Date post: | 14-Jan-2016 |
Category: |
Documents |
Upload: | simon-parker |
View: | 215 times |
Download: | 0 times |
Hydrologic Modeling in 2011David R. Maidment
Center for Research in Water ResourcesUniversity of Texas at Austin
Leader of the CUAHSI Hydrologic Information System Project
With acknowledgements to Rick Hooper, David Tarboton & Barbara Minsker
Hydrologic Modeling in 2011
• The charge and challenges
• Hydrologic information system – web services
• Integrating models and data using scientific workflows
• Hydrologic Observing System
Hydrologic Modeling in 2011
• The charge and challenges
• Hydrologic information system – web services
• Integrating models and data using scientific workflows
• Hydrologic Observing System
Workshop Charge
• What new technologies for observing, simulating, and tele-communicating will emerge over the next 5-10 years?
• how will they change the grand challenges for modeling, what will those challenges be?
• Challenge for this session:– How all the new devices/opportunities emerging in the
realm of “cyber-infrastructure”— including, perhaps especially, visualization schemes — might change the way models are developed and applied, including the new kinds of scientific questions to be asked in association with modeling.
Hydrologic Modeling
• We want to trace the movement of water, chemical and biological constituents through atmospheric, surface and subsurface water
• We want to do water, mass and energy balances
Hydrologic Information System
• A system is a connected set of components e.g. University of Texas System
• A web-based system is a set of components connected using the internet
• A hydrologic information system (HIS) is a web-based system linking hydrologic databases, tools and models CUAHSI HIS partner institutions
USGS Water Watch System
A national hydrologic observing system already exists – CUAHSI adds to it
Real-time Water Quality Estimates
Estimated total nitrogen
Stream discharge
mg/L cfs
CUAHSI Member Institutions
105 Universities as of May 2006
Challenges
• How to use test-beds to design real WATERS Observatories?
• How to share data from the test-beds with the whole community?
• How to include CUAHSI/CLEANER data not collected in the test-beds?
• How to empower individual scientists?
• How to make use of petascale computing?
Hydrologic Modeling in 2011
• The charge and challenges
• Hydrologic information system – web services
• Integrating models and data using scientific workflows
• Hydrologic Observing System
CUAHSI Web Services
CUAHSIWeb Services
Library
Web Application: Data Portal
Your application• Excel, ArcGIS, Matlab• Fortran, C/C++, Visual Basic• Hydrologic model• …………….
Your operating system• Windows, Unix, Linux, Mac
Internet Simple Object Access Protocol
http://www.cuahsi.org/HIS/
Rainfall & SnowWater quantity
and quality
Remote sensing
Water Data
Modeling Meteorology
Soil water
Water Data Web Sites
NWISWeb site output# agency_cd Agency Code# site_no USGS station number# dv_dt date of daily mean streamflow# dv_va daily mean streamflow value, in cubic-feet per-second# dv_cd daily mean streamflow value qualification code## Sites in this file include:# USGS 02087500 NEUSE RIVER NEAR CLAYTON, NC#agency_cd site_no dv_dt dv_va dv_cdUSGS 02087500 2003-09-01 1190USGS 02087500 2003-09-02 649USGS 02087500 2003-09-03 525USGS 02087500 2003-09-04 486USGS 02087500 2003-09-05 733USGS 02087500 2003-09-06 585USGS 02087500 2003-09-07 485USGS 02087500 2003-09-08 463USGS 02087500 2003-09-09 673USGS 02087500 2003-09-10 517USGS 02087500 2003-09-11 454
Time series of streamflow at a gaging station
CUAHSI Hydrologic Data Access System
A common data window for accessing, viewing and downloading hydrologic information
USGSUSGS
NASANASANCDCNCDCEPAEPA NWSNWS
ObservatoriesObservatories
http://river.sdsc.edu/HDAS
Observation Stations
Ameriflux Towers (NASA & DOE) NOAA Automated Surface Observing System
USGS National Water Information System NOAA Climate Reference Network
Map for the US
NWIS Station Observation Metadata
Describe what has been measured at this station
Web Page Scraping
ProgrammaticallyProgrammatically construct a construct a URL string as produced by URL string as produced by manual usemanual use of the web page of the web page
http://nwis.waterdata.usgs.gov/nwis/discharge?site_no=02087500&agency_cd=USGS&....http://nwis.waterdata.usgs.gov/nwis/discharge?site_no=02087500&agency_cd=USGS&....
ParseParse the resulting ASCII file the resulting ASCII file
NWISNWIS
ArcGISArcGIS
ExcelExcel
NCARNCAR
UnidataUnidata
NASANASAStoretStoret
CUAHSI CUAHSI
AmerifluxAmeriflux
MatlabMatlab
AccessAccess SASSAS
FortranFortran
Visual BasicVisual Basic
C/C++C/C++
Some operational services
CUAHSI Web ServicesCUAHSI Web Services
Data SourcesData Sources
ApplicationsApplications
Extract
Transform
Load
http://www.cuahsi.org/his/
Core Web Methods
Method Input Output
GetSites Obs Network All station codes in network
GetSiteInfo Station Code Lat/long, station name
GetVariables Obs Network or data source
All variable codes
GetVariableInfo Variable code Description of variable
GetValues Station code or lat/long point, variable code, begin date, end date
A time series of values
GetChart As for GetValue A chart plotting the values
Operational Services
Service Ameriflux Daymet MODIS NWIS NAM HODM
Bear Creek
GetSites Yes Yes
GetSiteInfo Yes Yes Yes
GetVariables Yes Yes
GetVariableInfo Yes Yes Yes
GetValues Yes Yes Yes Yes Yes Yes
GetChart Yes Yes
XML Output from GetValues
NWIS
DayMet
MODIS
What is a Data Model
• A data model is a model that describes in an abstract way how data is represented
• Data models describe structured data for storage in data management systems such as relational databases.
• Early phases of many software development projects emphasize the design of a conceptual data model.
Lets see what Wikipedia says
CUAHSI Point Hydrologic Observations Data Model
• A relational database stored in Access, PostgreSQL, SQL/Server, ….
• Stores observation data made at points
• Consistent format for storage of observations from many different sources and of many different types.
Streamflow
Flux towerdata
Precipitation& Climate
Groundwaterlevels
Water Quality
Soil moisture
data
Hydrologic Observations Data Model (HODM)
Serving investigator data
• Several choices– You build CUAHSI
compatible services from your database
– You copy data into the HODM and use CUAHSI services
– You copy your data to an HODM and it is served from SDSC
Your database
Your implementation ofCUAHSI services
HODM
StandardCUAHSI services
Modeling Services
• Simulation models can be packaged as web services
• They can be queried and provide responses just like data archives
• We have an integrated network of data sources and models
A big challenge to integrate all the data streams!
• Search multiple heterogeneous data sources simultaneously regardless of semantic or structural differences between them
Objective
NWIS
NARR
NAWQANAM-12
request
request
request
request
request
requestrequest
request
request
return
return
return
return
return
returnreturn
return
return
What we don’t want …..
Michael PiaseckiDrexel University
Semantic MediatorWhat we do want …..
NWIS
NAWQA
NARR
generic
request
request
request
request
request
request
requestrequest
request
request HODM
Michael PiaseckiDrexel University
Hydrologic Modeling in 2011
• The charge and challenges
• Hydrologic information system – web services
• Integrating models and data using scientific workflows
• Hydrologic Observing System
Regional Storm Water Regional Storm Water Modeling Program and Modeling Program and
Master Plan for San Master Plan for San AntonioAntonio
City ofSan Antonio
Modeling System
Rainfall Data:Rain gagesNexrad
Calibration Data:FlowsWater Quality
Geospatial Data:City, CountySARA, other
FloodplainManagement
IntegratedRegional Water
Resources planning
CapitalImprovemen
tPlanning
FloodForecasting
Water qualityplanning
San Antonio Regional Watershed Modeling System
“Bring the models together”
Database
Geo-HMS
Geo-RAS
GIS-Gflow
Interface
HEC-HMS
HEC-RAS
Gflow
GIS
GIS Preprocessors for Hydrologic Models
Interfacedata models
HMS
RAS
Gflow
GIS
GeoDatabase
Arc Hydrodata model
Connecting Arc Hydro and Hydrologic Models
Digital Rain Maps from National Weather Service (03/04/2004)
FEMA 100-year flood plain map in Bexar County
RC1 RU
09R CO
08R CO
07R CO06R CO
04R CO03R CO
01R CO
02R CO
05R CO
Regional Watershed Modeling System Case Study
Rosillo Creekwatershed
• Arc Hydro Geodatabasefor whole watershed• HEC-HMS hydrology modelfor whole watershed• HEC-RAS hydraulic model for Rosillo Creek
Salado Creek watershed
Components:
Bexar County
Arc Hydro and HEC-HMS
Arc HydroSchematic Network
HEC-HMSHydrologic
Model
Calculates Flows
Arc Hydro and HEC-RAS
Arc HydroChannel
Cross Sections
HEC-RASHydraulic
Model
Calculates Water Surface
Elevations
Flow Change PointsModels communicate with
one another through Arc Hydro at designated points
Nexrad Map to Flood Map in Arc 9 Model Builder FLO
ODPLAIN MAP
Flood map as output
Model for flood flow
Model for flood
depth
HMS
Nexrad rainfall map as input
Web-Accessible Regional Watershed Modeling System
Complete storage of simulationmodels and workflows in geodatabases
Hydrologic Modeling in 2011
• The charge and challenges
• Hydrologic information system – web services
• Integrating models and data using scientific workflows
• Hydrologic Observing System
CUAHSI Hydrologic Observing System
Continental US Scale (coast to coast data coverage, HIS-USA)
1:500,000 scale
Regional Scale (e.g. Neuse basin)
1:100,000 scale
Watershed Scale (e.g. Eno watershed )
1:24,000 scale
Site Scale (experimental site level)
Site scale
Mul
tisca
le in
form
atio
n de
liver
y
A multiscale web portal system for observing and interpreting hydrologic phenomena by integrating data and models for any location or region in the United States
Point Point Observation Scale (gage, sampling location)
North American Scale (e.g. North American
Regional Reanalysis of climate)
1:1,000,000 scale
GeoTemporal Reference Frame
• A defined geospatial coordinate system for (x,y,z)
• A defined time coordinate system (UTC, Eastern Standard Time, ….)
• A set of variables, V• Data values v(x,y,z,t)
Space (x,y,z)
Time, t
Variables, V
v – data values
Data Cube
Series and FieldsFeatures
Point, line, area, volumeDiscrete space representation
Series – ordered sequence of numbersTime series – indexed by time
Frequency series – indexed by frequency
Surfaces Fields – multidimensional arrays
Scalar fields – single value at each locationVector fields – magnitude and direction Random fields – probability distribution
Continuous space representation
mm / 3 hours
Precipitation Evaporation
North American Regional Reanalysis of Climate
Variation during the day, July 2003
NetCDF format
Continuous Space-Time Model – NetCDF (Unidata)
Space, L
Time, T
Variables, V
D
Coordinate dimensions
{X}
Variable dimensions{Y}
Space, FeatureID
Time, TSDateTime
Variables, TSTypeID
TSValue
Discrete Space-Time Data ModelArcHydro
Hydrologic Flux Coupler
Precipitation
Evaporation
Streamflow
Define the fluxes and flows associated with each hydrovolume
Groundwater recharge
See Chapter 9 of Status Report for Details
ArcGIS ModelBuilder Application for Automated Water Balancing
Fields Series
Geospatial
Water Resource Regions and HUC’s
NHDPlus for Region 17E
NHDPlus Reach Catchments ~ 3km2
Reach Attributes
• Slope• Elevation• Mean annual flow
– Corresponding velocity
• Drainage area• % of upstream
drainage area in different land uses
• Stream order
Ingestion of real-time streamflow data
A national hydrologic observing system already exists – CUAHSI adds to it
Continental Water Dynamics Model
Hydrologic Information System
Hydrologic Observing
System
Hydrologic Modeling System
Petascale Computing
• 2.6 million river reaches on a 1:100,000 scale map of continental US
• Solve continuity and momentum equations once on each reach (~ 5.2 million equations) takes ~ 200 parallel processors
• Pittsburgh Supercomputer Center has 3000 parallel processors
• It is within reach to simulate flows on all reaches continuously through time with data assimilation from gaging stations
Conclusions
• Web services support a web-based hydrologic information system connnecting data, tools and models
• Models can be configured as web services
• Scientific workflows automate the integration of components
• A continental water dynamics model is feasible