The Model and the River: The Model and the River: infrastructure and infrastructure and

deliberation in California deliberation in California water policywater policy

Arizona State UniversityArizona State UniversityOctober 28, 2005October 28, 2005

Steven JacksonSteven JacksonAssistant Professor and Research InvestigatorAssistant Professor and Research Investigator

School of InformationSchool of InformationUniversity of MichiganUniversity of Michiganhttp://www.si.umich.eduhttp://www.si.umich.edu

OverviewOverview

Modeling, prediction, and water Modeling, prediction, and water management in California (CALSIM)management in California (CALSIM)

Some themes…Some themes…

Numbers and democracy Numbers and democracy (Porter, Ezrahi, (Porter, Ezrahi, Rose)Rose)

Archives and government Archives and government (Derrida, (Derrida, professional archives lit)professional archives lit)

Deliberative infrastructure / CSDWDeliberative infrastructure / CSDW

……and fields of application.and fields of application.

Environmental (or geo-)informaticsEnvironmental (or geo-)informatics: “the : “the assemblage of visioning, processing, and assemblage of visioning, processing, and archiving techniques built around the network archiving techniques built around the network resources of post-war computing, dedicated to resources of post-war computing, dedicated to the production and refinement of ‘earthly the production and refinement of ‘earthly knowledges’” (computer models, GIS, satellite / knowledges’” (computer models, GIS, satellite / remote sensing, data management, remote sensing, data management, cyberinfrastructure and ‘E-science’ initiatives, cyberinfrastructure and ‘E-science’ initiatives, etc.)etc.)

Data Sharing /Collaboration

Data Storage /Archiving

Data Mining /Management

GISSatellite Imaging

Cyber-Infrastructures

RemoteSensing

SimulationModels

Conceptual Map –

Environmental Informatics

Science

Policy

Society

California water: a primer

20th-century history of massive systems development (urban extensions, Hoover Dam, the CVP, the SWP), from ‘total development’ to ‘public trust’

…renovations in the field of knowledge and representation…

…assembling the river.

Conceptual and numeric models…Conceptual and numeric models…

V = (1.49R2/3s1/2)/n

Physical models (‘scale analogs’)…

(Berkeley Hydraulics Lab, ca. 1942)

Electric models (‘process’ analogs)…

(Berkeley, ca. 1950s)

Some (social) epistemologies Some (social) epistemologies of modeling… of modeling…Epistemic status: Theory? Experiment? Epistemic status: Theory? Experiment?

Description? Story?Description? Story?

The validity of ‘analogical reasoning’?The validity of ‘analogical reasoning’?

Modeler’s regress and the problem of open-world Modeler’s regress and the problem of open-world

modeling? modeling?

The character of witnessing?The character of witnessing?

““Heuristic devices” or “predictive truth Heuristic devices” or “predictive truth machines”? (Shackley and Wynne, 1996) machines”? (Shackley and Wynne, 1996)

Simulation in water Simulation in water managementmanagement

1950s/70s – 1950s/70s – First introductions (though following on numeric First introductions (though following on numeric

traditions dating to early 20traditions dating to early 20thth-century); built around -century); built around mass balance equations (i.e. simple stock and flow mass balance equations (i.e. simple stock and flow models); technical form: hard-wired and spaghetti models); technical form: hard-wired and spaghetti coding (non-transparent)coding (non-transparent)

1980s/90s – 1980s/90s – Coalescence around agency in-house models: Coalescence around agency in-house models:

DWRSIM and PROSIMDWRSIM and PROSIM Models in the public sphere: new EI requirements, Models in the public sphere: new EI requirements,

tightening system constraints, increasingly restive tightening system constraints, increasingly restive and technically engaged ‘lay experts,’ inter-agency and technically engaged ‘lay experts,’ inter-agency conflictconflict

CALSIM – a fragile peace?CALSIM – a fragile peace?The ‘consensus model’ – a joint DWR/BR effortThe ‘consensus model’ – a joint DWR/BR effort

Some technical details:Some technical details:→ FORTRAN- and JAVA-based, through interface of WRESL FORTRAN- and JAVA-based, through interface of WRESL

(Water Resource and Environmental Simulation (Water Resource and Environmental Simulation Language)Language)

→ Object-oriented, structured, and soft-wired (‘data Object-oriented, structured, and soft-wired (‘data driven’) programming principlesdriven’) programming principles

→ Open source, freely downloadable*, and (in principle) Open source, freely downloadable*, and (in principle) transportable and transparenttransportable and transparent

→ User interface: spreadsheet and file processing inputs User interface: spreadsheet and file processing inputs (pre-processors), spreadsheet and graphing output (pre-processors), spreadsheet and graphing output functions (post-processors) functions (post-processors)

→ Monthly timesteps, solving iteratively according to Monthly timesteps, solving iteratively according to system of user-specified objectives and constraintssystem of user-specified objectives and constraints

→ NB: NB: NOTNOT visually rich visually rich

Objectives(weights and

priorities)

Constraints(hard, soft, or conditional)

Simulation / Optimization(single (monthly) time-step)

Model Inputs Model Outputs

CALSIM II Operation (simplified)

Mixed Integer LinearProgramming (MIP) Solver…

…iterative across multiplesimulation cycles.

State variables(input or pre-processed)

Operating policies and procedures(regulatory, con-

tractual, etc.)

State variables(raw or post-processed)

WRESL (naturallanguage interface)

Data interfaces(spreadsheet / file

management)

Simulationreports anddiagnostics

Othermodels

(DSM2, IGSM2, CALAG)

(static and/ordynamic (ANN))

CALSIM – a fragile peace?CALSIM – a fragile peace?The ‘consensus model’ – a joint DWR/BR effortThe ‘consensus model’ – a joint DWR/BR effort

Some technical details:Some technical details:→ FORTRAN- and JAVA-based, through interface of WRESL FORTRAN- and JAVA-based, through interface of WRESL

(Water Resource and Environmental Simulation Language)(Water Resource and Environmental Simulation Language)→ Object-oriented, structured, and soft-wired (‘data driven’) Object-oriented, structured, and soft-wired (‘data driven’)

programming principlesprogramming principles→ Open source, freely downloadable*, and (in principle) Open source, freely downloadable*, and (in principle)

transportable and transparenttransportable and transparent→ User interface: spreadsheet and file processing inputs User interface: spreadsheet and file processing inputs

(pre-processors), spreadsheet and graphing output (pre-processors), spreadsheet and graphing output functions (post-processors) functions (post-processors)

→ Monthly timesteps, solving iteratively according to system Monthly timesteps, solving iteratively according to system of user-specified objectives and constraintsof user-specified objectives and constraints

Science and the escape from politics?Science and the escape from politics?

Controversy and deliberation Controversy and deliberation (I): The 2002 SWP Reliability (I): The 2002 SWP Reliability

Report Report

CALSIM projection of the reliability of CALSIM projection of the reliability of future SWP deliveries to contractors – future SWP deliveries to contractors – quasi-legislative effects (Kuehl Bill) quasi-legislative effects (Kuehl Bill)

Produced numbers widely held to be Produced numbers widely held to be above all reasonable estimate – median above all reasonable estimate – median delivery rates delivery rates 50% higher 50% higher than historically than historically observed deliveries observed deliveries

Immediate public backlash – Immediate public backlash – conservationists, but also legislators, conservationists, but also legislators, water contractors, media, etc.water contractors, media, etc.

Controversy and deliberation Controversy and deliberation (II): 200? California Water Plan (II): 200? California Water Plan

Update Update

Updated once every five years since 1957, the Updated once every five years since 1957, the blueprint for statewide water planning / blueprint for statewide water planning / developmentdevelopment

Projections derived largely from CALSIM and Projections derived largely from CALSIM and subsidiary models (agricultural, delta, climate, subsidiary models (agricultural, delta, climate, groundwater, demographic, economic, etc.)groundwater, demographic, economic, etc.)

Public advisory committee Public advisory committee rejectsrejects the adequacy the adequacy of CALSIM, advocates a phased development of CALSIM, advocates a phased development approach and new tool developmentapproach and new tool development

Modeling as social Modeling as social technology…technology…

R1:R1: I think the model should be built as if it’s going to court. I think the model should be built as if it’s going to court. Because if it’s not already there, it soon will be.Because if it’s not already there, it soon will be.

- Interview transcript 9, p 11.- Interview transcript 9, p 11.

R1R1: The problem is, there aren’t enough staff at DWR or the Bureau : The problem is, there aren’t enough staff at DWR or the Bureau to do all the runs to study all the things people would like to see to do all the runs to study all the things people would like to see studied. So their needs get met first, and it’s harder to get studied. So their needs get met first, and it’s harder to get environmentally-oriented modeling conducted. So then it’s really environmentally-oriented modeling conducted. So then it’s really a matter of understanding the logistics, the weaknesses of the a matter of understanding the logistics, the weaknesses of the model. When the enviros come after CALSIM, it’s because they model. When the enviros come after CALSIM, it’s because they don’t like the results. You go after the model to undermine the don’t like the results. You go after the model to undermine the conclusion it comes to.conclusion it comes to.

- Interview transcript 23, p 3.- Interview transcript 23, p 3.

Modeling as social technology Modeling as social technology (cont’d)(cont’d)

R1R1: The problem is, when people critique a model, they’re actually : The problem is, when people critique a model, they’re actually critiquing all things around a model. And because people don’t critiquing all things around a model. And because people don’t speak the same language, they talk past each other. So it’s hard speak the same language, they talk past each other. So it’s hard to discern: what is their problem? to discern: what is their problem?

- Interview transcript 31, p 9.- Interview transcript 31, p 9.

R2R2: Generally speaking, people always have more trust in a model that tells : Generally speaking, people always have more trust in a model that tells them what they already think.them what they already think.

R3R3: And a model they understand.: And a model they understand.R2R2: And a model they understand. Or a model that they feel is understood : And a model they understand. Or a model that they feel is understood

and trusted by people they trust, that's I think the biggest thing. Policy and trusted by people they trust, that's I think the biggest thing. Policy people trust technical results that come out of people they trust. Because people trust technical results that come out of people they trust. Because they're never going to know that model, even if it's the simplest they're never going to know that model, even if it's the simplest spreadsheet.spreadsheet.

INTINT: So as long as Joe at the Bureau who they know and trust says this is : So as long as Joe at the Bureau who they know and trust says this is fine, we agree with the results, then that's enough?fine, we agree with the results, then that's enough?

R2R2: Yes. And everybody has a different Joe, and a different organization.: Yes. And everybody has a different Joe, and a different organization. - Interview transcript 4a, p 5. - Interview transcript 4a, p 5.

Problem? What’s the problem?Problem? What’s the problem?

(Technocratically-speaking): A politically (Technocratically-speaking): A politically dangerous crisis of faith –dangerous crisis of faith –

Placing future development in jeopardy?Placing future development in jeopardy?

Unraveling the peace-through-science settlement of the 1990s?Unraveling the peace-through-science settlement of the 1990s?

Delegitimation of modeling expertise?Delegitimation of modeling expertise?

(Deliberatively-speaking): An opportunity (Deliberatively-speaking): An opportunity for constructive public engagement –for constructive public engagement –

Building broader and more realistic expectations of models?Building broader and more realistic expectations of models?

Putting modeling on a sounder (more sustainable) long-term Putting modeling on a sounder (more sustainable) long-term footing?footing?

Engaging publics in the broader problematic(s) of California Engaging publics in the broader problematic(s) of California water?water?

Observations and ConclusionsObservations and Conclusions

Ontological sprawl:Ontological sprawl: the hybrid ecologies of models the hybrid ecologies of models (natural, technical, institutional, social) (natural, technical, institutional, social)

Models thrive within worlds made safe for Models thrive within worlds made safe for computing:computing: the fallacy of ‘computation in the wild’the fallacy of ‘computation in the wild’

The political language(s) of numbers (and The political language(s) of numbers (and pictures!):pictures!): the power of thin descriptionthe power of thin description

Deliberative geo-informatics: Deliberative geo-informatics: the democratic the democratic affordances of infrastructure; computer supported affordances of infrastructure; computer supported deliberative workdeliberative work

Future research and Future research and collaborations…collaborations…

U of Michigan School of Information U of Michigan School of Information (Comp Sci, Psych, Econ, Comm, History, Library Sci, (Comp Sci, Psych, Econ, Comm, History, Library Sci, STS) – human-computer interaction, computer-STS) – human-computer interaction, computer-supported cooperative work, info analysis and supported cooperative work, info analysis and retrieval, network analysis, natural language retrieval, network analysis, natural language processing, archives and records management, social processing, archives and records management, social

/ community informatics / community informatics Information, policy, and governance – Information, policy, and governance –

democratic implications, applications, and democratic implications, applications, and governance of advanced (or not) computational governance of advanced (or not) computational infrastructure infrastructure

Thank you – comments, questions, Thank you – comments, questions, ideas, and suggestions all ideas, and suggestions all welcome…welcome…

Steven JacksonSteven Jackson

Assistant Professor / Research InvestigatorAssistant Professor / Research Investigator

School of Information, University of MichiganSchool of Information, University of Michigan

301D West Hall, 1085 South University Avenue301D West Hall, 1085 South University Avenue

Ann Arbor, MI 48109-1107Ann Arbor, MI 48109-1107

Tel: 734-764-8058 Fax: 734-764-2475Tel: 734-764-8058 Fax: 734-764-2475

sjackso@umich.edusjackso@umich.edu

http://www.si.umich.eduhttp://www.si.umich.edu