international journal of ground sediment & waterijgsw.comze.com/paper_pdf/201705/201705.pdf ·...

ISSN:2372-0743 print International Journal of Ground Sediment & Water Vol. 05

2017ISSN:2373-2989 on line

Editor Board, Research/Engineering Paper 1. Editor Board Research Paper: 2. Numerical Transient Analysis of Pressure in Petroleum Reservoir......................................176-192

Pedro Victor Serra Mascarenhas, André Luís Brasil Cavalcante

3. The Challenges of Public Private Partnership (PPP) Projects in a Developing…………..193-204

Christian Azuka Olele

4.Genotypic Response to Salt Stress: II–Pattern of Differential Relative Behaviour of

Salt-Tolerant, Moderately Salt-Tolerant and Salt-Sensitive Wheat Cultivars under Salt Stressed

Conditions...................................................................................................................................205-216

Ravi Sharma

5. Groundwater arsenic contamination in shallow alluvial aquifers of Bhulri Shah Karim taluka,

Tando Muhammad Khan district, Sindh, Pakistan……………………………………….217-244

Adnan Khan, Viqar Husain, Asal Eghbal Bakhtiari, Muhammad Hamza Khan

International Journal of Ground Sediment & Water (ISSN: 2372-0743)

IJGSW 2017 Vol.05

2017 Vol. 05

Chief Editor Wang Guangqian Tsinghua University, China

Sun Jichao University of Wisconsin-Milwaukee, USA

China University of Geosciences, China

Associate Editor

Todd M. Davis, P.E. Milwaukee School of Engineering, USA

Rajan Saha University of Wisconsin-Milwaukee, USA

Marina Ivanovna Kozhukhova University of Wisconsin-Milwaukee, USA

Yang Jishan Yellow River Institute of Hydraulic Research, China

Huang Wendian Sichuan University, China

Huang Guoxian Cardiff University, UK

Kedar Bahadur Thapa Chung Yuan Christian University, Taiwan

Tahir Maqsood Sandhu Irrigation Department, Pakistan

Zhang Lixun University of Wisconsin-Milwaukee, USA

Feng Xin Milwaukee School of Engineering, USA

Ghulam Rasool Mashori Peoples University of Medical & Health Sciences for Women,

Pakistan

Yehia Khidr University of Sadat City, Egypt

Ali Almayahi University of Basra, Iraq

Nur E Alam Siddique Global Environment Consultants Ltd, Bangladesh

Mohamad Ali Fulazzaky Universiti Teknologi, Malaysia

Munawar Iqbal University of Peshawar, Pakistan

Hamed Metwalli Cairo University, Egypt

Jayakumar KV National Institute of Technology, Warangal, India

Saima Nasreen International Islamic University, Pakistan

Loutfy Hamid Madkour Al-Baha University, Saudi Arabia

André Luís Brasil Cavalcante University of Brasília, Brazil

Ravi Sharma Agra College, India

Ajaya Kumar Singh Govt. V. Y. T. PG. Autonomous College, India

Anam Yousaf The University of Manchester, UK

Wang Shudong Institute of Remote Sensing and Digital Earth, Chinese Academy of

Sciences, China

Liu Ronghua China Institute of Water Resources and Hydropower Research,

China

Submit your manuscript to E-mail: [email protected] or [email protected]

Please visit us at: http://ijgsw.comze.com

INTERNATIONAL JOURNAL OF

GROUND SEDIMENT & WATER ISSN: 2372-0743 (print) ISSN: 2373-2989 (on line)

ISSN:2372-0743 print ISSN:2373-2989 on line

International Journal of Ground Sediment & Water Vol. 052017

- 176 -

Numerical Transient Analysis of Pressure in Petroleum Reservoir

Pedro Victor Serra Mascarenhas1, André Luís Brasil Cavalcante1

1. University of Brasilia, Brasilia ,70910-900, Brazil E-mail:[email protected]; [email protected]

Abstract: This work regards oil flow in petroleum reservoirs. It is an analysis that aims the study of monophasic oil flow in porous media through the Diffusivity Equation’s analytical solution for a radial, transient flow when varying reservoir and fluid parameters. This solution is especially important for preliminaries studies of petroleum reservoir regarding its economic and technical production viability for a qualitative understanding of the flow in the reservoir. In addition, a numerical model based on the Finite Difference Method (FDM) is implemented to solve the radial flow and relax the simplifying hypothesis used to solve the governing equation analytically. The numerical, more realistic, solution is compared to the analytical solution and the effects of the simplifying hypotheses of the model are further discussed.

Keywords: Transient Analysis, Finite Difference Method, Petroleum Reservoir, Diffusivity Equation, Analytical Analysis

1. Introduction

Recent oil barrel values drop to low prices demanded more efficient and reliable viability studies. It is possible to minimize risks and avoid bad capital investment through preliminary studies and a better understanding of how each fluid and geological variable influences the flow.

The paper begins with of the background theory used to study flow in porous media, where the Continuity Equation, equations of state and Darcy’s Law are briefly discussed. By imposing the correct boundary conditions, these equations are combined to obtain the Diffusivity Equation, which is solved analytically to obtain an equation capable of describing pressure values at every point and time of the reservoir using geological and fluid information. Following that, the FDM model equations’ are presented and its implementation is further discussed. In order to accomplish this, Mathematica Wolfram [1] computer language is chosen as the computational tool.

The numerical model is especially useful to study real geometry and parameters cases when obtaining an analytical equation without simplifying assumptions is not possible.

◆Research Paper◆



- 177 -

2. Deriving the Diffusivity Equation

The Diffusivity Equation’s solution describes the pressure behavior with respect to the distance to the wellbore’s center and time passed since the start of the production, and it is used in analysis well test data [2]. It is obtained by combining three sets of equations: one that describes the linear momentum conservation (Darcy’s Law), one that describes the mass conservation (Continuity Equation) and equations that relate state variables, such as volume, pressure, temperature and mass (equations of state). The following topics are dedicated to introduce these equations, as well as the hypotheses behind their application.

Darcy’s Law: the Conservation of Linear Momentum Equation. Henry Darcy

first wrote Darcy’s Law in 1856. It is an equation that describes the flow of fluid through porous media using the concept of the linear momentum conservation [3]. It was obtained empirically when Darcy first wrote this equation, but later it was derived from the Navier-Stokes equation for stationary, creeping and incompressible flow [4]. Darcy’s Law is widely used in reservoir engineering for modeling flow in porous media, and those who intend to use it should understand its hypotheses: Darcy’s Law is valid for incompressible, laminar flow, negligible inertial effects, and the viscous part of the strength tensor behaves according to Newton’s Second Law for fluids [4].

Φ

-k d

vdl

(1)

where γ denotes the fluid’s specific weight [ML-2T-1]; μ denote the fluid’s viscosity [ML-1T-1]; k denotes the porous medium’s intrinsic permeability [L2]; v is the fluid’s instantaneous velocity [LT-1]; l is the direction of the fluid’s trajectory [L]; denotes the fluid flow potential [L]. The fluid potential is the negative integral of the force over the path taken by an infinitesimally small volume of fluid when it moves from a reference location to the point under consideration [4]. It is a measure of the specific potential energy stored within the fluid. Thus,

Φ o

p

p

o

dpZ Z

(2)

where p denotes the pressure [ML-1T2]; Z denotes the height with respect to a chosen datum [L] and the subindex “o” denotes reference values for the variables that it follows.

The derivative of the fluid potential with respect to the path the fluid takes is:

Φ 1d dp dZ

dl dl dl

(3)

Continuity Equation: The Mass Conversation Equation. The Continuity Equation states physically that the variation of fluid mass in a control volume within time is equal to the balance of fluid that flow inward and outwards of the volume plus any source within that volume, or diminished any sink that might be present inside the volume. The source/sink flow term is useful to model internal boundary conditions of



- 178 -

specified flow rates (i.e. injection or removal of hydrocarbonates through a well). The Continuity Equation is written as it follows[5]:

sctd

b

svt

q

V

(4)

where ρ denotes the fluid’s specific mass [ML-3]; Vb is the bulk volume [L3]; ϕ is the medium’s porosity [non-dimensional]; t is the time [T]; qsc [L

3T-1] is the source/sink rate term and the sub-index std stands for variables at standard pressure and temperature conditions.

Equations of State. Equations of state are any constitutive laws that relate

pressure, temperature, volume and mass for a given fluid. One much-known example of an equation of state is the Ideal Gas Law[3].

The importance of equations of state on the model is that they can be used to replace variables on the Diffusivity Equation by variables usually measured on field evaluations and variables that are easier to work with. Two important equations are going to be used for this purpose, fluid compressibility equation and rock formation compressibility equation, both specified for isothermal analysis. The fluid compressibility equation is defined as the percentage of the total volume that the volume variation rate with the pressure represents:

1 V

cV p

(5)

where c is the fluid’s isothermal compressibility [M-1LT-2] and V is the volume [L3]. One may write Equation (5) on the form that is more useful to the current purpose

using the definition of specific mass:

1

cp

(6)

The Equation (6) may also be used to write relations between specific mass and pressure spatial partial derivatives and specific mass and pressure time partial derivatives. These equations are:

1

pc

(7)

and

1p

t c t

(8)

The other equation of state, the rock formation compressibility, is the percentage of the rock porosity that the variation of porosity with respect to the pressure represents [3]:

1

fcp

(9)

Mathematical manipulations may as well allow Equation (9) to be written on a



- 179 -

way that may be applied to the model:

1

f

p

t c t

(10)

The sum of the two compressibilities showed on the text is called the total compressibility:

t fc c c (11)

It is also useful to use the defined compressibilities to obtain equations that allow to calculate porosity and oil formation volume factor for different times since the beginning of the production [5]:

1

o

o

BB

c p p

(12)

1o f oc p p (13)

where B is the oil formation volume factor [non-dimensional]. The Diffusivity Equation and its Solution. Equation (4) can be fully expanded

with respect to the space variables:

yx stdz

z

c

yx

s

b

p p p

x y z

Z Z Z

x y z

kk k

x y z

kk k

x

q

t

V

y z

(14)

where the subindexes x, y and z denotes the Cartesian direction on in the space [L]. The source/sink term is not necessary to solve Equation (14) analytically, because

it is redundant after applying boundary conditions. Therefore it may be considered zero. Rewriting Equation (14) into cylindrical coordinates:

2

2

1 1

1 1

r z

tr z

kk kp p pr

r r B r r B z B z

k ck kZ Z Z pr

r r B r r B z B z B t

(15)

where the sub-indexes r, and z are the cylindrical grid directions, r is the radial direction variable [L], is the angular direction variable [non-dimensional] and z is the depth direction variable [L].

Some important hypotheses are assumed in order to obtain the analytical solution. It is assumed that the rock is homogeneous and isotropic, the fluid’s viscosity is constant, fluid and rock compressibilities are small and constant, the fluid is isothermal and pressure gradients are small. It is also assumed that the flow is radial (i.e. no vertical pressure gradients) and transient (the reservoir behaves as if it is infinite and boundary conditions are not felt immediately along the reservoir extension. Equation (15) becomes:



- 180 -

1 1p p

rr r r t

(16)

where the rock and fluid parameters were replaced by the diffusivity constant [2]:

t

k

c

(17)

It is necessary to specify properly three boundary conditions to solve Equation (16) [2]: It is assumed that, at t = 0, the pressure inside the reservoir is constant p(r,0) = pt=0,

r>0. It is assumed that if a point sufficiently far is taken, its pressure is equal to the

initial pressure lim[p(r,t)]r→∞= pt=0. It is assumed that the flow rate inside the wellbore is constant qw=cte.

Furthermore, the last boundary condition may be written as it follows using Darcy’s Equation and taking its limit with r→∞:

0

lim2

w

r

qpr

r kh

(18)

where qw is the well rate and h is the reservoir width [L3T-1]. One may find the pressure equation along the reservoir [3] using these boundary

conditions and solving Equation (16):

0

2

-( , )4 4

w tt i

q c rp r t p E

kh kt

(19)

where Ei(X) is the integral exponential function, defined as follows [3]:

X

ie

E X d

(20)

Finite Difference Method Model. There are three most commonly used numerical methods for reservoir simulation. These are Finite Element Method, Finite Difference Method and the Finite Volume Method [6]. Each of them has its advantages and disadvantages. The chosen method for this paper is the Finite Difference Method, which is the most traditional numerical method on fluid flow studies and its pros and cons are summarized in Table 1.

The FDM method is chosen to be implicit with a radial and geometrically growing grid. The grid grows following the rule:

1i lg ir r (21)

where lg is the mesh growth factor [non-dimensional]. In order to keep the discrete and continuous form of the Darcy Equation, the

borders of the cells must be positioned according to the formula:



- 181 -

Table 1. Advantages and Disadvantages of the Finite Difference Method. Finite Difference Method[6]

Advantages Disadvantages Easy to write codes; Easy 3D

extension; Good compatibility of physical aspects of fluid flow in porous medium

Highly dependent on the mesh; Difficult to implement for complicated geometry; big numerical dispersion associated with truncation; poor precision for a heterogeneous medium with high capillary pressure variations.

11/2

1ln

i ii

i

i

r rr

r

r

(22)

The FDM formulation used here is developed in [5]. The implicit in time

formulation is used, since the mesh is radial and it grows geometrically. The final equation that describes the method is:

1 1 1 1 1, , , , 1 , , , , 1 , , , 1, , , , 1, , , 1, ,

1 1 1, , 1, , , , , , , ,

n n n n n n n n n ni j k i j k i j k i j k i j k i j k i j k i j k i j k i j k

n n n n ni j k i j k i j k i j k i j k

A p B p N p S p W p

E p C p Q

(23)

with,

, , , , 1/2n ni j k i j kA T (24)

, , , , 1/2n ni j k i j kB T (25)

, , , 1/2,n ni j k i j kN T (26)

, , , 1/2,n ni j k i j kS T (27)

, , 1/2, ,n n

i j k i j kW T (28)

, , 1/2, ,n ni j k i j kE T (29)

1

, ,1, , , , , , , , , , , , , ,

Γ

Δ

ni j kn n n n n n n

i j k i j k i j k i j k i j k i j k i j kC A B N S W Et

(30)

Each of these coefficients is a combination of transmissibilities through the face of two neighboring cell. The letters stand for the position of the cells in relation to the cell in analysis: above, below, north, west, east, south and center. Each of these coefficients shows how the pressure of cell itself and the pressure from neighboring cells are changing the pressure calculated.



- 182 -

The transmissibility is defined as:

Table 2. Expressions applied to Equation (31) to calculate the geometrical factor G [7]. Grid types and flow direction

Geometrical Factor ( Geometrical Factor (

Cylindrical, radial

1/2 1

, , 1, , 1/2

Δ Δ

1 1ln ln

j k

i i

r i j k i r i j k i

z

r r

k r k r

1/2

1, , 1 , , 1/2

Δ Δ

1 1ln ln

j k

i i

r i j k i r i j k i

z

r r

k r k r

Cylindrical, angular 1/2

1/2

1/2 1 1/2

, , , 1,

ln Δik

i

j j j j

i j k i j k

rz

r

k k

1/2

1/2

1/2 1 1/2

, 1, , ,

ln Δik

i

j j j j

i j k i j k

rz

r

k k

Cylindrical, vertical 2 2

1/2 1/2

1/2 1 1/2

, , , , 1

Δr r

2

ji i

k k k k

zi j k zi j k

z z z z

k k

2 2

1/2 1/2

1/2 1 1/2

, , 1 , , 1

Δr r

2

ji i

k k k k

zi j k zi j k

z z z z

k k

Cartesian, x‐direction

1/2 1 1/2

, , 1, ,

Δ Δj k

i i i i

xi j k xi j k

y z

x x x x

k k

1/2 1 1/2

1, , , ,

Δ Δj k

i i i i

xi j k xi j k

y z

x x x x

k k

Cartesian, y‐direction

1/2 1 1/2

, , , 1,

Δ Δi k

j j j j

yi j k yi j k

x z

y y y y

k k

1/2 1 1/2

, 1, , ,

Δ Δi k

j j j j

yi j k yi j k

x z

y y y y

k k

Cartesian, z‐direction

1/2 1 1/2

, , , , 1

Δ Δi j

k k k k

zi j k zi j k

x y

z z z z

k k

1/2 1 1/2

, , 1 , ,

Δ Δi j

k k k k

zi j k zi j k

x y

z z z z

k k

, ,, ,

1n

ni j k

i j k

T GB

(31)

where G is a geometric factor, calculated with the expressions presented in Table 2. Equation (32) shows the independent terms vector from the linear system.

Through this term, it is possible to implement internal boundary conditions and to relax gravitational hypothesis.



- 183 -

1

, , 1, , , , , ,

Γ

Δ

ni j kn n n n

i j k i j k sc Gi j kQ p q Qt

(32)

Equation (33) shows the storage term involving changes in porosity and on the oil formation volume factor. This term accounts for the total compressibility, and it represents an “inertia” to pressure changes. The gravitational term is written as:

1

1, , 1

Γn

n ti j k b n

cV

B

(33)

, , , , , , 1 , , , , 1 , , , 1,

1, , , 1, , , 1, , , , 1 , , , , , ,

n n n nGi j k Gi j k i j k Gi j k i j k Gi j k i j k

n n n nGi j K i j k Gi j k i j k Gi j k i i j k Gi j k i j k

Q A Z B Z N Z

S Z W Z E Z C Z

(34)

The term expressed in Equation (34) term takes into account the influence of the

hydraulic load of the neighboring cells, similarly to the Equation (23). The coefficients multiplying pressures are defined as following:

1, , , , , , 1/2 n n n

Gi j k i j k i j kA A (35)

1, , , , , , 1/2 n n n

Gi j k i j k i j kB B (36)

1, , , , , 1/2, n n n

Gi j k i j k i j kN N (37)

1, , , , , 1/2, n n n

Gi j k i j k i j kS S (38)

1, , , , 1/2, , n n n

Gi j k i j k i j kW W (39)

1, , , , 1/2, , n n n

Gi j k i j k i j kE E (40)

1, , , , , , , , , , , , , ,

n n n n n n nGi j k Gi j k Gi j k Gi j k Gi j k Gi j k Gi j kC A B N S W E (41)

3. Methodology

Plots of the pressure variation from the initial pressure within a distance from the wellbore and time from the production beginning were drawn through the usage of the Mathematica Wolfram Software language. The plots will only relate the variation of pressure to time or distance individually, while the other variable is kept constant. It is useful to define the pressure variation in order to accomplish that:

2

4 4

w ti i

q c rp p Ep

kh kt

(42)

It is necessary a brief discussion of what this new parameter represents in terms



- 184 -

of oil production and why it is important. Higher pressure variations within the time for a fixed point for two similar

reservoirs implies that the one with higher pressure variation has less energy stored for oil elevation, which is undesirable economically and technically for production. Hence, it is desirable that the reservoir parameters generate smaller pressure drops within the time from a production point of view so that it is possible to maintain the oil production.

Naturally, it is desirable that the reservoir shows smaller pressure variation and pressure gradient values on points further away from the well for a fixed time.

Assuming monophasic flow with no fluid injection through the reservoir limits, the flow regime will evolve to pseudo-permanent, since there is no fluid influx to the reservoir. Therefore, pressure drops will not be balanced through the reservoir limits. The flow rate through the wellbore is assumed constant, therefore bigger pressure variations means there will be less fluid volume produced.

The standard values of reservoir parameters are listed in the Table 3.

Table 3. Reservoir parameters original values [3]. Parameter Value Unity

Permeability 9,87x10-14 m2

Viscosity 3x10-3

Pa.s

Production flow rate 35 m3/day

Rock formation depth 4 m

Porosity

0,2 Non-dimensional

Compressibility

1,33x10-9 Pa-1

Well radius

0,1 m

The results are displayed by plotting the pressure against either distance from the wellbore center or time, keeping the other variable constant. The chosen fixed distance and time values are 300m and 30 days. A set of five plots were generated to study each parameter with five different parameters values ranging from usual values found on the field to discuss the influence that each parameter bears on the behavior of the flow.

Following, Equations (23) to (41) are implemented in Mathematica and the FDM model is validated by comparison with the analytical solution curves. The fixed values of distance and time are set to t = 10 days and r = 300 meters. The initial pressure is set to zero in order to obtain the pressure variation instead of the pressure in the reservoir, and the final answer is the negative of the output generated by the method. The analytical model is used to obtain the distance from the center of the wellbore for which the pressure variation is less than 0.1kPa to simulate and infinite dimension reservoir (a reservoir in transient flow conditions). The extension of the grid goes



- 185 -

from the well radius until that radius and the last cells are set to remain at the initial pressure conditions all the time. The constant rate well is modeled through the source/sink term in Equation (32). The grid generated has (nθ nr nz)= (900 4 4) cells, and nt= 200 (∆t = 0.05 days) . The values of porosity and oil formation volume factor are updated by applying Equations (12) and (13). The viscosity is not updated at the end of every time-step, since it’s values are reasonably constant with pressure variations for oils with no gas dissolved [5].

After the model validation, the hypothesis regarding no gravitational effects is relaxed and the analytical solution is compared with the new solution.

The next step is to keep hypothesis regarding no gravitational effects and to impose a pseudorandomly distributed permeability through the mesh and compare the new solution to the analytical one again.

At the end, gravitational effects and permeability hypothesis are simultaneously relaxed (using the same permeability values generated) and the final solution is compared to the analytical solution.

4. Results

Figs. 1 and 2 are plotted following the procedure listed in the methodology section with respect to the analytical solution of the Diffusivity Equation. Figure 1 brings the pressure variation plotted against distance and fixed in time, and Figure 2 plots pressure variation against time for a fixed distance to the wellbore.

Fig. 1a shows the original solution within time and plot 1b plots the original solution within distance. At the beginning, the entire reservoir is at the same pressure pt=0. When the production starts, the pressure begins to fall. At first, the pressure measured at a point sufficiently far from the center of the wellbore (which might be relatively close to the wellbore) will remain with the initial pressure for a certain time, without the influence of the production. The pressure on that point starts to drop after a sufficiently long time. The boundary conditions do not affect the entire fluid mass immediately; this is a particular quality of the transient flow regime. The model will show null pressure variation on that point if not enough time is waited. As the boundary conditions travel through the reservoir, the pressure variation starts to increase and it is bigger closer to the wellbore. The radius variation is more significant on the values that the pressure variation will assume, since it appears with a higher exponent than the time. This explains the basic behavior of the pressure variation.

Fig. 1b and Fig. 2b show the solutions for different permeability values. The bigger the fluid permeability, the lower it will take to move the fluid to the surface. This results in in small pressure variations, and it will be possible to keep the flow for a longer period. In addition, the boundary conditions imposed will travel to the limits of the reservoir faster, which implies higher pressure variation values at the beginning when comparing to reservoirs with smaller permeability. Moreover, the reservoir will change its flow regime faster. Fig. 1b shows that the pressure variation grows faster for higher permeability values at the beginning of the production, and reach smaller values for longer periods. Fig. 2b shows that the pressure variation is much smaller for higher permeability values along the reservoir extension for a fixed time.

Fig. 1c and 2c show the solutions with different viscosity values. The fluid viscosity has the opposite effect of the permeability of the pressure variation. The



- 186 -

flow in the direction of the well demands more energy for highly viscous fluids because of the increase of the energy lost due to friction. That means the pressure variation will be higher for viscous fluids, supposing constant flow rates. At the beginning of the production, however, the pressure variation will be smaller for highly viscous fluids. That happens because the pressure drop due to the production start propagates slower to the reservoir extension. Fig. 1c shows that the pressure variation increases faster for more viscous fluids at the beginning of the production, and it is soon exceeded by the curves of less viscous fluids. Fig. 2c shows that less viscous fluids cause smaller pressure variation values along the reservoir extension for a fixed time.

Fig. 1d and 2d show the solutions with different rock formation depth values. Deeper rock formations have bigger drained areas. In the case of vertical wells, it is necessary less energy to make a bigger fluid volume flow inwards the well and the pressure variation will be smaller. It is a good solution to build horizontal wells when dealing with shallow rock formations, because the draining area will be larger, and a smaller number of the well will be necessary for a feasible production. Pressure Variation is proportional to the inverse of rock formation depth. Plotting both variables on the same plane would result in a hyperbole. Fig. 1d shows that the pressure variation increases fast for shallower rock formations within time and much slower and smoother for deeper formations. Fig. 2d shows that deeper rock formation depth implies better results for the pressure variation along the reservoir extension.

Fig. 1e and Fig. 2e show the solution for different porosity values. It is assumed that the increase of porosity is homogeneously distributed in the rock formation for this analysis. Pores that create vertical paths are irrelevant to the radial flow, whereas pores that create continuous radial paths increases the flow easiness. This means that the increase of pores has a similar effect to that of the increase of the permeability, but with a smaller intensity. Therefore, a porosity increase implies a pressure variation decrease. Fig. 1e shows that the pressure variation in time is smaller for reservoirs that are more porous, and Fig. 2e shows that the pressure variation is also smaller for more porous reservoirs within distance since it is easier to move oil from any point of the reservoir to the wellbore.

Fig. 1f and Fig. 2f show the solution or different compressibility values. The total compressibility can be regarded as a measure of the amount of energy that the rock and fluid may be stored in the form of potential energy through deformation. The pressure drop travels along the reservoir and decompresses both fluid and rock when the production starts. The fluid and the rock expand and mitigate the pressure drop during the decompression. In addition, the high value of compressibility means there will be more energy for the fluid elevation stored in the reservoir, which makes the pressure variation smaller. Fig. 1f shows that, for smaller compressibility values, the pressure variation is bigger, which implies that more energy is spent. Fig 2f shows that the pressure variation along the extension of the reservoir is bigger for smaller compressibilities; therefore, more energy is spent to move the fluid from a certain point in the reservoir to the wellbore.



- 187 -

(a) (b)

(c) (d)

(e) (f)

Fig. 1. Pressure variation within time for r = 300 m; (a) Original solution; (b) different permeability values; (c) different viscosity values; (d) different rock depth values; (e)

different porosity values; (f) different compressibility values.



- 188 -

(a) (b)

(c) (d)

(e) (f)

Fig. 2. Pressure variation within distance for t=30 days; (a) Original solution; (b) different permeability values; (c) different viscosity values; (d) different rock depth

values; (e) different porosity values; (f) different compressibility values.

In summary, the permeability, higher values of rock formation depth, porosity, and total compressibility favors the production, while the viscosity disfavors it.



- 189 -

5. FDM Validation

Fig. 3, 4, 5, 6 of the numerical model are generated, continuing the steps listed in the methodology section. Fig. 3 is used for the validation of the model, while Fig. 4 and 5 are used to relaxed gravitational and permeability hypothesis individually and Fig. 6 shows the results when both hypotheses are relaxed.

The value of the radius that accomplishes the required is around 2500m is found using the procedure described in the methodology section to find the distance where pressure variation is smaller than 0.1kPa. However, the external radius adopted was 3000m, as it was possible to simulate a bigger radius without much increase in computational cost.

It is clear that the numerical model estimates the values of the analytical solution with minimal errors from Fig. 3a and Fig. 3b. Indeed, if the biggest absolute deviation is taken from the two cases and each of them is divided by the respective average value of the analytical solution on the intervals calculated, the ratios are 4.4% e 1.5%. In reality, the biggest absolute deviations occur on plot regions where the actual analytical pressure variation values are much bigger than the average pressure variation value; hence, the two percentages values obtained are actually overestimation of the deviation.

Higher oscillation on the numerical solution is observed next to the wellbore. That may be justified by the high-pressure variation gradient values next to the well, which causes some numerical instability. Overall, the numerical approximation is good.

The numerical solution is slightly displaced when relaxing the gravitation hypothesis as can be seen in Fig. 4a and Fig. 4b.

However, there is still no vertical flow, since the rock formation is horizontal. The displacement is caused because now, when specifying the initial condition on the program input, it is the initial fluid flow potential that is being specified, but the calculations are still aiming to obtain the pressure conditions. The pressure must be lesser than when calculated for no gravitational effects as both pressure and height values are positive and the fluid flow potential is the value that the pressure was supposed to be. The pressure variation is obtained by taking the negative values of the solution as it was stated in the methodology section. In other words, the pressure variation must be bigger because the pressure obtained is smaller than the previous value.

Fig. 5a and Fig. 5b are plotted by returning the gravitation hypothesis and imposing a pseudorandomly distributed permeability.

This hypothesis, so far, is shown to be the one that most introduces error to the analytical model hypothesis. However, that depends on how other reservoir natural characteristics are, of course. For example, if the rock formation had greatly varying height variations, it is possible that the gravitational effect would play a more important role. Nevertheless, in this case, the analytical model is shown to be ineffective for reasonable estimations of the pressure variation values of an anisotropic and heterogeneous permeability distribution. On the other side, the qualitative behavior is still the same.



- 190 -

(a) (b)

Fig. 3. Validation of the numerical model. (a) validation for the fixed in distance solution (r=300m); (b) Validation for the fixed in time solution (t= 10 days).

(a) (b)

Fig. 4. Relaxing gravitation hypothesis. (a) pressure variation plotted against time; (b) pressure variation plotted against distance.

(a) (b)

Fig. 5. Relaxing permeability hypothesis; (a) pressure variation plotted against time; (b) pressure variation plotted against distance.



- 191 -

One gets Fig. 6a and Fig. 6b by relaxing both hypotheses of the previous two sections simultaneously.

The behavior of the numerical solution has changed further than the superposition of effects of the two relaxations. This is a consequence of the non-linearity of the Diffusivity Equation.

(a) (b)

Fig. 6. Relaxing both gravitation and permeability hypothesis; (a) pressure variation plotted against time; (b) pressure variation plotted against distance.

6. Conclusions

The pressure variation analysis within the various parameters from the solution of Diffusivity Equation for a radial, transient flow is one of the starting points of the viability study.

It is concluded that rock thickness, intrinsic permeability, reservoir total compressibility, and porosity mitigates the energy demanded to elevate the oil, while viscosity enhances the energy loss by analyzing each of the parameters present in the analytical solution of the Equation (16). The explanation for why each of these variables causes the effects listed follows the curves for each individual parameter results.

The numerical model was successful validated, and its results showed reasonably low errors. It is clear that the permeability hypothesis showed a greater influence on the numerical solution deviation from the analytical solution when comparing the results of relaxing gravitational and permeability hypothesis individually. The curve deviation obtained cannot be seen as a superposition of effects of both effects individually when both hypotheses were relaxed simultaneously, because of the equation’s non-linear behavior.

In addition, it is possible to conclude that the analytical model might not represent correctly a more complex reservoir; however, it can be used to qualitatively study the behavior of oil reservoirs.



- 192 -

Acknowledges

The authors acknowledge the support of the following agencies: the National Council for Scientific and Technological Development (CNPq-Project 30449420127), the Coordination for the Improvement of Higher Level Personnel (CAPES-Project 1431/14-5), and the University of Brasilia for funding this research.

References

[1] I. Wolfram Research, Mathematica, Version 10.1 ed., Champaign, Illinois: Wolfram Research, Inc,

2015.

[2] T. Ahmed. Reservoir Engineering Handbook, United States: Elsevier, 2010.

[3] A. J. Rosa, R. d. S. Carvalho e J. A. D. Xavier. Engenharia de Reservatório de Petróleo, Brazil:

Interciência, 2006.

[4] A. Szymkiewicz. Modelling Water Flow in Unsaturated Porous Media, Poland: Springer, 2013.

[5] T. Ertekin, H. A.-K. Jamal e R. K. Gregory. Basic Applied Reservoir Engineering, United States:

Society of Petroleum Engineers, 2001.

[6] R. Firoozabadi, F. Sonier. Numerical simulation of complex reservoir problems and the need for a

different line of attack. The Way Ahead, 2007, 3(3): 17-19.

[7] K. Aziz e O. A. Pedrosa. Use of Hybrid Grid in Reservoir Simulation. SPE Reservoir engineering,

1986, 1(6), 611-621.

Journal Website: http://ijgsw.comze.com/ You can submit your paper to email: [email protected]

Or [email protected]



- 193 -

The Challenges of Public Private Partnership (PPP) Projects in a Developing Country: The Case Study of the Lekki Toll Road Infrastructure Project in Lagos, Nigeria Christian Azuka Olele,

EdgeGold Concept Services Limited, Lagos, Nigeria E-mail: [email protected]

Abstract: In developed and developing countries, government has significant

constraints in their ability to make investment in the provision of public infrastructure. This has brought about the involvement of private sector participants in the provision of such services. Nigeria as a developing country, since the embracement of democracy in 1999 the civilian democratic government took up the application of PPP framework as a medium to providing important infrastructure through the involvement of the organized private sector. In other to make PPP attractive to the private sector in Nigeria, the government set up attractive investment opportunities for PPP investors and also provide fair legal framework where the private sector investor will be allowed to come up with concession companies, have guarantees that compensation will be paid by the government if she defaults. In the development of PPP infrastructure projects, the private sector participants are exposed to risks associated with assets investment in public projects. As a result, the private sectors generally are inspired to ask for soaring investment guarantees, special considerations and other investment enticements so as to guard their investments. This paper is aimed at looking at the recent PPP infrastructural developments in Nigeria where the government has clinched the PPP framework policy since the passing of the PPP act 20. And secondly, to look at the benefits associated with the investment of the private sectors in the development of infrastructure.

◆ Engineering Research Paper ◆



- 194 -

Keywords

Project Management, Public Private Partnership, PPP, Nigeria, Lekki Toll Road Infrastructure Project, Lekki Concession Company, LCC, LASG, This paper looks at the challenges of Public Private Partnerships (PPPs). First it looks at the demand for PPP infrastructure and the expected benefits to stakeholders. This is then followed by the following sections: the overview of Lekki Toll Road Infrastructure Project, the demand for PPP Infrastructure and the expected benefits to stakeholders, the regulatory and political context, the environmental and social implications, the stakeholder’s interest, involvement and how their needs were managed and overcome. In many countries, implementing infrastructure development projects have always been an issue because the projects are not always completed, and it results in failure on government or the public sector. Failures in these projects gave way for the formation of PPP Models that making the private sector organizations to synchronize with the public sector to see how project can be embarked upon and be delivered effectively. Today, the government of many countries (both developed and developing) is involved in public-private partnership. Adebanjo & Mann (2000) explained that regardless of its enormous advantages, the concept of public-private partnership concept is on the increase, and a report by Jamali (2004) has also listed the following reasons why PPP Projects in many countries are not successful

Lack of Government Commitment Poor Risk Management Policies Poor Banking Policies and Unavailability of Loans Poorly drafted Regulatory and Legal Framework Inadequate Mechanism to Attract Foreign Investors and the Local Private

Sector Participants. Lack of Transparency and Competition

On the political dimension, Mewu (2009) for example suggested that some projects being conceived under the PPP model had encountered several problems due to political instability in Thailand. Levy (1996) also noted that in the U.S Highway projects under the PPP Model in Washington State and Arizona had encountered problems due to political opposition from congress. In the PPP Concession model, a separate company is set up for each project and the services are provided as specified in, for example, Design, Build, Operate and Maintain (DBOM) contract. The concession company does not carry out the works by itself, but it subcontracts the design and construction, as well as the operations and maintenance work. Funding for the project is provided by its own equity and external



- 195 -

capital. Wolmer (2002) concluded that PPP models vary from short-term to long-term contract and the variation to these models are identified as follows:

The duration of Contract The Capital Assets Ownership Risks Allocation and Responsibilities The Value on Return of Investment (ROI)

Hayford (2004) explained that in PPP policies and guidance materials, there are some common principles binding them and are listed as follows:

Private Sector Confidence: This is an objective of fostering private sector confidence in the ability of government to facilitate PPP projects and properly assess PPP proposals, with a view to encouraging private sector investment by ensuring that enough players are invited for the bidding process especially for smaller social infrastructure projects.

Safeguarding the Public and Stakeholders Interest: The Public and Stakeholders are interested in their security whereby their interest is protected and this is done by measuring PPP proposals against public interest criteria relating to efficiency, accountability, fairness, public admittance, end user rights, security, confidentiality and right of representation and appeal at the planning stages by affected individuals and the project host communities.

Competitive Tendering and Probity: There should be assurance that the project will be subject to a tendering process that will be competitive with probity and fairness maintained in the procedure.

The Lekki Toll Road Infrastructure Project – Overview

The Lekki Toll Road Infrastructure Project came into being when Lekki Concession Company (LCC) was incorporated specially to design, finance, rehabilitate, upgrade, operate and maintain the Lekki Toll Road, under a 30-year Concession mandate from the Lagos State Government. LCC’s Concession is the first ever Toll Road Public Private Partnership (PPP) scheme and is designed to deliver high quality road infrastructure and related services along 49.4KM of the Eti- Osa Lekki-Epe axis of Lagos. The Project is in two phases: Phase 1 is the construction of the Lekki-Epe Expressway which extends between the intersection of Falomo Bridge (0.15 Km - 49.36Km). The Works include the construction of a new access onto the existing Falomo Bridge, widening of certain parts of the existing road, construction of three new toll plazas and rehabilitation of about 30Km of existing highway. Phase 2 of the project entails construction of 20Km of coastal road from Lagos Bar Beach to Ogumgbo Beach. The works includes construction of new highway, culvert structures, provision of street lightings, and construction of two new toll plazas. The environmental impact assessment of the project has been published; the gazetted road alignment is approved and published.



- 196 -

Figure 1 Admiralty Circle Toll Plaza at CH 3+000 of the Lekki –Epe Toll Road. Under an Abridged Works Contract dated February 2007, the first twenty Kilometres of road construction has been successfully completed but only twelve Kilometres has been handed back to the Concessionaire (LCC Monthly Report, 2011b). The Employer’s Requirements in the LCC Monthly Reports (2010) and LCC Monthly Report (2011a) describes the Works as being divided into five sections as follows:

Section1 (Km 0.2 to 0.4) Falomo. New access onto Falomo bridge; Section 2 (Km -0.15 to 3.8) Maroko. Widening to six lanes, including Mobil

bridge, Toll Plaza No 1; Section 3 (Km 3.8 to 15) Express. Widening of first 2.2Km to six lanes, Toll

Plaza No 2 (at Km 13.64); Section 4 (Km 15 to 20) Ajah. Widening to six lanes at roundabouts only, two

new roundabouts; Section 5 (Km 20 to 49.36) Eleko. Widening to six lanes to proposed Toll

Plaza No 3 (at Km 23). The Toll Plaza at Km 23 which was designed to be located at the vicinity of Pan African University (Lagos Business School) was cancelled as a result of multiple consultations with stakeholders from the host communities.

The first 20Km up to Ajah is characterised by very heavy traffic with significant encroachment of the Right of Way (Row) by numerous small and medium scale businesses. Most, if not all of these businesses, may be occupying the Row without legal ownership of the land. Another key feature of the first 20Km is the significant difficulty associated with relocation or removal of existing services. In particular, the overhead power lines represent a major issue and it is understood that toll plaza 2



- 197 -

may be repositioned to mitigate problems with moving some of the overhead lines. LASG is responsible for providing to LCC land which is free of occupation and services.

Figure 2 Rehabilitated & Upgraded Section of the Lekki-Epe Toll Road.

The Demand for PPP Infrastructure and the Expected Benefits to

Stakeholders

According to Dulaimi (2010), the idea of the private sectors being involved in the provision of basic infrastructures has been identified as an important approach for the government of many countries. Garvin (2009) concluded that PPP refers to the contractual arrangement where the private sector participates in infrastructural development services that could have been provided by the government. A wide range of projects such as hospitals, schools, roads, bridges, prisons, and light rail, water and sewage plants could be implemented using the PPP models. Shen (2006) explained that there is a worldwide trend towards PPP’s in providing infrastructural development aimed at generating greater efficiencies and synergies, increased revenues and reduced debts, open doors for foreign investors, enhanced market opportunities and increase in competition. Bamgbelu (2004) described the advantages of PPP to stakeholders as follows:

Value for Money: it was imagined that the private sector novelty of combining all construction phases will eventually gain synergies. Current proof recommend that this is actually happening on contracts established under the PPP/PFI platform already, and for this reason contributing to a lessening of



- 198 -

costs of operation, improved level of services and the benefits gained from the transfer of risks to the private sector.

Innovation and Spread of Best Practice: modernization of the private sector is one of the foremost factors of the development of the PPP scheme as the government has come to realize that proficiency and skill does not exist within the sector.

Flexibility: PPP’s have the integral flexibility to be established successfully to different types of infrastructure, and the theory that strengthens PPP can be adapted to many circumstances (Robinson et al, 2011)

The Regulatory and Political Context

The principles of governance are examined to show how it affects processes, decision-makers and the general population of the country. Robinson et al. (2011) explained that the laws governing PPP Projects includes the agendas for controlling, managing and influencing the deployment of financial, staff and physical resources in an effective and fiscal affordable way. These laws and regulations are bound to protect processes such as

Value for Money, Financial Accountability Processes Appraisal and Evaluation Process

These factors will permit the private sector to envisage the project’s profitability and make a decision whether the contract is valuable to bid. Clive (2003) is of the view that if the legal and judicial environment is not well classified, investors and project participants will see the project as volatile and extremely risky and run away.

The Environmental and Social Implications

Infrastructure development has in recent time’s assumed a central importance in Nigeria’s fight to attain social and economic stability. Both the federal government and state government are using infrastructure as the focal point of their administrations and policy enactments. Infrastructure generally has to do with the fixed provision of tangible assets on which other intangibles can be built on. Environmental impacts on the location of the project and in related areas with example (ground water condition, flowing rivers, streams, lakes, or the atmosphere) include consequences on environmental resources attributed to pollutants. Emecheta (2009) explained that infrastructure projects will always have consequential environmental and social impacts during construction and operation of projects. These impacts can be either positive or negative and may consists of continuous effects which is beyond the project at hand or the case of secondary impacts occurs where the effects goes beyond the projects stakeholders.



- 199 -

Stakeholders' Interest, Involvement and How their needs were

Assessed

The diagram below shows the key stakeholders in the Lekki Toll Road Infrastructure Project, Lagos, Nigeria which is based on the BOT (PPP) Model.

Figure 3 Key Stakeholders in the Lekki Toll Road Infrastructure Project Private Sector Stakeholder Group:

Lekki Concession Co Ltd (‘’LCC’’) Hitech Construction Co Ltd (‘’Hitech’’) High Point Rendel (‘’HPR’’)

The interest of the private sector stakeholder group as follows: Provision of Quality Road Infrastructure Provision of Safety & Security Improvement Measures on Roads Job Creation and Poverty Reduction Measures Increase in Cost of Property Rental, Sales and Lease

Public Sector Stakeholder Group: Lagos State Government (‘’LASG’’)



- 200 -

Eti-Osa Lekki Local Government Council The Lekki Toll Road Users / Local Community

The interest of the public sector stakeholder group as follows: Decrease in Traffic Congestion Crime Reduction and Increase in Safety as a Result of Reviewed Municipality

Scenery Rejuvenated Vicinity and Industrial Districts Increase in Lease and Other Development Revenues

How Challenges Encountered were Managed and Overcome

For PPP projects be successful, there would be challenges along the line of each phase. Bamgbelu (2004) stated that successful PPPs require sound transaction skills on the part of the public sector, as well as the experienced private sector service provider whom has the interest of the project at heart due to his better understanding and skills. Mittal and Kalampukah (2009) listed the following points as partnership challenges: Conflict of interest of partner organizations Diversity of underlying goals among partner organizations Insurance of Power Balance Communication barriers among partner organizations Difficulty in Resource Commitment Ambiguous Definition of Contracts and Agreements

Also Edwards (2010) explained that PPP projects are faced with challenges like the following:

High Upfront Cost High Procurement Cost Inadequate Expert Knowledge Citizenry Rejection and Public Opposition

Mittal & Kalampukah (2009) suggested the following measures to overcome the challenges in PPP infrastructure projects: Establishment of Open and Informal Communication channel amongst partner

Organizations Clear Definition of Project Charter Develop an Exhausting Risk Management Sharing Plan & Proper Definition

of Roles and Responsibilities Ensure Proper Commitment of Resources by Partners.

In the Lekki Toll Road Infrastructure Project, high upfront cost, high procurement cost, and engaging & managing stakeholders were the basic challenges encountered. The high cost of materials was discussed with the Engineering, Procurement,



- 201 -

Construction and Maintenance (‘’EPCM’’) contractor and she informed Lekki Concession Company (LCC) that the amount fixed for procurement of materials was submitted in the Bill of Quantities (BOQ) during the bidding process stating that inflation is also the major factor looking at the period at which the priced BOQ was submitted and the contract awarded.

Summary

The paper tackles the comprehensive idea of developing infrastructure through the use of PPPs as an opportunity for enhanced service and investment to achieve profit in return. In the implementation of PPP concepts; one has to understand the need for accelerated infrastructure development; proper constitutional, legislative, and institutional frameworks; also how to develop a PPP through lessons learnt from local and international PPP projects, knowledge and ideology behind funding of PPP projects; the conventional procurement systems and standard contract methods used in PPP projects; the prospect and sustainability of PPPs worldwide, and recent developments in PPP investments in developing countries. This also provided an overview of the Lekki Toll Road Infrastructure Project starting with the present state of decaying infrastructure in Nigeria, and a vision to improving better fiscal growth in the 55 years of Nigeria’s existence, it is expected that the public and private sectors of Nigerian economy would grab hold of the opportunities offered by sprouting universal affiliations to build stable infrastructures and development in Nigeria. In summary, if the wrong model is chosen or the risk management for each model is inaccurately evaluated there will be a high impact consequences on the parties involved in the Public-Private Partnership Scheme. Therefore, it is clear that the Lekki Toll Road Infrastructure Project has come to stay despite its challenges and many other PPP project are lined up in the country.

Acknowledgements

The author is grateful to the office of Public Private Partnership (PPP), Lagos State Government, Alausa, and Lekki Concession Company Limited (LCC) for providing the available data and reports At least but not the last I express my sincere gratitude to Dr. Samuel Ankrah of The University of Liverpool, UK for his kind constructive review of this manuscript.



- 202 -

Authors introduction

Christian Azuka Olele Registered Professional Engineering Geologist with the Council of Nigerian

Mining Engineers and Geoscientists (COMEG) and Project Manager experienced in the sector of Geotechnical Engineering in Nigeria, West Africa. He received his B.Sc.(2001) and PGdip(2006) degrees in Geology from the University of Port Harcourt, Choba, Nigeria; and his M.Sc.(2012) degree in Project Management from the University of Liverpool, Liverpool, U.K

Christian Azuka Olele supervised several Sub-Structure Projects that has to do with Geotechnics on the Lekki Toll Road Infrastructure Project (Pedestrian Bridges, Falomo Ramp Bridge and Toll Booths & Plazas), Precast & Sheet Piles for Osborne Jetty Terminal, Ikoyi, Lagos.

He is Interested in dealing with Project Managing engineering geology and geotechnical engineering of Projects in Nigeria and African countries. Currently he is heading the construction management team of EdgeGold Concept Services Limited, Lagos

References:

[1] Adebanjo, D. & Mann, R. (2000) ‘Identifying Problems in Forecasting Consumer

Demand in The Fast Moving Consumer Goods Sector’, Benchmarking: An International Journal, 7(30) : 223-230, Emerald, DOI: 10.1108/14635770010331397

[2] Bamgbelu, O. (2004) the Management, Organization and Interface in Delivering the PPP Obligation, Unpublished MSC Thesis, South Bank University, London.

[3] Impacts and Policy Lessons, World Bank Working Paper. Available at: http://rru.worldbank.org/Documents/PapersLinks/1481.pdf

Crampes, C., & Estache, A. (1998).’ Regulatory Trade-Offs in Designing Concession Contracts for Infrastructure Networks. Utilities Policy 7(1): 1–13.

[4] Dulaimi , M.F. (2010) ‘The Execution of Public-Private Partnership Projects in the UAE’, Construction Management and Economics, 28 (4) Available at: http://www.tandfonline.com.ezproxy.liv.ac.uk/doi/full/10.1080/01446191003702492

[5] Edwards, S. (2010) Construction Management Ideologies, 2nd edn. New York: Chapman & Hall.



- 203 -

[6] Emecheta, G.N. (2009) ‘Public-Private Partnership: Challenges and Prospects’, [Lecture to MBA Students]. University of Agriculture, Markurdi.

[7] Garvin, M.J (2009) ‘Enabling Development of the Transportation Public-Private Partnership Market in the United States ‘, Journal of Construction Engineering and Management 136 (4) Available at: http://ascelibrary.org.ezproxy.liv.ac.uk/coo/resource/1/jcemd4/v136/i4/p402_s1?view=fulltext

[8] Hayford, O. (2004) ‘Risk Allocation and the Standardization of Contracts in Public Private Partnerships’ [Online]. Available at: http://www.allbusiness.com/human-resources/benefits-insurance-benefits/298110-1.html

[9] Jamali, D (2004) ‘Success and failure Mechanism of public private partnership (PPPs) in developing countries: Insight from Lebanon context’. International Journal of Public Sector Management, 17 (5): 414-430

[10] Lekki Concession Company (2010) ‘May Departmental Report’, 5 (6): 3-10. Lagos

[11] Lekki Concession Company (2011a) August Departmental Report, 8 (3) PP. 3-7. Lagos

[12] Lekki Concession Company (2011b) September Risk Register: 1-3. Lagos [13] Levy, S.M. (2008) ‘Public – Private Partnerships in Infrastructure’, Leadership

and Management in Engineering [Online] 8 (4) Available at http://ascelibrary.org.ezproxy.liv.ac.uk/leo/resource/1/lmeeaz/v8/i4/p217_s1?view=fulltext

[14] Mewu, U.M. (2009) ‘Risk Management in Public-Private Partnership Road Concession Projects’: a case study of Lagos state and Lekki Concession Co Ltd. Unpublished B.Tech Thesis. Lagos State University, Ojo

[15] Mittal, A., & Kalampukah, P.K (2009) ‘Partnership Challenges in Achieving Common Goals- A Study of Public Private Partnership in E-Governance Projects, Unpublished M.SC Thesis, Umea School of Business

[16] Robinson, H., Carrillo, P., Anumba, C. and Patel, M (2011) Making Public Private Partnership (PPP) Effective for Infrastructure Projects: Role of Governance and Knowledge Transfer’ European Financial Review, Available at http://www.europeanfinancialreview.com/?p=3948

[17] Shen, L.Y. (2006) ‘Role of Public Private Partnership to Manage Risks in Public Sector Projects in Hong Kong’, International Journal of Project Management, 24: 587-594

[18] Wolmer, C. (2002) ‘Down the Tube: ‘The Battle of London’s Underground’, London, Aurum Press.

[19] Zhou, J., Chen, X-G., and Yang, H.W. (2008) ‘Control Strategy on Road Toll Pricing under a BOT Scheme.’ System Engineering Theory, Pract., 28(2): 148-151



- 204 -

Journal Website: http://ijgsw.comze.com/You can submit your paper to email: [email protected]




- 205 -

Genotypic Response to Salt Stress: II–

Pattern of Differential Relative Behaviour of Salt-Tolerant, Moderately Salt-Tolerant and Salt-Sensitive Wheat Cultivars under Salt Stressed Conditions

Ravi Sharma1,2*

1. Eco-Physiology Laboratory, Department of PG Studies & Research in Botany, K. R. College, Mathura 2. Formerly Head Department of Botany K R College, Mathura and Ex-Principal ESS ESS College, Agra(Dr B R Ambedkar University formerly Agra University, Agra) 281001 UP India E-mail: [email protected].

Abstract: Screening of 42 wheat (Triticum aestivum L) cultivars for their relative salt tolerance at the early seedling stage showed only 11 cultivars found to have < 60% reduction in shoot growth while majority of the 31 had > 60% reduction at 16 EC dsm-1 in contrast with root growth where almost a reverse trend was noticed as only 15 cultivars showed > 60% reduction whereas 27 had < 60% reduction proving shoot to be more sensitive to salinity than the root demonstrating shoot growth to be a better index of relative salt tolerance. Further, a level of 12 EC was found to be critical level. Based on these observations all the cultivars were categorized into salt–tolerant, moderately salt–tolerant and salt–sensitive groups exhibiting < 40%, 40–60% and > 60% reduction respectively in shoot length at 12 EC (dsm-1) over control. Thus, a clear pattern of differential relative behavior of the three groups is visible in the gradual decrease in shoot growth in both the salt-tolerant and moderately salt-tolerant cultivars and a sharp decline in the salt-sensitive cultivars.

Keywords: Wheat cultivars, salt stress, salt-tolerant, moderately salt-tolerant, salt-sensitive

1 Introduction

Almost more than fifty years from now, Bernstein and Hayward [1958] wrote: “An understanding of the physiology of salt tolerance of plants is important for an effective approach to the salinity problem which is of increasing widespread




- 206 -

occurrence”. Coupling an understanding of the genetic control of salt tolerance with physiological approach adds another dimension of a promise leading to the development of salt tolerant crops [Epstein, 1963, 1972]. It is axiomatic in modern physiology and biochemistry that specific capabilities of organisms depend on the synthesis of appropriate enzymes, this synthesis in turn being gene-controlled. Assuredly, the specific capabilities possessed by those plants able to tolerate saline conditions _ fatal to other plants are no exception to this generalization.

Furthermore, if strains of crops capable of coping with sea water or brackish water salinity could be generated, what is now a problem could become a vast opportunity for crop production by tapping the immense wealth of water and mineral plant nutrients of the oceans without the energy-costly process of industrial de-salinization. Several authors have drawn attention to genotypic differences between salt-tolerant and salt-sensitive plants in respect to a number of pertinent physiological and biochemical parameters [Epstein, 1972; Ogra, 1981; Sharma, 1982; Nauhbar, 2005 Yadav, 2006; Rani, 2007; Gautam, 2009; Parashar, 2011; Sharma, 2015, 2016]. It is becoming evident that the combined tools of the plant physiologist, geneticist and breeder must be brought to bear on the increasing salinity problems confronting irrigation agriculture on a worldwide scale.

2 Materials and Methods

As reported earlier [Sharma, 2015, 2016] forty two wheat cultivars procured from Wheat Directorate, Division of Genetics and Plant Breeding, I. A. R. I., New Delhi and Chandra Sekhar Azad University of Agriculture and Technology, Kanpur (UP), India were subjected to screening for salt resistance [Garrard, 1945; Sarin and Rao, 1956; Sheoran and Garg, 1978; Sharma, 1982] wherein shoot and root growths of seedlings

were recorded at definite intervals. Observations on the influence of salinity levels at 4, 8, 12 and

16 EC dsm-1 of salt solution and the controls on the total length of shoot and root at early seedling stage were recorded at 24 hour intervals from 48 hours after sowing up to the end of 120 hours under green safe light. The relative tolerance of different cultivars was evaluated on the basis of the percentage reduction in shoot growth at 12 EC.

3 Results

As indicated (Table 1) only 11 cultivars showed less than 60 percent reduction in shoot growth while majority of the 31 had more than 60 percent reduction at 16 EC level. This is in contrast with root growth where almost a reverse trend was noticed, in that, out of the 42 cultivars only 15 showed more than 60 percent reduction at 16 EC salinity level whereas 27 had less than 60 percent reduction. This clearly shows that the shoot is more sensitive to salinity than the root growth. This differential response of shoot and root growth is shown in Fig. 1 whence also the mean shoot growth was found to be more adversely affected than root growth clearly demonstrating that shoot



- 207 -

Table. 1 Shoot and rot growth of certain certain wheat cultivars at 16 EC (dsm-1) salinity level (Data expressed as percent over control)

S.No. Cultivar Control Shoot Growth Root Growth

1 HD-2236 100% 05.599 12.905

2 WL-410 100% 18.731 47.188

3 Sharbati sonora 100% 40.300 59.912

4 Moti 100% 09.995 29.576

5 Sonalika 100% 43.217 66.694

6 HD-2160 100% 82.600 71.188

7 HD-2135 100% 09.892 28.569

8 IWP-503 100% 13.939 31.834

9 HS-43 100% 29.261 40.818

10 UP-262 100% 08.150 26.168

11 HD-2177 100% 06.716 36.919

12 WG-1559 100% 09.358 6.588

13 HD-2267 100% 08.245 02.870

14 IWP-72 100% 05.144 05.826

15 HD-2282 100% 35.213 56.434

16 WL-711 100% 46.128 54.350

17 Raj-1482 100% 32.378 44.231

18 HD-2260 100% 22.894 40.201

19 WH-246 100% 33.929 49.960

20 WL-2200 100% 35.279 60.244

21 K-7634 100% 52.179 59.321

22 Raj-1556 100% 44.063 55.695

23 UP-154 100% 49.523 68.645

24 HD-1977 100% 40.456 41.449

25 WG-1558 100% 35.207 43.319

26 HD-2204 100% 34.948 55.594

27 WL-1531 100% 33.061 40.895

28 K-7631 100% 47.321 58.887

29 Raj-1409 100% 17.708 27.941

30 Raj-1493 100% 26.721 37.093

31 Raj-1494 100% 11.217 22.251

32 WL-903 100% 38.822 57.263

33 UP-171 100% 14.612 28.072

34 HD-2275 100% 17.329 37.768

35 HD-1593 100% 14.944 20.465

36 HD-2252 100% 35.381 42.741



- 208 -

37 HP-1303 100% 39.090 42.038

38 UP-115 100% 40.169 42.637

39 HD-1980 100% 44.369 40.599

40 CC-464 100% 24.080 47.878

41 HD-2009 100% 39.097 50.406

42 Kharchia 100% 30.542 55.269

CD at 5% P = 0.064

SEm ± 0.023

CD at 5% P = 0.351

SEm ± 0.126

growth is a better index of relative salt tolerance of different cultivars at early seedling stage. Also, 12 EC salinity level was found to be a critical level for majority of the cultivars. Thus, on the basis of the percent reduction in shoot growth at 12 EC salinity level over respective control all the cultivars were categorized into three groups, viz., salt-tolerant, moderately salt-tolerant and salt-sensitive, showing less than 40 percent, 40–60 percent and more than 60 percent reduction respectively (Table 2 and Fig 1).

The different rates of shoot growth of the three groups as affected by increasing level of salinity could be observed as depicted in Table 3 and Fig 2–5. There was a gradual decrease in shoot growth up to 16 EC level in both the salt-tolerant (HD-2160) and moderately salt-tolerant (Sonalika) cultivars. On the other hand, the salt-sensitive (IWP-72) cultivar showed a sharp decline in growth with increasing salt concentration proves a differential pattern of relative behavior of the three groups of salt tolerance.

4 Discussion

As discussed by several workers [Ayers et al., 1952; Bernstein and Hayward, 1958; Uprety, 1970; Ogra, 1981; Sharma, 1982, 1987; Sharma and Baijal, 1984a,b, 1985a, b; Nauhbar, 2005; Yadav, 2006; Rani, 2007; Rani et al., 2007, 2009; Gautam, 2009; Parashar, 2011; Sharma, 2013, 2015, 2016] reduction in shoot and root growth is one of the most commonly observed responses to salinity. Further, all the plant parts are not equally affected by salt stress, shoot growth is often suppressed more than the root growth in spite of the fact that roots are in direct exposure to saline environments [Meiri and Poljakoff-Mayber, 1970; Ogra and Baijal, 1978; Sharma, 1982, 1987; Sharma and Baijal, 1985; Nauhbar, 2005; Yadav, 2006; Rani, 2007; Rani et al., 2007, 2009; Gautam, 2009] These observations and others [Eaton, 1942; Bernstin and Hayward, 1958; Sharma, 1987; Nauhbar, 2005; Yadav, 2006; Rani, 2007; Rani et al., 2007, 2009; Gautam, 2009; Sharma, 2015, 2016] have reported more inhibition in shoot growth as compared to the root growth as a result of salt stress.



- 209 -

Table. 2 Relative tolerance of certain cultivars of wheat based on the percent reduction in shoot growth at 12 EC (dsm-1) salinity level

Group I

Salt-tolerant

(Less than 40% reduction)

Group II

Moderately Salt-tolerant

(40 – 60% reduction)

Group III

Salt-sensitive

(More than 60% reduction)

1. HD-2160 85.219 1. WL-903 59.726 1. Raj-1409 38.980

2. K-7634 80.353 2. HD-2282 57.470 2. Raj-1482 38.573

3. WL-711 71.437 3. HD-2009 57.321 3. HD-2135 35.555

4. WL-1531 71.020 4. K-7631 56.250 4. IWP-503 29.346

5. HD-2260 70.284 5. HD-1980 54.406 5. UP-262 28.956

6. UP-115 66.535 6. HP-1303 54.166 6. HD-2177 28.527

7. HD-2252 65.759 7. Raj-1556 52.875 7. Raj-1494 28.353

8. UP-154 60.714 8. Raj-1493 50.815 8. HD-1593 27.746

9. Sharbati Sonora 48.574 9. HD-2275 25.738

10. Sonalika 48.179 10. WG-1559 20.454

11. CC-464 46.866 11. UP-171 17.195

12.WL-2200 46.654 12. HD-2267 11.873

13. HS-43 43.948 13. HD-2236 11.491

14. WL-410 43.746 14. Moti 11.423

15. WH-246 43.644 15. IWP-72 7.818

16. WG-1558 43.276

17. Kharchia 43.035

18. HD-1977 43.010

Wheat Cultivars

19. HD-2204 42.878

As indicated in the Table 1 only 11 cultivars showed less than 60 percent reduction

in shoot growth while majority of the 31 cultivars had more than 60 percent reduction at 16 EC. This is in contrast with root growth where almost a reverse trend was noticed, i.e., out of the 42 cultivars only 15 showed more than 60 percent reduction at 16 EC whereas 27 had less than 60 percent reduction. This clearly showed that the shoot is more sensitive to salinity than the root growth. This differential response of shoot and root growth is shown in Table 1 where the mean shoot growth was found to be more adversely affected than the root growth. Thus, it was interesting to find that not all plant parts were equally affected. In spite of the fact that the roots were directly exposed to the saline environment it seemed significant that shoot growth was affected more adversely than the root growth. With this also 12 EC was found to be a



- 210 -

critical level for most of the cultivars. Thus, shoot growth seemed to be better criterion for relative salt tolerance of the cultivars of the same species at early seedling stage. Based on these observations all the 42 wheat (Triticum aestivum L) cultivars were categorized into three groups viz., salt–tolerant, moderately salt–tolerant and salt–sensitive, showing <40 percent, 40–60 percent and >60 percent reduction in shoot growth at 12 EC over respective controls (Table 2 and Fig 1). Further, the different rates of shoot growth of the three groups as affected by increasing level of salinity showed a gradual decline in both the salt–tolerant and moderately salt–tolerant cultivars. On the other hand, the salt–sensitive cultivars had a sharp decline in growth with increasing salt concentrations (Table 3 and Fig 2 - 5).

Fig. 1 Relative tolerance of three groups (salt-tolerant; moderately salt-tolerant and

salt-sensitive) cultivars of wheat based on the percent reduction in shoot growth at 12 EC (dsm-1) salinity level

The relative comparisons of seedling growth between different wheat cultivars indicated better performance of HD–2160 at almost all levels of salinity when compared with controls. It showed highest tolerance to salinity (i.e., 82.60 percent shoot growth at 16 EC over control) and IWP–72 showing highest inhibition in shoot growth (i.e., only 5.14 percent growth at 16 EC over control). The next cultivars which were relatively lesser tolerant but close to HD–2160 were K–7634, WL–711, WL–1531, HD–2260, UP–115, HD–2252 and UP–154. Based on these growth responses other cultivars of wheat followed a sequence of decrease as shown in Table 2 as far as their resistance to salt stress was concerned.

It was observed that the changes induced by addition of NaCl to the growth medium became more distinct with increasing salinity perhaps due to a higher intake of ions [Sharma, 1982, 1987; Sharma and Baijal, 1984a, b; Nauhbar, 2005; Yadav, 2006; Rani, 2007; Rani et al., 2007, 2009; Gautam, 2009; Parashar, 2011; Sharma et



- 211 -

al., 2011; Sharma, 2013, 2015, 2016] which resulted in toxicity [Ayers and Hayward, 1948; Ota and Yasue, 1957; Wahhab, 1961]. Osmotic effects might also have contributed to the low growth rates under saline conditions [Dumbroff and Cooper, 1974].

Fig. 2 Shoot growth behaviour of three salt tolerance groups in wheat cultivars

Table. 3 Relative salt tolerance of three groups （salt-tolerant; moderately

salt-tolerant and salt-sensitive） wheat(Triticum aestivum L) cultivars under salt stress at the early seedling stage (data expressed as percent over control)

Shoot Root

Control 4EC 8EC 12EC 16EC Control 4EC 8EC 12EC 16EC

GROUP I

Salt

Tolerant

100% 95.13

5

91.113 85.219 82.600 100% 94.62

3

83.760 77.584 71.188

GROUP II

Moderately

Salt

Tolerant

100% 86.52

3

70.72

8

48.179 43.217 100% 95.22

2

89.470 80.958 66.694

GROUP III

Salt

Sensitive

100% 82.92

1

39.09

4

7.818 05.144 100% 84.87

4

48.701 14.736 05.826

CD at 5% P = 0.064 SEm ± 0.023

CD at 5% P = 0.351 SEm ± 0.126



- 212 -



Thus, it is clear from the data that the cultivars differed in their ability to grow as

seedlings under high salinity levels. That wheat showed fairly large varietal differences to salt stress had also been reported earlier by Bhardwaj [1961], Sarin and Narayanan [1968], Sharma [1982, 1987, 2015, 2016], Sharma and Baijal [1984a, b,



- 213 -

1985a, b], Yadav [2006]. Varietal differences to salt stress were also reported in other agricultural crops by several workers [Ayers, 1953; Wahhab, 1961; Sarin, 1962; Bhumbla and Singh, 1965; Puntamkar et al., 1970; Taylor, 1975; Epstein, 1976; Maas and Hoffman, 1977; Ogra, 1981; Sharma, 1982, 1987; Nauhbar, 2005; Yadav, 2006; Rani, 2007; Gautam, 2009; Parashar, 2011; Sharma et al., 2011; Sharma, 2013, 2015, 2016].


5 Conclusion

The observations recorded clearly indicated that the shoot is more sensitive to salt stress than the root and that shoot growth is a better index of relative salt tolerance of different cultivars of the same species at early seedling stage with this also 12 EC salinity level was found to be a critical level for majority of the cultivars. Thus, on the basis of the percent reduction in shoot growth at 12 EC salinity level over respective control all the cultivars were categorized into three groups viz., salt-tolerant, moderately salt-tolerant and salt-sensitive, showing less than 40%, 40–60% and more than 60% reduction respectively. Conclusively, a clear pattern of differential relative behavior of the three groups is visible in the gradual decrease in shoot growth in both the salt-tolerant and moderately salt-tolerant cultivars and a sharp decline in the salt-sensitive cultivars.

Acknowledgements

Author is indebted to (Late) Dr B D Baijal (Retd Professor Plant Physiology Department of Botany Agra College, Agra) for expert comments and to the Principal K R College, Mathura for providing necessary facilities.



- 214 -

References

Ayers, A. D. 1953 Germination and emergence of several varieties of barley in salinized soil

cultures; Agron J 45: 68-71.

Ayers, A. D. and H. E. Hayward 1948 A method for measuring the effects of soil salinity on

germination with observations on several crop plants; Amer Proc Soil Sci 13: 224-226.

Ayers, A. D., J. W. Brown and C. H. Wadleigh 1952 Salt tolerance of barley and wheat in soil plots

receiving several salinization regimes; Agron J 44: 307-310.

Bernstein, L. and H. E. Hayward 1958 Physiology of salt tolerance; Ann Rev Plant Physiol 9:

25-46.

Bhardwaj, S. N. 1961 Physiological studies on salt tolerance in crop plants, X: Effect of NaCl and

Na2CO3 on early seedling growth of wheat and gram; Proc. Natn. Acad. Sci., India, 31B: 143 –

155.

Bhumbla, D. R. and N. T. Singh 1965 Effect of salt on seed germination; Sci Cult 31: 96-97.

Dumbroff, E. B. and A. W. Cooper 1974 Effects of salt stress applied in balanced nutrient

solutions at several stages during growth of tomato; Bot Gaz 135: 219 – 224.

Eaton, F. M. 1942 Toxicity and accumulation of chloride and sulphate salts in plants; J Agric Res

64: 357-399.

Epstein, E. 1963 Selective ion transport in plants and its genetic control; Desalination Res. Conf.

Poc. N.A.S., 942: 284 – 298.

Epstein, E. 1972 Physiological genetics of plant nutrition; Mineral Nutrition of Plants: Principles

and Perspectives, John Willey and Sons, New York, 325 – 344.

Epstein, E. 1976 Genetic adaptation of crops to salinity; Proceedings, Workshop on Salt Effects on

Plant Structures and Processes, Riverside Calif April 1976: 51-53.

Garrard, A. 1945 The effect of b-indolyl acetic acid on the germination and root growth of certain

members of cruciferae; New Phytol., 53(2): 165 – 176.

Gautam, Aruna 2009 The Problem of Saline Wastelands and their Management – A Biological

Approach with Special Reference to Mathura; PhD Thesis, Dr B R Ambedkar Univ., formerly

Agra University, Agra.

Maas, E. V. and G. J. Hoffman 1977 Crop salt tolerance current assessment; J Irrig Drainage Div

ASCE 103 ; 115-134.

Nauhbar, Suman 2005 Relative Tolerance of Crop Plants to Salt Stress at the Early Seedling Stage,

Ph.D. Thesis, Dr B R Ambedkar Univ., formerly Agra University, Agra.

Nieman, R. H. 1962 Some effects of NaCl on growth, phtosynthesis and respiration of twelve crop

plants; Bot Gaz 123(4); 279-285.

Ogra, R. K. 1981 Physiological studies on salt tolerance in Sorghum; Ph D Thesis. Agra University,

Agra.

Ogra, R. K. and B. D. Baijal 1978 Relative tolerance of some sorghum varieties to salt stress at

early seedling stage; Indian J Agric Sci, 48(12): 713-717.

Ota, K. and T. Yasue 1957 Studies on the salt injury to crops, XI The differences on the salt



- 215 -

resistance in the young wheat varieties; Gifu U Facul Agric Res Bull 8: 14.

Parashar, Nidhi 2011 Planning and Investigation for City and Industrial Effluent Utilization in

Abating Pollution of River Yamuna and Improving Agricultural Production; Ph D Thesis, Dr B

R Ambedkar Univ., formerly Agra University, Agra.

Poljakoff-Mayber, A. and J. Gale 1975 Plants in Saline Environments, Ecological studies;

Springer-Verlag, Berlin, Heidelberg, N.Y. 15: pp 213.

Puntamkar, S. S., P. C. Mehta and S. P. Seth 1970 Note on the inducement of salt resistance in two

wheat varieties by presoaking with different salts of varying concentrations; Indian J Agric Sci

41(8): 717 – 718.

Rani, Saroj 2007 Investigation on salt tolerance parameters specially growth and biochemical

traits for selection of salt tolerant lines in legumes at the early seedling stage; PhD Thesis Dr B.

R. Ambedkar Univ., formerly Agra University, Agra .

Rani, Saroj, S. K. Sharma and Ravi Sharma 2007 Effect of salinity on germination and early

seedling growth in six leguminous pulse crops; XXX Annual Conference Indian Botanical

Society, Jiwaji University, Gwalior (MP) India, 28 – 30 Nov. Abst & Souvenir S7.27: 156.

Rani, Saroj, S. K. Sharma and Ravi Sharma 2009 Germination and early seedling growth in six

leguminous crops under salt stress; Plant Archives, 9(1): 145 – 151.

Sarin, M. N. 1962 Physiological studies on salt tolerance of crop plants V. Use of IAA to

overcome depressing effect of sodium sulphate on growth and maturity of wheat; Agra Univ J

Res (Sci) 11: 187 – 196.

Sarin, M. N. and A. Narayanan 1968 Effects of soil salinity and growth regulators on germination

and seedling metabolism of wheat; Physiol Plant 21: 1201-1209.

Sarin, M. N. and I. M. Rao 1956 Effect of sodium sulphate on early seedling growth of gram and

wheat; Agra Univ J Res Sci 5(1): 143 – 154.

Sharma, Ravi 1982 Physiology of plant tolerance to salinity at early seedling stage; Ph D Thesis,

Agra Univ., Agra.

Sharma, Ravi 1987 Towards an understanding of the physiology of salt tolerance in wheat

(Triticum aestivum L) at early seedling stage; XIV International Bot Cong Berlin, W Germany,

19th July-1 Aug., Sym 22(9-8): 32.

Sharma, 2013 Screening for salt tolerance – Selection of salt tolerant and salt sensitive wheat

cultivars; Third National Conference on Innovations in Indian Science, Engineering and

Technology (Bilingual Hindi & English) Organized by Swadeshi Science Movement of India,

Delhi at CSIR National Physical Laboratory and IARI, New Delhi, Feb. 25 – 27, 2013;

Souvenir: 270.

Sharma, Ravi 2015 Genotypic response to salt stress: I – Relative tolerance of certain wheat

cultivars to salinity; Adv Crop Sci Tech 3(4): 1000192 .

Sharma, Ravi 2016 Indole-acetic acid oxidase enzyme activity in three wheat cultivars under salt

stress conditions at the early seedling stage; Adv Plants Agric Res, 4(1): 1 – 8.

Sharma, Ravi and B. D. Baijal 1984a Ion uptake and ATPase activity in certain wheat cultivars

under salt stress conditions; VIII All India Bot Conference, Rajasthan University, Jaipur 28-30



- 216 -

Dec., J Ind Bot Soc 63: 97.

Sharma, Ravi and B. D. Baijal 1984b Carbohydrate metabolism in salt tolerant and salt sensitive

wheat cultivars under salt stress conditions; VII All India Botanical Conference, Rajasthan Univ,

Jaipur 28-30 Dec J Ind Bot Soc 63: 93.

Sharma, Ravi and B. D. Baijal 1985a Genotypic response to salt stress I: Screening for

salt-resistance – selection of salt-tolerant and salt-sensitive wheat varieties; National Seminar

on Plant Physiology, Institute of Agricultural Sciences, B.H.U., Varanasi 12-23, Feb. 127:

74-75.

Sharma, Ravi and B. D. Baijal 1985b Genotypic response to salt stress II: Differential

physiological and biochemical response of salt-tolerant and salt-sensitive wheat cultivars;

National Seminar on Plant Physiology, Institute of Agricultural Sciences, B.H.U., Varanasi

12-23, Feb. 128: 75-76.

Sharma, Ravi, Nidhi Parashar, S. K. Sharma, D. K. Singh, Dinesh Babu and A. K. Goswami 2011

Toxic effects of city and industrial effluents vis – a – vis effects of salinity and heavy metal

stresses on certain crop plants; XXXIV All India Botanical Conference of The Indian Botanical

Society, Oct., 10 – 12, 2011, Department of Botany University of Lucknow, Lucknow, Souvenir

and Abstracts, Section VII Plant Physiology, Biochemistry and Pharmacology, O. VII. 29: 285.

Sheoran, I. S. and O. P.Garg 1978 Effect of salinity on the activities of RNase, DNase and protease

during germination and early seedling growth of mung bean; Physiol Plant, 44(3): 171 – 174.

Taylor, R. M., E. F. Young Jr and R. L. Rivera 1975 Salt tolerance in cultivars of grain Sorghum;

Crop Sci 15: 734-735.

Uprety, D. C. 1970 Physiological studies on salt tolerance in two varieties of pea; Ph. D. Thesis,

Agra Univ., Agra

Wahhab, A. 1961 Salt tolerance of various varieties of agricultural crops at the germination stage,

Salinity Problems in Arid Zone; Proc Tehran Symp UNESCO 185.

Yadav, Neetu 2006 Physiology of Salt Tolerance for Effective Biological Control of Salinity, Ph D

Thesis, Dr B R Ambedkar Univ., formerly Agra University, Agra.



ISSN:2372-0743 print International Journal of Ground Sediment & Water Vol. 052017ISSN:2373-2989 on line

- 217-

Groundwater arsenic contamination in shallow alluvial aquifers of Bhulri Shah Karim taluka, Tando Muhammad Khan district, Sindh, Pakistan

Adnan Khan*, Viqar Husain, Asal Eghbal Bakhtiari, Muhammad Hamza Khan

Department of Geology University of Karachi, Karachi, 999010, Pakistan E-mail: [email protected].

Abstract: The aim of present study is to determine the groundwater arsenic contamination and identification of its possible sources through hydro-geochemistry in Bhulri Shah Karim Taluka which is part of Tando Muhammad Khan district, Sindh. For this purpose, 66 groundwater samples taken from shallow wells (depth < 30 meters) were analyzed to determine physicochemical and microbiological parameters including arsenic. Hydro-geochemical data reveal that groundwater is marginally saline (Mean TDS: 1166 mg/L) and slightly alkaline (Mean pH: 7.25). More than half of the groundwater wells (n = 25) are sewage impacted as indicated by the occurrence of pathogenic bacteria. Strong positive correlation of HCO3 with SO4 (r = 0.61), Cl- (r = 0.54), F- (r = 0.52) and NO3(r = 0.5) was observed which suggest that complex geochemical processes are operating in the study area. Hardness of groundwater showed the strong relationship with NO3 (r = 0.57) and HCO3 (r = 0.47) indicating the mineral and fertilizer contribution. On the other hand, weak but positive correlation of Fe with NO3(r = 0.22) suggests that denitrification process is active but slow in study area. In about 40% groundwater samples arsenic occurs in alarmingly high concentrations (up to 250µg/L) against WHO permissible limit of 10 µg/L for drinking water. About one third of total sewage impacted wells show arsenic concentrations in the range of 10-200 µg/L suggesting that arsenic release is somehow linked with sanitation. Correlation of As with Fe (r = 0.21) is weak but positive and strong with PO4 (r = 0.48) which suggest that as released from organic matter is followed by reductive dissolution of FeOOH through bacterial respiration in the groundwater of Bhulri Shah Karim.

Keywords: Groundwater, hydro-geochemistry, arsenic, pollution, Indus delta, Sindh



- 218-

Introduction

In many flood plain aquifers of South Asia, widespread contamination of As is reported (Smedley and Kinniburgh, 2002; Farooqi et al., 2009) which is mainly restricted to sedimentary aquifers of Holocene age (Bhattacharya et al., 1997; Ishiga et al., 2000; Anawar et al., 2002, 2003). Generally accepted geochemical model for arsenic release into such aquifer waters is mobilization of arsenate absorbed to Fe (iii) oxyhydroxide coated sediments under reducing conditions. Inorganic As is considered a potent human carcinogen, with increased risk of lung, kidney, liver and skin cancer (NRC, 1999; Fatmi et al, 2009; IARC, 2004; Ramadan and Al-Ashkar, 2007). Since the source of arsenic appears to be both natural and anthropogenic (Acharyya et al., 1999; Chowdhury et al., 1999; Nickson et al., 2000; McArthur et al., 2001; Anawar et al., 2002; Harvey et al., 2002).

Although alarmingly high concentration of arsenic is reported in the groundwater of deltaic regions of the world, but very limited studies have been carried out in the Indus deltaic plain which are attempted to the arsenic toxicity in southern part of Sindh province ( e.g. Arain et al., 2009; Kazi et al., 2009; Majidano et al., 2010). Elevated As concentration (up to 800μg/L) in Indus deltaic aquifers is reported to be caused by both Geogenic and anthropogenic (mainly sewage contamination) factors (Husain 2009; Naseem, 2012; Khan et al., 2014).

Study Area.

Bhulri Shah Karim (BSK) is Taluka of Tando Muhammad Khan district which is located between 68º15’E-68º45’E longitudes and 25º00’N-25º30’N latitudes, covering an area of 2600 km2. The study area is 19 m above sea level and 58 km away from Hyderabad (Fig. 1). The main crops in the area are wheat, rice, cotton and sugarcane. Climate of this area is semi-arid subtropical with an average rainfall of about 220 cm. The average humidity of about 76% with mean annual temperature of 84.2 oF (Kureshy, 1977; Haq, 1999; Memon, 2005). Semi-arid climate and scarce rainfall in study area have constrained the irrigation system to switch from surface water source to groundwater.

Fig. 1 Location map of Study area.


- 219-

Study area lies in lower part of Indus flood plain which covers an area of about 34 million hectares (over 85 million acre). This plain is filled with very thick fluvial deposits brought by Indus River during Pleistocene to Recent time (Kazmi and Jan, 1997). BSK taluka mostly occupies cultivable land constituting the enormous amount of alluvium (up to > 200 meter depth) brought by the Indus River and its tributaries from Himalaya during Holocene period (Chauhan and Almedia, 1993). The subsurface sediments are underlain by Tertiary rocks, which are exposed on the western margin of this taluka (Fig. 2). Study area enjoys very simple topography where most of the area is flat with devoid of any prominent natural drainage both surface and subsurface (Qureshi et al, 2008). Surface sediments are very fine textured comprising silt and clay with relatively less amount of sand.

Fig. 2 Surface geology of study area (after Akhtar et al., 2012). The fluvial landscape in the area is drained by Indus River (total length of 3180

km) which starts from Tibet and flows down along the transact of Pakistan and ultimately culminate the Arabian Sea in south. About 150 km wide alluvial valley of Indus plain is, formed by accumulation of enormous amount of sediments (600 million tons) in Indus Basin between Kirthar Range west in the and Thar Desert in the East (Fig.3). BSK and adjacent areas are characterized by active flood plain meanders and channel process. These Recent geomorphic signatures are rich in young and reactive organic matter. Indus River switched its channel from east to west of


- 220-

Hyderabad in recent past and ultimately formed its present course in the vicinity of delta (Wilhelm, 1967). Hierarchal four main aggradational stages of Indus River are Jacobabad-Samaro, Shehdadkot-Jhudo, Qambar-Tando Allayar, Ghambat-Tando Muhammad Khan (Kazmi and Jan, 1997).

Fig. 3 Geomorphic distribution of Lower Indus plain (after Holmes, 1968).

The remnants of these major avulsions includes oxbow lakes, sand bars, swales and fresh channel scars which exists near Khairpur to Daulatpur, Matiari and Tando Muhammad Khan districts (Fig. 4). The land through which river Indus passed during Holocene is prone to be the worst arsenic affected part of Sindh province including the study area.

Fig. 4 oxbow lake in Tando Muhammad Khan district.


- 221-

Materials and Methods

Sixty six groundwater samples were collected from shallow wells (depth >24 m) in sterile plastic bottles (0.5 and 1 liter) for the determination of physicochemical parameters including arsenic. Methods and equipments used to determine groundwater attributes are summarized in Table 1. For nitrate determination, groundwater samples were collected in100 ml bottles and 1 ml boric acid solution was poured with syringe to cease any reaction which could alter the nitrate (NO3) concentration. For pathogenic bacteria determination groundwater samples were directly poured into microbiological testing kits which were put in the incubator at 30° for 24 hours to get result.

Table 1. Equipment/methods used to analyze groundwater samples collected from

Bhulri Shah Karim taluka, Sindh. S.

No. Parameters Equipments

Turbidity Turbidity meter, Lamotte, model 2008, USA

1 Electrical Conductivity/TDS EC meter (Eutech Cyber Scan CON 11)

2 pH pH meter (JENCO 6230N)

3 Alkalinity 2320 Standard Method (1992)

4 Carbonate mg/L Titration Method, (USSL, 1954)

5 Bi-carbonate mg/L Titration Method, (USSL, 1954)

6 Calcium mg/L EDTA Titration Method

7 Chloride mg/L Argenometric Titration Method

8 Magnesium mg/L Titration Method

9 Potassium mg/L Flame photometer (JENWAY PFP7)

10 Sodium mg/L Flame photometer (JENWAY PFP7)

11 Sulphate mg/L Spectrophotometer (DR 2800)

12 Nitrate mg/L Spectrophotometer, HACH-8171

13 Hardness as CaCo3 EDTA titration standard method (1992)

14 iron Spectrophotometer (Model: U-1100, HITACHI)

15 Fluoride Spectrophotometer, SPADNS (HACH).

16 Arsenic Perkin Elmer A Analyst 600 Graphite Furnace Atomic

Absorption Spectrophotometer

Principal component analysis (PCA).

Statistical analysis was carried out by using PCA on data set of ground water parameters of Bulri Shah Karim taluka. The output of PCA was used to explain the variation of major data set of interrelated variables with small set of independent


- 222-

variable (Simeonov et al, 2003) and to trace the factors which affect each other. Components with Eigen values <1 were not taken into account as these explain insignificant variation.

Results and Discussion

1. Groundwater characterization

1.1. Physical properties Groundwater salinity is highly variable in Bhulri Shah Karim taluka where it

ranges between 260-5312 mg/L with a mean of 1166 mg/L. The pH is marginally alkaline (range: 5.9-8.17, mean: 7.2) which is generally within the permissible limit (6.5-8.5) of WHO set for drinking water. Slight variation in the pH of groundwater of study area may be attributed to the heterogeneous soil alkalinity, reaction of silicate minerals, fertilizer use, human activities, water logging and evaporation (Shahid and Jenkins, 1994; Sharma et al. 2000; Vanlenza et al., 2000; Farooqi et al., 2009; Nicolli et al, 2010). Ground water is formed to be very hard (mean: 432 mg/c) where about 38% samples showed variable value of hardness ranging between 140-1480.

Table 2. Physicochemical parameters of groundwater in Bhulri Shah KarimTaluka.

S. No.

Sample No.

Coordinates Well depth

(meters) pH TDS

(mg/L)

Micro

+ve/-ve

Alk. (m.mol/

l)

Hard.

(mg/l)

Lat. ºN

Long. ºE

1 TMK34 250653 682355 8 6.2 2342 +ve 9.2 810

2 TMK53 245147 681957 11 7.05 3104 +ve 5.2 980

3 TMK55 245132 682100 18 7.08 902 -ve 5.6 4604 TMK56 245121 681939 7 7.08 881 -ve 7.2 4105 TMK57 245144 681950 8 7.05 1085 -ve 4.8 5506 TMK58 245204 682003 15 7.32 683 +ve 6 3307 TMK120 245627 682123 24 7.49 753 -ve 7 3808 TMK121 245622 682036 24 7.05 908 -ve 7.2 450

9 TMK122 245625 682017 9 6.9 1196 -ve 8 55010 TMK123 245620 682017 8 6.69 5312 +ve 17.6 148011 TMK125 250218 682605 11 7.8 260 -ve 2.4 14012 TMK188 245759 682700 8 7.21 605 -ve 6 33013 TMK189 245636 682556 9 7.21 1009 -ve 6 41014 TMK190 245620 682547 12 7.06 1100 +ve 4.8 49015 TMK192 245653 682419 12 8.17 889 -ve 7.2 15016 TMK193 245445 682301 9 7.4 513 -ve 3.2 240


- 223-

17 TMK195 245220 681902 9 6.97 2176 +ve 9.2 61018 TMK196 245322 681820 12 7.89 773 -ve 7.6 160

19 TMK66 245814 682410 15 7.37 746 -ve 5.8 370

20 TMK70 245729 682947 15 7.82 298 -ve 2.8 17021 TMK79 245824 684552 9 7.66 626 +ve 3.6 32022 TMK116 250111 682348 11 7.11 1523 +ve 7.2 65023 TMK117 245954 682244 11 7.96 2009 -ve 12.8 35024 TMK191 245809 682433 9 7.99 397 -ve 3 18025 TMK202 245915 682350 12 7.37 986 +ve 4.6 38026 TMK203 245953 682425 9 7.21 737 -ve 4.8 350

27 TMK59 245219 682030 20 7.85 1149 -ve 7 380

28 TMK60 245531 682115 18 8.03 1574 -ve 9.6 230

29 TMK61 245518 681944 8 7.29 643 -ve 6 350

30 TMK62 245522 681832 9 7.56 824 +ve 8 430

31 TMK63 245436 682152 8 7.49 839 -ve 6 410

32 TMK64 245612 682126 20 7.52 406 +ve 4.4 250

33 TMK65 245721 682106 9 7.53 480 -ve 4.4 260

34 TMK119 245749 682141 9 7.23 1670 +ve 10 58035 TMK194 245428 682039 8 7.2 718 -ve 5.6 38036 TMK197 245306 682027 8 7.31 795 -ve 4.8 33037 TMK198 245357 681909 9 6.89 1754 -ve 4.2 68038 TMK199 245319 682028 21 7.23 1016 -ve 4 46039 TMK200 245416 682117 9 7.89 695 +ve 6.8 26040 TMK201 245628 682144 9 7.28 795 -ve 4.2 380

41 TMK36 250648 682140 14 6.42 1266 +ve 9 460

42 TMK37 250648 682140 21 6.36 1271 -ve 9.4 450

43 TMK38 250638 682130 11 6.61 574 -ve 7 340

44 TMK39 250633 681808 11 6.5 1067 +ve 9 440

45 TMK40 250554 682013 11 6.6 993 -ve 7.6 450

46 TMK118 ----- ----- 8 7.81 1077 -ve 8.2 310

47 TMK67 245736 682511 18 8.08 399 -ve 4.2 170

48 TMK68 245801 682600 9 7.55 870 -ve 6.4 300

49 TMK69 245759 682719 15 6.98 1862 +ve 4.4 880

50 TMK124 250004 682340 15 7.51 908 -ve 6.4 40051 TMK186 250035 682739 14 7.95 593 -ve 5.4 28052 TMK187 245840 682700 24 7.79 711 -ve 4.1 330

53 TMK28 250742 682951 21 6.84 2208 -ve 5.2 800


- 224-

54 TMK29 250742 682951 8 6.29 1121 -ve 7.6 610

55 TMK30 250754 682601 9 7.47 454 +ve 4.2 180

56 TMK31 250857 682558 11 6.29 1160 +ve 10 660

57 TMK32 250857 682558 12 6.34 2374 +ve 7.6 920

58 TMK33 250757 682505 14 6.27 858 +ve 8.4 450

59 TMK35 250937 682258 7 6.09 1114 +ve 7.6 570

60 TMK52 250423 682840 15 8.15 3411 -ve 16.8 260

61 TMK114 250253 682538 11 6.86 2425 +ve 11 107062 TMK148 250140 682525 8 7.54 617 -ve 6 32063 TMK149 250133 682533 8 6.83 1036 +ve 7.4 52064 TMK185 250114 682645 8 7.4 708 -ve 4.8 30065 TMK204 250134 682431 11 8.11 585 +ve 5 17066 TMK205 250348 682843 15 7.57 2138 +ve 8.6 270

Table 3.Chemical characteristic of groundwater from Bhulri Shah Karim taluka.

S.

No.

Sample

No.

Ca

(mg/L)

Mg(mg

/L)

HCO3(

mg/L)

Cl-(mg/

L)

SO4(m

g/L)

PO4(m

g/L)

NO3(m

g/L)

F-

(mg/L)

Na

(mg/L)

K(mg/

L)

Fe(mg/

L)

As

μg/L

1 TMK34 180 87 460 587 510 - 0.64 0.91 462 9 0.05 0

2 TMK53 216 107 260 1446 107 0.27 1.46 0.41 676 11 0.87 100

3 TMK55 104 49 280 257 54 - 0.58 0.09 107 7.5 0.62 0

4 TMK56 76 53 360 156 96 - 0.58 0.34 128 6 0.07 0

5 TMK57 128 56 240 351 103 - 0.74 0.41 141 9.8 0.02 0

6 TMK58 80 32 300 139 36 0.58 0.62 0.33 91 4.8 0.45 80

7 TMK120 72 49 350 85 104 - 1.69 0.48 91 6.6 0.44 40

8 TMK121 108 44 360 173 96 0.12 1.07 0.48 113 7.4 0.08 60

9 TMK122 116 63 400 255 160 0.15 0.89 0.52 168 8.6 0.05 80

10 TMK123 472 73 880 1743 556 - 19.41 1.21 1020 216 0.89 0

11 TMK125 32 15 120 37 26 - 0.65 0.37 27 3.3 0.04 0

12 TMK188 92 24 300 67 70 0.82 0.70 0.58 63 4.2 1.15 250

13 TMK189 80 51 300 243 128 - 0.44 0.51 164 11 0.14 5

14 TMK190 104 56 240 344 124 0.21 0.60 0.41 170 6.2 0.28 200

15 TMK192 36 15 360 156 100 0.34 0.60 1.76 240 3 0.06 200

16 TMK193 54 26 160 109 81 - 0.37 0.52 71 4 0.09 0

17 TMK195 108 83 460 639 315 0.15 0.93 0.9 476 10.6 0.61 200

18 TMK196 28 22 380 110 61 - 0.50 1.28 198 4.1 0.02 0

19 TMK66 68 49 290 141 89 0.18 0.63 0.15 96 7.1 0.06 100

20 TMK70 36 19 140 42 30 - 0.58 0.44 29 4.7 0.04 0


- 225-

21 TMK79 62 40 180 157 84 - 1.29 0.46 72 11.4 0.04 0

22 TMK116 116 87 360 386 270 - 0.91 0.57 230 8.7 0.06 0

23 TMK117 60 49 640 454 250 - 1.22 2.72 540 14.5 0.04 5

24 TMK191 40 19 150 67 59 - 0.39 0.57 56 3.9 0.03 0

25 TMK202 96 34 230 262 154 0.15 0.91 0.9 167 5 0.01 70

26 TMK203 88 32 240 140 126 0.22 0.68 0.45 93 14 0.4 25

27 TMK59 78 45 350 319 107 - 0.73 0.54 236 6.1 0.04 0

28 TMK60 44 29 480 489 45 0.87 1.29 0.94 448 6.2 0.23 150

29 TMK61 68 44 300 103 64 - 0.45 0.52 78 4.1 0.19 30

30 TMK62 84 53 400 117 74 - 0.72 0.3 97 6 0.02 0

31 TMK63 72 56 300 164 112 - 0.56 0.4 119 5.4 0.36 5

32 TMK64 44 34 220 39 46 0.02 0.57 0.03 33 3.8 0.04 100

33 TMK65 52 32 220 67 61 - 0.57 0.04 54 4 0.08 40

34 TMK119 112 73 500 390 230 - 1.27 0.75 322 9 0.01 5

35 TMK194 60 56 280 117 108 - 0.55 0.99 80 4.3 0.07 100

36 TMK197 92 24 240 159 138 - 0.46 0.57 134 4.1 0.45 100

37 TMK198 140 80 210 651 205 - 0.58 0.66 306 6.2 0.07 0

38 TMK199 96 53 200 315 130 0.23 0.76 0.68 144 10.6 0.04 5

39 TMK200 60 27 340 92 98 - 0.67 0.43 124 5. 8 0.02 25

40 TMK201 90 40 210 166 161 0.19 0.63 0.79 97 8.7 0.55 30

41 TMK36 76 66 450 305 152 - 0.70 0.6 260 11 0.08 0

42 TMK37 96 51 470 312 132 - 0.93 0.6 258 12 0.05 5

43 TMK38 68 41 350 71 42 - 0.54 0.46 47 7 0.04 0

44 TMK39 76 61 450 195 178 - 0.53 0.97 234 7 0.15 0

45 TMK40 68 68 380 255 106 - 0.55 0.34 198 5 0.02 40

46 TMK118 60 39 410 248 75 0.08 0.86 0.54 233 13.4 0.02 10

47 TMK67 36 19 210 53 29 - 0.88 0.6 67 3.6 0.03 5

48 TMK68 48 44 320 219 56 - 1.49 0.31 169 6.4 0.53 20

49 TMK69 148 124 220 815 73 - 1.07 0.24 232 94.2 0.12 0

50 TMK124 72 53 320 192 110 - 0.65 1.15 135 10.6 0.05 0

51 TMK-186 56 34 270 74 81 - 0.5 0.67 82 4.3 0.05 0

52 TMK-187 78 33 260 138 88 - 0.71 0.49 103 3.7 0.06 100

53 TMK28 128 117 260 549 655 - 0.98 0.94 422 5 0.22 0

54 TMK29 124 73 380 269 186 - 0.37 0.8 184 6 0.04 5

55 TMK30 36 22 210 70 40 - 0.62 0.58 79 2 0.05 20

56 TMK31 112 92 500 237 178 - 0.45 1.38 198 6 0.23 5

57 TMK32 172 119 380 658 515 - 0.81 0.75 422 11 2.78 0


- 226-

58 TMK33 80 61 420 103 100 - 0.43 0.22 102 6 0.09 5

59 TMK35 120 66 380 223 164 - 2.28 0.5 137 7 0.07 0

60 TMK52 68 22 840 823 615 - 0.61 2.21 1098 4.5 0.04 5

61 TMK114 288 85 550 593 455 - 1.17 0.76 368 9.5 0.07 0

62 TMK-148 52 46 300 77 66 - 0.76 0.43 70 5.5 0.02 0

63 TMK-149 140 41 370 193 151 - 0.77 0.29 127 5.6 0.03 0

64 TMK-185 72 29 240 167 84 - 0.41 0.72 114 3.3 0.04 5

65 TMK204 40 17 250 88 75 - 0.42 0.93 126 3.8 0.03 0

66 TMK205 36 44 430 616 332 - 0.57 3.16 627 4.2 0.05 0

1.2. Chemical characteristics of groundwater Analytical results of groundwater samples (n=66) collected from Bhulri Shah

Karim taluka have been given in Table 3. Both calcium and magnesium concentrations are highly variable which ranges between 28-472 mg/L and 15-124 mg/L respectively (Table 3). Although mean value (92.33 mg/L) of Ca is within the admissible limit of WHO (100 mg/L) for drinking water but 30% samples show Ca > 100 mg/L. On the other hand, 44% of total collected samples are very high in Mg concentration above WHO permissible value of 50 mg/L for drinking water. Interestingly, most of the samples high in their Ca content also exceed corresponding Mg concentration (Table 3). It suggests that the source of these ions is same which seems to be the dissolution of dolomitic limestone fragments occurring in the alluvium of study area. Moreover, elevated Ca concentration in groundwater of study area suggests feldspar dissolution which is assumed to be one of the main sources of this ion as feldspar is one of the most reactive minerals during chemical weathering (Mast and Drever, 1987). Similarly incongruent dissolution of plagioclase can release Ca (Saether et al, 2001) into the groundwater. Sodium and chloride concentrations ranged between 27-1098 mg/L and 37-1743 mg/L respectively. One third of total groundwater samples show very high sodium concentrations (> 200 mg/L) and about 40% wells have elevated chloride contents (> 250 mg/L) against the permissible limit of WHO for drinking water.

Generally very low nitrate content (< 1 mg/L) occurs in the groundwater of Bhulri Shah Karim taluka which is within the permissible guidelines of 10 mg/L for drinking water set by WHO, 2004. It suggests that nitrate reducing bacteria are very active in alluvial aquifers of study area. Nitrate generally moves in soil and groundwater with no transformation and volatilization and denitrification may reduce its concentration by denitrifying bacteria. Only one sample (TMK-123) collected from very shallow well (depth<8 meters) shows exceptionally high nitrate concentration (19.41 mg/L). This groundwater sample is also very high in its SO4, Cl-, HCO3 and iron contents which indicates that redox processes are taking place in aquifers (Lang et al 2006; Rowland et al., 2008; Shamsudduha et al, 2008; Nath et al., 2008; Mukherjee et al., 2009). High chloride coupled with high nitrate in this well suggests anthropogenic input (Gorski, 1989) which may be due to sewage disposal into nearby depression areas. Moreover, fertilizer application and subsequent irrigation is common in study area which in turn leads to high nitrate concentrations in shallow unconfined aquifers from recharge through soil (Spalding and Exner, 1993).Highly


- 227-

varying occurrence of sulphate content (range: 29-655 mg/L; mean: 153 mg/L) suggested that bacterial respiration is patchy in the groundwater which creates small scale redox zonations in study area.

Table 4. Statistical description of physicochemical parameters of groundwater samples.

Bicarbonate varies from 120 to 880 mg/l with elevated mean (338 mg/l) value. It is known that high HCO3 level generally indicates weathering of carbonates and degradation of organic matter under local reducing conditions (Chkirbene et al., 2009).Hence, both bicarbonate and dissolved organic carbon co-exist (Mukherjee-Goswami et al., 2008). Study area is comprises of many oxbow lakes which are rich in organic matter hence it is more close to decipher organic matter as source of bicarbonate in study area.

2. Principle Component Analysis (PCA) Multivariate statistical analysis expresses the relation/association between

different chemical components in the groundwater (Mukherjee-Goswami et al., 2008). Four components of PCA analysis revealed 80.28% of the total variance on data of 66 groundwater samples of Bulri Shah Karim (Table 5). First component (F1) encompasses 47.62% of the total variance in the data set of collected groundwater samples. Strong positive loading (> ± 0.5) of cation (Na) and anions (HCO3, SO4, Cl-, F-) associated with TDS and alkalinity represent the main dissolved load of groundwater which explains intense water-sediment interaction in a longer time (Mukherjee-Goswami et al., 2008). The second component (F2) (13.27%) shows strong positive loading of hardness with Ca, Mg, Cl and Fe which suggests climate effects (Braman et al, 2013). The third (F3) component of PCA revealed 10.85% of the total variations with positive loading of Ca, NO3, K, which clearly indicates the agricultural input or nutrient effect (Khan,2011;Simeonov et al, 2003; Zhang et al, 2011). Since the study area is an agricultural terrain the use of fertilizers is quite

Min Max Mean SD Hard. 140 1480 432.87 237.78 Mg 15 124 51.42 25.45 Ca 28 472 92.33 65.59

HCO3 120 880 338.03 140.37 Cl- 37 1743 292.07 304.13 SO4 26 655 153.12 143.28 PO4 0.02 0.87 0.28 0.25 NO3 0.37 19.41 1.04 2.32 F- 0.03 3.16 0.697 0.54 Na 27 1098 212.92 208.48 K 2 216 11.36 28.12 Fe 0.01 2.78 0.20 0.40 As 0 250 33.78 58.17 pH 6.09 8.17 7.25 0.54

TDS 260 5312 1166 836.36 EC 407 8300 1822 1306.87

Alkalinity 2.4 17.6 288.46 394.13


- 228-

common, which seems to be the main source of these ions (Ca, K, NO3) in the groundwater.

Table 5. Factors loadings of different chemical parameters of groundwater from study area.

F1 F2 F3 F4

Alkalinity .816 .055 .328 -.031 Hardness .245 .803 .494 -.075

Ca .263 .600 .696 -.009 Mg .153 .904 .050 -.158

HCO3 .816 .055 .328 -.031 Cl .575 .535 .489 .056

SO4 .723 .495 .088 -.127 PO4 -.015 -.087 -.002 .914 NO3 .269 .077 .931 .007

F .843 -.227 -.145 .000 Na .890 .262 .270 .038 K .204 .162 .919 -.051 Fe .049 .558 .095 .418 pH .087 -.698 -.113 .135 EC .737 .477 .454 .007

TDS .737 .477 .454 .007 As -.041 -.040 -.059 .908

Variance% 47.62 13.27 10.85 8.54

Cumulative % 47.62 60.89 71.70 80.28 Eigen value 8.67 2.78 2.08 2.02

Strong affinity of As with PO4 clearly indicates the role of organic matter

decomposition coupled with concomitant release of arsenic (Hossain et al., 2013) into the aquifer. On the other hand FeOOH decomposition is also supplementing the groundwater by As content into the through bacteria mediated oxidation of organic carbon.

Factor 4 (8.54%) includes high loadings of PO4 (0.91) and As (0.90) followed by Fe (0.41). The association of PO4 with As void the competitive adsorption/desorption hypothesis rather favors the reductive dissolution of FeOOH theory (co-occurrence of As and Fe) for the release of arsenic in the groundwater (Mukherjee-Goswami et al., 2008).

3. Interrelationship of Major Ions Very strong correlation between Na and Cl (r2 = 0.75) is observed which suggests

that same source is responsible for elevated concentration of these ions (Fig. 7).Weak correlation of SO4 with Ca (r2 = 0.02) and its positive relationship with chloride (r2 = 0.41) as shown in Fig. 6 suggests evaporation and contamination due to agricultural


- 229-

activities and leaching from contaminated fill sites (Appelo and Postma, 2005; Nicolli et al, 2010), which are responsible for high concentration of these ions in the study area. Strong positive correlation of EC with HCO3 (r2 = 0.53) indicates mineral dissolution (Montety, et al., 2008, Beaucaire, et al., 1999) causing elevated bicarbonate in the groundwater of study area. The possible sources of HCO3 ion are carbonates and feldspar minerals which are frequently available in the sediments of study area (Khan, 2014). However, weak positive correlation of HCO3 with Ca (r2 = 0.23) and Mg (r2 = 0.06) suggests that dissolution of carbonate minerals is not the major factor controlling high bicarbonate in the groundwater of study area. Contrary to this, good positive correlation (r2 = 0.43) of hardness with HCO3 (Fig. 8) confirms that organic matter decomposition is important factor in generating high HCO3 water.

Fig. 5 Relationship between Ca and Mg in the groundwater of study area.


- 230-

Fig 6. Relationship of SO4 with Ca (a) and Cl- (b) in the groundwater of study area.

Fig. 7 Na-Cl relationship in the groundwater of study area.

Fig. 8 Hardness–HCO3 relationship in the groundwater of study area.

4. Arsenic distribution Arsenic distribution is highly uneven in the groundwater (Fig. 9) suggesting the


- 231-

prevalence of small scale redox zonations in study area. Out of total (h=66) only 29 wells are reported arsenic free. 12 wells have shown As content within the permissible guideline (10µg/L) of WHO set for drinking water. On the other hand, 56% wells suffered from arsenic contamination where it varied b/w 10-250 (Table 3). Out of these, 15 groundwater samples show As > 50µg/L which fluctuated between 60-250 µg/L. Contrary to this, arsenic concentration ranged between 20- 40 µg/L in nine wells.

Fig. 9 Arsenic distribution in the groundwater of study area.

5. Arsenic Interrelationship

Pearson correlation is a measure of linear association among different variables which is used to observe the groundwater As relationship with the other parameters in study area (Table 6). Arsenic relationship with the quantifiable and qualitative parameters has been described below.

5.1. Arsenic and major ions

Arsenic demonstrated random relationship with Cl (r = -0.011; p > 0.05), SO4 (r = -0.153; p > 0.05) and NO3 (r = -0.066; p > 0.05). Nonlinear relationship of As with these ions is consistent with the fact that these anions (Cl, SO4, NO3) appear to have minimal impacts on arsenic desorption from soil to aquifer water, yet these ions can contribute to ionic strength and salinization effects on As desorption from sediments (Smith et al, 1998; Gupta and Cher, 1978). Similarly, arsenic did not show any significant relationship with major cations (Na, K, Mg,) suggesting that evaporative concentration is not the main mechanism controlling high arsenic in the groundwater of study area which is reported from other parts of country and other regions of the world (e.g. Farooqi et al., 2007; Nickson et al., 2005; Harvey et al., 2002).


- 232-

5.2. Arsenic and redox conditions

Arsenic showed weak relationship with pH (r = 0.12) and HCO3 (r = 0.05). It is known that combined role of pH and HCO3 ion exert a significant effect on As leaching from sediments (Anawar et al., 2003). Weak relationship between As and HCO3 in the groundwater of study area is due to patchy nature of small scale redox zonation which is evident by the fact that high arsenic wells are reported in the proximity of oxbow lakes where young and reactive organic matter occurs for degradation by bacteria. Degradation of organic matter through bacterial respiration releases the sorbed load of As from FeOOH and organic matter (Anawar et al., 2009).

5.3. Arsenic and FeOOH

About one third of high arsenic (As > 10 µg/L) groundwater has objectionable iron content (0.4- 1.15 mg/L) against WHO permissible guideline of 0.3 mg/L. The reduction of As rich FeOOH due to buried peat or other organic matter leads to As release to the aquifer (Bhattacharya et al., 1997; Nickson et al., 1998; 2000; 2005).Slightly positive correlation of As with Fetotal(r = 0.12; p > 0.05) suggests that reductive dissolution of FeOOH is taking place in the groundwater of study area which is consistent with the arsenic release mechanism in the alluvial aquifers of other deltaic regions (Battacharya et al, 1997; Nickson et al, 1998; 2000; Ahmed et al, 1998; McArthur et al, 2001; 2004; Dowling et al, 2002; Harvey et al,2002; Smedley and Kinniburgh, 2002; Acheryya et al, 2002; Anawar et al, 2003; Bennett and Dudas, 2003;Islam et al, 2004; Zheng et al, 2004; Makhurjee, 2006).

However weak correlation of As with dissolved Fetotal is due to near neutral pH(mean = 7.2) in the groundwater of Bhulri Shah Karim taluka which is consistent with the fact that at pH > 8, desorption of As from metal oxides (especially Fe, Mn) leads to high As groundwater (Smedley and Kinniburgh, 2002, 2005).On the other hand, the occurrence of excessive Fetotal in 20% of the collected samples is due to reduction of iron driven by microbial action on sedimentary organic matter (Holloway et al., 2007) in study area. This young and reactive organic matter is abundantly available in the study area hosted by oxbow lakes and as burnt residue of crops which is common practice in the area (Fig. 10).


- 233-

Fig. 10(a) In situ residue of burnt crop (b) oxbow lake in Gul Muhammad Sathyo Goth (c) flood irrigation showing the sources of organic matter and anoxia in Bhulri

Shah Karim taluka.

Table 6. Arsenic interrelationship with various physicochemical parameters of groundwater.

Interrelationship Pearson CorrelationValue

P value (2tailed)

As- SO4 -0.153 0.220

As- Cl- -0.011 0.928

As-NO3 -0.066 0.600

As- Fe 0.211 0.088


- 234-

As-HCO3 -0.073 0.562

As-PO4 0.480 0.060

As-pH 0.129 0.303

As-Depth 0.053 0.670

As-F- -0.027 0.831

As-Hardness -0.0185 0.0138

5.4. Arsenic and PO4 Phosphate content occurs only in 16 groundwater samples where its concentration

varies from 0.02 to 0.87 mg/L in the groundwater of Bhulri Shah Karim taluka (Table 4). Phosphorus is highly reactive in soil hence its leaching is substantial (Magahud and Asio, 2009). In agricultural soils, the soil solution concentrations of PO4 may reach as high as 6-8 mg/L after fertilization (Pierzynski, 1994b). However, its low concentration (PO4< 1 mg/L) in the groundwater of study area suggests that P is mainly fixed in the soil and crops cultivated in the area where phosphate fertilizer (Diammonium Phosphate) is applied as soil conditioner. Phosphate is sorbed strongly onto the solid phases, including Fe and Al oxides in the soil (Zahid et al., 2007) and amount of P released into water is related to the concentration of PO4 that exceeds the capacity of Fe to create insoluble iron phosphate (Lijkalema 1980). Strong correlation of PO4 (r = 0.49; p < 0.05) with Fe(total) suggest that phosphate is linked with iron due to its release from reductive dissolution of FeOOH (Sracek, 2005) in the groundwater of study area (Fig. 11).

Fig. 11 Correlation between dissolved Fe and PO4

Soil has significant sorption capacity for P thus minimizes its leaching loss and


- 235-

availability (Davies et al., 1993). In most of the soils, PO4 does not move in the soil water but becomes insoluble and subject to less leaching losses (Davies et al., 1993) which may be the reason of low PO4 concentration in the groundwater of study area. Similarly, flood plain soil is other important factor which mainly comprises of silty-clay. This clayey soil is assumed to adsorb more PO4 than sandy soils (Sawhney, 1997). Moreover, groundwater pH of Bhulri Shah Karim taluka is slightly alkaline (mean: 7.2) which further explains why low concentration of PO4 occurs in the study area as phosphorous leaching is greatest in slightly acidic (pH: 6-6.5) conditions (Pierzynski, 1994b).

All the groundwater samples reported for PO4occurence are concomitantly observed for arsenic presence where As ranged from 5 to 250 µg/L. Similarly, PO4 showed positive correlation with As (r = 0.48; p < 0.06) in study area which suggests that arsenic is strongly linked with organic matter decomposition and agricultural fertilizer (Acharya et al., 1999, 2000; Young and Ross, 2001; BGS, DPHE, 2001; Bhattacharya et al., 2002) because land use of Bhulri Shah Karimtaluka is mainly agriculture. As discussed earlier, low PO4 content in the groundwater of study area void the role of agricultural fertilizer as main source of arsenic in the groundwater. Hence, organic matter seems to be the main source of PO4 which is also releasing arsenic under local reducing conditions. Phosphorus movement occurs in heavily manured soils where organic matter together with other organic acids, iron and aluminum may accelerate its downward movement (Miller, 1979). A decrease in PO4 adsorption capacity follows manure addition, increasing the possibility of leaching. This is due to the effect of organic matter which may enhance P mobility by coating the soil surfaces responsible for P adsorption (Magahud and Asio, 2009). Moreover, organic complexes of phosphorus have been shown to leach more rapidly and to greater depths than inorganic soluble PO4 (Lal and Stewart, 1994). The latter usually accumulates after several years of fertilizer application (Davies et al., 1993). Similarly, Toor et al., (2003) observed that substantial amount of P that is leached from grassland soil occurs as organic P.

5.5. Arsenic and oxbow lakes Meandering behavior of river Indus has established a number of oxbow lakes in

the fluvial plain of study area (Fig. 10b). These oxbow lakes revealed that most of the high arsenic groundwater is strongly associated with these freshwater bodies (Fig. 9). It suggests significant role of these geomorphic expressions to serve as accumulating sites of arsenic hosted sediments (mainly clays) deposited in these micro basins which are rich in young and reactive organic matter. It is confirmed by study carried out by Khan (2014) which revealed that soil in Bhulri Shah Karim taluka is mainly comprised of clayey sediments as flood plain deposit. These flood plain and oxbow lake sediments are enriched in natural organic matter (Donselaar et al., 2013). Sediments below the oxbow lakes have low permeability due to its clay content leading to slower drainage after the rainy season. High water content in the oxbow lakes moves toward the sandy point bars adjoining the oxbow lakes due to hydraulic gradient. These organic rich sediments of oxbow lakes create reducing conditions which also shifts laterally to the sand bars where reaction takes place with solid state Fe-As oxides, leading to the release of As and control the distribution of arsenic concentration in the groundwater.

5.6. Arsenic and sewage Twenty five groundwater wells are found to be sewage impacted as indicated by


- 236-

the occurrence of pathogenic bacteria in such wells (Table 2). Since groundwater wells are very shallow (depth< 25 meters), sewage contamination is likely to occur in study area coupled with transport of other solutes including arsenic. About one third of these sewage impacted wells are also arsenic contaminated where arsenic ranged between 20 -200 µg/L. All these sewage impacted and arsenic contaminated groundwater samples were collected from rural areas where unlined sanitation is common. Free roaming animals and open air excretion is the common source of fecal material in the study area impact on arsenic release in groundwater (Cole et al., 2004). This organic excreta is rich in PO4 and pathogenic bacteria (fecal coli forms) which reaches the groundwater through aquifer depth. The occurrence of this dissolved organic matter creates reducing conditions which ultimately mobilizes arsenic from the aquifer sediments into the groundwater. The co-occurrence of As and PO4 is also supported by this mechanism.

6. Arsenic mobilization mechanism Arsenic concentration in the groundwater of study area (part of Indus deltaic

flood plain) is found to be highly variable on both local and regional scale. It supports the dispersed source of arsenic which negates the point source of arsenic (anthropogenic) in study area. In other words, the main source of arsenic in Indus deltaic aquifers is natural where release mechanism of arsenic is strongly influenced by the local factors as indicated by various researchers (e.g. Chatterjee et al., 2003; McArthur et al., 2004; Nath et al., 2008c). Many models have been put forwarded to explain the arsenic mobilization mechanism in reducing groundwaters (e.g. Mallickand Rajagopal, 1996; Das et al., 1996; Mandal et al., 1998; Chowdhuri et al., 1999; Nickson et al., 2000; Islam et al., 2004; McArthur et al., 2001; Bhattacharya et al., 2002; Bhattacharya et al., 2003a; Sracek et al., 2005; Charlet et al., 2007; Nath et al., 2008d) but reductive dissolution of FeOOH theory proposed by Bagla and Kaisar and Bhattacharya et al., (1997) earned more fame. According of this model, arsenic adsorbed on or co-precipitated with secondary iron phases like FeOOH is released into groundwater during reducing conditions.

The present study supports this model as one third of high arsenic (As > 10 µg/L) samples showed elevated iron content (0.4- 1.15 mg/L) indicating the prevalence of reducing conditions. Moreover, occurrence of very low nitrate (< 2 mg/L) content despite agricultural terrain, further support the prevalence of anoxia in the groundwater of study area. However, abundantly available SO4 content (mean: 153 mg/L) and weak correlation of As with Fetotal(r = 0.12; p > 0.05) suggests that reduction process is still in early phases and not yet reached where bacteria respire through iron reduction intensively. This could be the reason of why more wells in the study area are still arsenic free or within the permissible limit (Table 3). The reductive dissolution model is further supported by the strong association (co-occurrence) of As with PO4 in this study which is indicated by high loading (> ± 0.5) in factor 4 (8.54%) of PCA analysis. Phosphorus (Phosphate) is an important constituent of organic matter and essential for plant growth as well as an important component in the developmental processes of agricultural crops (Withers et al., 2008).The occurrence of organic matter from oxbow lakes and burnt residue of crops is common in the study area (Fig. 10).This organic matter is relatively young and reactive due to its proximal occurrence with river Indus. Thus, bacteria mediated decomposition of this organic matter is creating reducing conditions which trigger the release of arsenic into aquifer (Husain, 2009). Anoxia is prevailing further by flood irrigation practices in the study


- 237-

area (Fig. 10c) which is triggering the arsenic release from agricultural soils and transporting up to the aquifer depth through infiltration.

Conclusion

Present study revealed that the source of arsenic in deltaic flood plain of Indus river is natural where arsenic is hosted by the fine fluvial sediments associated with young and reactive organic matter deposited in oxbow lakes and meander scars. Besides serving as source, organic matter is fueling the bacteria to create anoxia leading to the release of arsenic from its host sediments which are coated with FeOOH. Redox sensitive geochemical signatures (NO3, SO4, HCO3 and Fe) indicates that prevalence of anoxia is in early phase which may increase arsenic release and its mobilization in the future if the rate of organic matter decomposition is triggered by anthropogenic activities like sewage contamination and flood irrigation practices. The role of geomorphic process is very important in controlling fine sediments as arsenic host and the organic matter accumulation in study area. Although this study highlighted the role of organic matter in arsenic mobilization but type and quality of organic matter is not determined which must be taken into account in future investigations to elaborate more explicitly the role of organic matter as source and arsenic releasing agent. Similarly, the role of sediment mineralogy and chemistry is important to investigate in further studies to elaborate more clear the source and mechanism involved in arsenic release in Indus deltaic aquifers of Holocene age.

Acknowledgements

This study supported by the project of Higher Education Commission (HEC) on Geochemical and Geo-microbiological Investigations of Groundwater Arsenic Contamination in District Tando Muhammad Khan, Sindh: Impact of Health Human and Migration Options.

References

Acharyya, S. K. (1997). Arsenic in Ground Water: Geological Overview. Consultation on Arsenic in

Drinking Water. World Health Organization, New Delhi.

Acharyya, S. K., Lahiri, S., Raymahashay, B. C., Bhowmik, A. (2000). Arsenic toxicity of groundwater

in parts of the Bengal basin in India and Bangladesh: the role of Quaternary Stratigraphy and

Holocene sea level fluctuation. Environ. Geol., 39, 1127–37.

Acharyya, S. K., Chakraborty, P., Lahiri, S., Raymahashay, B. C, Guha, S., Bhowmik, A. (1999).

Arsenic poisoning in the Ganges delta. Nature, 545, 401.

Ahmed, S. A., Bandaranayke, D., Khan, A.W. et al. (1998).Arsenic contamination in groundwater and

Arsenicosis in Bangladesh. International journal of environmental health research, 7, 271-276.

Anawar, H.M., Akai, J., Komaki, K., Terao, H., Yoshioka, T., Ishizuka, T., Safiullah, S., Kato, K. (2003).

Geochemical occurrence of arsenic in groundwater of Bangladesh: sources and mobilization

processes. J. Geochem. Explor., 77, 109–131.


- 238-

Anawar, H.M.; Akai, J. Mostofa, K. M., Safiullah, S., Tareq, S. M. (2002). Arsenic poisoning in

groundwater: Health risk and geochemical sources in Bangladesh. Environ. Int., 27, 597-604.

Anawar, H.M.; Mihaljevič, M. by A. A. Seddique, H. Masuda, M. Mitamura, K. Shinoda, T. Yamanaka,

T. Itai, T. Maruoka, K. Uesugi, K.M. Ahmed, D.K. Biswas. (2009). Comment on Arsenic release

from biotite into a Holocene groundwater aquifer in Bangladesh. Appl. Geochem., 24, 483–485.

Appelo, C. A. J., Postma, D. (2005). Geochemistry, Groundwater and pollution, second edition, CRC

press, Balkema, Rotterdam. 668p.

Arain, M. B., Kazi, T. G., Baig, J. E., Jamali, M. K., Afridi, H. I., Shah, E. Q. (2009). Determination of

Arsenic levels in lake Water, sediment, End foodstuff from selected area of Sindh, Pakistan:

estimation of daily dietary intake. Food Chem.Toxicol., 47, 242–8.

Arain, Y., Sparks, D. L., Davis, J. A. (2004). Effects of dissolved carbonate on arsenate adsorption and

surface speciation at the hematite-water interface. Environ. Sci.Technol., 38, 817–824.

Baig, J. A., Kazi, T. G., Arain, M. B., Afridi, H. I., Kandhro, G. A., Sarfraz, R. A., Jamal, M. K., Shah, A.

Q. (2009). Evaluation of arsenic and other physico-chemical parameters of surface and ground

water of Jamshoro. Pakistan Journal of Hazardous Materials, 166,622-9.

Bennett and Dudas. (2003). Release of arsenic and molybdenum by reductive dissolution of iron oxides

in a soil with enriched levels of native arsenic. J. Environ. Eng. Sci., 2, 265–272.

BGS, DPHE. (2001). Arsenic contamination of groundwater in Bangladesh, vol. 2, Final Report, BGS

Tech. Report. WC/00/19.

Bhattacharya, P., Chatterjee, D., and Jacks, G. (1997). Occurrence of As-contaminated groundwater in

alluvial aquifers from the Delta Plains, Eastern India: Options for safe drinking water supply.

Water Resource Development, 13, 79–92.

Bhattacharya, P., Mukherjee, A. B. (2002). In Chatterje, M., Arlosoroff, S., Guha, S. G. (Eds.),

Management of Arsenic Contaminated Groundwater in the Bengal Delta Plain. Conflict

Management of Water Resources. Asgate Publishers, UK, 308-348.

Bhattacharya, P., Tandukar, N., Neku, A., Valero, A. A,. Mukherjee, A. B. Gunnar, J. (2003). Geogenic

arsenic in groundwater from Terai Alluvial Plain of Nepal. J. Phys., 107, 173–176.

Beaucaire, C., Gassamaa, N., Tresonne, N., Louvat, D. (1999). Saline groundwaters in the Hercynian Granites (Chardon Mine, France): Geochemical Evidence for the Salinity Origin. Applied Geochemistry, 14, 67-84.

Chatterjee, N., Chen, Y. and Breslow, N. (2003).A pseudoscore estimator for regression problems with

two-phase sampling. Journal of the American Statistical Association, 98, 158–168.

Chauhan, O. S., Almeida, F. (1993). Influences of Holocene sea level, regional tectonics, and fluvial,

gravity and slope currents induced sedimentation on the regional geomorphology of the

continental slope off northwestern India. Mar. Geol., 112, 313-328.

Chkirbene, A., Tsujimura, M., Charef, A., Tadashi, T. (2009). Desalination Hydro-geochemical

evolution of groundwater in an alluvial aquifer: Case of Kurokawa aquifer, Tochigi prefecture.

Media water International Conference on Sustainable Water Management, Tunis, Japan. 246,

485-495.

Chowdhury, T. R., Basu, G. K., Mandal, B. K., Biswas, B. K., Samanta, G., Chowdhury, U. K. Chanda,


- 239-

C. R., Lodh, D., Roy, S. L., Saha, K. C., Roy, S., Kabir, S., Quamruzzaman, Q., Chakraborti, D.

(1999). Arsenic poisoning in the Ganges delta. Nature, 401, 545-546.

Cole, A. A., Smecker-Hane, T. A., Tolstoy, E., Bosler, T. L., Gallagher, J. S. (2004). The effects of age

on red giant metallicities derived from the near-infrared CaII triplet. Monthly Notices of the Royal

Astronomical Society, 347, 367-379.

Das, D., G. Samanata, B. K. Mandal, T. R. Chowdhury, C. R. Chanda, P. P. Chowdhury, G. K. Basu, and

D. Chakraborti. (1996). Arsenic in groundwater in six districts of West Bengal, India. Environ.

Geochem. Health, 18, 5–15

Davies AM, et al. (1993) Redesign of the interior hydrophilic region of mitochondrial cytochrome c by

site-directed mutagenesis. Biochemistry, 32, 5431-5.

Donselaar, M. Bhatt, A., Bose, N., Bruining, J., Ghosh, A. (2013). Point bars as stratigraphic traps for

arsenic contamination in groundwater-case study of the ganges river, bihar, india. In 75th EAGE

Conference & Exhibition incorporating SPE EUROPEC, 2013.

Dowling, C. B., Poreda, R. J., Basu, A. R., Peters, S. L., Aggarwal, P. K. (2002). Geochemical study of

arsenic release mechanisms in the Bengal basin groundwater. Water Res., 38,173–1190.

Farooqi, A., Masuda, H., Firdous, N. (2007). Toxic fluoride and arsenic contaminated water in Lahore

and Kasur district, Punjab, Pakistan and possible contaminant sources. Environ. Pollut., 145,

839–849.

Farooqi, A., Masuda, H., Siddiqui. R. (2009). Sources of Arsenic and Fluoride in highly contaminated

Soil causing groundwater contamination in Punjab, Pakistan Arch. Environ. contam.Toxicol., 56,

693-706.

Fatmi, Z., Azam, I., Ahmed, F. Kazi, A., Gill, A.B, Kadir, M. M, Ahmed, M., Ara, N., Janjua, N. Z.

(2009). Health burden of skin lesions at low arsenic exposure through groundwater in Pakistan. Is

river the source?. Environ. Res., 109, 575–581.

Gorski, J. (1989). Główneproblemychemizmuwódpodziemnychutworówkenozoikuśrodkowej

Wielkopolski (The main hydrochemical problems of cainozoic aquifers located in Central

Wielkopolska. ZeszytyNauk AGH: 45Kraków.

Gupta, S. K., Chen, K. Y. (1978). Arsenic removal by Adsorption. J. Water Pollution Control Fed.,

50,493–506.

Haq, B. U. (1999). Past, present and future of the Indus delta. In: Meadows, A., Meadows, P.S. (Eds.),

The Indus River, Biodiversity, Resources, Humankind. Linnaean Society of London, Oxford

University Press, Oxford, UK, 231–248.

Haq, I., Baig, M. A. Deedar, N., D., Hayat, W. (2007).Groundwater arsenic contamination – a multi

directional emerging threat to water scarce areas of Pakistan. 6th International IAHS Groundwater

Quality Conference, held in Fremantle, Western Australia.

Harvey, C. F., Swartz, C. H., Badruzzaman, A. B. M., Keon-Blute, N., Yu, W., Ali, M. A., Jay, J., Beckie,

R., Niedan, V., Brabander, D., Oates, P. M., Ashfaque, K. N., Islam, S., Hemond, H. F., Ahmed, M.

F. (2002). Arsenic mobility and groundwater extraction in Bangladesh. Science, 22, 1602–1606.

Harvey, C. F., Swartz, C. H., Badruzzaman, A. B. M., Keon-Blute, N., Yu, W., Ali, M. A., Jay, J., Beckie,

R., Niedan, V., Brabander, D., Oates, P.M., Ashfaque, K.N., Islam, S., Hemond, H.F., Ahmed, M.F.


- 240-

(2002). Arsenic mobility and groundwater extraction in Bangladesh.Science. 22:1602–1606.

Holloway, G., Dupont, F., Golubeva, E., Ha¨kkinen, S., Hunke, E., Jin, M., Karcher, M., Kauker, F.,

Maltrud, M., Maqueda, M. A., Maslowski, W., Platov, G., Stark, D., Steele, M., Suzuki, T., Wang,

J., Zhang, J. (2007). Water properties and circulation in Arctic Ocean models.journal of

geophysical research, vol. 112, C04S03, doi: 10.1029/2006JC003642.

Holmes, D.A. (1968). The recent history of the Indus. Geographical Journal. 134 (3), 367– 382.

Hossain, M. A., Tareq, S. M., Ahmed, G. (2013). Is organic matter a source or redox driver or both for

arsenic release in groundwater?. Contamination in water; 58-60, 49–56

Husain, V. (Report) Sindh Education Reform Program (SERP). (2009). Drinking Water Quality

component.A study for World Bank. 58p.

IARC. Some drinking-water disinfectants and contaminants, including arsenic. IARC

MonogrEvalCarcinog Risks Hum. 2004;84:1–477.

Ishiga, H., Dozen, K., Yamazaki, C., Ahmed, F., Islam, M. B., Rahman, M. H., Sattar, M. A., Yamamoto,

H., Itoh, K. (2000). Geological constraints on arsenic contamination of groundwater in Bangladesh.

International Forum on Arsenic Contamination of Groundwater in Asia, Yokohama, Japan, pp.

53–62.

Islam, F. S., Gault, A. G., Boothman, C., Polya, D. A., Charnock, J. M., Chatterjee, D., Lloyd, J. R.

(2004). Role of metal reducing bacteria in arsenic release in Bengal Delta sediments. Nature 430,

68–71.

Kazi, T. G., Arain, M. B., Baig, J. A., Jamali, M. K., Afridi, H. I., Jalbani, N., Sarfraz, R. A., Niaz, A.

(2009). The correlation of arsenic levels in drinking water with the biological samples of skin

disorders Sci. Total Environ., 407: 1019–1026

Kazmi, A. H., Jan, M. Q. (1997). Geology and Tectonics of Pakistan.Graphic publishers, Karachi, 554p.

Khan, A. (2014). Groundwater Studies for Arsenic Pollution in Indus Deltaic Aquifers of District Tando

Mohammad Khan, Sindh, Pakistan: Health-Environment Hazards and Mitigation Options. Ph.D.

thesis (unpub.).

Khan, H, Z., Iqbal, S., Iqbal A., Akbar, N., Jones, D. L. (2011). Response of maize (Zea mays L.)

varieties to different levels of nitrogen.crop& environment, 2(2): 15-19.

Kureshy, K. U. (1977). A Geography of Pakistan, 4th edition.

Lijklema, L. Interaction of orthophosphate with iron (III) and aluminum hydroxides. Environ. Sci.

Technol., 14, 537–540.

Lal, R., Stewart, B. A. (1994) .Soil processes and water quality In: R. Lal And B. A. Stewart

(Eds.) Soil processes and water quality. CRC Press, Boca Raton, FL., p.1-6.

Leng, Y. C., Liu, C. Q., Zhao, Z. Q., Li, S. L., Han, G. L. (2006). Geochemistry of surface and ground

water in Guiyang, China: Water/rock interaction End pollution in a karst hydrological system.

Applied Geochemistry, 21, 887-903.

Magahud, J. C., Asio, V. B. (2009). Nitrate and phosphate leaching from Lake DanaoAndisol treated

with manure and chemical fertilizer. Paper presented during the National Scientific Conference of

the Philippine Society of Soil Science and Technology (PSSST), 20-23 May 2009, Davao

City, Philippines.


- 241-

Majidano, S. A., Arain, G. M., Bajaj, D. R., Iqbal P., Khuhawar, M. Y. (2010). Assessment of

Groundwater Quality with Focus on Arsenic Contents and Consequences. Case Study of

TandoAllahyar District in Sindh Province.

Mallick S. and Rajagopal N. R. (1996). Groundwater development in the arsenic-affected alluvial belt

of West Bengal – Some Questions. Current Science, 70, 956-958.

Massacheleyn, P. H., DeLaune, R. D., Patrick, W. H. (1991). Effects of redox potential and pH on

arsenic speciation and solubility in a contaminated soil. Environ. Sci. Technol., 25, 1414– 9.

Mast, M. A., Drever, J. I. (1987). The effect of oxalate on the dissolution rates of oligoclase and

tremolite. Geochim. Cosmochim. Acta., 51, 2559-2568.

McArthur, J. M., Banerjee, D. M., Hudson-Edwards, K. A., Mishra, R ., Purohit, R., Ravenscroft, P.,

Cronin, A ., Howarth, R. J., Chatterjee, A ., Talukder, T ., Lowry, D., Houghton, S., Chadha, D.

K. (2004). Natural organic matter in sedimentary basins and its relation to arsenic in anoxic

ground water: the example of West Bengal and its worldwide implications. Applied

Geochemistry, 19, 1255–1293.

McArthur, J. M., Ravenscroft, P., Safiulla, S., Thirlwall, M. F. (2001). Arsenic in groundwater testing

pollution mechanisms for sedimentary aquifers in Bangladesh. Water. Res., 37,109–117.

Memon, A. A. (2005). Devastation of Indus Delta. Proceedings, World Water & Environmental

Resources Congress. American Society of Civil Engineers.

Mendel, B. K., Chowdhury, T. R., Semente, G., Mukherjee, D. P., Chende, C. R., Saha, K. C.,

Chakraborti, D. (1998). Impact of safe water for drinking on five families for 2 years in West

Bengal, India. Sci. Total Environ, 218, 185–201.

Miller, M. H. (1979). Contribution of nitrogen and phosphorus to subsurface drainage water from

intensively cropped mineral and organic soils in Ontario. J. Environ. Qual., 8, 42-48.

Montety, V. D., Radakovitch, O., Vallet-Coulomb, C., Blavoux, B., Hermitte, D., Valles, V. (2008).

Origin of groundwater salinity and hydrogeo chemical processes in a confined coastal aquifer:

Case of the Rhone delta (Southern France). Applied Geochemistry, 23, 2337-2348.

Mukherjee, A., Fryar, A. E., Thomas, W. A. (2009). Geologic, geomorphic, and hydrologic framework

and evolution of the Bengal basin, India and Bangladesh. J. Asian Earth Sci, 34, 227–244.

Mukherjee-Goswami, A., BibhashNath, B., Jana, J., SudipJyotiSahu, S. J., Sarkar, M. J., Jacks, G.,

Bhattacharya, P., Mukherjee, A., Polya, D. A., Jean, J. S., Debashis Chatterjee, D. (2008).

Hydrogeochemical behavior of arsenic-enriched groundwater in the deltaic environment:

Comparison between two study sites in West Bengal, India. Journal of Contaminant Hydrology,

99, 22–30.

Naseem S. (2012). Groundwater quality assessment for determining geogenic pollution, contamination

and health effects in Thatta-Hyderabad Region, Sindh.Ph.D. Thesis (unpub.)

Nath B, Stüeben D, BasuMallik S, Chatterjee D, Charlet L. Mobility of arsenic in West Bengal aquifers

conducting low and high groundwater arsenic. Part I: comparative hydrochemical and

hydrogeological characteristics. Appl. Geochem., 2008c; 23, 977–95.

Nath, B., Sahu, S. J., Jana, J., Mukherjee-Goswami, A., Roy, S., Sarkar, M. J., Chatterjee, D. (2008a).

Hydrochemistry of arsenic-enriched aquifer from rural West Bengal, India: a study of the arsenic


- 242-

exposure and mitigation option. Water, Air and Soil Pollution. 190:95–113.

Nickson R. T., McArthur J. M., Shrestha B. R., Kyaw-Myint T. O., Lowry D .(2005). Arsenic and other

drinking water quality issues, Muzaffargarh District, Pakistan, Applied Geochemistry, 20, 55-68.

Nickson, R., Mc Arthur, J., Burgess, W., Ahmed, K. M., Ravenscroft P., Rahman, M. (1998).Arsenic

poisoning of Bangladesh groundwater.Nature, 35, 395.

Nickson, R., Mc Arthur, J. M., Ravenscoft, P., Burgess, W. G., Ahmed, K. M. (2000). Appl. Geochem.,

15, 403–413

Nickson, R. T., McArthur, J. M., Ravenscroft, P., Burgess, W. B., Ahmed, K. M. (2000). Mechanism of

As poisoning of groundwater in Bangladesh and West Bengal. Applied Geochemistry, 15,

403–413.

Nickson, R. T., McArthur, J. M., Shresha, B., Kyaw-Myint, T. O. and Lowry, D. (2004). Arsenic and

other drinking water quality issues, Muzaffaragh District, Pakistan. Applied geochemistry, 20,

55-68.

Nicolli, H. B, Bundschuh, J., García, J. W., Falcón, C. M., Jeans, J. H. (2010). Sources and controls for

the mobility of arsenic in oxidizing groundwaters from loess-type sediments in arid/semi-arid dry

climates – Evidence from the Chaco–Pampean plain (Argentina). Water Research, Volume 44,

Issue 19, November, 5589–5604

NRC (National Research Council) (1999). Arsenic in drinking water. Washington, DC: National

Academy Press.

Pierzynski, G. M. (1994b). Soil Phosphorus and Environmental Quality. In: Soils and

Environmental Quality. p 103-141. CRC Press, Boca Raton, Florida.

Polizzotto, M. L., Hervey, C. F., Li, G., Badruzzman, B., Ali, A., Newville, M., Sutton, S., Fendorf, S.

(2006). Solid-phases and desorption processes of arsenic within Bangladesh sediments. Chem.

Geol., 228, 97-111.

Polizzotto, M. L., Kocar, B. D., Benner, S. G., Sampson, M., Fendorf, S. (2008).Near surface wetland

sediments as a source of arsenic release to ground water in Asia. Nature, 454, 505–508.

Qureshi, A. S., Ornick, P. G, Qadir, M., Aslam, Z. (2008) .Managing Salinity and Water logging in the

Indus Basin of Pakistan. Agriculture Water management, 95, 1-10.

Ramadan MAE, Al-Ashkar EA. The effect of different fertilizers on the heavy metals in soil and tomato

plant. Australian Journal of Basic and Applied., 2007; 1:300–306.

Rao, N. S. (2008). Factors controlling the salinity in groundwater in Parts of Guntur district, Andhra

Pradesh, India. Environ. Monit. Assess., 138, 327-341.

Rowland, H. A. L., Gault, A. G., Lythgoe, P., Polya, D. A. (2008). Geochemistry of aquifer sediments

and arsenic-rich groundwaters from Kandal Province, Cambodia. Applied Geochemistry, 23,

3029-3046.

Sawhney, B. L., Starr, J. L.: 1977, J. Water Poll. Control Fed., 49, 2238.

Saether, O. M., Andreassen, B.Th., Semb, A. (2001). Amounts and sources of fluoride in precipitation

over southern Norway. Atmos. Environ, 29,1785–1793.

Shahid, S. A., Jenkins D. A. (1994). Mineralogy and micro morphology salt crusts from the Punjab,

Pakistan. Dev Soil Science, 22, 799-810.


- 243-

Shamsudduha, M., Uddin, A., Saunders, J. A., Lee, M. K. (2008). Quaternary Stratigraphy, sediment

characteristics and geochemistry of arsenic-contaminated alluvial aquifers in the

Ganges–Brahmaputra floodplain in central Bangladesh. Journal of Contaminant Hydrology, 99,

112–136.

Sharma, R., Rensing, C., Rosen, B. P., Mitra, B. (2000). The ATP hydrolytic activity of purified Znta, a

Pb(II)/Cd(II)/Zn(II)-translocating ATPase from Escherichia coli. J. Biol. Chem., 275, 3873–3878

Simeonov V, Stratis J. A, Samara C et al. (2003). Assessment of the surface water quality in Northern

Greece J. Water Res., 37, 4119–4124.

Smedley, P., Kinniburgh, D. G. (2005) Arsenic in Groundwater and the Environment. In: Selinus, O.,

Ed., Essentials of Medical Geology, Elsevier, Amsterdam, 263-299.

Smedley, P. L., Kinniburgh, D. G. (2002). A review of the source, behavior and distribution of arsenic in

natural waters. Applied Geochemistry, 17, 517–568.

Smith, A. H.; Goycolea, M.; Haque, R.; Biggs, M. L. (1998). Marked increase in bladder and lung

cancer mortality in a region of Northern Chile due to arsenic in drinking water. Am. J. Epidemiol.,

147, 660–669.

Spalding, R. F., and Exner, M. E. (1993), Occurrence of nitrate in groundwater—a review: Journal of

Environmental Quality, v. 22, p. 392–402.

Sracek, O., Bhattacharya, P., von Brömssen, M., Jacks, G., Ahmed, K. M. (2005). In: Bundschuh, J.,

Bhattacharya, P., Chandrashekharam, D. (Eds.), Natural enrichment of Arsenic in groundwaters of

Brahmanbaria district, Bangladesh: geochemistry, speciation modeling and multivariate statistics.

Toor, G. S.; Condron, L. M.; Di, H. J.; Cameron, K. C., Cade-Menun, B. J. (2003) Characterization of

organic phosphorus in leachate from a grassland soil. Soil Biol. Biochem., 35,1317-1323.

Valenza, A., J. C. Grillot, and J. Dazy. (2000). Influence of groundwater on the degradation of irrigated

soils in a semi-arid region, the inner delta of the Niger River, Mali, Hydrogeol. J., 8, 417 – 429,.

Wilhelmy, H. (1967). The shifting river; studies in the history of the Indus valley.Universitas 10, 53-68.

Withers, P. J. A., Jarvie, H. P. (2008). Delivery and cycling of phosphorus in rivers, A review. Sci. Total

Environ. 400, 379-395.

Young, E., Rose, D. (2001). Phosphate release from seasonally flooded soils, a laboratory microcosm

study. J. Envir. Quality.,Vol. 30- 90-91.

Zahid, A., Hassan, M. Q., Balke, K. D., Flegr, M., Clark, D. W. (2007).Groundwater chemistry and

occurrence of arsenic in the Meghan floodplain aquifer, southeastern Bangladesh, Environ. Geol.,

doi: 10.1007/s00254-007-0907-3.

Zhang, F. S., Z. L. Cui, M. S. Fan, W. Zhang, X. Chen, and R. Jiang. (2011). Integrated soil-crop system

management: Reducing environmental risk while increasing crop productivity and improving

nutrient use efficiency in China. J. Environ. Qual., 40, 1051–1057. doi:10.2134/jeq2010.0292.

Zhang, Y., Stute, M., van Geen, A., Gavrieli, I., Dhar, R., Simpson, H. J., Schlosser, P., Ahmed, K. M.

(2004). Redox control of arsenic mobilization in Bangladesh groundwater. Appl. Geochem, 19,

201-214.

Zhuo, A., He, L., Zhao, H. (2009b).Effect of organic acids on inorganic phosphorus transformation in

soil with different phosphorus sources. China J. Appl. Environ. Biol, 15, 474-478.


- 244-

