SWMM6 & SWMM5 Enablement

Stormwater modeling notes, decoded.

SWMM5, SWMM6, XPSWMM, InfoSWMM, InfoSewer, OpenSWMM, and ICM — engine internals, error messages, calibration, and hard-won field wisdom from Robert Dickinson.

Browse error-message fixes EPA SWMM downloads

Five Parameters beside the Maximum Time Step that help control simulation length in InfoSWMM and SWMM

· May 18, 2013
FYI, If you like twitter and like to center your embeded tweets add this to the custom twitter code How to center your embedded tweets class="twitter-tweet tw-align-center">

From 3QD - THE MATHEMATICS OF ROUGHNESS

· May 08, 2013

THE MATHEMATICS OF ROUGHNESS

Holt_1-052313_jpg_230x1466_q85
Jim Holt reviews Benoit B. Mandelbrot's The Fractalist: Memoir of a Scientific Maverick, in the NYRB:
Benoit Mandelbrot, the brilliant Polish-French-American mathematician who died in 2010, had a poet’s taste for complexity and strangeness. His genius for noticing deep links among far-flung phenomena led him to create a new branch of geometry, one that has deepened our understanding of both natural forms and patterns of human behavior. The key to it is a simple yet elusive idea, that of self-similarity.
To see what self-similarity means, consider a homely example: the cauliflower. Take a head of this vegetable and observe its form—the way it is composed of florets. Pull off one of those florets. What does it look like? It looks like a little head of cauliflower, with its own subflorets. Now pull off one of those subflorets. What does that look like? A still tinier cauliflower. If you continue this process—and you may soon need a magnifying glass—you’ll find that the smaller and smaller pieces all resemble the head you started with. The cauliflower is thus said to be self-similar. Each of its parts echoes the whole.
Other self-similar phenomena, each with its distinctive form, include clouds, coastlines, bolts of lightning, clusters of galaxies, the network of blood vessels in our bodies, and, quite possibly, the pattern of ups and downs in financial markets. The closer you look at a coastline, the more you find it is jagged, not smooth, and each jagged segment contains smaller, similarly jagged segments that can be described by Mandelbrot’s methods. Because of the essential roughness of self-similar forms, classical mathematics is ill-equipped to deal with them. Its methods, from the Greeks on down to the last century, have been better suited to smooth forms, like circles. (Note that a circle is not self-similar: if you cut it up into smaller and smaller segments, those segments become nearly straight.)
Only in the last few decades has a mathematics of roughness emerged, one that can get a grip on self-similarity and kindred matters like turbulence, noise, clustering, and chaos. And Mandelbrot was the prime mover behind it. 
Posted by Robin Varghese at 12:51 PM | Permalink 

Increase in heavy rainfalls over past 60 years in upper Midwest, US

· March 14, 2013

Increase in heavy rainfalls over past 60 years in upper Midwest, US

http://www.sciencedaily.com/releases/2013/03/130313182312.htm
March 14, 2013
Mar. 13, 2013 — Heavy rains have become more frequent in the upper Midwest over the past 60 years, according to a study from the University of Iowa. The trend appears to hold true even with the current drought plaguing the region, the study's main author says.
The fact that temperatures over the country's midsection are rising, too, may be more than coincidence. The hotter the surface temperature, which has been the trend in the Midwest and the rest of the world, the more water that can be absorbed by the atmosphere. And the more water available for precipitation means a greater chance for heavy rains, explains Gabriele Villarini, assistant professor in engineering at the UI and lead author of the paper, published in the Journal of Climate, the official publication of the American Meteorological Society.
"We found that there is a tendency toward increasing trends in heavy rainfall in the northern part of the study region, roughly the upper Mississippi River basin," says Villarini, in the civil and environmental engineering department and an assistant research engineer at the IIHR-Hydroscience and Engineering. "We tried to explain these results in light of changes in temperature. We found that the northern part of the study region -- including Minnesota, Wisconsin, Iowa, and Illinois -- is also the area experiencing large increasing trends in temperature, resulting in an increase in atmospheric water vapor."
Villarini notes the current drought affecting the Midwest and other regions of the country has occurred too recently to be included in his study, whose data goes from about 1950 to 2010.
"I'm not looking at the average annual rainfall. I'm studying heavy rainfall events," he says. "We may currently be in deficit for overall rainfall, but we may also be in the normal range when it comes to the number of heavy rainfall days."
Villarini and his colleagues examined changes in the frequency of heavy rainfall through daily measurements at 447 rain gauge stations in the central and southern United States. The states included were: Minnesota, Wisconsin Michigan, Iowa, Illinois, Indiana, Missouri, Kentucky, Tennessee, Arkansas, Louisiana, Alabama, and Mississippi.
Each rain gauge station has a record of at least 50 years. The data cover much of the 20th century and the first decade of this century. For the purposes of the study, heavy rainfall was defined as days in which rainfall exceeded the 95th percentile of the at-site rainfall distribution.
Villarini notes that while his study focused on changes in temperature and the frequency of heavy rainfall over the central United States, other published results have shown rainfall increases to be linked to changes in irrigation over the Ogallala Aquifer, which runs from Nebraska to northern Texas. Based on those studies, he says it is reasonable to assume that changes in land use, land cover and agricultural practice would affect the amount of water vapor in the atmosphere as well.
His colleagues in the study are James Smith, professor at Princeton University; and Gabriel Vecchi, of the National Oceanic and Atmospheric Administration.
The research was funded by NASA and the Willis Research Network.
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Story Source:
The above story is reprinted from materials provided by University of Iowa. The original article was written by Gary Galluzzo.
Note: Materials may be edited for content and length. For further information, please contact the source cited above.

Journal Reference:
  1. Gabriele Villarini, James A. Smith, Gabriel A. Vecchi. Changing Frequency of Heavy Rainfall over the Central United States. Journal of Climate, 2013; 26 (1): 351 DOI: 10.1175/JCLI-D-12-00043.1

From the Dish - The Wisdom of Play

· February 10, 2013

The Wisdom Of Play

FEB 10 2013 @ 1:43PM
Mark Rowland meditates on the well-lived life, arguing that it “is play, and not work, that gives value to our lives”:
It might be that most of the things we do in life we do for the sake of something else. But there are still some things we do just to do them — for their own sake and not for the sake of anything else. If the former category is work, then the latter category is play. Work is activity directed at an external goal. Play is activity whose goal is internal or intrinsic to it. In its pure form, play has no external purpose or reward. We play just to play. When my sons’ volleys have been sufficiently consistent and accurate, their tennis coach will instigate a game. He yells, ‘Fruit basket!’ and lobs several balls into the air in quick succession. They have to drop their rackets, run and catch the balls before they stop bouncing. This is done amid much cackling and squeals of delight on their part — almost as if the rest of their lesson was work aimed at unleashing this bout of play. I love watching this, because I cannot imagine a purer form of play. There is no external goal or purpose. My sons do it simply because at that precise moment in time — and the squeals of delight are testament to this — there is nothing in the world they would rather be doing.

Ten years of cumulative precipitation

· January 29, 2013

Ten years of cumulative precipitation

January 28, 2013 to Mapping by Nathan Yau
We've all seen rain maps for a sliver of time. Screw that. I want to see the total amount of rainfall over a ten-year period. Bill Wheaton did just that in the video above, showing cumulative rainfall between 1960 and 1970. The cool part is that you see mountains appear, but they're not actually mapped.  Source on FlowingData
The hillshaded terrain (the growing hills and mountains) is based on the rainfall data, not on actual physical topography. In other words, hills and mountains are formed by the rainfall distribution itself and grow as the accumulated precipitation grows. High mountains and sharp edges occur where the distribution of precipitation varies substantially across short distances. Wide, broad plains and low hills are formed when the distribution of rainfall is relatively even across the landscape.
See also Wheaton's video that shows four years of rain straight up.
Is there more recent data? It could be an interesting complement to the drought maps we saw a few months ago. [Thanks, Bill]

Outlets in SWMM 5 can have reverse flow

· January 26, 2013
Outlets in SWMM 5 can have reverse flow

Outlets in SWMM 5 can have reverse flow (1) if the downstream head is greater than the upstream head (2), a flap gate (3) will prevent the flow reversal (4).  An outlet can have both positive and negative flow as long as you do not prevent it by having a flap gate.


Stopping Tolerance in InfoSWMM, H2OMAP SWMM and SWMM5 Internal Units

· January 17, 2013
Stopping Tolerance in InfoSWMM, H2OMAP SWMM and SWMM5 Internal Units

 InfoSWMM, H2OMAP SWMM and SWMM 5 share the same underlying dynamic engine code but one small difference is that InfoSWMM and H2OMAP SWMM allows the user to select the node stopping tolerance instead of always using the default SWMM 5 stopping tolerance of 0.0005  feet.  SWMM 5 uses internal units of feet and shows the output in meters if you are using SI units, as does InfoSWMM and H2OMAP SWMM.  The following table shows how the stopping tolerance translates to inches and millimeters in the engine of a US and SI model.   The smaller the tolerance the larger the number of iterations used during the simulation but using a very small tolerance does not always mean a better simulation.  If possible, for example, with pumps it is better to use a small time step and a medium level tolerance – for example 1 millimeter is a good starting  value, but maybe 2 or 3 millimeters may help if you have a continuity error at a pump node. 
The nodes are considered converged if the depths between successive iterations is less than the stop tolerance of the program (the default stop tolerance is less than the stopping tolerance (Figure 1)

Stopping Tolerance
Inches
Millimeters
0.1000000
1.2000000
30.4800000
0.0500000
0.6000000
15.2400000
0.0100000
0.1200000
3.0480000
0.0050000
0.0600000
1.5240000
0.0001000
0.0012000
0.0304800
0.0005000
0.0060000
0.1524000
0.0000100
0.0001200
0.0030480
0.0000500
0.0006000
0.0152400
0.0000010
0.0000120
0.0003048
0.0000050
0.0000600
0.0015240
0.0000001
0.0000012
0.0000305

Figure 1  If the node depths between successive iterations are less than the stopping tolerance then the node is considered to be converged.

Importing a Link Shapefile into InfoSWMM via GIS Gateway

· January 17, 2013
Importing a Link Shapefile into InfoSWMM via GIS Gateway

Here is how you map the shapefile pipe fields to the InfoSWMM data fields.  One note, you had two diameter fields (feet and inches) and the feet column was mostly zero so I used the inch column.  Here are the four steps and mapping you need to import all of the data from your shapefile.  You will have to use blockedit and convert the diameter from inches to feet in the DB link table (Step 5 – note there are still three missing pipe diameters).

Step 1.  Use the GIS Gateway command and set up the import of the file name, and ID field

Step 2. Set up the mapping between the Shapefile fields and InfoSWMM.  We used link offset and the pipe diameter in inches.

Step 3. Load the mapped shapefile

Step 4.  The imported data from your shapefile into the DB table of InfoSWMM

Step 5  Convert to feet from inches

Climate-proofing cities

· January 10, 2013
Here's just one example, from Singapore:
Singapore's Marina Barrage.RnD.de.PortraitsSingapore's Marina Barrage.
The Marina Barrage and Reservoir, which opened in 2008, is at the heart of Singapore's two-billion-dollar campaign to improve drainage infrastructure, reduce the size of flood-prone areas, and enhance the quality of city life. It has nine operable crest gates, a series of enormous pumps, and a ten-thousand-hectare catchment area that is roughly one-seventh the size of the country. The system not only protects low-lying urban neighborhoods from flooding during heavy rains; it also eliminates the tidal influence of the surrounding seawater, creating a rainfed supply of freshwater that currently meets ten percent of Singapore's demand. More over, by stabilizing water levels in the Marina basin the barriers have produced better conditions for water sports. The Marina's public areas, which include a sculpture garden, a water-play space, a green roof with dramatic skyline vistas, and the Sustainable Singapore Gallery, bolster the city's tourist economy as well.
That's a brilliant way to address two climate impacts -- large precipitation events and rising sea levels -- at once. Singapore has also elevated all access points to its underground subway a least a meter above high-water flood levels. It's also building desalination plants and systems to reuse waste water. It's also burying its power lines.
Engineers at the Dutch firm Arcadis recently proposed a large new sea barrier for north of New York City's Verrazano-Narrows Bridge. The price tag: $6.5 billion. And that's just one small piece of the puzzle. All this stuff is prudent, but it's expensive.

How to Compile SWMM 5 in Visual Studio 2010 Express

· January 01, 2013
How to Compile SWMM 5 in Visual Studio 2010 Express

Download the newest SWMM 5 code(Figure 1) from http://www.epa.gov/nrmrl/wswrd/wq/models/swmm/#Downloads and then make a new directory on your computer. We will call it c:\newSWMM5Code with a subdirectory C:\newSWMMCode\VC2005_DLL  in which the attached vcxproj file is placed.  The source code from the EPA should be placed on C:\newSWMMCode.  You can then open up the file swmm5_ms.vcxproj and make a new SWMM 5 DLL model with your code modifications (if needed). 

swmm5_ms.vcxproj Download this file

Singapore - Catching Every Drop of Rain

· December 28, 2012
Singapore - Catching Every Drop of Rain

The source of the map of the rivers of Singapore is the Singapore PUB
As a small island that doesn't have natural aquifers and lakes and with little land to collect rainwater, Singapore needs to maximize whatever it can harvest.
Currently, Singapore uses two separate systems to collect rainwater and used water. Rainwater is collected through a comprehensive network of drains, canals, rivers and stormwater collection ponds before it is channelled to Singapore's 17 reservoirs for storage. This makes Singapore one of the few countries in the world to harvest urban stormwater on a large scale for its water supply.
The newest reservoirs are Punggol and Serangoon Reservoirs which are our 16th and 17th reservoirs. By 2011, the water catchment area has increased from half to two-thirds of Singapore’s land surface with the completion of the Marina, Punggol and Serangoon reservoirs.
With all the major estuaries already dammed to create reservoirs, PUB aims to harness water from the remaining streams and rivulets near the shoreline using technology that can treat water of varying salinity. This will boost Singapore’s water catchment area to 90% by 2060,
The goal is to capture every drop of rain (Figure 1)


Reservoirs
Pandan ReservoirKranji Reservoir
Jurong Lake ReservoirMacRitchie Reservoir
Upper Peirce ReservoirLower Peirce Reservoir
Bedok ReservoirUpper Seletar Reservoir
Lower Seletar ReservoirPoyan Reservoir
Murai ReservoirTengeh Reservoir
Sarimbun ReservoirPulau Tekong Reservoir
Marina ReservoirSerangoon Reservoir
Punggol Reservoir

Rivers
Singapore RiverSungei Kallang
Rochor RiverSungei Whampoa
Geylang RiverSungei Bedok
Sungei KetapangSungei Changi
Sungei SelarangSungei Loyang
Sungei TampinesSungei Api Api
Sungei BlukarSungei Serangoon
Sungei PunggolSungei Tongkang
Sungei PinangSungei Seletar
Sungei Khatib BongsuSungei Seletar Simpang Kiri
Sungei SembawangSungei Mandai
Sungei ChinaSungei Mandai Kechil
Sungei Peng SiangSungei Tengah
Sungei KangkarSungei Buloh Besar
Sungei JurongSungei Lanchar
Sungei PandanSungei Ulu Pandan



Advances in artificial intelligence: deep learning

· December 27, 2012

Advances in artificial intelligence: deep learning

November 25, 2012 – 12:34 am
If you want to keep up with advances in artificial intelligence, the New York Times has an essentialarticle on a recent step forward called deep learning.
There is a rule of thumb for following how AI is progressing: keep track of what Geoffrey Hinton is doing.
Much of the current science of artificial neural networks and machine learning stems from his work or work he has done with collaborators.
The New York Times piece riffs on the fact that Hinton and his team just won a competition to design software to help find molecules that are most likely to be good candidates for new drugs.
Hinton’s team entered late, their software didn’t include a big detailed database of prior knowledge, and they easily won by applying deep learning methods.
To understand the advance you need to know a little about how modern AI works.
Most uses abstract statistical representations. For example, a face recognition system will not use human-familiar concepts like ‘mouth’, ‘nose’ and ‘eyes’ but statistical properties derived from the image that may bear no relation to how we talk about faces.
The innovation of deep learning is that it not only arranges these properties into hierarchies – with properties and sub-properties – but it works out how many levels of hierarchy best fit the data.
If you’re a machine learning aficionado Hinton described how they won the competition in a recent interview but he also puts all his scientific papersonline if you want the bare metal of the science.
Either way, while the NYT piece doesn’t go into how the new approach works, it nicely captures it’s implications for how AI is being applied.
And as many net applications now rely on communication with the cloud – think Siri or Google Maps – advances in artificial intelligence very quickly have an impact on our day-to-day tools.
 
Link to NYT on deep learning AI (via @hpashler)

Maximum HGL Head Class in InfoSWMM AND H2OMAP SWMM

· December 20, 2012
Maximum HGL Head Class in InfoSWMM AND H2OMAP SWMM

Maximum HGL Head Class in InfoSWMM AND H2OMAP SWMM

by dickinsonre
Maximum HGL Head Class in InfoSWMM AND H2OMAP SWMM
You can find the node flood or surcharge maximum occurrence during a simulation in the Junction Summary Report table in InfoSWMM and H2OMAP SWMM (Figure 1)
Empty                                   if the Node Head is below or equal to the Lowest Link Connecting  Elevation
Below Link Crown            if the Node Head is below or equal to the Highest Link Connecting Crown
Below Maximum Depth   if the Node Head is below or equal to the Node Invert + Full  Depth.  The column Max Surcharge Height above Crown will also tell you how deep the Surcharge in a Node.
Surchaged                           if none of the above is true.
Figure 1.  Junction Summary Report in InfoSWMM

Figure 2.  Maximum Surcharge Height above Crown Definition







InfoSewer Inflow Control for a Pump with a Pump Curve

· December 16, 2012
InfoSewer Inflow Control for a Pump with a Pump Curve

You can control the pumps in InfoSewer and H2OMap Sewer by using a Pump Control which will control the pump based on:

1.       Volume
2.      Level
3.      Discharge
4.     Inflow
5.      Time

If you use a By Inflow control the pump speed of the pump is increased or decreased to make the Upstream Wet Well Level Constant (Figure 1) for an exponential 3 point curve


InfoSewer By Discharge Control for PUMP

· December 16, 2012
InfoSewer By Discharge Control for a PUMP

InfoSewer By Discharge Control for a PUMP

by dickinsonre
InfoSewer By Discharge Control for a PUMP
You can control the pumps in InfoSewer and H2OMap Sewer by using a Pump Control which will control the pump based on:
1.       Volume
2.      Level
3.      Discharge
4.      Inflow
5.      Time
If you use a By Discharge control the pump speed of the pump is increased or decreased to pump the incoming Wet Well flow based on the pump rules and the geometry of the Wet Well (Figure 1).
Figure 1.  By Discharge Control for  PUMP in InfoSewer and H2OMAP Sewer will change the Pump Speed of the pump to follow the Base Pump Flow Rules.


InfoSewer Inflow Control for a PUMP

· December 16, 2012
InfoSewer Inflow Control for a PUMP

InfoSewer Inflow Control for a PUMP

by dickinsonre
InfoSewer Inflow Control for a PUMP

You can control the pumps in InfoSewer and H2OMap Sewer by using a Pump Control which will control the pump based on:

1.       Volume
2.      Level
3.      Discharge
4.      Inflow
5.      Time 
If you use a By Inflow control the pump speed of the pump is increased or decreased to make the Upstream Wet Well Level Constant (Figure 1).
Figure 1.  Inflow Control for  PUMP in InfoSewer and H2OMAP Sewer will change the Pump Speed of the pump to make the Wet Well level constant