conrad blucher institute coastal monitoring and mapping

Conrad Blucher Institute

forSurveying

and Science


Coastal Monitoring and Mapping

Dr. Patrick R. MichaudDecember 6, 2007


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and Science

Key points

Introduction to the Conrad Blucher Institute

Remote data collection and research capabilities

Long-term programs and partnerships


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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


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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


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TCOON Overview

Measurements• Precise Water

Levels• Wind• Temperature• Barometric Pressure

Follows NOAA/NOS standards

Real-time, online database


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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


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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


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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


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Real-time surge information


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Tide and surge predictions


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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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CCNAS ANN 24-hour forecasting:


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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


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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


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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)


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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)


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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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CCNAS ANN 12-hour Forecasts During 1998 Tropical Storm Frances

(ANN trained over 2001 Data Set)


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CCNAS ANN 24-hour Forecasts During 1998 Tropical Storm Frances (ANN trained over 2001 Data Set)

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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

conrad blucher institute coastal monitoring and mapping

Documents

water releaseswate

nos website

based forecasts

tcoonexpand use of gps

ngs standardsconnect

observaciones y predicciones

noaathe value

hour forecasting