HEC-WAT As A Framework for PFHA
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HEC-WAT As A Framework for PFHA William Lehman, Hydrologic Engineering Center
Transcript of HEC-WAT As A Framework for PFHA
HEC-WAT As A Framework for PFHAWilliam Lehman, Hydrologic Engineering Center
HEC-WAT Mission and Vision
"Integrating Water Resource Management"
MissionTo provide a water resources tool that integrates engineering and consequence software to support a wide range of water resources applications, including watershed and systems based risk analysis.
VisionDevelop the primary integration tool for engineering and water resources studies.
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HEC-WAT Goals
Goals• An excellent user experience• Provide innovative solutions to complex problems• World class training and documentation• Support field applications of HEC-WAT for real world problems
• Increase the combined capabilities of water resources software
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• Plugin Architecture• Supports Integration of any
water resources software• Watershed Systems Approach
• Model Linking• Risk Analysis
• Nested Loops
Overview of HEC-WAT
HEC-WAT Plugin Framework
Integrates Software• Hydrology
• Reservoirs• Hydraulics• Consequences
Facilitates linking• Inputs• Outputs
Results Storage
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HEC-WAT Framework
HEC-WATSimulation
With DefaultProgram
Order
HEC-ResSim Plug-In
HEC-RAS Plug-In
HEC-HMS HEC-ResSim HEC-RAS HEC-FIA
HEC-HMS Plug-In
HEC-FIA Plug-In
Model Results (simulation.dss)
Fragility Curve Editor• Samples System Response curves for Dams
HEC-HMS• Rainfall Runoff
Weather Generator• Stratified Stochastic Spatially distributed Precipitation hyetographs
HEC-RAS• River Hydraulics• Dam Breach Hydraulics
HEC-ResSim• System Operations• Simulate Post Dam breach operation
Integrated Applications
Project Area
• Five Main USACE Dams• Ray Roberts• Lewisville• Grapevine• Joe Pool• Benbrook
• Weather Generator• HEC-HMS• HEC-ResSim• HEC-RAS• Other Plugins
Combining Watershed Processes in HEC-WAT
Application Average Run time per event
HEC-HMS ~30 seconds
HEC-ResSim ~45 seconds
HEC-RAS ~90 seconds
Total (with all supporting plugins) ~175 seconds
Model LinkingModel Linking defines the flow of data• Precipitation can be generated externally and imported
• Data can be consumed by multiple subsequent processes
• Simulation time windows can be shortened for computationally intensive components
HEC-WAT Flood Risk Analysis
Natural Variability (Aleatory)Describing that things naturally vary
Knowledge Uncertainty (Epistemic)Uncertainty describing what we do not know
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HEC-WAT Flood Risk Analysis
EventsHow we represent Natural Variability
RealizationsHow we represent Knowledge Uncertainty
SimulationMultiple Realizations of multiple Events
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Events in a Realization
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1. Sample From Input Distribution1. Use number of events in EYOR
(ORANGE)
2. Develop Analytical fit1. Use same distribution type
(ORANGE)
3. Sample Events1. Sample realization number of
events (GREEN)
Probability
Precip
ita
tion
Realizations in a Simulation
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1. Repeat Process Many times1. Realizations Reflect Knowledge
Uncertainty due to EYOR (ORANGE)
Probability
Flow
Precipitation to Hazard Frequency
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Probability
Precip
itatio
n
Stage
Precip
itatio
n
Flow
Stage
Input Probability Stage
Uncertainties:• Basin
wetness• Reservoir
Operations
Uncertainties:• Breaches• Manning’s N
.002.005.01.020.050.10.20.50.80.90.950.99500
550
600
650
700
750
800
Ann
ual P
eak
Pool
Sta
ge (f
t)
Exceedance Probability
Pool Stage Examplesample of peak pool stage from one realization(spans natural variability)provides 1 estimate of peak frequency
sample of frequency curves from all realizations(spans knowledge uncertainty)provides distribution peak stage quantiles
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B A
Knowledge Uncertainty Only?
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Probability
Prec
ipita
tion
Flow
Prec
ipita
tion
Flow
Stag
e What about Natural Variabilities other than Event Magnitude?How does the WAT manage Natural Variabilities and Knowledge Uncertainties outside of precipitation or flow?
Plugins Receive 2 Seeds Per Event
• A Natural Variability Seed and a Knowledge Uncertainty Seed
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Annual Maximum FlowSnowmelt, Flow
Forecasting
Starting Storage / Elevation
Demands (water, power)
Sedimentation ProfileManning’s nBridge Debris, Ice
ThicknessDam/levee breeching
Flood Frequency Curve
Reservoir physical data:storage / elevation relation.release capacity
Weir, Gate, Bridge Coefficients
Contract / Expanscoefficients
Manning’s nTerrain Data
Flows
ReservoirModeling
ChannelRouting
Stratification
• In order to achieve sufficient modeling samples we stratified the Natural variability loop
Conclusions
• HEC-WAT can produce Hazard Frequency curves that show the influence of dam failure.
• Stratified Sampling is necessary to reduce computational burdens
• HEC-WAT distributed computes need better error handling and system operation tooling
• It is difficult to link HEC-RAS and HEC-ResSim to properly account for flood wave volume and pool frequency.
• HEC-ResSim needs to be able to respect dam failure as part of the rule operations.
