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Environmental Earth Sciences ISSN 1866-6280Volume 72Number 10 Environ Earth Sci (2014) 72:4047-4058DOI 10.1007/s12665-014-3294-6

Sizing first flush pollutant loading ofstormwater runoff in tropical urbancatchments

Ming Fai Chow & Zulkifli Yusop

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ORIGINAL ARTICLE

Sizing first flush pollutant loading of stormwater runoff in tropicalurban catchments

Ming Fai Chow • Zulkifli Yusop

Received: 9 May 2013 / Accepted: 16 April 2014 / Published online: 5 May 2014

� Springer-Verlag Berlin Heidelberg 2014

Abstract This study aimed at investigating the first flush

phenomenon from residential, commercial and industrial

catchments. Stormwater was grab sampled and the flow

rate was measured during 52 storm events. The dimen-

sionless cumulative pollutant mass and runoff volume were

used to determine the runoff volume needed to transport 50

and 80 % of total pollutant mass. Almost all the constitu-

ents did not satisfy this first flush definition except for total

suspended solids (TSS) in the commercial catchment. The

averages first runoff volume required to remove 50 and

80 % of the total pollutant mass were 37 and 67, 35 and 65,

and 36 and 64 % for the residential, commercial and

industrial catchments, respectively. It seemed that less

runoff is required to transport the same amount of pollutant

loadings in tropical urban catchments than in temperate

regions. BOD, COD, NH3-N, SRP and TP consistently

showed strong first flush effects in all catchments. The first

flush strengths of TSS, BOD, COD, NH3-N and TP in the

commercial catchment were strongly correlated with total

rainfall, rainfall duration, max 5 min intensity, runoff

volume and peak flow, but not with antecedent dry days.

Management of the first 10 mm runoff depth would be able

to capture about half of the total pollutant mass in storm-

water runoff that would otherwise goes to drains.

Keywords First flush � Pollutant loading � Stormwater �Mass-based first flush

Introduction

First flush is defined as a disproportionately high delivery

of either concentration or mass of a stormwater pollutant

during the early part of a storm runoff event (Sansalone and

Cristina 2004). First flush of various stormwater pollutants

has been studied in several countries, for example in Italy

(Gnecco et al. 2006), Korea (Kim et al. 2007), Los

Angeles, USA (Kang et al. 2008), Japan (Lee et al. 2005)

and Australia (McCarthy 2009). In most studies, the first

flush effect of stormwater pollutant was assessed qualita-

tively by using the dimensionless cumulative pollutant load

vs. cumulative runoff volume curves (e.g., Deletic and

Maksimovic 1998; Lee and Bang 2000; Sansalone and

Cristina 2004; McCarthy 2009; Chow et al. 2011). How-

ever, the terms ‘‘disproportionately high delivery’’ and

‘‘early part of a storm’’ are not defined precisely. There-

fore, a more quantitative definition of first flush effect has

been proposed based on a threshold ratio of percentage of

cumulative pollutant mass over percentage of cumulative

runoff volume (%M/%V). For example, 40–60/25 (Vorre-

iter and Hickey 1994), 40/20 (Deletic 1998), 50/25

(Wanielista and Yousef 1993), 80/30 (Bertrand-Krajewski

et al. 1998) and 80/20 (Stahre and Urbonas 1990) of

M/V ratios were applied. However, the first flush definitions

were proposed based on studies in temperate climate. On

the other hand, first flush phenomenon is complex and site

M. F. Chow

Center for Sustainable Technology and Environment,

College of Engineering, Universiti Tenaga Nasional (UNITEN),

Jalan IKRAM-UNITEN, 43000 Kajang, Selangor, Malaysia

M. F. Chow (&)

Research Center for Environmental Changes (RCEC),

Academia Sinica, 128 Academia Road, Section 2,

Nankang, Taipei 115, Taiwan

e-mail: mingfai1983@yahoo.com

Z. Yusop

Institute of Environmental and Water Resources Management,

Universiti Teknologi Malaysia (UTM), 81310 Skudai,

Johor Darul Ta’zim, Malaysia

123

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DOI 10.1007/s12665-014-3294-6

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specific (Taebi and Droste 2004; Kim et al. 2005; Deng

et al. 2005), thus could not be precisely defined by using a

universal set of climate, rainfall and runoff characteristics,

or universal types of regression curves (Bertrand-Krajew-

ski et al. 1998).

Various combinations of factors may be responsible for

the occurrence of first flush events. A strong first flush

phenomenon is usually more prevalent in small catchments

with high imperviousness (Lee and Bang 2000; Ma et al.

2002; Lee et al. 2002; Sansalone and Cristina 2004; Li

et al. 2007). Other factors that govern first flush are max-

imum rainfall intensity (Gupta and Saul 1996; Deletic

1998; Taebi and Droste 2004; Huang et al. 2007; Li et al.

2007), antecedent dry day (Gupta and Saul 1996; Deletic

and Maksimovic 1998; Soller et al. 2005; Li et al. 2007;

Huang et al. 2007), and rainfall duration (Gupta and Saul

1996; Taebi and Droste 2004). However, some studies

found no or weak correlation between first flush against

mean rainfall intensity and antecedent dry days (Saget et al.

1996; Deletic 1998; Lee et al. 2002; Han et al. 2006),

rainfall depth and duration (Deletic 1998) and catchment

characteristics like area, time of concentration, and average

slope (Saget et al. 1996; Lee et al. 2002). There are some

reasons for inconsistency of first flush, which include

insufficient stormwater sample, especially on the rising

limb of the hydrograph. Besides rapid rise in water level,

large variations in the concentration of constituents further

complicate the sampling exercise. Insufficient number of

sample is also common in the latter half of a storm event

because the recession time is much longer especially for a

large catchment. Consequently, many stormwater studies

failed to establish full assessment of first flush effect

because the pollutant’s peak concentration was missed

(Deletic 1998). Another reason for inconsistency in

reporting first flush phenomenon is due to differences in the

sampling protocol. As highlighted by Sansalone and Cri-

stina (2004), a widely spaced time interval of sample col-

lection across the hydrograph will not give an accurate

mass transport during the event. Unaccounted first flush

samples would usually lead to an underestimation of pol-

lutant loading rate.

Rainfall characteristic and land use could significantly

influence the stormwater quality and transport patterns of

constituents in urban catchment (Gan et al. 2008;

Munksgaard and Lottermoser 2010; Bian et al. 2011; Beck

and Birch 2012; Wang et al. 2013). Most of the related

studies have been carried out in developed countries under

temperate climate and there is still a lack of information for

urban catchments in tropical countries. This issue is

important because the rainfall pattern and distribution in

the tropics are different from those in the temperate. Short

and intense storms which are common in the tropics tend to

produce highly polluted runoff at the beginning of a storm

event. The site-specific characteristics of first flush suggest

that it is essential to have local data for assessing first flush

phenomenon. Therefore, the objectives of this study were:

(1) to determine the influence of first flush on the behavior

of stormwater constituents; (2) to determine the critical

amount of runoff volume for first flush; and (3) to deter-

mine the relationships between first flush strength and

storm characteristics. Quantitative characterization of first

flush at different land uses could provide necessary data to

evaluate the first flush phenomenon, relate impacts to best

management practices design and performance, and assess

impacts on water quality.

Methodology

Study sites and climate

Stormwaters were sampled at three different land uses,

namely residential, commercial and industrial catchments

in Johor, Malaysia (Fig. 1). Based on 62 years data from a

nearby (about 18 km) rainfall station, the mean annual

rainfall in this region was 2,417 mm, mean intensity was

2.7 mm/h and mean number of rainy days was 175 per

year. The median and mean dry days were 2 and 2.65,

respectively. On a yearly basis, the mean maximum con-

tinuous dry day was 15.56 and the median was 14 days.

All the study catchments are located within 3 km from

Universiti Teknologi Malaysia (UTM). This proximity has

provided enough time for our sampling teams to standby at

the study sites when a storm was expected to occur. The

residential catchment (C1) has an underground stormwater

drainage system, whereas the commercial (C2) and

industrial (C3) catchments have open channel system.

Inflow of groundwater into the drain is possible but this

was not quantified. None of these catchments have waste-

water treatment plant within it, thus the effect of land use

could be easily singled out. The detailed characteristics of

the catchments are summarized in Table 1.

Storm flow sampling

Rainfall in each catchment was measured by a HOBO tip-

ping bucket rain gauge (Model RG3) with resolution of

0.2 mm per tip. The rain gauges were maintained and ser-

viced weekly, during which data were retrieved using

‘‘BoxCar’’ software. During sampling of the first three

storm events, streamflow was measured using a current

meter (Model SWOFFER 2100). A staff gauge was also

installed to manually record the water level during sam-

pling. A stage-discharge rating curve was then developed

for each catchment to facilitate the conversion of water

level readings into flow rate for the subsequent samplings.

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Stormwaters were grab sampled using polyethylene bottles

at the catchment outlet. The sampling commenced when the

water level started to rise and ended when the falling limb of

the hydrograph began to flatten. Though laborious, manual

sampling allowed us to collect a larger volume of sample

(4.5 L) compared to automatic sampler. In addition, it could

minimize the risk of missing the peak concentration of

pollutants especially during the rapid water level rise (Lee

and Bang 2000). Manual grab sampling is also preferred

when the analysis include oil and grease (O&G) because it

could stick onto the inner surfaces of sampling tube, pump

and containers in the automatic sampler (US EPA 1992).

Between 8 and 15 samples were collected during each

storm. More samples were collected on the rising limb in

order to better assess the first flush occurrence. Depending

on the rapidity of the water level rise, the sampling intervals

were set from 1 to 10 min on the rising limb and 10–20 min

on the falling limb of the hydrographs. The detailed sam-

pling protocol was as recommended by Caltrans (2000).

Collected samples were analyzed for total suspended

solids (TSS), biochemical oxygen demand (BOD),

chemical oxygen demand (COD), O&G, nitrate-nitrogen

(NO3-N), nitrite-nitrogen (NO2-N), ammonia–nitrogen

(NH3-N), soluble reactive phosphorus (SRP), total phos-

phorus (TP) and zinc (Zn). The analytical procedures and

numbers as described in APHA et al. (2005) are: TSS

(2540D), BOD (5210B), COD (5220B), O&G (5520B),

NO3-N (4500-NO3 B), NO2-N (4500-NO2 B), NH3-N

(4500-NH3 F), soluble P (SP) (4500-P E), total P (TP)

(4500-P B) and Zn (3120 B).

Data analysis

Event mean concentrations

Pollutant concentrations were expressed as event mean

concentration (EMC) which is defined as the total con-

stituent mass discharged during an event divided by the

total runoff volume (Huber 1993), as follows:

Fig. 1 The locations of the study catchments

Table 1 Characteristics of the study catchments

Characteristics C1 C2 C3

Land use Residential Commercial Industrial

Catchment area (ha) 32.77 34.21 4.38

No. of houses/shops/

factories

473 597 25

Impervious area (%) 85 95 93

Average daily traffics

(cars/day)

7,811 33,286 3,148

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EMC =M

V¼R T

0QðtÞCðtÞdtR T

0QðtÞdt

ð1Þ

where, M is total pollutant mass (g), V is total runoff volume

(m3), Q(t) is time varying flow rate (m3/s), C(t) is time varying

pollutant concentration (g/m3), T is total duration of runoff (s).

Mass-based first flush (MBFF)

Mass-based first flush (MBFF) is a ratio of cumulative

mass to the cumulative flow volume (dimensionless) as

described by Ma et al. (2002). MBFF ratio for stormwater

constituent can be calculated by Eq. (2).

MBFFn ¼

R t

0CðtÞQðtÞdt

MR t

0QðtÞdt

V

ð2Þ

where t is lapsed flow time (min) corresponding to n %

total flow volume, C(t) is concentration of pollutant at time

t (mg/L), Q(t) is runoff flow rate at time t, M is total pol-

lutant mass (kg), V is total flow volume (m3). First flush

phenomenon occurs if MBFF is [1.0 (Ma et al. 2002).

First flush strength

The first flush strength was quantified by relating the

cumulative pollutant mass to cumulative runoff volume

using a power function as follows:

m tð Þ ¼ v tð Þ½ �b ð3Þ

where m(t) is normalized dimensionless cumulative mass;

v(t) is normalized dimensionless cumulative runoff volume,

and b is a power function. The power function was log

transformed to yield a linear regression as shown in Eq. (4):

ln m tð Þ ¼ b lnv tð Þ ð4Þ

where the b coefficient becomes the slope term from the

linear regression model. The y-intercept was fixed to zero

to ensure that 100 % of the pollutant load equals 100 % of

the runoff volume. A value of 1 corresponds to the 45�bisector line which represents uniform pollutant loading

throughout the event. A lower slope (smaller b value)

represents a stronger first flush effect, while a steeper slope

(larger b value) represents a weaker first flush effect. Slope

values above 1 indicate a dilution effect (Saget et al. 1996;

Bertrand-Krajewski et al. 1998).

Results and discussion

Storm characteristics

A total of 18 storm/rainfall events were sampled at the

residential catchment, and 17 events each at the

commercial and industrial catchments from March 2008 to

June 2009. The statistical summary of rainfall variables,

namely rainfall depth (Rd), duration (Rdur), hourly mean

intensity (I), max 5 min intensity (Imax5) and antecedent

dry days (ADD) are given in Table 2. These events rep-

resent frequent or common storms in the study area, having

return periods of \1 year and mostly fall within the

3 month intensity duration frequency (IDF) curve with

intensity of 33 mm/h (DID 2000). The stormflow durations

range from 0.18 to 2.5 h for the residential catchment,

0.23–4.85 h for the commercial catchment and 0.37–2.16 h

for the industrial catchment.

Event mean concentration (EMC)

The statistical summary of EMCs from 52 storm events is

presented in Table 3. The commercial catchment recorded

the highest means EMC for BOD, COD, TSS, SRP and TP.

The sources of high concentrations of BOD and COD in

the commercial catchment were most likely from wash-off

of food waste and sullage from restaurants. In total, there

are 54 restaurants operating in the commercial catchment.

According to Bannerman et al. (1993), streets are critical

source areas of stormwater pollutant in almost any land

use. On the other hand, parking lots are probably critical

source of solids in the commercial and industrial areas. The

commercial catchment has the highest traffic volume and

parking lots compared to the other two catchments.

Therefore, the high EMC value of TSS for the commercial

catchment is rather expected. Brezonik and Stadelmann

(2002) in Minnesota, USA, also found higher EMCs of

TSS and COD for commercial/industrial catchments than a

residential catchment. As for the industrial catchment, the

highest means EMC were observed for O&G, NO3-N,

NH3-N, NO2-N and Zn. Chang et al. (2004) in Texas found

a significant source of Zn from roof. Most factories in the

industrial catchment use galvanized iron roofs. The

industrial catchment also exhibits the highest EMC for

O&G compared to the other two catchments. The possible

sources of O&G were mainly from lubricant, used for

industrial machines and vehicles. In central Taiwan, Chong

et al. (2012) stated that pollutants from individual pre-

treatment plants could accumulate in storm drains before

being flushed by the subsequent storm.

First flush analysis

Hydrographs and pollutographs for each storm event were

plotted in order to assess first flush effect. Figure 2 shows

examples of pollutographs for NH3-N, TSS and O&G on

15 May 2009 at the residential catchment. The peak con-

centrations of TSS and NH3-N occurred before the peak

flow while for O&G, it coincided with the peak flow. More

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than half of the observed storms have peak concentrations

preceded the peak flow for all constituents. In fact TSS,

BOD, COD, NH3-N, SRP and TP consistently showed this

pattern for all events. However, the peak concentrations of

O&G, NO3-N, NO2-N, and Zn occasionally occurred after

the peak flow.

Mass-based first flush (MBFF) analysis was used to

qualitatively assess the first flush effect. Figure 3 shows the

box plots of MBFF for various constituents in all catch-

ments. Overall, BOD, COD, TSS, NH3-N, SRP and TP

have MBFF ratios [1.0, whereas O&G, NO3-N, NO2-N

and Zn have ratios B1.0. The MBFF median values for

Table 2 Rainfall

characteristics of the sampled

stormflow

Catchment Depth (Rd)

(mm)

Duration

(Rdur) (h)

Mean intensity

(I) (mm/h)

Max 5 min intensity

(Imax5) (mm/h)

Antecedent dry

day (ADD) (day)

Residential (n = 18)

Min/max 1.8/46.0 0.18/2.5 2.7/99.5 9.6/151.2 0.1/8.53

Median/mean 19.6/21.7 0.91/1.01 25.2/27.9 57.6/64.9 1.7/2.3

SD 15.4 0.62 24.8 45.9 2.2

Commercial (n = 17)

Min/max 2.0/107.4 0.23/4.85 2.7/53.7 4.8/146.4 0.03/16.53

Median/mean 11.0/30.2 1.12/1.22 22.1/23.0 50.4/65.6 3.74/2.12

SD 33.4 1.14 13.3 42.0 3.14

Industrial (n = 17)

Min/max 3.6/53.2 0.37/2.16 3.3/40.5 9.6/127.2 0.02/13.02

Median/mean 9.8/16.6 0.96/1.01 17.6/17.2 48.0/56.3 1.89/2.68

SD 14.4 0.51 10.3 31.6 3.33

Table 3 Statistical summary of

EMCs of various pollutants at

the residential, commercial and

industrial catchments

Variable EMC (mg/L)

Residential catchment Commercial catchment

n Min Max Mean Median SD n Min Max Mean Median SD

TSS 17 2 58 27 26 17 17 61 949 250 124 267

O&G 17 0.79 5.50 2.63 2.28 1.35 17 1.29 7.65 3.99 3.89 1.61

BOD 17 1.6 21.3 8.1 6.5 5.3 16 19.6 346.5 126.3 58.4 115.8

COD 18 14.9 147.4 45.1 38.7 36.6 17 45.9 762.1 301.7 195.6 231.3

NO3-N 18 0.351 2.470 0.990 0.937 0.491 17 0.466 2.467 1.042 0.800 0.562

NH3-N 18 0.018 2.385 0.408 0.174 0.598 17 0.114 7.162 1.259 0.701 1.718

NO2-N 17 0.003 0.088 0.016 0.008 0.021 17 0.003 0.018 0.006 0.006 0.004

SRP 17 0.015 0.281 0.101 0.084 0.075 17 0.02 1.45 0.23 0.08 0.36

TP 14 0.09 1.75 0.50 0.41 0.41 17 0.305 2.540 0.824 0.734 0.566

Zn 12 0.01 0.14 0.06 0.05 0.04 8 0.03 0.64 0.15 0.05 0.21

Variable EMC (mg/L)

Industrial catchment

n Min Max Mean Median SD

TSS 17 13 451 143 91 133

O&G 16 1.57 8.73 4.80 4.52 1.84

BOD 13 16.2 205.4 55.5 44.8 52.2

COD 15 61.7 321.3 134.6 97.3 79.4

NO3-N 17 0.415 3.348 1.369 1.139 0.738

NH3-N 17 0.118 11.859 1.439 0.457 2.850

NO2-N 16 0.0014 0.1207 0.019 0.009 0.0296

SRP 16 0.027 0.318 0.108 0.077 0.082

TP 14 0.12 2.62 0.77 0.62 0.63

Zn 11 0.07 0.64 0.29 0.29 0.18

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TSS and NH3-N showed obvious decreases as the storms

progress, while O&G, NO3-N, NO2-N and Zn were rela-

tively constant throughout the storm episode. A decreasing

trend in MBBF with cumulative runoff suggests dilution of

pollutant concentration over time. The pollution load

transported by the first 30 % of runoff volume (MBFF30)

was used as a benchmark to evaluate the magnitude of first

flush (Li et al. 2007; Nazahiyah et al. 2007). The MBFF30

median values for TSS were 1.5, 2.1 and 2.0 at the resi-

dential, commercial and industrial catchments, respec-

tively. These correspond to removals of 45, 63 and 60 % of

the total loadings by the first 30 % of the runoff volume.

The MBFF30 ratios for various pollutants were ranked by

their median values as shown in Table 4. Higher loadings

of NH3-N were observed in the first 30 % of runoff volume

at the residential site. The high variation among the

MBFF30 values indicates that the pollutant wash-off

mechanism was influenced by other factors besides rainfall.

The means MBFF30 for BOD, COD, TSS, O&G, NH3-N

and TP were 44, 45, 46, 40, 52 and 44 %, respectively.

These values are lower compared to those reported by Li

et al. (2007) in a catchment with a combined sewer net-

work in Wuhan City, China, who found means MBFF30 of

62.4 % for TSS and 59.4 % for COD.

Quantitative evaluation of first flush effect

The criterion of 50 % total mass transported by the first

25 % of total runoff as described by Wanielista and Yousef

(1993) was used to assess the occurrence of first flush

phenomenon. Only TSS at the commercial catchment has

met this criterion which requires about 22 % of the first

runoff volume (Table 5). First flush occurrence was most

prevalent for TSS, comprises 71 % of the storm events,

followed by SRP (53 %) and the least for O&G, NO2-N

and TP (about 6 % each). On the other hand, NO3-N did

not show any first flush and this is consistent with finding

by Wanielista and Yousef (1993). The frequency of first

flush in this study is quite different from a highway in

Mount Rainier, MD, USA (Flint and Davis 2007). As

shown in Table 5, the average runoff for transporting 50 %

of the pollutant masses ranged from 22 to 51 %. For the

commercial catchment, O&G, NO3-N, NO2-N, TP and Zn

required about 43 % of the total runoff, whereas BOD,

COD, TSS, NH3-N, and SRP required\30 % of the runoff.

Based on this criterion, TSS showed the strongest first flush

while TP the least. Similarly, Batroney et al. (2010) found

a strong first flush of TSS from a parking area but not for

TP. For the residential catchment, 33 % of the first runoff

volume was needed to remove 50 % of the total TSS

loading and the highest, 41 % was observed for NO3-N

(Table 5). Earlier, in a nearby residential catchment, Na-

zahiyah et al. (2007) found that the first 20–30 % of runoff

volume was able to transport from 15 to 78 % of the TSS

loading, 20–59 % for BOD, 15–69 % for COD, 14–49 %

for NO3-N, 23–53 % for NH3-N, 14–19 % for NO2-N, and

23–43 % for TP. Nazahiyah et al. (2007) also observed a

higher TSS loading in the first flush volume which could be

attributed to sediment sources from less pervious surfaces

near the catchment outlet. Using this definition, the per-

centages of first flush occurrence in the residential catch-

ment were 50 % for NH3-N, 17 % for TSS, 14 % for TP,

between 11 and 12 % for O&G, BOD, COD, NO2-N, and

SRP, and 8 % for Zn. For NH3-N, the first flush effect was

only prevalent in the residential catchment.

As for the industrial catchment, more than 50 % of the

storm events have met the first flush criterion for TSS. On

the other hand, O&G, NO3-N, NO2-N and Zn required

about 44 % of the total runoff volume whereas BOD, COD,

TSS, NH3-N, SRP and TP required about 30 % to transport

50 % of their pollutant masses. On averages, the first runoff

volumes required to remove 50 % of the pollutant mass

were 37, 35 and 36 % for the residential, commercial and

industrial catchments, respectively.

A more stringent first flush definition (80/30) as pro-

posed by Bertrand-Krajewski et al. (1998) was also eval-

uated in this study. However, only two storm events for

TSS and one event for NH3-N at the industrial catchment,

and one event each for TSS and NH3-N at the residential

catchment have met this criterion. On average, the runoff

required to transport 80 % of the pollutant mass were 67,

65 and 64 % for the residential, commercial and industrial

Fig. 2 Hydrograph and

pollutographs of NH3-N, TSS

and O&G on 15 May 2009 at

the residential catchment

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Fig. 3 Box plots of MBFF of

various pollutants at the

residential (RES), commercial

(COM) and industrial (IND)

catchments against increasing

cumulative runoff volume.

COM commercial, IND

industrial, RES residential

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catchments, respectively (Table 5). Overall, the industrial

catchment needs slightly lesser runoff volumes to transport

80 % of the pollutant mass. This may be due to smaller

catchment size (4.38 ha) compared to the commercial

catchment, thus the great bulk of the pollutant mass could

reach the catchment outlet faster. Further, Bertrand-kra-

jewski et al. (1998) in France found that about a half of the

events were able to evacuate 50 % of the total pollutant

mass in the first 38 % of the total runoff volume, and 80 %

of the total pollutant mass in the 74 % of the runoff in a

separate sewer systems. Compared with the results of

Bertrand-krajewski et al. (1998), it seems that less runoff is

required to transport the same amount of pollutant loadings

in tropical urban catchments.

First flush strength

The first flush coefficients, b which were derived from the

relationship between cumulative runoff mass M(t) and

cumulative runoff volume V(t) as described in Eq. (4) are

shown in Table 6. A smaller b value represents a stronger

first flush effect and vice versa. On this basis BOD, COD,

NH3-N, SRP and TP showed consistent strong first flush

effects in all catchments. Surprisingly, TSS only showed

first flush effect at the residential and commercial catch-

ments. The greatest magnitudes of first flush effect were

observed for TP, TSS and NH3-N for the residential,

commercial and industrial catchments, respectively. On

the other hand, O&G, NO3-N, NO2-N and Zn showed

dilution effect (b value [1.0) at all catchments. The first

flush strengths for various constituents are categorized

according to the six zones proposed by Bertrand-krajewski

et al. (1998): zone 1 (0 \ b B 0.185); zone 2

(0.185 \ b B 0.862); zone 3 (0.862 \ b B 1.0); zone 4

(1.0 \ b B 1.159); zone 5 (1.159 \ b B 5.395); and zone

6 (5.395 \ b B ? ?).

Pollutants such as TSS, BOD, COD, NH3-N, SRP and

TP mainly fall into zones 2 or 3 which showed medium or

negligible positive gap between dimensionless cumulative

mass volume [M(V)] curve from the bisector line. In

Table 4 Ranking of MBFF30

ratios at all catchmentsRanking Residential Commercial Industrial

Parameter MBFF30 Parameter MBFF30 Parameter MBFF30

1 NH3-N 1.85 TSS 2.07 TSS 2.00

2 COD 1.53 BOD 1.83 NH3-N 1.87

3 TSS 1.50 COD 1.83 COD 1.73

4 TP 1.43 SRP 1.77 BOD 1.67

5 BOD 1.40 NH3-N 1.67 SRP 1.63

6 NO2-N 1.27 TP 1.23 TP 1.53

7 NO3-N 1.25 NO3-N 1.20 O&G 1.20

8 Zn 1.23 NO2-N 1.17 NO3-N 1.13

9 SRP 1.22 O&G 1.13 NO2-N 1.00

10 O&G 1.20 Zn 1.07 Zn 0.90

Table 5 Average runoff

volume for transporting 50 and

80 % of the total pollutant mass

Parameter Catchment

Residential Commercial Industrial

n 50 % 80 % n 50 % 80 % n 50 % 80 %

TSS 17 33 61 17 22 52 17 27 50

O&G 17 38 68 17 46 72 16 41 70

BOD 17 36 67 16 27 58 13 34 64

COD 18 35 66 17 28 55 15 31 63

NO3-N 18 41 71 17 42 73 17 41 70

NH3-N 18 29 59 17 30 64 17 27 56

NO2-N 17 40 67 17 44 71 16 44 71

SRP 18 41 70 17 28 61 16 31 55

TP 14 34 65 17 41 71 14 33 64

Zn 12 42 71 8 42 70 10 51 75

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contrast, O&G, NO3-N, NO2-N and Zn mainly belong to

zone 4 which showed negligible negative gap. The only

constituent that showed medium negative gap is Zn at the

industrial catchment which is in zone 5.This suggests that

first flush is not significant for Zn in the industrial catch-

ment. Such behavior of Zn was also observed by Gnecco

et al. (2006). The possible sources of Zn in the industrial

catchment were from galvanized roof and metal manu-

facturing factories which present in trace quantities but the

supply is rather consistent. Table 6 ranks the average rel-

ative first flush strength for all constituents. These

sequences generally suggest that various pollutants showed

different first flush effect at different urban land uses. In

Iran, Taebi and Droste (2004) found similar strong first

flush effect for TSS in residential and commercial catch-

ments, while Lee et al. (2002) in Korea found strong first

flush effect for phosphorus in an industrial catchment.

Influences of hydrological variables on first flush

strength

The hydrological parameters used to assess the effect on

first flush strength are rainfall depth (Rd), rainfall duration

(RDur), mean rainfall intensity (I), maximum 5 min rainfall

intensity (Imax5), antecedent dry day (ADD), runoff volume

(Vol) and peak flow(Qpeak). The correlation analysis results

are summarized in Table 7. ADD correlates well with

b value of TSS (r = -0.72) and O&G (r = -0.64) in the

residential catchment. The strong negative correlation

between ADD and b values indicates that a longer ADD

would result in a smaller b value or a stronger first flush.

Such patterns could suggest limited supply of TSS and

O&G from the catchment surfaces. This concurs well with

the findings by Gupta and Saul (1996), Deletic and Mak-

simovic (1998), Soller et al. (2005), Nazahiyah et al.

(2007), Li et al. (2007) and Huang et al. (2007). As shown

in Table 7, the first flush strengths of TSS, BOD, COD,

NH3-N and TP in the commercial catchment are strongly

correlated with all the storm variables except for ADD.

Therefore, any increase in the magnitude of these storm

variables would result in a greater first flush effect. Taebi

and Droste (2004) in Isfahan, Iran, found similar findings.

However, there is no significant correlation between mean

rainfall intensity against TSS loading at the commercial

catchment. He et al. (2010) in Alberta, explained that TSS

loading is largely regulated by the flow magnitude even in

the initial phases of a storm. The results for industrial

catchment are not presented because none of the pollutants

are significantly correlated with first flush strength and

storm variables.

Implication for urban runoff management

First flush volume is crucial for designing urban runoff

quality control structures especially to determine the

required runoff depth for transporting 50 % of the total

pollutant loading. Most of the storms that have been

sampled are categorized as frequent storms of \3 month

average return interval (ARI) with design rainfall, derived

from intensity–duration–frequency curve of 33 mm (DID

2000). The mean runoff coefficients for residential, com-

mercial and industrial catchments are 0.73, 0.84 and 0.87,

respectively. Therefore, the design runoff depths for 37, 35

and 36 % of runoff volume (as determined in ‘‘Quantitative

evaluation of first flush effect’’) at the residential, com-

mercial and industrial catchments are 8.7, 9.5 and 9.5 mm,

respectively. Of the 18 storm events sampled at the resi-

dential catchment, 10 events produced runoff [8.7 mm.

For the commercial and industrial catchments, both have

eight storm events with runoff [9.5 mm. The results sug-

gest that the design rainfall of 3-month ARI would capture

pollutant loadings from 46 to 54 % at the residential

Table 6 First flush strength

(b) for constituents at all

catchments

± signs indicate standard

deviation

Ranking Catchment

Residential Commercial Industrial

Parameter b values Parameter b values Parameter b values

1 TP 0.82 ± 0.2 TSS 0.70 ± 0.1 NH3-N 0.84 ± 0.2

2 NH3-N 0.84 ± 0.2 SRP 0.72 ± 0.3 SRP 0.86 ± 0.3

3 BOD 0.84 ± 0.2 NH3-N 0.73 ± 0.2 TP 0.91 ± 0.2

4 COD 0.86 ± 0.1 COD 0.76 ± 0.2 BOD 0.94 ± 0.2

5 TSS 0.87 ± 0.2 BOD 0.81 ± 0.2 COD 0.96 ± 0.2

6 O&G 0.96 ± 0.2 TP 0.84 ± 0.1 NO3-N 1.01 ± 0.1

7 SRP 0.97 ± 0.2 Zn 0.96 ± 0.3 TSS 1.03 ± 0.2

8 NO2-N 1.00 ± 0.2 NO2-N 0.97 ± 0.1 NO2-N 1.03 ± 0.2

9 NO3-N 1.01 ± 0.1 NO3-N 0.99 ± 0.1 O&G 1.04 ± 0.2

10 Zn 1.01 ± 0.2 O&G 1.00 ± 0.1 Zn 1.22 ± 0.4

Environ Earth Sci (2014) 72:4047–4058 4055

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catchment, 28–62 % at the commercial catchment, and

43–72 % at the industrial catchment (Table 8). This ana-

lysis demonstrates that controlling the first 10 mm of the

runoff depth would capture about half of the total pollutant

loading that would otherwise enter the streams.

Conclusions

This study characterized first flush phenomenon in tropical

urban catchments and provides basis for designing runoff

quality control facilities. The important findings are con-

cluded as follows:

1. Strong first flush effects (MBFF [ 1.0) were observed

for BOD, COD, NH3-N, SRP and TP at all catchments.

TSS showed strong first flush effect only at the

residential and commercial catchments. On the other

hand, O&G, NO3-N, NO2-N and Zn showed weak or

no first flush effect at all catchments. Based on

MBFF30 analysis, the degree of first flush, at the

residential catchment was in the order NH3-N [ COD

[ TSS[TP[ BOD[NO2-N [NO3-N[ Zn [SRP

[O&G; commercial catchment—TSS [BOD &COD [ SRP [ NH3-N [ TP [ NO3-N [ NO2-N [O&G; and industrial catchment—TSS [ NH3-N

[ COD [ BOD [ SRP [ TP [ O&G [ NO3-N [NO2-N [ Zn.

2. On average, in order to transport 50 and 80 % of the

total pollutant mass, the corresponding runoff vol-

umes required are 37 and 67 % for the residential

catchment, 35–65 % for the commercial catchment

and 36–64 % for the industrial catchment. Appar-

ently, for the same amount of loadings, tropical

urban catchments need less runoff volume to trans-

port the pollutant compared to in the temperate

regions.

Table 7 Correlation

coefficients between first flush

strength (b value) and storm

characteristics for various

pollutants

* Correlation is significant at

P \ 0.05

** Correlation is significant at

P \ 0.01

Parameters Storm variable

Rd RDur I Imax5 ADD Vol Qpeak

Residential catchment

TSS -0.72**

O&G -0.64**

Commercial catchment

TSS -0.61** -0.70** -0.60* -0.60* -0.64**

BOD -0.76** -0.75** -0.77** -0.77** -0.81**

COD -0.64** -0.57* -0.74** -0.62** -0.76**

NH3-N -0.66** -0.54* -0.57* -0.65** -0.66**

SRP -0.51* -0.50* -0.55*

TP -0.57* -0.59* -0.65** -0.57* -0.69**

Table 8 Estimates of pollutant

loading (%) transported by

3 month design runoff volume

n number of sampled storm with

runoff greater than the design

runoff, cv coefficient of

variation, NA not applicable due

to small sample size

Catchment BOD COD TSS O&G NO3-N NH3-N NO2-N SRP TP

Residential

n 9 10 10 10 10 10 9 10 7

Mean 46 52 50 47 47 54 47 49 54

SD 11 20 21 17 16 23 13 18 21

cv 25 39 42 36 34 43 26 36 39

Commercial

n 8 8 8 8 8 8 8 8 8

Mean 60 59 62 28 32 52 30 54 36

SD 19 22 20 20 26 20 28 25 22

cv 31 38 32 73 80 38 94 46 62

Industrial

n NA 8 8 7 8 8 8 7 NA

Mean NA 62 71 51 57 65 55 61 NA

SD NA 16 15 19 16 14 24 24 NA

cv NA 27 21 36 27 21 43 40 NA

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3. Each catchment has different first flush response to

storm variables. The first flush strengths of TSS, BOD,

COD, NH3-N and TP in the commercial catchment

were strongly correlated with all the storm variables

except for ADD. However, in the residential catch-

ment, only ADD was correlated positively with first

flush strength of TSS and O&G. None of the storm

variables have significant influence on the first flush

strength in the industrial catchment.

4. Controlling the first 10 mm of the runoff depth would

be able to reduce about half of the total pollutant

loading from residential, commercial and industrial

catchments in this tropical site.

Acknowledgments The authors are grateful to UTM Research

Management Centre (RMC) for facilitating this research under Vot

GUP 01H72. This study was also supported by the Asian Core Pro-

gram of the Japanese Society for the Promotion of Science (JSPS) and

the Ministry of Education, Malaysia (MoEM).

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