Groundwater Flow and Contaminant Transport Modeling of Allen Forrest Zoo, Kanpur

7/24/2019 Groundwater Flow and Contaminant Transport Modeling of Allen Forrest Zoo, Kanpur

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Proceedings of International Conference of Benchmarks in Engineering Science and Technology (IC-BEST) 7-8 September 2012.

Groundwater Flow and Transport Modeling of Allen Forrest, Kanpur

Abhinav Srivastava, Dr. Deepesh Singh

B.Tech. Student, Assistant ProfessorDept. of Civil Engineering, H.B. Technological Institute, Kanpur (India)

[email protected], [email protected]

Abstract-This paper aims at studying the problem of

groundwater contamination of Allen Forest area,

Kanpur (U. P.) and suggests suitable observation well

management strategies for the area. In this respect,

groundwater flow and contaminant transport process

was simulated over the study area using a computer

based model, MOC v3.1. The study area was suitably

discretized into a block centered finite difference grid

which was limited to 1089m 961m. The simulationmodel utilizes the hydrogeological input data and

provides head and contaminant concentration values

for future time periods. It was observed that in 5

years simulation period around 42 percent of the total

study area is covered by the plume which crosses the

threshold limit of 300 mg/l. This work also utilizes the

breakthrough curves to explore suitable management

strategies for installation of observation wells in

different time periods depending upon the economic

constraints.

1. Introduction

Groundwater is a term used for the subsurface

water that occurs beneath the water table in soils andgeological formations that are fully saturated.

Groundwater is the most abundant source of fresh

water for mankind, with only 2.5% of water on earthbeing fresh, the total groundwater reserves account for

30% of this share [4]. As a result of our consumptive

way of life, the groundwater environment is being

assaulted with an ever increasing number of soluble

chemicals. From water quality viewpoint, degradation

of groundwater often requires long periods of timebefore the true extent of the problem is readily

detectable. It has thus become recognized as animportant environmental problem. With the increasingsense of awareness about the environment and the

recognition of the need for its protection, the study of

solute transport related to groundwater contaminationhas become the focus of numerous researchers.

Groundwater modelling is an effective way to

predict the flow of groundwater within an aquifer.

Groundwater modelling aims at studying the temporaland spatial distribution of such contaminants in the

aquifer and helps to formulate sustainable groundwater

management strategies. During the last three decades,

research activities in this area have accelerated to a

revolutionary level. Different investigators havestudied the solute transport from different perspectives.

Groundwater models can be divided into groundwater

flow models and solute transport models. Groundwaterflow models solve for the distribution of heads,

whereas solute transport models solve for

concentration of solute as affected by advection,dispersion and chemical reactions. Groundwater

models can be both analytical and numerical. While the

analytical models are wholly based on subjective

human judgments, numerical models simulate

groundwater flow indirectly by means of a governing

equation thought to represent the physical processesthat occur in the system, together with equations that

describe heads or flows along the boundaries of the

model [1].

After the contaminants and their behaviour havebeen detected, the well locations are monitored based

on which sustainable groundwater managementstrategies are devised. Along with these, efforts may

also be made for remediation of the problem by

implementing the three Es viz.engineering, education

and enforcement.

1.1. Objectives

This paper aims to address the spatial and temporal

distribution of water table and contaminant

concentrations in a confined aquifer with the following

objectives:i. Identification of various groundwater extraction,

recharge and contaminant sources in the area of

Allen Forest Zoo.ii. Implementation of a coding based numerical model

for groundwater flow and contaminant transport for

the area.


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iii. Prediction of the head distribution, fate of the

contaminants in different time periods.

iv. Developing sustainable strategies for groundwater

observation well installation in the study area.

2. Theoretical background

2.1. Groundwater flow equation

The equation describing the transient two-

dimensional areal flow of a homogeneous

compressible fluid through a non-homogeneous

anisotropic aquifer in Cartesian tensor notation can be

written as [8]:

, 1,2 1

Where:

Tij =transmissivity tensor, [L2/T];

=

Kij

b;

Kij = hydraulic conductivity tensor, [LT-1

];b = saturated thickness of aquifer, [L];

h = hydraulic head, [L] ;

S = storage coefficient, (dimensionless);

t = time, [T];

W = volume flux per unit area (positive sign foroutflow and negative for inflow), [L/T];

and

xiandxjare the Cartesian coordinates, [L].

2.2. Contaminant transport equation

The equation used to describe the two dimensional

areal transport and dispersion of a given non-reactivedissolved chemical species in flowing ground water is

as follows [2] and [3]:

2

Where:

C = concentration of the dissolved chemical

species, [M/L3];

Dij = coefficient of hydrodynamic dispersion (a

second-order tensor), [L2/T];

b = saturated thickness of the aquifer, [L]; and

C = concentration of the dissolved chemical in a

source or, sink fluid, [M/L3].

2.3. Method of characteristics

The method of characteristics is used in this model

to solve the contaminant transport equation. This

method was developed to solve hyperbolic differentialequations. The approach taken by the method of

characteristics is not to solve equation 2 directly, but

rather to solve an equivalent system of ordinary

differential equations. Considering saturated thickness

as a variable and by expanding the convective transport

term, equation 2 can be written as [7]:

1

3

2.4. Assumptions considered in model

Following assumptions are considered in the model:

i. Darcys law is valid and hydraulic-head gradients

are the only significant driving mechanism for fluidflow.

ii. The porosity and hydraulic conductivity of the

aquifer are constant with time, and porosity is

uniform in space.iii.

Gradients of fluid density, viscosity and

temperature do not affect the velocity distribution.

iv.No chemical reactions occur that affect theconcentration of the solute, the fluid properties, or

the aquifer properties.

v. Ionic and molecular diffusion are negligible

contributors to the total dispersive flux.vi.Vertical variations in head and concentration are

negligible.

vii.The aquifer is homogeneous and isotropic with

respect to the coefficients of longitudinal and

transverse dispersivity.viii.The gradients of fluid density, viscosity and

temperature do not affect the velocity distribution.

2.5. Methodology

The study area is discretized into a block-centred

finite difference grid having rows and columns. A

pumping well is represented as withdrawal (discharge)

well and is specified as one pumping well per node.The model assumes that stresses developed in the

aquifer are constant with time during each pumping

period. But the total number of wells, as well as theirlocations, flux rates, and source concentrations, may be

changed for successive pumping periods. The model

specifies observation wells on potential locations.Other parameters like contaminant source, constant

head boundaries, no-flow boundaries, transmissivitycan be given as input in model as node identification

array [9].

An output file was obtained detailing the inputvalues, head values and concentration values. This


3/8

Proceed

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4/8

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September 2012.

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5/8


Table 3. Hydro-geological inputs for the model

Parameter Value

Aquifer Thickness 20 feet

Potentiometric heads inthe water table

130 feet in the north and

north-east boundary and100 feet on the south and

south-west boundary

Transmissivity 0.12 ft2/sec

LongitudinalDispersivity

100 feet

Transverse Dispersivity 30 feet

Effective Porosity 0.30

Storage Co-efficient0, due to steady state

conditions

Number of Observation

Wells10

Number of Pumping

Wells2

Discharge of each

pumping well20.96 ft3/sec

4. Results and analysis

4.1. Spatial distribution of contaminant

concentration

The concentration values at all the nodes wereinterpolated in the entire study area by method of

Kriging utilized by Surfer10. Kriging is a statisticalinterpolation method that chooses the best linear

unbiased estimate and unlike other interpolationmethods, it preserves the field value at measurement

points [1]. The contours join all points of same

concentration. The successive contour maps help to get

an idea about the areal extent of contamination in

ground water. The various contour maps obtained werethen carefully superimposed over the study area.

The values on contour lines represent concentrationvalues in mg/l. The threshold limit of groundwater

contamination is assumed to be 300 mg/l. It was

observed that a total of 167 cells, around 42 percent of

the total study area cross the threshold limit at the endof simulation period of 5 years.

The number of cells crossing the threshold limit

after every time interval of 2 months up to 2.5 years

and 6 months from then onwards has been shown in

Table 4.

Table 4. Number of cells above the threshold limitwith time

Time (Months)Number of cells above

threshold limit

2 1074 136

6 1508 156

10 157

12 160

14 157

16 161

18 16220 161

22 160

24 16126 162

28 163

30 164

36 16242 165

48 164

54 165

60 167

The results indicate that as the total time of

simulation increases, the concentration of the

contaminant gradually spreads throughout thefinite difference grid. The study area consists of

400 finite difference cells out of which 167 cells

were observed to be above the threshold limit of300 mg/l. Fig. 4 shows a curve depicting the

number of cells crossing the threshold limit of300 mg/l with time.

Figure 4. Curve showing the number of cellscrossing the threshold limit with time

The spatial distribution of threshold limit ofcontaminant concentration at the end of simulation

period of 5 years has been shown in Fig. 5.

0

25

50

75

100

125

150

175

200

225

250

2 6 10 14 18 22 26 30 42 54Numberofcellsabovethreshold

limit

Time (Months)


6/8

Proceed

Figure 5.the

4.2. Hea

The di

model. Sistate the h

simulation

at the end

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September 2012.

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7/8


4.3. Temporal distribution of contaminant

concentration

For observing the temporal distribution ofconcentration, breakthrough curves were plotted at all

the ten identified potential locations for observation

well installations. A breakthrough curve can be definedas a graph between concentration and time at a

particular point at sampling location.

4.4. Observation well management strategies

An observation well is used to obtain representative

groundwater quality samples and hydrogeologicinformation. Observation wells are simple and

inexpensive monitoring tools that help in monitoring

groundwater trends. A properly designed, installed, and

developed groundwater observation well, provides thefollowing:

1. Representative samples of groundwater that can be

analyzed to determine physical properties andwater-quality parameters of the sample

2. Conducting aquifer tests used for the purpose of

determining the hydraulic properties of the

geologic materials.

4.4.1. Installation strategy of observation wells

For an entire study of the area it is needed to installobservation wells at different locations. As the

installation of observation wells involves a huge capital

investment it is many times not economical tocompletely utilise the observation wells. In this section

a methodology has been adopted to install the wellsstep by step with time. The methodology utilizes the

breakthrough curves. When the concentration value

crosses the threshold limit at a particular time, anobservation well is needed to be installed before that

time. It is assumed that a well can be installed one

month before that particular time.

With the help of breakthrough curves obtained, thewells which cross the threshold limit of 300 mg/l can

be predicted along with the time they would take tocross that limit. Due to economic constraints all the

wells cannot be installed at the same time. So, at a

time, observation wells need to be installed at those

locations only which cross the limit.With the help of breakthrough curves it can be seen

that observation well locations 1, 2 and 3 remain abovethe threshold limit throughout the simulation period so

an observation well should be installed at those

locations from the beginning of the simulation period.Well locations 4 and 5 cross the threshold limit

after 3 months of the simulation period so observation

wells should be installed at those locations during the

2ndmonth.

Well location 6 crosses the threshold limit after 4

months of the simulation period so observation wells

should be installed at this location during the 3rdmonth.

Well location 7 crosses the threshold limit after 45

months of the simulation period so observation wellsshould be installed at this location during the 44th

month.

Well locations 8, 9 and 10 never cross the threshold

limit during the simulation period so observation wellsneed not be installed at these locations.

4.5. Remedial measures

The other method for ensuring the wholesomenessof groundwater is the treatment of the influent water

which carries the contaminant being drained into the

lake. When situations arise like all the observation well

locations become unsafe, this method can be resortedto, though at a higher cost. A small treatment facilitycan be established anywhere in the course of the drain

or preferably, near its entrance in the lake. Although,

this method is expensive but it would benefit in thelong run because treating the contaminant at its very

source will reduce the concentration of contaminant

falling in the lake which, in turn, would gradually

render the groundwater safe.Finally, after the engineering aspect has been

covered, the next step should be to educate the

residents of the area about the problem so that they

remain cautious and use secondary methods to purify

the water before consuming it. As a long term planninga combined system with effluent treatment, regional

ordinances and observation wells may be adopted to

mitigate the groundwater contamination problem.

5. Conclusions

Two dimensional modelling was done forgroundwater flow and contaminant transport in the

study area, Allen Forest Zoo. The study area,

encompassing 48 acres was defined and a finitedifference grid was designed on it. The model predicts

the spread of plume after every specified time interval

starting from 2 months to 60 months (5 years) and alsothe head distribution at the end of the time step. The

simulation results indicate that as the total time fromthe beginning to the end of simulation increases, the

concentration of the contaminant gradually spreads

with the groundwater movement. At the end of thesimulation period, it was observed that around 42

percent of the total study area had crossed the threshold


8/8


limit of 300 mg/l. Ten potential observation well

locations were identified over the study area. At these

locations the model predicts the values of

concentration achieved throughout the simulation

period. This data was used for preparing breakthroughcurves which in turn helped to analyse the suitability of

installing an observation well at a particular location.

Considering the economic constraints, thepredictions of the simulation helped a lot to decide the

best management strategy for observation well

installation. It was suggested to install an observation

well, at a time, only at those locations where theconcentration of contaminant crosses the threshold

limit. It was also suggested that after all the well

locations cross the threshold limit, a small treatment

facility should be established at contaminant source.This would gradually improve the groundwater quality.

The aspects of education and enforcement were also

discussed very briefly for groundwater qualityimprovement which would spread awareness and

gradually reduce the outflow of contaminants in thewaste water.

REFERENCES

[1] Anderson M. P. and Woessner W. W. (1992) Applied

groundwater modeling: simulation of flow and advective transport.

Academic Press,San Diego, California.

[2] Bear, Jacob (1972). Dynamics of fluids in porous media,American Elsevier Publishing Co., New York, 764.

[3] Bredehoeft, J. D. and Pinder, G. F. (1973) Mass transport in

flowing groundwater Water Resources Research,9(1), 194-210.

[4] Chow, Ven Te; Maidment, David R. and Mays, Larry W. (1988).Applied Hydrology.New Delhi, Tata McGraw Hill, 4.

[5] Freeze,R.A.and Cherry, J. A. (1979). Groundwater. Englewood

Cliff, N. J. Prentice-Hall.[6] Golden Software Inc. (2011), SURFER version 10.0.

[7] Konikow, L. F. and Grove, D. B. (1977) Derivation of equations

describing solute transport in ground water U.S. Geological SurveyWater-Resources Investigatons 77-19, 30.

[8] Pinder,G.F. and Bredehoeft,J.D. (1968) Application of the

digital computer for aquifer evaluation Water Resources Research,

4(6), 1069-1093.[9] Singh, D. and Datta B. (2012). Linked Optimization Model for

Groundwater Monitoring Network Design, in proceedings of

International conference "ENSURE 2012: Environmentally

Sustainable Urban Ecosystems" IIT Guwahati, Assam, India

February 24-26, 2012 (in CD)

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Groundwater Flow and Contaminant Transport Modeling of Allen Forrest Zoo, Kanpur

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