Science of the Total Environment 380 (2007) 210 – 219
www.elsevier.com/locate/scitotenv

Simulation of the treatment performance of outdoor subsurface
flow constructed wetlands in temperate climates
Günter Langergraber ⁎Institute of Sanitary Engineering and Water Pollution Control, BOKU — University of Natural Resources and Applied Life Sciences,
Vienna, Muthgasse 18, A-1190 Vienna, Austria
Received 13 October 2005; received in revised form 23 June 2006; accepted 12 October 2006
Available online 8 December 2006

Abstract
Numerical models are a means to increase the understanding of the processes occurring in the “black box” constructed wetland.
Once reliable models for constructed wetlands are available they can be also used for evaluating and improving existing design
criteria. The paper shows simulation results for outdoor experimental subsurface vertical flow constructed wetlands using CW2D, amulti-component reactive transport module developed to simulate transport and reactions of the organic matter, nitrogen andphosphorus in subsurface flow constructed wetlands. The surface area of the experimental vertical flow bed was 20 m2. The
organic load applied was 27 g COD m− 2 d− 1 (corresponding to a specific surface area of 3 m2 per person). The aim of the work is
to calibrate the model for temperature dependency that has been implemented in CW2D. Water temperature during theinvestigation period varied between 4 °C and 18 °C. The measured effluent concentrations during summer could be simulatedusing the standard CW2D parameter set when the flow model was calibrated well. However, the increasing effluent concentrations
at low temperatures could not be simulated with the standard CW2D parameter set where temperature dependencies are considered
only for maximum growth, decay, and hydrolysis rates. By introducing temperature dependencies for half-saturation constants forthe hydrolysis and nitrification processes it was possible to simulate the observed behaviour. The work presented is a step on theway to validate the CW2D module. Model validation is a necessary step before numerical simulation can be finally used inpractice, e.g. for checking existing design guidelines.
© 2006 Elsevier B.V. All rights reserved.
Keywords: CW2D; Numerical simulation; Subsurface vertical flow constructed wetlands; Temperature dependency; Wastewater treatment

1. Introduction
Although much experience exists in constructing andoperating constructed wetlands (e.g. Kadlec et al., 2000)
they are still often looked at as a “black box” in which wateris purified. Therefore up to now the design of constructedwetlands is mainly based on rules of thumb using specificsurface area requirements (e.g. ÖNORM B 2505, 2005) or⁎ Tel.: +43 1 36006 5814; fax: +43 1 3689949.
E-mail address: guenter.langergraber@boku.ac.at.
0048-9697/$ - see front matter © 2006 Elsevier B.V. All rights reserved.
doi:10.1016/j.scitotenv.2006.10.030

simple first-order decay models (e.g. Kadlec and Knight,
1996). Numerical models can provide insight into the “blackbox” and therefore increase the system understanding. Once
reliable numerical models exist they can be used forevaluating and improving existing design criteria.
The multi-component reactive transport module
CW2D (Langergraber, 2001; Langergraber and Šimùnek,2005) was developed to model transport and reactions of
the main constituents of municipal wastewater insubsurface flow constructed wetlands. CW2D is able todescribe the biochemical elimination and transformation

G. Langergraber / Science of the Total Environment 380 (2007) 210–219

processes for dissolved forms of organic matter, nitrogenand phosphorus.
Main research needs regarding modelling of constructed wetland processes include (Langergraber, 2003):
detailed hydraulic investigations on full-scale constructed wetlands, simulations of outdoor constructedwetland systems, investigation of plant uptake models,
improving the simulation tool by including a model thatis able to describe substrate clogging processes, anddevelopment of experimental techniques for the measurement of CW2D model parameters.
The paper shows simulation results for outdoor
experimental subsurface vertical flow constructed wetlands to calibrate the model for temperature dependency
that has been implemented in CW2D. The special focusof the paper therefore is simulating the treatment
performance for different water temperatures.
2. Materials and methods
2.1.The multi-component reactive transport module CW2D
The multi-component reactive transport module CW2D
(Langergraber, 2001) was developed to describe thebiochemical transformation and degradation processes insubsurface flow constructed wetlands. CW2D is incorporated into the HYDRUS-2D variably-saturated water flow
and solute transport program (Šimùnek et al., 1999) andconsiders 12 components and 9 processes. The components include dissolved oxygen, organic matter (threefractions of different degradability), ammonium, nitrite,
nitrate, and nitrogen gas, inorganic phosphorus, andheterotrophic and autotrophic micro-organisms. Organic
nitrogen and organic phosphorus are modelled as nutrient
contents of the organic matter. The processes considered
are hydrolysis, mineralization of organic matter, nitrification (modelled as a two-step process), denitrification, and alysis process for the micro-organisms. The mathematicalstructure of CW2D is based on the mathematical structureof the Activated Sludge Models (ASMs) introduced byHenze et al. (2000). For a detailed discussion of the CW2D
module see Langergraber and Šimùnek (2005).
As CW2D is coupled with a mechanistic model able todescribe variably saturated water flow the tool can beapplied for both subsurface vertical and horizontal flow
constructed wetlands. A recently developed model(Rousseau, 2005) uses a similar reaction model. However, tanks-in-series are applied for describing water flow
and therefore it can only be used for modelling horizontal
flow systems where saturated water conditions occur. The
main drawback of CW2D is that up to now only dissolved
substances are considered. A more realistic model should

211

Table 1
Layout of the experimental CW in Ernsthofen (Lower Austria)
Parameter
Surface area
Specificsurface area
Organic loading(design)
Organic loading(measured)
Daily hydraulicloading

Unit

Bed 1

Bed 2

Bed 3

2

m
m2/PECOD

17.8
4

18.5
3

18.2
2

g COD/m2

20

27

40

g COD/m2

17.5 ± 0.5

23.4 ± 0.7

35.1 ± 1.5

L

573

795

1177

also include particulate wastewater constituents (Langergraber and Šimùnek, 2005).
In CW2D the reaction rates are calculated using
Monod-type kinetic expressions by
r ¼ −lmax dcdX
Ks þ cð1Þ

where r is the reaction rate [M L− 3 T− 1], μmax is the
maximum growth rate [T − 1 ], c is the substrateconcentration [M L− 3], Ks is the half-saturation constant[M L− 3], the concentration when the reaction rate is half
the maximum rate, and X is the biomass concentration[M L− 3].
In the standard parameter set for CW2D (Langergraber,2001) the following parameters are considered to betemperature dependent:- the saturation concentration of oxygen,- the diffusion coefficients,- the maximum growth/decay rates of the microorganisms, and- the maximum hydrolysis rate.
In the calculated reaction rates temperature dependency therefore is only included in the maximum
growth rates. The half-saturation constants are considered to be independent from temperature such as
proposed by Henze et al. (2000).
In HYDRUS-2D (Šimùnek et al., 1999) the Arrhenius
equation is used to describe the temperature dependencies. For a temperature dependent parameter “a” theArrhenius equation can be written as follows (e.g. Stummand Morgan, 1996):
ðaT ¼ a20-C de

Ead T A −T A
20
RdT A dT A
20

Þ
ð2Þ

where T A is the absolute temperature [K], a T is theAparameter value at the absolutetemperature T A, T 20
is theabsolute reference temperature (20 °C = 293.15 K), a20 °C

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G. Langergraber / Science of the Total Environment 380 (2007) 210–219

Table 2
Measured influent concentrations in (mg/l)
Parameter

SS

COD

BOD5

TOC⁎

NH4–N

NO3–N

Norg⁎

TN⁎

PO4–P

TP⁎

No. of samples
Median value
95% Conf.-Int.
Mean valueStandard dev.
Minimum
Maximum

49
130
10
133
34
70
270

49
545
17
554
61
402
728

45
380
11
375
37
280
460

6
179
18.8
183
23.4
146
216

55
68.0
1.5
67.6
5.8
52.9
81.7

49
0.4
0.0
0.4
0.1
0.3
0.6

6
14.7
3.5
15.8
4.3
10.9
23.1

6
83.9
3.2
84.8
4.0
81.0
89.6

49
12.5
0.3
12.5
1.0
9.5
15.2

6
12.0
0.6
12.1
0.8
11.0
13.2

⁎Analysed in the university lab; Conf.-Int. = Confidence interval; Standard dev. = Standard deviation.

is the parameter value at the reference temperature, R is
the universal gas constant [8.314 J/(mol.K)], and Ea is theactivation energy [J/mol].
2.2. The experimental plant
The experimental constructed wetlands are located at
the site of the wastewater treatment plant Ernsthofen(Lower Austria). A 3-chamber unit is used for mechanical pre-treatment. The experimental plant consists ofthree parallel operated subsurface vertical flow beds witha surface area of about 20 m2 each (Table 1) operated
with intermittent loading (4 loadings a day). The organicloads applied are 20, 27 and 40 g COD m− 2 d− 1, whichcorresponds to a specific surface area requirement of 4, 3
and 2 m2 per PECOD, respectively. The resulting hydraulic loading rates for bed 1 through 3 are 32.2, 43.0,
and 64.7 mm/d. The organic load of 20 g COD m− 2 d− 1
has been found to be the limit up to which subsurface
vertical flow beds with sandy substrate for the main layer
can be operated in temperate climates without clogging
problems (e.g. Winter and Goetz, 2003).
In this paper the results of bed 2 (3 m2/PECOD) areused for the investigations.
The main layer of the filter consists of 50 cm sandy
substrate (gravel size 0.06–4 mm, d10 = 0.2 mm). An

intermediate layer of 10 cm thickness with a gravel size of
4–8 mm prevents fine particles to be washed out into thedrainage layer (15 cm thick; gravel 16–32 mm) where theeffluent is collected by means of tile drains. The filter isplanted with common reed (Phragmites australis).
The experimental plant was operated automaticallyusing a LabView® program over a period of 20 months(including two winters). The pore water content indifferent depths of the main layer and effluent flow rates
have been recorded on-line. Water samples have beencollected by the local plant staff on a weekly basis andhave been analysed in the plant laboratory forsuspended solids (SS), organic matter (COD and
BOD5), nitrogen (NH4–N, NO2–N, and NO3–N) andphosphorus (PO4–P). The plant lab data have beenchecked every two months by analysing parallel
samples in the university lab. In addition the following
parameters have been analysed in the university lab:
Total organic carbon (TOC), organic and total nitrogen(Norg and TN, respectively), and total phosphorus (TP).
For small plants (i.e. less than 500 persons) the
standards in Austria (1.AEVkA, 1996) allow a maximum ammonia nitrogen effluent concentration of
10 mg/l. However, this limit only has to be met atwater temperatures higher than 12 °C. Effluent concentrations for organic matter (90 mg/l for COD and

Table 3
Measured effluent concentrations of bed 2 (3 m2/PECOD)
Parameter

Unit

Temperature

°C

4

6

8

10

12

14

16

18

mg/l
mg/l
mg/l
mg/l
mg/l
mg/l
mg/l
mg/l

7 (15)
57.6
8.1
28.4
7.2
27.23
5.89
25.5
7.6

9 (14)
43.4
6.3
14.3
6.6
13.48
6.26
42.4
9.9

3 (4)
33.6
2.7
5.0
1.4
3.53
3.16
53.6
5.0

2
30.4
9.5
6.0
4.2
0.64
0.23
55.3
5.8

8
26.8
6.3
4.7
1.5
0.06
0.05
56.4
6.8

7
27.4
5.1
4.0
1.3
0.06
0.07
47.9
8.6

9
27.6
2.6
4.0
0.7
0.05
0.04
58.2
6.3

3
30.0
1.7
4.3
0.6
0.03
0.01
63.7
5.0

No. of samples⁎
COD
Mean valueStandard deviation
Mean value
BOD5Standard deviation
NH4–N
Mean valueStandard deviation
NO3–N
Mean valueStandard deviation⁎Values in brackets for NH4–N that was analysed biweekly during the winter month.

G. Langergraber / Science of the Total Environment 380 (2007) 210–219

213

Fig. 1. Measured COD effluent concentration vs. temperature.

25 mg/l for BOD5, respectively) have to be met thewhole year around. For small plants there is no standard
for total nitrogen and phosphorus.

confidence interval for the median. If the notches of 2
median values do not overlap there is a statisticallysignificant difference amongst the median values at the
95% confidence level.

2.3. Statistical methods
3. Results and discussion“STATGRAPHICS Plus for Windows 4.0” was used
for statistical evaluation of the data. Figures show “Boxand-Whisker Plots”: The box encloses the middle 50%
and the median value is drawn as a vertical line inside
the box, the mean value is given as a cross. Horizontal
lines (whiskers) extend from each end of the box. The
lower/upper whisker is drawn from the lower/upper
quartile to the smallest/largest value within 1.5 interquartile ranges. The dots represent outliers. The lengthof the notch around the median value represents a 95%

3.1. Measured data
Table 2 shows the analyses of the measured concentrations of the mechanically pre-treated influent from May
2004 until April 2005. The influent concentrations havebeen rather constant throughout the investigation period.
Table 3 shows the effluent concentrations of COD,
BOD5, NH4–N and NO3–N for bed 2 (3 m2/PECOD) as afunction of the effluent water temperature. During the

Fig. 2. Measured NH4–N effluent concentration vs. temperature.

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G. Langergraber / Science of the Total Environment 380 (2007) 210–219

Fig. 3. Measured and simulated effluent flow and cumulative effluent.

investigation period wastewater temperatures varied
between 4 and 18 °C. Figs. 1 and 2 show the Box-andWhisker-Plots for effluent concentrations vs. wastewater temperature for COD and NH4–N, respectively. The
effluent concentration of COD does not exceed theAustrian effluent standards (Fig. 1) whereas they havebeen exceeded for BOD5 (Table 3). For NH4–N the
effluent standards have been met also for wastewatertemperatures of 8 °C (Fig. 2). Effluent concentrations
higher than 10 mg NH4–N/l only occurred at wastewatertemperatures lower than 8 °C.

and 33 rows. This results in a two-dimensional finite
element mesh consisting of 1023 nodes and 1920
triangular finite elements. An atmospheric boundary
condition was assigned to the top of the systemrepresenting the influent distribution system, and aconstant pressure head boundary condition (constanthead of − 4 cm) to one side of the drainage layer.
3.3. Simulation of water flow
It has been shown that a good match of simulation
results with CW2D can only be achieved once thehydraulic behaviour of the system has been modelled
successfully (Langergraber, 2003). Therefore as a firststep the flow model has to be calibrated. The main layersof the experimental plant consist of the same sandy
substrate as pilot-scale constructed wetlands (PSCWs)

3.2. Model set-up
The width of the transport domain in the numericalsimulations was 4 m, and its depth 0.8 m, while thetransport domain itself was discretized into 31 columns
Table 4CW2D influent concentrations and simulated effluent concentrations
Parameter

Temperature

CR

CS

CI

COD

NH4–N

NO2–N

NO3–N

Unit

°C

(mg/l)(mg/l)(mg/l)(mg/l)(mg/l)(mg/l)(mg/l)

Influent
Effluent

–
18
15
12
10
8
6
4

350
0.3
0.3
0.3
0.2
0.2
0.2
0.2

180
2.8
2.8
2.9
2.9
2.9
2.9
3.0

15
24.1
22.8
21.7
21.0
20.5
19.9
19.5

540
27.1
25.9
24.8
24.2
23.6
23.1
22.7

64
0.066
0.073
0.085
0.095
0.114
0.138
0.171

0.015
0.024
0.024
0.026
0.028
0.031
0.036
0.041

0.5
60.4
64.4
65.5
66.1
67.5
70.3
74.1

CR, CS, CI: readily, and slowly biodegradable, and inert organic matter, respectively (Langergraber, 2001) Influent fractionation of COD:
CODinfluent = CR + CS + CI; CI = 0.5 ⁎ CODeffluent; CR = ca. 2 ⁎ CS.

G. Langergraber / Science of the Total Environment 380 (2007) 210–219

215

Fig. 4. Measured and simulated COD and NH4–N effluent concentrations using the CW2D standard parameter set.

in Vienna (Langergraber et al., 2004). Effluent flow
measurements of the PSCWs were used as input data for
the inverse simulation to determine the parameters of themodel describing the unsaturated hydraulic properties(Mollner, 2005). The parameters obtained from the
PSCWs then have been used for the simulations of theexperimental plant Ernsthofen. Fig. 3 compares measured and simulated effluent flow rate and cumulative
effluent of the experimental plant. The simulation
results match the measured data well.
3.4. Simulations with the standard parameter set
Table 4 shows the CW2D influent concentrations used
for the simulations. For the simulations the model influent
concentrations were kept constant as the measured

concentrations have been rather constant during theinvestigation period (Table 2). Only the temperature waschanged for the different simulation runs.
The simulated effluent concentrations using thestandard parameter set of CW2D (Langergraber, 2001)
also are shown in Table 4 for different water temperatures. The simulated effluent concentrations for 18 °C
matched the measured data (Table 3).
Fig. 4 compares the mean values of the simulated
COD and NH4–N effluent concentrations and the measured data. The increased effluent concentrations measured at lower temperatures could not be simulated.
Applying only the temperature dependencies of the
maximum growth, decay, and hydrolysis rates it was notpossible to simulate the observed behaviour. In contrast
to the measured data the COD effluent concentrations

Fig. 5. Organic matter fractions and COD effluent concentrations at 4 °C for varying KX.

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G. Langergraber / Science of the Total Environment 380 (2007) 210–219

Fig. 6. COD, NH4–N and NO3–N effluent concentrations at 4 °C for varying KX.

decreased with decreasing temperature. This can be
explained because at low temperatures less lysis causes
less production organic matter and in addition hydrolysis was over predicted. For NH4–N only a slightincrease of the simulated effluent concentration occurred indicating that simulated nitrification rates at low
temperatures have been too high.

dencies of the half-saturation constants have been carriedout at a water temperature of 4 °C.
According to Langergraber and Šimùnek (2005) thereaction rate for hydrolysis, i.e. the conversion of slowly
biodegradable organic matter CS into readily biodegradable organic matter CR, is written as
cCS =cXH
cXH
KX þ ccs =cXH

3.5. Modification of the parameter set

rc1 ¼ Kh

Bornemann et al. (1998) defined a parameter set for theASM1 in which they introduced a temperature dependency for the half-saturation constants for hydrolysis andnitrification. The same concept has been applied for thiswork. The simulations to obtain the temperature depen-

where rc1 is the reaction rate for hydrolysis, Kh is the
maximum hydrolysis rate, cCS is the concentration ofslowly biodegradable organic matter, cXH is theconcentration of heterotrophic bacteria, and KX is thehalf-saturation constant for hydrolysis.

Fig. 7. COD, NH4–N and NO3–N effluent concentrations at 4 °C for varying KANs,NH4 ( KX = 0.35).

ð3Þ

G. Langergraber / Science of the Total Environment 380 (2007) 210–219
Table 5
Calculated activation energies for KX and KANs,NH4
Parameter

Value at 4 °C

Value at 20 °C

Ea (J/mol)

KX
KANs,NH4

0.35
25

0.1
0.5

− 53,000−160,000

COD effluent concentrations. The half-saturation
constant of ammonia at 4 °C was determined to
be KANs,NH4(4 °C) = 25 mg/l.
Table 5 gives the calculated activation energies for KX
and KANs,NH4 for the Arrhenius Eq. (2) using theparameters obtained from Figs. 6 and 7. Bornemannet al. (1998) report a value of 0.03 for KX at 20 °C and atemperature coefficient of 0.11 (resulting in a three-foldvalue for KX at 10 °C). For ASM2 Henze et al. (2000)
report KX values of 0.1 for 20 °C and 0.3 for 10 °C,
respectively. Calculating the activation energy one e gets
−74,000 J/mol for both literature values. The values
obtained in this study, KX(4 °C) = 0.35 and Ea =−53,000 J/mol, result in a KX values 0.22 for 10 °C.
Compared to the literature values the values obtained inthis study are in a similar range. Hydrolyses processes are
predicted to occur at a lower rate. For KANs,NH4
Bornemann et al. (1998) report a value of 0.5 at 20 °C
and a temperature coefficient of 0.09 (resulting in a twofold value for KX at 10 °C). The activation energy
calculated from these parameters is −46,000 J/mol. In thisstudy KANs,NH4(4 °C) = 25 mg/l and Ea = −160,000 J/mol
result in KANs,NH4(10 °C) = 5.5 mg/l, i.e. the five-foldvalue as the literature value. One has to take into accountthat the values by Bornemann et al. (1998) are reported for
activated sludge systems and for nitrification modelled asingle step process.
Table 6 shows the values of KX and KANs,NH4 calculated for different temperatures and the simulated effluent concentrations using these values. Fig. 8 finallycompares the measured and simulated COD and NH4–N
effluent concentrations using the modified parameter
set. The simulation results match the measured data wellfor COD and NH4–N effluent concentrations. However, the simulated effluent concentrations of NO3–N
are over predicted. Due to the reduced hydrolyses processes less readily biodegradable organic matter thatis required for denitrification is produced. In the model

An increasing KX value influences only the organic
matter fractions by allowing less slowly biodegradableorganic matter to be converted into readily biodegradable organic matter. Therefore the COD effluent
concentration increases (Fig. 5). Fig. 6 shows theCOD, NH4–N and NO3–N effluent concentrations at
4 °C for different half-saturation constants for hydrolysis
KX. NH4–N and NO3–N concentrations are not effectedby changing KX values. For 4 °C half-saturation constantfor hydrolysis was determined to be KX(4 °C) = 0.35.
The reaction rate for the first step of nitrification, i.e.
the conversion of ammonia into nitrite, is according toLangergraber and Šimùnek (2005):
cO2
cNH4
KANs;O2 þ cO2 KANs;NH4 þ cNH4
cIP

cXANs
KANs;IP þ cIP

217

rc6 ¼ lANs

ð4Þ

where rc6 is the reaction rate for the first step ofnitrification, μANs is the maximum aerobic growth rate
on ammonia, cO2 and KANs,O2 are the concentration andthe half-saturation constant of dissolved oxygen, cNH4and KANs,NH4 of ammonia, cIP and KANs,IP of inorganic
phosphorus, respectively, and cXANs is the concentrationof ammonia oxidizing bacteria (Nitrosomonas spp.).
Fig. 7 shows the COD, NH4–N and NO3–N effluent
concentrations at 4 °C for different half-saturation
constant of ammonia KANs,NH4. As expected theinhibition of the first step of nitrification due toincreasing KANs,NH4 values has no influence on the

Table 6
Values for KX and KANs,NH4 used and simulated effluent concentrations for the modified parameter set
Parameter

Temperature

KANs,NH4

Unit°C(mg/l)

Effluent

18
15
12
11
8
6
4

0.8
1.6
3.3
5.5
9.0
15.0
25.0

KX

CR

CS

(–)

(mg/l)(mg/l)

0.12
0.15
0.18
0.22
0.25
0.30
0.35

0.2
0.2
0.2
0.3
0.2
0.3
0.3

3.9
6.2
9.2
14.2
18.8
27.1
36.1

COD

NH4–N

NO2–N

NO3–N

(mg/l)(mg/l)(mg/l)(mg/l)(mg/l)

24.1
22.8
21.7
21.1
20.5
20.1
19.6

28.2
29.2
31.2
35.6
39.6
47.5
56.0

0.1
0.4
1.2
2.5
4.8
11.5
25.9

0.020
0.020
0.020
0.021
0.021
0.026
0.030

60.8
66.6
69.3
69.9
67.6
61.8
50.2

CI

CR, CS, CI: readily, and slowly biodegradable, and inert organic matter, respectively (Langergraber, 2001).

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G. Langergraber / Science of the Total Environment 380 (2007) 210–219

Fig. 8. Measured and simulated COD and NH4–N effluent concentrations using the modified parameter set.

this could be compensated by reducing the denitrification half-saturation constant for organic matter resulting in enhanced denitrification at low organic matter
concentrations.
4. Summary and conclusions
The paper shows simulation results for an outdoor
experimental subsurface vertical flow constructed wetland. The effluent concentrations during summer could
be simulated using the standard CW2D parameter set
when the flow model was calibrated well. However, theeffluent concentrations at low temperatures could not
be simulated with the standard CW2D parameter set
where temperature dependencies are considered only for
maximum growth, decay, and hydrolysis rates. Measured COD and NH4–N effluent concentrations could
not be simulated because hydrolysis and nitrification
at low temperatures were over predicted.
It was shown that by introducing temperature dependencies for the half-saturation constants of hydrolysis
and nitrification it is possible to simulate the COD
and NH4–N effluent concentrations at low temperatures. Temperature dependency for KX and KANs,NH4
has been considered also by e.g. Bornemann et al.
(1998). However, the new parameter set introduced
still has to be validated for other constructed wetland
systems.
The work is a step on the way to validate the multicomponent reactive transport module CW2D. Modelvalidation is necessary before numerical simulation canbe finally used in practice, e.g. for checking existing
design guidelines.

Acknowledgements
The experiments were carried out within the project“Optimization of subsurface vertical flow constructedwetlands” funded by the Austrian Ministry for Agriculture, Forestry, Environment and Water Management.
The author especially thanks the staff of the WWTP
Ernsthofen, Mr. Franz Eglseer and Mr. Karl Hiebl, for
operating the experimental plant and performing theweekly analyses.
The simulation work was done within the frameworkof the project “Characterisation of microbial biocoenosis to optimise removal efficiency and design ofsubsurface flow constructed wetlands for wastewater
treatment” funded by the Austrian Science Fund (FWF,
project no.: P16212-B06). The author is grateful for the
support.
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