Modeling the Layouts of Stormwater Retention Ponds using Residence Time

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1 Modeling 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 Abstract: - One of principal methods to treat stormwater runoff is stormwater retention ponds. In order to make se ponds hydraulically efficient, y should be designed to give maximum residence time to settle out suspended solids. In this study, effect of pond layout on residence time is investigated. A trapezoidal pond having top dimensions m m, depth 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 basis of residence time and compared to determine optimal pond design. Investigation of hydraulic parameters showed that an island or subsurface berm at a distance of one quarter of pond length from inlet gives 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 downstream ecosystem. The use of retention ponds on construction sites to treat stormwater runoff has increased rapidly during last ten years in Auckland, New Zealand, which is area under consideration in this study. Among or reasons, this is due to growing environmental awareness about 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 marine ecosystem and fresh water bodies, if not controlled on site. The use of storm water retention ponds is one of solutions to control se sediments [1]. For effective sedimentation, design of pond should be such that it provides sufficient residence time to settle 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 settling rate of suspended solids. Residence time is influenced by a number of factors including pond layout which is very important. Many researchers reported impact of pond layout (including use of baffles and an island) on pond residence time [2-10]. In most of studies, 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 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 above studies, two methods were adopted to model residence time, i.e. physical modeling and numerical modeling. The major limitations of physical modeling are that measurements can be made only after construction of a pond, which can be costly in space and time. Numerical modeling has some advantages over physical modeling, such as 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 interest in computational fluid dynamic (CFD) modeling. The selection of an appropriate CFD model, 2D or 3D, depends on nature of problem. A 3D model is complex and time consuming but provides much more detailed information as compared to 2D model, especially for a study involving pond hydraulics [3, 14, 15]. ISSN: ISBN:

2 In previous studies, simulations of 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 assumption that side slopes can be neglected due to large size of 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 side slopes. In present study, trapezoidal pond geometry is employed and circular pipe is used for inlet and outlet. These conditions are in accordance with most of field ponds. A 3-D numerical model was developed using ANSYS CFX 11.0 software to simulate hydraulic performance of a scaled down physical model of existing flocculation pond at Alpurt B2 Motorway site in Auckland, New Zealand. To study effect of pond layout on pond residence time, 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 basis of only one of se hydraulic parameters can give different results [19]. Therefore, comparison made in this study is based on three hydraulic parameters, which are described below. First, short-circuiting factor S is defined as (1) where t 16 is time when 16th percentile of tracer added at inlet has passed outlet and t 50 is time when half of tracer added at inlet has passed outlet. A value of S factor lower than 0.3 indicates shortcircuiting and a value higher than 0.4 is acceptable for an efficient pond [9]. Short circuiting is a situation in which some of water parcels reach outlet in a time less than 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, effective volume ratio is defined as ratio of mean residence time to nominal residence time. (2) In this study, mean residence time is replaced by median residence time (t 50 ). This simplification has advantage that re is no need to carry out simulations or measurements until 100% of tracer has reached 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 fluid particles reside in system around 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 time is time at which peak tracer concentration reaches 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, studied cases represent small ponds, being based on assumption of limited provision of space in field. A total of eight different cases were studied having same basic pond shape but with different internal geometries which represent most of possible scenarios of pond layouts. The studied cases are: Case 1 (no baffle) Case 2 (single baffle at one quarter of pond length from 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 inlet) Case 6 (an island placed at one tenth of pond length from inlet) Case 7 (a subsurface berm placed at one quarter of pond length from 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 Model set-up A 3-D numerical model, of similar geometry to that used in field, was developed. The model pond was ISSN: ISBN:

3 trapezoidal in cross-section with side slopes of 2:1(h: v). The circular inlet and outlet were positioned at top centre of ends of pond. The details of model are given in Table 1. For this study, 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 inlet while outlet was modelled as a pressure outlet assuming zero static pressure. The flow direction was set normal to inlet boundary condition and turbulence intensity at inlet was set at 1-5%. All or default 2-D regions, like sides and bottom of pond, were modelled as walls with no slip boundary conditions. The top of pond was set as a free surface and no fluid was allowed to pass through this face. Outlet Fig. 1: Studied cases Table 1: Dimensions of 3-D numerical model Top Area m 2 Bottom Area m 2 Depth Inlet Diameter Outlet Diameter Inlet Discharge Inlet m m m l/s assuming 50 l/s discharge in field 3.3 Tracer transport To model residence time of flow within 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 kg/m 3 at 25 o C and dynamic viscosity of kg/ms [21]. The tracer was introduced to software as a volumetric additional variable with units of kg/m 3 and kinematic diffusivity of m 2 /s [8]. The governing equation for tracer transport is Reynolds transport equation: (4) where is mixture density (mass per unit volume), is conserved quantity per unit mass, is tracer concentration, is velocity field, is a volumetric source term with units of conserved quantity per unit volume per unit time and is kinematic diffusivity for scalar. For turbulent flows, this equation is Reynolds-averaged: (5) where Sc t is turbulence Schmidt Number, and is turbulence viscosity. Sc t = and is a function of spread of velocity and mass concentration in turbulent mixing process [22, 23]. The kinematic diffusivity of scalar does not significantly affect 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 solution for three components of velocity, pressure, momentum, and two turbulence components. Secondly, 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 inlet region at start of simulation. Using previously stored values for velocity field 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 tracer has become fully mixed, at which stage it slowly washes out of pond. The initial time step was 2 seconds, increasing to 10 seconds for first 18 minutes and n to 100 seconds until end of simulation with 10 loops in each time step. A root mean square (RMS) residual of 10-6 was used in transient simulation to get a high level of convergence of simulated solution. The simulations were run for a time more than twice nominal residence time to ensure that at least 80 % of tracer added had passed outlet. Two additional points were used, one at inlet and or at outlet, to monitor amount of tracer with respect to time. The data observed at outlet were used to obtain RTD curves and data observed at inlet were used to record tracer input. ISSN: ISBN:

4 4 Results and discussion 4.1 Residencee time distribution by tracer study The RTD curves for eight different cases are a representation of tracer distribution and its movement through pond and indicate time that each water parcel resides in pond. To compare peaks of RTD curves, actual concentration (c) is normalized using a reference concentration (c o ), where c o is concentration addedd as a pulse during first 30 seconds. Comparison of se curves shows how peak concentration of tracer leaving pond at outlet is delayedd for different layouts, directly indicating residence times for each case. Fig. 3: Tracerr responses for layouts undertaken with baffles Fig. 2: Simulated tracer response of basic pond (Case 1) Baffles The RTD curves for simulations undertaken with baffles (Cases 2, 3 and 4 in fig. 1) are shown in fig. 3. It is apparent that time taken for first portion of water to reach outlet depends on layout (fig. 3). The results show that placing baffles in front of inlet increases hydraulic performance by increasing residence time and delaying peak tracer Tracer responses for different layouts are given in Figs. 2 to 5 while Fig. 6 shows simulated flow patterns for each case tested. The RTD for basic pond features three peaks (fig. 2). The first peak, which occurred after a very short time of tracer injection is steep and indicates strong short- circuiting. The peak occurred after 5 minutes of injection of tracer as compared to 43 minutes nominal residence time, demonstrating poor performance for this layout (fig. 2). The or two peaks indicate recirculation. The second peak of RTD curve may be due to tracer movement in eddies near inlet. Similar results have been reported by Wood et al and Adamsson et al The hydraulic efficiency and effective volume for this case were 12% and 62%, respectively, with 79% short-circuiting (table 2). concentration at outlet as compared to basic layout (fig. 3). The comparison of RTD curves in fig. 3 shows that Case 2 features a slightly delayed peak indicating relatively poor performance with respect to short-circuiting, effective volume and hydraulic efficiency (table 2). Case 3 features a longer delay in peak tracer concentration, providing reduced short-circuiting as compared to Cases 1, 2 and 4 (table 2). The shortcircuiting was 47% for Case 3 and increased to 52% when number of baffles was increased to three (Case 4). This should be compared to basic shape (Case 1) having 79% short-circuiting (table 2). The tracer concentration peaks occurred 5, 17 and 12 minutes after first injection of tracer for Cases 1, 3 and 4 respectively, whereas tracer concentration peak in Cases 1 and 2 occurred at about same time. This shows that, compared to Case 1, peak was delayed 12 minutes for Case 3 and 7 minutes for Case 4, indicating that increasing number of baffles may have a negative effect on over-all residence time as compared to case of one baffle at one half of pond length (Case 3). This may be due to narrow channelization of flow in pond in case of three baffles (Case 4 in fig. 6). It seems from se resultss that position and number of baffles is very important in modeling residence time Island and subsurface berm Cases 5 and 7 feature square island and a subsurface berm at one quarter of pond length from inlet, respectively. The results show that island and subsurface berm have some advantages over baffles in terms of residence time, hydraulic efficiency and short- parameters shows that Case 5 gives best hydraulic performance (table 2). Furr investigation showed circuiting (fig. 4 and table 2). Comparison of above cases in terms of hydraulic that ISSN: ISBN:

5 an island and a subsurface berm at a distance of one quarter of pond length give almost similar performance in terms of hydraulic efficiency, effective volume and short circuiting (table 2). The effective volume for case of an island placed at a distance of one quarter of pond length (Case 5 in fig. 1) was 88% and hydraulic efficiency was 77% as compared to basic layout for which effective volume 62 % and hydraulic efficiency 12% (table 2). The time of peak concentration was 5 minutes for Case 1, 34 minutes for Case 5 and 17 minutes for one baffle (Case 3) which shows that peak is delayed by 29 minutes for Case 5. The island gives more than 100% delay in peak concentration compared to a baffle at half of pond length (Case 3). This may be due to eddies before and after baffle which directed flow along a narrow path reducing residence time and effective volume (Case 3 in fig. 6). table 2). When subsurface berm is moved away from inlet at half of pond length (Case 8), it resulted in a short peak as compared to Cases 5, 6 and 7. Compared to Case 7, short-circuiting in Case 8 was increased by 50% and effective volume and hydraulic efficiency were reduced by 6% and 22.8% respectively (table 2). This shows that moving subsurface berm away from position of one quarter of pond length results in a poor performance. Fig. 4: Tracer responses undertaken for different layouts with island, subsurface berm and baffle The effects of position of island and subsurface berm on residence time and hydraulic efficiency are investigated. Two positions of island (Cases 5 and 6 in fig. 1) and two positions of subsurface berm (Cases 7 and 8 in fig. 1) were studied and compared. Case 6 resulted in a higher and steeper peak compared to Case 5 (fig. 5). The short-circuitinwhile effective volume and for Case 6 was increased 20% hydraulic efficiency were reduced 12.5% and 30% as compared to Case 5 (table 2). These results show that ree is a negative effect on overall performance of pond by moving island towards inlet (fig. 5 and Fig. 5: Tracerr responses undertaken for layouts with different positions of island and subsurface berm. Table 2: Calculated hydraulic parameters for eight cases, t n = V/Q = 43 min Case Case 1 Case 2 Case 3 Case 4 Case 5 Case 6 Case 7 Case 8 e S shortcircuiting λ ISSN: ISBN:

6 Fig. 6: Simulated flow patterns for eight cases 5 Conclusions This study shows that time that each parcel of water resides in pond depends on layout and that a layout equipped with an island, subsurface berm or baffle increases 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 inlet of one quarter of pond length, increases residence time and delays peak concentrations most efficiently. Also number and position of baffles and 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 [2] Abbas, H., R. Nasr, and H. Seif, Study of waste stabilization pond geometry for wastewater treatment efficiency, Ecological Engineering, 28(1), 2006, p [3] Adamsson, A., Three-dimensional simulation and physical modelling of flows in detention tanks - Studies of flow pattern, residence time and sedimentation, Doktorsavhandlingar vid Chalmers Tekniska Hogskola, (2116), [4] Bracho, N., B. Lloyd, and G. Aldana, Optimisation of hydraulic performance to maximise faecal coliform removal in maturation ponds, Water Research, 40(8), 2006, p [5] Koskiaho, J., Flow velocity retardation and sediment retention in two constructed wetlandponds, Ecological Engineering, 19(5), 2003, p [6] Muttamara, S. and U. Puetpaiboon, Roles of baffles in waste stabilization ponds, Water Science and Technology, 35(8), 1997, p [7] Persson, J., The hydraulic performance of ponds of various layouts, Urban Water, 2(3), 2000, p [8] Shilton, A., Studies into hudraulics of waste stabilization ponds, in Environmental Engineering. 2001, Massey University. [9] Thackston, E.L., F.D. Shields Jr, and P.R. Schroeder, Residence time distributions of shallow basins, Journal of Environmental Engineering, 116(6), [10] Walker, D.J., Modelling residence time in ISSN: ISBN:

7 stormwater ponds, Ecological Engineering, 10(3), 1998, p [11] Shilton, A. and J. Harrison, Development of guidelines for improved hydraulic design of waste stabilisation ponds, in Water Science and Technology p [12] Shilton, A.N. and D.D. Mara, CFD (computational fluid dynamics) modelling of baffles for optimizing tropical waste stabilization pond systems, in Water Science and Technology p [13] Vega, G.P., et al., Application of CFD modelling to study hydrodynamics of various anaerobic pond configurations, in Water Science and Technology p [14] Wood, M.G., et al., Two dimensional computational fluid dynamic models for waste stabilisation ponds, Water Research, 32(3), 1998, p [15] Adamsson, A., L. Bergdahl, and S. Lyngfelt, Measurement and three-dimensional simulation of flow in a rectangular detention tank, Urban Water Journal, 2(4), 2005, p [16] Quarini, G., et al., Hydrodynamic modelling of sedimentation tanks, Proceedings of Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 210(2), 1996, p [17] Reddy, S., et al., Improving Clearwell Design Using Computational Fluid Dynamics, in WRPMD 1999, Tempe, Arizona, USA: ASCE. [18] Ta, C.T. and W.J. Brignal, Application of computational fluid dynamics technique to storage reservoir studies, Water Science and Technology, , p [19] Adamsson, A. and L. Bergdahl, Extending Residence Time in a Detention Tank, Submitted to: Journal of Environmental Engineering, [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 [21] Baawain, M.S., M.G. El-Din, and D.W. Smith, Computational fluid dynamics application in modeling and improving performance of a storage reservoir used as a contact chamber for microorganism inactivation, Journal of Environmental Engineering and Science, 52006, p [22] Hassid, S., Turbulent schmidt number for diffusion models in neutral boundary layer, Atmospheric Environment (1967), 17(3), 1983, p [23] Koeltzsch, K., The height dependence of turbulent Schmidt number within boundary layer, Atmospheric Environment, 34(7), 2000, p [24] Jayanti, S., Hydrodynamics of jet mixing in vessels, Chemical Engineering Science, 56(1), 2001, p [25] Daily, J.W. and D.R.F. Harleman, Fluid dynamics [by] James W. Daily [and] Donald R. F. Harleman: Addison-Wesley Publishing Company, Inc. Reading, Massachusetts USA., ISSN: ISBN:

TRACER STUDIES ON AN AERATED LAGOON

TRACER STUDIES ON AN AERATED LAGOON Alistair Broughton 1 and Andy Shilton 2 1 CPG New Zealand Ltd, Private Bag 562, Palmerston North, New Zealand adbroughton@gmail.com 2 School of Engineering and Advanced