Institute for Ecological Economics Collaborative Spatial Ecological-Economic Modeling for Sustainable Management of Watershed Resources Thomas Maxwell Alexey Voinov Robert Costanza

Institute for Ecological Economics Collaborative Modeling Realistic models require multiple teams Modelers typically not computer scientists Stake holders must be integrated into the decision making process Communication to a wide audience

Institute for Ecological Economics Three Stage Modeling Process Scoping models –Consensus building Research models –Understanding dynamics Management models –Exploring scenarios

Institute for Ecological Economics Scoping Workshops Constructivist learning. Paradigm expansion. –(narrow,linear,static) -> –(broad,nonlinear,dynamic) Conflict resolution. Consensus building. Collective decision making. Develop management scenarios.

Institute for Ecological Economics Supporting Collaborative Modeling Graphical modeling tools Modular model development Transparent high performance computing Integrated data access Integrated visualization Variety of formalisms and frames

Institute for Ecological Economics Graphical Modeling Model viewed and manipulated graphically. Opens model development to non-programmers. Facilitates rapid development of models. Enforces modeling standards. Facilitates collaboration in model development. Graphical representation serves as a blackboard.

Institute for Ecological Economics STELLA Model

Institute for Ecological Economics Spatial Modeling Framework

Institute for Ecological Economics Two types of modules Ecological Modules –No general theory. –Primary focus on modeling. –Examples: Macrophytes, Epiphytes, Consumers, Phytoplankton –Modules developed in Stella/SME. Physical Modules –Theory well known (e.g. Navier Stokes). –Primary focus on computation. –Examples: hydrodynamics, atmospheric dynamics. –Modules developed externally and linked to SME.

Institute for Ecological Economics Typical State Variables Examples of some typical state variables: –(Dissolved Inorganic) Nitrogen, Phosphorus –Water (Saturated, Unsaturated, Surface, Snow) –Detritus –Macrophyte (Non)Photosynthetic Biomass –Consumers –Deposited Organic Matter –Phytoplankton –Epiphytes

Institute for Ecological Economics Spatial Modeling Environment Collaborative Spatial Modeling Workbench Includes integrated support for: –Icon-based unit module development –Module archiving and reuse –Integration of multiple spatial representations –Distributed computing –Web-based modeling & simulation Configuration, control, and visualization of remote simulations. –Data access and visualization –Real-time links to other apps (e.g. Swarm).

Institute for Ecological Economics Spatial Modeling Environment STELLA PowerSim SME Module Editor Module Constructor SMML Module Library Module Repository Module Builder Simulation Driver Code Generator HPC Java Portal Unit model Spatial modelGraphical modeling

Institute for Ecological Economics SME Java Portal Desktop access to remote supercomputing resources Web-enabled ( using java servlets ) Grid enabled ( using globus gram utility ) Java applet Java servlet C++ apps Portal interfaces include: –Workspace management –Module development –Model configuration –Simulation initialization, control, & visualization

Institute for Ecological Economics WorkSpace Manager

Institute for Ecological Economics Documentation Panel Documentation of selected command Model Panel Hierarchical View of model objects Associated commands as boxes Command Panel Structure of selected command Property Panel Command Arguments Configuration Manager

Institute for Ecological Economics Parameter Editor Edit Simulation Parameters Spreadsheet format

Institute for Ecological Economics Simulation Control Control Execution View Model Structure Trace Dependencies View Model Equations Configure Visualization

Institute for Ecological Economics SME Python Shell

Institute for Ecological Economics Associates DataSets with Viewers Creates Viewers Manages DataSets ViewServer Control Panel

Institute for Ecological Economics 2D Animation Viewer 2D Animation Control Dynamic and manual rescaling ColorMap editor Data viewer (point/spreadsheet) Export as GIF or JPG

Institute for Ecological Economics 3D Animation Viewer Dynamic Landscapes Variable1 -> Altitude Variable2 -> Color Mouse controlled navigation

Institute for Ecological Economics Image Spreadsheet Simultaneous display of variables at multiple timesteps Useful for time series comparisons Configure: start time, time step, magnification, scaling, etc.

Institute for Ecological Economics  View spatial data Attach to vis panels Follows animation Export to Stat packages. Numerical Spreadsheet

Institute for Ecological Economics Agent Based Modeling in SME Swarm agents can populate SME landscapes. SME-Swarm integration: – Swarm classes serve as wrappers for: –SME model. –SME grid layers. –SME spatial variables. Two-way remote data transfer. Built on SNI simulation server architecture: –

Institute for Ecological Economics Multi-Grid Library Integrates multiple spatial representations Implements space in SME Major Components include: –Cell: Spatially referenced area (or volume) element. –Grid: Distributed set of Cells + links. –Frame: Hierarchy of distributed Grids. –Link: Connection between Cells. Intra-Grid: spatial contiguity. Inter-grid: scaling relations or mappings. –Activation Layer: Subset of Cells in a Frame. –Coverage: Mapping:: Activation Layer -> floats.

Institute for Ecological Economics  Spatial grid partitioned over processors Highly parallel application Recursive N-section: excellent load balancing Fully transparent to user Distributed Processing

Institute for Ecological Economics Model Calibration toolkit Built on MPE toolkit: – Calculate performance measure (MPE) –Estimate of match between model & system. –Weighted sum of tests (Bounds, Theil, Freq, etc). Search parameter space to maximize MPE. –Evolutionary and gradient searches. Params, tests, & searches configured in SME.

Institute for Ecological Economics Example Applications Everglades Landscape Model – Patuxent Landscape Model – Baltimore Ecosystem Study – Great Bay Estuarine Model – Illinois TES Models – IGERT & CoreModels programs

Institute for Ecological Economics CavernSoft Collaborative Environment Environmental Hydrology Applications Team Inputs to multiple models Environmental Modeling Workbench Integrated wireless Sensor web Coupled Bio-Hydro Simulation Spatial Modeling Environment

Institute for Ecological Economics Links components: –Circulation (OM3) –Ecology (SME) –Atmospheric coupling Environmental Hydrology Applications Team Chesapeake Bay Model

Institute for Ecological Economics Environmental Hydrology Applications Team Collaborative Virtual Environment Chesapeake Bay data in CVE with Cave5D/Virtual Director

Institute for Ecological Economics Landuse Evolution and Impact Assessment Model LEAM, University of Illinois at Urbana-Champaign

Institute for Ecological Economics LEAM Framewor k L E A M planning group simulation model drivers randomgeographytransportopen space neighbor- hood economicpopulationsocial landuse change waterairhabitattes fiscalenergywasteenviron sustainable indices impact assessment

Institute for Ecological Economics LEAM Portal

Institute for Ecological Economics Resolution - 1 km (200m for subwatersheds) 2562 grid cells A model in each cell: hydrology nutrients (N, P) vegetation Forcing functions: climatic conditions land use map nutrient loadings from -atmosphere -fertilizers -septics -point sources Patuxent Landscape Model (PLM)

Institute for Ecological Economics State variables and main processes in the landscape model

Institute for Ecological Economics Library of Hydro-Ecological Modules

Institute for Ecological Economics Main Drivers Landuse change - number if cells in different habitat categories and their patterns The total amount of nutrients that is contributed annually from various sources to the watershed. At this time atmospheric deposition is the main source of non-point pollution

Institute for Ecological Economics Results  historical land use in 1650, 1850, 1950, 1972, 1990 and 1997;  a “buildout” scenario based on fully developing all the land currently zoned for development;  four future development patterns based on an empirical economic land use conversion model;  agricultural “best management practices” which lower fertilizer application;  four “replacement” scenarios of land use change to analyze the relative contributions of agriculture and urban land uses; and  two “clustering” scenarios with significantly more and less clustered residential development than the current pattern. We analyzed 18 scenarios including

Institute for Ecological Economics SME Distribution The SME home page: Includes: –Overview. –Technical documentation. –Publications. –Source code (C++ and java). –Links