Simulation of Saline and Fresh Water Interference in Saturated and Unsaturated Zones Using Physical and Hydrus-2D Model

Document Type : Research Article

Authors

1 MSc Student in Department of Irrigation & Reclamation Engineering, Campus of Agriculture and Natural Resources, University of Tehran

2 Professor in Department of Irrigation & Reclamation Engineering, Campus of Agriculture and Natural Resources, University of Tehran

3 Assistant Professor Water Sciences and Engineering Department Imam Khomeini International University, Qazvin, Iran

Abstract

One of the threatening factors to fresh water resources is the advancement of saline water and intrusion into the groundwater aquifer. This problem occurs in coastal zones and desert margins which causes reduction in the quality of fresh water. Evaporation from the soil surface and the water table depth are factors affecting the salinity and salt distribution in the saturated and unsaturated zones. In this study, by constructing a physical model with dimensions of 4×1×1 m, the proposed situation of saline and fresh aquifer levels was studied in four different hydraulic gradients. During the experiment, moisture and salinity data were collected from the physical model and then the salinity distribution in the physical model was numerically simulated using Hydrus-2D software. The results showed that Hydrus-2D model simulates moisture and salinity distribution well. The Maximum Normalized Root Mean Square Error (NRMSE) for simulation of moisture and salinity were 9.28 and 21.69 percent. The results showed that the pattern of salinity progression and regression were different. In conditions where the fresh water level is higher, it prevents the advance of saline water in saturated zone, and in unsaturated zone it does not have a significant effect on controlling salinity due to evaporation from the soil surface. In the saturated zone, when the saline and fresh water levels were equal, three units’ salinity increase in saline zone and when the saline water level was higher, 6.5 units salinity increase was observed in the middle of the two saline and fresh water reservoirs.

Keywords

References

[1]. Azari A, Liaghat Z, Darbandi S. Drainage; Quantity and Quality of Return Flow. 1nd ed. Tehran. Iranian National Committee on Irrigation and Drainage; 2002. [Persian]
[2]. Banayi M H. Resources and Capacity of Iranian soils Map. Soil and water Research Institute. Iran. 2002; 6(p). [Persian]
 [3]. Momeni A. Geographical distribution and salinity levels of Iranian soil resources. Journal of Soil Research. 2011; 24(3):203-215.[Persian]
[4]. Barlow PM, Reichard EG. Saltwater intrusion in coastal regions of North America. Hydrogeology Journal. 2010 Feb 1;18(1):247-260.
[5]. Goswami RR, Clement TP. Laboratory‐scale investigation of saltwater intrusion dynamics. Water Resources Research. 2007 Apr;43(4):335-348.
[6]. Sriapai T, Walsri C, Phueakphum D, Fuenkajorn K. Physical model simulations of seawater intrusion in unconfined aquifer. Songklanakarin Journal of Science & Technology. 2012 Nov 1;34(6):679-687.
[7]. Ahmadi H, Hemmati M, Motallebian M. Assessment of accuracy of CTRAN/W and SEAWAT models for prediction of saltwater wedge under intruding and receding conditions. Journal of Water and Soil. 2018;32(1):13-27. [Persian]
[8]. Aflatooni M, Eskandari L, Dehghanisanij H. Calibration and Sensitivity Analysis of Hydraulic Behavior in Qazvin Plain Aquifer. Iranian Journal of Soil and Water Research. 2015;45(3):283-291. [Persian]
[9]. Johannsen K, Kinzelbach W, Oswald S, Wittum G. The saltpool benchmark problem–numerical simulation of saltwater upconing in a porous medium. Advances in Water Resources. 2002 Mar 1;25(3):335-48.
[10]. Maghooli G. Saltware intrusion assessment along swamp casts (Case study: Central salt marsh of Qazvin). Irrigation and Reclamation Engineering Department. University of Tehran; 2016 sep. [Persian]
 
[11]. KardanMoghadam H, Banihabib M. Investigation of Interference of Salt water in Desert Aquifers (Case study: South Khorasan, Sarayan Aquifer). 2017; 31(3):673-688. [Persian]
[12]. Noorabadi S, Sadraddini AA, Nazemi AH, Delirhasannia R. Laboratory and numerical investigation of saltwater intrusion into aquifers. Journal of Materials and Environmental Sciences. 2017;8(12):4273-83.
[ 13]. Mehdizadeh SS, Ketabchi H, Ghoroqi M, Hasanzadeh AK. Experimental and numerical assessment of saltwater recession in coastal aquifers by constructing check dams. Journal of Contaminant Hydrology. 2020 Mar 12:103637.
[14]. Memari SS, Bedekar VS, Clement TP. Laboratory and Numerical Investigation of Saltwater Intrusion Processes in a Circular Island Aquifer. Water Resources Research. 2020 Feb;56(2):e2019WR025325.
[15]. Šimůnek J, Van Genuchten MT, Šejna M. The HYDRUS software package for simulating the two-and three-dimensional movement of water, heat, and multiple solutes in variably-saturated porous media. Technical manual. 2012 Sep.
[16]. Ranjbar A, Rahimikhoob A, Ebrahimian H, Varavipour M. Simultaneous Simulation of Water, Nitrate and Ammonium Transport in Soil Using HYDRUS-2D Model in Furrow Irrigated Maize. 2017; 31.2(2):25-276. [Persian]
[17]. Mekala C, Nambi IM. Experimental and simulation studies on nitrogen dynamics in unsaturated and saturated soil using HYDRUS-2D. Procedia Technology. 2016 Jan 1;25:122-9.
[18]. Soltani M, Rahimikhoob A, Sotoodehnia A, Akram M. Evaluation of HYDRUS_2D Software in Simulating Dry Drainage. 2018; 31.4(4):595-607. [Persian]
 
[19]. Van Genuchten MT. A closed‐form equation for predicting the hydraulic conductivity of unsaturated soils. Soil science society of America journal. 1980 Sep;44(5):892-8.
[20]. Mualem Y. A new model for predicting the hydraulic conductivity of unsaturated porous media. Water resources research. 1976 Jun;12(3):513-22.
[21]. Ghorbani B. A mathematical model to predict surface runoff under sprinkler irrigation conditions. Doctoral dissertation. Cranfield University. Silsoe College; 1997.
[22]. Fan AW, Liu W, Xu GL. Numerical investigation on the temperature effect on the transport of soil solute. Heat Transfer Asian Research: Co‐sponsored by the Society of Chemical Engineers of Japan and the Heat Transfer Division of ASME. 2006 Dec;35(8):539-52.
[23]. Jamieson PD, Porter JR, Wilson DR. A test of the computer simulation model ARCWHEAT1 on wheat crops grown in New Zealand. Field crops research. 1991 Nov 1;27(4):337-50.
[24]. Mohammadi M, Ghahraman B, Davary K, Liaghat AM, Bannayan M. Pan coefficient (K p) estimation under uncertainty on fetch. Meteorology and Atmospheric Physics. 2012 Jul 1;117(1-2):73-83.
[25]. Ghamarnia H, Soltani N. Evaluating the Efficiency of Empirical Estimation of Reference Evapotranspiration (Pan Based Method) in Different Climate Conditions of Iran. 1397 Jan 1; 14(4): 170-183. [Persian]
[26]. Abbasi F. Advanced Soil Physics. 3nd ed. Tehran: University of Tehran Press (UTP); 2015. [Persian]
Iranian journal of Ecohydrology
Volume 7, Issue 4
January 2021
Pages 907-919

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History

  • Receive Date: 15 July 2020
  • Revise Date: 01 September 2020
  • Accept Date: 01 September 2020
  • First Publish Date: 01 December 2020
  • Publish Date: 21 December 2020

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