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A numerical modelling on the effectiveness of
bioretention system for dengue control
Zhen Jie Choong1, Cha Yao Tan1*, Chow Hock Lim1, Sin Poh Lim1, Anurita Selvarajoo1
and Fang Yenn Teo1†
1University of Nottingham Malaysia, Jalan Broga, 43500, Selangor, Malaysia.
Abstract. Conventional urban drainage structures that store water over time
are habitat for the mosquito larvae. Appropriate stormwater management
practices can help in preventing the breeding of the mosquito larvae. Thus,
a study was conducted to evaluate the performance of a proposed
bioretention system in controlling dengue at the campus university in
Semenyih, Malaysia. The XP Stormwater Management Model (XPSWMM)
was applied for the numerical analysis and modelling in this study. A series
of simulations were carried out for the ARI of 2, 5, and 10 years to evaluate
the performance under the two scenarios of conventional drainage system
and bioretention system, taking into considerations the maximum water
depth (stages), inflow volume from runoff, and pollutant load reduction from
the sub-catchments to control the breeding of aedes mosquitoes. The
simulated results indicated that the bioretention system is capable of
reducing the maximum water depth (stages) of the sub-catchments to up to
85% as compared to the conventional drainage system. In addition, the
reduction of the inflow volume from runoff ranges from 0.3% to 0.5% and
the pollutant loads reduced by approximately 100%. The reduction in water
depth and inflow volume will result in mitigating the risk of water stagnancy
within all the sub-catchments of the study area. The simulated results
demonstrated that bioretention system could be used effectively to control
the breeding of mosquitoes. Hence, the findings obtained in this study can
assist the decision makers of the university in the adoption of bioretention
system to control dengue within the campus.
1 Introduction
Since the first dengue outbreak in the year of 1973, a total of cases of 969 and 54 deaths have
been reported in Malaysia [1]. Since then, Malaysia has been struck badly by the epidemic,
with the rising cases of infection, especially among the urban areas. From Fig. 1, it clearly
showed that the number of dengue cases has been rising sharply since 2011. Notably, the
number of cases per annum has reached a new record with a total of 130,101 cases reported
in 2019, and significant spike is observed in the rate of incidences, at a staggering rate of
390.4 from the year of 2018 [2].
* Corresponding author 1: keey5tcy@nottingham.edu.my
† Corresponding author 2: fangyenn.teo@nottingham.edu.my
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© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
Fig.1. Number of cases and the rates from dengue fever 2000-2019 [2]
The rapid growth of urbanisation has increased the application of artificial impermeable
surfaces. Hence, increasing the surface runoff significantly at the expense of infiltration and
resulting in more frequent flooding. Moreover, the pollutants from the surface runoff
ultimately enter and pollute the natural watercourses. In order to mitigate flooding,
conventional type of drainage infrastructure has often been provided. However, in many
cases, the drainage structures that store water over time can create a natural habitat for the
birth of mosquito larvae.
Appropriate stormwater management that facilitates the effective storage of flood water
plays a key role in preventing the breeding of the mosquito larvae, hence addressing the issue
of dengue control at the urban drainage system level. This study requires the fundamental
understanding of the relationship between Sustainable Urban Drainage System (SUDS) and
dengue control. SUDS uses a natural approach that mimics the nature’s ways in storing and
allowing the surface runoff to be pre-treated or infiltrated into the groundwater. Hence, SUDS
not only help to reduce runoff quantity, but also treating the pollutants from the runoff. The
application of bioretention system which is one of the SUDS techniques was chosen for this
study.
This study has made use of numerical modelling to compare the performance between
bioretention system and the conventional drainage system in controlling mosquitoes
breeding.
The objectives of this study are:
1) To review and study the fundamental understanding of the relationship between
bioretention system and mosquito breeding control,
2) To investigate and analyze the stormwater quality and quantity performance for
conventional drainage system and bioretention system, and to compare their
effectiveness in controlling mosquitoes breeding, and
3) To model the water stages in the bioretention system to control mosquitoes
breeding.
2 Study area and methodology
The study area is situated within the University of Nottingham Malaysia Campus, Semenyih
in the state of Selangor in Malaysia. The study area covers a total of 1.68 hectares of different
land-uses such as sport fields, institutional complex, and other infrastructure.
Firstly, the main factors of dengue outbreak will be extracted from the research papers
reviewed. Then, the stormwater quality and quantity aspects of the urban drainage system
that contributes to the transmissions of dengue virus will be classified. Subsequently, the
suitability of each SUDS techniques will be studied based on the Stormwater Management
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Manual for Malaysia 2nd Edition (MSMA 2nd Edition) [3] and other scientific papers. Based
on the literature reviewed, bioretention system are chosen to be analysed against the
conventional urban drainage system.
Secondly, the two scenarios, conventional and SUDS of bioretention system are
modelled at the study area by using XPSWMM software to evaluate their effectiveness in
controlling dengue. Moreover, the input parameters for the base scenario (existing drainage
system) will be based on the field observation conducted at the study area, as the sizing and
features of the Bioretention system will be designed according to the Stormwater
Management Manual for Malaysia [3]. Ultimately, this study aims to reduce the stages in the
hydraulics structure to break the lifecycle of Ae. Aegypti.
The bioretention system is selected to provide runoff volume reduction as the stagnant
water in the catchments and manholes are the main habitats for larval production in urban
areas. Besides, the water quality treatment of the design also has a direct impact in reducing
the larval habitats, as the sediments attached with other pollutants can create an organic
habitat for the larval. Therefore, the models are comprised of stormwater quantity and quality
measures to determine which system is more effective in controlling dengue.
Where Sustainable Urban Drainage System (SUDS) uses a natural approach that mimics
the nature’s ways in storing and allowing the surface runoff to be pre-treated or infiltrated
into the groundwater. Hence, SUDS not only reduces the runoff quantity, but also treating
the pollutants from the runoff. Hence, stormwater management plays a key role in avoiding
the mosquito larval habitats by managing the water storage in the drainage systems.
Furthermore, a field observation has been carried out to identify the location of the
manholes and the sewers network connecting to the nearby watercourse in Campus.
Moreover, Google Earth Pro is used to obtain the Latitude coordinate, Longitude coordinate
and the elevation details of each manhole.
XP Storm Water Management Model (XPSWMM) is a numerical modelling software
that is capable of simulating rainfall-runoff processes and the hydraulic performance of
drainage system. Moreover, it can be utilized to analyze the pollutant reduction. In this study,
one-dimensional stormwater model is simulated with the data collected in field observation.
The XPSWMM has been selected to compare the runoff reduction and water quality
treatment to mitigate the growth of dengue mosquitoes in two scenarios as follows:
1. Base scenario: Model the existing stormwater system in the study area.
2. Sustainable urban drainage scenario: Model the existing stormwater system with
Bioretention system in the study area.
To simulate a stormwater model, the input parameters include rainfall data, hydrological
components (sub-catchments, sewer system network map, etc.) and run time controls (time
step, simulation start and ending time).
For the rainfall data, the rainfall event is obtained from the historical rainfall data based
in Kuala Lumpur, Malaysia. The design rainfall intensity for the respective ARI was obtained
from Intensity-Duration-Frequency (IDF) curve from site 3117070 at Department of
Irrigation and Drainage Malaysia (DID) Ampang. Therefore, the rainfall intensity used for 2,
5, 10 years ARI storm are 65.9, 78.9, and 87.4 mm/hour respectively which according to
MSMA 2nd Edition [3]. The storm duration is set to 60 minutes.
Total Suspended Solids (TSS) and Total Phosphorous (TP) were selected to be used to
simulate the stormwater quality model. Furthermore, the water quality data are assigned into
each sub-catchment based on the land uses.
2.1 Model setup for conventional system
Firstly, the data regarding the x-y coordinates and elevations of each manhole on the existing
stormwater system are entered as the input data of the model. The typical manhole height of
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1.57 m is used. Then followed by the sewer pipes connecting to each manhole with the
respective slope, length, and diameter. The surface roughness of 0.0013 is used for the pipe.
Moreover, the shape for all the sewer pipe is circular, except for the trapezoidal channel that
connects to the outlet.
The catchment is distributed into multiple sub-catchments according to the types of land
use as shown in Fig. 2. Then, the imperviousness and area of each sub catchments are entered
as the input data. The Runoff dispersing technique is used to model multiple bioretention in
the larger drainage areas in the study area. Furthermore, the rational method is applied in the
surface routing of the stormwater model.
Fig. 2. The setup of the model in XPSWMM.
The conventional drainage system is simulated with and without the bioretention system. The
simulation period is 24 hours. The catchments are linked to the nearby manholes in the study
area. The catchments are then categorised based on the respective land uses as shown in Table
1. Moreover, the higher runoff coefficient indicates larger runoff generated from the
precipitation, due to the larger area of impervious surface with lower permeability and vice
versa.
Table 1. Land-uses and runoff coefficients for each sub-catchment
Moreover, two types of pollutants namely, Total Suspended Solids (TSS) and Total
Phosphorous (TP) are simulated to assess the stormwater quality of the model. Furthermore,
the amount of the pollutants (kg) is determined by the land use of each sub-catchments. For
instance, the sub-catchments with higher runoff coefficient generates more pollutants than
Sub-
catchment Area (ha) Runoff Coefficient
(Pervious) Land-use Percentage of
land-use
S1 0.154 0.30 Grasslan
d
50
S3 0.219 0.30 Grasslan
d
50
S4 0.117 0.90 Pave
d
80
S8 0.205 0.60 Grasslan
d
25
S9 0.584 0.60 Pave
d
25
S10 0.311 0.30 Grasslan
d
80
S14 0.325 0.30 Grasslan
d
80
S13 0.245 0.30 Grasslan
d
80
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the lower runoff coefficient. This can be justified by the impact of high imperviousness that
restrict infiltration to occur, hence more runoff that carries the pollutants are generated.
2.2 Model setup for SUDS
The bioretention system is designed according to the specifications set in the MSMA 2nd
Edition [3] as shown in Table 2. For instance, the size of 6m × 3m (length × width) is adopted
for a single unit of bioretention system in the XPSWMM model. The maximum emptying
time of less than 24 hours is used to avoid larva production. Moreover, the ponding depth of
200 mm is used in the bioretention system. The groundwater table is assumed to be a
minimum of 0.60 m below the drainage layer of the bioretention system.
Table 2. Physical specification and sizing of bio-retention system. [3]
The bioretention system are modelled in three stages. The first stage is the storage
process, where the specifications of the bioretention system are input. This will prompt the
model to use this feature as a storage unit for the runoff generated from the rainfall. In the
storage unit dialog, the pollutants removal equation is entered to specify the pollutants
removal parameters. Followed by the outflow process, where the runoff and stored in the
bioretention system will flow out of the system. Lastly, the residual pollutant that trapped by
the system are disposed and treated before discharging to the sub-catchments.
3 Results and discussion
3.1 Stormwater quantity
Sub-catchment S4 has been discussed specifically because it consisted of a higher runoff
coefficient as the land use are predominantly impervious pavements. The below Fig. 3 (a-c)
depicts the stage (m) against time plot for sub-catchment S4. In the ARI of 2 years, the
maximum stage has been reduced significantly from 76.08 m to 75.50 m when bioretention
system is adopted. Moreover, the reduction of final stage in sub-catchment has been the most
effective during ARI of 2 years. The plots demonstrated that as the rainfall intensity increases,
the effectiveness of final stage reduction decreases. Moreover, the final stage in the
bioretention system during ARI of 5 years is higher than in the conventional system. This
occurs when the rainfall intensities are larger than the rate of infiltration of the native soil,
which would result in the higher stage in the sub-catchment.
Parameter Specification
Minimum Size 3m wide by 6m long
Length and Width ratio 2:1
Maximum Emptying Time Less than 24 hours
Permeability of Planting Bed More than 13 mm/hr
Ponding Depth 150 mm- 300 mm
Depth of Groundwater Table (below
drainage layer)
Minimum of 0.60 m
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3(a)
3(b)
3(c)
Fig. 3. Stage (m) against time plot in S4 for (a) ARI of 2 years, (b) ARI of 5 years, (c) ARI of 10 years.
3.2 Stormwater quality
The Fig. 4 (a-c) below depicts the Total Suspended Solids (TSS) load (kg) over time plot for
the sub-catchments. The figure demonstrated that the TSS load increases with the rainfall
intensities. This can be explained by the larger runoff volume constitutes more TSS pollutants
generated from the urban area. This is only valid until a point where the increase in rainfall
intensities will result in ‘flushing’ effect of the pollutant hence reducing the pollutants in the
sub-catchments.
Moreover, the percentage reduction of the TSS load by the bioretention system is
approximately 100 percent. The result showed that the efficiency of TSS reduction by the
bioretention system increases with rainfall intensity.
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4(a)
4(b)
4(c)
Fig. 4. Load against time plot for total suspended solids in S4 for (a) ARI of 2 years, (b) ARI of 5 years,
and (c) ARI of 10 years.
Below is Fig. 5. (a-c) showing the Total Phosphorus (TP) load (kg) against time plot for
the sub-catchments. The trend of the plot is similar to that of in the case of TSS, but in a
lower magnitude. Hence, small amount TP load are required to be treated by the bioretention
system. Moreover, the results demonstrated that the TP reduction increases with the rainfall
intensities. The bioretention system also showed that it can reduce the TP completely.
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5(a)
5(b)
5(c)
Fig. 5. Load (kg) against time plot for total phosphorus in S4 for (a) ARI of 2 years. (b) ARI of 5 years
and (c) ARI of 10 years.
3.3 Stormwater quantity in bioretention system
Moreover, the result demonstrated that with the implementation of bioretention system, the
maximum water depth in the sub-catchment have been significantly reduced. However, the
percentage reduction for the maximum water depth ranged from 7% to 85%.
Table 3 below shows the results extracted from the XPSWMM model for both scenarios.
As the ARIs increases, the inflow volume from runoff increases with the rainfall intensities.
From the Table 3, the inflow volume from runoff reduction ranged only from 0.3% to 0.5%.
Moreover, the reduction of inflow volume from runoff increases negligibly from ARI of 2
years to 5 years. The increasing percentage reduction for volume inflow with higher ARIs
are not valid to the findings by Sun et. al., 2019 [4], which stated that the higher in runoff
generated from rainfall, the lower the reduction of volume inflow by the bioretention system.
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Table 3. Percentage reduction for volume of inflow and maximum stage results from XPSWMM
model for different ARI storm.
3.4 Stormwater quality in bioretention system
The result demonstrated that the TSS constitutes a bigger part of the pollutants in the runoff
than TP. This can indicate that the TSS settles more easily than TP, which can clog the sub-
catchments. Therefore, creating a natural habitat that encourages the production of mosquito
larvae.
Even if the plots showed that the efficiency of pollutants reduction by the bioretention
system increased with the rainfall intensity. The bioretention system may not have
contributed entirely for pollutants reduction, as the increasing rainfall can create a ‘flushing’
effect that lead to vigorous draining of the pollutants under a short period of time, without
settling at the base of the sub-catchments.
ARI (year） Manhole Percentage reduction
for volume of inflow
Percentage
reduction for the
maximum stage
2
S1 0.28 12
S3 0.43 45
S4 0.43 81
S8 0.43 83
S9 0.43 74
S10 0.43 33
S13 0.43 70
S14 0.43 74
5
S1 0.29 7
S3 0.48 70
S4 0.48 78
S8 0.48 85
S9 0.48 74
S10 0.48 19
S13 0.48 71
S14 0.48 66
10
S1 0.29 51
S3 0.49 76
S4 0.49 80
S8 0.49 85
S9 0.49 73
S10 0.49 17
S13 0.49 72
S14 0.49 64
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4 Conclusion
In conclusion, the simulated results demonstrated that the bioretention system are capable of
reducing the maximum stage up to 85% of the sub-catchment in the convention drainage
system. The maximum stage in the sub-catchment is one of the factors for dengue outbreak.
Moreover, the reduction of up to 0.49% of inflow volume by the bioretention system showed
that, the infiltration of the native soils is important in assessing the performance of the system.
Furthermore, the results have demonstrated that the percentage reduction of the
maximum flow increases by 0.05% with the Average Recurrence Interval (ARI). Hence, the
results do not valid with the findings by Sun et. al., 2019 [4], which stated that the higher in
runoff generated from rainfall, the lower the reduction of volume inflow by the bioretention
system. Hence, the results indicated the high ARI affected the accuracy of the results.
The bioretention system have proved that it can control dengue by reducing the
maximum stage efficiently in each sub-catchment. With the maximum stage been greatly
reduced, the likelihood of mosquito production would be reduced. The performance of the
bioretention system in maximum stage reduction is highly dependent to the runoff coefficient
and land use. As lower runoff coefficients can improve the efficiency of the bioretention
system in maximum stage reduction.
References
1. H. G. Wallace, T. W. Lim, A. Rudnick, A. B. Knudsen, W. H. Cheong, V. Chew,
Southeast Asian J Trop Med Public Health, 11(1), 1-13 (1980)
2. iDengue Versi 3.0, Dengue Statistic, Disease Control Division, Ministry of Health
Malaysia (Accessed 13 September 2021)
3. Department of Irrigation and Drainage Malaysia, Urban Stormwater Management
Manual for Malaysia 2nd edition (MSMA 2nd edition), Department of Irrigation and
Drainage Malaysia, Kuala Lumpur (2012)
4. Y. Sun, C. Pomeroy, Q. Li, C. Xu, Water Sci. Eng. 12(2), 98-107 (2019)
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