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Institute for Ecological Economics
Collaborative Spatial Ecological-Economic
Modeling for Sustainable Management of Watershed
ResourcesThomas MaxwellAlexey 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 ModuleEditor
ModuleConstructor
SMML Module Library
ModuleRepository
ModuleBuilder
SimulationDriver
Code Generator
HPC
JavaPortal
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 PanelDocumentation of selected command
Model PanelHierarchical View of model objects
Associated commands as boxes
Command PanelStructure 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:
– http://iee.umces.edu/~villa/swarmsme
• 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:
– http://iee.umces.edu/~villa/sni
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:– http://iee.umces.edu/~villa/svp/
• 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– http://www.sfwmd.gov/org/erd/esr/elm/intro/welcome.htm
• Patuxent Landscape Model– http://iee.umces.edu/PLM
• Baltimore Ecosystem Study– http://baltimore.umbc.edu/lter
• Great Bay Estuarine Model– http://iee.umces.edu/GrBay
• Illinois TES Models– http://blizzard.gis.uiuc.edu/
• IGERT & CoreModels programs
Institute for Ecological Economics
CavernSoft
Collaborative
Environment
Environmental Hydrology Applications Team
Inputs to multiple models
Environmental Modeling Workbench
Integrated wirelessSensor web
CoupledBio-HydroSimulation
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 EconomicsEnvironmental Hydrology Applications Team
Collaborative Virtual Environment
Chesapeake Bay data in CVE with Cave5D/Virtual Director
Institute for Ecological Economics
MMMM
MM
MMMM MMMMMMMMMMMMMMMMMMMMMMMMMM
MM
MMMMMMMMMMMMMM
MMMM
MMMMMMMMMMMMM MM
MMMM
MMMMMMMMMMM MMMMMMMMMMMMMMM
MMMMMMMMMMMMMMMMM
MMMMMM
STELLAª Model
Population
M
EX LANDUSE ALT LANDUSE
CHANGE
LU MAP
EXISTING
DEV PROBABILITY
O CHANGE
OPEN SPACE
OPEN SPACE SWITCH
ECONOMICS
SOCIAL MODEL
UTILITIES
SPONTANEOUS
NEIGHBORS
DEV PROBABILITY
~
ECON TRENDS
DEM
GROWTH TRENDSPLANNING MAP
TRANSPORTATION MODEL
OPEN SPACE SWITCH
Landuse Evolution and Impact Assessment ModelLanduse Evolution and Impact Assessment ModelLEAM, University of Illinois at Urbana-ChampaignLEAM, University of Illinois at Urbana-Champaign
Institute for Ecological Economics
LEAM Framewor
kL E A ML E A ML E A ML E A M
planning groupplanning group planning groupplanning groupsimulationsimulation
model driversmodel drivers
random geography transport open space neighbor-
hood economic population social
landuse changelanduse change
water air habitat tes fiscal energy waste environ
sustainable indicessustainable 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:
hydrologynutrients (N, P)vegetation
• Forcing functions:climatic conditionsland use mapnutrient loadings from
-atmosphere-fertilizers-septics-point sources
Patuxent Landscape ModelPatuxent Landscape Model(PLM)(PLM)
Institute for Ecological Economics
PhotosyntheticBiomass
Surface Water
Unsaturated Water
Saturated Water
PrecipitationEvaporation
Overland flow
Surface -Saturatedexchanges
Percolation& upflow
Groundwaterflow
Transpiration
Infiltration
SnowIce
Non-PhotoBiomass
Runoff
N insediment
Photosynthesis
N onsurface
Detritus
DOM
Translocation
Mortality
Decomposition
Uptake
State variables and main processes in the State variables and main processes in the landscape modellandscape model
Institute for Ecological Economics
Library of Hydro-Ecological Modules
SurfaceHydrology& NutrientTransport
SimulationModule
Markup LanguageSpatial
ModelingEnvironemnt
- SME. . .
. . .
Hydrology
Nutr ientCycling
PlantGrowth
Dead OrganicDecomposition
PhysicalConditions
Local Dynamics
GroundwaterHydrology& NutrientTransport
LanduseChange
CropRotation
Spatial Dynamics
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:
http://www.uvm.edu/giee/SME3/
Includes:– Overview.– Technical documentation.– Publications.– Source code (C++ and java).– Links