Modeling of Groundwater Quality for Drinking and Agricultural Purpose: A Case Study in Kahorestan plain

Journal of Environmental Treatment Techniques

2020, Volume 8, Issue 1, Pages: 346-352

J. Environ. Treat. Tech.

ISSN: 2309-1185

Journal web link: http://www.jett.dormaj.com

Modeling of Groundwater Quality for Drinking

and Agricultural Purpose: A Case Study in

Kahorestan plain

Marjan Salari , Maryam HosseiniKheirabad , Majid Ehteshami , Sayedeh Niloufar

Moaddeli and Ehsan Teymouri

Department of Civil and Environmental Engineering, Sirjan University of Technology, Kerman, Iran

Department of Civil Engineering, Payame noor University, Shiraz, Iran

Head and Assistant Professor, Environmental Eng. Dept. KN Toosi Univ. of Technology, Tehran, Iran

Department of Civil Engineering, Estahban University, Fars province, Iran

Graduated MSc.student, Faculty of Civil Engineering, Semnen University, Semnan, Iran

Received: 27/09/2019

Accepted: 15/12/2019

Published: 20/02/2020

Abstract

In the current study, planning for optimal utilization of groundwater resources is described. Kahorestan plain in Hormozgan

province was the study zone. Since the main problem of the plain is high salinity of groundwater, chloride concentration was

examined as an indicator of salt and also water quality degradations. This decision was made due to its high solubility, poor

absorption, and stability of the compounds in the groundwater. A quality model was developed using software coding of visual

mudflow to identify the problem. The collected chloride data of Kahorestan water wells were processed as an input in MT3D

software from 2007 to 2011. Longitudinal and transverse diffusion coefficients were calibrated and the distribution of contaminants

in the Kahorestan aquifer was analyzed. The mathematical model was developed to predict and simulate groundwater quality by

October-2014. According to a developed qualitative model, the average concentration of chloride in groundwater was increased

due to the need for more withdraw about a 5% increase in some parts of the northwest plains. Besides, the plain faces with a growth

rate of chloride concentration about 3% compared to the initial situation in October-2011. Furthermore, to reduce the salinity,

management schemes and plans were presented to reform water-use patterns, especially in the agricultural sectors.

Keywords: Groundwater, Salt, Chloride, Mathematical Modeling, Visual Mudflow

pond, supply, and tube-well water quality parameters (12

Introduction¹

parameters such as pH, TDS, TS, SS, DO, COD, BOD, etc.)

and identified water collection and distribution system in

Chandpur district of Bangladesh. They found that all the

parameters vary significantly with the types of water. Water

quality management programs should be initiated under the

supervision of the government to maintain the acceptable

limit and proper water supply schemes should be followed

for effective water collection and distribution systems [8].

Garba et al. (2016), evaluated 9 open well water

contamination in the high-density residential area. Microbial

contaminants, the concentration of some chemical and

physical parameters were tested. The results showed that

Nitrate exceeded the limit range in about 75% of samples

while e- Coli bacteria were observed in 8 out of 9 samples.

Overall, they recommended that another source of domestic

Nowadays, Changes in the quality of groundwaters and

salty water resources have been becoming the greatest

warning to the agriculture industry, in particular, in arid and

semi-arid lands. Therefore, many researchers have been

doing to evaluate, estimate and measuring the concentration

of contaminant properties either in fields or using a

computation model [1-5].

Theorical foundations for describing the transfer of

sakts, which is a conceptual framework to model analysis the

modeling of the processes of transfering physical salts in

underground water, was presented by Domenico and

Schwartz [6] Khalifa, (1996) calculated the pizpmetric

future levels and budget of water volume by a 3-D limited

difference method for SiwaOasis project [7].

Lokman Hossain et al. (2013), investigated the status of

Corresponding author: (a) Marjan Salari, Department of Civil Engineering, Sirjan University of Technology, Kerman, Iran, E-

mails: salari.marjan@gmail.com. (b) Majid Ehteshami, Head and Assistant Professor, Environmental Eng. Dept. KN Toosi Univ.

of Technology, Tehran, Iran, P.O Box 1587-544-16, Tel. +98-21-88770006, Fax: Tel. +98-21-88779476. E-mail:

Maehtesh@gmail.com.

Journal of Environmental Treatment Techniques

2020, Volume 8, Issue 1, Pages: 346-352

water supply and other water purification techniques that is

consumer-friendly is needed for the area [9].

precision would better to be used to provide the most likely

conditions similar to what is in the reality and result in

satisfactory outcomes [17]. The combination of chlorine,

which considers in halogen categories, and sodium leads to

produce salt. Serious kidney damages a high blood pressure

are repercussions of increasing salt in drinking water [18, 19

and 20]. It is also might lead to stroke and left ventricular

hypertrophy in a long-term period of consuming [21]. Some

evidence has shown that consuming excess salt is an indirect

reason for obesity with drinking soda [22]. It has been said

that the risk of kidney stones, osteoporosis and one of the

main reasons for gastric cancer are overusing salt [23 and

24]. Since the salt is the most soluble and the most extensive

types of salt, it would be dangerous for the plants provided

that there has not been an envolved mechanism to regulate

its accumulation [25 and 26]. One of the predominant effects

of chlorine on the human’s health is disinfection by-product

(DBPs) which define as side-substance that are produced in

the presence of chlorine. This substance is caused by the

reaction of chlorine and organic materials. Terly Halo

Methane, Nitrozomines, and Halo acetic acid are the most

important examples of DBPs that have great potential for

cancer and genetic mutations in humans [27]. Hence, in the

present study, we focused on the application of a quality

model using software coding of visual mudflow to identify

chloride concentration as an indicator of salt and also water

quality degradations the problem. The collected chloride

data of Kahorestan water wells was processed as an input in

MT3D software from 2007 to 2011.

Richards et al. (2019), investigated the spatial

relationships between functional genes with chlorinated

ethene concentrations in a surficial aquifer at a contaminated

site by using cryogenic soil coring, and this result in that

both aerobic methanotrophs and anaerobic VC-

dechlorinators may play

a significant role in VC

biodegradation in aquifers that have little dissolved

oxygen [10]. Panjaitan et al. (2018), used Chloride

Bicarbonate Ratio Method to determine the seawater

intrusion in the shallow aquifer by taking 30 samples with a

km distance each and measured Cl−, HCO3 −, CO3 – and

EC as chemical parameters. The experiment showed that

water usage debit and aquifer permeability affected seawater

intrusion significantly with an adjusted coefficient R2 of

.797 [11]. Banks et al. (2018), used the chloride mass

balance (CMB) method to determine chloride

decomposition in rainfall to estimate regional groundwater

recharge in Africa. In order to provide input data for

recharge estimation, simple rainfall collectors were

developed and installed in sites, and also, other available

researches data about chloride concentration in rainfall were

used to create a regional map of chloride decomposition

[

12]. Xie et al. (2018), utilize an analytical model in three

cases for contaminant transport in a vertical cut-off wall and

an aquifer system. With a fixed hydraulic gradient of 0.5, the

chloride (Cl-) breakthrough time increased by 1.7 which was

more sensitive to the scale of the aquifer that the same trend

of lead (Pb) [13]. Alexandria Demi (2018), considered the

variation in groundwater geochemistry in the Great Bend

Prairie aquifer by collecting samples from 24 wells and

comparing results to previous data. Results demonstrated

that water quality in the aquifer has degraded over the past

Methodology

.1 Case Study

Khahorestan plain is located 90 kilometers away on the

west of Bandar Abbas, and DMS latitude and longitude

coordinates for Kahorestan are: 55°27’ up to 55° and 27°8’

up to 27°16’. Average altitude of the plain is 66 meters and

almost 62 percent of the area is between 50 to 100 meters.

Kahorestan plain is considered as the hot and dry areas with

0 to 40 years due to nitrate accumulation [14].

Mountadar et al. (2018), studied the salinization

mechanisms in the coastal area between Sidi Abed and

Ouled Ghanem (El Jadida Province, Morocco) based on

analyzing and discussing the physicochemical data of water

samples from 73 wells. They found that the wells which

were located in the coastal fringe are characterized by a high

concentration of sodium and chloride and EC values but

lower values were found in that of located in upstream, and

the groundwater is contaminated by seawater intrusion [15].

Underground waters, is very important in Iran because

of its dry climate. During the past 20 years, quick population

growth, developing urban and agriculture areas, surface

water restriction and overuse of underground water have led

to serious damages to underground water aquifers in the

country. Kahorestan plain in an important agriculture center

in the west of the Hormozgan province which provides a

portion of drinking water of Bandar Khamir and surrounding

villages and also supplies the water requirement of the

cement factory of the Hormozgan through the under-

groundwater sources from its northwest part. Consequently,

underground water quality has been decreased due to

overusing [16]. Management of underground water in both

forms of quality and quantity needs to be noted carefully. On

the one hand, sources of contaminants and related equations

should be well-known and on the other hand, advanced

methods such as simulators and models with clockwork

56 millimeters average annual rainfall and 27°C average

annual temperature. Average annual evaporation is about

680 millimeters. Almost 60 of 260 square kilometer of the

plain is suitable to be noticed and studied, and the rest is

practically useless because of high salinity of underground

water (Laar Consaltant Engineering Company).

Underground water flow modeling and soluble transfer

휕

휕ℎ

휕

휕ℎ

휕

휕ℎ

(

퐾_푥_푥_휕_푥) + (퐾_푦_푦) + (퐾_푧_푧_휕_푧) − 푊 = 푆_푠_휕_푡

ꢀ1ꢁ

휕푥

휕푦

휕푧

휕퐶

휕푡

휕

휕퐶

휕

푞ꢇ

ꢀ푉 ꢆꢁ + ꢆ_푠+ ∑^푁푅_푘

ꢂ퐷_ꢃ_푗ꢅ −

ꢀ2ꢁ

ꢃ

푘ꢈꢉ

휕푥푖

휕푥ꢄ

휕푥푖

휃

.2 Ground water flow model and soluble transfer

Among the groundwater movement simulation

programs, PMWIN and MT3D are more widely used due to

the physical properties of the porous medium and their

completeness. Most numerical models of groundwater are

based on the solving of two differential equations with

partial derivatives, which are the three-dimensional

equations for the movement of groundwater with constant

density in the porous medium, being explained as follows:

Journal of Environmental Treatment Techniques

2020, Volume 8, Issue 1, Pages: 346-352

휕

휕ℎ 휕 휕ℎ 휕 휕ℎ 휕ℎ

퐾_푥_푥_휕_푥) + (퐾_푦_푦) + (퐾_푧_푧_휕_푧) − 푊 = 푆_푠_휕_푡ꢀ3ꢁ

휕푦 휕푦 휕푧

(

휕푥

where α_L and α_T are the longitudinal and transverse

diffusion coefficient, V are the average water velocity of the

groundwater and D is the Effective molecular Dispersion

coefficient.

In this equation, K is hydraulic conductivity, h is the

potential load, W is the volume flux in the volume unit,

which indicates the discharge and feed, 푆 is specific storage

푠

for porous materials, t indicates time, and X, Y and Z

represent the Cartesian coordinates [25 to 28]. The partial

differential equations for transporting materials in a three-

dimensional system in an underground aquifer are as

follows:

푃ꢐ

^푅⁼^[¹⁺^퐾푑_푛

]

(9)

C) Retardation: The process of delaying the movement

of pollution in underground water due to the

absorption mechanism, which is carried out both

for organic particles and non-organic particles. The

Retardation coefficient is calculated using the

diffusion coefficients, absorption and soil porosity

characteristics as follows:

휕퐶

휕푡

휕

휕퐶

휕

푞ꢇ

ꢀ푉 ꢆꢁ + ꢆ + ∑^푁^푅푘

^ꢂ^퐷ꢃ푗

ꢅ −

ꢀ4ꢁ

ꢃ

푠

푘ꢈꢉ

휕푥푖

휕푥ꢄ

휕푥푖

휃

where: C is the concentration of groundwater soluble

contaminants, t times, x_i, the distance in the X direction in

the Cartesian coordinate system, D_ij, the hydrodynamic

relaxation coefficient, V_i the velocity of water in the

aggregates, q_s the volume of the inlet or outlet in the unit

that Inputs are positive and outputs are negative, C_s are the

푃ꢐ

푅 = [1 + 퐾_푑_푛

]

(10)

where K

is the absorption coefficient, P

is the density of

soil particles and n is soil porosity [35-36]. In this research,

the quantitative model was first made, calibrated and

validated by MODFLOW, then it was used to prepare a

qualitative model. To provide a qualitative model of the

MT3D package and the qualitative data of the 15 observation

wells, chlorine measurements were used, as shown in Fig. 1.

Due to the fact that we prepared and calibrated a small plain

model for the years 87-88, we prepared a qualitative model

for the year 2010 and we used the information from the

following years to validate the model.

concentrations of inputs and outputs, θ are the porosity of the

kꢈꢉ

medium and ∑

R are the term of chemical interactions

[

29]. Three factors contributing to the transmission of

pollution in groundwater include:

A) Advection: The contaminants in groundwater are

transmitted according to Darcy law. According to

the law, the flow rate from point 1 to point 2 is

proportional to the head loss and has Photo ratio

with the length of the path.

ℎꢊꢋℎꢌ

푄 = −퐾. 퐴.

(5)

2.3 Predict the quantitative status of the aquifer in

Kahurestan plain in Mehr (September- October: 2015)

In this section, a quantitative aquifer model is used to

predict the level of aquifer water level up to 2015. In order

to predict the future status of the aquifer, the level of water

level in mehr October 2011 is given as the initial level of

aquifer water level and is simulated for a 4-year period of

aquifer.

퐿

The actual speed of passing through the soil pores is

calculated as follows:

ꢍ

ꢏ

ℎꢊꢋℎꢌ

퐿

푉 =

⁼⁻푛

(6)

푛.ꢎ

where n is the Effective porosity or percentage of porosity

that flow is passing through them. Therefore, only when the

flow transfer is significant, the pollutant, along with the

groundwater flow, does not move at the same rate and the

concentration of the pollutant in the flow path will not be

reduced.

B) Dispersion: Dispersion in underground waters

actually indicates the spread of a contaminated

substance in an area with groundwater velocity.

The hydrodynamic diffusion coefficient is as

follows:

퐷 = 훼 푉 + 퐷

(7)

(8)

퐿

Fig 2: Forecast water level for October 2015

퐷_푇= 훼 푉 + 퐷

푇

Journal of Environmental Treatment Techniques

2020, Volume 8, Issue 1, Pages: 346-352

Fig 1: Chlorine observation wells and quantitative model range of plain aquifer

Figure 2 shows the distribution of water loss in the plain

from mehr October 2011 to mehr September 2015 during a

four-year period. As can be seen, using the quantitative

model we conclude that the highest amount of water loss

occurs in the northwestern part of Kahurestan plain.

the calibration period, that is, after one year of simulation,

two amounts of observed and calculated concentrations are

compared.

.3. Calibration of the model

In qualitative aquifer modeling, the parameters that are

affected by the distribution process (absorption coefficient,

horizontal distribution ratios to distribution length, vertical

distribution to distribution length and distribution length) are

calibrated. Basically, these parameters should be obtained

from laboratory studies, but due to the lack of laboratory

results data evidence, this was done by using trial and error

and matching observational values with computational

values. The calibrated parameters of the model are described

in Table 1.

Fig 3: Lines map of calculated and observed Cl concentration in

65-day time step during the calibration period (2009-2008)

.4 Error Distribution

Scatter diagram is a Comparison of the values calculated

by the observation model as a graph. The distribution curve

is, in fact, a kind of comparison of model results errors. Fig

Table 1: The calibrated parameters of the model

TRPT

TRPV

DMCOEF

0.1

shows the fitting of the results for the calibration period,

which are acceptable with respect to the number of 15

observation plains wells. In addition, the qualitative model

was calibrated for a one-year period. In Fig. 3, at the end of

Longitudinal Dispersivity

235

Journal of Environmental Treatment Techniques

2020, Volume 8, Issue 1, Pages: 346-352

Fig 4: Distribution study of the calculated and modeled values

.5 Parameters Sensitivity analysis

The purpose of the sensitivity analysis is to demonstrate

after 2 years (October 2009) and the accuracy of the model

after 3 years (October 2010).

the response of the quality model to the change of an

unconfident input parameter. The model response to the

variation of the input parameter can be high or low. The

quality model of groundwater in Kahurestan Plain is

sensitive to the length of distribution and the concentration

of nitrate input and output of the aquifer respectively, and

the model sensitivity to density of soil particles is low.

Figure 5 shows the variation of the model error relative to

the distribution length parameter.

1.65

1.6

1.55

1.5

1.45

.35

0 45 40 35 30 25 23 21 20 15 10

.6 Model Verification

50 1

To validate the model and determine the accuracy of it,

Series1 1.6 1.6 1.6 1.5 1.5 1.5 1.4 1.4 1.5 1.5 1.5 1.5 1.5

the initial aquifer concentration was assumed to be the

concentration for October 2007, and run the model for

several consecutive time periods. The model results showed

that the more predictive time goes, the greater the predictive

error becomes. Based on the results, it can be said that it is

quite obvious that maximum of 2 to 3 years to come can be

predicted by this model and, for more than that, prediction

accuracy becomes low, and is not recommended. Figure 6

illustrates this point and shows the accuracy of the model

Longitudinal Dispersivity

Fig 5: Model sensitivity to diffusion coefficient

.7 Predict

In this section, the model was used to predict the three-

year period. To do this, we initially considered the data of

007 as the initial concentration and simulated the aquifer

Journal of Environmental Treatment Techniques

2020, Volume 8, Issue 1, Pages: 346-352

for a period of three years. As a result, the chlorine map in

010 was shown in Fig. 7.

Fig 7: Forecasted Chlorine Map for 2014

Then, in order to predict the chlorine concentration in the

aquifer, the qualitative parameters in October 2011 as the

initial values of concentration were given to the model and

simulated for a 3-year period of the aquifer. In Figure 8, solid

lines of the map, are chlorine concentration lines in the

October 2011, and dotted lines, are chlorine concentration

lines in October 2011 Kahurestan plain.

A: Model accuracy after 2 years (October 2009)

Fig 8: Forecasted Chlorine Map for 2014

Conclusion

In this study, PMWIN showed that it is a good option,

both quantitatively and qualitatively, for the groundwater

quality modeling of Hormozgan Plain. Modeling for the

three-year forecast indicates that the amount of chlorine in

the whole plain has a relative increase, which the average is

.3% for the whole plain. This increase is due to more water

harvesting in the northwestern plain. Thus, due to

concidering the decrease in groundwater level, it is

recommended to apply smart meter devices in these areas for

efficient management of crop permitting, given the

estimated water requirement of crops grown in the area and

the methods of compensating for the loss of moisture.

The following two main axes can be examined. Long-

term methods, including the proper use of modern irrigation

and agricultural methods, are recommended and also

necessary groundwater management changes in the area to

compensate for groundwater quality. Short-term approaches

include the creation of artificial feeding plans with regard to

the potential of surface currents along the plain. This can be

partially offset by a reduction in reservoir volume and

improved groundwater quality. Therefore, by protecting

water in agriculture by improving irrigation methods by

taking steps such as problem solving and increasing the level

of knowledge of farmers, developing an optimal cropping

B: Model accuracy after 3 years (October 2010)

Fig 6: Distribution graph of observed and modeled chlorine

concentration values

Journal of Environmental Treatment Techniques

2020, Volume 8, Issue 1, Pages: 346-352

pattern, preventing unauthorized harvesting and non-

issuance of new licenses, protecting aquifers and artificial

feeding. This can minimize the rate of groundwater level loss

and its consequences.

12 Banks, Eddie W., Peter Cook, Michael Owor, Seifu Kebede,

Prince Mleta, Helen Bonsor, and Alan MacDonald. "Chloride

deposition in rainfall to estimate regional groundwater recharge

in Africa." In EGU General Assembly Conference Abstracts,

vol. 20, p. 14713. 2018.

Xie, Haijian, Shaoyi Wang, Yun Chen, Jianqun Jiang, and

Zhanhong Qiu. "An analytical model for contaminant transport

in cut-off wall and aquifer system." Environmental

Geotechnics (2018): 1-10.

Ethical issue

Authors are aware of, and comply with, best practice in

publication ethics specifically with regard to authorship

Richard, Alexandria Demi. "Variation in groundwater

geochemistry and microbial communities in the High Plains

aquifer system, south-central Kansas." PhD diss., 2018.

(avoidance of guest authorship), dual submission,

manipulation of figures, competing interests and compliance

with policies on research ethics. Authors adhere to

publication requirements that submitted work is original and

has not been published elsewhere in any language.

15 Mountadar, Sara, Abdelkader Younsi, Abdelkader Hayani,

Mustapha Siniti, and Soufiane Tahiri. "Groundwater

salinization process in the coastal aquifer sidi abed-ouled

ghanem (province of el Jadida, Morocco)." Journal of African

Earth Sciences 147 (2018): 169-177.

Competing interests

The authors declare that there is no conflict of interest

that would prejudice the impartiality of this scientific work.

He, Feng J., and Graham A. MacGregor. "Salt, blood pressure

and cardiovascular disease." Current opinion in cardiology 22,

no. 4 (2007): 298-305.

Meneton, Pierre, Xavier Jeunemaitre, Hugh E. de Wardener,

and Graham A. Macgregor. "Links between dietary salt intake,

renal salt handling, blood pressure, and cardiovascular

diseases." Physiological reviews 85, no. 2 (2005): 679-715.

Swift, Pauline A., Nirmala D. Markandu, Giuseppe A. Sagnella,

Feng J. He, and Graham A. MacGregor. "Modest salt reduction

reduces blood pressure and urine protein excretion in black

hypertensives: a randomized control trial." Hypertension 46,

no. 2 (2005): 308-312.

Authors’ contribution

All authors of this study have a complete contribution

for data collection, data analyses and manuscript writing.

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