conrad blucher institute coastal monitoring and mapping
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Conrad Blucher Institute Coastal Monitoring and Mapping. Dr. Patrick R. Michaud December 6, 2007. Key points. Introduction to the Conrad Blucher Institute Remote data collection and research capabilities Long-term programs and partnerships. Gulf Monitoring Projects. - PowerPoint PPT PresentationTRANSCRIPT
Conrad Blucher Institute
forSurveying
and Science
Conrad Blucher Institute
Coastal Monitoring and Mapping
Dr. Patrick R. MichaudDecember 6, 2007
Conrad Blucher Institute
forSurveying
and Science
Key points
Introduction to the Conrad Blucher Institute
Remote data collection and research capabilities
Long-term programs and partnerships
Conrad Blucher Institute
forSurveying
and Science
Gulf Monitoring Projects
Texas Coastal Ocean Observation Network
NOAA/NOS National Water Level Observation Network
Physical Oceanographic Real Time System (PORTS)
National/Global Ocean Observing System
Conrad Blucher Institute
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TCOON Overview
Started 1988
Over 50 stations
Primary Sponsors• Texas General Land
Office• National Ocean
Service• US Corps of Eng• Texas Water
Development Board
Conrad Blucher Institute
forSurveying
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TCOON Overview
Measurements• Precise Water
Levels• Wind• Temperature• Barometric Pressure
Follows NOAA/NOS standards
Real-time, online database
Conrad Blucher Institute
forSurveying
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Typical TCOON Station
Wind anemometer
Radio Antenna
Satellite Transmitter
Solar Panels
Data Collector
Water Level Sensor
Water Quality Sensor
Current Meter
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Data Management
Automated Acquisition, Archive, Processing, Retrieval
10-year Historical Database
Most processing takes place via Internet
Infrastructure for other observation systems
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Data Management Design Principles
Preserve source data• Annotate instead of modify
Automate as much as possibleMaintain a standard interchange format
Avoid complex or proprietary components
Emphasize long-term reliability over short-term costs
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Tidal Datums
Used for• Coastal property boundaries• Nautical charts• Bridge and engineering structures
National Ocean Service standards
Automated processing
Legally defensible datums
Technology transfer to/from NOS
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Partnership with NOAA
“The value in TCOON's use of NOS data collection standards and formats is realized in the ability to display TCOON data on the NOS website with confidence that the data is accurate. The ongoing, partnership between NOS, GLO, and [CBI] over the last 16 years has resulted in enormous benefits to the agencies and to the user community.”
http://tidesandcurrents.noaa.gov/tcoon.shtml
Conrad Blucher Institute
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Expansion
NWLON stations in Texas
Houston/Galveston PORTS
Expansion to other states and systems
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Other CBI Monitoring Projects
Nueces Bay Salinity
Real Time Navigation System (RTNS)
San Antonio Bay Water Monitoring
Bahia Grande Water Quality Monitoring
Mission Aransas National Estuarine Research Reserve
Corpus Christi Marina Weather Station
Red de Observaciones y Predicciones de Variables Oceanicas (ROPVO)
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Uses of CBI/TCOON Data
Tidal Datums
Littoral Boundaries
Oil-Spill Response
Navigation
Storm Preparation/ Response
Water Quality Studies
Research
Conrad Blucher Institute
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Research
Real-time Automated Data Processing
Tidal Datum Processing
Web-based Visualization and Manipulation of Coastal Data
Neural-Network-based forecasts from real-time observations
Specialized sensor and data acquisition system development
Support for other research efforts
Conrad Blucher Institute
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Real-time surge information
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Tide and surge predictions
Conrad Blucher Institute
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Neural Network Forecasting
Use neural network to model non-tidal component of water level
Reliable short-term predictions
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Julian Day,1997
CCNAS ANN 24-hour forecasting:
Conrad Blucher Institute
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Texas Height Modernization
CBI lead in cooperation with NGS
Selected goals:• Re-establish NAVD 88 elevations to NGS standards
• Connect NAVD 88 heights to TCOON• Expand use of GPS for elevation measurement
• Build online data warehouse
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Opportunity
Problem: The tide charts do not work for most of the Texas coast
Opportunity: We have extensive time series of water level and weather measurements for most of the Texas coast
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Data Intensive Modeling
Real time data availability is rapidly increasing
Cost of weather sensors and telecommunication equipment is steadily decreasing while performance is improving
How to use these new streams of data / can new modeling techniques be developed
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Bob Hall Pier
Packery Channel
Naval Air Station
Aquarium InglesidePort Aransas
Nueces Bay
Corpus Christi Bay
Gulf of Mexico
Oso BayPort of Corpus Christi
6 TCOON Stations Measuring:
• Water levels (6)
• Wind speeds (4)
• Wind directions (4)
10 x 8760 hourly measurements per year
• Barometric pressure
• Air temperature
• Water temperature
TCOON Data in CC Bay
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Data Intensive Modeling
Classic models (large computer codes - finite elements based) need boundary conditions and forcing functions which are difficult to provide during storm events
Neural Network modeling can take advantage of high data density and does not require the explicit input of boundary conditions and forcing functions
The modeling is focused on forecasting water levels at specific locations
Conrad Blucher Institute
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Neural Network Features
Non linear modeling capability
Generic modeling capability
Robustness to noisy data
Ability for dynamic learning
Requires availability of high density of data
Conrad Blucher Institute
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BHP Performance Analysis
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Forecasting Period
harmonic forecasts (blue/squares), Persistence model (green/diamonds), ANN model without wind forecasts (red dashed/triangles) and ANN model with wind forecasts
(red/circles)
Conrad Blucher Institute
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CCNAS Performance Analysis
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Forecasting Period
Harmonic forecasts (blue/squares), Persistent model (green/diamonds), ANN model with only NAS data (red dashed/triangles) and ANN model with additional BHP data
(red/circles)
Conrad Blucher Institute
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Tropical Storms and Hurricanes
Need for short to medium term water level forecasts during tropical storms and hurricanes
Tropical storms and hurricanes are relatively infrequent and have each their own characteristics.
ANN model performance?
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Forecasts in storm events
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Julian Day,1998
CCNAS ANN 12-hour Forecasts During 1998 Tropical Storm Frances
(ANN trained over 2001 Data Set)
Conrad Blucher Institute
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CCNAS ANN 24-hour Forecasts During 1998 Tropical Storm Frances (ANN trained over 2001 Data Set)
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Julian Day,1998
Conrad Blucher Institute
forSurveying
and Science
Conclusions
Long-term, data-rich observation network
Web-based infrastructure for automated collection and processing of marine data
Research in datum computation and coastal forecasting