U. Dittmer*, D. Meyer* and G. Langergraber***Institute of Environmental Engineering, Technical University of Kaiserslautern, Paul-Ehrlich-Strasse, 14-316,
D-67663 Kaiserslautern, Germany (E-mail: dittmer@rhrk.uni-kl.de)**Institute of Sanitary Engineering and Water Pollution Control, BOKU - University of Natural Resources andApplied Life Sciences, Vienna, Muthgasse 18, A-1190 Vienna, Austria (E-mail: guenter.langergraber@boku.ac.at)
Abstract Constructed wetlands (CWs) have proved to be a highly effective measure to reduce theecological impact of combined sewer overflows (CSOs) on receiving waters. Due to the stochastic nature of
the loading regime and the multitude of environmental influences, assessment of the performance of suchplants requires detailed mathematical modelling. A multi-component reactive transport module (CW2D) wasapplied to simulate the flow, transport and degradation processes occurring in a CW for CSO treatment.
CW2D was originally developed to simulate the treatment of municipal wastewater in subsurface flow CWs.
Loading and operational conditions in CSO treatment differ fundamentally from the conditions occurring for
wastewater treatment. Despite these differences, first results from the simulation of lab-scale experiments
show, that the model is generally applicable to this type of plant. Modelling of adsorption, degradation
processes, and influent fractionation, however, require further research.
Keywords Combined sewer overflow; CW2D; numerical simulation; stormwater treatment; subsurface flow
constructed wetlands

Water Science & Technology Vol 51 No 9 pp 225–232 Q IWA Publishing 2005

Simulation of a subsurface vertical flow constructedwetland for CSO treatment

Introduction
Constructed wetlands for CSO treatment

Constructed wetlands (CWs) for the treatment of combined sewer overflows (CSO) are
generally designed as vertical flow soil filters with a detention basin on top of the filter
layer. In most cases sand is used as filter material. The sand layer is commonly plantedwith reed (Phragmites australis). A throttle in the outlet structure is used to control thefiltration rate and the detention time in the system. The main treatment objectives for
CSO are: (1) detention and reduction of peak flows, (2) reduction of suspended solids byfiltration and (3) reduction of soluble and particulate pollutants by adsorption and subsequent biological degradation.
The filter layer is completely drained after every loading event to ensure maximum
aeration and aerobic degradation during the dry period. To prevent clogging of the filter
due to excessive loads of suspended solids (SS), pre-treatment is essential. This is
generally done by sedimentation in a conventional storm water tank. Details of design,operation and performance of constructed wetlands for CSO treatment are described by
Uhl and Dittmer (2005).
Loading characteristics

Fundamental differences between wetlands for wastewater and for CSO treatment are theloading regime and the quality parameters of the inflow. In CSO treatment the successionof loading events and dry periods is characterized by the stochastic nature of rainfall
and the runoff behavior of the catchment area. Extreme cases are permanent loading forweeks on one hand, and several months without any loading event on the other. Loading225

U. Dittmer et al.

rates (inflow/filter area) show a high variability ranging from mean values of 0.02 mm/s
for less intensive rain events, up to peak flows of 1 mm/s during intensive storm events.
Quality parameters of CSO show generally lower pollution than wastewater. Organic
matter predominantly occurs in particulate form, which can mainly be attributed to remobilisation of sewer sediments. As this effect is strongly related to the flow rate, SS concentrations as well as solute/particulate ratio of pollutants are highly variable within thecourse of a rain event.
Aim of the study

The performance of CWs for CSO treatment depends on a multitude of influences suchas temperature, loading rate, pollution and duration of the actual loading, previous dry
period, hydraulic and quality characteristics of previous loading events (Dittmer et al.,2004). All of these parameters vary stochastically. Thus determining the performance
during a specific loading event requires mathematical modelling. This applies particularly
when influences of changes in design and operation need to be evaluated.
The assessment of emissions from CSOs is generally based on long-term simulationsof the entire sewer system. The overall goal of modelling CWs for CSO treatment is thedevelopment of a simulation tool that allows long-term simulation and that therefore canbe combined with pollution load models for sewer systems. Within this framework, thespecific aim of this study is to investigated if a detailed model that was developed for thesimulation of CWs for wastewater treatment can also be applied for CSO treatment.
Further on the processes which can be basically transferred and which require substantial
modifications should be derived from these results.
Materials and methods
Simulation of subsurface flow constructed wetlands

The multi-component reactive transport module (CW2D, Langergraber, 2001) that is
implemented into HYDRUS-2D (Simunek et al., 1999) is applied to simulate the flow,transport and degradation processes occurring in a constructed wetland for the treatmentof CSOs. CW2D was developed to model transport and reactions of the main constituentsof municipal wastewater in subsurface flow constructed wetlands. It is able to describe
the biochemical elimination and transformation processes for organic matter, nitrogenand phosphorus.
Lab-scale columns

226

Loading and environmental conditions of full-scale plants can be neither predicted nor
controlled. Thus, lab-scale columns (Ø 200 mm) were used to test the simulation tool
under defined conditions. Figure 1 shows the layout of the filter columns that corresponds
directly to the layering of a full-scale CW.
The main filter layer consists of sand (grain size 0/2 mm, effective size 0.1 mm, coefficient of uniformity 2.8). The upper gravel layer serves to prevent erosion, while thegravel layer below the filter represents the drainage system. The test rig consists of 6 columns that are all fed identically. The filtration rate of columns 1 to 4 is manually controlled by a throttle in the outlet; Columns 5 and 6 have a free drainage (see Table 1).
The identical operation of pairs ensures the reproducibility of results and helps in separating systematically from random effects.
In the first period the columns were loaded regularly once a week with 15.7 litre ofsynthetic sewer, which corresponds to a loading rate of 0.5 m/event. The synthetic seweris based on the OECD guideline 303A (OECD, 1981), but is diluted to obtain concentrations within the range of CSO quality parameters. The constituents are given insupernatantwater

deaeration
pipe

gravel,2/8 mm,5 cm

U. Dittmer et al.

∆H

sand,
0/2 mm100 cmgravel,2/8 mm25 cm

throttle

Figure 1 Lab-scale filter column

Table 1 Drainage regime of the filter columns
C1/2

Drainage
Limited filtration rate (m/h)

C3/4

C5/6

0.180

free
–

throttled
0.036

Table 2. In a second phase loading intervals and concentrations of pollutants were variedsystematically.
The entire loading volume is applied within about 3 minutes. During infiltration the levelof the supernatant water, the water level in the de-aeration pipe and the effluent flow rate
are measured (variable time steps 30 sec to 30 min). If necessary, the setting of the throttles
is adjusted. The difference between water levels in the column and in the de-aeration pipe
allows for observing the hydraulic conductivity in columns 1 to 4. All columns show aconstant conductivity without any tendency for clogging (C1/2 ¼ 90 cm/h,
C2/4 ¼ 100 cm/h). Lower conductivity of columns 1 and 2 can be explained by the higher
amount of biomass due to longer contact time with nutrients. This observation corresponds
to the significantly higher purification efficiency of these columns.
Tracer experiments using potassium bromide (KBr) were carried out, to calibrate thetransport model. To obtain breakthrough curves, the loading procedure was divided into
Table 2 Composition of synthetic sewer (mg/l)

PeptoneMeat extract
Urea
K2HPO4NaCl
CaCl2·2H2O
Mg2SO4·7H2O

96
66
18
16.8
4.2
2.4
1.2

227

U. Dittmer et al.

three steps. The columns were first loaded with 9.5 litres to obtain saturated conditions.
After this volume had infiltrated, another 2.5 litres were applied containing 10 mg/l Br2.
After the tracer has infiltrated, the last 3.5 litres are loaded. Br2 concentrations in theeffluent were measured with an ion-selective electrode. As the tracer was not washed out
completely, measurements were continued during the next regular loading. For verification of the flow and transport model the same tracer concentration was added to the synthetic sewer and applied under regular loading conditions to columns 2 and 4.
Model of the lab-scale plant

For the simulations of the columns a 2D finite element mesh (105 rows and 3 columns)
was used. On top of the upper gravel layer an atmospheric boundary condition wasapplied, at the bottom a free drainage boundary condition was used.
The supernatant water level decreases from about 40 to 45 cm immediately after theloading with a rate of 2.5 cm per minute. The model is not able to simulate this variable
pressure head. To simulate the behaviour of the supernatant water level a “virtual” layer
with a pore volume of 100% was used. As the lab-scale columns were not planted, theinfluence of vegetation was not considered in the model.
Simulation results and discussion

It has been shown that a good calibration of the flow model is a prerequisite to obtain
good simulation results for multi-component reactive transport simulations (Langergraber,
2003).
Up to now CW2D has successfully been applied to model wetlands for wastewater
treatment with free drainage. CWs for CSO treatment are generally operated with a controlled effluent flow rate. As loading rates and intervals are determined by rainfall, operation of the effluent throttle is the only way to influence the performance of the plant. It
is therefore essential that the model gives correct results for a wide span of possible effluent flow rates. Hence, the flow model was calibrated on the basis of data obtained fromoperation with free drainage to obtain the parameters to describe unsaturated flow. The
calibrated model was than applied to the columns with controlled effluent rates.
Calibration of the flow and single-solute transport model

Volumetric water content and hydraulic conductivity for unsaturated conditions weremodelled using the van Genuchten–Mualem equations implemented in HYDRUS-2D(Simunek et al., 1999). Hysteresis was not considered. The corresponding soil hydraulicproperties are described by the van Genuchten parameters. Values for the sandy main
layer are given in Table 3. a and n are empirical coefficients that influence the shape ofthe functions Q(h) and K(h). The virtual layer for supernatant water was simulated with
Qr ¼ 0 and Qs ¼ 1 and Ks ¼ 106 cm/h. With these values, head loss and retardation
within the additional layer are negligible. Values for the gravel layers were taken fromliterature (Schneider, 2003).
Table 3 Soil hydraulic parameters of the main layer for the van Genuchten modelParameter

Unit
Value
228

Residual water

Saturated water

Saturated hydrauliccontent Qr

content Qs

conductivity Ks(dm3w/dm3s )0.050(dm3w/dm3s )
0.304

(m/h)
0.65

Empirical parameters
a

n

(dm21
s )
0.02

(2)
3

K s ½m=s ¼ 0:0116·d210 ½mm

ð1Þ

U. Dittmer et al.

Estimating the van Genuchten parameters of the sand layer by inverse simulation(implemented in HYDRUS-2D) did not give reasonable results. To calibrate the flow
model, these parameters were fitted by matching the curves of simulated and measured
effluent rates as functions of time. Best results were obtained with the values given in
Table 3. The values for a and n are close to those given by Schaap et al. (1998). Qs is
also within the range of values given in the literature. Ks is significantly lower than thevalues determined in columns 1 to 4. However, a rough estimation using the Hazen
approach (e.g. Vukovic and Soro, 1992)

gives an even lower conductivity of Ks ¼ 0.40 m/h.
Figure 2 shows the corresponding simulated effluent flow rate compared with several
measured curves from column 6 (free drainage). Despite virtually identical conditions of
all loading events, measured effluent curves show significant variations. This confirmsthat the infiltration process under the given combination of basic conditions (free drainage, extremely high loading rate and pressure head of supernatant water) is extremely
sensitive to the slightest variations of environmental conditions. Considering these uncertainties simulated and measured data show a good match.
Figure 3 shows the measured and simulated breakthrough curves of the tracer experiment using the basis of the soil parameters given in Table 3 and roughly estimatedvalues for the dispersivity (DL ¼ 0.3 dm, DT ¼ 1 dm). The simulated curve fits themeasured data well.
Simulation with controlled flow rate

As the calibration of the flow and single-solute transport model was successful for freedrainage, the simulation should also produce correct results when the effluent rate is controlled by a throttle. Figure 4 shows measured and simulated breakthrough curves for columns 2 and 4, respectively, under regular loading conditions. As the change in theboundary condition does not affect the transport model, simulated curves for both columns are identical. This theoretical assumption is confirmed by measured data as the datafor both columns show only slight variations. The simulation results match the measured
data well.
12

Measured
Simulated

Effluent flow rate (ml/s)

10
8
6
4
2
0
0

10

20

30

40

50

60

Time after feeding (min)Figure 2 Measured and simulated effluent flow rate for free drainage

229

10

Measured
Simulated

U. Dittmer et al.

Tracer concentration (mg/l)

9
8
7
6
5
4
3
2
1
0

0

5

10
15
20
Cumulated effluent volume (litre)

25

30

Figure 3 Measured and simulated breakthrough curves of column 6

Tracer concentration (mg/l)

12
10
8
6
4

Column 4 (0.180 mm/h)-measured
Column 4 (0.180 mm/h)-simulated
Column 2 (0.036 mm/h)-measured
Column 2 (0.036 mm/h)-simulated

2
0

0

2

4
6
8
10
Cumulated effluent volume (litre)

12

14

Figure 4 Measured and simulated breakthrough curves for controlled effluent flow rate
Reactive transport model

230

The multi-component reactive transport model CW2D was tested for the column withfree drainage. The standard parameter set as given by Langergraber (2001) was used
except for the nitrogen content of COD. Adsorption was only considered for ammonia
and inorganic phosphorus.
The model requires three fractions of organic matter (COD): inert, readily and slowly
biodegradable organic matter (CI, CR and CS, respectively). As commonly applied formunicipal wastewater CI was set to 80% of the mean effluent concentration of COD. The
CR to CS ratio of the remaining COD was estimated to be about 2:1. Measured inflow
concentrations of organic nitrogen were around 26.5 mg/l, with 8.5 mg/l originating fromurea. Assuming instantaneous hydrolysis of urea, this fraction was considered as ammonia nitrogen. The remaining fraction of 18 mg/l is contained in proteins. Thus, the nitrogen content of COD was set to 0.10 gN/gCOD for all COD fractions.
After about 20 weeks the simulated system reached a steady state, i.e. the mean effluent concentrations of each loading remained constant. Table 4 gives influent and steadystate mean effluent concentrations.

Table 4 Measured influent and effluent concentrations and simulation results
CR

CS

CI

COD

NH4-N

NO2-N

NO3-N

Norg

Unit

mgCOD/l

mgCOD/l

mgCOD/l

mg/l

mg/l

mg/l

mg/l

mg/l

Influent
Effl. measured
Effl. simulated

(95)
–
12.8

(45)
–
6.5

(40)
–
40.5

180
51
59.8

8.5
0.44
1.19

0.030
0.025
0.065

0.9
17.8
9.2

26.5 (18)9.5
6.0() … estimated composition of organic matter (COD) for the simulation

COD elimination in reality occurs by adsorption and subsequent degradation oforganic matter. As adsorption of COD is not considered in the model, degradation is limited to the detention time within the active sand layer. Further investigations are stillrequired regarding the correct influent fractionation of COD mainly due to the use of thesynthetic sewer in particular and for CSO in general.
Like degradation of organic matter, nitrification also takes place during the dry
periods, resulting in high effluent concentrations of nitrate nitrogen. Due to the complete
aeration between the events generally only little denitrification occurs. The simulation
gives an effluent concentration of total nitrogen of 16.4 mg/l, while measurements show aconcentration of 27.7 mg/l. This difference can be partly explained by the high content oforganic nitrogen in the synthetic sewer and by the lack of knowledge about the details of
the adsorption process that plays a major role in the nitrogen transformation processes.

U. Dittmer et al.

Component

Conclusions and outlook

The results show, that CW2D is generally applicable for the simulation of CWs for CSO
treatment. Flow and single-solute transport simulations give plausible results for freedrainage as well as for controlled flow filtration rates. This is essential in the field of CSO
treatment, as the effluent throttle is the only way to influence the performance of a fullscale plant during operation. The measurements and simulation results show that unsaturated flow is extremely sensitive against slight variations of experimental conditions.
The laboratory experiments were not originally designed to be the basis for a model
calibration. Several adjustments in the operation are therefore required to obtain more
realistic conditions. Using a synthetic sewer ensures constant influent composition andreproducible results. On the other hand, adsorption and degradation characteristics of theconstituents differ from those of a real sewer. Further investigations are also required for
the COD fractionating for CSO that differs significantly from wastewater during dry
weather conditions. Therefore in future experiments the filter columns will be loadedwith real sewer.
As degradation predominantly occurs in the dry period between the loadings, adsorption of solute compounds is fundamental for the performance of the CW. Additional
experiments will be carried out to analyze sorption processes in detail and determine
influences of environmental conditions. An adequate model (linear, Freundlich or Langmuir isotherms) should be determined and calibrated.
Soil analyses of a full-scale plant have shown pronounced gradients of biologicalactivity in vertical and horizontal direction. In the vertical direction, adsorption anddegradation are almost limited to the upper 10 cm of the sandy main layer. Even higher
activity is found in the sediment layer accumulating on top of the filter. This sedimentlayer preferentially develops close to the inlet. The same goes for the development of thebiocoenosis in the main layer.
The laboratory experiments are basically 1D flow processes, while a detailed simulation of the full-scale plant requires a 2D model, considering the variations of hydraulic231

U. Dittmer et al.

and adsorption parameters of the soil in both dimensions. Calibration based on measured
data has to demonstrate how far the system can be simplified without decreasing the significance of the results.
As the loading occurs stochastically, biological processes within a full-scale plant do
generally not reach a steady state. Further simulations will show if the model is able toassess the performance of a wetland during permanent inundation as well as the effect oflong dry periods.
Acknowledgements

The lab-scale experiments were part of the research project “Development of strategies
for enhanced CSO treatment using constructed wetlands” funded by the German Federal
Ministry of Education and Research (project no.: 02WA0084).

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