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11th International Conference on Urban Drainage, Edinburgh, Scotland, UK, 2008

Zawilski and Sakson 1

Modelling of detention-sedimentation basins for stormwater treatment using SWMM software

M.Zawilski1*, G.Sakson1

1Department of Environmental Engineering, Technical University of Lodz Al.Politechniki 6, 90-924 Lodz, Poland

*Corresponding author, e-mail: [email protected]

ABSTRACT In the paper, application of the model for total suspended solids removal with the use of SWMM software is analysed. Two types of kinetics were checked: first order and second order. In the SWMM model two types of detention-sedimentation tank were input: a single completely stirred reactor and a reactor of the same mixing conditions but divided into four subsequent parts. The model was calibrated according to field investigations of a real tank. The modelling results show a good accordance of the modelled and measured parameters, especially of the outflow TSS load. The best results were obtained for the single CSTR and the second order kinetics. The proposed model is sensitive to changes of decay rate constant. Removal of TSS depends also on the tank area and outflow intensity. However, these changes are essential for intense storm events. Despite some simplifications, the SWMM model can be used for practical calculations.

KEYWORDS Detention tanks; total suspended solids; sedimentation; urban drainage; SWMM software.

INTRODUCTION Detention-sedimentation basins are frequently used for stormwater treatment prior to its draining into natural waters. The random character of rainfall events and unsteady flow conditions make it difficult to evaluate the technological effect of such facilities. It is well-known that elimination of suspended solids is essential for stormwater treatment and allows for elimination of other pollutants (like heavy metals and organic contaminants) associated with suspended solids.

In detention-sedimentation basins, various processes occur: detention of water as a consequence of throttling of the outflow, flocculation and sedimentation of (mainly mineral) particles, resuspension of sediments, flotation of oils, light particles and so on. In practical engineering analyses, there is an urgent need to evaluate the efficiency of such tanks depending on their size, hydraulic loading, pollutant level of influent stormwater and other factors. Long-term computer simulation is one of techniques used for this purpose. A detention tank usually is an element of sewerage network and often is situated at the outlet of a main stormwater sewer. The tank receives all the catchment runoff and depending of the tank size (area, active depth) a removal of certain portion of incoming load of suspended solids is possible. So far, several original simple and sophisticated models for such tanks have been elaborated. However, the popular SWMM software can be used for this purpose but the

Modelling of detention-sedimentation basins

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user should introduce a treatment function. In the paper, a proposal for using such SWMM option is presented. The proposed algorithm resulted from own investigation of a real tank.

METHODS The principle of detention-sedimentation tanks is capturing storm runoff together with transported pollutant load. Usually, this can be achieved by installation of a throttling device or a regulator at the tank bottom end. Capturing of inflow or pollutant load from a certain period (for instance the whole year) may be a basic design criterion (Vaes and Berlamont, 2004; Birch et al., 2006; Calabro and Viviani, 2006). Another option is limiting the annual volume or load input from a catchment into receiving water body. Computer modelling is an effective method for assessing the technological efficiency of stormwater detention-sedimentation tanks situated at outlets from urban catchments.

Models of detention-sedimentation tanks The functioning of the detention-sedimentation tank can be described either as a hydraulic or a technological efficiency (i.e. reducing the flow, volume of stormwater or the pollutant load). Long-term simulations can be used for this purpose. Having a well-calibrated model for calculation of runoff, stormwater flow and load from a catchment, it is necessary to introduce certain treatment efficiency formula for a possible tank.

Sedimentation of suspended solid particles was recognised as the main technological process for traditional and also modern sediment trap devices (Phipps et al., 2005). Removing of turbidity of stormwater is especially difficult (Han and Mun, 2007). However, the sedimentation process occur in non-standard conditions, for instance in comparison with typical primary settling tanks used in wastewater treatment plants. The main difference is unsteady inflow, outflow and active volume which make impossible a direct application of known simple sedimentation models for typical clarifiers. Additionally, inflow and (in consequence) outflow pollutant concentration are highly variable in time as well as a flow turbulence undergo rapid changes, especially in real tanks of non-ideal shapes (Vaes, 1998). Models for describing objects are formulated with some simplifications. For instance, Takamatsu et al. (2006) assumed the plug-flow inside the tank which made possible adaptation of the known Camp theory of particle movement in the tank active volume. If a particle settling velocity distribution is known, this theory makes possible calculating technological effect as a portion of removed load of solid particles in relation to the inflow load. Other assumptions take non-ideal flow conditions, i.e. longitudinal mixing into consideration (Jensen, 2005). This effect, as known, can be modelled as a flow through a completely stirred tank reactors (CSTRs) in series and usually few (4-10) such reactors can be assumed. This model, however, does not allow for detailed calculating of particle trajectories during settling process and a kinetic model for pollutant removal has to be applied instead. Nonetheless, such models may give satisfactory results (Zawilski, 1997; Person et al., 1999;Wong et al., 2002).

EPA SWMM model for treatment facilities EPA SWMM (Stormwater Management Model) is the widely known and free software used for modelling of sewerage systems. Among others, it contains a procedure for modelling the technological effect taking place at any node of a sewer network. The node can be declared as a storage unit with an assumed treatment function which the option can serve for modelling detention-sedimentation facilities. The user, however, should input his own formula (or a set of formulas) calculating the removal efficiency using some standard technological parameters. Some general hints for the algorithm are known only. Basically, a treatment function for the



pollutant concentration (C) in a stream entering the tank can be used. The following process variables may be used in the formula:

FLOW for flow rate into node (in user-defined flow units) DEPTH for water depth above node invert (ft or m) AREA for node surface area (ft2 or m2) DT for routing time step (sec) HRT for hydraulic residence time (hours)

Also, a fractional removal (R) of some other tracer pollutants (usually associated with TSS) can be formulated. In this case a simple proportional formula type R= aR(TSS) is proposed. It is logical that the used treatment formula should be verified according to investigations of a pilot or real object.

Proposed treatment formula First of all, it was checked whether a reasonable simple formula for a single CSTR can be applied. Formally, the process of static sedimentation can be modeled using first order kinetic. However, as it was stated earlier for the investigated real tank, also other phenomena affect the sedimentation efficiency:

characteristics of inflowing TSS strongly depends on rainfall intensity; there is a strong correlation between TSS concentration and settling velocity distribution, i.e. smaller TSS concentration always is correlated with smaller settling velocities and vice-versa (Zawilski, 1996, 1998). However, only a crude relationship can be derived from real data because of random variation of TSS composition transported from the catchment after each rainfall event,

As it was proved earlier, a certain portion of TSS of low settling velocity cannot be removed during dynamic conditions with variable water level inside the tank (Takamatsu et al., 2006),

Turbulence of flow may have greater influence on removal of particles of low settling velocity.

Therefore the influence of TSS concentration cannot be ignored as it dominates the kinetics especially for low concentration inflows. Similar relationship was found for settling tanks at wastewater treatment plants (Lessard and Beck, 1988). Taking this into consideration, two types of kinetic reactions for inflow TSS concentration were checked:

First order kinetic

inkcdtdc

= (1) Second order kinetic

2inkcdt

dc= (2)

These kinetic equations result in following formulas for pollutant removal:

First order kinetic HRT)kEXP(1R = (3)


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Second order kinetic

HRTkc1HRTkcR

in

in

+

= (4)

where hydraulic residence time HRT is assumed as a driving parameter.

A dependence of settling velocity on TSS concentration was stated earlier by the author and considered for the first-order kinetics (Zawilski 1996). A correction in the formula for TSS removal efficiency was proposed. In this paper, a similar attitude for formula (3) is applied, resulting in the following expression:

=

n

1000TSSHRTkEXP1R (5)

In other words, in this corrected formula low TSS concentration causes the same effect as shortening of HRT. The above formula (5) can be called the improved first order kinetic. In the SWMM algorithm, HRT is represented by the instantaneous volume divided by outflow intensity. The outflow intensity can be obtained from the water balance (as it will be described later).

Additionally, the model for 4 CSTR in series was checked, too. This option was supposed to give better fitting to measured data as it represents longitudinal mixing of the tank content better. For this purpose, a series of four sub-tanks were input. The sub-tanks, each of 25% area of the total area were connected with short virtual channels of big dimensions in order to avoid artificial throttling effects. Outflow was modeled with the input of outlet characteristics from the last tank only. Inflow was input to the first tank in series. For each of the sub-tanks the same kinetic equation was assumed but the decay rate k could be different in comparison with a single CSTR and should be adjusted separately.

Description of the research object Lodz city (central Poland) was equipped with a separate sewerage system in the city districts outside the centre where still the combined system is operated. The stormwater separate outlets direct runoff into local urban rivers. Therefore, some of the outlets were equipped with detention-sedimentation tanks in order to remove most of stormwater pollutants prior to their diverting into receiving waters. One of the biggest tanks was built in 1970s at the outlet of a sewer serving for a 300 ha urban catchment. The geometrical parameters of the tank are given in Table 1.

Table 1. Geometrical parameters of the investigated tank Category Unit Value

Bottom area m2 4233 Minimum water depth m 0.16

Water level area increase m2m depth 477 Crest height of emergency overflow

above bottom level m 1.52 Inflow channel (long.slope 7%) m 2.601.60

Outflow pipes (29) mm 100 Box filter length m 2G20 Box filter width m 0.5



The open triangular tank is situated at a local urban river. During first years of functioning, outflow from the tank was taking place through 29 pipes of 100 mm diameter. Afterwards, a special filter as an open-work box made from bricks filled with wood-wool was constructed few meters in front of the end wall (Fig.1). The role of the filter is retaining oils. The filter, however, functions as a ponding device because of its significant flow resistance. In the middle of the box filter a concrete wall with small openings at the tank bottom was constructed (Fig.1). The inlet to the tank was constructed as a short open channel with the slope of 7%. This allows avoiding of backwater in the inlet rectangular sewer. The tank collects sediments which are removed from the bottom once a year, usually at the end of the year (November-December) when no frequent storms over the catchment are observed.

Figure.1. Scheme of the investigated tank

Experimental data The investigations were performed on the basis of older but still valuable measurements made for the five years research campaign in 1987-1991 (Table 2). The general results were already presented (Zawilski 1996).

Inflow measurements were carried out with the use of a limnigraph situated in the side well at the last segment of the inflow sewer. Simultaneously, water depth in the tank was measured with the time interval depending on the water level variations. During the research period,


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activating of the emergency overflow was observed only once but not for an investigated run. Also, in most cases the receiving water level was well below the tank bottom level. The TSS concentration was determined in grab samples taken: - at the inlet at the lowest point of the inflow channel (where strong turbulence of flowing stormwater is observed), -at the outlet at the middle of the filter wall for samples taken from below 20 cm depth; if the active depth was less than about 40 cm, samples were taken from the outflow opening in the wall.

Table 2. Characteristics of investigated runoff events Inflow Rainfall

Run Qmax (m3/s)

TSSmax (g/m3)

Cw# (g/m3)

V (m3)

LTSS (kg)

h (mm)

t (min)

imean (mm/h)

1 5.11 1900 1044 10061 10507 7.98 22 21.76 2 3.40 1326 294 5902 1736 7.39 26 17.05 3 0.69 1230 699 2571 1796 10.26 430 1.44 4 3.64 5875 933 5528 5158 6.56 135 2.91 5 1.58 3105 2486 2972 7388 3.78 124 1.83 6 0.13 640 195 5904 1149 - - 1.1* 7 0.23 164 83 9216 761 13.94 1493 0.58 8 0.59 916 639 1856 1186 3.49 62 3.38 9 1.91 2257 549 3488 1916 5.53 40 8.31

10 0.29 296 89 3325 296 7.64 306 1.51 11 0.19 503 183 1041 191 2.31 323 0.43

# TSS concentration weighted by flow for the whole event * snowmelt event; intensity of equivalent rainfall caused the same average outflow

The effect of the wood-wool filter was not investigated although apart from oils it is likely able to capture some portion of fine suspended solids.

For the SWMM implementation, the obtained flow, depth and TSS measurements were input into text files using the necessary format.

RESULTS Calibration of SWMM model For all measured runs, separate calculations were carried out in order to adjust model parameters. At first, for each run outflow characteristics were found. The outflow from the tank as the flow through the wood-wool filter was not measurable in details. However, its value can be determined from the water balance:

dtdVQQ inout = (6)

This equation was solved twice: - with the use of the SWMM procedure as fitting the outflow parameters (see below) so that the measured and calculated water level in the tank were in close agreement, and for control with the use of own calculation procedure numerically determining values of dV/dt for any time point. The SWMM formula for outflow intensity is:

Bout hAQ = (7)



This formula was checked for its applicability and satisfactory results were obtained (Figure 2). However, the outflow parameter A had to be adjusted for each run independently and turned out to be much greater after the periodical exchange of wood-wool in comparison with the periods of partly clogged material. During few months of filter functioning, the parameter A was gradually decreasing from 3.0 to 0.3. The value of parameter B was around 2.8.

For the calibration of TSS removal model, several computation runs were carried out for different values of kinetic coefficients. The main optimisation fitting criterion was the correlation between the measured and modelled outflow TSS load. This relationship was assumed as linear:

meas

outmodout LaL = (8)

with ideal fitting for a=1 and R2=1.

It was stated that the pure first order kinetics (Equation 3) gives wrong model results.

All calculations were made for the time step of 30 seconds. This parameter proved to be essential for model results to some extent, decreasing the outflow TSS load with a decreasing of time step. However, this effect was not studied in detail since input of very short time steps results in a substantial increase of calculation time. This would be very unfavorable in the case of simultaneous modeling the runoff from a catchment, flow in sewer networks and treatment in the tank.

One run had to be rejected from the whole experimental set. For this run, a considerable scouring of TSS from the tank bottom was detected. Unfortunately, this effect cannot be directly modeled as the SWMM removal formula allows for positive reduction of pollutant only. During the rejected run, the maximum inflow was equal to 5 m3/s and was reached soon after a very intense rainfall and with a corresponding rapid increase of the inflow. The results of calibration are presented in Table 3.

Table 3. Results of calibration of the SWMM model Type of tank Improved first order kinetics

(formula (5)) Second order kinetics

(formula (4)) Single CSTR k = 0.42; n =2

a = 1.007 R2 = 0.91

k = 0.0011 a = 0.978 R2 = 0.97

Four CSTRs k = 0.98; n = 2 a = 1.015 R2 = 0.92

k = 0.00085 a = 1.002 R2 = 0.92

In Figure 2 some modelling results are presented. Surprisingly, the best results were obtained for a single CSTR and assumption of four CSTRs in series did not improve the general fitting. This result can be explained as following: the SWMM model is able to predict the removal of the total TSS load from a single event and a series of events. However, simplified calculation formula for pollutant removal cannot describe outflow pollutographs ideally. Especially, the TSS concentration is underestimated in its late part, i.e. the concentration tail is not represented and the TSS level decreases to zero. Most of the TSS load is being removed during first phases of the tank filling when it works in a manner similar to a single CSTR. The later rest of TSS load is not decisive for the result.


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Modelling of COD concentration and load The COD parameter is one of most important ones for evaluating of the influence of stormwater on receiving waters. This parameter can be modelled in similar way like TSS. However, it would be necessary to gather a COD database similar to that of TSS and to calibrate the model. Other simplified method is using the relationship between the two parameters. The relationship can serve for recalculating of COD from TSS at the outlet of the tank. For the investigated catchment and the tank, the following relationship was found:

70TSS2.08COD 0.66 += (9)

in which the value 70 represents the average soluble fraction of COD (non-degradable in the tank). The formula is valid both for the inflow, as and the outflow COD, therefore can be applied in the SWMM removal model. The relationship may be input as the treatment formula for any node downstream of the tank.

Figure 2. Examples of modelling results for run no.4. Water depth and outflow TSS with dots as measurement data (above), inflow - outflow discharge and inflow - outflow TSS (below).



0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7Multiplication factor for tank bottom area

Perc

en

tage

o

f ou

tflo

w TS

S lo

ad

Run 1 Run 7

Sensitivity analysis of the model For the purpose of evaluation of the model, a sensitivity analysis was made. The analysis was carried out for the single tank, second-order model and the best fitted decay rate k=0.0011 was taken as a base value.

Figure 3. Sensitivity analysis of the model for the decay rate

Figure 4. Effect of hydraulic loading and outflow discharge onto outflow TSS load

From Figure 3 it can be concluded that the model is very sensitive to changes of decay rate constant. Therefore, the decay coefficient should be determined in field tests, possibly with the use of a real or pilot installation.

Removal of TSS depends also on the tank area and outflow intensity (Figure 4). However, the appropriate changes of TSS load are essential for intense storm events. For weak rainfalls, the efficiency of the tank is usually poor; therefore the effect of the tank area and outflow discharge is relatively less.

0.4

0.6

0.8

1

1.2

1.4

1.6

0 0.0005 0.001 0.0015 0.002 0.0025

Decay rate constant

Fitti

ng

co

effi

cie

nt

70

80

90

100

110

120

130

0 0.5 1 1.5 2 2.5

Outflow coefficient

Perc

en

tage

o

f ou

tflo

w TS

S lo

ad

Run 1Run 7


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CONCLUSIONS The SWMM model proved to be able to predict TSS removal in detention-sedimentation tanks properly. However, it is necessary to use a proper formula for TSS removal and to determine kinetic coefficients. For the investigated real tank, the second order kinetics and single CSTR reactor turned out to be the best model option. Alternatively, the first order kinetics with a correction for TSS concentration can be used. In both cases, best results were obtained for modelling the TSS outflow load, the TSS outflow pollutographs are modelled with a less precision. For further practical use of the removal model a credible and not complicated test methodology for determining the decay rate of TSS removal in dynamic flow conditions should be elaborated.

REFERENCES Birch G., Matthai C. and Fazeli M. (2006). Efficiency of a retention/detention basin to remove contaminants

from urban stormwater. Urban Water Journal, 3(2), 69-77. Calabro P.S. and Viviani G. (2006). Simulation of the operation of detention tanks. Water Research, 40, 83-90. Han M.Y. and Mun J.S. (2007). Particle behaviour consideration to maximize the settling capacity of rainwater

storage tanks. Wat.Sci.Tech., 56(11), 73-79. Jensen M. (2005). Sediment retention in rectangular storage tanks: Computations with a mass transport model

and comparison with laboratory experiments. Proc. of the 10th International Conference on Urban Drainage (10ICUD), Copenhagen., a CD-ROM collection of papers.

Lessard P. and Beck M. B. (1988). Dynamic Modeling of Primary Sedimentation. JEED, ASCE, Vol. 114. no.4, pp. 753-769.

Person J., Somes N.L.G. and Wong T.H.F. (1999). Hydraulics efficiency of constructed wetlands and ponds., Wat.Sci.Tech., 40(3), 291-300.

Phipps D.A. and Alkhaddar R.M., Faram M.G. (2005). Pollutants retention in stormwater treatment chambers. Proc. of the 10th International Conference on Urban Drainage (10ICUD), Copenhagen, a CD-ROM collection of papers.

Takamatsu M., Barrett M. and Charbeneau R.J. (2006). Modeling of Sedimentation in Stormwater Detention Basins. WEFTEC06 (Water Environmental Foundation Conference), 5559-5577.

Vaes G. (1998). Design of storage sedimentation basins. Proc. of the NOVATECH98 conference Innovative technologies in urban drainage, Lyon, a CD-ROM collection of papers.

Vaes G. and Berlamont J.(2004). Source control design using contiuous long term modeling. 6th Int. Conf. on Urban Drainage Modelling, Dresden, 599-608.

Wong T. H. F., Fletcher T. D., Duncan H.P., Coleman J. R. and Jenkins G. A (2002). A Model for Urban Stormwater Improvement Conceptualization. 9th International Conference on Urban Drainage (9ICUD), Portland., 598, and a CD-ROM collection of papers.

Zawilski M. (1996). Technological modelling of detention-sedimentation tanks for stormwater treatment. Proc. 7th.Int.Conf. on Urban Storm Drainage. Hannover, t.III, pp.1275-1280

Zawilski M. (1997). Prognosing of amount and pollutant loads of stormwater from urbanised areas. Zeszyty Naukowe Politechniki dzkiej, no 792 (in Polish).

Zawilski M. (1998). Distribution of settling velocity - a tool of predicting the stormwater solid contamination characteristics. Proc. of the NOVATECH98 conference Innovative technologies in urban drainage, Lyon, a CD-ROM collection of papers, vol.2, 231-238.

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