Evaluation of the Groundwater Quality Using the Water Quality Index and Geostatistical Analysis in the Dier al-Balah Governorate, Gaza Strip ...

water
Article
Evaluation of the Groundwater Quality Using the
Water Quality Index and Geostatistical Analysis in
the Dier al-Balah Governorate, Gaza Strip, Palestine
Moustafa El Baba 1, *, Prabin Kayastha 1,2 , Marijke Huysmans 1 and Florimond De Smedt 1
 1 Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels,
 Belgium; prabinkayastha@yahoo.com (P.K.); Marijke.Huysmans@vub.be (M.H.); fdesmedt@vub.be (F.D.S.)
 2 Shellharbour City Council, Shellharbour, NSW 2529, Australia
 * Correspondence: melbaba@vub.ac.be; Tel.: +32-262-935-47
 



 Received: 13 December 2019; Accepted: 14 January 2020; Published: 16 January 2020 


 Abstract: Groundwater contamination is a major problem in the Gaza Strip. In this study we
 investigate the groundwater quality in the Dier al-Balah Governorate. Water samples were collected
 from 19 municipal wells in April 2009 and April 2014 and analyzed for physio-chemical parameters
 (pH, TDS, Ca2+ , Mg2+ , Na+ , K+ , Cl− , SO4 2– , HCO3 − and NO3 − ). The aim of the research is to
 determine the groundwater quality and to produce groundwater quality maps using the water
 quality index (WQI) method and geostatistical analysis. The results show that all water samples
 are very saline due to the intrusion of Mediterranean seawater in the coastal aquifer. Differences
 in chemical composition between 2009 and 2014 indicate that about 1% more seawater was mixed
 with the groundwater in this period. The majority of the observed chemical parameters of all wells
 are well above the WHO water quality standards and all WQI values indicate that the water quality
 is problematic. The spatial variation of the WQI scores is modelled by a deterministic component
 expressing a linear dependence on the distance to the coastline and a stochastic residual described
 by an exponential variogram with a practical range of 3000 m. The mapping of the WQI scores and
 derived water quality classes is achieved through regression-kriging. The results indicate that the
 groundwater in a large area along the coastline is unsuitable for human consumption and comparison
 of the maps of 2009 and 2014 shows that this region further expanded by about 700 m inland in
 a period of 5 years. The results of this study are worrying, but they also contribute to a better
 understanding of the factors that determine the groundwater quality and can help authorities and
 stakeholders with sustainable development.

 Keywords: groundwater quality; water quality index (WQI); regression-kriging; seawater intrusion;
 Gaza coastal aquifer; Palestine

1. Introduction
 Groundwater is an important source of fresh water for human consumption, irrigation and
industrial use in many countries of the world. However, residential, industrial, commercial, agricultural
and other anthropogenic activities together with natural conditions often lead to a deterioration in
groundwater quality [1,2]. That is why an assessment of the quality of groundwater is of great
importance for society. Water quality assessment includes an evaluation of the physical, biological and
chemical properties of water in relation to the natural quality, intended use and human effects that can
influence the health of aquatic systems [3].
 More than 90% of the population in the Gaza Strip is dependent on the municipal drinking
water network, while the remaining 10% of the population rural areas is dependent on private

Water 2020, 12, 262; doi:10.3390/w12010262 www.mdpi.com/journal/water

Water 2020, 12, 262 2 of 14

sources [4]. The quality of groundwater in the Gaza Strip is influenced by many processes, including
return flow from irrigation, wastewater leakage, upconing of underground brine water and sea water
intrusion [5,6]. Shomar [4] found that only 10% of the municipal wells meet WHO drinking water
standards; in particular the chloride, nitrate and fluoride concentrations are 2–9 times higher than
WHO standards. Almasri and Ghabayen [7] reported that a large portion of nitrate concentrations
observed in wells in the Gaza Strip did not meet the US Environmental Protection Agency drinking
water standard for the years 1990 and 2000–2004. Chemical analysis of municipal wells conducted
in 2009 by Aish [8] showed that total dissolve solids, chloride and sodium values exceeded WHO
standards. Abbas et al. [9] sampled 58 municipal wells in 2010 and found that no groundwater in
the Gaza Strip meets all WHO drinking water standards. Alastal et al. [10] derived groundwater
quality maps for the Gaza Strip using six water quality parameters (chloride, nitrate, sulfate, calcium,
magnesium, and alkalinity) and found that the fraction for which the groundwater quality is not good
increased from 30% to 55% between 2000 and 2010. The Palestinian Water Authority [11] reported that
only 12.4% of the wells comply with the WHO standard for nitrate and only 19.3% with the WHO
standard for chloride. Abu-alnaeem et al. [12] reported that around 90% of all wells in the Gaza Strip
are polluted by nitrate, mainly due to wastewater inputs.
 To assess the suitability of groundwater for human consumption, it is essential to determine
and evaluate its quality. Researchers have used different methods to express water resources
quality. Traditionally, water engineering professionals compare individual chemical parameters
with recommended allowable limits. In many regions with scarce water resource, however, the use of
water at concentrations slightly above these limits is generally not harmful. Horton [13] proposed a
water quality index (WQI) to describe the suitability water for human consumption in a single score
that can be ranked into categories using terms such as excellent, good, poor, very poor and unsuitable
for use, which are easy to understand for decision makers and consumers. Various methods have
been proposed to derive WQI scores [14]. A weighted WQI score is usually used in which ratios of
concentrations of water quality parameters and their recommended standard values are weighted and
combined in a single number. Recent applications of the weighted WQI approach in groundwater
quality studies have been presented [10,15–18]. All methods used to derive WQI scores are similar, the
only difference being the number of parameters (observations) used and their corresponding weights.
 The purpose of this study was: (1) to assess the groundwater quality in the Dier al-Balah
Governorate of the Gaza Strip using groundwater samples taken from municipal wells in 2009 and
2014, (2) to evaluate the suitability of the groundwater for human consumption using the WQI method,
(3) map the spatial distribution of the groundwater quality, and (4) evaluating the evolution of the
groundwater quality for the 2009–2014 period.

2. Materials and Methods

2.1. Study Area
 The Dier al-Balah Governorate is located in the center of the Gaza Strip (Figure 1a). The governorate
is about 10 km long and 5.5 km wide, with a total land area of 55.2 km2 and covers 15% of the Gaza Strip.
Located in a coastal zone, transitional between the temperate Mediterranean climate and arid climate
of the Negev and Sinai deserts, the Gaza Strip experiences a semi-arid climate with two well-defined
seasons: a wet season from October to April and a dry season from May to September. The average
daily temperature ranges from 27 ◦ C in summer to 13 ◦ C in winter and the average annual rainfall is
about 335 mm/y [19]. In 2017 around 273,200 people lived in the Dier al-Balah Governorate resulting
in a population density of 4949 persons per km2 . In recent decades, the demand for water for domestic
purposes has increased noticeably as a result of the high population growth.

Water 2020, 12, x FOR PEER REVIEW 3 of 14

 the Dier al-Balah Governorate belongs to Pliocene-Pleistocene age and consists of Kurkar Group
 deposits of calcareous sandstone, silt, clay, unconsolidated sands and conglomerates [21]. The
 aquifer
Water 2020,is12,the
 262only natural water resource and is used for various purposes, such as drinking water,
 3 of 14
 crop irrigation and industrial uses [10].

 (a) (b)
 Figure1.1.Map
 Figure Mapofofthe
 theGaza
 GazaStrip
 Stripwith
 withindication
 indicationofofthe
 theDier
 Dieral-Balah
 al-BalahGovernorate
 Governorate(a);(a);map
 mapofofthe
 theDier
 Dier
 al-BalahGovernorate
 al-Balah Governorate(study
 (studyarea)
 area)with
 withthe
 thelocation
 locationofofthe
 themunicipal
 municipalwells
 wellsused
 usedininthis
 thisstudy
 study(b).
 (b).

 2.2. Data Collection
 The Dier andGovernorate
 al-Balah Procedures is generally flat with an average topographic elevation of about
45 m above
 In Aprilthe2009
 mean seaApril
 and level.2014,
 The water
 soil type is mainly
 samples sandy
 were loessfrom
 collected or loessal sand in addition
 19 municipal wells in tothesome
 Dier
sandy regosols along the coast [20]. Land use is dominated by agricultural land, urban
 al-Balah Governorate (Figure 1b) by the first author on behalf of the Coastal Municipalities Water and built-up
areas, natural
 Utility, reserves
 responsible forand
 the recreational
 production of areas in thewater.
 drinking coastalThe
 part [20]. of
 depth Thethecoastal aquiferfrom
 wells varies in the60Dier
 m to
al-Balah Governorate belongs to Pliocene-Pleistocene age and consists of Kurkar
 90 m. Groundwater quality parameters were analyzed using standard procedures and suggested Group deposits of
calcareous sandstone, silt, clay, unconsolidated sands and conglomerates
 precautions were taken to prevent contamination [22]. During the groundwater sampling,[21]. The aquifer is the only
natural water resource
 temperature, pH andand is used conductivity
 electrical for various purposes, suchmeasured
 (EC) were as drinking in water, crop irrigation
 situ according and
 to WHO
industrial uses [10].
 guidelines [3,23]. Total dissolved solids (TDS) was derived from EC using a calibrated linear
 relationship. Concentrations of major cations (Ca2+, Mg2+, Na+ and K+) and anions (HCO3–, SO42–, Cl–
2.2. Data Collection and Procedures
 and NO3–) were determined in the laboratory of the Coastal Municipalities Water Utility according to
 In April
 standard 2009 and
 methods April 2014,
 prescribed water
 by the samplesPublic
 American were Health
 collected from 19 municipal
 Association wells inassurance
 [22]. For quality the Dier
al-Balah Governorate (Figure 1b) by the first author on behalf of the Coastal
 and quality control, duplicate tests were performed throughout the laboratory analyses. Municipalities Water Utility,
responsible for the production
 An indication of drinking
 of the accuracy water.analysis
 of the water The depth canofbethe wells varies
 obtained usingfrom 60 m to 90 m.
 the charge-balance
Groundwater
 equation based quality
 on theparameters were analyzed
 electroneutrality condition.usingThestandard
 deviation procedures and suggested
 from equality precautions
 is expressed as:
were taken to prevent contamination [22]. During the groundwater sampling, temperature, pH and
 ∑cations ∑anions
electrical conductivity (EC) were measured = in situ according to WHO 100%guidelines [3,23]. Total dissolved (1)
 ∑cations ∑anions
solids (TDS) was derived from EC using a calibrated linear relationship. Concentrations of major
cations is
 where (Ca 2+the 2+ , Na+ and K+error,
 , Mgcharge-balance ) and and
 anions ∑cations
 (HCO3 −and, SO∑anions
 2– − are the
 4 , Cl and
 −
 NOsums of cations
 3 ) were and anions,
 determined in the
 respectively, expressed in equivalents per liter. The calculated charge-balance
laboratory of the Coastal Municipalities Water Utility according to standard methods prescribed by theerror must be within
 an acceptable
American Public limit of ±10%
 Health [24]. The
 Association [22].major cation assurance
 For quality and anionand compositions of the
 quality control, groundwater
 duplicate tests
 samples are presented in a piper diagram
were performed throughout the laboratory analyses. [25], with which hydrogeochemical facies can be
 categorized and trends in the data can be detected.
 An indication of the accuracy of the water analysis can be obtained using the charge-balance
equation based on the electroneutrality condition. The deviation from equality is expressed as:
 2.3. Water Quality Index P P
 cations − anions
 The derivation of WQI involves E = weight assignment
 P P × 100%
 for each parameter, normalization of (1) the
 cations + anions
 weights, standardization of the parameters, calculation of individual WQI scores and aggregation of
 the scores. Weights for the parameters
 error, and (pH, TDS,andCa2+, Mg 2+, Na+, K+, HCO3–, SO42–, Cl– and NO3–)
 P P
where E is the charge-balance cations anions are the sums of cations and anions,
 given in Table
respectively, 1 were in
 expressed adapted from per
 equivalents previous studies
 liter. The [10,16].charge-balance
 calculated The weights values rangebefrom
 error must oneanto
 within
 five basedlimit
acceptable on their
 of ±10%importance
 [24]. The formajorwater
 cation quality assessment.
 and anion Total dissolved
 compositions solids and
 of the groundwater nitrate
 samples
are presented in a piper diagram [25], with which hydrogeochemical facies can be categorized and
trends in the data can be detected.

Water 2020, 12, 262 4 of 14

2.3. Water Quality Index
 The derivation of WQI involves weight assignment for each parameter, normalization of the
weights, standardization of the parameters, calculation of individual WQI scores and aggregation of
the scores. Weights for the parameters (pH, TDS, Ca2+ , Mg2+ , Na+ , K+ , HCO3 − , SO4 2– , Cl− and NO3 − )
given in Table 1 were adapted from previous studies [10,16]. The weights values range from one to five
based on their importance for water quality assessment. Total dissolved solids and nitrate concentration
are given the maximum weight of five because these are important indicators for assessment of the
overall water quality, while potassium is given the minimum weight of one because it poses little risk
to consumer health. Other chemical parameters are assigned a weight between one and five depending
on their importance in determining the water quality. A factor of three is assigned to pH because of the
indication of alkalinity and effect on hardness and to sodium, chloride and sulfate because of their
indication of salinity and effect on taste. Calcium, magnesium and bicarbonate are given a weight of
two because of their effect on hardness.

 Table 1. List of physico-chemical parameters with corresponding unit, WHO standard (Si ), WQI
 weight (Wi ), and normalized weight (wi ).

 Standard Weight Relative Weight
 Chemical Parameter Unit
 Si Wi wi
 pH - 6.5–8.5 3 0.103
 TDS mg/L 500 5 0.172
 Ca2+ mg/L 75 2 0.069
 Mg2+ mg/L 50 2 0.069
 Na+ mg/L 200 3 0.103
 K+ mg/L 12 1 0.034
 HCO3 − mg/L 120 2 0.069
 SO4 2– mg/L 250 3 0.103
 Cl− mg/L 250 3 0.103
 NO3 − mg/L 45 5 0.172
 Total 29 1.000

 The normalized weight of each parameter is obtained as:
 Xn
 wi = Wi / Wi (2)
 i=1

where wi is the normalized weight for parameter i, Wi is the assigned weight for parameter i, and n is
the total number of parameters. Water quality observations are then standardized by dividing the
values by their corresponding water quality standard:

 qi = Ci /Si (3)

where qi is the partial WQI score for parameter i, Ci is the observed concentration for parameter i
(pH–7 for acidity), and Si is the water quality standard for parameter i. For the water quality standards,
we use the WHO 2011 [26] guidelines for drinking-water, as shown in Table 1. The overall WQI score
is obtained by summation of the scores of each parameter multiplied by their normalized weight:
 Xn
 WQI = wi qi (4)
 i=1

 A WQI value less than one indicates that the water can be used without any precaution, while higher
values indicate poorer water quality. WQI scores make it possible to classify the suitability of water for
human consumption into categories such as excellent, good, poor, very poor and unsuitable for use as
shown in Table 2 [9,14,15]. Our method for deriving WQI scores does not differ from what is in the

Water 2020, 12, 262 5 of 14

literature, the only minor difference is that we have not multiplied the values by one hundred as is
traditionally done, but that actually serves no purpose.

 Table 2. Classification of the water quality according to the WQI score.

 WQI Water Quality
 Range Class
 3 Unsuitable

2.4. Geostatistical Data Analysis
 Mapping of the WQI estimates is achieved by geostatistical analysis in which an empirical
variogram is derived, fitted by a variogram model, cross-validation of the model variogram and
regression-kriging using the gstat library in R [27,28]. The spatial variation of WQI is modeled as:

 WQI(x) = m(x) + (x) (5)

where x is the location vector, m(x) is the deterministic component of the water quality index and (x)
is the stochastic residual. The empirical variogram of the stochastic residual is estimated based on the
observations as
 1 X h  i2
 γ(h) = (xi ) −  x j (6)
 2N (h)
 (i,j)∈N (h)

where γ is the variogram or semi-variance, h is the lag distance and N (h) is the number of observed
pairs within the lag distance interval. The empirical variogram is fitted by an exponential model:

 γ(h) = n + (s − n)[1 − exp(−3h/r)] (7)

where n is the nugget, s is the sill and r is the practical range. The variogram model is verified by
cross-validation whereby the data points are removed one by one and predicted by regression-kriging
using the remaining data. Finally, maps of WQI are obtained by spatial interpolation using
regression-kriging
 Xp XN ( x )
 WQI(x) = βk qk (x) + λi (xi ) (8)
 k =1 i=1

where βk are optimized deterministic model coefficients, qk (x) are external drift components, p is the
number of external drift components, λi are optimized kriging weights and N (x) is the number of data
points selected within the neighborhood of x.

3. Results and Discussion

3.1. Hydro-Chemical Characterization
 The results of in the in-situ tests and laboratory analyzes of the water samples from the 19 municipal
wells in the Dier al-Balah Governorate in 2009 and 2014 are shown in Table 3; Table 4, respectively.
These tables also provide the average and standard deviation for each parameter. The second-to-last
column of Tables 3 and 4 shows the charge-balance error obtained with Equation (1). All charge-balance
errors are within an acceptable limit of ±10%, except for the sample from well W11 in 2014, which is
just above the limit. This small might be due to some ions missing in the analysis, such as for example
organic acids that may be present due to contamination by industrial or household waste.

Water 2020, 12, 262 6 of 14

 Table 3. Physio-chemical analysis of the groundwater samples taken in 2009; also given are the
 charge-balance error E, the WQI score, the water quality classification, and the mean and standard
 deviation (SD).

 Well TDS Ca2+ Mg2+ Na+ K+ HCO3 − SO4 2– Cl− NO3 − E WQI Water Quality
 pH
 ID mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L % Score Class
 W1 7.40 3241 190 105 670 5.7 273 265 1126 139 3.76 3.15 Unsuitable
 W2 7.10 2737 161 103 480 7.9 574 267 920 200 −7.97 3.18 Unsuitable
 W3 7.30 2912 182 132 524 8.1 421 252 987 191 −0.14 3.22 Unsuitable
 W4 7.60 3493 226 125 640 14.5 323 204 1269 183 1.49 3.54 Unsuitable
 W5 7.10 3108 160 141 600 7.5 268 380 1140 147 −0.99 3.18 Unsuitable
 W6 7.60 2877 131 86 775 5.5 231 272 1028 54 9.34 2.62 Very poor
 W7 7.00 2779 174 128 620 5.1 286 241 973 113 8.64 2.82 Very poor
 W8 7.10 2597 160 139 660 9.1 370 511 821 132 7.04 2.96 Very poor
 W9 7.90 1953 86 57 480 4.0 233 204 662 38 4.54 1.82 Poor
 W10 7.80 2198 111 71 520 4.2 246 209 759 62 5.11 2.11 Very poor
 W11 8.00 715 62 31 130 1.2 201 60 172 50 5.43 0.92 Good
 W12 7.60 1932 112 58 460 11.1 323 186 655 99 2.33 2.12 Very poor
 W13 7.50 2114 80 35 440 2.6 266 186 717 61 −6.02 1.94 Poor
 W14 7.30 1631 84 38 310 2.8 360 65 552 42 −5.96 1.57 Poor
 W15 7.60 2002 74 53 400 4.1 254 227 632 43 −3.53 1.81 Poor
 W16 7.20 3598 165 123 780 17.4 427 511 1160 190 −0.64 3.77 Unsuitable
 W17 7.50 2100 138 73 360 6.7 248 128 681 102 2.05 2.12 Very poor
 W18 7.50 2233 121 60 455 5.1 273 156 681 120 3.41 2.27 Very poor
 W19 7.50 2436 150 97 370 7.7 278 407 698 120 –4.37 2.49 Very poor
 Mean 7.45 2456 135 87 509 6.9 308 249 823 110 1.24 2.51
 SD 0.28 700 45 37 163 4.0 90 126 265 55 5.08 0.75

 Table 4. Physio-chemical analysis of the groundwater samples taken in 2014; also given are the
 charge-balance error E, the WQI score, the water quality classification, and the mean and standard
 deviation (SD).

 Well TDS Ca2+ Mg2+ Na+ K+ HCO3 − SO4 2– Cl− NO3 − E WQI Water Quality
 pH
 ID mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L % Score Class
 W1 7.95 3409 207 117 760 6.0 328 312 1279 144 2.80 3.43 Unsuitable
 W2 7.76 2912 176 116 560 6.3 598 331 1032 211 −6.91 3.44 Unsuitable
 W3 7.50 3493 198 147 660 6.8 578 353 1179 236 −2.89 3.91 Unsuitable
 W4 7.65 3514 243 168 760 15.2 397 273 1389 233 3.73 4.01 Unsuitable
 W5 7.54 3395 179 162 740 7.7 281 413 1272 171 2.64 3.57 Unsuitable
 W6 7.71 3031 155 98 863 5.6 271 329 1259 72 5.44 2.97 Very poor
 W7 7.53 2968 185 137 674 5.7 313 273 1124 122 5.80 3.06 Unsuitable
 W8 8.16 3003 189 146 720 5.4 409 535 1022 169 3.43 3.42 Unsuitable
 W9 7.77 1862 96 59 509 4.2 246 241 708 47 3.43 1.90 Poor
 W10 7.51 2359 132 86 634 5.7 323 277 853 79 6.42 2.45 Very poor
 W11 7.66 774.2 64 44 164 1.4 216 71 191 62 10.16 1.04 Poor
 W12 7.61 2170 136 74 503 6.1 382 262 794 118 −1.56 2.45 Very poor
 W13 8.20 2464 98 53 523 3.7 304 218 893 83 −5.80 2.35 Very poor
 W14 8.10 1729 97 58 398 3.7 394 103 623 52 0.01 1.81 Poor
 W15 7.09 2366 91 67 530 4.5 360 277 777 55 −1.84 2.22 Very poor
 W16 7.90 3906 169 136 860 20.0 456 554 1326 204 −1.84 4.11 Unsuitable
 W17 8.00 2954 153 92 461 7.5 293 154 998 126 −3.72 2.77 Very poor
 W18 8.10 2975 133 83 630 6.1 311 182 977 133 3.06 2.87 Very poor
 W19 7.68 2618 169 106 503 6.8 311 442 872 132 –2.26 2.81 Very poor
 Mean 7.80 2732 151 103 603 6.8 356 295 977 129 1.06 2.87
 SD 0.30 749 47 39 170 4.2 101 129 293 62 4.51 0.81

 Tables 3 and 4 indicate that the ionic dominance pattern is of the order Na+ > Ca2+ > Mg2+ > K+ for
the cations and Cl− > HCO3 − > SO4 2– > NO3 − for the anions, both in 2009 and 2014. Figure 2 shows the
major ion composition in a piper plot. All water quality samples are clustered in the sodium-chloride
category (Na+ + K+ > 50%, Cl− > 50%), from which we can conclude that the groundwater is very
brackish. Also shown in Figure 2 is the theoretical mixing line between fresh groundwater (100%
Ca2+ + Mg2+ , 100% HCO3 − ) and Eastern Mediterranean seawater (78% Na+ , 100% Cl− + SO4 2– ) [29].

Water 2020, 12, 262 7 of 14

All groundwater samples are clustered around this line, which suggest that the groundwater quality is
Water 2020, 12, x FOR PEER REVIEW 8 of 14
likely to be influenced by mixing with seawater.

 Data 2009

 Ca
 80
 80
 4)

 lc
 O

 ium
 (S
 Data 2014

 te

 (C
 lfa

 a)
 Su

 60
 60

 +M
 Seawater mixing

 l) +

 ag
 (C

 ne
 ide

 siu
 lor

 m
 40
 40
 Ch

 (M
 20 g)
 20
 0

 10
 0

 0
 10

 0
 20

 20
 3)
 CO
 20

 80
 80

 20
 (
 So

 te
 40

 40
 diu

 na
 rbo
 m
 g)

 Su
 (M

 (N

 Ca
 a)

 lfa
 m

 40

 60
 60

 40
 +

 te
 +P
 iu

 3)
 60
 es

 60

 (S O
 CO
 ota
 gn

 4)
 (H
 ssi
 Ma

 um

 ate
 60

 40
 40

 60
 on
 (K )

 80

 80
 arb
 Bic
 20

 80
 80

 20
 10

 0

 0
 0

 10
 0

 100 80 60 40 20 0 0 20 40 60 80 100

 Calcium (Ca) Chloride (Cl)

 Figure 2.2.Piper
 Figure Piperplot showing
 plot the major
 showing ion composition
 the major of the groundwater
 ion composition samples and
 of the groundwater the theoretical
 samples and the
 mixing line between fresh groundwater and seawater.
 theoretical mixing line between fresh groundwater and seawater.

 There
 There appears
 appearstotobebe little difference
 little difference in the
 inmajor ion composition
 the major ion compositionbetween the groundwater
 between samples
 the groundwater
collected in 2009 and 2014. However, the Piper diagram shows
samples collected in 2009 and 2014. However, the Piper diagram shows only the relative only the relative distribution, while
absolute concentration
distribution, valuesconcentration
 while absolute indicate a clear increase
 values in salinity
 indicate a clearover time.in
 increase This is shown
 salinity overin Figure
 time. This3
where the total cation concentration is plotted against the chloride
is shown in Figure 3 where the total cation concentration is plotted against the chloride concentration, both expressed in
milliequivalent
concentration, both per liter. The total
 expressed cation content is
 in milliequivalent perused
 liter.here
 Thebecause the relative
 total cation contentdistribution
 is used here of
cations is influenced by adsorption and desorption of cations on soil particles,
because the relative distribution of cations is influenced by adsorption and desorption of cations on while chloride is a
conservative tracer. In the graph, samples taken from a particular well in 2009
soil particles, while chloride is a conservative tracer. In the graph, samples taken from a particular and 2014 are linked to
show
well inthe chemical
 2009 evolution
 and 2014 are linkedoverto time,
 show which clearly indicates
 the chemical evolution that for time,
 over all wells bothclearly
 which the total cation
 indicates
content and chloride concentration increase considerably. The solid blue line
that for all wells both the total cation content and chloride concentration increase considerably. The in the graph shows the
chemical evolution of mixing fresh water with East-Mediterranean
solid blue line in the graph shows the chemical evolution of mixing fresh water with seawater; the ratio between the
total cation content and
East-Mediterranean the chloride
 seawater; content
 the ratio betweenfor Eastern
 the totalMediterranean
 cation contentseawater
 and the is 1:0.90 [29].
 chloride All the
 content for
groundwater samples plot above this line because groundwater has
Eastern Mediterranean seawater is 1:0.90 [29]. All the groundwater samples plot above this line a larger cation versus chloride
ratio thangroundwater
because East-Mediterranean seawater
 has a larger cationdue versus
 to the presence
 chlorideofratiomorethanbicarbonate and sulfate. However,
 East-Mediterranean seawater
the increase in ion content of the well samples from 2009 to 2014
due to the presence of more bicarbonate and sulfate. However, the increase in ion contentis generally parallel to theofseathewater
 well
mixing line, which suggests that the groundwater is constantly mixed
samples from 2009 to 2014 is generally parallel to the sea water mixing line, which suggests that thewith seawater. A probable
explanation
groundwaterfor is the chemical
 constantly evolution
 mixed of the groundwater
 with seawater. A probable is explanation
 given by thefor dotted line, which
 the chemical shows
 evolution
the mixing of seawater with groundwater with an initial ion
of the groundwater is given by the dotted line, which shows the mixing of seawater withcontent of 20 meq/L without chloride.
groundwater with an initial ion content of 20 meq/L without chloride. This line runs more or less
through most of groundwater samples and indicates that the chemical evolution of the groundwater
is strongly determined by the intrusion of seawater. The marks on this mixing line indicate increases
by 1% sea water during the mixing process. Most groundwater samples plot along a range of 3–6%

Water 2020, 12, 262 8 of 14

This line runs more or less through most of groundwater samples and indicates that the chemical
evolution of the groundwater is strongly determined by the intrusion of seawater. The marks on9 this
Water 2020, 12, x FOR PEER REVIEW of 14
mixing line indicate increases by 1% sea water during the mixing process. Most groundwater samples
plot along a range
of seawater of 3–6%
 mixing, whileofthe
 seawater mixing,
 increase in ionwhile thefrom
 content increase
 2009in to
 ion2014
 content from 2009 to 2014
 is approximately 1% ofis
approximately
seawater mixing. 1% of seawater mixing.

 60

 50
 Cations (meq/l)

 40

 30

 20
 Data 2009
 10
 Data 2014
 Seawater mixing
 Seawater mixing
 0
 0 10 20 30 40
 Cl (meq/l)
 Figure 3.
 Figure 3. Plot
 Plot of
 of the
 the total
 totalcation
 cationconcentration
 concentration versus
 versus the
 the chloride
 chloride concentration
 concentration and
 and the
 the theoretical
 theoretical
 mixing line
 mixing line between
 between fresh
 fresh groundwater
 groundwater and
 and seawater
 seawater (solid
 (solid line)
 line) or
 or between
 between groundwater
 groundwater withwith an
 an
 initialion
 initial ioncontent
 content of of
 20 20 meq/L
 meq/L and and no chloride
 no chloride and seawater
 and seawater (dotted(dotted
 line, theline, the markings
 markings indicate
 indicate intervals
 intervals
 of of 1%inincrease
 1% increase sea waterin sea water mixing).
 mixing).

3.2.
3.2. Water
 Water Quality
 Quality
 The
 The pH-values
 pH-values show show thatthat all
 all samples
 samples have have alkaline
 alkaline properties
 properties as as expected
 expected for for groundwater.
 groundwater.
There seems to be a slight increase from 2009 to 2014, but all values
There seems to be a slight increase from 2009 to 2014, but all values are well within the are well within the WHO standard.
 WHO
Although the pH usually has no direct influence on human health
standard. Although the pH usually has no direct influence on human health [26], it can have [26], it can have an effect on the an
hardness of water. There are also no real health guidelines for major
effect on the hardness of water. There are also no real health guidelines for major ions or TDS in ions or TDS in drinking water,
but excessive
drinking salinity
 water, but can have ansalinity
 excessive effect on odor
 can haveandantaste, while
 effect on high
 odorlevels of calcium
 and taste, whileand magnesium
 high levels of
can
calcium and magnesium can lead to scaling. All TDS values are well above the WHO standard,larger,
 lead to scaling. All TDS values are well above the WHO standard, some are 5 to 6 times some
making the water less suitable for domestic use. TDS increased slightly
are 5 to 6 times larger, making the water less suitable for domestic use. TDS increased slightly from from 2009 to 2014, except
for
2009wells W17except
 to 2014, and W18 for for which
 wells W17TDS andincreased by approximately
 W18 for which TDS increased 30%; bythese wells are close
 approximately 30%;tothese
 the
coastline.
wells are closeTDS values for groundwater
 to the coastline. TDS valuesthat exceed the WHO standard
 for groundwater that exceed in Gaza
 the WHO have standard
 been reportedin Gazaby
other researchers; Aish [8] reported TDS values between 680 mg/L and
have been reported by other researchers; Aish [8] reported TDS values between 680 mg/l and 3107 3107 mg/L for 9 municipal wells
sampled
mg/l for 9inmunicipal
 2009 and Abbas et al. [9] reported
 wells sampled in 2009 and thatAbbas
 88% ofettheal. TDS values sampled
 [9] reported that 88%from of the58TDS
 municipal
 values
wells in 2010 exceeded the WHO standard.
sampled from 58 municipal wells in 2010 exceeded the WHO standard.
 For
 For thethemajor
 majorions,
 ions,excessive
 excessive amounts
 amounts of of
 sodium,
 sodium, chloride
 chloride andand
 bicarbonate
 bicarbonate are found, two to
 are found, twofour to
times higher than the WHO standards and for calcium and magnesium
four times higher than the WHO standards and for calcium and magnesium one to two times highr one to two times highr than
the
thanWHO the WHO standards in all wells,
 standards in allexcept
 wells, well
 exceptW11.wellThe levels
 W11. Theof potassium and sulfate
 levels of potassium andaresulfate
 moderate are
and
moderate and are all below or around the WHO standards. The major ion levels in all from
 are all below or around the WHO standards. The major ion levels in all wells increased wells
2009 to 2014
increased fromexcept
 2009potassium.
 to 2014 except In particular,
 potassium. chloride and sodium
 In particular, levels
 chloride andincreased
 sodium levelssignificantly
 increased in
all wells, some by more than 30%, suggesting salinization due to seawater
significantly in all wells, some by more than 30%, suggesting salinization due to seawater intrusion intrusion in the aquifer.
Excessive
in the aquifer. concentrations of sodium and of
 Excessive concentrations chloride
 sodium above WHO standards
 and chloride above WHO in thestandards
 Gaza Strip inhave also
 the Gaza
been
Stripreported
 have alsobybeen otherreported
 researchers; Aish researchers;
 by other [8] reported Aishsodium [8] levels in the
 reported range levels
 sodium of 109–680
 in themg/L
 rangeand of
chloride
109–680 mg/1 and chloride levels in the range 179–1231 mg/L for nine municipal wells sampled[9]
 levels in the range 179–1231 mg/L for nine municipal wells sampled in 2009, Abbas et al. in
reported
2009, Abbas thatet67% of the
 al. [9] 58 wells
 reported thatsampled
 67% of the in 2010 had sampled
 58 wells sodium levelsin 2010 above the WHO
 had sodium standard
 levels aboveand the
71%
WHO above the WHO
 standard and 71% standard
 abovefor thechloride,
 WHO standardAbu-alnaeem et al. [12]
 for chloride, found that 75%
 Abu-alnaeem et al.of[12]
 thefound
 219 wells
 that
75% of the 219 wells sampled in 2013–2014 were above the WHO standard for sodium and 80%
above the WHO standard for chloride.
 High levels of nitrate in drinking water are undesirable because of a potential reduction to
nitrite that can be hazardous to health, especially for infants and pregnant women. Moreover, nitrate
in groundwater is mainly due to contamination, for example leaching of fertilizers or manure,

Water 2020, 12, 262 9 of 14

sampled in 2013–2014 were above the WHO standard for sodium and 80% above the WHO standard
for chloride.
 High12,
Water 2020, levels
 x FORof nitrate
 PEER in drinking water are undesirable because of a potential reduction to 10
 REVIEW nitrite
 of 14
that can be hazardous to health, especially for infants and pregnant women. Moreover, nitrate in
wastewater
groundwaterdisposal,
 is mainlyleakage from septic tanks,
 due to contamination, for etc., and leaching
 example as such itofindicates
 fertilizersthe
 orpossible
 manure, presence
 wastewater of
other hazardous contaminants, such as bacteria or pesticides. Almost all nitrate
disposal, leakage from septic tanks, etc., and as such it indicates the possible presence of other hazardous levels in the well
samples are above
contaminants, suchthe WHO standard,
 as bacteria someAlmost
 or pesticides. even three to four
 all nitrate times
 levels inhigher;
 the wellonly the samples
 samples are above from
 the
wells W9, W14 and W15 in 2009 had a nitrate concentration within
WHO standard, some even three to four times higher; only the samples from wells W9, W14 and W15 the permissible range.
Large-scale
in 2009 had pollution of groundwater
 a nitrate concentration by nitrate
 within has also range.
 the permissible been reported
 Large-scale in other studies;
 pollution Shomar [4]
 of groundwater
found thathas
by nitrate 89%alsoofbeen
 the reported
 94 wellsinsampled in 2002–2004
 other studies; Shomar [4] showed
 found thatnitrate
 89%levels
 of theabove
 94 wells the WHO
 sampled
standard, Almasri and Ghabayen [7] reported that 75% of the 2,413 nitrate
in 2002–2004 showed nitrate levels above the WHO standard, Almasri and Ghabayen [7] reported that concentrations observed
in
75%568 wells
 of the 2413innitrate
 1990 and 2000–2004observed
 concentrations exceededinthe 568 WHO
 wells instandard
 1990 andand Abu-alnaeem
 2000–2004 exceededetthe al.WHO
 [12]
reported
standard thatand 90% of 219 wells
 Abu-alnaeem were
 et al. [12]nitrate
 reported polluted
 that 90% in of
 2013–2014.
 219 wells were nitrate polluted in 2013–2014.
 The
 The WQI scores and associated water quality classes areare
 WQI scores and associated water quality classes given
 given in last
 in the the columns
 last columns of Tables
 of Tables 3 and 34.
and 4. Allscores
All WQI WQI scores are all than
 are all larger larger than
 one, one, except
 except well W11well inW11
 2009,inwhich
 2009, indicates
 which indicates
 that thethat
 waterthequality
 water
quality is problematic. The average WQI score was 2.51 in 2009
is problematic. The average WQI score was 2.51 in 2009 and rose to 2.87 in 2014, demonstrating and rose to 2.87 in 2014,a
demonstrating a continuous deterioration in water quality. All water samples
continuous deterioration in water quality. All water samples collected from wells close to the coast collected from wells
close
have toWQI thescores
 coast greater
 have WQI than scores
 two, greater
 indicatingthan two,
 very poorindicating very poor
 water quality andwater
 about quality and about
 half of them even
half of them even have values greater than three, indicating that the groundwater
have values greater than three, indicating that the groundwater is unsuitable for human consumption. is unsuitable for
human consumption. The inland wells generally have WQI scores less than
The inland wells generally have WQI scores less than 2.5 and can be classified as having poor or 2.5 and can be classified
as having
very poor quality,
 poor water or very with
 poorthe water quality,
 exception withW11
 of well the inexception
 2009, theofonly well W11 in 2009,
 groundwater the only
 sample with
groundwater
good quality. sample with good quality.

3.3.
3.3. Water
 Water Quality
 Quality Mapping
 Mapping
 The
 The water
 water quality
 quality of
 of the
 the well
 well samples
 samples isis clearly
 clearly influenced
 influenced byby the
 the proximity
 proximity toto the
 the coastline,
 coastline,
which clearly indicates
 indicates a strong influence of salinization due to sea water intrusion. FigureFigure 44 shows
 shows
the
the observed
 observed WQI
 WQI scores
 scores plotted
 plotted against
 against the
 the distance
 distance to
 to the
 the coast.
 coast. Also
 Also shown
 shown inin the
 the figure
 figure are
 are the
 the
fitted
fitted linear
 linear regression
 regression lines
 lines through
 through thethe data
 data points,
 points, which
 which suggest
 suggest aa significant
 significant decrease
 decrease inin WQI
 WQI
score
score with distance to the sea. The
 The influence
 influence of
 of the
 the proximity
 proximity of
 of the
 the coastline
 coastline was
 was also
 also noted
 noted by
 by other
 other
researchers
researchers [6,9,12].

 5

 4
 Water Quality Index

 3

 2

 1
 Data 2009
 Data 2014
 0
 0 2000 4000 6000
 Distance from the coast (m)

 Figure Observed water
 Figure 4. Observed waterquality
 qualityindex
 index plotted
 plotted against
 against thethe distance
 distance to coastline
 to the the coastline andfitted
 and the the fitted
 linear
 regression
 linear lines. lines.
 regression

 The distance
 The distance to
 to the
 the coast
 coast is
 is therefore
 therefore an
 an external
 external drift
 drift component
 component that
 that explains
 explains the
 the deterministic
 deterministic
part of the spatial model for WQI, expressed by Equation (5). The stochastic residuals
part of the spatial model for WQI, expressed by Equation (5). The stochastic residuals of theof the model can
 model
can be estimated from Figure 4 as the differences between the WQI values and the corresponding
values derived by linear regression. These residuals make it possible to determine the experimental
variogram with Equation (6), for which we used a lag of 500 m. The results are shown in Figure 5,
which indicates a spatial correlation of the residuals up to a distance of about 3000 m. The empirical
variograms of the data for 2009 and 2014 do not differ much, so one suitable variogram model can be

Water 2020, 12, 262 10 of 14

be estimated from Figure 4 as the differences between the WQI values and the corresponding values
derived by linear regression. These residuals make it possible to determine the experimental variogram
with Equation (6), for which we used a lag of 500 m. The results are shown in Figure 5, which indicates
Water 2020, 12, x FOR PEER REVIEW 11 of 14
Water 2020,correlation
a spatial 12, x FOR PEER ofREVIEW
 the residuals up to a distance of about 3000 m. The empirical variograms 11 of of
 14
the data forrange
practical 2009 and 2014 do
 of 3000 m.not differ
 This much, so one
 variogram model suitable variogram
 is verified bymodel can be fitted using
 cross-validation to all
the data with
practical range
regression-krigingthe following
 ofwith
 3000 parameters:
 the m. exponential
 This tovariogram
 distance the type,
 model
 coastline zeroverified
 is
 as a drift nugget, by
 component.a sillThe
 of 0.23 andare
 cross-validation
 results a practical
 using
 given in
range of 3000
regression-krigingm.
Figure 6, which shows This variogram
 with the model
 theestimated
 distance to is verified
 the scores
 WQI by
 coastline cross-validation
 as a the
 versus using
 driftobservations.
 component. The regression-kriging
 The 1:1
 results linewith
 are given
 identity in
 and
the
the distance
Figure
 95%6, whichto the coastline
 shows
 confidence as a drift
 also component.
 the estimated
 bands are WQI
 shown. TheThe
 scores versusresults
 latter the are given as
 are observations.
 derived in Figure
 ±1.96
 The 1:1 6, identity
 which
 times theshows the
 line and
 standard
estimated
the 95% WQI scores
 confidence versus
 bands the
 are observations.
 also shown. The 1:1 identity
 latter are line and
 derived the
 as ±1.96
 95% confidence
 times
deviation of the residuals, which can be estimated as the square root of the sill. The results show that the bands
 standardare
also shown.
deviation The latter
 of thevalues
all estimated are
 residuals, derived
 are which
 withincanas ±1.96 times
 be estimated
 acceptable the standard
 as the
 range, square
 which deviation of
 root ofthat
 proves the
 the sill.residuals,
 the The which
 results show
 variogram can
 model be
 thatis
estimated
all as thevalues
 estimated
acceptable. squareare
 rootwithin
 of the sill. The results
 acceptable showwhich
 range, that allproves
 estimated
 thatvalues are within acceptable
 the variogram model is
range, which proves that the variogram model is acceptable.
acceptable.
 0.25
 0.25
 0.2
 0.2
 Variogram

 0.15
 Variogram

 0.15
 0.1 Data 2009
 0.1 Data
 0.05
 Data 2009
 2014
 0.05
 Data
 Model2014
 0 Model
 0 0 2000 4000
 0 2000
 Distance (m) 4000
 Distance (m)
 Figure 5. Empirical variogram of the stochastic residual of the water quality index and fitted
 Figure 5. Empirical variogram of the stochastic residual of the water quality index and fitted exponential
 Figure 5. Empirical
 exponential variogram variogram
 model. of the stochastic residual of the water quality index and fitted
 variogram model.
 exponential variogram model.
 4
 4

 3
 - predicted

 3
 - predicted

 2
 2
 WQI
 WQI

 1 Data 2009
 1 Data
 Data 2009
 2014
 Data
 1:1 2014
 1:1
 95% conf.
 0
 95% conf.
 0 0 1 2 3 4
 0 1 2
 WQI - observed 3 4
 WQI - observed
 Figure 6. Cross-validation
 Figure 6. Cross-validation results
 results with
 with estimated
 estimated WQI
 WQI scores
 scores versus
 versus observations
 observations and
 and the
 the 1:1
 1:1 identity
 identity
 line with
 Figure 95% confidence
 6. Cross-validation
 line with bands (conf.).
 results(conf.).
 95% confidence bands with estimated WQI scores versus observations and the 1:1 identity
 line with 95% confidence bands (conf.).
 Water
 Waterquality
 qualityindex
 indexmaps
 mapsfor
 for2009
 2009and
 and2014
 2014derived
 derivedbybyregression-kriging
 regression-krigingare shown
 are shown inin
 Figure
 Figure7.
The maps
 Water
7. The clearly
 maps indicate
 quality
 clearlyindex a regional
 maps
 indicate a for trend in
 2009 and
 regional water
 trend2014 quality
 derived
 in water as a result of sea water
 by regression-kriging
 quality intrusion,
 as a result of seaare shown
 water in addition
 in Figure
 intrusion, in
to
7. some small-scale
 The maps
addition clearly
 to some variations as a result
 indicate variations
 small-scale a regional asof local
 trend contamination
 in water
 a result quality
 of local by domestic, agricultural
 as a resultbyofdomestic,
 contamination or industrial
 sea wateragricultural
 intrusion, in
 or
addition
industrialtowaste.
 some small-scale
 The regional variations as a result
 trend shows of local
 a decrease contamination
 in WQI by per
 by about 0.4 domestic, agricultural
 km distance from theor
industrial
sea. Local waste. Theinregional
 increases trend
 WQI scores shows
 are notedaaround
 decrease in WQI
 well by about
 W16 and around0.4wells
 per kmW3distance
 and W4,from the
 the first
sea.
due Local
 to highincreases in WQIand
 sulfate levels scores are noted
 the later due toaround well W16
 high levels and aroundComparison
 of bicarbonate. wells W3 and ofW4, the first
 the maps of
due to high sulfate levels and the later due to high levels of bicarbonate. Comparison
2009 and 2014 shows a clear increase of the WQI scores over time by about 0.36 on average or about of the maps of
2009 andyear,
0.07 per 2014 especially
 shows a clear increase
 in the of trend
 regional the WQIthatscores overthe
 expresses time by aboutof0.36
 intrusion salt on average
 water. Qahmanor about
 and

Water 2020, 12, x FOR PEER REVIEW 12 of 14
Water 2020, 12, 262 11 of 14
Larabi [30] also reported a continuous decline in groundwater quality as a result of over-exploitation
of groundwater resulting in seawater intrusion.
waste. The regional trend shows a decrease in WQI by about 0.4 per km distance from the sea.
 The groundwater quality classification maps for 2009 and 2014 are also shown in Figure 7. For
Local increases in WQI scores are noted around well W16 and around wells W3 and W4, the first
both years there are only three important water quality classes: poor, very poor and unsuitable for
due to high sulfate levels and the later due to high levels of bicarbonate. Comparison of the maps of
human consumption. In 2009, about 35% of the groundwater in the governorate was unsuitable for
2009 and 2014 shows a clear increase of the WQI scores over time by about 0.36 on average or about
human consumption, which increased to 53% in 2014. All unsuitable groundwater is along the coast
0.07 per year, especially in the regional trend that expresses the intrusion of salt water. Qahman and
and the figures show that the boundary between unsuitable and very poor groundwater quality
Larabi [30] also reported a continuous decline in groundwater quality as a result of over-exploitation
shifted by around 700 m inland in a span of 5 years. If this trend continues, there will soon be no safe
of groundwater resulting in seawater intrusion.
groundwater left.

 (a) (b)

 (c) (d)
 Figure
 Figure 7. Maps with
 7. Maps withthe
 thespatial
 spatialdistribution
 distribution
 of of
 (a)(a)
 WQIWQI scores
 scores basedbased on data
 on data from from
 2009, 2009, (b) scores
 (b) WQI WQI
 scores based on data from 2004, (c) groundwater quality classification for 2009 and (d) groundwater
 based on data from 2004, (c) groundwater quality classification for 2009 and (d) groundwater quality
 quality classification
 classification for 2014.
 for 2014.

4. Conclusions
 The groundwater quality classification maps for 2009 and 2014 are also shown in Figure 7. For both
yearsWater
 there are only three
 samples important
 collected from water quality classes:
 19 municipal wells inpoor, very
 April poor
 2009 and
 and unsuitable
 April 2014 infor human
 the Dier
 consumption. In 2009, about 35% of the groundwater in the governorate was unsuitable
al-Balah Governorate of the Gaza Strip indicate a sodium-chloride dominated water quality. Plotted for human
 consumption,
in whichthe
 a piper diagram, increased to 53%
 major ion in 2014. All
 composition unsuitable
 appears to be groundwater is along
 clearly influenced by the coastwith
 mixing and
 the figures show that the boundary between unsuitable and very poor groundwater
Mediterranean seawater. When the chloride concentration is plotted against the total cation quality shifted
 by around 700itm
concentration, inland
 can also beinconcluded
 a span of that
 5 years. If this trend
 the observed continues,
 groundwater there are
 samples willmainly
 soon betheno safe
 result
 groundwater left.
of mixing with 3–6% seawater, while in the period 2009–2014 there was an increase by about 1%
more seawater mixing with the groundwater.
 Almost all observed chemical parameters are above their WHO water quality standard, in
particular for total dissolved solids, sodium, chloride and nitrate and for the wells close to the
coastline. The differences between 2009 and 2004 show an increase in all major ion concentrations in

Water 2020, 12, 262 12 of 14

4. Conclusions
 Water samples collected from 19 municipal wells in April 2009 and April 2014 in the Dier al-Balah
Governorate of the Gaza Strip indicate a sodium-chloride dominated water quality. Plotted in a piper
diagram, the major ion composition appears to be clearly influenced by mixing with Mediterranean
seawater. When the chloride concentration is plotted against the total cation concentration, it can
also be concluded that the observed groundwater samples are mainly the result of mixing with 3–6%
seawater, while in the period 2009–2014 there was an increase by about 1% more seawater mixing with
the groundwater.
 Almost all observed chemical parameters are above their WHO water quality standard, in particular
for total dissolved solids, sodium, chloride and nitrate and for the wells close to the coastline.
The differences between 2009 and 2004 show an increase in all major ion concentrations in particular
for sodium and chloride. The resulting scores for the water quality index indicate that the water
quality is very problematic, since almost all samples classify from poor water quality to unsuitable for
human consumption.
 The observed water quality depends on the distance to the coastline. Thus, the spatial variation of
the WQI scores can be described by a model with a deterministic drift depending on the distance to
the coastline and a stochastic residual described by an exponential variogram and a practical range
of 3000 m. This model is verified by cross-validation and mapping of the groundwater quality is
achieved by regression-kriging. The results indicate that the groundwater in a large area along the
coastline is not suitable for human consumption and that this zone considerably expanded inland over
a period of five years (2009–2014). It is therefore appropriate that the authorities concerned in the Dier
al-Balah Governorate closely monitor the continued deterioration of groundwater, take the necessary
precautions to prevent use of contaminated water for human consumption and develop alternatives or
corrective measures to meet the water needs of the region.
 Seawater intrusion in the Gaza Strip is a national problem, but mitigation measures are lacking.
Possible solutions and mitigation measures as rain water harvesting, seawater desalination and
wastewater treatment and reuse are well known and have been recommended in the literature
(e.g., [31,32]). It is recommended that seawater intrusion be regularly monitored to improve
groundwater management in the Gaza strip.

Author Contributions: Conceptualization, M.E.B. and P.K.; methodology, M.E.B. and F.D.S.; software, M.E.B. and
P.K.; validation, M.E.B., P.K. and F.D.S.; writing—original draft preparation, M.E.B. and P.K.; writing—review and
editing, M.H. and F.D.S.; supervision, M.H. and F.D.S. All authors have read and agreed to the published version
of the manuscript.
Funding: This research received no external funding.
Acknowledgments: The first author acknowledges the support from Erasmus Mundus and the Vrije Universiteit
Brussel for providing financial support for his PhD research. The authors are thankful to the Palestinian Water
Authority, the Palestinian Meteorological Office, the Coastal Municipalities Water Utility, and the Ministry of
Health for providing data and information.
Conflicts of Interest: The authors declare no conflict of interest.

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