SESSION RECORDER
NAME
Erin Cobb
FEMA HQ
TABLE GROUP MEMBERS & AFFLIATIONS
Michael Crenshaw, XP Solutions
Charles Real, CA Geological Survey
Josh Mendes, DHI Water & Environment
Mitchell Blum, HDR Engineering
Bill Syme, BMT WBM
Mark Forest, HDR Engineering
Liang Xu, Santa Clara Valley Water District
Mark Forest, HDR Engineering
Gabriel Vallin, Santa Clara Valley Water District
CONTACT
INFORMATION:
Erin.cobb@dhs.gov
202.646.3798
GOALS:
1. Everyone to find and embrace and learn about all the issues that come with 2D modeling. If your expertise is software development, I want you to understand what the end user sees/feels/experiences; and vice versa.
2. Develop a laundry list of issues that community/FEMA faces when we attempt to use 2D modeling.
Want to categorize these issues so we can attempt to begin to solve them.
Your input will hopefully lead to a resolution one day!
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Table Notes FMA Sept. 4

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LEGEND: A = Policy; B = Process and Procedures; C = Standards and Specifications; D = Research and Development
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A B C D
S1: Models to maps
S1: How communities use info to administer
NFIP
Model is where FEMA gets data for maps; but many other key inputs. Topo is foundation; also hydrologic analyses. Modeling is only as good as topo and hydrologic analyses. Also use field data and surveys (channel geometry, roughness coefficients, structures). Modeling gives us WSEL, whether 1D
or 2D; floodway stations (pts along regulatory floodway); most important element of FIRM is SFHA.
Difference in modeling: 1D calculates elevations using xs (assume prescribed flow direction); 2D modeling can delineate the floodplain/fw (uses unsteady hydrograph).
Advantages of 2D: split flows, wide floodplain, scour, etc.
1D follows hydraulic baseline, which generates flood profile and tables in FIS, in order to map floodzones.
Used for permitting decisions and general floodplain management. Before NFIP, few communities had process to consider flood risk in local decision-making. Process is setup on FIRM; standard used for
FIRM is basis for making local decisions (esp in the SFHA and reg floodway).
Questions for Today:
What issues does FEMA face in using 2D and unsteady models?
What underlying assumptions of each model are valid/invalid?
When do the benefits outweigh the costs for another analysis type?
Should we let a 2D hydraulic model delineate the mapped fp boundaries (or a separate GIS application as typically done with 1D analysis)?
How can/should 1% chance flood elevations be recorded for individual structures (to the nearest tenth of a foot) using 2D models?
Can 2D programs efficiently model floodways? If not, should NFIP fp mgmt and mapping criteria be
Table Notes FMA Sept. 4

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For which analyses should 1D and 2D modeling be linked?
(Others from the group?)
S2: Expiernces of
2D modeling --
Challenges for
Local/State
Agencies using 2D to administer
NFIP
Rohin: 1D vs 2D is a problem we all face, esp depending on topo availability. Ex: San Lorenzo Creek.
Orig project constructed in 60s and designed off 10 yrs of gage records. Conditions gradually increase in rainfall intensity since then. Oct 2005, USGS calculated new 100yr return (16,100cfs; previously
1000cfs). 2D model drastically reduced the floodplain from a 1D. Using 2D to create map creates lots of
“bubbles” rather than a continuous floodplain. Created issues with public – neighbors comparing backyard elevations to each other and confused about why they needed insurance when neighbor didn’t.
Sergio: What happens when you change the map multiple times b/c of newer data, and neighbors comparing in/out?
2D gives ability to look at multiple directions and compare reasonableness to determine if we can support results. Then we evaluate what we can do to solve the problem.
Calibrated for rainfall/runoff volume; fairly confident. Accurate representation of site conditions to verify if 2D was valid (chose 20’ grid for urbanized setting). Used LiDAR and detailed photogrammetic site specific info. Used hydrograph volumes. Created floodplain and baseline (Q100) flows/velocity.
Shows where it’s moving and where it’s storing water. Gives us better cost-benefit analysis to
determine if/where to address problems. Better way to identify solution and distribute cost.
Appropriate to use where you have the values and understand infrastructure works. Accuracy depends on conveyance, landuse, and topo representation. Consider 2D modeling more appropriate in
urbanized overland flooding determination.
Kathy: How did community receive and how did you present?
Sergio: Presented to municipal action communities as a matter-of-fact (research). Addressed concerns of why they were paying flood insurance. Explained in plain language the implications from a major storm. Explain that flooding is not just low frequency storms. When the big storms do come, community will call their officials about why. Tools were effective in communicating b/c they could see where the water would go and the depths and velocities.
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Tom: Combined hydro and hydra models are critical, importance of rainfall loss estimation and challenges using 2D in NFIP.
Maricopa uses 2D for sheetflow systems rather than riverine. Used in master draininage plan, flood studies and dam safety program/plans. Primarily flow-2D.
Define flood prone and flooding problem areas; define mitigation strategies and projects that goes into master plan.
Hydro and hydra are dependent on other for sheetflow areas. Peak discharges and WSELs are needed virtually everywhere in the study area. Level of detail needed for modeling is very high.
Development occurred without floodplain delineations, so not much forethought and planning/mitigation during developing the urbanized area.
FLO2d computes rainfall losses and transmission losses. Parameters used for 1D not necessarily appropriate for 2D(don’t do transmission losses with 1D). with 2d, infiltration continuing along surfaces.
Parameters used must be accurate or will overestimate loss and underestimate flow. Added limited infiltration depth option to limit rainfall loss.
Challenge for NFIP: FEMA approval of 2D for hydrology. Models must be calibrated and verifies. Need guidance from FEMA on criteria to define what is acceptable. FEMA slow response time to rapidly developing technology.
Approach to calibration – use GARR data and measured runoff; use watershed-specific Green and Ampt parameters; use physical evidence (drainage complaints, high water marks, photos from public, maintenance records, newspaper articles, news video footage, etc). If nothing available, use limiting infiltration depth options to compute rainfall loss for study area using 1D then limit total rainfall and transmission losses to rainfall loss only using limiting infiltration depth option.
Karen: What happens when you discover a mistake and have to correct.
Salvador Creek map issued 2010. Model generated using survey and LiDAR and calibrated to 2005 flood.
One issue was notification to property owners. Difficult message for properties that haven’t flooded before. Lots of outreach/public meetings. Zone AH (street flooding) which would cross the frontage of many properties. Many folks hired surveyor b/c they thought house was above BFE and just property would be in floodplain. Met with ~100 owners for LOMCs and found that entire lot was above the elevation. Prompted us to look at map. Map issued in NAVD88, but BFEs were NGVD29 (difference of
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Table Notes FMA Sept. 4

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2+ ft.). Problem was BFE was too low. All LOMCs issued were invalid. Had difficulties when converting
AH; base floods didn’t have reasonable results. Changed zone to AO but needed highest curb to add to depth to determine BFE. City hired surveyor to survey all sites to determine appropriate base flood.
Costly to develop survey info, hold additional public mtgs and sit with home owners. Better info submitted and we changed BFE a third time. Each time BFE changed, had to redetermine each property to determine risk of flooding. Mapped properties OAS if fp boundary was at least 10 feet away from structure.
Kathy – quality is critical. This occurred b/c of one mistake on one workmap.
Kathy (on behalf of Yiguo Liang, CA DWR) – DWR funding restudy of entire valley; develop foundational datasets, models and tools to support legislative mandates and be used by FEMA and locals. Study has a deadline by state mandate. Required to have results completed by Dec 2013. Calibrated 1D riverine model for state plan of flood control system (HEC-RAS). 2D hydraulic models representing floodplains outside of the riverine systems. Primarliy to perform fp delinieations and define storage areas of hecras. Setup grid; hydraulically significant overbank features and streams and cannals. 25 domains, five modeling teams, approx. 7K miles of modeling. What happens when you try to model this large of an area using different teams and being consistent? Data storage issues? Developed tools to increase efficiency and accuracy of model. QA/QC checklists. Bi-wkly model review mtgs. Library of models
(check-in and –out). Think not only at local level, but challenges for using this for a large area.
What grid size used in order to convince the public?
Sergio: 20’ or 10’. If larger, overall change to map is not dramatic. However, overlayed on GIS models, see difference. Can model streets for urbanized areas and delineate street conveyace to verland flow.
Karen: 2.5m by 2.5m grid
Tom: 1 acre and 25’. Could drill in and do animations to see where water came from and flowed around their house or IN their house. Had an event a few weeks later that substantiated the models!
Rohin: 15’ grid; wasn’t enough. Now hope to go to 5’ grid to resolve someo f the issues.
DWR: 400’ grids.
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Table Notes FMA Sept. 4

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S3: Types of 2D models for
Riverine Analysis
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Simulation is our best interpretation of reality and then we approximate a solution to that reality. Full scale/small scale experiments, analog solutions, and theoretical-numerical solutions.
Full scale – deploy instruments and observe variables over short time (not just how high the water is but what’s in the water – important for cleanup!)
Small scale – deploy and observe variables for long time; address non-observed conditions; need to represent the dynamics correctly, scale effects appear (distortion).
Numerical – don’t have scale effects (can use 1:1), not 24 hr looks, no equipment (people in boats or driving levees). Grasp physical reality as best we can and develop theoretical model to derive mathematical model. Then develop solution method. From that we can make a prediction (solution).
Whatever we decide to do is in itself an approximation. This makes simulation half science, half art.
Model developers – develop model
Model users – apply model (this is why we have different results with the same data in the same model)
Mesh convergence should be developed to ensure grid is appropriate for physics used.
“If it’s not too deep, it’s 2D.” – Canadian colleague
All equations and models are approximations – 1D, 2D or 3D. Must understand how Manning’s values vary from 1D to 2D. In 2D, Manning’s is a function of the cell/grid rather than (average for) the entire cross-section (as in 1D). 1D – will get similar answers from different folks; 2D – will likely get different results b/c we differ on really small inputs (like Manning’s) which could drastically change the results
(have to know what’s going on in field for 2D b/c it’s calculated at cell level).
1D advantages: fast, fewer data to calibrate, easier to implement
1D disadv: limitations to simulation of levee breaches and computations of complex areas.
2D advantages: more accurate, simulate complex areas and levee breaches
2D disadv: more time, more specific data, must understand floodplain roughness (more cost)
Choosing grid resolution: minor differences at 100m2, 50m2 and 25m2, 12 hour; more differences at 16 hours; time and duration changes
Computation time goes up 6fold for each type of modeling from 5 min for 100m to many hours for 25m
Choosing roughness: larger roughness, less flow into floodplain; impact on inundation pattern and
Table Notes FMA Sept. 4

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ISSUES depth change over time; changes indundation phase (flash flood, redistribution, equilibrium). Get phases in dynamic simulation vs equilibrium in steady state simulation. Simulations should consider variability of roughness (vegetation changes in time – more vegetation in spring growth vs winter).
Meaning of flood value – range of Q
2D requires more detailed data to be valid. Manning’s influences flooded area and also time to peak and duration of flood.
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Exercise 1:
What issues to FEMA using 2D?
General guidance FEMA should implement to use 2D?
S4: Modeling
Challenge Results
32 total successful challenge submittals (11 firms): 12 for Challenge 1, 13 for Challenge 2, 5+2 for
Challenge 3
Challenge Model 1 – (Napa, CA area) Urban Riverine Area; data based on effective data submitted to
FEMA (aerial photography, 2 ft contour, inflow hydrograph, cross sections and structures data, downstream boundary condition); what data does FEMA need to store in order to recreate the model?
Challenge Model 2 – tidally influenced Coastal floodplain; data based on eff data submitted to FEMA
(5m DEM, upstream hydrograph, ocean tide elevations, high water marks); complaints that there were mixed data sets (meters and feet)
Challenge Model 3 – Non-urban riverine with levees; data provided from DWR CVFED program (high res aerial imagery, LiDAR LAS files, high res gridded regular network based files in the GMG format, supplementary survey points/breaklines, boundary conditions, land use data); concerns that LiDAR data was overwhelming & infiltration has a major impact on floodplain
How many different types of models were submitted? 8 different software models were used.
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Any variations in input assumptions? Yes; some evaluation in how to interpret 2 ft contours. Came back as a lessons-learned for how to store this data.
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S5: Model
Calibration,
Verification and
Validation
ASCE spent time in recent years to explain differences in these terms (all synonyms).
Principles of Modeling:
1. All models are wrong…but
2. Properly done, they can be useful
3. Best model to use is the one you know best!
4. Use simplest model (do I even have enough info to use a 2D model?)
Verification: process to determine the solution consistency, stability and convergence, and the quantitative determination of the Order of Convergence
Compare numerical results to values of selected analytical results (if line up, then I’ve solved math correctly)
2 nd process to verify – compare results with lab measurements to demonstrate whether we’re actually solving the problem (are the physics sufficient?)
Meaning of verification – without ‘tuning’, code is correct and math formulation is valid for solivng the problem; errors will still exist
NOT ALL MODELS HAVE BEEN VERIFIED IN THIS WAY – this process used to be required b/f you could publish the model; now it’s simply accepted – most codes have not been reviewed this closely; some have sophisticated GUIs applies that can alter solutions, particularly where they apply structures and other controls
Calibration/Validation: aka – “application site validation”; actual domain at site must be identified and discretized to produce a model suitable to the questions asked (ex: Manning’s values); parameters which are modified must not be outside the range of reality; convergence testing still required
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Sufficient data must be available to perform this task; if insufficient data, cannot predict the error in a future response
2 nd step in process is to validate with independent filed data, i.e., test calibrated model with an independent set of boundary conditions (e.g., used flood records for an area from various years) – again, need sufficient data in order to calibrate accurately
Mesh convergence is a good practice that needs to be done, even with 1D model (costly and takes time).
When it comes to N factor whether 1 or 2D, and you do hydraulic model for FEMA, might have different n values from field depending on when you’re in the field. What’s the difference for 1 or 2D for
Manning’s value, when you still have to average the value? Can be a problem when patterns change; if rotates from year to year, then we change from year to year. In urban areas, we know that a new development will have a much different roughness value 10 or 20 years from now. Unfortunately, how you account for that in a model is a one-shot deal. We come up with the best calibration we can over the range of years. But yes, we can’t account for every single change or would have to modify the model on a regular basis. In 1D, you are using an average of variations across a cross-section, but this doesn’t necessarily account for change in time. In 2D, the water isn’t going in one direction, so you can account for variations by cell. The difference in the two models is how it “directs” the flow of water based on the Manning’s values.
Is computational fluid analysis models? Is it necessary for floodplain mapping? Kathy: there is a system in AZ that uses a combination of things – models and geomorphology and drew maps from geology rather than model
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Table Notes FMA Sept. 4

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Exercise 2
What data should FEMA be storing?
What are some of the issues FEMA needs to address for calibration?
Do we need a specific model setup that we “calibrate” models to?
S6: Challenge
Models 2012
(Meshes & Grids)
Of 32 models, 8 (25%) were mesh models and 24 were grid. Representative of current practices, but expect this is changing and they will balance out.
Mesh submitted– Ch1 17%; Ch2 38%; Ch3 20%
Grids submitted – Ch1 83%; Ch2 62%; Ch3 80%
Why different results:
- different modelers
- combination of SI and English units in data provided
- terrain: limited to data we provided, some added to the detail we provided and interpreted differently
- level of detail/effort
- differences in methodologies (difference equations, grids and meshes)
- assumptions
- n values (highwater marks from 90s; terrain more recent)
- overbank/lateral spill elevations
- National Land Cover dataset very course for Challenge 2 compared to the CA DWR data for Ch3
How will models be used?
- FMA is assemblins statistics and will share presntations and findings
- additional review by flue ribbon panel of experts
- there may be a need for more Challenge Models
Next time…
- more time to model
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- provide more complete data that limits what is tested
- lots of potential additional subjects/scenarios (integrated hydrology, urban isolated floodplain, floodway, LAMP, alluvial, sediment/mobile bed, levee breach/dam breach, converting results to maps)
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