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06/12/2022 Department of Civil, Architectural & Environmental Engineering 1 Development of a Hydrologic Community Modeling System Using a Workflow Engine 6/12/22 BO LU Drexel University Committee Dr. Michael Piasecki Dr. Ilya Zaslavsky Dr. Mira Olson Dr. Franco Montalto Dr. Jonathan Goodall

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Page 1: Presentation   for slideshare

Department of Civil, Architectural & Environmental Engineering 104/12/2023

Development of a Hydrologic Community Modeling System Using a Workflow Engine

April 12, 2023

BO LU

Drexel University

Committee

Dr. Michael Piasecki

Dr. Ilya Zaslavsky

Dr. Mira Olson

Dr. Franco Montalto

Dr. Jonathan Goodall

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Department of Civil, Architectural & Environmental Engineering04/12/2023 1

Let’s imagine…

Data

Model

Tool Model

Model

Model

ModelData

Data

Data

Data

Tool Tool

Tool

Tool

Tool

Model

DataModel

Model

Data

Tool

Model/Module

Data/Data access

Tools of transformation, analysis, display etc.

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Let’s imagine…

Data

Model

Tool Model

Model

Model

ModelData

Data

Data

Data

Tool Tool

Tool

Tool

Tool

Model

DataModel

Data

Data

Model

Model

Data

Tool

Model/Module

Data/Data access

Tools of transformation, analysis, display etc.

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Let’s imagine…

Data

Model

Tool Model

Model

Model

ModelData

Data

Data

Data

Tool Tool

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Tool

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DataModel

Data

Data

ModelTool Tool

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Model

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Model/Module

Data/Data access

Tools of transformation, analysis, display etc.

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Department of Civil, Architectural & Environmental Engineering04/12/2023 1

Let’s imagine…

Data

Model

Tool Model

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ModelData

Data

Data

Data

Tool Tool

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ModelTool Tool

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Data

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Model/Module

Data/Data access

Tools of transformation, analysis, display etc.

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Department of Civil, Architectural & Environmental Engineering04/12/2023 1

Let’s imagine…

Data

Model

Tool Model

Model

Model

ModelData

Data

Data

Data

Tool Tool

Tool

Tool

Tool

Model

DataModel

Data

Data

ModelTool Tool

ToolModel

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Data

Tool

Model/Module

Data/Data access

Tools of transformation, analysis, display etc.

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Department of Civil, Architectural & Environmental Engineering04/12/2023 1

Let’s imagine…

Data

Model

Tool Model

Model

Model

ModelData

Data

Data

Data

Tool Tool

Tool

Tool

Tool

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Model/Module

Data/Data access

Tools of transformation, analysis, display etc.

Objective: Develop a Hydrologic Community Modeling System(HCMS) that allows constructing seamlessly integrated hydrologic models with swappable and portable modules.

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04/12/2023 Department of Civil, Architectural & Environmental Engineering 2

Technical Issues

Migration of legacy models

Model Integration

Data Interoperability

Lack of modular model structure

Poor documentation of source codes

Lack of credibility of the algorithms or methods encapsulated in the codes

Lack of “good coding practices”

Intertwining of user interfaces and computing kernels

Incompatible programming languages

Distinct input and output data structures of models

Distinct data models undertaken by disparate data sources

Data semantics

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What can facilitate this development?

Model standard or protocol: standard interfaces that component models should comply with, description of model structure, data model etc.

Coupling Frameworks and Workflow Engines

Facilities: tools that ease the development of component models or the migration of legacy models. Data analysis tools, transformation tools etc.

Workbench: a platform for model linkage, execution and management, usually supports graphical, icon-based model construction.

Our choice: Microsoft’s TRIDENT workflow engine

How well a workflow engine can facilitate the development of community modeling system?

Programming background

Supporting high-performance computations and provenance capture.

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Issues in development

Will the auxiliary platform be convenient to use? Does it involve a steep learning curve?

Will its run-time performance be affected when migrating a legacy model into the environment?

Will the developed hydrologic community modeling system be flexible to use?

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Development of a Hydrologic Community Modeling System (HCMS) using TRIDENT workflow engine

TRIDENT

Data Access Lib.

Data Process Lib. Hydrologic Model Lib.

Analysis&Utilities Lib.

Get data from online repositories(CUAHSI HIS, NLDAS, MPE, USGS NED, NLCD, SSURGO etc.)

Get data from local repository, e.g. NetCDF, Excel, SQL Database… Time series data

processing: temporal interpolation, unit conversion…

Geospatial data processing: watershed delineation, land cover\soil data processing…

Evapotranspiration

Runoff Yield

Direct Runoff Routing

Base Flow

Channel Routing

Model Performance Analysis: Water balance check, simulated vs. observed hydrograph comparison, performance statistics… Result Storage &Visualization

Seamless Integration

SWAT

TOPMODEL

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workflows(.xoml)

invoke

Workflows (.wfl)

myExperiment website

Publish : workflows

Supported Services

Management Studio

TRIDENT SQL DATABASE

Message Passing Service

Schedule Execution Service

Provenance Recording Service

Interactive Execution Service

workflows(.twp)

Workflow Composer Workflow Application WORD Add-in

• Composing, execut-ing, monitoring and recording workflows

• Managing workflows, activities, users, work-flow provenance

• Scheduling workflow execution

• Running multiple work-flows on different nodes of a server clus-ter

• Executing a workflow on its located server

• Loading/running workflows from local/remote data-base

• Embedding and run-ning workflows in Word documents

• Loading/running workflows from local/remote data-base

• Loading/running workflows from local/remote data-base

Activities(.dll)

Standard Classes

What is TRIDENT?

A workflow engine that facilitates composing, executing, archiving and sharing scientific workflows.

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Why use TRIDENT in hydrologic modeling?

Allowing parallel or concurrent execution, distributed computations in the GRID environment.

Recording who, how, what and which resources are used in a work-flow, and the derivation flow of data products. It ensures repeatability of model executions.

Sharing workflow through publication mechanisms or repositories.

Allowing automatic and holistic execution without any external in-tervenes, or alternatively, interactive execution with the control of users.

Composing workflows with swappable activities via the drag-and-drop manner on a GUI.

Interactive/Non-interactive Execution

Easy to Share

Flexible Model Setup

High-performance Computing

Provenance Capture

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Introduction of the libraries of HCMS

Data Access Library

Data Processing Library

Hydrologic Model Library

Post-Anaylysis & Utilities Library

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1.Data Access Library

Data Sources:

Acronym Data Availability Data Scale Web Sites

USGS NED National Elevation Data, accessed via “Application Services”

1,1/3,1/9 arc second http://seamless.usgs.gov/app_services.php

USGS NLCD National Land Cover Data, accessed via “Application Services”

30m*30m http://seamless.usgs.gov/app_services.php

NRCS SSURGO Soil survey spatial and tabular data, accessed via Soil Data Access web services

Currently only restricted areas.

http://sdmdataaccess.nrcs.usda.gov/

NLDAS-2 Meteorological data (temperature, precipitation, radiation etc), accessed via FTP

1/8 degree1979.1-present,1hr

ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/

NWIS MPE Multi-sensor Precipitation Estimates, accessed via FTP

4km*4km2005.01.01-present,24hr

http://water.weather.gov/precip/p_download_new/

CUAHSI HIS Hydrological and Meteorological data, accessed via WaterOneFlow web services from multiple data servers

Mostly time series data, varied temporal scale

http://water.sdsc.edu/wateroneflow/

EPA Geospatial Data

National Hydrography Dataset(watershed and stream shapefiles), accessed via EPA Geospatial services

Medium and High resolutions

http://www.epa.gov/waters/geoservices/index.html

Retrieving data from following data sources using SOAP/FTP protocols .

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Get National Elevation Data(NED), National Land Cover Data (NLCD)

NED: [1, 1/3, 1/9 arc second], [ ArcGrid, GeoTIFF, GridFloat, BIL]

NLCD: 30m * 30m, GeoTIFF

[Activity 1] — Access NED or NLCD data within a specified area via Application Services.

[Activity 2] — Decompress downloaded data files.

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Get National Elevation Data(NED), National Land Cover Data (NLCD)

NED: [1, 1/3, 1/9 arc second], [ ArcGrid, GeoTIFF, GridFloat, BIL]

NLCD: 30m * 30m, GeoTIFF

[Activity 1] — Access NED or NLCD data within a specified area via Application Services.

[Activity 2] — Decompress downloaded data files.

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Get National Elevation Data(NED), National Land Cover Data (NLCD)

NED: [1, 1/3, 1/9 arc second], [ ArcGrid, GeoTIFF, GridFloat, BIL]

NLCD: 30m * 30m, GeoTIFF

[Activity 1] — Access NED or NLCD data within a specified area via Application Services.

[Activity 2] — Decompress downloaded data files.

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Get NASA Land Data Assimilation System(NLDAS-2) Data

[Activity 1] — Download hourly data files(GRIB) from NLDAS-2 data server. ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/NLDAS_FORA0125_H.002/

[Activity 2] — Make a choice of fields from a given field list, the activity then extracts data of selected fields from the downloaded data files via a decoder “WGRIB”.

[Activity 3] — Cut gridded data set within a specified geospatial extent.

National coverage, 0.125*0.125 degree (approximately 13.8km), 1979-present, 1-hour time interval. Temperature, Precipitation, Long wave/Short wave radiation, Pressure, Vertical/Horizontal wind speed etc.

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Get NASA Land Data Assimilation System(NLDAS-2) Data

[Activity 1] — Download hourly data files(GRIB) from NLDAS-2 data server. ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/NLDAS_FORA0125_H.002/

[Activity 2] — Make a choice of fields from a given field list, the activity then extracts data of selected fields from the downloaded data files via a decoder “WGRIB”.

[Activity 3] — Cut gridded data set within a specified geospatial extent.

National coverage, 0.125*0.125 degree (approximately 13.8km), 1979-present, 1-hour time interval. Temperature, Precipitation, Long wave/Short wave radiation, Pressure, Vertical/Horizontal wind speed etc.

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Get NWS Multi-sensor Precipitation Estimates (MPE)

National coverage, 4km*4km, 2005-present, 1-day time interval.

[Activity 1] — Download 24-hour data files(NetCDF) from NWS MPE data server. http://water.weather.gov/precip/p_download_new/

[Activity 2] — Parse precipitation data from downloaded NetCDF files, and export them in the format of standard arrays.

[Activity 3] — Cut gridded data set within a specified geospatial extent.

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Get Data via WaterOneFlow web services

Semantic Checking… Get Web Services In Box

Verify Variable Catalog

HIS Central Metadata WS

WaterOneFlow WS

Ontology Dictionary

Get Time Series Data

Parse

WaterMLVariable Codes

Get Variables

UI

Time Series Data/Metadata

Variable Name (e.g. precipitation)

Geographical Extent (watershed boundary or latitude/longitude )

Service ID (optional)

Get Sites

Temporal Extent

Sites Metadata

Web Service IDs Updated Variables

Processing Step Web ServiceConfiguration Input Output

WaterOneFlow: a family of web services developed by CUAHSI using the SOAP protocol. It facilitates retrieving hydrologic and meteorological observation time series data from a central metadata catalogue

(HISCentral located at the San Diego Supercomputer Center) which holds the richest metadata information in the world for water data.

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Get Data via WaterOneFlow Web Services in TRIDENT

[Activity 1] — Get web services within a specified geospatial extent.

[Activity 2] — Get site and variable metadata based on given variable name.

[Activity 3] — Get time series data of given variable within the given geospatial extent.

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Get SSURGO Soil Data & Get EPA

Accessing geospatial soil data via Soil Data Access(SDA) web services, currently only for small areas.

Accessing National Hydrography Dataset( watershed and stream shapefile) via EPA Geospatial Services.

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2. Data Processing Library

Geospatial Data Processing

Time Series Processing

Data processing customized for data sources

Delineate watershed/sub-watershed boundary, Generate river network; Create Triangulated Irregular Network(TIN); Process Soil, Land Cover data; Create Hydrologic Response Unit (HRU).

Interpolation/Extrapolation, Unit Conversion.

Aggregate NLDAS-2, MPE gridded data for sub-watersheds.

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DEM Processing

Perform DEM processing step by step — based on the procedures deployed in the Terrain Analy-sis Using Digital Elevation Models (TauDEM)

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DEM Processing

Perform DEM processing step by step — based on the procedures deployed in the Terrain Analy-sis Using Digital Elevation Models (TauDEM)

Locate the outlet

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Geospatial Data Processing

Perform DEM processing and TIN generation via WPS web services

Client

Watershed Delineation

Watershed Triangulation

WPS web ser-

vices

• DEM Processing - Delineate watershed

boundary - Generate river system - Divide subbasins

• TIN Generation -Delaunay Triangulation

Server

• WPS(OpenGIS ® Web Processing Service) provides rules to standardize inputs and outputs for geospatial processing services, and to request execution of a process and handle output from the process.

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Geospatial Data Processing

Perform DEM processing and TIN generation via WPS web services

Client

Watershed Delineation

Watershed Triangulation

WPS web ser-

vices

• DEM Processing - Delineate watershed

boundary - Generate river system - Divide subbasins

• TIN Generation -Delaunay Triangulation

Server

• WPS(OpenGIS ® Web Processing Service) provides rules to standardize inputs and outputs for geospatial processing services, and to request execution of a process and handle output from the process.

via Local activities

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Creating Hydrologic Response Unit

Step 1: Processing SSURGO Soil Data

For soil data accessed via SDA web service

For soil data accessed via Soil Data Mart

Simplify soil groups to A, B, C, D (Optional)

(1) Merge map units based on hydro groups

(2) Clip the shapefile with watershed boundary

(1) Merge map units for each county-based shapefile

(2) Merge county-based shapefiles

(3) Clip the merged shapefile with watershed boundary

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Creating Hydrologic Response Unit

Step 2: Processing Land Cover Data

Step 3: Create HRU Default Land Cover Classification Original Land Cover Classification

New ID Type ID Type

1 Water11 Open Water90 Woody wetlands95 Emergent herbaceous wetlands

2 Medium Residency

21 Developed, open space22 Developed, low intensity23 Developed, medium intensity24 Developed, high intensity

3 Forest41 Deciduous forest42 Evergreen forest43 Mixed forest

4 Agriculture

31 Barren land52 Shrub/scub71 Grassland/herbaceous81 Pasture/hay82 Cultivated crops

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Processing Time Series Data

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Processing NLDAS-2, MPE Gridded data

Aggregate Gridded Data for (sub-)Watersheds

• For NLDAS-2 gridded data • For MPE gridded data

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Processing NLDAS-2, MPE Gridded data

Aggregate Gridded Data for (sub-)Watersheds

• For NLDAS-2 gridded data • For MPE gridded data

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3. Hydrologic Model Library – TOPMODEL

TOPMODEL A physically based, semi-distributed watershed model that simulates hydrologic fluxes.

[Activity 1] — Compute Topographic Index Histogram for the whole watershed or each sub-basin.

[Activity 2] — Compute Area-Distance Histogram for routing flow.

[Activity 3] — Interactive activity for inputting/modifying initial condition and parameters.

[Activity 4] — TOPMODEL computation kernel.

The VB version converted from 9502 FORTRAN version is migrated into the following workflow.

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3. Hydrologic Model Library – SWAT

The hydrology component in SWAT is based on the water balance equation in the soil profile and simulates pro-cesses including canopy interception, snow melt, infiltration, surface runoff, evapotranspiration, lateral flow and perco-lation. Source codes: SWAT 2005 version

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Main Stream

Individual Hydrologic Methods

Hydrologic processes Methods

Potential Evapotranspiration

Penman-Monteith method

Thornthwaite method

Priestly-Taylor method

Hargreaves method

Runoff YieldSCS Curve Number

Green&Ampt method

Direct Runoff Routing

SCS Unit Hydrograph

Synder Unit Hydrograph

Clark Unit Hydrograph

Base FlowLinear Reservoir

Recession Baseflow

Channel Flow RoutingMuskingum method

Modified Wave method

3. Hydrologic Model Library– Single hydrologic processes

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4. Post-Analysis & Utilities Library

Comparison of simulated and observed hydrographs

Display both hydrographs

Compute seven performance measures

-- Hydrograph shape

-- Peak time and amount

-- Time lag or shifts

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4. Post-Analysis & Utilities Library

Water Balance Check

--Total Amount

--Distribution among hydrologic components

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Code Implementation

Activities

Encoded in C# and compiled into Dynamic Link Libraries (DLL).

Define input/output variables explicitly via a metadata-tagging approach.

Define “Execute” function that is invoked by the engine at run time.

Programming work

Scripting from the ground up.

Converting legacy codes from other language to C#.

e.g. from VB to C# (TOPMODEL)

from C to C# (SWAT)

Compiling legacy codes into DLL, and creating invoker interface to access functions within the DLL.

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Data Structure

Major components

physical computation elements: Sub-basin, River, HRU

Time Series: gridded or gauge-based.

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Applications

• Schuylkill Watershed: Located in Southeastern Pennsylvania, U.S.A. The river is approxi-mately 209km in length, and the watershed covers about 5,229 sq.km.

Studies

Sub-studies

• conduct DEM processing via three types of workflows, and subdivide watershed under two schemes.

apply the SWAT workflow to simulate daily runoff hydrographs over a 4 year period ranging from 2005 to 2008.

apply the TOPMODEL workflow along with a loosely coupled hydrologic model for the simulation of a flood event.

• analyze precipitation data accessed from different data sources.

• estimate potential evapotranpiration using activities encapsulating different approaches.

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Raw DEM Sink Filled DEM Flow Direction Flow Accumulation Total Flow Path

Stream Raster Stream order Watershed Grid Watershed and River Network (.shp)

Step 1: Delineate watershed and generate river network

• Schuylkill DEM: Cell size 1 arc second,4950*3826 cells, Geospatial Extent (39.86,-76.4,40.9,-75.1)• Workflows: 1)Step by Step workflow, 2)Terrain Processing workflow, 3)Web service based work-

flow• Delineation: 1) 7 sub-basins: 500,000 cells as threshold 2) 33 sub-basins: 100,000 cells as threshold

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Step 2: Create Hydrologic Response Units

• Reclassified Land Cover Data • Merged Soil Groups

• HRUS

-- 7 sub-basin watershed contains 23 HRUs

-- 33 sub-basin watershed contains 114 HRUs

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Step 3: Access and process meteorological data

• Get precipitation data from NLDAS-2 and NWS MPE

• Temperature, Solar radiation, wind speed, pressure are accessed from NLDAS-2

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Step 3: Access and process meteorological data

• Get precipitation data from NLDAS-2 and NWS MPE

• Temperature, Solar radiation, wind speed, pressure are accessed from NLDAS-2

The NLDAS and NWIS precipitation data exhibit a good correlation.

The NLDAS precipitation data are adopted in the following modeling.

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Step 4: Compute Daily Potential Evapotranspiration

PET Approaches

Penman-Monteith

Priestley-Taylor

Hargreaves

Thornthwaite

----temperature, atmospheric pres-sure, relative humidity, solar radia-tion, wind speed

----temperature, atmospheric pres-sure, relative humidity, solar radia-tion

----temperature

----temperature

The Thornthwaite underestimates the PET significantly, while the other three methods exhibit close simula-tions.

The estimates of Penman-Monteith method are adopted in the following modeling.

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Step 5: Simulating Daily Hydrographs via SWAT workflow

Workflow: run for 7-sub-basin and 33-sub-basin watershed, over a period of 4 years(2005-2008)

----not fit well.

----no significant difference between two simula-tions.

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Step 5: Simulating Daily Hydrographs via SWAT workflow

Water Balance Check

Difference=Precipitation-Evaporation-Runoff-∆Soil Water

Precipitation Evaporation Runoff ΔSoil Water Difference

7-Subbasin(in) 193.7 186.2 5.05 -0.05 2.5

33-Subbasin(in) 193.7 189.08 4.88 -0.05 -0.21

Water Balance Comparison over Sub-basins

• Add river discharge as an additional input in computing water balance for each sub-basin.

• Aggregate the water balance of finer sub-basins belonging to each coarse sub-basin.

• The water balance accumulated from that of finer sub-basins is close to the one of corresponding coarse sub-basin.

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Step 6: Simulating hourly hydrographs via TOPMODEL workflow & a loosely coupled hydrologic model workflow

Loosely coupled hydrologic model workflow

TOPMODEL workflow

Inputs

----NLDAS-2 hourly precipitation

----Penman-Monteith PET

Inputs

----NLDAS-2 hourly precipitation

Flood Event

----October 8th -11th ,2005

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Step 6: Simulating hourly hydrographs via TOPMODEL workflow & a loosely coupled hydrologic model workflow

Loosely coupled hydrologic model workflow

TOPMODEL workflow

Inputs

----NLDAS-2 hourly precipitation

----Penman-Monteith PET

Inputs

----NLDAS-2 hourly precipitation

Flood Event

----October 8th -11th ,2005

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Discussions

Applicability of HCMS

Performance of HCMS

In general, it is remarkably straightforward to build up workflows in the HCMS for hydrologic modeling purposes.

It can save time and effort through the automated execution that the workflow sequences afford.

With the nationwide data coverage of incorporated data sources, the HCMS can be applied to anywhere in the US.

Execution time losses

---- The workflow engine needs 15-40 seconds to initiate the workflow before execution.

---- The interactive activity takes an additional 5-15 seconds to start up the interactive window.

The losses are insignificant for workflows involving heavy computations, e.g. DEM processing for large areas; How-ever, they are indeed considered as a burden for the workflows need less run time.

Saved time

---- in the preparation of model input.

---- in parallel execution using web service based activities.

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Summary

The purpose of our work is to design a hydrologic community modeling sys-tem(HCMS) that permits the seamless integration of data flows from source, to preparation, to ingestion, to model execution, to harvesting and analysis of result data.

TRIDENT workflow system provides a platform for designing the HCMS and for assembling hydrologic models as workflow sequences.

The HCMS was tested by carrying out several typical hydrologic modeling studies over Schuylkill watershed. It is proved to be used quite well as a mod-eling platform. While it is not computational cost free due to the middle ware layer, the additional time consumption is “affordable”, especially in the lengthy data preparation arena.

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Future Work

Data

Model

Tool Model

Model

Model

ModelData

Data

Data

Data

Tool Tool

Tool

Tool

Tool

Model

DataModel

ModelModel

ModelModelModel

Model

Data

DataDataData

Data Data

ToolTool

ToolToolTool

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Future Work

Data

Model

Tool Model

Model

Model

ModelData

Data

Data

Data

Tool Tool

Tool

Tool

Tool

Model

DataModel

ModelModel

ModelModelModel

Model

Data

DataDataData

Data Data

ToolTool

ToolToolTool

Data

Model

Tool

Model

Model

ModelData

Data

Data

DataTool Tool

Tool

Tool

Tool

Model

Data

Model

Data

Model

Tool Model

Model

Model

ModelData

Data

Data

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