# Tracer Experiments and Hydraulic Performance Improvements in a Treatment Pond

^{1}

^{2}

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## Abstract

**:**

## 1. Introduction

## 2. Methods

#### 2.1. Study Area

#### 2.2. Tracer Experiments

^{−1}[27,29,30,31]. Therefore, rhodamine WT was used as a tracer in the present study to observe the flow and diffusion of contaminants in the water body. A 200 mL volume of the tracer with a concentration of 25,000 mg·L

^{−1}was instantaneously added at the pond inlet. At the outlet, variations in the tracer concentration were measured over time to obtain the tracer response curve and the RTD curve and to assess the overall hydraulic performance of the wetland. In addition, a rectangular weir was installed at the outlet to measure the flow rate. A submerged underwater fluorescence meter (Cyclops-7, Turner Designs, San Jose, CA, USA) and an automatic recorder were installed in front of this weir to record changes in the tracer concentration every 30 min. Three different sets of experiments were conducted to assess three different flow rates (0.0026, 0.0011, and 0.0039 m

^{3}·s

^{−1}) at the same water depth (2.0 m).

#### 2.3. Hydraulic Performance

_{v}is the effective volume ratio and N is the number of continuously stirred tank reactors (CSTR) in series. The hydraulic efficiency $\lambda $ can be categorized into three levels: (1) good hydraulic efficiency, $\lambda \ge 0.75$; (2) satisfactory hydraulic efficiency, $0.5<\lambda <0.75$; and (3) poor hydraulic efficiency, $\lambda \le 0.5$.

_{v}indicates the utilization of the effective volume ratio of a detention system:

_{n}is the mean residence time in [h], as shown in Equation (3), and t

_{m}is the nominal retention time in [h] calculated from the first moment of the tracer response curve [6]:

^{3}] and Q is the flow rate in [m

^{3}·s

^{−1}].

^{−1}], t is the time of measurement [h], and t

_{m}is the mean residence time in [h].

_{p}is the time of the peak concentration in the tracer response curve measured at the outlet of the pond in [h].

#### 2.4. Mathematical Model

#### 2.4.1. RMA2 Module

^{−3}]; h is the water depth in [m]; u and v are the velocities in the x- and y-directions, respectively, in [m·s

^{−1}]; E

_{xx}, E

_{yy}, E

_{xy}and E

_{yx}are the eddy viscosity coefficientsin [Pascal·s]; a is the elevation of the bottom in [m]; and τ

_{x}and τ

_{y}are external forces in the x- and y-directions, respectively, in [m·s

^{−2}].

#### 2.4.2. RMA4 Module

^{−1}], D

_{x}and D

_{y}are turbulent mixing (dispersion) coefficients in [m

^{2}·s

^{−1}], σ is the source/sink of the constituent in [μg·L

^{−1}·s

^{−1}], k

_{c}is the first-order decay coefficient of the tracer in [day

^{−1}], and R(c) is the rainfall/evaporation rate. The first-order decay coefficient, k

_{c}, was used in the model to simulate the non-conservative behavior of rhodamine WT [35,36,37].

#### 2.4.3. Determination of Parameters

_{c}, which were determined via the parameter calibration and model verification process described in Section 3.2.1.

#### 2.4.4. Determination of Boundary Conditions

#### 2.4.5. Numerical Experiments

^{3}·s

^{−1}) in cases of different water depths. Nine cases of different inlet and outlet locations were also investigated. The following inlets and outlets were tested: Case IO-0 was the original site design (i.e., inlet and outlet located at the corners); in Case IO-1, the inlet was located at the corner and the outlet at the boundary midpoint; and in Case IO-2, the inlet was located at the corner and the outlet on the diagonal. The flow rate and water depth for the cases of different inlet and outlet locations were set to constant values of 0.002 m

^{3}·s

^{−1}and 2.0 m, respectively.

^{3}·s

^{−1}and 2.0 m, respectively.

## 3. Results and Discussion

#### 3.1. Tracer Experiments

^{−1}) occurred at t = 76.5 h after introduction of the tracer. A second peak appeared at t = 100.0 h. Approximately 10 days after the beginning of the experiment, the tracer concentration returned to the baseline level (Figure 2a). In the second experiment, the peak value of 7.85 μg·L

^{−1}was measured at t = 98.0 h. On approximately the 11th day, the values returned to the baseline (Figure 2b). In the third experiment, a peak value of 10.0 μg·L

^{−1}was measured at t = 75.0 h. On approximately the 8th day, the values returned to the baseline (Figure 2c). The effective volume ratios were estimated as 0.56 in Experiment No. 1 (Exp. 1), 0.25 in Exp. 2, and 0.26 in Exp. 3. The hydraulic efficiencies were calculated as 0.18 in Exp. 1, 0.02 in Exp. 2, and 0.05 in Exp. 3 (Table 1). The pond exhibited a generally poor hydraulic performance. The experiments yielded a complete concentration hydrograph and, because rainfall did not occur during the survey, these data were used to adjust the parameters of the mathematical model.

#### 3.2. Mathematical Model Simulation

#### 3.2.1. Parameter Calibration and Model Verification

_{c}) were adjusted from experiment 1 (calibration) and determined from experiments 2 and 3 (verification). The correlation coefficients (R

^{2}) between field investigations and model simulations were 0.83, 0.62, and 0.66, and they indicated significant dependence between the measured and simulated results (p < 0.01). The simulated and measured tracer concentration values were consistent, except for the background concentrations and tracer tails of all of the experiments and the peak concentrations of experiments 2 and 3. The invalid tracer tails were due to transient storage, which was attributable to hyporheic exchange [28]. Although most areas of pond bed were embedded with concrete, other areas such as the pond bank exhibited possible signs of lateral hyporheic exchange through the bank (S.S. Shih, personal observations). Although the model simulations did not yield background and peak concentrations that were consistent with field observations, the key hydraulic parameters derived from the method of moments were not affected [26], suggesting comparable values of effective volume ratio and hydraulic efficiency (Table 1). The results indicated that the mathematical model simulations yielded acceptable calculations of hydraulic performance.

#### 3.2.2. Flow Hydrodynamics and Hydraulic Performance

^{−1}to 0.0001 m·s

^{−1}in the shallow-water area and from 0.00001 m·s

^{−1}to 0.00008 m·s

^{−1}in the deep-water area. The water depth ranged from 0.8 m to 1.2 m in the shallow-water area and from 1.2 m to 2.5 m in the deep-water area. The Froude number ranged from 0.32 to 0.56 in the shallow-water area and from 0.12 to 0.39 in the deep-water area, which indicated a subcritical flow condition in the entire pond. The results indicated a low velocity, deeper water, and non-uniform flow conditions in the deep-water area relative to those in the shallow-water area. The dead zones (i.e., areas with a flow velocity below 0.00005 m·s

^{−1}) occurred in the upper right corner and lower left corner of the deep-water area, which may have decreased the hydraulic performance by inhibiting water exchange with other zones. A region of short-circuited flow (i.e., a region of high flow velocity) was observed from the lower right corner to the upper left corner of the deep-water area, which may have reduced the residence time and flow uniformity and thereby decreased the hydraulic performance and treatment efficiency. The poor hydraulic efficiency resulted primarily from short-circuited flow and the presence of a dead zone in the deep-water area. Hydraulically, treatment efficiency is considered satisfactory as long as the system is well mixed and the physical characteristics are uniform across the wetland perpendicular to the flow [40]. The poor treatment efficiencies of suspended solids were detected due to the occurrence of short-circuited flow. In addition, a low nitrogen removal rate was likely due to the dead zone in the deep-water area. The results may be different for other pollutants, such as biochemical oxygen demand (BOD), for which adsorption does not occur.

#### 3.3. Changing the Flow Rate and Water Depth to Improve Hydraulic Performance

#### 3.3.1. Flow Rate

^{3}·s

^{−1}to 0.010 m

^{3}·s

^{−1}) decreased the nominal retention time (t

_{n}), mean residence time (t

_{m}) and time of peak concentration (t

_{p}) values. The effective volume ratio and the hydraulic efficiency increased with increasing flow rate. The increase in the flow rate exhibited a positive linear relationship with the hydraulic efficiency (Figure 4). When the flow rate was increased to 0.010 m

^{3}·s

^{−1}, the hydraulic efficiency increased to a satisfactory level (λ = 0.74).

#### 3.3.2. Water Depth

_{m}) and the nominal retention time (t

_{n}) was reduced, which increased the effective volume ratio. In addition, at greater water depths, longer mean residence time (t

_{m}) values and lower effective volume ratios were observed, which resulted in a reduction in hydraulic efficiency. Water depth exhibited a negative linear relationship with hydraulic efficiency (Figure 5). By decreasing the water depth of the pond outlet to 1.4 m, the hydraulic efficiency was increased to 0.30, which indicated a poor hydraulic level. Decreasing the downstream water depth yielded slight improvements in the effective volume ratio and hydraulic efficiency.

#### 3.4. Altering Inlet and Outlet Locations to Improve Hydraulic Performance

#### 3.5. Adding Emergent Baffles to Improve Hydraulic Performance

## 4. Conclusions

## Acknowledgments

## Author Contributions

## Conflicts of Interest

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**Figure 1.**Location of the study area. The blue arrows indicate the flow inlet and outlet, and the schematic shows the main flow direction.

**Figure 2.**Results of mathematical model validation: (

**a**) measurements from Exp. 1 for model calibration; (

**b**) measurements from Exp. 2 for the first verification; and (

**c**) measurements from Exp. 3 for the second verification. The correlation coefficients (R

^{2}) were 0.83, 0.62, and 0.66. The eddy viscosity (E), dispersion coefficient (D), and decay coefficient (K

_{c}) were determined to be 12, 0.012, and 0.21, respectively.

**Figure 3.**(

**a**) Finite element mesh; (

**b**) bathymetry; (

**c**) flow direction; (

**d**) flow velocity; (

**e**) water depth; and (

**f**) tracer concentration distribution in the pond.

**Figure 4.**(

**a**) Tracer concentration hydrograph and (

**b**) hydraulic efficiency at the pond outlet across the entire pond for different flow rates.

**Figure 5.**(

**a**) Tracer concentration hydrograph and (

**b**) hydraulic efficiency at the pond outlet across the entire pond for different water depths.

**Figure 6.**Spatial distribution of the flow velocity in the treatment pond for different inlet and outlet configurations. Case IO-0 represents the current conditions of the pond, and the other cases represent scenarios for improving the hydraulic efficiency. The blue arrows indicate the flow inlet and outlet. The hydraulic efficiency is shown in parentheses according to the name of each scenario.

**Figure 7.**Spatial distribution of the flow velocity in the pond after installing a single baffle with different dimensions in different locations. Case ob1-0 represents the current conditions, and the other cases represent the experimental scenarios. The blue arrows indicate the flow inlet and outlet, whereas the white rectangular bars represent the baffles. The hydraulic efficiency is shown in parentheses according to the name of each scenario.

**Figure 8.**Spatial distribution of the flow velocity in the pond after installing two baffles in different locations with different dimensions. The blue arrows indicate the flow inlet and outlet, whereas the white rectangular bars represent the baffles. The hydraulic efficiency is shown in parentheses according to the name of each scenario.

**Table 1.**Model validation by field measurements of hydraulic retention time, effective volume ratio, and hydraulic efficiency.

Experiment | t_{n} (h) | t_{m} (h) | t_{p} (h) | e_{v} | λ | |
---|---|---|---|---|---|---|

1 | Field | 239.6 | 134.2 | 76.5 | 0.56 | 0.18 |

Model | 239.6 | 135.8 | 66.5 | 0.57 | 0.16 | |

2 | Field | 860.3 | 169.4 | 98.0 | 0.25 | 0.02 |

Model | 860.3 | 211.6 | 90.0 | 0.25 | 0.03 | |

3 | Field | 354.8 | 90.6 | 75.0 | 0.26 | 0.05 |

Model | 354.8 | 135.1 | 68.5 | 0.38 | 0.07 |

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**MDPI and ACS Style**

Shih, S.; Zeng, Y.; Lee, H.; Otte, M.L.; Fang, W. Tracer Experiments and Hydraulic Performance Improvements in a Treatment Pond. *Water* **2017**, *9*, 137.
https://doi.org/10.3390/w9020137

**AMA Style**

Shih S, Zeng Y, Lee H, Otte ML, Fang W. Tracer Experiments and Hydraulic Performance Improvements in a Treatment Pond. *Water*. 2017; 9(2):137.
https://doi.org/10.3390/w9020137

**Chicago/Turabian Style**

Shih, Shang‐Shu, Yun‐Qi Zeng, Hong‐Yuan Lee, Marinus L. Otte, and Wei‐Ta Fang. 2017. "Tracer Experiments and Hydraulic Performance Improvements in a Treatment Pond" *Water* 9, no. 2: 137.
https://doi.org/10.3390/w9020137