SWMM5 1000 Year Runoff Flow Duration Curve using SWMM 5 Statistics

SWMM5 1000 Year Runoff Flow Duration Curve using SWMM 5 Statistics twitpic.com/ck37uw
— RDickinson (@RDickinson) April 18, 2013

How to calculate the Maximum Unfilled Manhole Depth in InfoSewer

How to calculate the Maximum Unfilled Manhole Depth in InfoSewertwitpic.com/cif0zd
— RDickinson (@RDickinson) April 10, 2013

SWMM 5 Statistics for a 1000 year Simulation

SWMM 5 Statistics for a 1000 year Simulationtwitpic.com/cifasa
— RDickinson (@RDickinson) April 10, 2013

Mass Balance in SWMM 5

Mass Balance in SWMM 5twitpic.com/celztg
— RDickinson (@RDickinson) March 26, 2013

How to switch the upstream and downstream nodes in SWMM 5

How to switch the upstream and downstream nodes in SWMM 5 twitpic.com/choav7
— RDickinson (@RDickinson) April 7, 2013

Live Link between the HGL Plot in InfoSWMM and the DB Tables/ Attribute Browser

Live Link between the HGL Plot in InfoSWMM and the DB Tables/ Attribute Browser twitpic.com/cbygp8
— RDickinson (@RDickinson) March 17, 2013

Storage Nodes in InfoSWMM 2D

Storage Nodes in InfoSWMM 2Dyoutu.be/Jqk4YPMu3hY via @youtube

— RDickinson (@RDickinson) March 15, 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 20^th 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 95^th 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

How to define link widths in InfoSWMM and H2OMap SWMM

How to define link widths in InfoSWMM and H2OMap SWMMtwitpic.com/c8n3g4
— RDickinson (@RDickinson) March 4, 2013

How to Map Maximum Top Width in InfoSWMM

How to Map Maximum Top Width in InfoSWMMtwitpic.com/c8utbx
— RDickinson (@RDickinson) March 5, 2013

How to Rename a Scenario in InfoSWMM

How to Rename a Scenario in InfoSWMMtwitpic.com/c7l5t3

— RDickinson (@RDickinson) February 28, 2013

How to have backwater in a dummy OUTLET in SWMM 5

How to have backwater in a dummy OUTLET in SWMM 5twitpic.com/c7mhau

— RDickinson (@RDickinson) March 1, 2013

New Top Width Graph Feature in InfoSWMM

New Top Width Graph Feature in InfoSWMM

New Top Width Graph Feature in InfoSWMM

Genetic Algorithm and GIS Addons to InfoSWMM

Genetic Algorithm and GIS Addons to InfoSWMM

google6b814b77922a6829.html

google-site-verification: google6b814b77922a6829.html

From the Dish - The Wisdom of Play

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 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]

How To Run the SWMM 5 Console from the SWMM 5 GUI

How To Run the SWMM 5 Console from the SWMM 5 GUI

Use the SWMM 5 tools, define the program as the DOS engine or SWMM5.EXE (1), run the tool (2) and see the dos output in the command window of Windows 7 or Windows XP.  It should also be possible to call Matlab and have Matlab call the SWMM 5 program using the SWMM 5 interface.

InfoSWMM Import and Export from SWMM

Outlets in SWMM 5 can have reverse flow

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.

InfoSWMM and InfoSewer Product Pages and Videos

InfoSewer Product Page
InfoSWMM Product Page
InfoSWMM 2D Product Page
Innovyze Videos

Stopping Tolerance in InfoSWMM, H2OMAP SWMM and SWMM5 Internal Units

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

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

Here's just one example, from Singapore:

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.

Via http://grist.org/climate-energy/climate-proofing-cities-not-something-conservatives-are-going-to-be-good-at/

How to Compile SWMM 5 in Visual Studio 2010 Express

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

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 Reservoir	Kranji Reservoir
Jurong Lake Reservoir	MacRitchie Reservoir
Upper Peirce Reservoir	Lower Peirce Reservoir
Bedok Reservoir	Upper Seletar Reservoir
Lower Seletar Reservoir	Poyan Reservoir
Murai Reservoir	Tengeh Reservoir
Sarimbun Reservoir	Pulau Tekong Reservoir
Marina Reservoir	Serangoon Reservoir
Punggol Reservoir

Rivers

Singapore River	Sungei Kallang
Rochor River	Sungei Whampoa
Geylang River	Sungei Bedok
Sungei Ketapang	Sungei Changi
Sungei Selarang	Sungei Loyang
Sungei Tampines	Sungei Api Api
Sungei Blukar	Sungei Serangoon
Sungei Punggol	Sungei Tongkang
Sungei Pinang	Sungei Seletar
Sungei Khatib Bongsu	Sungei Seletar Simpang Kiri
Sungei Sembawang	Sungei Mandai
Sungei China	Sungei Mandai Kechil
Sungei Peng Siang	Sungei Tengah
Sungei Kangkar	Sungei Buloh Besar
Sungei Jurong	Sungei Lanchar
Sungei Pandan	Sungei Ulu Pandan

Advances in artificial intelligence: deep learning

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)

via Mind Hacks  

Maximum HGL Head Class in InfoSWMM AND H2OMAP SWMM

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 via Blogger http://www.swmm5.net/2013/08/maximum-hgl-head-class-in-infoswmm-and.html

InfoSewer Inflow Control for a Pump with a Pump Curve

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

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.

via Blogger http://www.swmm5.net/2013/08/infosewer-by-discharge-control-for-pump.html

InfoSewer Inflow Control for a PUMP

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 via Blogger http://www.swmm5.net/2013/08/infosewer-inflow-control-for-pump.html

LEGO, Brick by Brick

Brick By Brick

Chana Joffe-Walt examines Lego's dominance despite their products' high cost and lack of exclusive patent:

Lego goes to great lengths to make its pieces really, really well, according to David Robertson, who is working on a book about Lego. Inside every Lego brick, there are three numbers, that identify exactly what mold the brick came from, and what position it was in in that mold. That way, if there's a bad brick somewhere, the company can go back and fix the mold. For decades this is what kept Lego ahead. It's actually pretty hard to make millions of plastic blocks that all fit together.

Dreher recently sang the praises of the toy company. Tip, The Daily Dish

InfoSewer Minimum Travel Time Sensitivity

InfoSewer Minimum Travel Time Sensitivity

InfoSewer Minimum Travel Time Sensitivity by dickinsonre InfoSewer Minimum Travel Time Sensitivity The three Run manager parameters, Maximum Number of Segments, Minimum Travel Distance and the Minimum Travel Time in InfoSewer and H2OMAP Sewer affect the shape and flow attenuation of the flow in a link.  The effect of decreasing the Minimum Travel Time is to reduce the peak flow and spread out the flow as the number of segments increases(Figure 1).  The larger the Minimum Travel Time, which has the effect of decreasing 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. Figure 1.  Effect of the Minimum Travel Time in InfoSewer and H2OMAP Sewer via Blogger http://www.swmm5.net/2013/08/infosewer-minimum-travel-time.html