PCSWMM / SWMM modeling capabilities

Rob James, Nandana Perera, Karen Finney, and Mark RandallComputational Hydraulics Int. (CHI)

1977SWMM ported to minicomputer

1981EPA SWMM 3released

1984PCSWMM released1st PC versionFORTRAN

1988EPA SWMM 4released

2004EPA SWMM 5released

1991PCSWMM4First GUI versionBASIC

1995PCSWMM ‘95First 32-bit Windowsversion - Visual Basic

1998PCSWMM ’98First GIS-based versionVisual Basic

2002PCSWMM 2002Genetic algorithmbased calibration

IBM PC/AT Intel 80-486 IBM PowerPC Intel Pentium III Intel Quad Core

1993SWMM-USERSlistserv

2007PCSWMM.NETFirst multi-threadedversion - C#, .NET 3.5

2011-2012PCSWMM 2011• Real-time flood

forecasting• Integrated 2D

modeling• French, Spanish,

Chinese language versions

Intel i7

Processing power increase over the history of PCSWMM

100,000,000

TIMES

PCSWMM`s computational grid at CHI

1,000,000,000,000

FLOPS

So how much is 1 trillion floating point operations?

1 x 60s x 60m x 2100h x 40y

302,400,0001,000,000,000,000

= 0.03%

Overview

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Jeffries, 2006

Area-duration-frequency analysis

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

California delta

California delta

California delta

California delta

California delta

California delta

California delta

Resolution

• Unlimited number of entities• Variance can be systematically reduced

by including (explaining) more and more relevant processes, at a higher time and spatial resolution.

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Resolution

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Time Time

Rain

fall

Flow

1m1min 0.01s

Temporal Spatial

Hydrology

PrecipitationClimatologyLand surfacesGroundwater

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Precipitation

• Dynamic rainfall• Snow• Radar-rainfall• Calibration events• Credible continuous time series• Design storms

Resolution

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Time

Rain

fall

Rain gauge-calibrated radar rainfall

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Radar fills in the blanks between rain gauges

Z-R relationship and bias removal

Rain gauge-calibrated radar rainfall• Leverages the spatial resolution and

remote sensing capabilities of radar• Produces rain gauge-calibrated radar

rainfall• Area-weights individual subcatchment

hyetographs• Determines storm speed and direction

to forecast up to 3 hours aheadC O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Radar Rainfall Repository

NOAA WSR-88D ServerRain & Flow Gauge Network

SQL ServerDatabase

PCSWMM Radar Acquisition & Processing

PCSWMM Real-Time Flood Inundation Forecasting

Climatology

• Temperature• Wind speed• Potential evaporation

Land surfaces

RainfallRun-on

Infiltration

Evaporation

ddp

Runoff (Q)

2/13/5p S)dd(

n49.1WQ

GroundwaterInfiltration

Deep percolation

Evapotranspiration

PercolationLateral flow

Unsaturatedzone

Saturatedzone

Discretization

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Impervious

Pervious

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Observed data

Validation

Green infrastructure

• Infiltration trenches• Bio-retention cells• Porous pavement• Vegetative swales• Rain barrels

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Bio-retention cell

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

RainfallRun-onRunoff

Infiltration

Drainage

Deep percolation

Evapo-transpiration

Surface

Growingmedia

Storagemedia

Percolation

Porous pavement

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

RainfallRun-onRunoffInfiltration

Drainage

Deep percolation

Pavers &sand

Storagemedia

Hydraulics

ChannelsCulverts & bridgesPonds, lakes & wetlandsControl structures & urban drainage

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

ChannelsLeft overbank Right overbankChannel

Channels

• Import from HEC-RAS• Reaches• Cross-sections• Losses• Bridges & culverts

• Auto-delineate from DEM• Overbank & center channel averaging

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

HGL comparison (HEC-RAS)

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Bridges

High chordLow chord

Piers

Transect

Culverts

Flared wingwalls

Double-barrelled

FHWA equations*57 configurations

* Hydraulic Design of Highway Culverts, FHWA-NHI-01-020, May 2005

Culverts Inlet/outlet controlSuper/sub-critical transitionsSurcharged & reverse flow

Culverts & pipes

• 25+ closed and open conduits

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Arch pipe Elliptical Partially-filled

Culverts & swales

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

In-stream erosion

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

In-stream erosion

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Bank effective Workindex

Bed effective work index

Ponds, lakes & wetlands

Area Depth Time

Stag

e

Dis

char

ge

Flow

Bottomorifice

Sideorifice

Overflowweir

Tailwater effect

Irrigation

Storage & treatment

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

TimeTS

S lo

adin

g Inflow

Outflow

Treatment plants

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Treatment train

Control structures

• Weirs• Orifices• Pumps• Rules

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Diameter Width

Height

Offset Offset

V-notch Transverse / side flow

Control structures

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Dual-drainage

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Manhole

Manhole

Dynamicinteractionthroughcatch-basins

Discharge

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Time

WSE

Receivingwater

FixedTime series

Tidal

Freeor normal

Water Quality

Build-upWash-offTransportTreatment

Build-up

• Empirical equations based on land-use, time

• Loading from time series

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Time

Load

Exponential

Time series

Power/saturation

Build-up

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Power function

Exponential function

Saturation function

External time series• Uses a time series to describe the rate of buildup

),( 321

CtCCMinB

)1( 21

tCeCB

tCtCB

2

1

Wash-off

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Exponential function

Rating curve

Event mean concentration • special case of rating curve method where C2=1

BqCW C21

21

CQCW

Integrated form of complete mixing quality routing

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

)()()()()()()( tVtKCtCtOtCtIdtVCd I

Where:V = reservoir volume, ft3

CI = influent pollutant concentrationC = effluent and reservoir pollutant concentrationI = inflow rateO = outflow rate t = timeK = decay coefficient

TreatmentTreatment expressions have the general form:

R = f(P, R_P, V) or

C = f(P, R_P, V) where:

R = fractional removal,C = outlet concentration,P = one or more pollutant names,R_P = one or more pollutant removalsV = one or more process variables (FLOW, DEPTH, HRT, DT, AREA)

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

Calibration & error analysis

• Demo• SRTCintroduction.mp4

C O M P U T A T I O N A L H Y D R A U L I C S I N T E R N A T I O N A L

PCSWMM 2013