# Physical Experiment and Numerical Simulation of the Artificial Recharge Effect on Groundwater Reservoir

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Physical Model

#### 2.1. Experiment Setup

#### 2.2. Experimental Method

_{s}) and the ESR (β) in time t can be obtained from the following equations:

_{s}(t) is the ESC of the groundwater reservoir; S

_{y}is the specific yield of the aquifer; V*(t) is the groundwater storage variation volume; β(t) is the effective storage rate; and, Q

_{r}(t) is the quantity of artificial recharge.

_{t}) are different in every point, it is difficult to calculate the difference between instant and initial groundwater level directly. Using the calculus equation (Equation (3)), which was developed by Equation (1) and Equation (2), can simplify the process of calculating the groundwater storage variation volume (V*) in the aquifer. V* is equal to the area surrounded by the groundwater levels in 0 and t s, which can be easily measured (Figure 3).

_{0}is initial groundwater level, h

_{0}= f

_{0}(x); h

_{t}is groundwater level after artificial recharge for t seconds, h

_{t}= f

_{t}(x); and, A (t) is the area surrounded by the groundwater levels in 0 and t s.

#### 2.3. Experimental Results

#### 2.3.1. Effect of Relative Distance between Infiltration Basin and Pumping Well

_{s})—distance (s) relationship curves and the ESR (β)—distance (s) relationship curves were shown in Figure 4 and Figure 5.

#### 2.3.2. Effect of Recharge Intensity

_{s})—recharge intensity, (q) relationship curves (Figure 6), and the ESR (β)—recharge intensity (q) relationship curves (Figure 7) in different time periods were drawn separately.

## 3. Numerical Simulations

#### 3.1. Model Setup

^{2}; thus, the simulation accuracy can meet the requirements of the study. The initial time step is specified as 0.1 s, and automatic time steps are used during an 1800 s simulation period. A pumping well is set at the model with a pumping rate of 6 mL/s and is located 130 cm away from left side. Two types of hydrogeology boundaries are presented in Figure 8, including the Dirichlet boundary condition and Neumann boundary condition. Two Dirichlet boundaries are set on the left (30 cm) and right (25 cm) sides to simulate the constant head boundaries at both sides, and the Neumann boundary condition is used to simulate the infiltration basin in the top of the model. At the bottom of the model, two observation points are chosen beneath the infiltration basin and pumping well, as the observation points 1 and 2, respectively.

_{i}is the simulated value at time-step i; O

_{i}is the observed flow at time-step i; and, Ō is the average value of the observed flow.

#### 3.2. Simulation Results

#### 3.2.1. Analysis of Water Balance

_{i}is inflow rate; q

_{o}is outflow rate.

#### 3.2.2. Analysis of Influencing Factors

_{s}) and the time (t), as well as that the correlation of the ESR (β) change with time (t).

_{max}is the maximum ESC (maximum storage capacity); a is the time parameter; and, q is the recharge intensity.

_{max}) is an important index to estimate the ESC and the ESR in the study of groundwater reservoir artificial recharge effect. In this paper, Q

_{max}is mainly affected by the recharge intensity (q) and relative distance (s) between the infiltration basin and pumping well. The correlation between Q

_{max}and s, q (Figure 15) is shown as in the fitting equation (Equation (8)). The maximum capacity and distance would be in a quadratic function relationship. The relationship between maximum capacity and q is a linear function, which is the same as it have mentioned in the physical experiment. Using this binomial regression model can illustrate the relationship of recharge intensity and location of the infiltration basin in practical problems.

#### 3.2.3. Analysis of the Effect of intermittent Recharge

## 4. Conclusions

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## References

- Scanlon, B.R.; Keese, K.E.; Flint, A.L.; Flint, L.E.; Gaye, C.B.; Edmunds, W.M.; Simmers, I. Global synthesis of groundwater recharge in semiarid and arid regions. Hydrol. Process.
**2006**, 20, 3335–3370. [Google Scholar] [CrossRef] - Orellana, F.; Verma, P.; Ii, S.P.L.; Daly, E. Monitoring and modeling water-vegetation interactions in groundwater-dependent ecosystems. Rev Geophys.
**2012**, 50, RG3003. [Google Scholar] [CrossRef] - Zhao, T.S. Discussion of problems for groundwater reservoir. Hydrogeol. Eng. Geol.
**2002**, 29, 65–67. (In Chinese) [Google Scholar] - Li, L.W.; Shu, L.C.; Yin, Z.Z. Concept and design theory of groundwater reservoir. J. Hydraul. Eng.
**2006**, 13, 123–132. [Google Scholar] - Pyne, R.D.G. Groundwater Recharge and Wells: A Guide to Aquifer Storage and Recovery; CRC Press: Boca Raton, FL, USA, 1995; p. 401. [Google Scholar]
- Ward, J.D.; Simmons, C.T.; Dillon, P.J. A theoretical analysis of mixed convection in aquifer storage and recovery: How important are density effects? J. Hydrol.
**2007**, 343, 169–186. [Google Scholar] [CrossRef] - Page, D.W.; Peeters, L.; Vanderzalm, J.; Barry, K.; Gonzalez, D. Effect of aquifer storage and recovery (ASR) on recovered stormwater quality variability. Water Res.
**2017**, 117, 1–8. [Google Scholar] [CrossRef] [PubMed] - Zhang, G.; Feng, G.; Li, X.; Xie, C.; Pi, X. Flood effect on groundwater recharge on a typical silt loam soil. Water
**2017**, 9, 523. [Google Scholar] [CrossRef] - Ong’Or, B.T.I.; Shu, L.C. Groundwater overdraft and the impact of artificial recharge on groundwater quality in a cone of depression, Jining, China. Water Int.
**2009**, 34, 468–483. [Google Scholar] [CrossRef] - Zhang, Y.; Wu, J.C.; Xue, Y.Q.; Wang, Z.C.; Yao, Y.G.; Yan, X.X.; Wang, H.M. Land subsidence and uplift due to long-term groundwater extraction and artificial recharge in Shanghai, China. Hydrogeol. J.
**2015**, 23, 1851–1866. [Google Scholar] [CrossRef] - Shi, X.Q.; Jiang, S.M.; Xu, H.X.; Jiang, F.; He, Z.F.; Wu, J.C. The effects of artificial recharge of groundwater on controlling land subsidence and its influence on groundwater quality and aquifer energy storage in Shanghai, China. Environ. Earth
**2016**, 75, 1–18. [Google Scholar] [CrossRef] - Sophiya, M.S.; Syed, T.H. Assessment of vulnerability to seawater intrusion and potential remediation measures for coastal aquifers: A case study from eastern India. Environ. Earth.
**2013**, 70, 1197–1209. [Google Scholar] [CrossRef] - Thompson, A.; Nimmer, M.; Misra, D. Effects of variations in hydrogeological parameters on water-table mounding in sandy loam and loamy sand soils beneath stormwater infiltration basins. Hydrogeol. J.
**2010**, 18, 501–508. [Google Scholar] [CrossRef] - Nimmer, M.; Thompson, A.; Misra, D. Modeling water table mounding and contaminant transport beneath stormwater infiltration basins. J. Hydrol. Eng.
**2010**, 15, 963–973. [Google Scholar] [CrossRef] - Du, S.H.; Su, X.X.; Zhang, W.J. Effective storage rates analysis of groundwater reservoir with surplus local and transferred water used in Shijiazhuang City, China. Water Resour. Manag.
**2013**, 27, 157–169. [Google Scholar] [CrossRef] - Dillon, P. Future management of aquifer recharge. Hydrogeol. J.
**2005**, 13, 313–316. [Google Scholar] [CrossRef] - Maréchal, J.C.; Dewandel, B.; Ahmed, S.; Galeazzi, L.; Zaidi, F.K. Combined estimation of specific yield and natural recharge in a semi-arid groundwater basin with irrigated agriculture. J. Hydrol.
**2006**, 329, 281–293. [Google Scholar] [CrossRef] - Stauffer, F.; Attinger, S.; Zimmermann, S.; Kinzelbach, W. Uncertainty estimation of well catchments in heterogeneous aquifers. Water Res.
**2002**, 38, 20–21. [Google Scholar] [CrossRef] - Manghi, F.; Mortazavi, B.; Crother, C.; Hamdi, M.R. Estimating regional groundwater recharge using a hydrological budget method. Water Resour. Manag.
**2009**, 23, 2475–2489. [Google Scholar] [CrossRef] - Hernández-Espriú, A.; Arango-Galván, C.; Reyes-Pimentel, A.; Martínez-Santos, P.; Paz, C.P.D.L.; Macías-Medrano, S. Water supply source evaluation in unmanaged aquifer recharge zones: The mezquital valley (Mexico) case study. Water
**2016**, 9, 4. [Google Scholar] [CrossRef] - Sharda, V.N.; Kurothe, R.S.; Sena, D.R.; Pande, V.C.; Tiwari, S.P. Estimation of groundwater recharge from water storage structures in a semi-arid climate of India. J. Hydrol.
**2006**, 329, 224–243. [Google Scholar] [CrossRef] - Crosbie, R.S.; Binning, P.; Kalma, J.D. A time series approach to inferring groundwater recharge using the water table fluctuation method. Water Resour. Res.
**2005**, 41, 287–295. [Google Scholar] [CrossRef] - Niazi, A.; Prasher, S.O.; Adamowski, J.; Gleeson, T. A system dynamics model to conserve arid region water resources through aquifer storage and recovery in conjunction with a dam. Water
**2014**, 6, 2300–2321. [Google Scholar] [CrossRef] - Kasper, J.W.; Denver, J.M.; McKenna, T.E.; Ullman, W.J. Simulated impacts of artificial groundwater recharge and discharge on the source area and source volume of an Atlantic coastal plain stream, Delaware, USA. Hydrogeol. J.
**2010**, 18, 1855–1866. [Google Scholar] [CrossRef] - Edwards, E.C.; Harter, T.; Fogg, G.E.; Washburn, B.; Hamad, H. Assessing the effectiveness of drywells as tools for stormwater management and aquifer recharge and their groundwater contamination potential. J. Hydrol.
**2016**, 539, 539–553. [Google Scholar] [CrossRef] - Clement, T.P.; Kim, Y.C.; Gautam, T.R.; Lee, K.K. Experimental and numerical investigation of DNAPLdissolution processes in a laboratory aquifer model. Groundwater Monit. Remediat.
**2004**, 24, 88–96. [Google Scholar] [CrossRef] - Hans, J.G. DHI-WASY Software FEFLOW Reference Manual; DHI WASY GmbH: Berlin, Germany, 2005. [Google Scholar]
- Nash, J.E.; Sutcliffe, J.V. River flow forecasting through conceptual models part I—A discussion of principles. J. Hydrol.
**1970**, 10, 282–290. [Google Scholar] [CrossRef]

**Figure 9.**Comparison between observed and simulated groundwater levels at pressure sensor point 2, 5, 8.

**Figure 10.**Comparison between observed and simulated groundwater levels at time of: (

**a**) 0 min; (

**b**) 1 min; (

**c**) 2 min; (

**d**) 3 min; (

**e**) 5 min; and, (

**f**) 15 min.

Content (%) | <10 | <25 | <50 | <75 | <90 | Average | Mid-Value |
---|---|---|---|---|---|---|---|

Diameter(um) | 310.5 | 401.8 | 509.6 | 630.8 | 749.8 | 520.4 | 509.6 |

Pressure Sensor Point | 2 | 5 | 8 |
---|---|---|---|

NSE | 0.973 | 0.936 | 0.797 |

Time Period (s) | Inflow | Outflow | Storage Variation (mL) | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|

Lateral Inflow | Artificial Recharge | Total (mL) | Lateral Outflow | Artificial Exploitation | Total (mL) | ||||||

Quantity (mL) | Percentage (%) | Quantity (mL) | Percentage (%) | Quantity (mL) | Percentage (%) | Quantity (mL) | Percentage (%) | ||||

0.0 | 0.0 | - | 0.0 | - | 0.0 | 0.0 | - | 0.0 | - | 0.0 | 0.0 |

1.3 | 80.7 | 57.0 | 60.8 | 43.0 | 141.5 | 0.0 | 0.0 | 81.0 | 100.0 | 81.0 | 60.5 |

14.0 | 825.1 | 56.4 | 638.7 | 43.6 | 1463.8 | 0.0 | 0.0 | 837.5 | 100.0 | 837.5 | 626.3 |

32.3 | 1800.3 | 54.6 | 1495.4 | 45.4 | 3295.8 | 1.1 | 0.1 | 1936.4 | 99.9 | 1937.6 | 1358.2 |

79.3 | 3944.7 | 51.5 | 3717.6 | 48.5 | 7662.3 | 234.7 | 4.7 | 4758.5 | 95.3 | 4993.2 | 2669.1 |

145.6 | 6810.0 | 49.8 | 6874.0 | 50.2 | 13,684.0 | 1094.1 | 11.1 | 8735.2 | 88.9 | 9829.3 | 3854.7 |

325.5 | 14,323.1 | 48.1 | 15,475.6 | 51.9 | 29,798.7 | 4519.6 | 18.8 | 19,529.9 | 81.2 | 24,049.5 | 5749.2 |

581.7 | 24,470.1 | 46.9 | 27,748.2 | 53.1 | 52,218.3 | 10,231.7 | 22.7 | 34,902.2 | 77.3 | 45,133.8 | 7084.4 |

1244.3 | 49,380.7 | 45.3 | 59,517.9 | 54.7 | 108,898.6 | 26,141.8 | 25.9 | 74,659.8 | 74.1 | 100,801.7 | 8096.9 |

1800.0 | 69,855.7 | 44.8 | 86,175.5 | 55.2 | 156,031.2 | 39,776.7 | 26.9 | 108,000.0 | 73.1 | 147,776.7 | 8254.5 |

Scenario | Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | Scenario 5 |
---|---|---|---|---|---|

recharge intensity (mL/s) | 2.4 | 3.6 | 4.8 | 6 | 7.2 |

recharge time(s) | 150 | 100 | 75 | 60 | 50 |

interval time(s) | 0 | 50 | 75 | 90 | 100 |

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**MDPI and ACS Style**

Xu, Y.; Shu, L.; Zhang, Y.; Wu, P.; Atlabachew Eshete, A.; Mabedi, E.C.
Physical Experiment and Numerical Simulation of the Artificial Recharge Effect on Groundwater Reservoir. *Water* **2017**, *9*, 908.
https://doi.org/10.3390/w9120908

**AMA Style**

Xu Y, Shu L, Zhang Y, Wu P, Atlabachew Eshete A, Mabedi EC.
Physical Experiment and Numerical Simulation of the Artificial Recharge Effect on Groundwater Reservoir. *Water*. 2017; 9(12):908.
https://doi.org/10.3390/w9120908

**Chicago/Turabian Style**

Xu, Yang, Longcang Shu, Yongjie Zhang, Peipeng Wu, Abunu Atlabachew Eshete, and Esther Chifuniro Mabedi.
2017. "Physical Experiment and Numerical Simulation of the Artificial Recharge Effect on Groundwater Reservoir" *Water* 9, no. 12: 908.
https://doi.org/10.3390/w9120908