The Sewer Infiltration Global Data dialog deals with data to estimate infiltration in a sewer system based upon existing information about the sewer, its surrounding soil and groundwater, and precipitation.

  1. Sewer infiltration is added in sanitary mode.
  2. In the Sanitary Job Control dialog, Sewer Infiltration should be checked and the appropriate sewer infiltration global database record should be selected.
  3. The sewer infiltration flows are added to the upstream nodes of links that are active in the sanitary node.

Infiltration is classified into four categories:

  1. miscellaneous sources causing a base dry weather inflow,
  2. frozen residual moisture,
  3. antecedent precipitation, and
  4. high groundwater.

Infiltration is defined as:

QINF = DINFIL + RINFIL + SINFIL for low groundwater

QINF = GINFIL, for high groundwater

Where:

QINF = total infiltration

DINFIL = dry weather infiltration

RINFIL = wet weather infiltration

SINFIL = melting residual ice and snow infiltration

GINFIL = groundwater infiltration

The totals for the study area must be entered; the model then apportions these flows to each conduit. The criterion chosen for apportionment is an opportunity factor which represents the relative number and length of openings susceptible to infiltration. Pipe joints constitute the primary avenue for entry of infiltration. The number and length of joints is assumed to be proportional to the relative surface area of each conduit. The fraction of total infiltration is calculated as:

OPINF = Af * DIST / Σ (Af * DIST)

Where:

OPINF = fraction of total infiltration to a conduit

Af = cross-sectional area of conduit

DIST = conduit length 

The summation in the denominator is for all conduits.

The apportioned infiltration enters the system at the node immediately upstream of the conduit. This procedure allocates the most infiltration to the largest and longest conduits. It is also possible to enter infiltrations directly at manholes, if local information dictates otherwise.

When GINFIL is greater than 0 (high groundwater condition), DINFIL, RINFIL, and SINFIL (low groundwater condition) are ignored.

Wet Weather Infiltration (Rinfil)

The rainwater infiltration, in cfs [cms]. This parameter depends on antecedent precipitation occurring within the nine day period prior to an estimate. If antecedent rainfall is unavailable or less than about 0.25 in. (6.4 mm), the rainwater contribution to total infiltration is usually small.

For larger antecedent rainfall contributions, regression techniques offer a suitable method for estimating this parameter. Three study areas in which sewer flow data were not affected by melting were shown to satisfy the following linear relationship:

RINFIL = ALF + SUM (ALF[n] * RN[n]), for n=0,9

= SWFLOW - DINFIL - SMMDWF

where

RINFIL = rainwater infiltration, gpm

ALF[n] = coefficient to rainfall for ‘n’ days prior to estimate, gpm/in

RN[n] = precipitation on ‘n’ days prior to estimate, in.

SWFLOW = daily average sewer flow excluding surface runoff, gpm

SMMDWF = otherwise accounted for sewage flow, gpm

DINFIL = dry weather infiltration, gpm

To determine the coefficients, a multiple linear regression should be run on existing flow and rainfall data. Some results are given in the following table (Lentz, 1963; Metcalf and Eddy et al., 1971):

Rainfall Coefficient
Study AreaALF ALF0 ALF1ALF2ALF3ALF4ALF5ALF6ALF7ALF8ALF9
Brandenton, FL4.1 2.9 17.5 15.0 12.8 13.0 10.4 13.2 10.1 11.8 9.5

Baltimore, MD

2.4 11.3 11.6 5.5 6.4 4.8 3.6 1.0 1.5 1.4 1.9

Springfield, MO

2.0 18.3 13.9 8.9 5.5 6.7 16.0 5.2 4.6 4.4 1.3

Residual Moisture Peak Contribution (RSMAX)

This infiltration arises from residual precipitation such as snow as it melts following cold periods. Published data in the form of degree-days (sum of deviations below 65 degrees fahrenheit) provide an excellent index as to the significance of this parameter. The onset and duration of melting can be estimated by noting the degree-days above and immediately below a value of 750.

The maximum contribution from residual moisture can be determined from previous gauging of the study area or local estimates. This parameter is used in the infiltration calculation as follows:

SINFIL = RSMAX * SIN (180 * (NDYUD-MLTBE)/(MLTEN-MLTBE))

or

SINFIL = 0.0, if NDYUD is not in melting period or if NDD never exceeds 750

where

SINFIL = melting residual ice and snow infiltration

RSMAX = residual moisture peak contribution, gpm

NDYUD = day on which infiltration estimate is required, day

MLTBE = day on which melting period begins, day

MLTEN = day on which melting period ends, day

NDD = number of degree-days for the month

Note that degree-day information is also required in calculating this infiltration.  

Dry weather infiltration

The total base infiltration for the study area in dry weather, cfs [cms]. If the study area has been gauged, base dry-weather infiltration can be taken from inspection of the flow data. In the absence of flow data, an estimate of the unit infiltration rate (gpm per inch-diameter per mile) must be obtained from local professionals. From data in this form, the following equation can be used:

DINFIL = XLOCAL * DIAM * PLEN

where

DINFIL = dry weather infiltration, gpm

DIAM = average sewer diameter, inch

PLEN = pipe length, mile

XLOCAL = unit infiltration rate, gpm/inch-diameter/mile

Values of XLOCAL range from 250 to 600 gpm/in-diam/day and may be even higher for laterals with many stubs. The importance of local data cannot be over-emphasized.

Groundwater infiltration

That component of total infiltration originating from groundwater, cfs [cms]. For locations and times of the year where the groundwater table is above the sewer invert, groundwater infiltration supersedes contribution from all other sources. Groundwater infiltration can be determined from historical sewer flow data, by inspection, or regression analysis. For example, a regression analysis could involve determination of the BETA coefficient in the following formulation:

GINFIL = BETA + BETA1*GWHD + BETA2*GWHD^2 + BETA3*GWHD^0.5

where

GINFIL = groundwater infiltration.

GWHD = groundwater table elevation above sewer invert

BETAn = coefficient for term n

Degree Days

The sum of deviations of temperatures below 65 degrees fahrenheit. Only deviations below 65 degrees are counted. Figures for various cities in the United States can be obtained from the “Heating, Ventilating, Air Conditioning Guide”, American Society of Heating and Air Conditioning Engineers. Sample values for various cities are shown in the following table, from that source:

State Station Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun
Ala Montgomery 0 0 0 55 267 458 483 360 265 66 00
Ariz Phoenix 0 0 0 13 182 360 425 275 175 62 0 0
Calif Los Angeles 0 0 17 41 140 253 328 244 212 129 68 19
D.C.Washington 0 0 32 231 510 831 884 770 606 314 80 0
Fla Tampa 0 0 0 0 60 163 201 148 1020 0 0
Ill Chicago 0 0 90 350 765 1147 1243 1053 868507229 58
Kan Wichita 0 0 32 219 597 915 1023 778 619 280 101 7
La New Orleans 0 0 0 5 141 283 341 223 163 19 0 0
Mass Boston 0 7 77 315 618 998 1113 1002 849 534 236 42
Mich Detroit City 0 8 96 381 747 1101 1203 1972 927 558 251 60
Nev Reno 27 61 165 443 744 986 1048 804 756 519 318 165
N.Y. New York 0 0 31 250 552 902 1001 910 747 435 130 7
Ohio Cleveland 0 9 60 311 636 995 1101 977 846 510 223 49
Ore Portland 13 14 85 280 534 701 791 594 515 347 199 70
Tenn Memphis 0 0 13 98 392 639 716 574 423 131 20 0
Texas Houston 0 0 0 0 162 303 378 240 166 27 0 0
Wyo Cheyenne 33 39 241 577 897 1125 1225 1044 1029 717 315 100

Pollutant Concentration

This dialog provides for the input of constant concentrations of pollutants in inflows. Although infiltration is often assumed to be "clean" due to its origin in the soil layers, in-conduit measurements usually indicate non-zero levels of most parameters.

Pollutant Name

Pollutant name reference. These pollutants are defined from the 'Pollutant List' item in Job Control.

Pollutant Concentration

The constant concentration of the given pollutant in the inflow from infiltration. The concentration is given in units consistent with the pollutant, as defined in the Pollutants Global Database.