Coastal Hazards System:

Interpretation and Application

Victor M. Gonzalez, P.E.

Team: PI: Jeffrey A. Melby, PhD

Co-PI: Norberto C. Nadal-Caraballo, PhD

Fatima Diop

Debbie Green

Coastal and Hydraulics LaboratoryUS Army Engineer R&D Center

Vicksburg, MS

Victor.M.Gonzalez@usace.army.mil

Lessons Learned and Best Practices:

Resilience of Coastal Infrastructure

Hato Rey, PR – March 8-9, 2017

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Coastal Hazards SystemBackground

Main features of Probabilistic Coastal Hazard

Assessment (PCHA)

► Full quantification of the hazard in a probabilistic context

► Coverage of practical forcing-parameter and probability space

► Computation of joint probability of storm forcing and responses,

maintaining the relationship between both and across responses

► High fidelity in modeling and statistics

► Regional

► Quantification of uncertainty (how accurate?)

PCHA allows comprehensive and accurate

understanding of the storm hazard for use in risk context

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Coastal Hazards SystemBackground

PCHA study outputs

► Climatology: Historical storms, synthetic-storm suite with

associated relative probabilities, extratropical storm reanalysis

data, measurements.

► Meteorological modeling simulation results (e.g. wind speed)

► Hydrodynamic modeling: grids, simulation results (e.g. currents,

peaks and time series for tide, surge, total water level, and wave

height, with corresponding wave period and direction).

► Statistical analysis results: JPM, hazard curves, and uncertainty.

Regional, high fidelity, and scenarios (e.g. SLC, tide, etc.)

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Very Large Datasets

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Coastal Hazards System

Maximize data relevance and usability

Coastal storm hazards data repository and mining

system

Delivery framework for wide range of coastal hazards

tools and capabilities, not just a database

Leverage federal regional wave/water level modeling

studies (National coastal storm hazard data resource)

Visualize and download through user friendly web tool

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Coastal Hazards SystemGoals

Long-term storage and public access > well-vetted

measured and high-fidelity modeled coastal storm data.

Easily accessible data; search, browse, visualize

Contextual data products and tools that support

federal decision making

► Complete statistical description

► Support risk management/ assessment/ communication

► Support project design and evaluation

► Support expedient coastal storm response prediction,

emergency management, operations

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Coastal Hazards System

Regions

Gulf of

Mexico

North Pacific Mainland

Southern North

Pacific

Hawaii

South

Pacific

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Model Results

ADCIRCWater

Elevation, Wind, Current,

Pressure

STWAVE SWAN WAM

Wave Height, Direction, Period

Observations

NOAA6min, Hourly,

Monthly Water

Level

NDBCHourly wave

Statistics

NLRAstronomical

Tide Bias &

Uncertainty

Global Sea Level

Change Bias &

Uncertainty

AEPExpected

Value AverageRecurrence

Interval Confidence

Limit for eachAEP

SRRStorm relative

Probabilities

Storm Rate,

Low & High

intensity storm

rate

For each Project

StormConditions

HURDATCentral

Pressure,

Rmax,

Forward

Speed

TROPCentral

Pressure,

Rmax,

Forward

Speed

CHS – Data Available

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• Approximately 19,000 output locations

• Peaks and time series files for all storms in

HDF5 format

• Thirteen (13) Annual Exceedance

Probability (AEP) values corresponding

to:1, 2, 5, 10, 20, 50, 100, 200, 500, 1000,

2000, 5000, 10000 years ARI

• Confidence Limits :2%, 5%, 10%, 16%,

84%, 90%, 95%, 98% (2,16, 84, 98% plots)

• Storm recurrence rates, storm relative

probabilities

• Measurements for storms and associated

GPD AEP

• Grids, model inputs, reports, Matlab codes.

Coastal Hazards SystemNACCS Example Data

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https://chs.erdc.dren.mil/

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Transitioning CHS map interface to ESRI

► Eliminate browser compatibility issues

► Provide enhanced geospatial capabilities

► USACE, South Atlantic Division

• Mobile District team

• Irven Ingram – Technical Lead

► Code modifications underway

► ESRI ArcGIS API for JavaScript SceneView

Coastal Hazards SystemMap Interface Improvements

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Select “CHS Web Tool”Select Project Select Sub-Project / Simulation Conditions

NEW: Statistics Results

Annual ExceedanceProbability (AEP)

Non-Linear

Residual

(NLR)

CHS NACCS Example

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Clicking the AEPicon displays

point information and a plot image

CHS NACCS Example - AEPZoom in to view icons

Clicking on an icon displays icons for each

type of model result andstatistic result selected in Navigation Options pane

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Unique features of CHS

Entire hazard

Joint statistics

Updatable

Self-describing files

Summary info and detailed modeling scenarios

Storm probabilities for sampling

Downscaled storm set – recompute probabilities

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CHS Applications

Making use of CHS

► Consume end product – e.g. hazard curves

► Apply the statistical relationships between forcing and responses

• Stochastic design

• Stochastic risk assessment

Monte Carlo Simulation (MCS) - Storm relative

probabilities and storm recurrence rates at specific

locations can be used to sample storms.

Coastal Structure Reliability –Joint evaluation of WL and

waves (Hm0, Tp, & θ) with MCS Storms

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• StormSim – Monte Carlo Simulation (MCS)• Tropical cyclones

• Storm rates for tropical cyclones

• Storm relative probabilities

• Extratropical cyclones

• Gaussian Copula

• StormSim – Coastal Structure Reliability• CHS epistemic uncertainty

• Structure section/material properties

• Structure model epistemic uncertainty

• Level III reliability analysis

• Limit state exceedance (damage, overtopping, transmission, etc.)

• Probability of failure or conversely, reliability

Lajes, Azores AFB breakwater damage/repairStochastic design: reliability

Stochastic assessment: MCS, risk

CHS Applications: Risk and Reliability

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CHS ApplicationsCoastal Hazard Rapid Prediction System (CHRPS)

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High-fidelity Surrogate Models for Hurricane Response

► Training of CHS forcing and response using GPM.

► Rapid prediction of response: inundation (surge+tide), wave

height, wave period, wave direction, currents, wind speed, wind

direction

► Forecasts at multiple days prior to landfall

► NOAA and Coastal Hazards System data linkage for scenario

predictions

► Uncertainty estimates

► Risk Estimates

CHS or Stand-alone

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CHS regional storm modeling

Overview

Response data: correct

dry nodes, etc.

Train metamodel

Neural Networks

Gaussian Processes

Validate

metamodel

NOAA cyclone

forecast: lat, lon,

DP, v, q, Rmax

Predict high-

fidelity

response

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CHS Applications - CHRPS

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CHRPS – Katrina Validation

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Contact Information

Victor M. Gonzalez, P.E.

U.S. Army Engineer R&D Center

Coastal and Hydraulics Laboratory

email: Victor M. Gonzalez@usace.army.mil

Questions?

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