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![Page 1: Institute for Ecological Economics Collaborative Spatial Ecological-Economic Modeling for Sustainable Management of Watershed Resources Thomas Maxwell.](https://reader030.fdocuments.in/reader030/viewer/2022032606/56649eac5503460f94bb25c6/html5/thumbnails/1.jpg)
Institute for Ecological Economics
Collaborative Spatial Ecological-Economic
Modeling for Sustainable Management of Watershed
ResourcesThomas MaxwellAlexey Voinov
Robert Costanza
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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
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Institute for Ecological Economics
Three Stage Modeling Process
• Scoping models– Consensus building
• Research models– Understanding dynamics
• Management models– Exploring scenarios
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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.
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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
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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.
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Institute for Ecological Economics
STELLA Model
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Institute for Ecological Economics
Spatial Modeling
Framework
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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.
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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
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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).
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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
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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
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Institute for Ecological Economics
WorkSpace Manager
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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
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Institute for Ecological Economics
Parameter Editor
Edit Simulation Parameters
Spreadsheet format
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Institute for Ecological Economics
Simulation Control
Control Execution
View Model Structure
Trace Dependencies
View Model Equations
Configure Visualization
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Institute for Ecological Economics
SME Python Shell
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Institute for Ecological Economics
Associates DataSets with Viewers
Creates Viewers
Manages DataSets
ViewServer Control Panel
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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
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Institute for Ecological Economics
3D Animation Viewer
Dynamic Landscapes
Variable1 -> Altitude
Variable2 -> Color Mouse controlled
navigation
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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.
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Institute for Ecological Economics
View spatial data Attach to vis panels
Follows animation Export to Stat
packages.
Numerical Spreadsheet
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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
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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.
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Institute for Ecological Economics
Spatial grid partitioned over processors
Highly parallel application
Recursive N-section: excellent load balancing
Fully transparent to user
Distributed Processing
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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.
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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
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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
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Institute for Ecological Economics
• Links components: – Circulation (OM3) – Ecology (SME)– Atmospheric coupling
Environmental Hydrology Applications Team
Chesapeake Bay Model
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Institute for Ecological EconomicsEnvironmental Hydrology Applications Team
Collaborative Virtual Environment
Chesapeake Bay data in CVE with Cave5D/Virtual Director
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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
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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
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Institute for Ecological Economics
LEAM Portal
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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)
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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
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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
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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
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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
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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