How is the Mass Balance Calculated in the SWMM 5 Groundwater Component?

Subject:   How is the Mass Balance Calculated in the SWMM 5 Groundwater Component?

How is the Mass Balance Calculated in the SWMM 5 Groundwater Component? by dickinsonre Subject:   How is the Mass Balance Calculated in the SWMM 5 Groundwater Component? The groundwater component of SWMM 5 is found in the gwater.c code.  It (as is all of SWMM 5) is excellently written in small functions by Lew Rossman of the EPA during the SWMM 5 development process.  However, code being code sometimes it is easier to see how the code is functioning.  This blog or note tries to show the mass balance local function updateMassBal The groundwater component consists of groundwater data (gw in the equation) and aquifer data (a) in the equation.  The equation for the groundwater mass balance is shown in Figure 1.   The infiltration, evaporation occur only over the perviousarea but the percolation out the bottom of the aquifer occurs over the whole Subcatchment. Figure 1.  Groundwater Mass Balance via Blogger http://www.swmm5.net/2013/08/how-is-mass-balance-calculated-in-swmm.html

Make study more effective, the easy way

Make study more effective, the easy way

October 24, 2011 – 8:59 am from http://mindhacks.com/2011/10/24/make-study-more-effective-the-easy-way/

Decades old research into how memory works should have revolutionised University teaching. It didn’t.

If you’re a student, what I’m about to tell you will let you change how you study so that it is more effective, more enjoyable and easier. If you work at a University, you – like me – should hang your head in shame that we’ve known this for decades but still teach the way we do.

There’s a dangerous idea in education that students are receptacles, and teachers are responsible for providing content that fills them up. This model encourages us to test students by the amount of content they can regurgitate, to focus overly on statements rather than skills in assessment and on syllabuses rather than values in teaching. It also encourages us to believe that we should try and learn things by trying to remember them. Sounds plausible, perhaps, but there’s a problem. Research into the psychology of memory shows that intention to remember is a very minor factor in whether you remember something or not. Far more important than whether you want to remember something is how you think about the material when you encounter it.

A classic experiment by Hyde and Jenkins (1973) illustrates this. These researchers gave participants lists of words, which they later tested recall of, as their memory items. To affect their thinking about the words, half the participants were told to rate the pleasantness of each word, and half were told to check if the word contained the letters ‘e’ or ‘g’. This manipulation was designed to affect ‘depth of processing’. The participants in the rating-pleasantness condition had to think about what the word meant, and relate it to themselves (how they felt about it) – “deep processing”. Participants in the letter-checking condition just had to look at the shape of the letters, they didn’t even have to read the word if they didn’t want to – “shallow processing”. The second, independent, manipulation concerned whether participants knew that they would be tested later on the words. Half of each group were told this – the “intentional learning” condition – and half weren’t told, the test would come as a surprise – the “incidental learning” condition.

I’ve made a graph so you can see the effects of these two manipulations

As you can see, there isn’t much difference between the intentional and incidental learning conditions. Whether or not a participant wanted to remember the words didn’t affect how many words they remembered. Instead, the major effect is due to how participants thought about the words when they encountered them. Participants who thought deeply about the words remembered nearly twice as many as participants who only thought shallowly about the words, regardless of whether they intended to remember them or not.

The implications for how we teach and learn should be clear. Wanting to remember, or telling people to remember, isn’t effective. If you want to remember something you need to think about it deeply. This means you need to think about what you are trying to remember means, both in relationship to other material you are trying to learn, and to yourself. Other research in memory has shown the importance of schema – memory patterns and structures – for recall. As teachers, we try and organise our course material for the convenience of students, to best help them understand it. Unfortunately, this organisation – the schema – for the material then becomes part of the assessment and something which students try to remember. What this research suggests is that, merely in terms of remembering, it would be more effective for students to come up with their own organisation for course material.

If you are a student the implication of this study and those like it is clear : don’t stress yourself with revision where you read and re-read textbooks and course notes. You’ll remember better (and understand much better) if you try and re-organise the material you’ve been given in your own way.

If you are a teacher, like me, then this research raises some disturbing questions. At a University the main form of teaching we do is the lecture, which puts the student in a passive role and, essentially, asks them to “remember this” – an instruction we know to be ineffective. Instead, we should be thinking hard, always, about how to create teaching experiences in which students are more active, and about creating courses in which students are permitted and encouraged to come up with their own organisation of material, rather than just forced to regurgitate ours.

Reference: Hyde, T. S., & Jenkins, J. J. (1973). Recall for words as a function of semantic, graphic, and syntactic orienting tasks. Journal of Verbal Learning and Verbal Behavior, 12(5), 471–480.

How is the Volume Calculated in the SWMM 5 Groundwater Component?

Subject:   How is the Volume Calculated in the SWMM 5 Groundwater Component?

How is the Volume Calculated in the SWMM 5 Groundwater Component? by dickinsonre Subject:   How is the Volume Calculated in the SWMM 5 Groundwater Component?  The groundwater component of SWMM 5 is found in the gwater.c code.  It (as is all of SWMM 5) is excellently written in small functions by Lew Rossman of the EPA during the SWMM 5 development process.  However, code being code sometimes it is easier to see how the code is functioning.  This blog or note tries to show that function.   The groundwater component consists of groundwater data (gw in the equation) and aquifer data (a) in the equation.  The equation for the groundwater volume is shown in Figure 1.   The volume is the water content (theta) times the upper depth and the porosity of the aquifer times the lower depth (Figure 2).  Figure 1.  Groundwater Volume Calculations    Figure 2.  Lower and Upper Depth of the Groundwater Compartrment   via Blogger http://www.swmm5.net/2013/08/how-is-volume-calculated-in-swmm-5.html

Aquifer and Groundwater Objects in SWMM 5

Subject:   Aquifer and Groundwater Objects in SWMM 5

Aquifer and Groundwater Objects in SWMM 5 by dickinsonre Subject:   Aquifer and Groundwater Objects in SWMM 5  There are two types of data objects in SWMM 5 to describe the Groundwater flow component.  There is a Groundwater data object associated with a Subcatchment that describes flow equations, the interaction between the Subcatchment infiltration and the Groundwater component and an Aquifer data object that describes the characteristics of the Aquifer that may span one or more Subcatchments.  The Groundwater data is specific to one Subcatchment but the Aquifer may    via Blogger http://www.swmm5.net/2013/08/aquifer-and-groundwater-objects-in-swmm.html

Hierarchy of Your Network in InfoSWMM and H2OMAP SWMM

Subject: Hierarchy of Your Network in InfoSWMM and H2OMAP SWMM

Hierarchy of Your Network in InfoSWMM and H2OMAP SWMM by dickinsonre Subject:  Hierarchy of Your Network in InfoSWMM and H2OMAP SWMM In both InfoSWMM and H2OMAP SWMM you can run a subset of the network by using the Facility Manager to make part of thenetwork inactive and not solved.  You can make the output files smaller if you are performing a continuous simulation and save only the results of All, the Domain Only or a Selection Set to the graphical output file (Figure 1).   Figure 2 shows a few ways to query, view, graph and perform statistics for the model run.  Figure 1.  Options for saving the Active Network Data to the Graphical Output Data Set. Figure 2.  Output View, Query and Graphical Options.c. via Blogger http://www.swmm5.net/2013/08/hierarchy-of-your-network-in-infoswmm.htm

al Options.

Import of Sections from SWMM 5 into InfoSWMM and H2oMAP SWMM

Subject:   Import of Sections from SWMM 5 into InfoSWMM and H2oMAP SWMM

Import of Sections from SWMM 5 into InfoSWMM and H2oMAP SWMM by dickinsonre Subject:   Import of Sections from SWMM 5 into InfoSWMM and H2oMAP SWMM A very useful hidden feature of the import SWMM 5 to InfoSWMM and H2OMAP SWMM is the ability to import all of the data or just one section.  For example, you can import the LID data, DWF patterns, control rules, pollutants, transects and other data that is transferable between different networks.   via Blogger http://www.swmm5.net/2013/08/import-of-sections-from-swmm-5-into.html

History of SWMM to the Year 2005

Subject:   History of SWMM to the Year 2005

History of SWMM to the Year 2005 by dickinsonre Subject:   History of SWMM to the Year 2005  Note on the symbols:  The Gator is the University of Florida and the Beaver is Oregon State University.  The connection is they are both associated with water and Dr Wayne Huber.    via Blogger http://www.swmm5.net/2013/08/history-of-swmm-to-year-2005.html

SWMM 5 Loss Term Values for various velocities and K values

Subject:   SWMM 5 Loss Term Values for various velocities and K values

SWMM 5 has three loss terms available for each link:  Entrance, Exit and Other losses.  The Entrance loss uses the upstream link velocity, the  Other loss uses the center link velocity and the Exit loss uses the downstream link velocity.  The general form of the loss term in the St. Venant equation is K*V^2/2g Table 1 shows the loss in feet of head for various combinations of velocity and K value.  If you want to  simulate a little loss of head at each node then a small value of K should be used otherwise the cumulative loss in the whole networks will be many feet of head.

  Loss Term units equals K * V^2/2g = ft/sec * ft/sec * sec^2/ft = ft

Table 1:  Loss in feet of head for various combinations of velocity and K values.

Velocity (ft/sec)	K	K	K	K	K	K
	0.050	0.100	0.250	0.500	0.750	1.000
1	0.001	0.002	0.004	0.008	0.012	0.016
2	0.003	0.006	0.016	0.031	0.047	0.062
3	0.007	0.014	0.035	0.070	0.105	0.140
4	0.012	0.025	0.062	0.124	0.186	0.248
5	0.019	0.039	0.097	0.194	0.291	0.388
6	0.028	0.056	0.140	0.280	0.419	0.559
7	0.038	0.076	0.190	0.380	0.571	0.761
8	0.050	0.099	0.248	0.497	0.745	0.994
8	0.050	0.099	0.248	0.497	0.745	0.994
9	0.063	0.126	0.314	0.629	0.943	1.258
10	0.078	0.155	0.388	0.776	1.165	1.553

SWMM 5 Inlet Control Culvert Equations

Subject:   SWMM 5 Inlet Control Culvert Equations

SWMM 5 Inlet Control Culvert Equations by dickinsonre Subject:   SWMM 5 Inlet Control Culvert Equations  The newer option for SWMM 5 culverts uses three culvert classifications and associated equations to compute the inletcontrolled flow into a culvert using the FHWA (1985) equations.  The culvert code in the culvert.c code of SWMM 5 uses:  1.   Two Equations for Unsubmerged culvert flow, 2.   One Equation for the Transition flow, and 3.   One Equation for Submerged flow. via Blogger http://www.swmm5.net/2013/08/swmm-5-inlet-control-culvert-equations.html

SWMM 5 Culvert Data from FHWA, HDS No. 5, Hydraulic Design of Highway Culverts, 1985

Subject:  SWMM 5 Culvert Data from FHWA, HDS No. 5, Hydraulic Design of Highway Culverts, 1985

SWMM 5 Culvert Data from FHWA, HDS No. 5, Hydraulic Design of Highway Culverts, 1985 by dickinsonre Subject:  SWMM 5 Culvert Data from FHWA, HDS No. 5, Hydraulic Design of Highway Culverts, 1985 If you use the culvert option in later versions of SWMM 5 then when the inlet control equation flow is less than the computed St Venant flow then the FHWA equations will be used for the current iteration in the SWMM 5 Dynamic Wave Solution. via Blogger http://www.swmm5.net/2013/08/swmm-5-culvert-data-from-fhwa-hds-no-5.html

Understanding Your Model Output in H2oMAP SWMM and InfoSWMM

Three Hidden Secrets to Speeding up your SWMM 5, H2OMAP SWMM or InfoSWMM Model

Three Hidden Secrets to Speeding up your SWMM 5, H2OMAP SWMM or InfoSWMM Model by dickinsonre    Minimum Time Step               Average Time Step        Maximum Time Step Minimum Time Step (sec)             0.984 Average Time Step (sec)              9.071 Maximum Time Step (sec)            30.000 Percent in Steady State (%)          0.000 Average Iterations per Time Step  4.821 Use a maximum time that will lower your average iterations per time step to speed up the simulation,decrease the maximum time step to lower the number of iterations, use equivalent conduit lengthening to increase the minimum time step, the model is fastest if the minimum and maximum time steps are not too small or large compared to the average time step.  Adjust the stopping tolerance and the number of iterations if you can to speed up your model You can also decrease the number of iterations or the stopping tolerance to speed up the model or improve the continuity error of themodel.   If you are doing a continuous simulation then you can have a reduced graphical output data set to speedup the simulation    If you have a duo or quad core computer another option to speed up the simulations is to use 1, 2, 3 or 4 cores for the simulation  via Blogger http://www.swmm5.net/2013/08/three-hidden-secrets-to-speeding-up.html