George H. Leavesley & O. David The Object Modeling...
Transcript of George H. Leavesley & O. David The Object Modeling...
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The Object Modeling System Framework for Water- and Environmental-Model Development and Application for Resource Management
George H. Leavesley & O. David
Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO; U.S. Geological Survey, Denver, CO (retired)
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STARTING POINTS
• There are no universal models• Models for different purposes require different levels of detail and comprehensiveness
• Appropriate model process conceptualizations are a function of problem objectives, data constraints, and spatial and temporal scales of application
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Modeling Conundrum
• Experimental science builds on hypothesis testing and interpretation based on earlier published hypotheses and results
• Modelers tend to build from the ground up because existing models are not well designed for incremental improvement by others
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Object Modeling System (OMS)
•Provide a common framework for model development and operational applications
•Facilitate the integration of multi-disciplinary modeling approaches for use in addressing complex, multi-objective, resource-management problems
•Provide a toolbox-approach to the development of resource-management, decision-support systems
Integrated systems of computer software developed to:
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Object Modeling System (OMS)
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•Modular Modeling System (MMS)• Object Based• C and Java Language Framework• Fortran, C module support• Windows environment
•Object Modeling System (OMS)• Object Oriented• Java Language Framework• Java, C, C++, Fortran module support• Platform independent
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TOOL BOX MODELING VIEWS
• Research Model Developer Complex Detail• Application Model Developer• Model User• Resource Manager• Policy Maker Condensed Analysis
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LEVELS OF MODULAR DESIGN
• PROCESS• MODEL• FULLY COUPLED MODELS• LOOSELY COUPLED MODELS• RESOURCE MANAGEMENT DECISION SUPPORT SYSTEMS
• ANALYSIS AND SUPPORT TOOLS
Single Purpose
Multi-objective, Complex
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LEVELS OF MODULAR DESIGN
• PROCESS• MODEL• FULLY COUPLED MODELS• LOOSELY COUPLED MODELS• RESOURCE MANAGEMENT DECISION SUPPORT SYSTEMS
• ANALYSIS AND SUPPORT TOOLS
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Module / Component Library
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CRITERIA AND RULES FOR GOOD MODULE DESIGN
• relate directly to real world components or processes• have input and output variables that are measurable values
• communicate solely via these input and output variables
Modules should
Reynolds J.F., and Acock, B., 1997, Modularity and genericness in plant and ecosystem models: Ecological Modeling 94, p 7-16
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PRMS
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Model Building Tools
MMS
OMS
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Time – Space – Process Configurations
TimeSpace
Space
Processes
Processes
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LEVELS OF MODULAR DESIGN
• PROCESS• MODEL• FULLY COUPLED MODELS• LOOSELY COUPLED MODELS• RESOURCE MANAGEMENT DECISION SUPPORT SYSTEMS
• ANALYSIS AND SUPPORT TOOLS
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Ground Water-Surface Water Coupling
MODFLOW
PRMS
SFR2
UZF1
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GSFLOW -- Coupled PRMS, MODFLOW, SFR, and Unsaturated Zone Models
Streamflow
Unsaturated Zone Model:
PRMS to UZF UZF to MODFLOW
PRMS to SFR2
PRMS to MODFLOW
MODFLOW to SFR2
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LEVELS OF MODULAR DESIGN
• PROCESS• MODEL• FULLY COUPLED MODELS• LOOSELY COUPLED MODELS• RESOURCE MANAGEMENT DECISION SUPPORT SYSTEMS
• ANALYSIS AND SUPPORT TOOLS
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LOOSELEY COUPLED MODELS
Watershed Model
Hydraulics Model
Database
Fish ModelData Management Interface (DMI)
Modular ModelOff-the-shelf Model
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LOOSELEY COUPLED MODELS
Watershed Model
Hydraulics Model
Database
Fish ModelData Management Interface (DMI)
MMS Model
Off-the-shelf Model
Model Management Interface (MMI) [XML]
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LOOSELEY COUPLED MODELS
Watershed Model
Hydraulics Model
Fish Model
PRMS
Habitat Suitability Index
Channel Geometry Analysis Program (CGAP)
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Aquatic Habitat Models
Watershed Model
Hydraulics Model
Fish Model
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Aquatic Habitat Models Results
ft2
ft3/s
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LEVELS OF MODULAR DESIGN
• PROCESS• MODEL• FULLY COUPLED MODELS• LOOSELY COUPLED MODELS• RESOURCE MANAGEMENT DECISION SUPPORT SYSTEMS
• ANALYSIS AND SUPPORT TOOLS
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RiverWare – Lower Colorado River
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Upper Gunnison River DSS
HydrologicDatabase
HydrometReal-time climate data feed
RiverWareReservoir and River SystemOperations Model
DMI
DMI
DMI
Object User InterfaceInterface for data visualizationand modeling Modular Modeling
SystemPrecipitation/Runoff Model (PRMS)
DMI
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OBJECT USER INTERFACE (OUI)
• Java based, modular interface• Data retrieval and management• Visualization of data and model parameters• Model output analysis and visualization• Model animation• Manage single and multiple model runs• User definable using Xml
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OBJECT USER INTEFACE (OUI)
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3-D Animation
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OBJECT USER INTEFACE (OUI)
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LEVELS OF MODULAR DESIGN
• PROCESS• MODEL • FULLY COUPLED MODELS• LOOSELY COUPLED MODELS• RESOURCE MANAGEMENT DECISION SUPPORT SYSTEMS
• ANALYSIS AND SUPPORT TOOLS
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Simulation 1.1
Data
Resampled DEMFilled DEM
nhru
Processed
Model Input
Model Output
GIS ParametersRaw
Processed
Model Dimension
Flow Direction
DEMLULC
Analysis
Model
Executables
Run ModesOMSESPLUCA…
PRMS
VegSoil
…
QC Climate Data…
ntemp
nmonths
AttributesMaps…
hru_slope
hru_elev
GIS Attribute
Derivation Equation
GIS Attribute…
GIS Attribute
Derivation Equation
pkwater_equiv
soil_moist
…
…
Climate Data
transp_beg
…
hru_psta
ProcessedAttributesMapsGIS Parameters
Driving Datatsta_elev
GIS Attribute
Derivation Equation
tmaxtmin
Non-GIS Parameters
dday_slopejh_coef
…
Model OutputMonthly Streamflow Monthly Precip…
… (multidimensions)
Derivation Equation
Non-GIS parameters
Model Input
Model Input
Modeling Process
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GIS WEASEL
Delineation:•Only requires elevation Grid as input
•Interactively delineate •Area of Interest•Many kinds of features
•Streams•Elevation bands•Landuse•Contributing areas•Topographic index•……
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Vegetation Type (USFS)
Vegetation Density (USFS)
Land Use-Land Cover (USGS)
DIGITAL DATABASES STATSGO Soils (USDA)
Satellite SW Radiation (U Md)
Monthly PET
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AUTOMATED PARAMETER ESTIMATION
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GIS WEASEL
Parameterization:•200+ methods available•Easily add custom methods
•Configure recipes•Apply to feature maps
•Exploit many types of data•Produce maps and ASCII files of parameters
+
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ProjectBrowser
SimulationNavigator
Data Table
EquationBox
MapWindow
HRU 15Selected
Data Table Filters
TimeSlider
Integrated Modeling and Visualization Tools
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GeoWind
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Visualization and Analysis Tool
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ANALYSIS and SUPPORT TOOLS
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Multi-step Calibration
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Luca -
Hay and Umemoto, 2006, Multiple-Objective Step-Wise Calibration using Luca: U.S. Geological Survey OFR 2006-1323.
Multiple-Objective Step-Wise Calibration Tool
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Statistical and graphical sensitivity and uncertainty analysis tools
Sensitivity and Uncertainty Analysis
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Forecast Methodologies
- Historic data as analog for the future Ensemble Streamflow Prediction (ESP)
-Synthetic time-series Weather Generator
- Atmospheric model output Dynamical Downscaling
Statistical Downscaling
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Ensemble Streamflow Prediction
Using history as an analog for the future
Simulate to today
Predict future using historic data
Probability of exceedence
NOAA
USGS
BOR
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MMS ESP Tool
Manager selected 10, 50, and 90 % probability of exceedance
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ESP Trace Analysis
• Ensemble Streamflow Prediction (ESP) Tool
• Statistical analysis• Report generation
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Graphical Analysis Tools•Canned analysis configurations
•Analysis of output data• Graphs
• TimeSeries Plot• XY Error• Flow duration• Residuals
• Statistics•Table IO/API
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Integrated Adaptive-Modeling and Decision-Support System Summary
•Facilitates multi-disciplinary integration of models and tools to address the issues of water and environmental-resource management.•Allows rapid evaluation of the effects of decision and management scenarios.•Allows incorporation of continuing advances in physical, social, and economic sciences. •Provides an effective means for sharing scientific understanding with stakeholders and decision makers. •Open source software design allows many to share resources, expertise, knowledge, and costs.
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FOCUS ISSUES ARE ADDRESSED THROUGH COLLABORATIVE MULTI-DISCIPLINARY EFFORTS
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UNIVERSITY COLLABORATION• University of Colorado
• NOAA funded -- Coupling of hydrologic and atmospheric models to provide short- to long-term forecasts
• Colorado State University• Interagency MOU funded – OMS, Parameter estimation,
optimization, and sensitivity analysis tools
• Friedrich Schiller University• Collaborative funding – Watershed process modules and
modular modeling frameworks
•University of Trento• EU funding – Training, Geotop, NewAge, JGrasstools
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Water Supply Forecasts
Distributed by the Natural Resources Conservation Service (NRCS)
http://www.wcc.nrcs.usda.gov/wsf
Combined product of NRCS and National Weather Service Forecasts
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Working with the Natural Resources Conservation Service (NRCS) to develop a streamflow forecasting toolbox using OMS and PRMS
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The USDA Conservation Effects Assessment Project (CEAP)
A Cooperative Effort to Assess Environmental Effects and Benefits from Conservation
Programs at National and Watershed Scales
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U.S. MULTI-AGENCY MEMORANDUM OF UNDERSTANDING
❑ Nuclear Regulatory Commission (NRC)
❑ Army Corp of Engineers (COE)
❑ US Geological Survey (USGS)
❑ NOAA❑ Department of
Homeland Security
Facilitates cooperation in R&D of multi-media environmental models, frameworks, and databases for use in human and environmental health risk assessment
❑ Environmental Protection Agency (EPA)
❑ Department of Energy (DOE)❑ US Agricultural Research
Service (ARS)❑ Natural Resources
Conservation Service (NRCS)
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Website Information http://sites.google.com/a/environmental-modeling.org/environmental-modeling/Home
• MOU and addendums• Workshop proceedings• ISCMEM meeting minutes• Working group proposals/plans• Announcements of upcoming meetings
• Contact info
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International Collaboration
• Friedrich Schiller University, Jena, Germany• Chinese Academy of Sciences, Geography and Natural Resources Institute, Beijing
• Chinese Academy of Sciences, CARRERI, Lanzhou• International Atomic Energy Agency, Vienna• University of Bodenkultur, Vienna, Austria• Public Works Research Institute, Japan• Korean Water Resources Corp., South Korea• International Water Management Institute, Sri Lanka• University Trento, Italy
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OMS Summary ision-Support System Toolboxes that:
•Facilitate multi-disciplinary integration of models and tools to address the issues of water and environmental-resource management.•Allow rapid evaluation of the effects of decision and management scenarios.
•Allow incorporation of continuing advances in physical , social, and economic sciences.•Provide an effective means for sharing scientific understanding with stakeholders and decision makers. •Are open source.
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Chicken Soup for the Modeling Soul
“A fool with a tool is still a fool.”
System Development magazine
POINT
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OMS3 Overview
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Object Modeling System• Reduce redundancy in model development• Improve model code quality• Simplify model technology transfer• Allow simulation traceability, support auditing• Improve model maintainability• Flexible use and rigorous testing of models• Allow flexible change in science• Open source
• Software Framework for Environmental Modeling• “Science building blocks”
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Optimization
TemporalSpatial
ETP
Inter-ception
Snow
Soil-water
Ground-water
SS RO
GW Flow
SurfaceRO
Irrigation
Erosion
Surfacewater use
Groundwater use
Plantgrowth
Stream RO
System Components
Calibration
Sensitivity
Science Components
Erosion
Plant Growth
Groundwater
Water Quality
ET
Uncertainty
Visualization Reporting
Component Based Model
Control
Statistics
Time
Space
Data IO
OMS Principal Architecture
....
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OMS3 Features• Lightweight, non-invasive, component-based modeling framework
• Dataflow driven, Multithreaded execution• Multi-language support• Conversions / Transformation SPI • (Ontologies)• DSLs for Simulations, Calibration, Uncertainty, and Sensitivity analysis
• Auditing, Traceability, Doc generation• EMF interoperability
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History of the OMS development
2001/02 2003/04 2005/06 2007/09 2010/12/13
Netbeans PlatformRefactoringCentral Version ControlStandardize Component API
PRMS - Prototype
Modeling ProjectsUSDA CoLab Use Project Plan/Process
PRMS WSFCEAP
Initial PrototypeSwing based
Calibration ToolsSensitivity AnalysisUncertainty AnalysisData ProvisioningAgency Governance
J2000(S), PRMS WSF,WWEM, Range,
OMS3COSUCSIPCloud ComputingParallelization
CEAP-AgEs, AgesUI,PRMS WSF, WWEM, Range,McCabe MWBWASP-Hydrus 1DHymod, (GeoTop)IAEARusle2
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OMS3 and other IMFs
Jaegers B. et al., 2010 Proc IEMSS, Ottawa, Canada
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OMS Console Versions
1.0
2.2
3.0
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Example Measures McCabe WBM
Language/Framework
TotalLOC
AverageCC/method
TotalCC
FORTRAN only 244 3.33 40OMS 3.0 Java 295 2.38 31
Java only 319 2.85 37C++ only 405 2.41 41
OMS 2.2 Java 450 1.18 103ESMF 3.1.1 C 583 1.97 65ESMF 3.1.1 FORTRAN 683 1.44 56
OpenMI 1.4 Java 880 1.61 116CCA 0.6.6 Java 1635 2.25 276
[Lloyd, 2011]
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Components / Model
Simulations
Java / FORTRAN / C / C++
DSL (Groovy/Java)
Main OMS3 concepts
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Component Class Design
Modeling Component = POJO + Annotations
Meta data provide execution control and connectivity, execution support, and documentation/repository support
Plain Old Java Object
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POJOSimple example “plain old java object” POJO
public class CircleArea {
public double radius; public double area;
public void runme() { area = Math.PI * radius * radius; }
}
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POJO + AnnotationsSimple example component with annotated I/O fields .
public class CircleArea {
@In public double radius; @Out public double area;
@Execute public void runme() { area = Math.PI * radius * radius; }
}
Tag the fields being used for input and output with @In and @Out Fields can have any data type (primitive, custom, or parameterized
types) and should be public.No arguments for @In and @OutRequired Meta dataApplies similar to languages such as FORTRAN, C, C++
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Building Models
pgs: PlantGrowthStress
intc : Interception
hruhru
…out2in(intc, “hru”, pgs);…
class GroundwaterN { @Out public HRU hru; ...}
class PlantGrowthStress { @In public HRU hru; ...}
… out2in, field2in, out2field, feedback, ..
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Annotations
@Description@Author@Bibliography@Status@VersionInfo@SourceInfo@Keywords@Label
@Description
@Unit@In@Out@Range@Role@Bound@Label
@Execute@Initialize@Finalize
Component Field Method
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Simulation Editor
Console Output
Toolbar
Project DirectorySimulation Tabs
Status Line
Toolbar
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Table View (Filter for ‘nhru’ dimensioned parameter)
Statistics on Selection
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Output folder
Analysis tabs
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Auto Documentation
•Docbook5 • Model meta data• Components meta data• Parameter sets• Simulations
•Docbook5 →• PDF• HTML• DOC(X)• …
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Components / Model
Simulations
Java / FORTRAN / C / C++
DSL (Groovy/Java)
Main OMS3 concepts
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DSLs for simulation• Lightweight model ‘orchestration’ layer• Based on language level Builder Pattern • Descriptive and programmatic• Scalable for various modeling applications• Flexible, domain expert can understand it
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Simulation DSL●Descriptive expression of simulations ●Thin layer on top of simulation engines●Language scripts vs. DSLs, dividing line?
Other Application Examples●Anti-malaria drug resistance simulations●Insurances, Financial Institutions, Loan processing●Nuclear safety simulations
DSL -> Simulation DSL
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Simulation
Simulation
Model
ComponentComponent
OutputDescriptor
Parameter
Resources
Connectivity
Analysis
Simulation = Executable Model + Input Data +
Execution Method + Context +
Input management
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sim{} elements
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Creating and Connecting Sim s = new Sim(); s.setName(“Drake"); s.setTiming(true); s.setSanitychecks(false); OutputDescriptor o = new OutputDescriptor(); o.setDir(work + "/output"); o.setScheme(SimConst.SIMPLE); s.setOutputDescriptor(o); Model m = new Model(); m.setClassname(“ages.Main"); s.setModel(m); Params p = new Params(); p.setFile(work + "/data/drake.csv"); m.setParams(p); ….
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Configuring Sim s = new Sim(); s.setName("Drake"); s.setTiming(true); s.setSanitychecks(false); OutputDescriptor o = new OutputDescriptor(); s.setOutputDescriptor(o);
o.setDir(work + "/output");o.setScheme(SimConst.SIMPLE);
Model m = new Model(); m.setClassname(“ages.Main");
s.setModel(m); Params p = new Params(); p.setFile(work + "/data/drake.csv");
m.setParams(p); ….
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Language Noise import oms3.dsl.*; import oms3.*;
Sim s = new Sim(); s.setName(“Drake"); s.setTiming(true); s.setSanitychecks(false); OutputDescriptor o = new OutputDescriptor(); s.setOutputDescriptor(o); o.setDir(work + "/output"); o.setScheme(SimConst.SIMPLE); Model m = new Model(); m.setClassname(“ages.Main"); s.setModel(m); Params p = new Params(); p.setFile(work + "/data/drake.csv"); m.setParams(p); ….
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Simulation Builder sim(name:“Drake", timing:true, sanitychecks:false) { outputstrategy(dir:"$work/output", scheme:SIMPLE) model(classname:"ages.Main") { parameter (file:"$work/data/drake.csv") }}
• Creation via DSL key words• Containment handled via scopes• Configuration via properties• No “language noise”
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Language level Builder Pattern
• Simple mechanism to create a tree-structured graph• Syntax – level builder pattern (GoF)• Internally: Chained method invocation, closures, parentheses omission
• Existing Builders• Object Graphs, HTML, Swing, Ant, CLI, JMX, …
-> Simulation Builder
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Sim (1)sim(name:"Efcarson") { // workspace directory def work = System.getProperty("oms3.work");
// define output strategy: output base dir and // the scheme NUMBERED|SIMPLE|DATE outputstrategy(dir:"$work/output", scheme:NUMBERED)
// for class loading: model location resource "$work/dist/*.jar"
// define models model(classname:"model.PrmsDdJh") { // parameter parameter (file:"$work/data/efcarson/params.csv") { inputFile "$work/data/efcarson/data.csv" outFile "out.csv" sumFile "basinsum.csv" out "summary.txt" startTime "1980-10-01" endTime "1986-09-30" }
logging { "Strmflow" "INFO" } } // …
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Sim (2) ... //model efficiency (optional) efficiency(obs:"runoff[0]", sim:"basin_cfs", methods:NS+ABSDIF+RMSE, file:"sum1.txt")
// compute some summary for runoff 'on-the-fly' (optional) summary(time:"date", var:"basin_cfs", moments:MEAN+MIN, period:MONTHLY, file:"sum.txt") summary(time:"date", var:"basin_gwflow_cfs", moments:MEAN+MIN+MAX+LAG1, period:YEARLY, file:"sum.txt")
output(time:"date", vars:"basin_gwflow_cfs,basin_cfs,runoff[0]", fformat:"7.5f", file:"out1.csv")
analysis(title:"Simulation Output") { timeseries(title:"East Fork Carson", view: COMBINED) { // view: COMBINED | MULTI | STACKED x(file:"%last/out1.csv", column:"date") y(file:"%last/out1.csv", column:"basin_cfs") calc(eq:"sim - obs") { sim(file:"%last/out1.csv", column:"basin_cfs") obs(file:"%last/out1.csv", column:"runoff[0]") }
y(file:"%last/out1.csv", column:"runoff[0]") } }
}
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Ensemble streamflow prediction: espesp(name:"EFCarson") { def work = System.getProperty("oms3.work");
// define output strategy: output base dir and // the strategy NUMBERED|SIMPLE|DATE outputstrategy(dir: "$work/output", scheme:NUMBERED)
// for class loading: model locations resource "$work/dist/*.jar"
// define model model(classname:"model.PrmsDdJh") { //.. }
// the number of forecast days after the end of the simulation period forecast_days 15 // forecast_end "1984-10-15"
// historical years for to be used for traces // years are inclusive first_year 1981 last_year 1983 analysis(title:"Trace analysis") { // relative path name, last output esptraces(title:"test 2", dir:"%last", var:"basin_cfs") }}
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Mixing Scripts / DSL// list of watersheds to analyzewatersheds = ["YampaStmBt", "East", "Animas"]
/////////////////// Implementation
// base output folder for todays runtoday = new File(batch_out, SimConst.now(date_pattern))
// create a simulation builder for all watershedssim = new SimBuilder().esp(name:"ALL") { analysis(title:"Batch trace analysis: $today") { watersheds.each { esptraces(title:it, dir:"$today/$it/out", var:"basin_cfs",
report:"$today/${it}.txt") } }}
sim.graph()
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OMS3 Simulations•Simulations = Model applications with data•Calibration
Shuffled Complex Evolution(SCA) Dynamically Dimensioned Search (DDS), LUCA (MO SCE),
•Sensitivity Analysis Morris Screening, Extended FAST, ..
•Uncertainty Analysis • GLUE, Bayesian Monte Carlo,…
•Forecasting • Ensemble Streamflow Prediction
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featurerich scripting editor:● simulation templates● syntax coloring for
OMS3● command completion on
modules ● editor features like word
completions, find, replace, IDE-like shortcuts for advanced and faster usage
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