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Analysis of Nitrate Contamination
of Gaza Coastal Aquifer, Palestine
Mohammad N. Almasri1and Said M. S. Ghabayen2
Abstract: The ongoing degradation of the water quality of the Gaza Coastal Aquifer 共GCA兲is of a great concern for the different
authorities and agencies involved in the water sector in the Gaza Strip, Palestine. The GCA is almost the only source of fresh water to over
1.5 million residents where it is utilized extensively to satisfy agricultural, domestic, and industrial water demands. The aquifer is
currently being overpumped where pumping largely exceeds total recharge. In addition, manmade sources of pollution endanger the water
resources supplies in the major municipalities of the Gaza Strip. Many water quality parameters in the GCA presently exceed the
maximum contaminant level 共MCL兲of the US Environmental Protection Agency drinking water standards, especially for nitrate and
chloride. This case study analyzes nitrate concentration distribution for the GCA at different levels such as land use classes and sampling
depth. Nitrate concentration data from 1990 and from 2000 to 2004 were compiled and assembled into a single composite database. A
geographic information system was used to assess the spatial and temporal variability of nitrate occurrences in the aquifer. Results show
that the first quartile of nitrate concentration for the years 1990 and 2000–2004 exceeds the MCL. In addition, the analyses demonstrated
a generally increasing trend in groundwater nitrate concentration. The areas with the most elevated nitrate concentrations are areas
characterized by heavy agricultural activities and urban areas. Elevated nitrate concentrations in the GCA indicate anthropogenic con-
tamination sources.
DOI: 10.1061/共ASCE兲1084-0699共2008兲13:3共132兲
CE Database subject headings: Nitrates; Ground-water pollution; Agriculture; Fertilizers; Aquifers; Coastal environment; Palestine.
Introduction
Nitrogen 共N兲is an indispensable input for the sustainability of
agriculture 共Lake et al. 2003兲. Nevertheless, nitrate 共NO3兲con-
tamination of groundwater is a worldwide problem mainly due to
the excessive use of fertilizers in intensive agriculture. Because
nitrate is both soluble and mobile, it is prone to leaching through
soil with infiltrating water and can persist in shallow groundwater
for years 共Shrestha and Ladha 2002; Nolan et al. 2002; Almasri
2003; Almasri and Kaluarachchi 2004a,b, 2005a,b兲.
Agricultural practices generally result in nonpoint source pol-
lution of groundwater 共Hall et al. 2001; Delgado and Shaffer
2002兲. With nonpoint sources, groundwater quality may be de-
pleted over time due to the cumulative effects of several years of
practices 共Addiscott et al. 1992; Schilling and Wolter 2001兲. Non-
point sources of nitrogen from agricultural activities include fer-
tilizers, manure application, and leguminous crops. For instance,
the extensive use of fertilizers on row crops is considered a main
source of nitrate leaching to groundwater particularly in sandy
soils 共Hubbard and Sheridan 1994兲. Point sources of nitrogen are
shown to contribute to nitrate pollution of groundwater. The
major point sources include septic tanks and dairy lagoons. Many
studies have shown high concentrations of nitrate in areas with
septic tanks 共Cantor and Knox 1984; Keeney 1986; Arnade 1999;
MacQuarrie et al. 2001兲. This is of particular concern to rural
homeowners who use shallow drinking water wells that can be
easily contaminated with septic tank effluent including bacteria
and viruses. Seepage from dairy lagoons has been found to be a
source of elevated nitrate in shallow groundwater 共Erickson
1992兲.
Public concern over the groundwater quality of the Gaza
Coastal Aquifer 共GCA兲has grown significantly in recent years
and has focused increasingly on anthropogenic sources for the
problem. The GCA is almost the only source of fresh water to
over 1.5 million residents where it is utilized extensively to sat-
isfy agricultural, domestic, and industrial water demands. Evi-
dence indicates that the nitrate levels routinely exceeded the
maximum contaminant level 共MCL兲of 10 mg/LNO
3–N in 90%
of the water supply wells 共Ghabayen et al. 2006兲. Degradation of
groundwater quality in the GCA due to nitrate pollution and the
continuously increasing demand for potable water have motivated
the restoration of the aquifer. Restoration efforts have intensified
the dire need for developing protection alternative measures and
management options such that the ultimate nitrate concentrations
at the critical receptors are below the MCL.
Since the GCA is the only source of water for the residents of
Gaza Strip, nitrate contamination of the aquifer is a public-health
concern. A recent survey shows that 124 out of 640 infants 共chil-
dren under the age of 6 months兲have methemoglobin levels
above 20%. There are numerous sources of nitrate contamination
in the aquifer, including agricultural fertilizers, cesspits, waste
1Assistant Professor, Water and Environmental Studies Institute,
An-Najah National Univ., P.O. Box 7, Nablus, Palestine 共corresponding
author兲. E-mail: mnmasri@najah.edu
2Assistant Professor, College of Applied Engineering and Urban Plan-
ning, Univ. of Palestine, Gaza, Palestine. E-mail: saidghabayen@
yahoo.com
Note. Discussion open until August 1, 2008. Separate discussions
must be submitted for individual papers. To extend the closing date by
one month, a written request must be filed with the ASCE Managing
Editor. The manuscript for this paper was submitted for review and pos-
sible publication on April 6, 2006; approved on April 16, 2007. This
paper is part of the Journal of Hydrologic Engineering, Vol. 13, No. 3,
March 1, 2008. ©ASCE, ISSN 1084-0699/2008/3-132–140/$25.00.
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dumping, and direct discharge of raw sewage to the ground sur-
face 共Ghabayen et al. 2006兲. Recently, improving nitrogen and
nitrate management has become essential due to the elevated con-
centrations of nitrate in the GCA associated with high rates of
nitrogen-based fertilizers applied to crops. Managing nitrate con-
tamination of the GCA entails mainly the restriction on fertilizer
application and the control of the unsupervised utilization and
disposal of untreated wastewater effluent. In other words, we need
to adopt a nitrate contamination management scheme that aims at
minimizing nitrate leaching to groundwater and hence nitrate oc-
currences in the GCA. Accurate quantification of nitrate leaching
is difficult 共Almasri and Kaluarachchi 2005a兲. Nitrate leaching
from the soil zone is a complex interaction of many factors 共see
Fig. 1兲such as the land use practices, on-ground nitrogen loading,
groundwater recharge, soil nitrogen dynamics, soil characteristics,
and the depth to water table 共Almasri 2003; Almasri and Kalu-
arachchi 2004b兲. Once reaching the groundwater, nitrate migrates
in the saturated zone via advection and dispersion.
In order to restore the quality of the GCA, Almasri et al.
共2005兲developed a conceptual framework for managing nitrate
contamination of the GCA. Fig. 2 depicts the general proposed
management framework for nitrate contamination control of the
GCA. As can be seen, the framework starts by the assessment and
analysis of the field data to identify and evaluate nitrate contami-
nation extent. Thereafter, the possible contamination sources are
characterized to facilitate the development of the management
options that target these sources. Decision analysis utilizes and
employs the management options developed to choose the best
option. Since the ultimate objective of the management frame-
work is the determination and promotion of the best management
options, it is important to simulate the outcome of these manage-
ment options through the development and utilization of
mathematical models of nitrate fate and transport in soil and
groundwater.
This case study addresses the first step in the conceptual
framework for managing nitrate contamination of the GCA 共see
Fig. 2兲. In addition, the paper analyzes the nitrate occurrences in
the GCA in order to draw strong justifications for conducting the
proposed management framework depicted in Fig. 2 especially
when considering that this pollution is attributed to anthropogenic
sources that involve on-ground activities. Data pertaining to ni-
trate concentration in the GCA were collected and later processed
using ArcView geographic information system 共GIS兲of ESRI
共1999兲. The analysis considers nitrate concentration distribution
across the entire GCA, nitrate occurrences in the groundwater of
different municipalities, nitrate concentration distribution in rela-
tion to the land use type, and nitrate concentration variability with
sampling depth. In addition, the distribution of on-ground nitro-
Fig. 1. Schematic describing integrated three-process approach to conceptualize on-ground nitrogen loading, soil nitrogen transformations, and
fate and transport of nitrate in groundwater
Fig. 2. Flow chart depicting general proposed management
framework for nitrate contamination control
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gen loading due to agricultural practices from nonpoint sources
was determined. The assessment is carried out using GIS tools.
This assessment is intended to aid in the development and imple-
mentation of the proposed management framework of which the
conceptual model for fate and transport of nitrate ought to be
prepared.
Description of Study Area
This section provides a concise overview of the Gaza Strip and
GCA. The Gaza Strip is a narrow, low-lying stretch of sand dunes
bordering the Mediterranean Sea as shown in Fig. 3. It forms the
foreshore that slopes gently up to an elevation of 90 m. The total
area of the Gaza Strip is approximately 365 km2with an approxi-
mate population of 1.5 million and a coastline of 40 km. The
topography of the Gaza Strip is characterized by elongated ridges
and depressions, dry streambeds, and shifting sand dunes. The
Gaza Strip has a characteristically semiarid climate. Annual aver-
age rainfall ranges between 400 mm/year in the north to about
200 mm/year in the south near Rafah. Apparently, there is a gen-
eral north-south pattern of rainfall. There is a 5-month period in
winter 共November–March兲with a rainfall surplus. During the rest
of the year, evaporation greatly exceeds the rainfall. The annual
average relative humidity is about 72%. The average mean daily
temperature in Gaza City ranges from 26°C in summer to 12° C
in winter 共Metcalf and Eddy 2000; Ghabayen 2004兲.
The width of the GCA varies from 15 km in the north to about
20 km in the south. The depth to groundwater in the GCA ranges
from 20 m in the south-east to about 180 m in the north-west. The
GCA is composed of sands, calcareous sandstone, and pebbles.
Semipermeable and impermeable layers are sandwiched in
between, dividing the aquifer system into subaquifers in the west-
ern part. Further inland, the subaquifers effectively merge to form
one system. GCA consists of the Pleistocene age Kurkar Group
and recent 共Holocene age兲sand dunes. The Kurkar Group consists
of marine sandstone, reddish silty sandstone, silts, clays, uncon-
solidated sands, and conglomerates. Regionally, the Kurkar
Group is distributed in a belt parallel to the coastline.
Regional groundwater flow is toward the Mediterranean Sea.
However, natural flow patterns have been disturbed by pumping.
Within the Gaza Strip, large cones of depression have formed
over the past years within the Gaza, Khan Younis, and Rafah
Table 1. Breakdown of Land Use by Category for Gaza Strip and
Corresponding Percentage and Area Occupied by Each Category
共Obtained after Processing Fig. 4 Using GIS Statistical Capabilities兲
Land use
Area
共km2兲
Percentage
共%兲
Almond 6.3 1.7
Citrus 41.6 11.6
Dates 7.8 2.2
Grapes 5.0 1.4
Greenhouses 9.2 2.6
Horticulture 22.1 6.1
Olives 1.9 0.5
Field crops 112.0 31.1
Fruits 14.3 4.0
Vegetables 5.7 1.6
Built-up areas 59.1 15.0
Settlements 共formerly兲17.6 4.9
Open area 62.1 17.3
Fig. 3. Regional location of Gaza Strip
Fig. 4. Land use distribution of Gaza Strip 共adapted from database of
PWA兲. Land use classes were grouped into three categories for ease
of visualization.
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municipalities. All along the coast, there are areas of seawater
intrusion due to overpumping of the freshwater aquifer 共Gha-
bayen 2004兲.
Heavy agricultural activities take place in the Gaza Strip in-
cluding citrus and greenhouses. A land use map of the Gaza Strip
is shown in Fig. 4 and is based on the regional plan developed by
the Ministry of Planning and International Cooperation in 1998
for the West Bank and Gaza Strip. The breakdown of land use by
category is summarized in Table 1. Agricultural land occupies
about 65% of the land surface and is the dominant economic
sector in the Gaza Strip.
Methods and Data Analysis
Data Collection
Nitrate concentration data employed in the analysis were obtained
mainly from the database of the Palestinian Water Authority
共PWA 2004兲. All available data pertaining to the nitrate concen-
tration in the GCA were assembled into a single composite data-
base in a GIS-based format. The total number of wells in the
database is 568 with 2,413 measurements of nitrate. The database
mainly includes the well ID, well coordinates, date of sampling,
sampling depth, municipality, concentration, and well use. A GIS
point shapefile of well spatial locations and the corresponding
data were developed and used in the analysis. The analysis covers
the year 1990 and the period from 2000 to 2004.
On-Ground Nitrogen Loading in Study Area
The on-ground nitrogen loading distribution for the GCA was
estimated from the nonpoint sources pertaining to the agricultural
practices. Two potential nonpoint sources were considered includ-
ing the application of nitrogen-based fertilizers and NO3– N from
irrigation with contaminated water. The detailed land use map of
the Gaza Strip was utilized in computing the distribution of on-
ground nitrogen loading. Annual fertilizer application rates corre-
sponding to the land use classes summarized in Table 1 were
obtained from the Palestinian Ministry of Agriculture and allo-
cated accordingly using a GIS grid calculator. The on-ground ni-
trogen loading from irrigation was obtained by multiplying the
annual irrigation volume with the average nitrate concentration
distribution for the years from 2000 to 2004. This distribution was
obtained using the Thiessen method for the monitored nitrate con-
centrations. The total on-ground nitrogen loading 共summation of
loadings from fertilizer and irrigation兲was then computed as
shown in Fig. 5. As can be inferred from Fig. 5, high on-ground
nitrogen loadings are encountered in the southern western parts of
the Gaza Strip. An additional major source of nitrate contamina-
tion in the aquifer can be attributed to the cesspits that are used
for waste disposal in the residential areas that are uncovered by
wastewater collection systems. This is a chief source of pollution,
especially when considering the high infiltration potential of the
soil and that the design of these cesspits is not done in an envi-
ronmentally responsible way.
Nitrate Distribution across Study Area
Since one of the objectives of the analysis is to characterize the
overall trend of nitrate contamination in the GCA, no attempt was
made to eliminate wells of short time series that do not represent
a long period. This approach is common in many studies, espe-
cially studies conducted for regional-scale assessment to infer
best management practices 共see for instance Nolan and Stoner
2000; Parliman 2002兲.
Fig. 6 depicts the boxplots of nitrate concentration for the
GCA for selected years. In preparing the boxplots of Fig. 6, all the
nitrate concentration data were grouped according to the year of
sampling and later utilized in developing the boxplots. Appar-
ently, nitrate concentration distribution of the first quartile for the
years 1990 and 2000–2004 exceeds the MCL 共the dashed line in
Fig. 6兲of 10 mg /LNO
3–N. That is 75% of the nitrate concen-
tration measured values exceed the MCL. The maximum ob-
served value of nitrate concentration was reported in the year
2001 where nitrate concentration was approximately 237 mg/L
NO3–N. Fig. 7 provides a close look at the point spatial distribu-
tion of mean nitrate concentration for the northern portion of the
GCA with emphasis on the Gaza and Jabalia areas where the
extreme value of 237 mg/LNO
3–N was reported 共encircled in
Fig. 7兲. Other values as high as 110 mg/L can be noticed in the
proximity of the well of 237 mg/LNO
3–N.
The variability of the temporal distribution of nitrate concen-
tration across the GCA for the years 2000–2004 was characterized
as shown in Fig. 8. No conclusive trend can be inferred out of
Fig. 8. Nevertheless, there is a noticeable increasing trend in the
maximum and first and third quartiles of nitrate concentrations in
the months from March to June. The highest median and maxi-
mum nitrate concentrations are observed in February. The analy-
Fig. 5. Total annual on-ground nitrogen loading from fertilizer appli-
cation and irrigation for Gaza Strip
Fig. 6. Boxplots of monthly nitrate concentration in aquifer for years
from 2000 to 2004. Dotted line denotes MCL.
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sis considering the mean and median shows that the mean values
do not change significantly with a maximum value of mean of
32.2 mg/LNO
3–N occurring in November. As for the median,
the maximum median value is 24.9 mg/LNO
3–N and occurs in
February followed by a value of 24.8 mg/LNO
3–N for Novem-
ber. Upon ranking the months according to the mean and median
values, it is quite difficult to identify a definite monthly trend. To
check for seasonal trends, data were grouped according to the
sampling season. Thereafter, mean and median concentrations
were computed and plotted as shown in Fig. 9. Apparently, the
mean nitrate concentrations across all the seasons during the years
2000–2004 were all above the MCL. The same applies for the
median except for fall 2004. However, the number of sampling
wells varies considerably from season to season as the case for
fall 2004 where only three sampling points were collected. As can
be inferred from Fig. 9, high median nitrate concentrations are
encountered in winter and summer seasons, where for instance
the highest median concentration 共⬃40 mg/LNO
3–N兲is en-
countered in winter 2004 followed by summer 2003, spring 2004,
and the two summer seasons of 2004 and 2002.
The spatial distribution of the mean nitrate concentrations
across the GCA for the year 2000 is shown in Fig. 10. To assess
the probable anthropogenic effects on groundwater quality, nitrate
concentrations across the GCA were classified into four groups
based on the work of Madison and Brunett 共1985兲and Cox and
Kahle 共1999兲. The four concentration ranges as shown in Fig. 10
are: 0– 1 mg/LNO
3–N to indicate the most likely background
concentration; 1 –3 mg/LNO
3–N to indicate a possible human
influence; 3– 10 mg/LNO
3–N to indicate pollution due to
human influence; and greater than 10 mg/LNO
3–N to indicate
that the MCL was exceeded as a result of extensive human activi-
ties. Apparently, the majority of the concentrations exceed the
MCL of 10 mg /LNO
3–N that indeed indicates extensive human
activities. To get a better appreciation of the spatial distribution of
nitrate concentrations across the GCA, interpolation using kriging
was followed to develop a contour map of concentrations for the
year 2001. This map is shown in Fig. 11. Apparently, there are
two distinctive areas of high concentrations greater than 48 mg/L
NO3–N. These areas correspond to Gaza City and Khan Younis,
where concentrated high groundwater pumping is encountered. A
trend in nitrate concentration across the GCA is observed where
the median values increase with time which might be considered
Fig. 7. Spatial distribution of mean nitrate concentrations for
Northern GCA for year 2001. Occurrence of high concentration value
of 237 was encircled.
Fig. 8. Boxplots of nitrate concentration in aquifer for 2000–2004.
Dotted line denotes MCL.
Fig. 9. Seasonal average and median nitrate concentrations for GCA
Fig. 10. Mean nitrate concentration for GCA in 2000
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as an indicator of the existence of ongoing pollution sources
present in the study area that are responsible for the persisting
degradation of water quality of the GCA.
Nitrate Distribution in Individual Municipalities
Administratively, the Gaza Strip is divided into 24 municipalities
as shown in Fig. 12. Nitrate occurrences in the GCA were ana-
lyzed according to the boundaries of the municipalities through
utilizing GIS spatial join capabilities by simply locating all the
nitrate receptors that fall within each municipality. The main sta-
tistical measures: the mean, minimum, and maximum concentra-
tions, were computed for each municipality for different years.
Although the nitrate fate and transport in groundwater is not at all
dictated by political boundaries, the main intent from carrying out
this analysis at this scale is to point out areas that might witness
high pollution from nitrate, which in turn indicates ongoing ac-
tivities that might be closely monitored and supervised in a regu-
larized manner.
The mean, minimum, and maximum nitrate concentration val-
ues for the years from 2000 to 2004 were computed 共results are
not presented herein兲. As was inferred from the results, Khan
Younis municipality ranked the first in terms of the mean nitrate
concentration for the years 2000, 2001, 2003, and 2004 and came
in second for the year 2002. Apparently this is an indicator of the
possible existence of anthropogenic sources of nitrate pollution.
Rafah and Jabalia have generally advanced ranked positions indi-
cating high pollution in the GCA under these governorates.
However, a great deal of caution should be considered when
analyzing such results since nitrate occurrence in the groundwater
is a function of many complicated and interrelated fate and trans-
port processes in the unsaturated and the saturated zones as can be
deduced from Fig. 1. For instance, nitrate after leaching from the
soil zone and reaching the aquifer will be advected by the ground-
water flow and will ultimately appear at locations far away from
pollution sources. In other words, on-ground nitrogen sources
might be in one municipality 共or a specific land use class兲and the
detection in groundwater might be in another municipality. Yet,
when considering the issue of steady-state repetitive nitrogen-
based practices, then much of the pollution of groundwater re-
sources can be attributed to on-ground activities. This will depend
largely on travel time through the vadose zone and on the depth to
water table.
Nitrate Distribution in Different Land Use Classes
Further analyses were conducted to assess nitrate contamination
of the GCA for the different land use classes. Many studies in the
literature have investigated the relationship between land use
classes and nitrate concentrations in groundwater 共Ator and Fer-
rari 1997; Tesoriero and Voss 1997; Nolan and Stoner 2000; Al-
masri and Kaluarachchi 2004a兲but none was carried out for the
GCA. GIS spatial and statistical capabilities were utilized in this
analysis where the detailed land use map along with GIS point
shapefile of nitrate concentration wells across the Gaza Strip were
employed. Therefore, GIS was used to spatially join the nitrate
well with the polygon of the land use class using the GIS shape-
files of the well distribution and land use polygons. The spatial
joining using GIS is based on the geographic location of the wells
with reference to the land use polygons. Table 2 summarizes the
main statistics of nitrate concentrations for the different land use
classes. Table 2 provides a good insight regarding the proposed
areas for possible monitoring activities such that the complex
nature of nitrate occurrences in the GCA is better assessed and
subsequently to enhance the evaluation of the potential manage-
ment options for future intervention.
As can be inferred from Table 2, the mean, median, maximum,
and third quartile are all above the MCL for all land use classes.
It is difficult to deduce a conclusive trend in nitrate concentra-
tions, especially when considering that the land use classes are
close to each other with steep groundwater gradients that cause
rapid nitrate migration in the subsurface from one area to another.
However, to facilitate comparison of the different land use classes
in terms of nitrate concentration, the different land use classes
were ranked based on the mean, median, and maximum nitrate
Fig. 11. Contours of nitrate concentration for year 2001 for GCA as
interpolated using Kriging
Fig. 12. Municipalities 共cities兲of Gaza Strip
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concentrations. Apparently, the vegetable land use ranks the high-
est in terms of mean and median concentrations with zero per-
centage of concentrations below the MCL. Urban areas come in
second in terms of median nitrate concentration. This signifies
possible contamination from the cesspits 共disposal of untreated
wastewater兲or possible migration of nitrate from neighboring
areas. Open area and citrus come in the first and second places in
terms of the maximum nitrate concentration, respectively. Green-
house areas have the second highest mean nitrate concentration. It
is worthwhile to mention that the number of samples varies across
all land use classes and therefore caution should be considered
when attempting to analyze the results of Table 2.
Another fact to be mentioned is that in order for this sort of
correlation between well nitrate concentration and land use to be
scientifically sound, the recharge area of the well should signifi-
cantly overlap the overlying land use polygon in the GIS shape-
file. This can happen when having shallow wells or high pumping
rates. For the GCA, the majority of the wells taps shallow depths
共these wells are used in agriculture兲while the deeper wells that
are used for municipal purposes are of significant pumping rates.
Yet, there might be exceptions 共for instance deep wells with in-
significant pumping rates兲.
Vertical Nitrate Distribution in Groundwater
Based on the published literature, the nitrate concentration in
groundwater decreases with increasing sampling depth 共Hallberg
and Keeney 1993; Tesoriero and Voss 1997; Almasri and Kalu-
arachchi 2004a兲. Fig. 13 depicts this relationship for the GCA,
especially when considering the interpolated linear trend line that
appears in the figure. Many observations can be drawn based on
Fig. 13. First, the results compare well with the general trend of
nitrate concentration with the sampling depth reported in many
studies from the literature 共Nolan and Stoner 2000; Parliman
2002; Hanson 2002; Almasri and Kaluarachchi 2004a兲. For the
GCA and based on Fig. 13, no explicit justifications and conclu-
sions can be made with respect to the vertical nitrate profile in
groundwater; nevertheless, this phenomenon can be attributed
mainly to three factors: denitrification, vertical groundwater
movement and the associated nitrate transport, and mixing.
Denitrification of nitrate is an anaerobic process by which bac-
teria convert nitrate to N2and N2O gases. The importance of
denitrification as a major pathway of nitrate removal from aqui-
fers has been reported in many studies 共Frind et al. 1990; Postma
et al. 1991; Korom 1992; Tesoriero and Voss 1997; Tesoriero
et al. 2000兲. The common requirements for denitrification are as
follows 共Korom 1992兲: the presence of an electron acceptor
which in this case is nitrate, the presence of a microbial popula-
tion that possess the metabolic capacity, the presence of suitable
electron donors, and the presence of anaerobic conditions or re-
stricted oxygen availability. The main limiting condition from
these four conditions is the presence of dissolved oxygen, which
is preferred over nitrate due to the high redox potential. Dissolved
oxygen diffuses about 10,000 times more slowly through water
than through air 共Addiscott et al. 1992兲. As such, it is common to
observe higher dissolved oxygen content in shallow depths than at
deeper depths.
The second factor affecting nitrate variability with depth is the
vertical groundwater movement, which is influenced mainly by
water pumping from the deeper aquifers. However, the majority
of the wells in the GCA are extracting water from the upper layer
共with an average thickness of less than 30 m兲. The third possible
factor that can affect the nitrate variability with depth is the mix-
ing of water of high nitrate concentrations when it enters deep
Table 2. Mean, Median, Minimum, Maximum, First and Third Quartile of Nitrate Concentrations 共mg/L NO3–N兲for Different Land Use Classes for Year
1990 and Period from 2000 to 2004 along with Land Use Ranking Based on Nitrate Concentrations for Different Statistical Measures, Percentage of
Concentrations below MCL, Total Number of Nitrate Concentration Samples
Land use
Ranking based on Statistical measures Quartile
Percent ⬍MCL CountMean Med Max Mean Min Max Med 1st 3rd
Citrus 9 9 2 18.73 0.45 182.68 14.23 10.39 20.77 23.59 532
Dates 11 11 8 15.05 7.90 79.71 11.74 9.94 13.55 25.89 33
Field crops 8 8 3 21.23 2.94 130.29 14.68 9.48 26.70 28.29 412
Fruits 6 6 10 24.19 4.74 50.35 24.39 15.47 31.50 13.11 47
Grapes 10 10 11 16.26 7.45 36.58 12.19 9.15 19.65 33.81 7
Greenhouses 2 3 6 37.70 0.68 98.23 29.58 16.82 53.85 6.56 99
Horticulture 5 5 7 29.57 1.13 97.55 24.61 14.23 39.06 10.05 201
Olives 7 7 9 23.00 9.26 66.16 18.29 13.32 24.39 8.48 49
Open area 4 4 1 33.02 0.90 236.87 29.58 19.87 43.07 10.00 474
Urban 3 2 5 34.77 1.13 118.55 31.61 19.19 47.42 10.34 457
Vegetables 1 1 4 41.22 10.61 119.68 37.03 21.90 44.71 0 77
Note: Med=median.
Fig. 13. Variability of nitrate concentration with sampling depth for
GCA
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groundwater. To better assess the variability of NO3with depth,
boxplots of nitrate concentrations with depth were prepared as
depicted in Fig. 14. It can be concluded from Fig. 14 that high
nitrate concentrations in terms of median values are within the
upper 60 m of groundwater in the GCA. After this depth, median
nitrate concentrations decrease with depth.
Management of Nitrate Contamination of GCA
The elevated nitrate concentrations in the GCA can be attributed
to a variety of practices including mainly the excessive use of
nitrogen-based fertilizers and the disposal of untreated wastewater
in an unsupervised manner. Management options related to fertil-
izer loading entail, for instance, the reduction in loading through
setting up realistic crop yield goals. As a management tool to
predict the impacts of different management alternatives, a suit-
able nitrate fate and transport model needs to be developed to
assist in the management and decision-making processes.
There are two broad types of models that can be developed for
the GCA; one is a high resolution distributed model and the other
is a lumped parameter model. The distributed model is more
applicable when there is a drastic variability in the on-ground
activities that lead to nitrate contamination of groundwater and
when there is a noticeable spatial two-dimensional 共2D兲and ver-
tical variability in the nitrate concentrations in groundwater. In
addition, the distributed models can provide the time series of the
nitrate concentration at specific locations. This very capability is
of great importance when there is an interest in figuring out the
aquifer response at different locations in terms of nitrate concen-
trations for the different management options introduced at spe-
cific areas. Once a broad range of alternatives and the correspond-
ing impacts on groundwater quality are identified, the best
alternative out of the proposed set of alternatives can be imple-
mented through discussion between regulators and stakeholders.
However, such models are highly demanding in terms of data
requirements. This limitation can be overcome through the devel-
opment of local scale models for areas of interest.
The advantage of local-scale models is that more accurate in-
formation related to the nitrogen transformation potential in the
unsaturated zone, mass loading of nitrogen to groundwater, travel
time from ground surface to the water table, and the fate and
transport of nitrate in groundwater can be integrated within these
models. In addition, this modeling approach can provide informa-
tion related to the relative degree of importance of various input
parameters such that subsequent data gathering can be more
focused.
As for lumped parameter models, they are suitable as screen-
ing tools for preliminary assessment of various management al-
ternatives at the municipality level. Lumped parameter models do
not require much data and allow the modeler to aggregate the
stresses into one or a few cells. These models provide an assess-
ment of the general trends in nitrate occurrences with time. How-
ever, many limitations are associated with the use of lumped
parameter models including the inability to represent the correct
nitrate mass lost from the aquifer when having considerable vari-
ability in the spatial and vertical nitrate concentrations. The use of
lumped parameter models can be largely influenced by shallow
groundwater depths or short travel times between municipalities.
In addition, the assumption of complete mixing is essential and
must be persuasively valid before applying such models.
Summary
As mentioned earlier, the main intent from analyzing the occur-
rences of nitrate in the GCA at different levels was to explore the
severity of the problem of nitrate contamination of the GCA.
Elevated nitrate concentrations in the GCA are of increasing con-
cern for the residents of the Gaza Strip, Palestine. Agricultural
practices involving the use of nitrogen-based fertilizers have been
identified as the main sources of nitrate contamination of ground-
water in the Gaza Strip along with the unsupervised cesspits. The
GCA and the overlying soil are composed mainly of sands, which
indeed promote the vulnerability of the GCA to contamination
through the high potential of nitrate leaching to groundwater. His-
torical nitrate concentration data were obtained from the PWA and
later analyzed. The first quartile of nitrate concentration for the
years 1990 and 2000–2004 exceeds the MCL. The analyses dem-
onstrated a general increase in groundwater nitrate concentration.
The areas with the most elevated nitrate concentrations are areas
characterized by heavy agricultural activities. Elevated nitrate
concentrations in GCA indicate manmade contamination sources.
The main limitation of this work is that the analysis conducted
to evaluate nitrate occurrences in the study area was not limited to
the same well locations across all years. Although, from a theo-
retical point of view, the same wells are desirable to avoid any
bias, yet practically this is not possible because groundwater qual-
ity monitoring in the study area does not necessarily follow a
well-developed plan. On the other hand, elimination of valuable
concentration data to have the same set of monitoring locations in
the analysis is a step backwards as the uncertainty of predictions
and conclusions decreases with an increase in the data pool. Since
the main objective of this paper is to provide a preliminary analy-
sis regarding the nitrate contamination of the GCA, a future work
that utilizes profound statistical analyses is recommended.
Acknowledgments
This work was financially supported, in part, by UNESCO under
Grant No. 513RAB2041 and the Water and Environmental Stud-
ies Institute at An-Najah National University, Nablus, Palestine.
Data were obtained from the database of the Palestinian Water
Authority, Gaza, Palestine.
Fig. 14. Boxplots of nitrate concentration distribution with sampling
depth for GCA
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References
Addiscott, T. M., Whitmore, A. P., and Powlson, D. S. 共1992兲.Farming,
fertilizers and the nitrate problem, CAB International, Wallingford,
U.K.
Almasri, M. N. 共2003兲. “Optimal management of nitrate contamination of
ground water.” Ph.D. dissertation, Utah State Univ., Logan, Utah.
Almasri, M. N., Ghabayen, S., Kaluarachchi, J. J., Jarrar, A., Jayyousi,
A., and McKee, M. 共2005兲. “A conceptual framework for managing
nitrate contamination of the Gaza coastal aquifer, Palestine.” Proc.,
ASCE-EWRI Conf., ASCE, Reston, Va.
Almasri, M. N., and Kaluarachchi, J. J. 共2004a兲. “Assessment and man-
agement of long-term nitrate pollution of ground water in agriculture-
dominated watersheds.” J. Hydrol., 295, 225–245.
Almasri, M. N., and Kaluarachchi, J. J. 共2004b兲. “Implications of on-
ground nitrogen loading and soil transformations on ground water
quality management.” J. Am. Water Resour. Assoc.,40共1兲, 165–186.
Almasri, M. N., and Kaluarachchi, J. J. 共2005a兲. “Modular neural net-
works to predict the nitrate distribution in ground water using the
on-ground nitrogen loading and recharge data.” Environ. Modell. Soft-
ware, 20, 851–871.
Almasri, M. N., and Kaluarachchi, J. J. 共2005b兲. “Multi-criteria decision
analysis for the optimal management of nitrate contamination of aqui-
fers.” J. Environ. Manage., 74, 365–381.
Arnade, L. J. 共1999兲. “Seasonal correlation of well contamination and
septic tank distance.” Ground Water,37共6兲, 920–923.
Ator, S. W., and Ferrari, M. J. 共1997兲. “Nitrate and selected pesticides in
ground water of the Mid-Atlantic region.” Water-Resources Investiga-
tion Rep. No. 97-4139, US Geological Survey, Tacoma, Wash.
Cantor, L., and Knox, R. C. 共1984兲. “Evaluation of septic tank effects on
ground-water quality.” EPA-600/2-284-107, U.S. Environmental Pro-
tection Agency, Washington, D.C.
Cox, S. E., and Kahle, S. C. 共1999兲. “Hydrogeology, ground-water qual-
ity, and sources of nitrate in lowland glacial aquifer of Whatcom
County, Washington, and British Columbia, Canada.” Water Re-
sources Investigation Rep. No. 98-4195, U.S. Geological Survey,
Tacoma, Wash.
Delgado, J. A., and Shaffer, M. J. 共2002兲. “Essentials of a national nitrate
leaching index assessment tool.” Avtometriya, 57, 327–335.
Environmental Systems Research Institute, Inc. 共ESRI兲.共1999兲.ArcView.
Erickson, D. 共1992兲. “Ground water quality assessment, Whatcom
County Dairy Lagoon #2, Lynden, Washington.” Washington State
Department of Ecology, Open-File Rep., Wash.
Frind, E., Duynisveld, W., Strebel, O., and Boettcher, J. 共1990兲. “Model-
ing of multicomponent transport with microbial transformation in
ground water: The Fuhrberg case.” Water Resour. Res.,26共8兲, 1707–
1719.
Ghabayen, S. M. 共2004兲. “A probabilistic expert systems approach for
analysis and optimization of a large-scale water resources system.”
Ph.D. dissertation, Logan, Utah.
Ghabayen, S. M., McKee, M., and Kemblowski, M. 共2006兲. “Ionic and
isotopic ratios for identification of salinity sources and missing data in
the Gaza aquifer.” J. Hydrol., 318, 360–373.
Hall, M. D., Shaffer, M. J., Waskom, R. M., and Delgado, J. A. 共2001兲.
“Regional nitrate leaching variability: What makes a difference in
northeastern Colorado.” J. Am. Water Resour. Assoc.,37共1兲, 139–408.
Hallberg, G. R., and Keeney, D. R. 共1993兲. “Nitrate.” Regional ground-
water quality, W. M. Alley, ed., U.S. Geological Survey, Van Nos-
trand Reinhold, New York, 297–321.
Hanson, C. R. 共2002兲. “Nitrate concentrations in Canterbury
groundwater—A review of existing data.” Rep. No. R02-17, Environ-
ment Canterbury, 具http://www.ecan.govt.nz/Plans-Reports/water/R02-
17.pdf典.
Hubbard, R. K., and Sheridan, J. M. 共1994兲.Contamination of ground
waters, D. C. Adriano, A. K. Iskandar, and I. P. Murarka, eds., Sci-
ence Reviews, Northwood.
Keeney, D. R. 共1986兲. “Sources of nitrate to ground water.” Crit Rev.
Environ. Control, 16, 257–303.
Korom, S. 共1992兲. “Natural denitrification in the saturated zone: A re-
view.” Water Resour. Res.,28共6兲, 1657–1668.
Lake, I. R., et al. 共2003兲. “Evaluating factors influencing groundwater
vulnerability to nitrate pollution: Developing the potential of GIS.” J.
Environ. Manage.,68共3兲, 315–328.
MacQuarrie, K. T. B., Sudicky, E., and Robertson, W. D. 共2001兲. “Nu-
merical simulation of a fine-grained denitrification layer for removing
septic system nitrate from shallow ground water.” J. Hydrol., 52,
29–55.
Madison, R. J., and Brunett, J. O. 共1985兲. “Overview of the occurrence of
nitrate in ground water of the United States.” National water summary
1984, U.S. Geological Survey Water-Supply Paper 2275, USGS,
Tacoma, Wash.
Metcalf and Eddy. 共2000兲. “Coastal aquifer management program
共CAMP兲: Final model report.” Rep., USAID and PWA, Gaza,
Palestine.
Nolan, B. T., Hitt, K., and Ruddy, B. 共2002兲. “Probability of nitrate con-
tamination of recently recharged ground waters in the conterminous
United States.” Environ. Sci. Technol.,36共10兲, 2138–2145.
Nolan, B. T., and Stoner, J. D. 共2000兲. “Nutrients in ground waters of the
conterminous United States, 1992–1995.” Environ. Sci. Technol.,
34共7兲, 1156–1165.
Palestinian Water Authority 共PWA兲.共2004兲.GIS database.
Parliman, D. J. 共2002兲. “Analysis of nitrate 共NO3-N兲concentration trends
in 25 ground-water-quality management areas, Idaho, 1961–2001.”
Water-Resources Investigation Rep. No. 02-4056, U.S. Geological
Survey, Tacoma, Wash.
Postma, D., Boesen, C., Kristiansen, H., and Larsen, F. 共1991兲. “Nitrate
reduction in an unconfined sandy aquifer. Water chemistry, reduction
processes, and geochemical modeling.” Water Resour. Res.,27共8兲,
2027–2045.
Schilling, K. E., and Wolter, C. F. 共2001兲. “Contribution of base flow to
nonpoint source pollution loads in an agricultural watershed.” Ground
Water,39共1兲, 49–58.
Shrestha, R. K., and Ladha, J. K. 共2002兲. “Nitrate pollution in groundwa-
ter and strategies to reduce pollution.” Water Sci. Technol.,45共9兲,
29–35.
Tesoriero, A. J., Liecscher, H., and Cox, S. 共2000兲. “Mechanism and rate
of denitrification in an agricultural watershed: Electron and mass bal-
ance along ground water flow paths.” Water Resour. Res.,36共6兲,
1545–1559.
Tesoriero, A. J., and Voss, F. D. 共1997兲. “Predicting the probability of
elevated nitrate concentrations in the Puget Sound Basin. Implications
for aquifer susceptibility and vulnerability.” Ground Water,35共6兲,
1029–1039.
140 / JOURNAL OF HYDROLOGIC ENGINEERING © ASCE / MARCH 2008
J. Hydrol. Eng. 2008.13:132-140.
Downloaded from ascelibrary.org by UTAH STATE UNIVERSITY on 11/08/13. Copyright ASCE. For personal use only; all rights reserved.
