UNIVERSITI PUTRA MALAYSIA

EFFECTS OF WATER TABLE MANAGEMENT PRACTICES ON THE TRANSPORT OF NITRATES IN SANDY UNDERGROUND

ENVIRONMENT

ABDUL HAKIM MASAUD MUSSA ALMDNY

FK 2003 52

EFFECTS OF WATER TABLE MANAGEMENT PRACTICES ON THE TRANSPORT OF NIlRATES IN SANDY UNDERGROUND

ENVIRONMENT

By

ABDUL HAKIM MASAUD MUSSA ALMDNY

Thesis Submitted to the School of Graduate Studies, Universiti Putra Malaysia, in Fulfilment of the Requirements for the

Degree of Doctor of Philosophy

July 2003

Dedicated to

My Parents, Wife, Daughter, and Son

11

Abstract of dissertation presented to the Senate ofUniversiti Putra Malaysia in fulfilment of the requirements for the degree of Doctor of Philosophy

EFFECTS OF WATER TABLE MANAGEMENT PRACTICES ON THE TRANSPORT OF NITRATES IN SANDY UNDERGROUND

ENVIRONMENT

By

ABDUL HAKIM MASAUD MUSSA ALMDNY

July 2003

Chairman: Professor Salim Said, Ph.D.

Faculty: Engineering

Enhancing the degradation of agrochemical pollutants by managing the water

table has introduced a new horizon in agricultural pollution control. Experimental

work in this area shows that the degradation of agrochemicals such as nitrate is

dependent on the soil water content. The aim of this study was to evaluate the effect

of water table fluctuations on the nitrate and chloride transport. A set of laboratory

column experiments was conducted to investigate the transport of two non-sorptive

chemicals nitrate and chloride (N03, CI) to underground environment as effected by

water table fluctuation. Three-controlled water table depths set at 0.25 m, 0.50 m,

0.75 m from the surface and free drainage treatment were used. The concentration

curves for nitrate measured at different water table depths were not similar. The

difference in the mean and the peak nitrate concentrations indicates highly significant

difference in nitrate concentration among the water table depths. Through the values

of mean and peak nitrate concentrations, the 0.25 m and 0.50 m water table depths

gave the lowest mean and peak nitrate concentrations compared to the free drainage

water table treatment. Descriptive statistical analysis indicates that there was highly

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significant difference in the mean and the peak nitrate concentrations among the

water table treatments. These results suggest that the saturation conditions

associated with high water table will cause more nitrate degradation. The

concentration curves for chloride measured at difference water table depths were

similar, with slight difference in terms of peak and mean. The average chloride

recovery rate was approximately 91% in all water table treatments. The results

suggest that the chloride was not subjected to degradation and can be used as a good

conservative tracer for nitrate transport. Comparison between nitrate and chloride

concentrations among water table depths leads to the conclusion that water table

depth was an important factor effecting nitrate transport. Based on the data from this

experiment, nitrate has linear relation with chloride, and can be expressed as NOj =

kc Ct. The coefficient of linear relation, kc is affected by water table depth. Statistical

model (R2 =0. 83%) to simulate reduction and transport of nitrate as effected by

different water table depths was established and fitted to the experimental data. The

simulation results show reasonable agreement between predicted and measured data.

These results revealed that water table level was an important factor affecting

chemical transport. Anaerobic conditions associated with saturation condition have

created the potential for more degradation and promote biological and chemical

degradation to reduce nitrate transport. In this study, analytical deterministic model,

CXTFIT, was used to simulate and to describe nitrate and chloride transport under

different water table depths. The basis of the model is the solution to the convection­

dispersion transport equation. This model allows estimation of transport parameters

such as pore water velocity, dispersion coefficient and retardation factor and

degradation rate as the main factors affecting in nitrate transport. Predicted and

observed values of nitrate concentration were compared. Good agreement was

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obtained between the observed and predicted values. The results suggest that nitrate

degradation increases for the case of a fluctuating water table. Results of this

simulation study indicate that the CXTFIT model can be employed to predict nitrate

concentrations under water table management practices. More experimental and field

observation data are required to improve the accuracy of the model predictions.

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Abstrak tesis yang dikemukakan kepada Senat Universiti Putra Malaysia sebagai memenuhi keperluan untuk ijazah Doktor Falsafah

KESAN AMALAN PENGUR USAN ARAS AIR BUMI KE ATAS PENGANGKUTAN BAHAN KIMIA PERTANIAN DALAM

PERSEKITARAN BA WAH T ANAH

Oleh

ABDUL HAKIM MASAUD MUSSA ALMDNY

Julai2003

Pegerusi : Profesor Salim Said, Ph.D.

Fakulti : Kejuruteraan

Memperce degradasi pencemar kimia pertanian secara mengawal aras air bumi

memperkenalkan suatu ufuk baru dalam pengawalan pencemaran pertanian. UjikaJi

dalam bidang ini menunjukkan degradasi bahan kimia pertanian seperti nitrat adalah

bergantung kepada kandungan air tanah. Matlamat kajian ini adalah untuk menilai

kesan turun-naik aras air bumi ke atas pengangkutan nitrat dan kloride . Satu set

ujikaji menggunakan turus ujiun makmal telah dijalankan untuk menyiasat

pengangkutan dua bahan non-sorptif iaitu nitrat dan, kloride (N03, Cl) terhadap

persekitaran bawah tanah terkesan oleh turun-naik aras air bumi. Tiga kedalaman

aras airbumi dikwal pada 0.25 m, 0.50 m dan 0.75 m dari permukaan tanah, dan satu

rawatan penyaliran bebas telah digunakan. Lengkung kepekatan nitrat yang berbeza

telah diperolehi bagi pengukuran pada beberapa kedalaman. Perbezaan min dan

puncak kepekatan nitrat menunjukkan perbezaan signifikan yang tinggi bagi

kepekatan nitrat pada beberapa kedalamen. Dari nilai min dan puncak kepekatan

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nitrat, kedalarnan 25 em dan 50em memberikan min dan puncak yang terendah

berbanding rawatan penyaliran bebas. Analisis statistik diskriptif menunjukkan ada

perbezaan signifikan yang tinggi dalarn min dan puncak kepekatan nitrat di antara

berbagai rawatan aras air bumi. Keputusan ini mencadangkan keadaan tepu berkaitan

dengan aras airbumi yang tinggi akan meningkatkan keupayaan degradasi nitrat.

Lengkung kepekatan untuk klorida diukur pada kedalarnan aras air bumi yang

berbeza adalah sarna, hanya berbeza sedikit pada nilai puncak dan min. Purata kadar

perolehan semula klorida dalarn semua rawatan aras air bumi ialah lebihkurang

91 %. Keputusan ini menunjukkan bahawa klorida tidak terkesan oleh degradasi dan

boleh digunakan sebagai unsure tracer konservatif bagi pengangkutan nitrat .

Perbandingan di antara kepekatan nitrat dan klorida bagi berbagai kedalarnan aras

air bumi mengarah kepada kesimpulan bahawa aras air bumi adalah factor penting

yang mempengaruhi pengankutan nitrat. Berdasarkan data ujikaji ini, nitrat

mempunyai hubungan lelurus dengan klorida, dan boleh dinyatakan sebagai N03 =

keel. Pekali lelurus ke adalah terkesan oleh aras air bumi. Model satatistik (R2= 0.83)

untuk simulais pengurangan dan pengangkutan nitrat sebagaiman yang terkesan ol;eh

aras air bumi yang berbeza ditentukan dan disesuaikan dengan data ujikaji.

Keputusan simulasi menunjukan persetujuan yang memuaskan diantara rarnalan dan

data yang dicerap. Keputusan ini menunjukkan aras airbumi adalah factor penting

dalarn mempengaruhi pegangkutan bahan kimia. Keadaan anaerobic berpunca dari

keadaan tepu telah meningkatkan potensi untuk degradasi bahan kimiayang lebih

baik untuk mengurangkan pengangkutan nitrat. Dalarn kajian ini model deterministic

analitikal, CXTFIT, telah digunakan untuk simulasi dan untuk memperihalkan

pengangkutan nitrat dan klorida degan pelbagai rawatan kedalarnan aras air bumi.

Model ini membenarkan anggaran parameter pengangkutan serpti halaju air liang,

Vll

pekali sebaran, factor rencatan dan kadar degradasi sebagai factor terpenting dalam

pengangkutan nitrat. Nilai kepekatan nitrat yang diramal dan tercerap telah

dibandingkan . Pesetuijuan baik telah diperolehi di antara data tercerap dan nilai

ramalan. Keputusan menunjukkan degradasi nitrat meningkat untuk kes aras air

bumi yang turun-naik. Keputusan kajian simulasi ini menunjukkan model CXTFIT

boleh digunakan untuk meramal kepekatan nitrat dalam pengurusan aras air bumi.

Lebih banyak data kajian di lapangan adalah diperlukan untuk memperbaiki

kejituan model ramalan tersebut.

Vlll

ACKNOWLEDGEMENTS

I would like to take this opportunity to express my sincere thanks to the

chairman of the supervisory committee Prof Salim Said for his continuous help,

support, friendship, encouragement and personal interest during the period of this

study. Sincere thanks are extended to the members of the committee, Prof Ir Dr

Mohd Soom and Dr. Thamer Ahmed Mohammed for their support, cooperation and

guidance. Sincere thanks to Dr. Suleyman Muyibi for his support and useful

contributions.

Special thanks to Mr. Ghazali Kassim for his constant assistance during the

construction of the experimental setup. I wish to express my gratitude to my friends

in faculty of engineering for their help and support in this study especially Mr. Salah

athloothi for his help and support. I am grateful to the University Putra Malaysia for

all facilities and help during this study. I also express my deepest gratitude to the

staff of the Graduate School for all kinds of assistance provided to us as international

students that make our life in UPM at ease.

I am grateful to the peoples of the Libyan Arab Jamahiriya and AI- Fateh

University who offer me the scholarship for pursuing the Ph.D degree at University

Putra Malaysia.

Special thanks go to all the members of my family who without their

encouragement and overwhelming support this work would not have been possible.

Finally and above of all, much thanks and praise are directed to Allah (sbt), the

controller of the whole universe, who has provide me with health and makes this

work comes true.

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I certify that an Examination Committee met on 7tlt July 2003 to conduct the final examination of Abdul Hakim Masaud Mussa AI-Mdny on his Doctor of Philosophy thesis entitled" Effects of Water Table Management Practices on the Transport of Nitrates in Sandy Underground Environment" in accordance with Universiti Pertanian Malaysia (Higher Degree) Act 1980 and Universiti Pertanian Malaysia (Higher Degree) Regulations 1 98 1. The Committee recommends that the candidate be awarded a relevant degree. Members of the Examination Committee are as follows:

KwokChea Yan Faculty of Engineering Universiti Putra Malaysia (Chairman)

Salim Said, Ph.D. Professor Faculty of Engineering Universiti Putra Malaysia (Member)

Mohd Amin Mohd Soom, Ph.D. Professor Faculty of Engineering Universiti Putra Malaysia (Member)

Thamer Ahmed Mohammed, Ph.D. Faculty of Engineering Universiti Putra Malaysia (Member)

Frederik J. Putuhena, Ph.D. Professor Faculty of Engineering UNlMAS (Independent Examiner)

Date: 30 SEP 2003

x

This thesis submitted to the Senate of Universiti Putra Malaysia and has been accepted as fulfilment of the requirements for the degree of Doctor of Philosophy. The members of the Supervisory Committee are as follows:

Salim Said, Ph.D. Professor Faculty of Engineering Universiti Putra Malaysia (Chairman)

Mohd Amin Mohd 800m, Ph.D. Professor Faculty of Engineering Universiti Putra Malaysia (Member)

Thamer Ahmed Mohammed, Ph.D. Faculty of Engineering Universiti Putra Malaysia (Member)

Xl

r? ."J · .J �----:T AINI IDERIS, Ph.D. Professor / Dean School of Graduate Studies Universiti Putra Malaysia

Date: 'I 4 Nov 2003

DECLARATION

I hereby declare that the thesis is based on my original work except for quotations and citations, which have been duly acknowledged. I also declare that it has not been previously or currently submitted for any other degree at UPM or other institutions.

XlI

ABD�UDMUSSA

Date: A '1 � <? P ? 003

TABLE OF CONTENTS

Page

DEDICATION 11 ABSTRACT 111 ABSTRACT VI ACKNOWLEDGMENTS lX APPROVAL x

DECLARATION XlI LIST OF TABLES XV1 LIST OF FIGURES XVII LIST OF ABBREVIATIONS XIX

CHAPTER

1 INTRODUCTION 1 General Introduction 1 Objectives of the Study 9 Thesis Organization 1 0

2 LITERATURE REVIEW 1 1 Agrochemical Problems In the Environment 11 Fate and Transport of Agrochemical in the 1 7 Environment Agricultural Drainage and Water Quality 24 Water Table Management 27

Definition and Descriptions 27 Water Table Management for Water Quality 29 Improvement

General Mechanisms of Subsurface Water 44 Contamination Contaminant Transport Processes 45 Mathematical Description of Contaminant Fate and 48 Transport Modeling of Contaminant Transport and Fate 50

3 MATERIALS AND METHODS 5 5 Experimental Procedures 56

Soil Column unit 5 6 Soil Preparation 57

Determination of Soil Properties 57 Soil texture 57 Bulk Density 5 8 Porosity 59 Saturated Hydraulic Conductivity 60

Soil Columns 61 Water Table Treatments 62 Water Sample collection 63

Xill

Water Sample Analysis 64 Chemical Preparation and application 64 Water application 65 Presentation of Experimental Results 65

Comparison Nitrate Concentration for Various 66 Water Table Depths Comparison of Nitrate and Chloride 68 Concentration Treatments Statistical Analysis 69 Simulation Model 70 Model Description 71 Governing Equation of Solute Transport 7 1 Inverse Modeling (Parameter Estimation) 74 Sensitivity Analysis of Simulation model to 75 Input parameters Verification Test 75

4 RESULTS AND DISCUSSIONS 77 Effect of Water Table Management on the Transport of Nitrate and Chloride to the Underground Environment Introduction 77

Comparison of Nitrate Transport Through Water 78 Table Depths Comparison between Chloride and Nitrate 88 Concentration Modeling Nitrate Transport 100 Statistical Model Development 100 Verification of the Regression Equation 105 Comparison of model output with experimental 107 results

5 RESULTS AND DISCUSSIONS 119 Simulation of Nitrate Transport Under Control Water Table Using the CXTFIT Model Introduction 119 Model Description 120 Governing Equation of Solute Transport 120 Model Parameter Estimation 122 Chloride Concentrations and Model Representation 123 Nitrate Concentration and Model Representation 130 Sensitivity Analysis 141 Model Verification 150 Discussion of the Simulation Results 164

6 SUMMARY AND CONCLUSIONS 172 Summary 172 Recommendations for Further Work 176

XIV

REFERENCES 177

APPENDICES 1 90 Appendix A 1 91 AppendixB 1 95 Appendix C 1 99 Appendix D 203

VITA 205

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LIST OF TABLES

Table Page 3.1 Selected soil properties used in this study. 61 3.2 Chemical concentration and application 65 4.1 Summary of statistical comparison between mean and 87

peak nitrate concentration at different water table depths 4.2 Model summary 101 4.3 Analysis of variance of the regression model 102 4.4 Coefficient for the regression model 104 4.5 Summary of statistical parameters used during the 115

regression model testing 5.l Fitted parameter of the pour water velocity and 124

dispersion coefficient with coefficient of determination R2 obtained by fitting to the observed chloride concentration for each water table depth using CXTFIT model

5.2 Fitted Parameter of retardation factor and degradation 131 rate constant with determination coefficient R2 obtained by fitting to the nitrate data for each water table depth using CXTFIT model

5.3 Optimized values of estimated parameters and statistics 139 obtained by fitting CXTFIT to the observed chloride and nitrate concentration data

5.4 Summary of sensitivity analysis interpreted as percent 150 change in the model outputs with respect to change in the model inputs

5.5 Summary results of statistical measures that were used 163 during the model testing

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LIST OF FIGURES

Figure Page 3.1 Soil column experiment system 56 3.2 Soil columns and water table instrumentation 63 4.1 Nitrate concentration at 0.25 m water table depth as compared 80

with free drainage water table treatment 4.2 Nitrate concentration at 0.50 m water table depth as compared 83

with free drainage water table treatment 4.3 Nitrate concentration at 0.75 m water table depth as compared 85

with free drainage water table treatment 4.4 Chloride concentration at different water table depths 89 4.5 Comparison of chloride and nitrate concentration for 0.25 m 90

water table depth 4.6 Comparison of chloride and nitrate concentration for 0.50 m 91

water table depth 4.7 Comparison of chloride and nitrate concentration for 0.75 m 92

water table depth 4.8 Comparison of chloride and nitrate concentration for free 94

drainage water table treatment 4.9 Correlation of nitrate and chloride concentrations at 0.25 m 96

water table treatment 4.10 Correlation of nitrate and chloride concentrations at 0.50 m 97

water table treatment 4.11 Correlation of nitrate and chloride concentrations at 0.75 m 98

water table treatment 4.12 Correlation of nitrate and chloride concentrations at free 99

drainage water table treatment 4.13 Observed and predicted nitrate concentration for different water 107

table depth 4.14 Observed and predictive nitrate concentration at 0.25 m water 110

table depth 4.15 Observed and predictive nitrate concentration at 0.50 m water 111

table depth

4.16 Observed and predictive nitrate concentration at 0.75 m water 113 table depth

4.17 Observed and predictive nitrate concentration free drainage 114 water table treatment

5.1 The best fit of the model simulated and observed chloride 125 concentration during the parameter estimation at 0.25 m water table depth

5.2 The best fit of the model simulated and observed chloride 127 concentration during the parameter estimation at 0.50 m water table depth

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5.3 The best fit of the model simulated and observed chloride 1 28 concentration during the parameter estimation at 0.75 m water table depth

5 .4 The best fit of the model simulated and observed chloride 129 concentration during the parameter estimation at free drainage water table treatment

5 .5 The best fit of the model simulated and observed nitrate 1 32 concentration during the parameter estimation at 0.25 m water table depth

5 .6 The best fit of the model simulated and observed nitrate 1 33 concentration during the parameter estimation at 0.50 m water table depth

5 .7 The best fit of the model simulated and observed nitrate 1 35 concentration during the parameter estimation at 0.7 5 m water table depth

5.8 The best results of the model simulated and observed nitrate 1 37 concentration during the parameter estimation at free drainage water table treatment

5 .9 Sensitivity of concentration curves to changing in pore water 1 43 velocity

5.10 Sensitivity of concentration curves to changing in dispersion 1 44 coefficient

5.1 1 Sensitivity of concentration curves to changing in retardation 1 46 factor

5 . 12 Sensitivity of concentration curves to changing in degradation 1 47 rate constant

5 . 1 3 Comparison of the predicted and observed nitrate 1 5 3 concentrations with time at 0.25 m water table depth

5. 1 4 Predicted versus observed N03 concentration at 0.25 m water 1 54 table depth

5 . 15 Comparison of the predicted and observed nitrate 1 55 concentrations with time at 0.50 m water table depth

5 . 1 6 Predicted versus observed N03 concentration a t 0.50m water 1 57 table depth

5. 1 7 Comparison of the predicted and observed nitrate 158 concentrations with time at 0.75 m water table depth

5 . 18 Predicted versus observed N03 concentration a t 0.75 m water 1 60 table depth

5.19 Comparison of the predicted and observed nitrate 1 61 concentrations with time at free drainage water table treatment

5 .20 Predicted versus observed N03 concentration free drainage 1 63 water table depth

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ME RMSE U R2

r D v R

Ii S CDE CXTFIT fJ Db J advection J dispersion SSQ (b) Column A ColumnB Column C Column D t d S n k K p kc M; Pi SPSS EEC WHO MEPA USEPA

LIST OF ABBREVIATIONS

Mean error Root mean square error Theil's coefficient Determination coefficient Correlation coefficient Dispersion coefficient Pore water velocity Retardation factor Degradation rate constant Adsorbed concentration per unit mass of soled phase Convection dispersion equation Program for analyzing contaminant transport in soil Particle density of soil

Bulk density Mass flux of solute transported by advection Mass flux of solute transported by dispersion Sum of squared residuals Soil column with 0.25 m water table depth Soil column with 0.50 m water table depth Soil column with 0.75 m water table depth Free drainage water table treatment (FD) Time Water table depth from the surface Saturation depth Volumetric water content Distribution coefficient for the chemical Hydraulic conductivity Porosity Coefficient of linear relation between nitrate and chloride Measured result Simulated result Statistical software European Economic Community World Health Organization Metrology and Environmental Protection Administration U S Environmental Protection Agency

xix

CHAPTERl

INTRODUCTION

General Introduction

Ground water is the main source of domestic, agricultural, and industrial supplies

in many places of the world. It constitutes the largest available source of freshwater.

Therefore, a proper development and utilization of this renewable natural resource

are of interest for all water supply requirements. In any evaluation of groundwater

resources, physical and biological characteristics of the water are of major

importance in determining whether or not water is suitable for domestic, industrial,

or agricultural use. With increasing demand for water and with the intensification of

water utilization, the quality problem becomes the limiting factor in the development

of water resources; especially in agricultural areas where exist variety of chemicals

that can pass through the ground surface to the water table of the aquifer

The contaminations of groundwater by chemical substances from various point

and non-point sources create many significant problems. Generally, groundwater

contamination is traced back to environmental, agricultural, domestic and industrial

sources. Environmental contamination can be due to the environment through which

the flow of groundwater takes place. Seawater intrusion is an example of this

pollution. Agricultural pollution can be due to irrigation and rainwater dissolving

and carrying fertilizers and salts as they infiltrate through the ground surface and

provide a major source of elevated nutrient levels to the subsurface water. Domestic

and industrial contaminations can be caused by many ways such as percolation

1

from septic tanks and artificial recharge of aquifers by sewage water. This study is

concerned with groundwater pollution that is caused by agrochemicals.

Non point source pollution is a major problem associated with current intensive

agricultural production methods. Surface and groundwater contamination from

agricultural drainage water is of major environmental concern in the pursuit of

sustainable agriculture. Groundwater in agricultural areas often has a distinct water

quality signature composed of salt, nitrate, phosphorus, sediment, heavy metals,

tracer elements, bacteria and pesticides. The sources of these compounds frequently

come from agricultural chemicals such as fertilizers, pesticides and herbicides. These

pollutants may destroy aquatic ecosystems and impair downstream water quality

(Madramootoo,1996).

Ground water monitoring programs throughout the world have revealed some

pollution of groundwater supplies by nitrate and pesticides. Pollution of water

resources by agricultural chemicals may cause health problem to humans. For

example, a nitrate concentration in drinking water over 1 0 mg/l, the EPA safe

drinking water limit, may cause clinical blue baby syndrome in infants. In additional

to human health concerns, water pollution by agricultural chemicals affects fish and

wildlife, commercial fisheries, recreational uses of surface waters, and water

treatment facilities. Another concern is that once groundwater is contaminated, the

problem is extremely difficult and expensive to remedy.

The potential for surface and groundwater pollution by agricultural chemicals

lost from agricultural fields depends upon many factors including soil �e, climate,

2

geological, and agricultural management practices. To reduce subsurface water

pollution from agricultural chemicals it is important to know the transport

mechanisms and extent of their loss on a specific pathway. Researchers have

investigated the mechanisms of chemical transport in soil profile under various

conditions and identified several physical, chemicals and biological processes that

control chemical behavior in soil. These processes are transport, sorption,

transformation, degradation, volatilization, and plant uptake. The occurrence of each

process depends upon pollutants characteristics, soil properties, microorganisms,

environmental conditions, and the agricultural and water management practices

employed. The interactions of these processes over time and space determine the fate

of chemicals in soils. Subsurface flow is likely to be the major mechanism for the

transport of soluble pollutants in many catchments areas, especially when water table

approaches the soil surface. Pollutants such as nitrate, pesticides and herbicides

which are normally applied in liquid or solid form, may be transported during runoff

and join the river system to cause surface water pollution; they may also infiltrate

into the soil and pollute the subsurface water. The increased infiltration of water, due

to subsurface drainage may results in increased leaching and, subsequently, an

increase in ground water contamination. Hallberg, (1986) has suggested that

infiltration recharge may be the primary delivery mechanism of agricultural related

contaminants to the ground water. The main factors affecting agricultural chemical

loss from agricultural fields by leaching include the flow of water through the soil

profile, and the amount of agrochemical for leaching at the time of water movement.

Many agrochemicals such as nitrate and pesticides are subjected to degradation

in the environment. These agrochemicals are known to be degraded through both

3

chemical and biological processes. Chemical reactions are mediated by soil

properties, such as PH, or catalyzed by soil minerals. The usually moist and aerated

upper layer of agricultural soils provides favorable conditions for chemical reactions,

particularly hydrolysis and oxidation. In a natural environment it is often difficult to

separate biological transformation from chemical transformation. The predominant

means of transformation for wide variety of chemical compounds is biological, i.e.,

microbial or enzymatic. The kinetics of chemical compounds to degradation is

effected by the quantity and availability of the chemicals, the presence of

microorganisms or enzyme systems capable of degrading the chemicals, and the

activity level of the microorganisms as affected by the nutrients available to sustain

the microbial popUlation and by environmental and soil conditions such as

temperature, moisture, aeration, pH, organic matter and cation exchange capacity.

Researchers have examined various methods to reduce the effect of agricultural

chemicals loads on the environment. Agricultural management practices such as

chemical management and water table management are being considered to reduce

the negative effects of the use of agrochemicals on groundwater. Water table

management is defined as any system that influences the elevation of the shallow

water table, including practices such as controlled surface drainage and subsurface

drainage. Water table management has been used in poorly drained agricultural soils

to control water table in the soil profile. Historically, subsurface drainage systems

were not designed as water quality management tools, but they have an impact on

chemical fate and transport within agricultural soils. Very little attention has been

given to proper management of existing subsurface drainage systems and subsequent

impact on ground water quality. These drainage systems actually provide the

4

opportunity to detect some water quality problems, and then possibly control or

eliminate the problems by controlling the water table to promote biological and

chemical degradation of contaminants. Enhancing the degradation of agrochemicals

by controlling the water table in the field has introduced a new horizon III

agricultural pollution control. However, the use of water table management to

enhance degradation of pollutants is a new area of research which hypothesized that

the contamination of water bodies by agrochemicals transport from the agricultural

areas through drainage systems can be substantially reduced or perhaps entirely

prevented by water table management techniques.

Recently, water table management practices have received much attention as

potential measures to reduce pollution hazard to groundwater. The greatest benefit

of water table management practices on water quality has been its influence on the

total nutrient loadings to drainage outflow (Evans et aI., 1989). The reduction of

agrochemical pollution such as nitrate and pesticides is attributed to enhanced

denitrification as well as restricted outflow under water table management.

Denitrification is a very complicated biological chemical process and the most

important process for removing nitrate in water. It is an anaerobic process and is

carried out by microorganisms, which use nitrate as their primary electron acceptor

for obtaining energy from organic compounds. Because higher water tables reduce

aeration and diffusion, denitrification is enhanced under water table management and

excess nitrate is converted to its gaseous form to be returned to the atmosphere,

rather than being leached to drainage water. Also, the shallow water table that

persists for extended periods each year can create an anaerobic condition that could

5