics to computational agents Validate statistical consistency Agents 11 1111 11 01 0011 10 11 0101 01 01 0101 01 01 0110 00 11 0111 11 01 0111 11 01 0011 11 N = 5400 Empirical Parameterization (2) Actors Data processing N = 5400 n = 250

27. 1. Area of land 2. # plots 3. # hh members 4. Educational level 4. Age of members 5. # cows 6. # goats 7. # chicken Agent No. 1 Empirical Parameterization (3) Monte-Carlo Data Generator Objective: Automated generation of possible agent populations Procedure: Sequential assignment following distribution functions

28. Empirical Parameterization (4) Empirical distribution over all farm households Berger/Schreinemachers (2006)

29. Empirical Parameterization (5) Empirical distribution in household clusters Berger/Schreinemachers (2006)

30. Empirical Parameterization (6) Family composition (survey vs. model results) Berger/Schreinemachers (2006)

31. Recursive agent decision model Expectations for next year prices, water Household agent performance last year Agent interactions Agent decision making Communication networks Off-farm; migration Investments yes Continue farming? Tenure Resource markets land, labor, water no Production Water return flows Production & marketing results Irrigation Agent Behavior

32. Modeling Agent Decision-Making Maximization of expected household income implemented with mixed-integer mathematical programming (MIP) Consumption side 1.Savings (Quadratic savings model) 2.Food expenditures (Working-Leser model) 3.Food item expenditures (LA/AIDS model) Production side 1.Mitscherlich yield response (TSPC) 2.Labor reduction factor (Cobb-Douglas production function) Schreinemachers/Berger (in print)

33. Validation of WASIM-ETH Leemhuis (2006)

34. Graphical User Interface • Environmental indicators • Land use • Nutrient balances • Water return-flows • Socioeconomic indicators • Cash-flow • On-farm capital • On-farm labor • Relative factor payment Thanks to T. Arnold (UHOH)

35. Preliminary Simulation Results Berger et al. (2006)

36. Why Integration? • “Value Added“ of bridging knowledge domains • Feedback loops, thresholds and irreversibilities • Biophysical and socioeconomic data sets becoming available • 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)

37. 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

38. Challenges Ahead • Model sensitivity analysis • Data analysis and interpretation • Representation of social interactions • Practical use of PRMS • Knowledge representation and knowledge engineering

39. Model Team at UHOH