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Models Matter Choice and use of modern stormwater models

Modelling Concepts

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I gave this talk at a stormwater conference to help people think through some of the reasons for modelling, and how to get the most from their modelling efforts.

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Page 1: Modelling Concepts

Models MatterChoice and use of modern stormwater 

models

Page 2: Modelling Concepts

Get out your superglue!

Image: Enviroscape® classroom kit

Page 3: Modelling Concepts

A topic only an engineer could love

Page 4: Modelling Concepts

Getting what you need from  stormwater studies

Are your consultants not answering the questions that matter to you?Are they answering questions you didn’t ask? Are they ensuring the long‐term function of your project?Are they presenting the material in a form you can understand?Are they considering the environmental impacts?

Page 5: Modelling Concepts

What do you want to know?

Figure: USGS

Page 6: Modelling Concepts

Common drainage study objectives

Develop my property without causing flooding (and lawsuits) downstreamSize my new culvert to ensure that it doesn’t overtopGuide my city’s development to ensure that our streams are not impairedSet our new water intake to ensure that it doesn’t go dryRestore my city’s stream to provide good fishing habitatDo the bare minimum to meet those @#$!@# regulations

Page 7: Modelling Concepts

Why model?

To keep brilliant consultants in jobs

To meet your objectives 

Page 8: Modelling Concepts

How does a model work?

InputsWhat causes the process? 

ResponsesHow does the system respond?

ObjectivesWhat important effects occur?

ErrorHow reliable are my results?

Page 9: Modelling Concepts

InputsMost typical is rainfallBaseflow/dry weather flowSnowmeltExisting watershed conditionTemperatureHumidityWindSun

Page 10: Modelling Concepts

ResponsesInfiltration over timeGroundwater rechargeRunoff over timeFlowrateFlow depthFlow velocity

Page 11: Modelling Concepts

ObjectivesMaximum values

What will be the peak flood level for a given storm?Minimum values

Will I have any flow in my stream during an August drought?Total values

How much rain will infiltrate the soil in a given year?Average valuesNumber of exceedances

How many times is my building likely to flood in 100 years?Number of deficits

How many times is my pond likely to dry up in 100 years?

Page 12: Modelling Concepts

Deficit Level

Exceedance Level

Time Flooded

Time Flooded

Time w/out water

Example River Level Objectives

Page 13: Modelling Concepts

ErrorHow closely does your model mirror reality? 

Error AnalysisHow do your assumptions affect your results?

Sensitivity AnalysisCan you optimize your assumptions to reduce error?

Calibration

Page 14: Modelling Concepts

Define your objectivesMeet with your consultant

On site if possibleDon’t let him leave until he completely understands your objectives

Define how you will measure successBe clear and conciseWrite objectives into the contract

His recommended modelling plan should address all of the aspects that follow

Page 15: Modelling Concepts

What data currently exists?Surveying, constructing, testing, and calibrating a model for a large watershed takes a lot of time and moneyIs the existing dataset detailed enough?Is the existing dataset reliable?Does the existing data require significant re‐formatting?Often there are existing studies that can provide a starting point

FEMACorps of EngineersCity engineer

Page 16: Modelling Concepts

Where do you want to focus?

Be clear about where the critical locations areNon‐critical locations can be modelled more roughlyCritical locations will require more detail Take care in applying existing models: they may have been made for a different purpose

Page 17: Modelling Concepts

Under what range of conditions?100‐yr storm

Has a 1% chance of occurring in a given yearYou may have three 100‐yr storms in a yearEvent modelling – hypothetical storms

A 100‐yr storm doesn’t necessarily produce a 100‐yr runoff; soil moisture, storm duration, rainfall distribution and several other factors come into playLong‐term rainfall/runoff conditions

Continuous modelling – calibrates model with recorded data and tests future case against the long‐term rainfall

Page 18: Modelling Concepts

What exactly is a 25‐yr storm?

You may encounter a 25‐year storm two years in a rowMore accurate to say “4%” chance stormA rainfall distribution is required to understand how the total rainfall depth falls over time

Page 19: Modelling Concepts

How certain do you need to be?

Figure: Cooperative Research Center for Catchment Hydrology

75%?99%?Within 0.5 feet elevation?Within 100 cubic feet per second?Which parameter will be used for calibration and error analysis?

Flow?Water elevation?

Perform sensitivity analysis and calibration to increase confidence

Data is hard to find for small watershedsCan another similar watershed be used for calibration?

Page 20: Modelling Concepts

Sensitivity Analysis to Increase Confidence

Change uncertain model parameters and examine the effects on the results

Infiltration parameters are usually a good candidateKeep parameters within a reasonable rangeTypically done one at a timeLook at effects over a range of conditionsResults are “sensitive” to a parameter when a change in the parameter makes a large difference in the result

Measured parameters are typically not changedPipe diameterChannel length

Page 21: Modelling Concepts

Sensitivity Example

100 % Parameter Change

% R

esul

t Cha

nge

0

100

-100

-100

= mild positive sensitivity

= negligible sensitivity

= strong negative sensitivity

Page 22: Modelling Concepts

Calibration to Increase ConfidenceNeeded especially for physical modelsCompare modelled results with measured results and adjust for better fit using what was learned from sensitivity analysisDegree of fit can be measured using several statistical techniquesFormal calibration can be done with recorded rainfall and flow time seriesInformal calibration can be performed with measured total rainfall and high water marks

Page 23: Modelling Concepts

Figure: William James, Computational Hydraulics International

Calibration Example

Page 24: Modelling Concepts

What future scenarios?After construction of a 1.5 acre restaurant siteAt full build‐out per the city 20‐year planWith our 75‐year old culvert collapsed

Page 25: Modelling Concepts

What expertise is available?Some models require significantly more expertise to operate than othersDoes your staff or consultant:

Have a thorough understanding of the processes involved in your watershed?Have a solid foundation in the model being employed and the algorithms driving it?Have the community relations skills to present your project to the public?Have the availability to perform the work?

Page 26: Modelling Concepts

What is your schedule and budget?

Consider the cost of making a wrong decisionA perfect model a year late is useless

Page 27: Modelling Concepts

Do you need a model?

Long term gauge data is preferred, but doesn’t exist many places

Image: USACE EM 1110-2-1415

Page 28: Modelling Concepts

OK: you have defined objectives you know you need a model

Now what?

Page 29: Modelling Concepts

Model Selection and Proper Application

Page 30: Modelling Concepts

Hydrology

Hydrology: the science dealing with the occurrence, circulation, distribution, and properties of the waters of the earth and its atmosphereMany hydrologic parameters are hard to measure

= part of a simple drainage study

Modelling

other parts of the 

water cycle helps us to 

understand the long‐term 

environmental impacts of land 

use decisions 

Hydrology

Page 31: Modelling Concepts

Hydraulics: the science dealing with the laws governing water or other liquids in motion and their applications in engineering; practical or applied hydrodynamicsHydraulic parameters are typically easier to measure

Hydraulics

Image: Tarleton University Hydraulics Lab

Page 32: Modelling Concepts

Model selection criteriaAbility to explain past observations

Can be improved through calibration 

Ability to predict future observations Cost of creation and use

Especially for models that will be maintained into the future

RobustnessA robust model will perform well under a wide range of conditions and will remain stable under reasonable conditions

SimplicityModels with the fewest number of parameters are usually best for a given error level

Page 33: Modelling Concepts

Model Structure

Figure: Cooperative Research Center for Catchment Hydrology

Empirical‐based on statistical analysis of other watershedsConceptual‐based on a conceptual understanding of watershed processesPhysical‐based on physical processes that can be tied directly to measured characteristics

Page 34: Modelling Concepts

Empirical Hydrologic ModelsDo not attempt to explain the driving processes, they simply transform an input into a result based on statistical analysis of previous resultsCan provide reliable results if used within the constraints of the original study:

Studies typically provide bounds of applicability based on factors like location, rainfall distribution, or land use

Robust and simple, but high error

Page 35: Modelling Concepts

Empirical Hydrologic Models:  Regional Regression

Table and Figure: USGS Water Resources Investigation Report 03-4176

Peak flows onlyBe sure to choose the right regionUsually limited by drainage areaNote the prediction error

Page 36: Modelling Concepts

Empirical Hydrologic Models:  Rational Method

Table: NOAA Atlas 14 for University of Tennessee Knoxville Monitoring Station

Q=CiAQ=flow (ac‐in/hr≈cfs)i = rainfall intensity for time of concentration (in/hr)A = area (acres)

Peak flows onlyBest for small urban watershedsCan lead to paradoxical results

Page 37: Modelling Concepts

Rational Method Example

Page 38: Modelling Concepts

Rational Method ExampleSite is 6 acres

2 acres grass (C = 0.12) that flow onto:4 acres paved (C = 0.95)Overall C = 0.67

Time of Concentration (Tc)Grass sheetflow Tc = 8 minsPaved shallow concentrated Tc = 2 minTotal Tc = 10 minsCorresponding intensity = 6.8”/hr for 100‐yr storm

Q = CiA = 0.67*6.8*6 = 27.5 cfs

Figure from Andy Reese, AMEC

Page 39: Modelling Concepts

Rational Method QuandarySite is 6 acres

2 acres grass (C = 0.12) that flow onto:4 acres paved (C = 0.95)Only consider paved area

TcPaved shallow concentrated Tc = 2 min (use 5‐min intensity)Corresponding intensity = 8.5”/hr for 100‐yr storm

Q = CiA = 0.95*8.5*4 = 32.3 cfsWhy the flow increase?Tough to determine C for complex watershedsMany communities put a cap on Rational Method area

Figure from Andy Reese, AMEC

Page 40: Modelling Concepts

Conceptual Hydrologic ModelsExplain driving processes like infiltration and runoff to some extentSeveral inputs may be lumped into non‐measurable factors that replicate processes like infiltrationMany of the processes are still based on regression equations

Page 41: Modelling Concepts

Conceptual Hydrologic Models: SCSMore sophisticated than the Rational methodConsiders:

Rainfall distributionInitial rainfall lossesLand use (CN) – not a directly measurable parameterTime of concentration (Tc)

Provides peak flows as well as:Total infiltration and runoff volumesOutflow hydrographs

However, several aspects of the model are still based on regression analysis and don’t explain the underlying processes.

Page 42: Modelling Concepts

SCS Method Example

Page 43: Modelling Concepts

Physical Hydrologic ModelsModel the actual physical processes that drive the water cycleHave large data requirementsShould be calibrated to some extentExamples

SWMMInfoWorksMike SHE

Page 44: Modelling Concepts

Physical Hydrologic Models: SWMMHas hydrologic, hydraulic and water quality modulesAllows for choice of several physical hydrologic methods

Page 45: Modelling Concepts

SWMM Examples

Page 46: Modelling Concepts

Spatial and Time ScalesLevel of detail should be based on your objectives:

You care about 2 acre watersheds and pipe flow for your new subdivisionYou don’t care about such fine detail for the Mississippi River‐different processes are important

Page 47: Modelling Concepts

Lumped vs. distributed models

Lumped:Basin is divided into subbasinsThe characteristics of each subbasin are represented by a weighted average

Distributed:Watershed characteristics are determined at each locationLarge amounts of data requiredMost data is satellite derivedLong run times

Page 48: Modelling Concepts

Necessity of Fieldwork

Page 49: Modelling Concepts

Design Event ModelsMany design studies are driven using a single storm eventThe chosen event is often chosen based on a regulated design storm with a specified probability of occurrence (e.g. 2% probability storm)Remember: a 2% probability storm does not mean a 2% probability runoffWhat happens between storms?What about the regional water balance?What about water quality?Soil moisture conditions at the start of the storm must be assumed

Page 50: Modelling Concepts

Continuous Stormwater ModelsAre calibrated using a long‐term historical datasetRather than run a hypothetical 2% probability design storm, run 50 years of data and perform a flood frequency analysis on the outputLow flow conditions can be examined for water qualityLand use impacts on water supply can be examined for drought periodsThe impact of soil moisture on runoff can be realistically considered

Page 51: Modelling Concepts

Hydraulic Governing EquationsThe St. Venant equations are used to model flow

Continuity

Momentum

Hydrologic models: continuity onlyHydraulic routing models: continuity and some form of momentumSome situations can be approximated well with simplificationsSome situations require more exacting analysis

Page 52: Modelling Concepts

Flood Routing MethodsKinematic Wave

Gravity balances frictionIgnores tailwaterFlow is uniformHydrograph is merely translatedOnly for steep, well defined channelsOnly for slowly rising floodwatersCan use long time steps

Diffusion WaveAdds attenuationAllows for downstream boundary conditionAllows for moderately rising floodwaters

Dynamic WaveAllows for convective and local accelerationHandles looped networksRequires short time steps

Page 53: Modelling Concepts

Routing Method Choice

Page 54: Modelling Concepts

Overall Complexity“Things should be made as simple as possible, but not any simpler” ‐Albert Einstein

Modelling Costs

Modelling Error

Modelling Value

Model Complexity

Optimum Model Complexity

ComplexSimple

Page 55: Modelling Concepts

Making the most of your  modelling investment

So far, you have:Defined your study objectivesChosen a model that can analyze for your objectivesSet up the model to take best advantage of the available dataRun the modelPerformed sensitivity and/or error and calibration analysis to give an idea of the certainty your model can provide

Now, try to get as much useful information as possible from the model you have worked so hard on

Page 56: Modelling Concepts

Water QualityExpand your SWMM hydrology and hydraulics model with water quality parameters to account for pollutants such as sedimentModel contaminant breakdown using models like HSPFUse your long‐term continuous model to:

Examine what happens to pollutants during low flows

Page 57: Modelling Concepts

Outlet Protection

Photo: Mary Halley

A random pile of gravel does not make for good outlet protectionModelled outlet velocity and tailwater conditions can be used to design proper outlet protection given the local soils

Page 58: Modelling Concepts

Culvert Flushing

Photo: Greg Wilson

Use model to check that culvert flow velocities are high enough (>2.5 ft/s) to flush culvert when flowing partially fullSediment traps and low‐flow barrels can be used to ensure flushing

Page 59: Modelling Concepts

Low Flow Channels

Typical stream crossing: improperly 

sized culvert

New properly sized and 

positioned culvert with 

additional bankfull culvert to 

allow stream to stay 

connected to its floodplain at 

times of bankfull and beyond 

bankfull flow

Page 60: Modelling Concepts

Streambank Erosion

Photo: Mary Halley

Use model to check that natural streams will be kept in equilibrium (e.g. no net erosion or deposition)Requires knowledge of soilsShear stress methodTable methodGeomorphologic method

Page 61: Modelling Concepts

Stream Erosion vs. Deposition

Page 62: Modelling Concepts

Debris Blockage

Photo: Lee Gentry

Assume that a percentage of any culvert will be blocked by debrisCheck for flooding effects

Page 63: Modelling Concepts

Inlet CapacitySimply sizing a pipe to carry flow is not enoughInlets are more often than not the limiting factorFHWA publication HY‐22FHWA or other curves can be used in a dual‐drainage model to correctly model overland flow

Page 64: Modelling Concepts

Design Information (Input) MINOR MAJOR

Type of Inlet Type =

Local Depression (additional to continuous gutter depression 'a' from 'Q-Allow') aLOCAL = 1.0 1.0 inches

Total Number of Units in the Inlet (Grate or Curb Opening) No = 1 1

Length of a Single Unit Inlet (Grate or Curb Opening) Lo = 6.00 6.00 ft

Width of a Unit Grate (cannot be greater than W from Q-Allow) Wo = N/A N/A ft

Clogging Factor for a Single Unit Grate (typical min. value = 0.5) Cf-G = N/A N/A

Clogging Factor for a Single Unit Curb Opening (typical min. value = 0.1) Cf-C = 0.10 0.10

Denver No. 14 Curb Opening

H-VertH-Curb

W

Lo (C)

Lo (G)

WoWP

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Q for 1/2 Street (cfs)

Q In

terc

epte

d &

Bypa

ssed

(cfs

), Fl

ow S

prea

d T

& T-

Crow

n (ft

), Fl

ow D

epth

(inc

hes)

Q Intercepted (cfs) Q Bypassed (cfs) Spread T (ft), Limited by T-CROWN

Spread T (ft), Not Limited by T-CROWN

Flow Depth d (inches)

Gutter Geometry (Enter data in the blue cells)Maximum Allowable Width for Spread Behind Curb TBACK = 5.0 ftSide Slope Behind Curb (leave blank for no conveyance credit behind curb) SBACK = 0.1000 ft. vert. / ft. horizManning's Roughness Behind Curb nBACK = 0.1000

Height of Curb at Gutter Flow Line HCURB = 6.00 inchesDistance from Curb Face to Street Crown TCROWN = 13.0 ftGutter Depression a = 1.64 inchesGutter Width W = 1.50 ftStreet Transverse Slope SX = 0.0200 ft. vert. / ft. horizStreet Longitudinal Slope - Enter 0 for sump condition SO = 0.0300 ft. vert. / ft. horizManning's Roughness for Street Section nSTREET = 0.0150

Minor Storm Major StormMax. Allowable Water Spread for Minor & Major Storm TMAX = 5.0 10.0 ftMax. Allowable Depth at Gutter Flow Line for Minor & Major Storm dMAX = inchesAllow Flow Depth at Street Crown (leave blank for no) X = yes

Hy

d xS

S wa

S tree t C row n

WT , T .

Tx

Q xwQ

T . C R O W N

C U R B

SBA C K

T .B A C KM AX

Minor Storm Major StormMax. Allowable Gutter Capacity Based on Minimum of QT or Qd Qallow = 1.5 5.5 cfs

Inlet Capacity

Page 65: Modelling Concepts