Three Inertial Term Options in SWMM 5 and InfoSWMM/H2OMAP SWMM

Subject:  Three Inertial Term Options in SWMM 5 and InfoSWMM/H2OMAP SWMM

The dynamic wave flow in SWMM5 and InfoSWMM is calculated from the following equation

Q  =   (Qold – dq2 + dq3*sigma +  dq4*sigma ) / ( 1  + dq1 + dq5)

Where,

Qold               =         Last Time Step Flow in the Link

dq1                 =         friction loss term

dq2                 =         water suface slope + bed slope term

dq3                 =         midpoint area non linear term

dq4                 =         upstream and downstream area non linear term

dq5                 =         Entrance, Other and Exit Loss Term

sigma            =         function of the Froude number and a function of the Three Intertial Term Options

Figure 1 shows how Sigma is set based on the user selection of the Three Intertial Terms.  Figure 2 shows how Sigma is calculated for the Dampen Option.  If you use Ignore then dq3 and dq4 are ignored all of the time, if you use Dampen then dq3 and dq4 are used for a Froude number less than 0.5 and then the terms gradually fade away until a Froude number of 1 is reached.   If you use Keep then the non linear terms are used all of the time no matter the value of the link Froude Number. There is one exception to this rule: If a closed link is full then the value of sigma is set to 0.0 no matter what is selected for the Intertial Term.

Figure 1.  The value of Sigma for each of the Three Inertial Term Options in SWMM 5 and InfoSWMM/H2OMAP SWMM

Figure 2.  At each iteration for each link during the simulation the link Froude Number is calculated and based on the Froude Number the value of Sigma is Set.

Link Simulated Parameters used in either the Normal Flow or St Venant Equation of SWMM 5

Subject:  Link Simulated Parameters used in either the Normal Flow or St Venant Equation of SWMM 5

St. Venant equation – this is the link attribute data used when the St. Venant Equation is used in SWMM 5.  Simulated Parameters from the upstream, midpoint and downstream sections of the link are used.

Normal Flow Equation – this is the link attribute data used when the Normal Flow Equation is used in SWMM 5. Only simulated parameters from the upstream end of the link areused if the normal flow equation is used for the time step.

Exit, Other and Entrance Loss Values in SWMM 5, InfoSWMM

Subject:  Exit, Other and Entrance Loss Values in SWMM 5, InfoSWMM

The entrance, exit and other losses in SWMM 5 are computed at the upstream, downstream and midpoint of the sections of the link.  However, if the normal flow equation is used for the link during a time step then these losses are zero as the flow in the link is based solely on the upstream area and upstream hydraulic radius of the link.   If you add loss coefficients and the normal flow equation is used then you will not see any change in the flow as you modify the loss coefficients.

The Groundwater Flow Component in SWMM5

Subject:  The Groundwater flow in SWMM 5 Groundwater

The Groundwater flow in SWMM 5 is actually made up of three components:

1.   A groundwater flow computed from the coefficient a1 and exponent b1

2.   A groundwater flow computed from the coefficient a2 and exponent b2 and

3.   A Surface Water / Groundwater Interaction coefficient a3

The total Groundwater flow is the sum of the flow from 1, 2 and 3 – normally 2 is the opposite of 1.

RDII Initial Abstraction in SWMM 5

Subject:  RDII Initial Abstraction in SWMM 5

The initial abstraction in each of the three components of RDII in SWMM 5 are updated at each time step.  The initialabstraction (ia) is:

ia = iaMax - iaUsed

based on the maximum amount of ia, the ia used (iaUsed), the recovery rate (iaRecov) and the month and class of RDII.  You can enter a value for iaMax, iaInit and iaRecov for each month.

The iaUsed at the beginning of the simulation is set equal to iaInit

and if there is no rainfall

RDII Parameters for SWMM 5

Subject:  RDII Parameters for SWMM 5

There are three types of RDII Response, six different parameters and an annual and optional twelve monthly sets of distinctparameters.

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Steady State Flow Analysis in InfoSWMM using a Ramp DWF

Subject:  Steady State Flow Analysis in InfoSWMM using a Ramp DWF

This can be easily created using a few steps in InfoSWMM. 

Step 1:  Using Scenario Explorer make a cloned Child Scenario and a cloned DWF Set which will be later modified.

Step 2:  Using DB Manager and the BlockEdit tool and increase the mean DWF by a factor of 10, 100 or 1000 to drown out all Wet Wells and cause the pumps to turn on and stay turned on during the simulation in the newly created DWF Set.

Step 3.  Run the batch manager and create two output files – Normal and Steady State for comparison.

Step 4.  You can now compare the two scenario's using Output Manager and the Compare Graph tool.  The Ramped Model should have constant flows in both links and pumps.  It was not necessary to change any of the patterns.

Step 5.  The model is still  in balance – the excess DWF Inflow ends up as flooded flow and is listed as Internal Outflow.

Steady State Flow Analysis in InfoSWMM using an External Flow Time Series

Subject:  Steady State Flow Analysis in InfoSWMM using an External Flow Time Series

This can be easily created using a few steps in InfoSWMM.  The flow ramp is in the Routing Interface File.  The advantage is that you are able to have different ramps for the various nodes using this method.

Step 1:  In Run Manager Set up the Process Models Options to use just the External Inflow and NOT the Dry Weather Flow

Step 2.  Create the External Inflows File (see the help file for the format)

SWMM5 Interface File

300  - reporting time step in sec

1    - number of constituents as listed below:

FLOW CFS

2    - number of nodes as listed below:

36

24

Node             Year Mon Day Hr  Min Sec FLOW     

36               2002 01  01  00  00  00  0.000000 

24               2002 01  01  00  00  00  0.000000 

36               2002 01  01  01  00  00  1000.000000 

24               2002 01  01  01  00  00  1000.000000 

36               2002 01  02  01  00  00  1000.000000 

24               2002 01  02  01  00  00  1000.000000   

This file loads two manholes with a ramped inflow up to 1000 cfs to again drown out the wet wells and cause the pumps to have a steady flow.

Step 3.  Use the Tab File command and use the created External Inflows File

Step 4.  Run the simulation and see if the pump flows are constant.

InfoSWMM and Arc GIS for Surcharge and Flooded Time

Subject:  InfoSWMM and Arc GIS Layer Properties for Surcharge and Flooded Time

An important advantage of using InfoSWMM is the ability to use all of the Arc GIS layer and programming tools.  For example, you can graph the model results for the flooded and surcharged time in a node using a Bar/Column plot to show the surcharge time in the node and the flooded time in the node.  A flooded node is always considered to be surcharged but a surcharged node does not always flood.  The surcharge level is any water surface elevation above the highest connecting crown elevation but the flooded time is a water surface elevation at or exceeded the rim elevation of the node.

InfoSWMM and Arc GIS Layer Properties for Surcharge and Flooded Time

InfoSWMM and Arc GIS for Create Graphs Using Network Data and Model Results

Subject: InfoSWMM and Arc GIS for Create Graphs Using Network Data and Model Results

An important advantage of using InfoSWMM is the ability to use all of the Arc GIS layer and programming tools.  For example, you can graph the model results in Bar,  Pie, Scatter, Bubble or other types of Graphs once the model data and model result layers are Joined together.  The image below shows a thematic mapping for Node Flooding, Conduit Force Main Type and a Pie and Bar Chart of Node Flooding Time and the Q Full in the links, respectively.

World Wide Visitor Coverage of WWW.SWMM2000.COM

Note:  For the 1^st time in 4 years we have had a visitor from Central Asia.  This now means we have had visitors from all Google defined Geographic Regions on Earth even though we still have not had visitors from every country at www.swmm2000.com  The statistics below exclude the 58 percent visitors from North America but overall we have had on September 3rd, 2011 (1st column) compared to August 3, 2013 (2nd column)

1.   40,190 Visitors to 78,840 Visitors in 2013(Cumulative)
2.   22 Continental Regions to 23 Regions
3.   157 Countries  to 179 Countries
4.   5951 Cities to 6235 Cities
5.   100,180 Pageviews in 2011 to 193,142 Pageviews in  2013(Cumulative)
6.   86 Languages to 106 Languages

Statistics from 2013 

Statistics from 2011

InfoSWMM 2D Layer Properties and Mesh ID

Subject:   InfoSWMM 2D Layer Properties and Mesh ID

You can use the Layer Properties for layers in the Table of Contents to see the Mesh ID and other simulation data for the 2D mesh in InfoSWMM 2D.  The Mesh ID can be seen using the Labels/Label Expression command and if you use an expression you can see the results data as well on the mesh.  The Mesh ID is used as the label as well in the 2D Output modeling report.  The Net Inflow and Net Outflow is by Mesh ID.  In this example, the flow comes out of Node 80408 to Mesh ID 131 and enters the 1D network again at Mesh ID 848.

Detention Pond Infiltration and Evaporation Losses in SWMM 5

Subject:  Detention Pond Infiltration and Evaporation Losses 

You can also add a storage pond infiltration and surface evaporation losses to the pond.  The surface evaporation is added to theinfiltration (computed from the green ampt parameters); a storage volume summary listing the average and maximum volume and the percent loss from the combined infiltration and evaporation from the ponds.  The pond infiltration loss during a time step is basd on the areal weighed average depth, the Green Ampt infiltration and the Area of the pond.

Detention Basin Basics in SWMM 5

Subject:  Detention Basin Basics in SWMM 5

What are the basic elements of a detention pond in SWMM 5?  They are common in our backyards and cities and just require a few basic elements to model.  Here is a model in SWMM 5.0.022 that even has a fountain in the real pond – which we not model for now.   The components of the model are:

1.   An inlet to the pond with a simple time series – a subcatchment can be added to it in a more complicated model but for now we will just have a triangular time series,

2.   A pipe to simulate the flow into the pond from the inlet,

3.   A Storage Node to simulate the Pond that consists of a tabular area curve to estimate the depth and area relationship,

4.   A Storage Node to simulate the Outlet Box of the Pond

5.   Two Small Rectangular Orifices to simulate the low flow outflow from the pond at an elevation less than the weir

6.   A large rectangular orifice to simulate the normal inflow to the Box

7.   A rectangular weir to simulate the flow into the box when the pond water surface elevation is above the box

8.   The outlet of the Box is a circular link with a Free outfall as the downstream boundary condition

9.   The flow graph in the image shows the flow into the box starts from the two small orifices, next from the large orifice and finally from the top of the box or the weir.

How the State InfoSewer solution solves for the link flow and node heads

Note: State InfoSewer solution solves for the link flow and node heads

Here is an example of how the Steady State InfoSewer solution solves for the link flow and node heads or depths:

•         1^ST Flow is computed in each link and d and d/D is calculated based on pipe flow and manhole loading data and not the adjusted data from the 2^nd pass.

•         2^nd InfoSewer adjusts the link depth based on the manhole head and lists the adjusted depth in the browser and the Report Table after the manhole depths are calculated from downstream to upstream in the network.

•         Result: The HGL graph shows the link d and d/D based on pipe flow not the adjusted depth so you are looking at the results of the 1^st pass in the links and the 2^nd Pass in the Nodes in a HGL Plot  for a Steady State Simulation.

Here is one example of this sequence of events: The downstream head at the outfall causes a backwater condition in all of the links.  The d/D and q/Q is based on the manhole loading flow in the 1st pass and indicates the pipe is NOT full. However, in the 2nd Pass where the manhole depths are calculated from downstream to upstream the effect of the downstream boundary condition is felt.  The head shows that there is a full downstream boundary condition which is reflected in the condition of backwater and in the adjusted depth value.  The links are now full and the full depth is reflected in the value of the adjusted depth and the graphical presentation.

How to interpret this result:

1.   Based on the manhole loading to the network the pipes are NOT full which is indicated by the value of d/D and q/Q, however

2.   Based on the head calculations which account for downstream boundary conditions the pipes are full due to the backwater effect.  The backwater condition is reflected in the value of the adjusted depth – the adjusted depth shows the pipe to be full.

Figure 1.  Backwater is caused by the downstream boundary condition and shows full pipes but d/D is less than 1 based on the 1^st Pass Link Flow Values.

Figure 2. InfoSewer solves for the flows in the links in the 1^st pass and the heads at the nodes in the 2^nd pass for the Steady State solution.

Figure 3.  Pipe Summary Table Shows the Pipe Adjustments based on 2^nd Pass Head calculations and the d/D and q/Q values from the 1^st Pass Link Flow Calculations.

Figure 4:  Two Pass Solution for InfoSewer (1) Flow and (2) Head

InfoSewer Maximum Number of Segments Sensitivity

InfoSewer Maximum Number of Segments Sensitivity

The three Run manager parameters, Maximum Number of Segments, Minimum Travel Distance and the Minimum Travel Distance in InfoSewer and H2OMAP Sewer affect the shape and flow attenuation of the flow in a link.  The effect of decreasing the Minimum Travel Distance is to reduce the peak flow and spread out the flow as the number of segments increases(Figure 1).  The smaller the minimum travel distance, which has the effect of increasing the number of segments in a link up the limit of the parameter Maximum Number of segments, the smaller the peak and the more attenuation of the flow in InfoSewer.

There is three ways to control attenuation in InfoSewer: (1) use the flow attenuation option, (2) increase the Maximum Number of Segments per link and (3) decrease the Minimum travel distance.    You can also use all three parameters to make more segments per link for long links and only a few segments for short links.

Additional Features in InfoSWMM and InfoSWMM SA

Subject:   Additional Features in InfoSWMM and InfoSWMM SA

The additional features supply the tools for your modeling or modelling:

1.   Dry Flow Allocation for your Sanitary or Combined Sewer Model
2.   Subcatchment Manager to estimate the impervious, slope, width and area of your Subcatchments,
3.   RDII Analyst to estimate the Infiltration/Inflow into your Sanitary Network,
4.   Calibrator to help calibrate the model data to monitored data
5.   Designer to design new links to prevent flooded or surcharge,
6.   InfoSWMM 2D to link your 1D network to a 2D network
7.   CapPlan for Capacity Analysis and Capital Planning,
8.   Pond Design for Stormwater Ponds
9. Import from InfoSewer and Import/Export from SWMM5
10. Hydraulic Engines for InfoMaster Sewer

Contrasting Add On Features for InfoSWMM and H2OMap SWMM

InfoSWMM	H2OMAP SWMM
Calibator	Calibator
Conduit Storage Synthesizer	Conduit Storage Synthesizer
Designer	Designer
DWF Allocator	DWF Allocator
InfoSWMM 2D	n/a
InfoSWMM CapPlan	InfoSWMM CapPlan
NetView to KML	NetView to KML
Pond Design	Pond Design
RDII Analyst	RDII Analyst
Risk Assesment Manager	n/a
Subcatchment Manager	n/a
InfoSWMM SFEM	n/a
An Engine for InfoMaster Sewer	An Engine for InfoMaster Sewer
Imports InfoSewer, SWMM 5, H2OMAP SWMM, HEC-RAS Geometry	Imports H2OMap Sewer, SWMM 5, InfoSWMM, HEC-RAS Geometry

Variables for Controlling the Continuity Error in InfoSWMM and H2OMAP SWMM compared to SWMM 5

Subject:  Variables for Controlling the Continuity Error in InfoSWMM and H2OMAP SWMM compared to SWMM 5

Time step is always a key parameter in SWMM 5 as it is the main parameter for a user to adjust in case of a significant continuity error.   InfoSWMM has additional flexibility and allows the user to control the number of Picard iterations and the Node continuity stopping tolerance.   SWMM 5.0.022 has the number of iterations fixed at 8 and the stopping tolerance fixed at 0.005 feet.   The stopping tolerance is important because it controls the number of iterations during a time step.  For example, if all of the Nodes have a current and former iteration depth difference (absolute) less than 0.005 feet then the time step is deemed converged and the node and link flow computations are stopped for that time step.  In SWMM 5 since the stopping tolerance is fixed then your main option is to reduce the time step.  In InfoSWMM you can also decrease the stopping tolerance, increase the number of iterations or decrease the time step.  In most models it is best to alter all three parameters for the fastest model.  For example, a slightly smaller maximum time step or a smaller variable time step adjustment factor, more iterations and a smaller tolerance will normally work better than just lowering the time step.

Iterations and Stopping Tolerances