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Fifty Years Of Watershed Modeling - Past, Present
And Future
Proceedings
2012
Modeling Urban Watersheds Impacted by CSOs
and SSOs
Ted Burgess
CDM Smith, USA
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Recommended Citation
Ted Burgess, "Modeling Urban Watersheds Impacted by CSOs and SSOs" in "Fifty Years Of Watershed Modeling - Past, Present And
Future", A.S. Donigian, AQUA TERRA Consultants; Richard Field, US EPA (retired); Michael Baker Jr., Inc. Eds, ECI Symposium
Series, (2013). http://dc.engconfintl.org/watershed/20
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MODELING URBAN WATERSHEDS IMPACTED BY CSOS AND SSOS
Ted Burgess
Fifty Years of Watershed Management –
Past, Present and Future
September 24‐26, 2012
Presentation Agenda
•
•
•
•
•
•
•
Current state of modeling software
Developing dry‐weather flow rates
Rainfall data used in model calibration
Si l
Single‐event and continuous model calibration
d
i
d l lib i
Flow data analysis for model calibration
Modeling green stormwater infrastructure
Modeling green stormwater
Integration of (increasingly digital) field data and SCADA with collection system models
Urban Watershed / Collection Systems Models
Aqualyze
q y – h3O
Bentley – SewerGEMS, SewerCAD
BOSS – StormNET
CHI (C d ) PCSWMM
CHI (Canada) –
DHI (Denmark) – MIKE URBAN
Delft (Netherlands) –
elft (Netherlands) SO
SOBEK
K
Innovyze (formerly MWH Soft) – InfoSWMM, InfoSewer, InfoWorks (formerly Wallingford Software, UK)
• U.S.ACE –
U S ACE HEC‐HMS / HEC‐RAS HEC HMS / HEC RAS
• U.S.EPA – SWMM 5
(
) xpswmm
p
• XP Software (Australia) –
•
•
•
•
•
•
•
U S EPA SWMM 5 and Commercial “Spin‐offs”
U.S.EPA SWMM 5 and Commercial Spin‐offs
Aqualyze h3O
xpswmm
p
Bentley SewerGEMS
Innovyze
y InfoSWMM
BOSS StormNET
CHI PCSWMM
DHI MIKE URBAN
Gal/day/capita Water/Sewer Billing Analysis / y/ p
/
g
y
• Data source requirements: – Water (or sewer) billing records for winter periods
W t (
) billi
d f
i t
i d
– Geo‐reference property addresses to model catchments
Sewer Billing Data – Catchment Level
Sewer Billing Results
Radar‐Rainfall Analysis: 2031 grid cells vs 49 rain gauges
2031 grid cells vs. 49 rain gauges
Example: Area Weighted Radar‐Rainfall X
Basin BW‐AL‐14 (352.618 ac or 1.427 km2)
Area weights for each pixel
Area covered by radar pixels (1 * 1 km2)
Area Weighted Radar Rainfall for the basin is calculated as:
= 29.7%* + 1.5%* + 32.5% * + 36.4%*
Selecting Calibration Storms
Selecting Calibration Storms (continued)
Unit Hydrograph Methodology in SWMM 5: Continuous
Simulation of Rainfall‐Dependent Inflow/Infiltration
Rainfall Data Analysis for Continuous Simulation
Seasonal Wet Weather Response Growth vs. Dormant Variability in Mean Dmax
U.S.EPA’s Sanitary Sewer Overflow Analysis and Planning (SSOAP) Toolbox
Planning (SSOAP) Toolbox
SSOAP Toolbox - Data Flow
External Data Sources
Sewer System
Time Series
Flow
Velocity
Depth
Time Series
Rainfall
SSO Volume
Capture Flow Volume
Overflow Frequency
q
y
Flooding Locations
Pipe Capacity
Sewer System
GIS Database
D t b
Flow Monitoring
Data
Rainfall
Data
Hydraulic
Analysis
Data
Internal Data Sources
Sewer System
Flow Data
Rainfall Data
RDII Analysis
T l
Tool
RTK parameters
Rainfall Data
Sewer System
Database
Management
Tool
DWF analysis results
Wet-weather selection results
WWF analysis results
RDII results
Event based RTK parameters
RTK predictive analysis results
RDII
Hydrograph
Generation
Tool
RDII
Hydrograph
SSOAP
System
Database
in MS-ACCESS
SSOAP-SWMM5
Interfacing
Tool
SWMM 5 Input File
SWMM 5 Input File with RDII Hydrograph
SWMM 5
Example Calibration Results: Continuous RDI/I in SWMM5 OL-UP-10
RainFall ((in)
0.0
0.1
01
0.1
0.2
0.3
0.4
Depth (ft)
0.8
4
3
2
1
Flow (mgd)
0.2
3
2
4
0.8
0.6
4
3
2
1 Sun
Jun 2008
8 Sun
15 Sun
Date/Time
22 Sun
STA_OL-UP-10
0742S0009
0742S0009 (obs)
0742S0010:0742S0009
0742S0010:0742S0009 (obs)
0.0
Velocity
y (ft/s)
Velocity (ft/s)
Flow (mgd)
Depth (ft)
RainFall (in)
OL-UP-10
STA_OL-UP-10
0742S0009
0742S0009 (obs)
0742S0010:0742S0009
0742S0010:0742S0009 (obs)
0.6
0.4
1
3
2
1 Mon
Sep 2008
1 Tue
Depth (ft)
0.8
06
0.6
4
Flow (mgd)
Flow (mgd)
0.4
3
2
Velocity (ft/s)
1
3
2
8 Mon
Dec 2008
15 Mon
Date/Time
15 Mon
Date/Time
22 Mon
OL-UP-10
STA_OL-UP-10
_
0742S0009
0742S0009 ((obs))
0742S0010:0742S0009
0742S0010:0742S0009 (obs)
RainFall (in)
0.00
0.05
0.10
0.15
Velocity (ft/s)
Depth (ft)
RainFall (in)
OL-UP-10
8 Mon
22 Mon
1 Thu
0.000
STA_OL-UP-10
_
0742S0009
0742S0009 ((obs))
0742S0010:0742S0009
0742S0010:0742S0009 (obs)
0.025
0.050
0.075
0.75
0 50
0.50
0.25
0.00
3
2
Auto-calibration approaches
using Genetic Algorithm-based
2
techniques and graphical tools
0
1 Thu
8 Thu
15 Thu
22 Thu
1this
Sun
8process.
Sun
15 Sun 22 Sun
1 Sun
can
facilitate
Jan 2009
Date/Time
1
0
4
Continuous simulation runtimes for large q
networks still require skeletonization
Modeling the relationship between sanitary/combined sewers and storm sewers for SSO / CSO control
sewers and storm sewers for SSO / CSO control
Initial Abstraction
Groundwater Recharge
(Deep Infiltration)
Infiltration
Infiltration to Collection Systems
Precipitation
Infiltration to Stormwater or Combined Collection System
Infiltration to Sanitary Sewer System
Runoff to Stormwater Collection System
Runoff
Green Stormwater
Infrastructure
Direct Inflow to Sanitary or Combined S
Sewer System
S t
Session II – Modeling Urban Watersheds Impacted by CSOs and SSOs
19
Changes in SWMM5 facilitate green stormwater
infrastructure modeling
infrastructure modeling
Catchment routing –
g
traditional approach
Catchment routing –
g
new SWMM 5 options
Transfer
Transfer
Effective
I
Impervious
i
(DCIA)
Pervious
Inlet
I
Impervious
i
Pervious
Receiving
Catchment
SWMM5 LID Control Editors
Bio-Retention
Porous Pavement
Vegetative Swale
Infiltration Trench
Rain Barrel
Modeling
21
Digital advancements in other sewer system technologies allows integration of modeling with field information
3D Viewer Tool: Linking system condition and GIS data with sewer network data
and GIS data with sewer network data
SCADA integration example: Key Flow Control Structure
Whittier Street Regulator Gates
T B li
To Berliner Park
P k
Regulator Gates
N
From/to DSR83
/
Whittier Street Storm Tanks
Modeler’s View of Collection System
Operator’s Views of Collection System
SCADA display of selected system conditions
SCADA
to
SWMM5
Control
Rules
Editor
Conclusions • As computers get faster, models get bigger and p
g
,
g
gg
more detailed (so we still live with long runtimes)
– CSO modeling: Typical year sufficient – no problem
– SSO modeling: Design targets ~ 2‐10 year return periods – require much longer simulation periods and impractical runtimes
• Current focus on green stormwater infrastructure imposes new demands on established watershed modeling tools
modeling tools
• Convergence of field data tools (inspection databases, SCADA) and modeling tools is opening
databases, SCADA) and modeling tools is opening up new capabilities