Urban Watershed Urban Watershed ChallengeChallenge

Storm Sewers & Watershed ModelsStorm Sewers & Watershed Models

Delineation QuestionsDelineation Questions

Height-of-land delineation is altered by Height-of-land delineation is altered by storm sewer storm sewer Gravity and force mainGravity and force main

Do we need to correct for storm sewers?Do we need to correct for storm sewers? Significance of storm sewers is scale Significance of storm sewers is scale

dependentdependent Can we correct for storm sewers?Can we correct for storm sewers?

Semi-Automated DelineationSemi-Automated Delineation

Burn streams into DEMBurn streams into DEM Run initial delineation on modified DEMRun initial delineation on modified DEM Check with local sources and expertsCheck with local sources and experts Review DOQsReview DOQs Modify streams and repeat the processModify streams and repeat the process

Boundary DisagreementBoundary Disagreement

Stream modified DEM boundary

Manually delineated boundary

Storm Sewer DataStorm Sewer Data

Acquire dataAcquire data Mostly CAD formatMostly CAD format

Import to GISImport to GIS GeoreferenceGeoreference

no metadatano metadata unknown coordinate systemsunknown coordinate systems

Challenge #1: GeoreferencingChallenge #1: Georeferencing

Spatial adjustment tool used to fix georeferencing problem

Georeferenced DataGeoreferenced Data

Example: Effect of Lift StationsExample: Effect of Lift Stations

Stream modified DEM boundary

Manually delineated boundary

Challenge #2: Jurisdictional IssuesChallenge #2: Jurisdictional Issues

Stream modified DEM boundary

Manually delineated boundaryCity of Edina

Storm SewerHennepin County Storm Sewer

Example: Revised DelineationExample: Revised Delineation

Challenge #3: DirectionalityChallenge #3: Directionality

Limited use of Limited use of directionalitydirectionality

Challenge #4: ConnectivityChallenge #4: Connectivity

Interrupted by other Interrupted by other feature typesfeature types maintenace access maintenace access

holesholes

Interrupted by missing Interrupted by missing surface water featuresurface water feature open ditchopen ditch

Challenge #5: AttributesChallenge #5: Attributes

Inconsistent attributes Inconsistent attributes between sourcesbetween sources

Typically limited Typically limited attributesattributes

Attributes may be as Attributes may be as graphical annotationgraphical annotation

Summary of ChallengesSummary of Challenges

Unknown coordinate systemsUnknown coordinate systems Overlapping jurisdictionsOverlapping jurisdictions Lack of directionalityLack of directionality Lack of connectivityLack of connectivity Inconsistent and sparse attributesInconsistent and sparse attributes

Urban Watershed ModelsUrban Watershed Models

Three basic algorithms for water quality Three basic algorithms for water quality modeling of urban watershedsmodeling of urban watersheds

Event-mean concentration (EMC)Event-mean concentration (EMC)

Regression model (rating curve)Regression model (rating curve)

Build-up / wash-offBuild-up / wash-off

EMCEMC

Simplest approach - event mean concentration Simplest approach - event mean concentration (EMC) (EMC)

Many published valuesMany published valuesOften monitoring is land use specificOften monitoring is land use specificEMCs area-weighted based on land useEMCs area-weighted based on land use

i

iiwtarea A

EMCAEMC

i

iiwtarea A

EMCAEMC

EMCEMC

Land UseLand Use TNTN TPTP TSSTSS BODBOD

Low-density residentialLow-density residential 1.771.77 0.180.18 19.119.1 4.44.4

Single family residentialSingle family residential 2.292.29 0.30.3 2727 7.47.4

Multi-family residentialMulti-family residential 2.422.42 0.490.49 71.771.7 1111

Low-intensity commercialLow-intensity commercial 1.181.18 0.150.15 8181 8.28.2

High-intensity commercialHigh-intensity commercial 2.832.83 0.430.43 94.394.3 7.27.2

IndustrialIndustrial 1.791.79 0.310.31 93.993.9 9.69.6

HighwayHighway 2.082.08 0.340.34 50.350.3 5.65.6

PasturePasture 2.482.48 0.4760.476 94.394.3 5.15.1

General agriculturalGeneral agricultural 2.322.32 0.3440.344 55.355.3 3.83.8

Open spaceOpen space 1.251.25 0.0530.053 11.111.1 1.451.45

Adapted from Harper, H. H. (1998).

Land Use Specific EMCs (mg/L)Land Use Specific EMCs (mg/L)

EMCEMC

AdvantagesAdvantages

Allows evaluation of various land use scenariosAllows evaluation of various land use scenarios

It’s simple (cheap)It’s simple (cheap)

DisadvantagesDisadvantages

Too simple?Too simple?

Ignores high variability (spatially and temporally)Ignores high variability (spatially and temporally)

No statistically significant difference between urban No statistically significant difference between urban land uses (NURP)land uses (NURP)

Examples – Pondnet (Walker)Examples – Pondnet (Walker)

Regression ModelsRegression Models

Another approach is to develop empirical Another approach is to develop empirical relationships between runoff concentration relationships between runoff concentration and predictor variablesand predictor variables FlowFlow Land useLand use SoilsSoils ClimateClimate

Regression ModelsRegression Models

10

100

1000

1 10 100 1000

Flow (cfs)

Chl

orid

e (m

g/L)

1

10

100

1000

1 10 100 1000

Flow (cfs)

TS

S (

mg/

L)

Regression ModelsRegression Models

AdvantagesAdvantages Allows evaluation of various land use & soilsAllows evaluation of various land use & soils Still pretty simpleStill pretty simple

DisadvantagesDisadvantages Can account for spatial and temporal Can account for spatial and temporal

variabilityvariability Not mechanisticNot mechanistic

Examples - Tasker & Driver (1988), SWMM, Examples - Tasker & Driver (1988), SWMM, SWATSWAT

Build-Up / Wash-OffBuild-Up / Wash-Off

Build-up & wash-offBuild-up & wash-off Mass balance of pollutants on impervious surfacesMass balance of pollutants on impervious surfaces A constant rate of accumulationA constant rate of accumulation A first-order rate of non-runoff removalA first-order rate of non-runoff removal

kMLdt

dM kML

dt

dM

AccumulationNon-runoffremoval

Build-Up / Wash-OffBuild-Up / Wash-Off

0

5

10

15

20

25

0 10 20 30 40 50

Antecedent Dry Days

Mas

s (k

g/m

2)

0

0.2

0.4

0.6

0.8

1

0 0.5 1 1.5 2 2.5

Daily Rainfall Intensity (in/hr)

Fra

ctio

n M

ass

Rem

aini

ng

Build-Up

Wash-Off

Build-Up / Wash-OffBuild-Up / Wash-Off

Advantages Advantages More mechanistic approachMore mechanistic approach Hopefully more broadly applicableHopefully more broadly applicable

DisadvantagesDisadvantages More complicatedMore complicated Lack the data needed to calibrate this modelLack the data needed to calibrate this model Doesn’t address contributions from pervious Doesn’t address contributions from pervious

areasareas Examples – P8, SLAMM, SWMM, SWATExamples – P8, SLAMM, SWMM, SWAT