This calculator was developed for the
Little Stringybark
Creek project by:
 Christopher J Walsh, University of Melbourne
(maintainer: cwalsh@unimelb.edu.au);
 Tim D Fletcher, Monash University;
 Darren Bos, University of Melbourne;
 Sharyn RossRakesh, Melbourne Water;
 Veronika Nemes, Claire Edwards and Andrew O'Keefe, Department of
Sustainability and Environment, Victoria.
 with subsequent improvements to the underlying code by Rhys Eddy of Enviss P/L
This page gives the full technical details of the revised EB
calculator that was used for the Stormwater Fund, beginning 15
Feb 2010.
Technical details of the original (now nonfunctional)
EB calculator (used for the Stormwater Tender
20082009) can be found here.
The pollutant removal in EB calculator is derived from research
undertaken at the Facility for Advancing Water Biofiltration (FAWB: see www.monash.edu.au/fawb). We particularly wish to thank Dr. Belinda Hatt and Assoc. Prof. Ana Deletic for their contribution. The infiltration modelling was assisted by advice and calibration from Dale Browne (PhD student, Department of Civil Engineering, Monash University)
It uses RStudio Shiny, a package that permits a webbased applications using
the mathematical and statistical program R.
The calculator uses two primary models written as R functions:
tankmodel and
gardenmodel, both in the file
modelfunctions.R .
Running these in R allows more flexibility: other rainfall records can be used,
uses of tank water other than the calculator's limited options can be
modelled (the 'other' argument in tankmodel), other soil profiles can
be used (using the functions filter.profile to
produce a data frame that is used for the filtr.prfile argument of
gardenmodel).
More complex treatment trains can be calculated in R as well, using
the functions tank.as.garden.inflow
and garden.as.tank.inflow. (see
this page for more information.)
Overview of the differences between the old and new EB calculators
 The new web calculator has been somewhat simplified, with fewer
options (e.g consideration of unconnected surfaces, or the
presence of septic tanks are no longer included): however, the new
calculator gives the option of tanks with leaks for passive irrigation
(which can substantially increase environmental benefit with little loss of
yield from the tank)
 The old raingarden model assumed a uniform infiltration rate for
surrounding soils. The new model assumes a variable soil profile closer
to that observed in systems already built in Mt Evelyn. The
infiltration capacity of the underlying soil = 0.005 mm/h, while
that of the surface 30 cm is assumed to be 2.5 mm/h
 The old EB index was based on three subindices: a) reduction in
flow frequency, b) reduction in nitrogen export, and c) volume of
water consumed. The new EB index is based on four sub indices that
are of more direct ecological relevance to streams: a) reduction in
flow frequency (as before), b) equivalence between the preurban
volume of subsurface flows and filtered flows from raingardens, c)
median concentrations of 3 pollutants in filtered flows from raingarden (N, P, TSS), and d)
reduction in total volume of water exported (can be used or lost
through evapotranspiration).
 The old raingarden model assumed an erroneously high
evapotranspiration (ET) loss (to correct for the overly conservative soil
profile assumption). The new model assumes ET loss from a wet, vegetated
raingarden of x sq m is equivalent to the theoretical potential ET
loss from x sq m (using Bureau of Meteorology PET estimates).
Unvegetated systems are assumed to have no ET loss. However, if an unlined
raingarden is within 3 m of at least one large tree, the effective
area available for ET loss is assumed to be equal to half the canopy area of
the tree(s) (+ area of raingarden, if vegetated).
The calculator uses the rainfall record from Croydon, which is a few km
west of Mt Evelyn. So, the results produced will be applicable for most of the
eastern suburbs of Melbourne, and any other area with similar climate (temperate, mean annual rainfall of
~900 mm), and with thick, clayey soils
The caculator uses 3 years of rainfall data:
an average year, 1965 (actually Apr 1965  Mar 1966), 956 mm;
a dry year, 1967, 661 mm;
a wet year, 1970, 1085 mm.
The old tankmodel calculated EB indices using the mean value for all
three years, and the old gardenmodel used just data from 1965. In the
new version, both the raingarden and tank models calculate EB indices
using just 1965 data, although the web calculator uses the wet and
dry year for graphical comparisons. The new calculator now gives the
option of trying two other rainfall series (but these only use a single (average) year for now.
Still not enough detail for you? Read on!
To estimate tank water usage and overflow
frequency, the R function tankmodel
is used. This function requires input of the following variables
(some of which EBI calculator requires the user to enter, and others that EBI
calculator assumes values for).
 Daily runoff or rainfall data. EB calculator uses daily runoff data for Croydon over three
years that were chosen from the available record (6 minute records) from
that site for which there was no missing data, and no accumulated data
> 1 day in duration. The three years chosen represent a year with
average rainfall (1965 &ndash actually 1 Apr 1965 &ndash 31 Mar 1966, with 950 mm of
rain), a dry year (1967 with 660 mm), and a wet year (1970, with 1085
mm). Runoff was derived from hourly data (while none of the chose years
had missing data, 1967 and 1970 each had nine blocks for which rainfall
was aggregated, ranging from 2 to 24 hours &ndash for all but 3 of these
blocks, the aggregated data was distributed across the blocks in
proportion to rain that was recorded at the Melbourne station over the
same block. For the remaining 3 blocks for which Melbourne also lacked
data (all < 8 h), the aggregated rainfall was distributed evenly across
the block. Runoff was estimated from the hourly data by assuming that the first 1 mm in a rain event was lost to
evaporation (and therefore did not become runoff), and that a rain event was defined as any record of rain that
followed at least one hour of zero recorded rain. This calculation
of hourly runoff for the Croydon record was calculated using the function compile.inflow.R, and
then converted to daily runoff. EB indices are calculated using
1965 data, but all three years are used for graphical comparisons.
 Tank volume, and the volume of water
in the tank at the beginning of the simulation. EB calculator uses the value entered for tank volume in the
second tab, and assumes that the tank was 50%
full at the start of the simulation.
 Catchment area for the tank. EB calculator uses the roof area values entered in the 'Your tank' tab for this variable.
 Initial loss of rainfall before it becomes runoff. EB calculator sets
this to zero, because initial loss has been estimated already in the
runoff input vector.
 First flush volume. EB calculator requires this as an input.
There are many types of first flush diverters that divert
varying amounts of water from the tank before allowing runoff to enter. A
critical assumption for EBI calculator is that any
diverted first flush water either overflows to the modelled raingarden, or
if there is no raingarden to the property's normal garden. If first flush
water is diverted to a stormwater drain, then the estimated benefit to the
stream should be considered zero.
 Number of people living in the house. EB calculator uses the number of people entered in the
first tab. This is used to calculate consumption patterns as below.
Water usage volumes are assumed as follows
after Wilkenfield and associates (2006. Water saving requirements for new residential buildings
in Victoria: options for flexible compliance. Melbourne: Department of Sustainability and Environment.).
When each use is selected on the second tab the following values are used.
 Toilet. EBI
calculator assumes toilets use 18.9 L per
person per day.
 Washing machine. EBI calculator assumes
washing machines use 35.31 L per day for the first person and 23.54 L for
each additional person.
 Hot water systems. EBI calculator
assumes that hot water systems use 46.9 L per person per day (calculated
from Wilkenfield's estimate of 61.9 minus half the washing machine use).
 Garden area. EBI
calculator uses the value entered in the second tab
 Annual outdoor irrigation and monthly
distribution. EBI calculator assumes garden watering uses 12,971 L per 100 m^{2}
of garden per year, spread over the 12 months of the year in the following
proportions: 0.27, 0.21, 0.09, 0.07, 0.05, 0, 0, 0, 0.03, 0.04, 0.04, 0.2.
 Other uses.
The function (in the R function, but not given as an option on the web calculator)
allows the user to supply their own monthly usage patterns
which are then spread evenly across the days of each month. EBI
calculator assumes zero other uses, but allows them to be entered in the
second tab.
 Use for drinking and carwashing has very small effects on yield, and have not been
included as options. They could be included as part of other uses.
EB calculator takes uses selected and the
number of people and calculates and estimated daily demand for the house for
water from the tank, over the 3 years. (The program actually uses a matrix of
demand patterns for all possible combinations of uses for the given number of
people and the given garden area.) For each day over the period, inflow from
runoff is added to the volume in the tank at the end of the previous day and
subtracts the demand that can be extracted from the available volume. If the
demand exceeds the volume in the tank at the start of the day, then only the
available volume is used. If the inflow exceeds the space available in the
tank after demand is extracted, then the excess is assumed to overflow from the
tank.
tankmodel
records the complete time series of water consumed,
that overflowed and that remained in the tank each day.
The function tank.EBstats takes each series and
calculates two of the four sub indices (overflow frequency and volume
reduction). Tanks score zero for the other two subindices:
filtered flow volume and filtered flow pollutant concentrations
(because tanks do not restore lost infiltration flows). The EB
score is the average of the four subindices (2 scoring zero),
calculated for the average year (1965).
The flowfrequency subindex is a measure of the
reduction in runoff frequency afforded by the tank. It is assumed that
runoff is generated from the roof 121 days per year,
and that overland flow would have been generated
from the preurban forest floor 12 days per year. Furthermore, it is
assumed that any impervious areas that are not
connected to the formal (piped) stormwater drainage system do not contribute to
increased runoff frequency (while this is unlikely to be the case, the
finding that such areas currently have no detectable environmental impact
compared to the directly connected impervious areas, they are not considered a
high priority for treatment). The flowfrequency subindex is calculated as:
_{},
where A = the area (m^{2})
of currently connected roof to be drained by the tank; R_{g} =
number of days of runoff per year from A following treatment by tank (or garden, see below); R_{n}
= frequency of runoff from A in preurban state (12 days per year0; R_{u}
= frequency of runoff from A before treatment (121 days per year). All
three indices are standardized by impervious catchment area: one unit measures
the environmental benefit from 100 m^{2}.
The volume reduction target is based on the understanding that the
replacement of vegetation by roofs or paving reduces the amount of
rainwater that is lost back to the air through evapotranspiration.
In the forest of Mt Evelyn before development, 85% of average annual
rainfall was lost back to the air, and only 15% drained to the
creek. The optimal target therefore is for 85% of rainfall to be
used (in houses and exported to the sewerage treatment plant), or to
be lost through vegetation.
The volumereduction subindex is
calculated as:
_{},
where V_{e} =
the excess volume of water generated by impervious surface A (i.e the difference between the volume of runoff from an area of forest equivalent to A and the volume of runoff from the impervious surface); V_{c}
= the volume of water consumed from the tank (or lost from a raingarden through evapotranspiration: see below). One unit measures the environmental benefit from 100m^{2}.
If a tank system uses all runoff that drains to it, it is possible
for this subindex to be as high as 1.36 (in this region). We have
chosen to encourage as much extraction as possible from tanks,
because we know it will be impossible to lose the target volume of
runoff from raingardens in this catchment.
The overall EB score for a tank = (0.25 x FF + 0.25 x VR). The
maximum potential EB score for a 100 sq m impervious surface is 1.
The maximum EB score a rainwater tank treating such a surface (without a leak for passive irrigation) can
score is 0.59: [0.25* x 1 + 0.25 x 1.36]. If an appropriate slow leak is incorporated into the tank design to allow passive irrigation of an appropriately
large area of garden, restoration of lost infiltration and evapotranspiration losses are achievable, meaning closer to the maximum potential score is possible.
EB calculator allows the modelling of four
simple scenarios:
a) a tank by itself,
b) a raingarden by itself
c) a tank and a raingarden with no
interaction (note in this case, an unchecked assumption is that diverted first
flush water from the tank goes to the garden and not the stormwater drain), and
d) a tank whose overflow (and first flush)
drains to the raingarden.
More complex scenarios can be modelled by
using the Rfunctions outside the webpage environment, or by running EBI calculator
in separate runs and doing some simple calculations. For instance, to estimate
the EBI improvement of connecting an existing rainwater tank to household
appliances, first calculate EBI scores for the existing set up, and then
calculate the scores for the proposed set up. The EBI improvement that could
attract a rebate is the difference between the two.
Raingarden behaviour is modelled using the
function gardenmodel.
It uses hourly inflow data. If there is no tank upstream, the model uses hourly rainfall data from Croydon (1965, as above other rainfall data can be used if gardenmodel is run using R: see above), converted to impervious runoff (by removing the first mm of rain in each day), and multiplied by the impervious catchment area to get inflow in litres per hour. If there is a tank upstream, then the daily overflow (and firstflush, if relevant) volume from the tank is converted to hourly data (with the overflow volume distributed among the hours to match the hourly runoff pattern). This calculation of inflows from a tank is done with with the functions 'distribute.firstflush','distribute.overflow', and 'compile.inflow'.
The function requires a filter profile as an input. The default filter profile for Mt Evelyn is as follows:
d.dm 
porosity 
Ksu.dm.h 
2 
1 
0.25 
5 
0.4 
0.25 
5.05 
0.4 
0.00005 
7.5 
0.4 
0.00005 
12 
0.6 
0.00005 
This default profile assumes a pond depth of 20cm (0.2dm, porosity of air = 1: this depth is subtracted from subsequent depths to calculate depth below the soil surface), and filter medium of loamy sand (to soil depth of 55cm (5.5 dm), porosity =0.4, with underlying gravel to 100cm deep (porosity = 0.6). It assumes that the top 30 cm (3 dm) has an infiltration capacity of 0.25 dm/h (25 mm/h), with the underlying soils with much lower infiltration capacity (0.005 mm/h). This soil profile is a close approximation to that found in our monitored raingarden.
These values are changed as a result of the pond and filter depths, depth of surface soil, and medium values that are entered on the web page. The depth of surface soil is zero for conventional raingardens, but a 60cm deep, sublawn gravelfilled infiltration system under 10 cm of surface soil would have depth of surface soil = 10cm). The soil profile for such a system would be adjusted to the following value:
d.dm 
porosity 
Ksu.dm.h 
0 
1 
0.25 
2 
0.6 
0.25 
6 
0.6 
0.00005 
The web page asks for dimensions of the raingarden that allow it to adjust the above soil profiles, and to calculate the area and perimeter of the filter and pond. It also asks if the bottom is lined, and how much of the sides are lined. From this information, the gardenmodel works out the volume of water that can exfiltrate out through the sides or bottom of the garden at each time step given the depth of water in the garden. The web version assumes that the underlying infiltration rate is also 0.005 mm/h, but this can be altered using the argument Ksu.mm.h in the R version of the model.
The web page asks if the raingarden is vegetated (setting the isveg argument in the R model). If vegetated the model assumes that water is lost from the garden (when it contains any) at a rate equivalent to the potential evapotranspiration rate for Croydon. (Other transpiration rates could be incorporated by including in the rainfall input file.) If it is unvegetated no evapotranspiration is assumed. (Infiltration systems that are sunk below turf should be considered unvegetated as grass roots are unlikely to be deep enough to access water in the system). However, any infiltration system that is at laeast partly unlined is assumed to be accessible by trees within 3 m of the system. The calculator asks for the area (the web page asks for the diameter and converts to area) of the canopy of any nearby trees. The calculator assumes that nearby trees lose water to evapotranspiration at 0.5 times the potential rate from their canopy area.
The critical variables in the gardenmodel function are Af (area of filter), Ap (area of pond), carea (impervious catchment area) all in sq m; Pf (perimeter of filter), Hf (height of the mediumfilled filter), Hp (height of pond), Ho (Height of outlet pipe, if present), all in m (entered as cm on the web page). The web page assumes that an outlet pipe will be choked to permit an outflow at the rate of (impervious catchment area + filter area) * 0.1. This is approximately the highest rate of baseflow observed in Olinda Creek, and is therefore the highest permissible filtered flow. If the outlet pipe is a standard unchoked agricultural pipe, then outlet.rate.L.h should equal the infiltration rate of the filtration medium.
The gardenmodel steps through each time step, distributing existing water in the system plus inflow water between pond, filter, outlet pipe (if present), surrounding soils through exfiltration, and if the capacity of each of these sinks is exceeded by inputs, then water is allocated to overflow. Water quality of the filtered water flowing out of the system is modelled as follows.
Nitrogen concentration of stormwater inflows is assumed to be 2.2 mg/L. Overflow water is assumed to have the same nitrogen concentration as inflow water. and nitrogen removal is modelled according to the following table, and the resulting concentrations are assumed for water flowing out through the outflow pipe, as well as water exfiltrating into the surrounding soils (as it is assumed that N loss from soils is minimal, as it will be dominated by nitrate which is mobile through soils:
Medium

Vegetation type

Normal (wet)

After Dry

Loamy sand

Veg

59%

If ADWP <=4 days then Removal =
59%
Else Removal = 59%  0.3% x ADWP (days)

Unveg

101%

If ADWP <=5 days then Removal =
101%
Else Removal =101%  0.2% x ADWP (days)

Sand

Veg

72%

72%

Unveg

32%

32%

Gravel (Scoria)

Unveg

39%

39%

Note the calculator does not allow the option of a vegetated gravel raingarden.
Phosphorus concentration of inflow water is assumed to equal 0.35 mg/L. For outflow pipe water from sand or loamy sand systems, phosphorus concentration is assumed to be 26% of inflow concentration if vegetated, and 14% of inflow concentrations in unvegetated systems. Unvegetated gravel systems are assumed to reduce P concentrations by 20%. Water that exfiltrates into surrounding soils is assumed to lose almost all phosphorus, with a concentration of 0.001 mg/L assumed.
It is assumed that all sand or loamy sand systems are very efficient at reducing total suspended solids (99% removal through outlet pipes). Unvegetated gravel systems are assumed to reduce TSS concentrations by 20%.
The gardenmodel
function produces a list of the following values:
 budget, a list of vectors of hourly values for inflow (flowin), outflow through an outlet pipe if present (out), evapotranspiration loss (et),
nitrogen load in outflow (Nout), nitrogen concentration of outflow (Nconcout), phosphorus concentration of outflow (Pconcout), total suspended solid concentration of outflow (TSSout), overflow (over), volume of water in pond (store.pond), volume of water in filter (store.filter), exfiltration flow to surrounding soils (Qexf), height of water in system (height.dm).
 filter profile used.
The environmental benefit scores are calculated using the function
garden.EBstats, which requires as input:
 budget, as above
 carea, impervious catchment area of direct runoff inputs into raingarden
 gardenarea, area of the filter
 mean.annrain.mm, mean annual rainfall, set to 950 mm for Mt Evelyn in the web page
 ndaysro.target, target number of days for overflow from the system, set to 12 for Mt Evelyn
 ndaysro.urban, number of days of impervious runoff = number of days with >1 mm rainfall, set to 121 for Mt Evelyn
 Nconc.target, target x percentile nitrogen concentration for any flow out of the system, set to 0.6 mg/L for Mt Evelyn
 Pconc.target, target x percentile phosphorus concentration for any flow out of the system, set to 0.05 mg/L for Mt Evelyn
 TSSconc.target, target x percentile nitrogen concentration for any flow out of the system, set to 20 mg/L for Mt Evelyn
 percentile, value of x in the above percentiles, set to 50, i.e. medians
 filtro.target, permissible flow rate out of the outflow pipe
The EB score of the garden is calculated based on the total area of all upstream impervious surfaces: those draining directly to the garden plus catchment areas of any tanks that drain into the garden. The EB score is the mean of four subindices
 The flowfrequency subindex, FF
 The volumereduction index, VR. Both of these indices were described for tanks, above.
 The waterquality subindex, WQ,
calculated as the mean of the following three subsubindices:
_{},
where [N], [P], [TSS] are concentrations of nitrogen, phosphorus and total suspended solids, respectively. [X]_{g} is the median (or other defined percentile) concentration of element X flowing from the system, and [X]_{t} is the target concentration as defined above. The first number in each denominator is the assumed concentration of untreated stormwater in mg/L. A is the impervious catchment area, as defined above for the other subindices.
 The filtered flow volume index, FV. calculated as:
,
where FV_{g} = the volume of filtered water flowing out of the system, both through the outlet pipe (if present), and through exfiltration to the surrounding soils. FV_{forest} and FV_{pasture} represent the bounds of ideal filtered flow volume. They are derived from the model of Zhang et al. (2001) that predicted evapotranspiration and runoff from catchments with forest and pasture vegetation, as a function of annual rainfall (see figure below). Following the logic above for volume reduction, we assume the ideal volume of filtered flow corresponds to the volume of stream flow generated from a forest. However, we assume that good ecological health would still be feasible if stream flow volumes approached the volumes generated by grassed catchments. We therefore award systems a perfect score for the filtered volume index if the filtered volume is between the runoff volume from a forest and that from pasture.
The figure on the left shows the stream flow coefficients from forested and grassed (pasture) catchments as predicted by annual rainfall (Zhang et al. 2001). The black squares indicate the predicted stream flow coefficients for a catchment with Mt Evelyn's rainfall. The figure on the right shows the relationship between the filtered volume (as a proportion of total runoff) and FV_{g} in Mt Evelyn.
Reference
Zhang L., Dawes W. R., and Walker G. R. (2001). Response of mean annual evapotranspiration to vegetation changes at catchment scale. Water Resources Research 37, 701708.
