modeling the layouts of stormwater retention ponds using ......modeling the layouts of stormwater...

Modeling the Layouts of Stormwater Retention Ponds using Residence Time

SHER KHAN, BRUCE W. MELVILLE, ASAAD Y. SHAMSELDIN

Department of Civil and Environmental Engineering, The University of Auckland

Private Bag 92019, Auckland Mail Centre Auckland 1142

NEW ZEALAND [email protected]

Abstract: - One of the principal methods to treat stormwater runoff is stormwater retention ponds. In order to make these ponds hydraulically efficient, they should be designed to give the maximum residence time to settle out the suspended solids. In this study, the effect of pond layout on residence time is investigated. A trapezoidal pond having top dimensions 1.025 m 0.375 m, depth 0.0575 m and side slopes of 2:1 (horizontal to vertical), was used. Numerical simulations were carried out to produce retention time distribution (RTD) curves for different layouts of a stormwater retention pond. Short-circuiting, effective volume and hydraulic efficiencies of eight different layouts were investigated on the basis of residence time and compared to determine the optimal pond design. Investigation of the hydraulic parameters showed that an island or subsurface berm at a distance of one quarter of pond length from the inlet gives the best hydraulic performance in terms of residence time. Key-Words: - hydraulics, residence time, retention ponds, hydraulic efficiency, computational fluid dynamics, numerical modeling 1 Introduction Stormwater retention ponds are constructed to manage storm water runoff, to improve water quality and to protect the downstream ecosystem. The use of retention ponds on construction sites to treat stormwater runoff has increased rapidly during the last ten years in Auckland, New Zealand, which is the area under consideration in this study. Among other reasons, this is due to the growing environmental awareness about the water health and marine ecosystem in New Zealand. Stormwater may contain a large quantity of sediments especially in areas which are comprised of erosive soils. These sediments can destroy the marine ecosystem and fresh water bodies, if not controlled on the site. The use of storm water retention ponds is one of the solutions to control these sediments [1]. For effective sedimentation, the design of the pond should be such that it provides sufficient residence time to settle the sediments.

Residence time is a function of pond volume and inlet discharge and is a key factor affecting pond performance. The different parameters which are used to compare pond layouts for optimal design can be derived from residence times. A high residence time gives better hydraulic performance and better flow regime which ultimately increases the settling rate of suspended solids. Residence time is influenced by a number of factors including pond layout which is very important. Many researchers reported the impact of pond layout

(including the use of baffles and an island) on pond residence time [2-10]. In most of the studies, the recommended layout includes at least two baffles for maximum residence time [11-13]. The layout with an island or subsurface berm placed in front of the inlet has also some advantages in terms of improved hydraulic efficiency and longer residence time as compared to a pond layout without such arrangements [7].

In all the above studies, two methods were adopted to model the residence time, i.e. physical modeling and numerical modeling. The major limitations of physical modeling are that the measurements can be made only after the construction of a pond, which can be costly in space and time. Numerical modeling has some advantages over physical modeling, such as the residence time can be studied in detail without construction of a physical model. It is also possible to study different layouts which makes numerical modeling economical.

The advantages of numerical modeling over physical modeling have increased the interest in computational fluid dynamic (CFD) modeling. The selection of an appropriate CFD model, 2D or 3D, depends on the nature of the problem. A 3D model is complex and time consuming but provides much more detailed information as compared to the 2D model, especially for a study involving pond hydraulics [3, 14, 15].

Proceedings of the 4th IASME / WSEAS Int. Conference on WATER RESOURCES, HYDRAULICS & HYDROLOGY (WHH'09)

ISSN: 1790-2769 77 ISBN: 978-960-474-057-4

In the previous studies, the simulations of the residence time in stormwater ponds were carried out, for both 2D and 3D studies, using rectangular pond geometry [7, 15]. This simplification was made on the assumption that the side slopes can be neglected due to the large size of the pond. However, retention ponds used in New Zealand are relatively small being designed typically for small catchment areas and it is not appropriate to neglect the side slopes. In the present study, trapezoidal pond geometry is employed and circular pipe is used for the inlet and outlet. These conditions are in accordance with most of the field ponds.

A 3-D numerical model was developed using ANSYS CFX 11.0 software to simulate the hydraulic performance of a scaled down physical model of the existing flocculation pond at the Alpurt B2 Motorway site in Auckland, New Zealand. To study the effect of pond layout on pond residence time, the numerical model was undertaken with baffles and an island. 2 Comparison of pond performance in terms of residence time Several parameters have been used in past studies, using both numerical and physical models, to compare different pond layouts [3, 7, 9, 16-18]. The parameters chosen for this study are short-circuiting, effective volume, and hydraulic efficiency. Comparison on the basis of only one of these hydraulic parameters can give different results [19]. Therefore, the comparison made in this study is based on the three hydraulic parameters, which are described below.

First, the short-circuiting factor S is defined as

(1)

where t16 is the time when 16th percentile of the tracer added at the inlet has passed the outlet and t50 is the time when half of the tracer added at the inlet has passed the outlet. A value of S factor lower than 0.3 indicates short-circuiting and a value higher than 0.4 is acceptable for an efficient pond [9]. Short circuiting is a situation in which some of the water parcels reach the outlet in a time less than the nominal residence time and is calculated as 1-S, where nominal residence time is calculated as pond volume divided by inflow rate [9]. The maximum value of S=1, which would indicate no short-circuiting.

Secondly, the effective volume ratio is defined as the ratio of mean residence time to the nominal residence time.

(2)

In this study, the mean residence time is replaced by the median residence time (t50). This simplification has the advantage that there is no need to carry out the simulations or measurements until 100% of the tracer has reached the outlet [15]. The maximum value for this parameter is unity, which indicates completely mixed flow or plug flow. Plug flow is a condition in which all the fluid particles reside in the system around the nominal residence time and have a uniform velocity profile.

Thirdly, hydraulic efficiency is defined by Person et al (1999) as

(3)

where is hydraulic efficiency and the time is the time at which the peak tracer concentration reaches the outlet. A value of hydraulic efficiency above 0.5 is satisfactory [20]. 3 Methodology 3.1 Pond layouts In New Zealand, stormwater retention ponds are typically designed for a catchment area of 5 hectares [1]. Hence, the studied cases represent small ponds, being based on the assumption of limited provision of space in the field. A total of eight different cases were studied having the same basic pond shape but with different internal geometries which represent most of the possible scenarios of pond layouts. The studied cases are:

• Case 1 (no baffle) • Case 2 (single baffle at one quarter of pond

length from the inlet covering two thirds of pond width)

• Case 3 (single baffle placed at half of pond length covering two thirds of pond width)

• Case 4 (three baffles placed at equal distances covering two thirds of pond width )

• Case 5 (an island placed at one quarter of pond length from the inlet)

• Case 6 (an island placed at one tenth of pond length from the inlet)

• Case 7 (a subsurface berm placed at one quarter of pond length from the inlet covering 80% of pond depth)

• Case 8 (a subsurface berm placed at half of pond length covering 80% of pond depth)

The eight layouts are shown in Fig. 1. 3.2 Model set-up A 3-D numerical model, of similar geometry to that used in the field, was developed. The model pond was


ISSN: 1790-2769 78 ISBN: 978-960-474-057-4

trapezoidal in cross-section with side slopes of 2:1(h: v). The circular inlet and outlet were positioned at the top centre of the ends of the pond. The details of the model are given in Table 1.

For this study, the most robust boundary conditions were applied. The flow region to be modelled was identified as a 3-D region. A constant mass flow rate was applied at the inlet while the outlet was modelled as a pressure outlet assuming zero static pressure. The flow direction was set normal to the inlet boundary condition and the turbulence intensity at inlet was set at 1-5%. All other default 2-D regions, like the sides and bottom of the pond, were modelled as walls with no slip boundary conditions. The top of the pond was set as a free surface and no fluid was allowed to pass through this face.

Fig. 1: Studied cases

Table 1: Dimensions of the 3-D numerical model Top Area 1.025×0.375 m2

Bottom Area 0.750 ×0.125 m2

Depth 0.0575 m

Inlet Diameter 0.01125 m

Outlet Diameter 0.02625 m

Inlet Discharge 0.005 l/s assuming 50 l/s discharge in the field

3.3 Tracer transport To model the residence time of flow within the pond, rhodamine WT was added as a virtual tracer [3, 8, 21]. The properties of Rhodamine WT are molecular mass of 567 g/mole, density of 1030 50 kg/m3 at 25 oC and dynamic viscosity of 1.8×10-3 kg/ms [21].

The tracer was introduced to the software as a volumetric additional variable with units of kg/m3 and kinematic diffusivity of 3.6×10-10 m2/s [8]. The

governing equation for the tracer transport is the Reynolds transport equation:

(4)

where is mixture density (mass per unit volume), is conserved quantity per unit mass, is tracer

concentration, is the velocity field, is a volumetric source term with units of conserved quantity per unit volume per unit time and is kinematic diffusivity for the scalar. For turbulent flows, this equation is Reynolds-averaged:

(5)

where Sct is the turbulence Schmidt Number, and is turbulence viscosity. Sct=0.7-0.8 and is a function of the spread of velocity and mass concentration in the turbulent mixing process [22, 23]. The kinematic diffusivity of the scalar does not significantly affect the tracer transport [15, 24] because it is many orders of magnitude less than turbulence diffusion and can be neglected in simulating turbulent flows [25]. 3.4 Simulation process The simulation was undertaken in two steps. The model was first run for steady state conditions to obtain the solution for the three components of velocity, pressure, momentum, and two turbulence components.

Secondly, the transport equation was solved for transient conditions. Retention time distribution (RTD) curves were analysed by introducing a tracer. The tracer was added as a pulse at the inlet region at the start of the simulation. Using the previously stored values for the velocity field the tracer transport was simulated through a series of consecutive time steps, starting from a very short time step and progressing to relatively long time steps. The latter is appropriate once the tracer has become fully mixed, at which stage it slowly washes out of the pond. The initial time step was 2 seconds, increasing to 10 seconds for the first 18 minutes and then to 100 seconds until the end of simulation with 10 loops in each time step. A root mean square (RMS) residual of 10-6 was used in the transient simulation to get a high level of convergence of the simulated solution. The simulations were run for a time more than the twice the nominal residence time to ensure that at least 80 % of the tracer added had passed the outlet. Two additional points were used, one at the inlet and the other at the outlet, to monitor the amount of the tracer with respect to time. The data observed at the outlet were used to obtain the RTD curves and the data observed at the inlet were used to record the tracer input.

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ISSN: 1790-2769 79 ISBN: 978-960-474-057-4

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ISSN: 1790-2769 80 ISBN: 978-960-474-057-4

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ISSN: 1790-2769 81 ISBN: 978-960-474-057-4

Fig. 6: Simulated flow patterns for the eight cases

5 Conclusions This study shows that the time that each parcel of water resides in the pond depends on the layout and that a layout equipped with an island, subsurface berm or baffle increases the pond performance with respect to short-circuiting, effective volume and hydraulic efficiency. It has been found that an island or a subsurface berm situated a distance downstream from the inlet of one quarter of pond length, increases the residence time and delays the peak concentrations most efficiently. Also the number and position of baffles and the position of an island and subsurface berm are important in terms of performance. References: [1] ARC, Erosion and Sediment Control:

Guidelines for Land Disturbing Activities in Auckland Region, in Auckland Regional Council Technical Publication No. 90. 1999.

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[6] Muttamara, S. and U. Puetpaiboon, Roles of baffles in waste stabilization ponds, Water Science and Technology, 35(8), 1997, p. 275-284.

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1

8 7

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3 2


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stormwater ponds, Ecological Engineering, 10(3), 1998, p. 247-262.

[11] Shilton, A. and J. Harrison, Development of guidelines for improved hydraulic design of waste stabilisation ponds, in Water Science and Technology. 2003. p. 173-180.

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[16] Quarini, G., et al., Hydrodynamic modelling of sedimentation tanks, Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 210(2), 1996, p. 83-91.

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[18] Ta, C.T. and W.J. Brignal, Application of computational fluid dynamics technique to storage reservoir studies, Water Science and Technology, 371998, p. 219-226.

[19] Adamsson, A. and L. Bergdahl, Extending Residence Time in a Detention Tank, Submitted to: Journal of Environmental Engineering, 2004.

[20] Persson, J., N.L.G. Somes, and T.H.F. Wong, Hydraulics efficiency of constructed wetlands and ponds, Water Science and Technology, 40(3), 1999, p. 291-300.

[21] Baawain, M.S., M.G. El-Din, and D.W. Smith, Computational fluid dynamics application in modeling and improving the performance of a storage reservoir used as a contact chamber for microorganism inactivation, Journal of Environmental Engineering and Science, 52006, p. 151-162.

[22] Hassid, S., Turbulent schmidt number for diffusion models in the neutral boundary layer, Atmospheric Environment (1967), 17(3), 1983, p. 523-527.

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ISSN: 1790-2769 83 ISBN: 978-960-474-057-4

modeling the layouts of stormwater retention ponds using ......modeling the layouts of stormwater...

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