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Robert Dickinson commented on Robert Dickinson's group 'ExtraVariables'
QA/QC version based on v22 of EPA SWMM 5 with the ability to read older SWMM 5 OUT files. swmm5.dll Epaswmm5.exe
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Robert Dickinson commented on Robert Dickinson's group 'Stream of Information'
Video: How Snowflakes Are Formed February 4th, 2012 | Posted by Jaime Menchén in Science Videos This time-lapse video lasts 11 seconds, with no music or voice-over. And still you’ll want to see it over and over again. The…
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This is a galaxy

This is a galaxy. Or is it? A remix of material originally produced for BBC Stargazing Live 2012 If you liked this video, follow me on twitter to hear about ...
Video posted by Robert Dickinson 17 hours ago
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2 blog posts by Robert Dickinson were featured yesterday
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Blog posts by Robert Dickinson yesterday
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Fateme Fallah replied to Fateme Fallah's discussion 'Uncertainty Analysis'
Dear Lionel, This matter is explained in Appendix D of SWMM manual under the title of “Command line SWMM”. So in MATLAB you can use below format under DOS window: "The address of place that SWMM is there"   input…
Saturday
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Robert Dickinson commented on Robert Dickinson's group 'Stream of Information'
Now the new images, courtesy of the Suomi NPP satellite (2012): The above two photos are pretty much what you would see with your naked eyes if you were at the altitude of this satellite.  It's humbling to realize that all you…
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glenn gradin, Bryant McDonnell and Lionel joined SWMM5 - Stormwater Management Model Thursday
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Lionel replied to Lionel's discussion 'Linking Matlab with SWMM5'
Thanks Robert for your prompt help!
Thursday
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Lionel replied to Fateme Fallah's discussion 'Uncertainty Analysis'
Hi Fateme Fallah,   I am doing something similar but in my case I am varying the infiltration factor. I am not very good with Matlab so require a bit of help on the coding. I would like to check if you have been successful in your attempt to…
Thursday
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Linking Matlab with SWMM5

Hi, I am currently trying to use Matlab to create a set of random values and inputting these random values into SWMM 5 to vary the different parameters (e.g. decay constant) so I will get a range of results. Has anyone done it before? Thanks!See More
Discussion posted by Lionel Thursday
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North Carolina City Chooses InfoSewer

North Carolina City Chooses InfoSewerArcGIS Based Sewer Modeling Package Helps Hendersonville, NC Model and Manage Its Collection SystemBroomfield, Colorado, USA, January 31, 2012Innovyze, a leading global innovator of business analytics software and technologies for wet infrastructure, today announced the City of Hendersonville, North Carolina, has selected InfoSewer for ArcGIS (Esri, Redlands, CA) as its sewer modeling platform.InfoSewer has helped define the standard in the industry for…See More
A blog post by Robert Dickinson was featured Tuesday
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North Carolina City Chooses InfoSewer

North Carolina City Chooses InfoSewerArcGIS Based Sewer Modeling Package Helps Hendersonville, NC Model and Manage Its Collection SystemBroomfield, Colorado, USA, January 31, 2012Innovyze, a leading global innovator of business analytics software and technologies for wet infrastructure, today announced the City of Hendersonville, North Carolina, has selected InfoSewer for ArcGIS (Esri, Redlands, CA) as its sewer modeling platform.InfoSewer has helped define the standard in the industry for…See More
Blog post by Robert Dickinson Tuesday
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Robert Dickinson left a comment for oliver kemp
Welcome Oliver!
Tuesday
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oliver kemp is now a member of SWMM5 - Stormwater Management Model Jan 31
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Design Storms

Video posted by Robert Dickinson Jan 31

Soil Conservation Service Curve Numbersti

One of the advantages of use of the curve number (CN) method for loss estimates (Section 3.3) is the highly structured method for CN estimates provided by the NRCS (SCS, 1972,1988; McCuen, 1998, Bedient and Huber, 2002 and virtually every hydrology text).  Such estimates are embedded in engineering practice through Table 3-18, in which CN values are given as function of land use and soil Hydrologic Soil Group (A through D).  Hydrologic Soil Group has the meaning indicated in Table 3-17, ranging from well-drained (type A) to poorly drained (type D).  Every soil in the United States has an A-D classification, or sometimes a dual classification, such as B/D, meaning drained (artificially) and undrained (natural) condition. 

 

Table 3-17. Hydrologic soil group meanings (SCS, 1972, Chapter 7).

Group

Meaning

A

Low runoff potential. Soils having high infiltration rates even when thoroughly wetted and consisting chiefly of deep, well to excessively drained sands or gravels.

B

Soils having moderate infiltration rates when thoroughly wetted and consisting chiefly of moderately deep to deep, moderately well to well-drained soils with moderately fine to moderately coarse textures.  E.g., shallow loess, sandy loam.

C

Soils having slow infiltration rates when thoroughly wetted and consisting chiefly of soils with a layer that impedes downward movement of water, or soils with moderately fine to fine textures. E.g., clay loams, shallow sandy loam.

D

High runoff potential.  Soils having very slow infiltration rates when thoroughly wetted and consisting chiefly of clay soils with a high swelling potential, soils with a permanent high water table, soils with a clay-pan or clay layer at or near the surface, and shallow soils over nearly impervious material.

 

            Hydrologic Soil Group is provided on the Soil Survey Interpretation sheets discussed in Section 3.8.8.2.  For instance, the Conestoga Silt Loam of Figure 3-37a is in hydrologic soil group B.  A more concise listing is provided in the Soil Survey for each county, published by the NRCS or the local Soil and Water Conservation District. 

            Hence, parameter estimation for SWMM (and any use of curve numbers) is straightforward and relatively unambiguous.  Curve numbers may also be used to back-calculate estimates of initial moisture deficit, as discussed earlier in conjunction with Equation 3-135, since the CN and storage, S, are related through

 

                                                                                                             (3-136)

 

where it is essential to remember that units of S are in inches.  And early discussion of Horton infiltration parameters has also been related to Hydrologic Soil Group. 


Table 3-18. Runoff curve numbers for selected agricultural, suburban, and urban land use (SCS, 1986).  (Antecedent moisture condition II; Ia = 0.2S)

Hydrologic Soil Group

Land Use Description

A

B

C

D

Cultivated land1

 

 

 

 

Without conservation treatment

72

81

88

91

With conservation treatment

62

71

78

81

Pasture or range land

 

 

 

 

Poor condition

68

79

86

89

Good condition

39

61

74

80

Meadow

 

 

 

 

Good condition

30

58

71

78

Wood or forest land

 

 

 

 

Thin stand, poor cover, no mulch

45

66

77

83

Good cover2

25

55

70

77

Open spaces, lawns, parks, golf courses, cemeteries, etc.

 

 

 

 

Good condition: grass cover on 75% or more of the area

39

61

74

80

Fair condition: grass cover on 50 – 75% of the area

49

69

79

84

Commercial and business areas (85% impervious)

89

92

94

95

Industrial districts (72% impervious)

81

88

91

93

Residential3

 

 

 

 

Average lot size

Average % impervious4

 

 

 

 

1/8 ac or less

65

77

85

90

92

1/4 ac

38

61

75

83

87

1/3 ac

30

57

72

81

86

1/2 ac

25

54

70

80

85

1 ac

20

51

68

79

84

Paved parking lots, roofs, driveways, etc.5

98

98

98

98

Streets and roads

 

 

 

 

Paved with curbs and storm sewers5

98

98

98

98

Gravel

76

85

89

91

Dirt

72

82

87

89

1. For a more detailed description of agricultural land use curve numbers, refer to the SCS (1972) National Engineering Handbook, Section 4, “Hydrology.”

2. Good cover is protected from grazing and litter and brush cover soil.

3. Curve numbers are computed assuming that the runoff from the house and driveway is directed toward the street with a minimum of roof water directed to lawns where additional infiltration could occur.

4. The remaining pervious areas (lawn) are considered to be in good pasture condition for these curve numbers.

5. In some warmer climates of the country a curve number of 95 may be used.

Last updated by Robert Dickinson Apr 21, 2008.

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