The influence of vegetation in stormwater biofilters on infiltration and nitrogen
removal: preliminary findings
T. Pham*, E. G. Payne*, T. D. Fletcher**, P. L. Cook *, A. Deletic * and B. E. Hatt *,
* Department of Civil Engineering, Monash University, Wellington Rd, Clayton, Victoria, 3800,
Australia (E-mail: tracey.pham@monash.edu.au; Emily.payne@monash.edu.au)
** Dept. of Resource Mgt & Geography, The University of Melbourne, Burnley Campus, 500
Yarra Boulevard, Burnley, Victoria,
ABSTRACT
This study provides new information on the influence of vegetation type on the infiltration rate and
removal of nutrients in biofilters. Compared to previous studies, a wider range of plant species (11
species native to Western Australia, and 11 native to Victoria) and plant types (lawn grasses,
grasses, sedges, rushes and shrubs) were examined in a laboratory-column study. The preliminary
results indicate that the presence and type of vegetation influence infiltration rate and nitrogen
removal in biofilters. In the early stages of the experiment, vegetation reduced the infiltration rate of
columns as compared to soil-only controls, but over time this trend began to change, with.
Importantly, whilst all plant species were able to reduce effluent concentrations for Total Nitrogen
(TN) and nitrogen oxides (NOx), soil-only control columns leached NOx. Columns with submerged
zones universally resulted in greater reductions in concentration for TN and NOx than traditional
non-submerged columns (although the differences were often minor). Whilst there were some
differences in removal performance between plant species, these differences were also relatively
small, with TN outflow concentration averaging 0.44 mg/L and 0.26 mg/L for non-submerged and
submerged columns respectively, an 80% and 88% reduction from the inflow concentration of
2.27mg/L. These preliminary results demonstrate that as long as the media is carefully selected,
designers can choose from a relatively wide range of plant species and still achieve effective
nutrient removal.
KEYWORDS
biofiltration, bioretention, nitrogen, phosphorus, vegetation selection
INTRODUCTION
Changes in land-use due to urbanisation mean that urban waterways experience increased peak
flows and increased runoff volumes at higher frequencies as compared to their pre-developed
conditions
(Kibler,
1982).
Further,
urban
stormwater pollutants
originating
from anthropogenic activities deteriorate the water quality of the receiving waterway (Klein, 1979).
Biofiltration systems, which consist of a vegetated basin overlying a soil-based filter media, aim to
mitigate the impact of urban stormwater, both in terms of hydrology and water quality. Past
research has demonstrated that biofilters are able to attenuate flows (Hunt et al., 2008, Barber et al.,
2003), as well as reduce suspended solids, heavy metal and phosphorus concentrations in
stormwater (Hatt et al., 2007, Bratieres et al., 2008). Many studies have explored ways to enhance
biofilter performance by modifying the traditional biofilter design. For example, introduction of a
submerged zone containing a carbon source can greatly enhance nitrate removal by promoting
denitrification, thereby improving overall nitrogen removal rates (Zinger et al., 2007a, Kim et al.,
2003). Yet, nitrogen removal in biofilters continues to be inconsistent (Bratieres et al., 2008).
One aspect of biofilter design which has not been thoroughly investigated is vegetation selection.
While many studies have demonstrated that the presence of vegetation is crucial (Henderson et al.,
2007, Lucas and Greenway, 2008, Bratieres et al., 2008), only a few studies have considered the
actual mechanisms by which plants contribute to biofilter performance. To reduce clogging in
biofilters, some authors suggest that plant species with thick roots may be preferred as they leave
larger macropores for water flow in the soil when the root decays (Le Coustumer et al., 2009, Read
et al., 2010). Although Le Coustumer et al. (2009) speculated that vegetation species which have a
high proportion of fine roots should be avoided; they may worsen the effect of clogging by reducing
pore space, Read et. al (2008, 2010) showed that a dense fine root system is important for
maximising nutrient removal. Other studies also suggest that variation in plant species may account
for variations in treatment performance. Bratieres et al. (2008) concluded that Carex appressa and
Melaleuca ericifolia were significantly better for nitrogen removal because the roots of these
species are better able to exploit the surrounding soil than other plants studied. Large amounts of
microscopic root hairs on Carex roots, and arbuscular mycorrhizal fungi growing on the roots of
Melaleuca led to increased root surface-area of these species.
The study by Read et al. (2010) showed that variation in growth and morphology of plant species
influenced pollutant removal. They recommended that plants chosen for biofilters should have high
growth rates, high root density, high root mass and deep roots (FAWB, 2009). Unfortunately, the
study conducted by Read et al. (2010) encompassed a relatively short time frame so that vegetation
effects over the long term were not tested. Furthermore, only plants indigenous to south-eastern
Australia were tested.
This paper presents the preliminary findings of a larger column study whose broader aims are to
understand the role of vegetation in nitrogen removal by biofilters. The paper aims to identify any
early outstanding plant types or species which are demonstrating an ability to 1) reduce clogging by
maintaining the infiltration rate of biofilters, and 2) minimise nitrogen concentrations in outflows.
It specifically tests species from both south-eastern and south-western Australia.
METHODS
Experimental Setup
Twenty-two Australian plant species (11 indigenous to Western Australia (WA), and 11 indigenous
to Victoria (VIC)) were used for this study. Plant types included lawn grasses, grasses, sedges,
rushes and shrubs in order to represent the range of plant types and morphology commonly found in
biofilters (see Table 1). Ten plants from each species (except C. appressa which had a total of 15
plant representatives) were sourced from nurseries local to the plant species and planted into
300mm high x 150mm diameter black planter bags filled with loamy sand; the media typically used
in biofilters. Plants were grown outside and allowed four months to acclimatise to their new growth
conditions. During this time, they were watered with 400mL of tap water at a frequency sufficient
to maintain them in a vigorous growing condition (typically every 2-3 days).
Following the four-month acclimatisation period, each plant was planted individually into 150 mm
diameter laboratory-scale test columns (that is, one plant per column). Of these ten replicate
columns, five contained a 300mm deep Submerged-Zone (SZ) which was created by a raised outlet
pipe, and five were non-submerged (NS) (i.e., the outlet was located at the base of the column) (See
Figure 1). A mixture of pine chips and sugar-cane mulch was added as a carbon source into the
submerged sections (transition and gravel layer) of SZ columns to assist with denitrification as
specified by FAWB (2009). The biofilter columns were 800mm in height and contained four main
sections (see Figure 1). The upper 200mm consisted of a ponding zone constructed from perspex to
allow sunlight to reach the plant and allow the accurate measurement of the ponding depth in the
column. The rest of the column was made of a PVC pipe and designed in a similar manner to that of
field-scale biofilters: 300mm filter media, 200 mm transition layer, and 100 mm drainage layer
(FAWB, 2009). The inside of the PVC pipes were sand-papered to reduce any preferential flow
down the sides of the column. Additionally, ten control columns (unvegetated) were constructed;
five to be subject to WA climate conditions and five to be subject to Victorian conditions (see
details of dosing below).
Table 1: Plant species chosen for this study. (L) - Lawn Grass, (G) - Grasses, (S) - Sedges, (R) -Rushes, (SH) - Shrubs
VIC Plants
WA Plants
Soft Leaf Buffalo (LG)
Poa labillardieri (G)
Poa sieberiana (G)
Carex appressa (S)
Veletene (LG)
Sporobolus virginicus (G)
Austrodanthonia caepitosa (G)
Poa poiformis (G)
Cyperus gymnocaulos (R)
Juncus kraussii (R)
Gahnia trifida (S)
Carex tereticaulis (S)
Melaleuca incana (SH)
Astartea scorpia (SH)
Hypocalymma augustifolium (SH)
200 mm
Ponding zone (clear
perspex)
300
Loamy sand filter media
(Ks = 180 mm/hr)
200
Sand transition layer (SZ
with carbon addition)
100
Gahnia sieberiana (S)
Juncus pallidus (R)
Dianella revoluta (S)
Dianella tasmanica (S)
Allocasurina littoralis (SH)
Leptospermum continentale (SH)
Hakea laurina (SH)
Gravel drainage layer SZ
with carbon addition)
SZ outlet
Normal
outlet
Figure 1: Column configuration. A “Normal outlet” situated at the base of the column is used for Non-Submerged (NS)
columns, while “SZ outlet” is used to create a Submerged-Zone (SZ).
Stormwater Dosing
A semi-natural stormwater was used for dosing the columns as this offered the best compromise
between providing real stormwater quality and consistent concentrations for experimental control.
The semi-natural stormwater was manufactured by mixing a concentrated “slurry” with
dechlorinated tap water and chemicals to obtain target sediment and pollutant concentrations which
were consistent with Australian urban stormwater quality as specified by Duncan (1999) and Taylor
et al. (2005). The concentrated “slurry” was formed by passing sediment collected from a nearby
stormwater pond through a 300 µm sieve. The columns were dosed twice weekly with the seminatural stormwater from 17th of December 2010 to simulate a ‘wet period’. Based on climate
patterns local to the plant species and assuming a biofilter sized to 2.5% of its catchment area,
dosing volumes of 3.7L and 4.2L were calculated for Victorian and WA columns, respectively.
Infiltration measurements
Infiltration measurements were conducted every three months to determine the influence of
vegetation on the evolution of hydraulic conductivity over time. The infiltration rate was calculated
by pre-soaking the columns (approximately 24 hours before commencement of the experiment) and
measuring the drop in water level every two minutes for at least one hour. For extremely slow
draining columns, measurements were taken every two minutes for the first hour, and then
randomly throughout the day with the time noted so that the infiltration rate could be calculated.
Infiltration measurements were also taken the following day for columns that were still draining. It
is important to note that the measurements do not necessarily represent a saturated hydraulic
conductivity, but the infiltration rate, measured using pre-wetted conditions typical of a biofilter in
field practice. Ensuring saturation of the columns (which could have taken longer than 48 hours)
was not considered desirable, given the likely artificial impacts on treatment performance.
This paper presents results from the infiltration measurements conducted on the 21st and 22nd of
June 2011 for NS columns and 5th and 6th of July 2011 for SZ columns, but data on the temporal
evolution of infiltration rate over the experimental period to date (December 2010 to December
2011) are also presented.
Stormwater Sampling
To determine the influence of vegetation on pollutant removal, inflow and outflow water quality
samples were collected on a monthly basis. A sub-sample was collected from the inflow tank,
while the whole outflow volume of the columns were collected into 5L bottles then sub-sampled.
All water quality samples were analysed by a NATA-certified laboratory for Total Nitrogen (TN),
Total Dissolved Nitrogen (TDN), ammonia (NH3), and oxidised nitrogen (NOx). Additionally,
Dissolved Organic Nitrogen (DON) was calculated by subtracting the sum of NH3 and NOx from
TDN and Particulate Organic Nitrogen (PON) was calculated as the difference between TN and
TDN. This paper only examines the results of the June 2011 dosing run..
Data analysis
To determine whether vegetation significantly influenced the data collected (i.e infiltration rates and
effluent N concentrations), an independant t-test was carried out between soil-only and vegetated
columns for both NS and SZ designs separately. Levene’s test was used to assess the equality of
variances of the data sets. In instances where homogeneity of variance was not assumed, Welch’s ttest was employed. One-way ANOVA was used to further investigate the influence of plant types
(Lawn Grass, Grass, Sedge, Rush, and Shrubs) and plant species. To compare vegetated types and
species against control columns, a post-hoc multi-comparison test was employed (Tukey or GamesHowell test depending on the homogeneity of data). Additionally, Pearson’s correlation determined
any associations between infiltration rate and nitrogen species. SPSS v.19® was used for all
analysis. A critical value of p= 0.05 was considered for hypothesis tests. Finally, Cube-root
transformation was applied to infiltration data in order to meet normality assumptions.
RESULTS AND DISCUSSION
Infiltration Rate
The presence of vegetation appears to slow the infiltration rate when compared to soil-only
columns. The mean infiltration rates for soil-only columns were 70 mm/hr and 68 mm/hr for NS
and SZ designs respectively, while the mean infiltration rates for vegetated columns were 49 mm/hr
and 35 mm/hr (for NS and SZ designs respectively). Particularly slow draining plant species for NS
and SZ columns (respectively) included J. palllidus (µ= 36 mm/hr and 11 mm/hr), M. incana (µ=
16 mm/hr and 10 mm/hr) and Velvetene lawn grass (µ= 4 mm/hr and 13mm/hr). It is hypothesised
that the root volume of these species may be a factor causing the drainage rates to be slower than
other columns; this will be investigated further in a final harvest which will examine vegetation
characteristics.
Vegetation type has a significant effect on infiltration rates (Figure 2). Lawn grass (p <0.05), rushes
(p = 0.001) and shrubs (p<0.05) were significantly slower draining than soil-only control columns
for NS column designs. For SZ columns, all plant types observed significantly slower infiltration
rates than soil-only (p<0.05). Lawn grasses had the lowest mean infiltration rate of 18 mm/hr and
19 mm/hr for NS columns and SZ columns respectively, compared to 70 mm/hr and 68 mm/hr for
soil-only NS and SZ columns, respectively. The lawn grass covers the entire surface area of the
column thus its root may reduce flow pathways more so than other plant types.
Figure 2: Mean, maximum and minimum bar graph comparing infiltration rates of various plant types: Lawn grass (n=
10), Grass (n=25), Sedge (n=30), Rush (n=15), Shrub (n=30) and Soil-Only controls (n=10) for each NS and SZ column
design.
It thus appears that in the early stages of the experiment, vegetation has a negative influence on
infiltration rate, but this may be an artefact of the small column size and may also be a temporary
effect. These results were taken in June 2011 early in the study and during winter when vegetation
is mostly dormant. During more active seasons, root growth disturbs the soil in the vicinity of the
roots, thereby causing movement in the soil substrate. The movement of soils may enlarge existing
macropores or create new ones for water flow (Angers and Caron, 1998). Several studies have
observed initially low infiltration rates of soils under plants which progressively increase with time
(Lewis et al., 2008, Meek et al., 1992). The hydraulic conductivity of vegetated field biofilters
studied by Lewis et al. (2008) initially decreased to 15mm/hr in winter, however improved over
time. Figure 3 suggests that similar behaviour is occurring with the columns; it is thus possible that
the vegetated systems will end up with the highest infiltration rates, at least for some vegetation
types. Ongoing experiments will help to answer this question.
Figure 3: Temporal evolution of infiltration rate over the duration of the experiment to date, showing the increase in
variability of infiltration over time for soil-only (n=10) and vegetated systems (n=10).
Stormwater treatment
Vegetated columns significantly reduced the outflow concentrations of TN, TDN and NOx from
their inflow concentrations (µ = 2.27 TN mg/L, 1.89 TDN mg/L, 0.97 NOx mg/L). Furthermore, the
presence of vegetation significantly reduced the outflow concentrations of TN, TDN and NOx
compared to soil-only controls regardless of plant type (see Figure 4). The mean TN outflow
concentrations of soil-only columns were 1.71 mg/L and 1.35 mg/L (NS and SZ columns
respectively). On the other hand, vegetated columns had a mean TN outflow concentration of 0.44
mg/L and 0.26 mg/L (NS and SZ columns respectively). SZ columns further enhanced pollutant
removal of TN, TDN and NOx.
Figure 4: Mean, maximum and minimum bar graph comparing inflow TN concentrations (n=15) to various plant types:
Lawn grass (n = 10), Grass (n=25), Sedge (n=30), Rush (n=15), Shrub (n=30) and Soil-Only controls (n=10) for each
NS and SZ column design
Overall, NH3 concentrations in the effluent were extremely low compared to the mean inflow
concentration of 0.39 mg/L. The mean concentrations of NH3 for vegetated columns were 0.003
mg/L and 0.019 mg/L for NS and SZ respectively, which was not significantly different from the
mean concentration of soil-only columns; 0.004 mg/L and 0.021 mg/L for NS and SZ respectively.
Zinger et al (2007) attributes the addition of a carbon source, which promotes ammonification and
possibly dissimilatory nitrate reduction to ammonium (DNRA), to the increased outflow of NH3 in
the SZ columns compared to NS columns. Given that the outflow concentrations of NH3, DON and
PON were low for all columns (soil-only and vegetated) compared to inflow concentrations, the
effect of vegetation is less important than has been shown in previous studies (e.g. Bratieres et al.,
2008).
Interestingly, soil-only columns for both NS and SZ designs leached NOx (µ = 1.58 mg/L and 1.14
mg/L respectively) compared to the inflow NOx concentration of 0.97 mg/L (See Figure 5). Greater
NOx removal from vegetated as compared to unvegetated systems has also been observed in other
studies (Henderson et al., 2007, Denman et al., 2007). These results suggest nitrification is taking
place, but that there is a lack of denitrification occurring to complete the nitrogen removal process.
On the other hand, plant root exudates from vegetated columns may provide a carbon supply to
support heterotrophic denitrifying bacteria, leading to effective NOx transformation to gaseous end
products. Plants may also be responsible for the direct uptake of some of the NOx, along with
facilitating microbial uptake, particularly around the rhizosphere. Given that TDN (which consists
of DON, NH3, and NOx) makes up 80% of TN in typical urban stormwater (Taylor et al., 2005), any
removal of dissolved nitrogen offered by vegetation is crucial to overall TN removal, hence
amplifying the importance of vegetation in biofilters.
Figure 5: Mean, maximum and minimum bar graph comparing inflow NOx concentrations (n=15) to various plant
types: Lawn grass (n = 10), Grass (n=25), Sedge (n=30), Rush (n=15), Shrub (n=30) and Soil-Only controls (n=10) for
each NS and SZ column design
Infiltration rate and treatment performance
As expected, the treatment ability of the columns is related to their infiltration rate. However, this
was only noticed for vegetated columns; there was no correlation between infiltration rate and the
concentration of any nitrogen species for soil-only control columns (n= 20). This further highlights
the effect of vegetation on both infiltration rate and treatment performance. Outflow concentrations
of TN (p<0.001), TDN (p<0.001), NOx (p<0.001) and PON (p<0.05) were all positively correlated
with infiltration rate for vegetated columns. In other words, slower draining columns provided a
longer detention time for treatment processes to occur, and resulted in low pollutant outflow
concentrations. NH3 effluent concentrations weakly correlated with the infiltration rates for columns
with shrubs (n= 60, R= 0.026) and sedges (n= 60, R= -0.263) only.
It is difficult to tell whether improved treatment performance by columns with a SZ is the primary
result of anoxic conditions within the saturated zone, which promote denitrification, or the
increased retention time of effluent within these columns, providing greater opportunity for biotic
uptake or transformation. Further studies are required to better understand nitrogen pathways within
biofilters, and this could include the use of isotopes to identify key processes and storages.
IMPLICATIONS FOR BIOFILTER DESIGN
The presence of vegetation in biofilters influences both infiltration rate and treatment performance.
At least in the early stages of this study, vegetation has reduced the infiltration rate, but in turn this
decreased outflow concentrations of nitrogen, a pollutant which is typically difficult to consistently
remove. In part, this may be because increased detention time simply gives more time for biological
transformation and uptake processes to take place. Designers should thus consider making larger
biofilters with slower-draining media, because these systems are likely to have improved overall
performance.
Ideally, vegetation selection for biofilters should be a balance of infiltration rates and treatment
performance. Although biofilters planted with lawn grasses provide easy maintenance, the
preliminary results of this study demonstrate that the nature of their design (that is, lawn grasses
covering the entire surface area of the biofilter) may encounter some drainage issues. Nevertheless,
the results are preliminary and lawn grasses should not be ruled out entirely, especially if their
infiltration rates improve in the future. Vegetation is essential for nitrogen removal, and from this
study, it appears that provided the media is selected carefully so that it does not contain excessive
nutrients (FAWB, 2009), many plant species can be effective in ensuring high levels of nitrogen
removal. Consequently, there is a relatively large range of plant species to choose from which will
still achieve effective nutrient removal.
Furthermore, vegetation selection should consider the ability to survive and contribute to biofilter
performance under stressful conditions such as drought. Future work will investigate the effect of
dry periods on vegetation, and overall biofilter performance.
ACKNOWLEDGEMENT
This project was funded by an ARC Linkage Project (LP0990153) with partner funding
from Melbourne Water and the WA Department of Water. We would like to thank J. Read, R.
Williamson, F. Winston, T. Hines and K. Browne for their contribution to this project.
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