Delineation of temporal variability and governing ...

Journal of Hydrology 432–433 (2012) 26–42

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Delineation of temporal variability and governing factors influencing the spatial variability of shallow groundwater chemistry in a tropical sedimentary island Chin Yik Lin a,⇑, Mohd Harun Abdullah b, Sarva Mangala Praveena a, Aminatul Hawa Bt Yahaya c, Baba Musta a a

School of Science and Technology, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia Water Research Unit, School of Science and Technology, Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia c Applied Science and Technology Section, Universiti Kuala Lumpur, Institute of Marine Engineering Technology, Jalan Pantai Remis, 32200 Lumut, Perak, Malaysia b

a r t i c l e

i n f o

Article history: Received 16 June 2011 Received in revised form 4 February 2012 Accepted 7 February 2012 Available online 16 February 2012 This manuscript was handled by Laurent Charlet, Editor-in-Chief, with the assistance of P.J. Depetris, Associate Editor Keywords: Temporal variability Seawater intrusion Multivariate analysis Geostatistical contour map Groundwater chemistry Small tropical island

s u m m a r y An attempt has been made to delineate the temporal variability and factors governing the shallow groundwater chemistry using analysis of variance (ANOVA) and multivariate analysis notably R-mode factor (FA) and hierarchical cluster analysis (HCA). Subsequently, geostatistical isoplethic maps were applied to convey better understanding on the distribution of selected groundwater parameters. The Manukan Island’s shallow aquifer with sedimentary setting that constantly abstracted for freshwater supply has been selected for this study. One-way ANOVA suggested that neither changes of tide level nor rainfall volume appeared to exert significant influence on the groundwater chemistry of the small island. Rather, the groundwater chemistry was greatly governed by influence from seawater intrusion, which characterized by considerable amount of Ca, Na, and Cl. Such condition was well explained by a Piper diagram, where most plots were situated at the middle diamond shaped diagram, indicating mixing condition. FA likewise revealed that the shallow groundwater receives marked influence from carbonate dissolution and silicate weathering processes, especially boreholes located in the inland area. This can be clearly noted from the distinct groupings of relationships among different factors. HCA classified boreholes into three groups according to their locations in the coastal area, suggesting significant chemical variations between boreholes with distance from coast. Such distribution pattern was particularly evident in the isoplethic map. Overall, it appears that the shallow groundwater in the tropical island is not an appropriate source for drinking water in concern to its exceptionally high salinity and several elevated minor elements (Mn, Pb, and Se). For this, it is suggested that efforts in exploring other alternative sources should be performed outright. Ó 2012 Elsevier B.V. All rights reserved.

1. Introduction Groundwater in small islands is particularly vulnerable to multifarious pollutions as the water properties are easily subjected to stress, in terms of quality and quantity. Quality wise, it appears to be affected by numerous factors which includes: climate, tidal fluctuation, nature of soil, general geology, topography of the area and seawater intrusion, regardless to natural occurrence or anthropogenic factors (Adams et al., 2001; Andre et al., 2005; Aris et al., 2007; Lin et al., 2009; Reghunath et al., 2002). And in terms of quantity, most small islands appear to have exceptionally limited fresh groundwater resource, primarily corresponded to its small surface area. Unfortunately, such depleted water resource is al⇑ Corresponding author. Address: 14, Lorong Nipah Lima, Taman Lip Sin, 11900 Bayan Lepas, Pulau Pinang, Malaysia. Tel.: +60 4 6430769, +60 17 4839158. E-mail addresses: [email protected], [email protected] (C.Y. Lin). 0022-1694/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.jhydrol.2012.02.015

ways susceptible to contamination via seawater intrusion, which further deteriorates the quality of groundwater. Moreover, intense pumping activities of groundwater from phreatic zone may greatly provoke artificial seawater intrusion into the aquifer where such process is virtually irreversible. To preclude further occurrence of seawater intrusion and to cope with its consequent problems, it is of most imperative to thoroughly examine the spatial and temporal groundwater chemistry in a small island’s shallow aquifer while interpreting other possible contributing sources and processes of the groundwater salinity. In Malaysia, most of the groundwater studies on small islands were focused on the general hydrochemistry and emphasis on the spatial variability of the water quality data (Abdullah et al., 1997a,b; Aris et al., 2007; Isa and Aris, 2012; Lin et al., 2009, 2010) without taken account of the temporal changes of groundwater chemistry. In view of this, present study, exemplified by Manukan Island of Eastern Malaysia, has been undertaken to

C.Y. Lin et al. / Journal of Hydrology 432–433 (2012) 26–42

bridge this information gap. We aim to delineate the governing factors that influencing the spatial and temporal variability of groundwater chemistry in a small tropical island. To address this, combination of various statistical techniques (multivariate analysis, ANOVA, and geostatistical contour map) has been employed to comprehensively study the hydrochemical characteristics associated with periodical hydrographic influences. Multivariate statistical analysis is an efficient tool of portraying complex relationships among variables. As a result, most studies often coupled factor analysis (FA) and hierarchical cluster analysis (HCA) in conducting analysis of spatial and temporal variance (Dou et al., 2008; Helena et al., 2000; Lambraski et al., 2004; Reghunath et al., 2002; Shyu et al., 2011; Varol et al., 2012). By applying multivariate statistical analysis to a huge data set, the interpretation can be simplified by using rotational procedures, detecting similarities among variables and thus leading to meaningful insight (Reghunath et al., 2002; Subba Rao et al., 2001). In this paper, we opted to incorporate groundwater chemical compositions, both major and minor, into multivariate statistical techniques (factor analysis – FA; and hierarchical cluster analysis – HCA) to evaluate multiple sources of ions and delineate factors controlling the groundwater chemistry along natural flow path (transect) of a shallow aquifer. Besides, we also deemed that tidal information and meteorological conditions of the study domain is particularly essential in order to understand their influences on the groundwater chemistry, both spatially and temporally. Thus, discussions on the said factors (by applying ANOVA test) were likewise incorporated. In the last section of this manuscript, we visually display the spatial variability of groundwater in isoplethic (contour) map for better interpretation of the complex relations between groundwater hydrochemical properties and environmental factors. Hitherto, there was no such comprehensive attempt being made within a small tropical island setting. Consequently, present work is deemed beneficial to provide benchmark and steppingstone for better groundwater resource management, planning and designing monitoring network, recommendations and mitigation measures, which includes those yet to be made, on the groundwater salinization problem caused by seawater intrusion. 1.1. Site descriptions Manukan Island is situated off the western coast of Sabah, Malaysia (Fig. 1a). Almost 80% of the island is covered by forest

27

on the high relief side, while the rest 20% of the low lying area is developed for tourism activities (Abdullah et al., 1997b). The shape of the island is like a crescent and it is one and half kilometer long and three hundred meters wide in the middle (schematic drawings, Fig. 1b and c). The mean temperature of the study area is approximately 23–32 °C (Malaysian Meteorological Department, 2009). The island receives profound precipitation during the southwest monsoon (April–October) and the southeast monsoon (October–February) and this high volume of rainfall is much dependent on the transition of monsoon seasons (Malaysian Meteorological Department, 2009). Manukan Island has a hilly topography with high elevation of approximately 30–50 m in the western and slopes down towards the eastern coast (Abdullah et al., 1997b) as depicted in the contour map (Fig. 2). The topographically high terrains serve as freshwater recharge areas for the lowland areas. The hydraulic potential developed at these high elevations generated a sufficient hydraulic gradient (topology-driven flow) for direct infiltrating groundwater towards the low lying area and the coast (Abdullah et al., 1997b). Most of the beach and sand deposits are mobile; yet, certain locations further inland were gradually stabilized which can be characterized by the presence of vegetation. Beach and remnant reef materials (coral rubbles) are primarily composed of calcium carbonates and had probably undergone various extents of diagenetic changes immediately after deposition (Ong et al., 2000).

1.2. Geology and hydrogeology Manukan Island is underlain by folded sandstone and comprised of various sedimentary rocks (Abdullah et al., 1997b; Basir et al., 1991). This island consists of interbedded clastic sandstone and shale classified as the Crocker Formation deposited during Late Eocene to Middle Miocene (Abdullah et al., 1997b; Basir et al., 1991). The sedimentary rock of Manukan Island is found to dip towards the low relief area (east–northeast), with dipping angles of 15–45°. The fold forms a slight symmetrical syncline in the low lying area where small scale normal faults and joint sets can be observed in several locations of the island (Abdullah et al., 1997b). Parent materials found in the high relief side of the island are thick sandstone and thin shale while in the low relief side is composed of quaternary alluvium and thin sandstone (Abdullah et al., 1997b). The eustatic sea level changes that occur during quaternary age,

Fig. 1. The geographical location of Manukan Island in Sabah, Malaysia. The shape of the island resembles a crescent and it is one and a half kilometer long and three hundred meters wide in the middle. Only low elevation area was focused, where substantial groundwater are available. Captions of the composite maps were given in parentheses.

28


Fig. 2. Contour map of Manukan Island represents the elevation of sampling sites (elevation unit in m). The island has a hilly topography with maximum elevation of approximately 30 m to 50 m in the western coast and slopes down towards the eastern coast. BK denotes the highest point within the vicinity of sampling boreholes. Transect (A–A0 ) of boreholes were installed perpendicularly from the coastline towards inland over a distance of 130 m.

Fig. 3. Average monthly rainfall data for year 2008–2009 in the study area. Sampling periods for groundwater were shaded, the average annual precipitation in Manukan Island is 3453.6 mm.

caused the formation of limestone terraces in coastal areas. The shallow, unconfined aquifer is formed of carbonate rocks that originated from coral deposits and overlain by quaternary alluvium (Basir et al., 1991). The alluvium is found to be loose, not cemented and possibly acted as superior water storage aquifer, which depends on its thickness (Abdullah et al., 2009). Porosity of the sandy soil is rather high, approximately 0.30, thus susceptible to the intrusion of seawater (Abdullah et al., 2009; Dykes and Gunn 2006). Average monthly rainfall data 2008–2009 for Kota Kinabalu Airport, representing the study area obtained from the Department of Meteorology, Sabah, Malaysia is depicted in Fig. 3. Based on the one-year period (May 2008–May 2009) rainfall hydrograph presented below, the average annual precipitation at Manukan Island is 3453.6 mm. Studies reported that both groundwater quality and groundwater level of small island are strongly dependent on the ti-

dal effect as the seawater may intruded via coarse sand layer into a given island’s aquifer and alters the position of seawater/freshwater interface (Abdullah et al., 1997a; Ong et al., 2000; Sabbagh Yazdi, 2004; Usui et al., 1998; Xun et al., 2006). Therefore, hydrographic data is considered as a crucial component and must be taken into utmost consideration in relevance to coastal sandy aquifer. Data of tidal level for Kota Kinabalu during the sampling periods (October 2008–March 2009) are depicted in Fig. 4 (National Hydrographic Center, 2009). 2. Materials and methods 2.1. Groundwater sampling and boreholes installation A total of 59 groundwater samples were collected monthly from October 2008 to March 2009 at the study site. Seawater and rain-

29


Fig. 4. Hydrographic changes based on a 24-h record on the day of groundwater sampling. Shaded area represents the time when groundwater sampling was carried out.

water samples were also collected as ancillary data. Groundwater samples were sampled from 10 boreholes, which were drilled by using hand auger. The depths of boreholes ranged from 1.5 m to 3 m, approximately at the depth of phreatic zone. Cross section (A–A0 ) of boreholes was installed perpendicularly from the coastline towards inland over a distance of 130 m (Fig. 5). Boreholes’ material were made from 30 mm-diameter PVC pipe, with perforated slots and fitted with 10 cm (3 in.) screen of galvanized wire mesh at the bottom, which is resistant to corrosion and were

plunged at base. Table 1 summarizes the boreholes’ location and features in Manukan Island. All sampling bottles were acid washed prior to sampling. In the field, groundwater was extracted from boreholes using a portable vacuum pump interconnected with a 0.3 in. polyethylene tube. Subsequently, groundwater was allowed to run for approximately 10 min in order to purge several boreholes volumes. The main reason was to remove stagnant water and allow representative groundwater to be sampled. Prior to each sample collection, the

Fig. 5. Cross-section topography of Manukan Island. Location of pumping well was shaded in gray color. Based on the diagram, topological driven flow from the highland towards the lowland is expected. This schematic diagram is capable of clearly represent the hydrogeology aspect in the study area. Yet, it should be advise that this diagram was drawn not to scale, it made only based on GPS estimation.

Table 1 Summary of boreholes’ GPS location and general hydrogeological information in the studied aquifer. Groundwater level was calculated using mean.

a

Boreholesa

GPS coordinates

B1 B2 B3 B4 B5 B6 B7 B8 B9 B10

N N N N N N N N N N

05°580 58200 05°580 58300 05°580 58400 05°580 58600 05°580 59400 05°580 59600 05°580 60000 05°580 60600 05°580 61200 05°580 62000

E E E E E E E E E E

116°000 18000 116°000 18000 116°000 18000 116°000 18000 116°000 18000 116°000 18000 116°000 18000 116°000 18000 116°000 18000 116°000 18000

All boreholes’ screen is made of galvanized wire mesh.

Distance from shore (m)

Boreholes’ depth (m)

Groundwater level (m)

28.75 31.05 33.28 35.63 69.33 74.45 80.15 85.25 94.45 125.25

1.69 1.70 2.30 2.70 1.74 1.65 1.69 2.50 3.00 1.50

1.18 1.09 1.02 1.04 1.31 1.31 1.38 1.40 1.14 1.18

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bottles were rinsed thoroughly with groundwater extracted from the respective borehole. Sample bottles were fully filled with water samples to ensure the elimination of air bubbles and organic particulate matters entrapped in the bottles (Brassington, 2007). This procedure prevented the occurrence of biochemical and surface reactions of the water samples, which tend to undergo reduction process during transportation and storage. For quality control procedures, accuracy of the method was assured by triplicate analysis. Routine replicates from each sampling stations were collected at all sampling campaigns to increase the power of analysis. General procedures for groundwater sampling, preservation, and chemical analyses were carried out in accordance to the APHA (1995) standard procedure. 2.2. Samples determination and preservations In-situ parameters such as pH, redox potential (Eh), and electrical conductivity (EC) were measured on site. Water samples were collected in 1L polyethylene (PE) bottles for anions and cations analysis. After filling the bottles with samples, the bottles were capped tightly, labeled and stored in a cooler box. The water samples were cooled to 4 °C for SO4, HCO3 and Cl analysis. Groundwater samples were first filtered through WHATMAN 0.45 lm membrane cellulose nitrate filter paper using glass filtration unit. The samples were acidified with concentrated Analar HNO3 to pH < 2 for major cations (Ca, Mg, Na, K, H4SiO4) and minor elements (Al, Ba, Be, Fe, Li, Mn, Pb, Se, Sr) analysis to prevent adsorption onto the container surface, retard biological activity while avoiding hydrolysis and precipitation of cations within the matrix (APHA, 1995). 2.3. Laboratory analysis Concentrations of major cations (Ca, Mg, Na, K) were analyzed by using direct air-acetylene flame atomic absorption spectrophotometer (FAAS Perkin Elmer – 4100). Raw and un-acidified samples for Cl and HCO3 determination were conducted using argentometric (AgNO3 0.0141 N) and titration techniques (HCl 0.02 N) as suggested by APHA (1995). Filtered (0.45 lm) and un-acidified samples for SO4 analysis were detected spectrometrically using HACH Water Analysis Kit model DR/2010. Whereas minor elements (Al, Ba, Be, Fe, Li, Mn, Pb, Se, Sr) and dissolved silica (H4SiO4) were determined by inductively coupled plasma-optical emission spectroscopy (ICP-OES Optima 5000 DV Perkin Elmer) in the Laboratory of Inorganic Chemistry, School of Science and Technology, Universiti Malaysia Sabah. Data from quality control samples show good reproducibility and indicate no contamination derived from sampling procedures and equipment. 2.4. Statistical applications The obtained data were evaluated by conducting ANOVA, FA, and HCA for all parameters using Statistical Package for Social Sciences (SPSS) for Window v. 16.0. For ANOVA test, two independent factors of concern were (i) sampling events and (ii) tidal change. One-way ANOVA was performed to evaluate the influence of both independent factors towards the groundwater chemistry. FA is a multivariate statistical technique employed to reduce immense data sets of high complexity by determining a small number of variables that account for the greatest variance in all of the original variables (Reghunath et al., 2002; Subba Rao et al., 2001; Voudouris et al., 2000). In this study, R-mode FA was applied to delineate the controlling factors that governed the groundwater chemistry of a small island shallow aquifer. FA was performed on a subset of 19 selected variables (pH, EC, Ca, Mg, Na, K, HCO3, Cl, SO4, H4SiO4, Al, Ba, Be, Fe, Li, Mn, Pb, Se, and Sr), which represented the

overall groundwater chemistry framework. Data sets were logtransformed before subjected to FA. Redox potential (Eh) was disregarded from multivariate statistical analysis to avoid singularity with pH in response to nearly perfect correlation. The technique employed for initial factor extraction was the principal component analysis. The maximum number of factors to be extracted was fixed by the Kaiser Criterion, which takes into account only factors having eigenvalues greater than 1. Maximum number of iterations for convergence was set to 25. Following this procedure, five factors were obtained and rotated according to the orthogonal Varimax method. Interpretation of output is according to rotated factors, rotated eigenvalues and rotated loadings. All variables analyzed showed communalities after extraction were higher than 0.5, indicating adequate participation of these variable in the factors (Subba Rao et al., 2001; Trabelsi et al., 2007). HCA was undertaken to obtain fundamental understanding on the groundwater hydrochemical system by discretization of sampling boreholes into different groups. This method of cluster analysis has the advantage of not demanding any priori assumption of the number of cluster (Reghunath et al., 2002; Shyu et al., 2011; Varol et al., 2012). In clustering, cases with homogeneity properties or otherwise cases with heterogeneity would be enclosed into identical group (Lambraski et al., 2004; Shyu et al., 2011). Current study employed the Ward’s-algorithmic clustering procedure subsequent to the squared euclidean distance, which considered as the most powerful grouping mechanism (Dou et al., 2008; Lambraski et al., 2004; Reghunath et al., 2002; Shyu et al., 2011). Ward’s method is capable of minimizing the distorting effect or sum of square distances of centroids from two hypothetical groups generated at each stage (Lambraski et al., 2004). Applying factor extracted scores (from FA) into HCA is a remarkable technique for data simplification by generalizing groupings into a more expressive form despite the ignorance of certain potentially meaningful environmental data. However, it does not takes data authenticity and discrete values into account and it disregard plausible and potential interactions or similarities (also known as statistical interferences) between variables which are rather evident in most environmental data. As such, the output would have been inevitable to manipulation and not be considered as absolute environmentally meaningful data. Hence, we opt to incorporate only raw data into the HCA where detailed investigation on each grouping is achievable and real/natural (without alteration) condition of environmental data were able to be represented (Saleh et al., 1999; Raju, 2006). 2.5. Geostatistical presentation (isoplethic maps) Geostatistical tool such as variogram analysis allows the differentiation between spatial variability to be presented in illustrations. The actual value of a geostatistical analysis involves the estimation of hydrochemical properties for locations within the area that are not sampled (Ceron et al., 2000; Lin et al., 2006). For each estimated point, the adjacent points provide a weighted contribution to the estimate, depending upon the semi-variogram function (Fernandes et al., 2008). The semi-variogram c(h) is mentioned by Aishah et al. (2010), Imrie et al. (2008), and Lin (2002) as follows:

1 2

cðhÞ ¼ Var½ZðxÞ Zðx þ hÞ

ð1Þ

where h denotes the lag distance which separates two sampling points, Var the variance of argument, Z(x) the observed value of the regionalized parameter at location x, and Z(x + h) the value at location x + h (Lin, 2002). Therefore, ordinary kriging interpolation method was applied to estimate the value of each un-sampled point along the lowland


transect by constructing an isoplethic map using SurferÒ 9.0 (Golden Software Inc.). Variables with different sampling events were averaged and used. We only consider elements that exhibit pronounce influence to the groundwater chemistry that derived from FA. In this case, Na, K, Ca, Cl, Mg, Al, Ba, Fe, Mn, H4SiO4, Pb, Se, and Sr were selected. 3. Results and discussion 3.1. Physico-chemical properties

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(Cl and SO2 4 ) was unclear, as it did not correspond to the other independent variables such as tidal influence and rainfall volume. As such, Cl demonstrated wide range variability in the inland boreholes (B5, B6, B7, B8, B9, and B10), suggested the conservative character of Cl- had been greatly influenced by other unknown 2 sources. Overall, Ca2+, Mg2+, Na+, HCO revealed 3 , Cl , and SO4 moderately weak temporal variation, implied that seasonal effects might not be significant in influencing the major groundwater chemistry of the shallow aquifer. 3.3. Minor elements

Majority of sampling sites experienced pH condition of circumneutral to moderately alkaline (pH 6–8). Redox potential of groundwater varies from 83 to 19 mV, where a negative value implies that reducing condition prevailed in the shallow aquifer. The groundwater of Manukan Island was moderately mineralized, indicated by its moderate to high EC readings from 460 lS/cm to 3400 lS/cm. Highest EC value was registered at location B4 perhaps due to deeper borehole’s depth (3.0 m) and its proximal distance to the coast, where tidal processes commonly exert potent influence on the groundwater salinity. Data of physico-chemical parameters are presented in Table 2. 3.2. Major elements Considerably high concentrations of Ca2+ were documented in all sampling campaigns with a maximum value of 178.76 mg l1. Such elevated Ca2+ concentration might be corresponded to the congruent dissolution of calcitic shell materials, which occur ubiquitously in the shallow aquifer. Conversely, lowest Ca2+ concentration was recorded in borehole B2. Such observation is mainly explained by the relatively shallow borehole’s depth (1.5 m) where interactions between carbonate components and seawater constituents were minimal. Similar explanation is likewise found in Freeze and Cherry (1979), who mentioned that low mineralized water is likely to be occurred at the shallower zone as a result of active flushing. Subsequently, Mg2+ showed moderately weak temporal variability at most of the sampling boreholes, with exceptions to B3 and B4. Such ambiguous temporal behavior might be rendered by manifold of effects, which include dissolution of magnesium bearing calcite (as confirmed by the X-ray diffraction data, not reported here), pluvial input and seawater contributions. The lower Mg2+ in B6 and B7 (Fig. 6) have been derived from diffuse sources, probably due to extensive incongruent dissolution of magnesium calcite deposits in the vicinity as described in the generalized form of chemical reaction (Eq. (2)) (Appelo and Postma, 2005; Dogramaci et al., 1998):

Ca2þ þ ðCa1X MgX ÞCO2 CaCO3 þ Mg2þ

ð2Þ +

Comparable trend was also observed for Na , where boreholes B4 and B9 evinced dramatic increase of Na+ compared to the adjacent boreholes. High concentration of Na+ in certain boreholes could be partly ascribed by periodic incursion of seawater and cation exchange reactions at those locations. Data from October 2008 registered the highest mean (6.28 mg l1) of K+ concentration while sampling campaign of February 2009 has the lowest (3.76 mg l1). With regards to K+, we noticed that boreholes located at the shoreline (B1, B2, B3, and B4) were rather responsive to temporal changes, suggesting the depletion of this ion as a consequence of constant abstraction. Conversely, all major anions exhibited relatively weak temporal variability. HCO 3 revealed a steady trend with progressive increase in concentration towards inland whereas Cl and SO2 disclosed 4 comparable behavior across transect but with moderately weak temporal variability. Reason causing such poor temporal variability

Concentrations of minor elements (Al, Ba, Be, Fe, Li, Mn, Pb, Se, Sr) in groundwater are presented in Table 3. It is noticed that certain elements such as Al, Be, Fe, and Pb exhibit marked temporal variability. These elements were regarded to be responsive to rainfall event in some extent, due to their known redox sensitive character and involvement in biogeochemical processes. This can be observed by the slight increase in elemental concentrations of Al, Be, Fe, and Pb on the subsequent month with profound rainfall. Comparable behavior showing Fe with temporal variability was documented in Davison and Vonhof (1978), where Fe content in the groundwater increased dramatically prompted to rainfall event. Conversely, minor elements notably Ba, Li, Mn, Si, and Sr did not display any significant behavior towards temporal variations (Fig. 7a–e). The lack of temporal response suggested that Ba, Li, Mn, Si, and Sr were rather stable in the aquifer matrix and did not show abrupt reactions with pluvial input. Silicic acid (H4SiO4) exhibited narrow temporal variability with progressive increase in dissolved concentration as distance increases from shoreline, indicating the enrichment of quarzitic minerals and depletion of carbonate minerals at the inland area. Also, greater degree of silicate weathering might have occurred in the inland area with more mature water (greater residence time). Nevertheless, selenium did not shows noticeable temporal variations (Fig. 7f) for all sampling periods despite the irregular and wide concentration ranging from 3.58 lg l1 to 49.44 lg l1, suggested that this element exhibited a distinct chemical behavior from other elements measured in the shallow aquifer. 3.4. Groundwater evolution Temporal variation of general groundwater chemistry of an aquifer could be superficially detected by examining the evolution trend in a Piper diagram. In general, Piper plot (Fig. 8) of the groundwater data indicates that Ca2+ was the predominant cation while HCO 3 and Cl were the predominant anions. Basically, the data were clustered in the middle of the diamond shaped diagram, suggested the mixing of water from both end member sources (Panagopoulos et al., 2005). In fact, by investigating the temporal variation of groundwater chemistry through the Piper diagram, it was possible to discriminate the extent of mixing between both end member sources. Present study evinced that groundwater from both end member sources were moderately mixed to a certain degree, as noticeable variations could be evident by the shifting plots in the Piper diagram. Piper plot overall displayed a weak re-freshening process where shifting route was initiated from (1): most samples were plotted closer to the seawater portion, followed by general shift towards the center of the diagram (2) where mixing of water can be clearly observed. Subsequently, all samples underwent a slightly upward movement as elucidated by magnitude (3) in Fig. 8. Overall re-freshening process can be clearly depicted in a time series graph with sampling events plotted against EC and tidal level (Fig. 9). From the graph, one can easily deduce that the tidal level does not pose appreciable influence on the overall re-freshening process. Instead, substantial amount

32


Table 2 In-situ and major ion concentrations (in mg l1) of groundwater samples (n = 59). pH, Eh (in millivolt), and EC (Electrical conductivity in lS cm1) were determined in situ, while major ions were analyzed in the laboratory. (n = 59)

Date

pH

Eh

EC

Ca

Mg

Na

K

HCO3

Cl

SO4

H4SiO4

B1

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

7.14 6.96 7.72 7.03 7.13 7.37

32 34 63 41 47 62

1665 1252 1293 1134 1048 746

89.1 83.5 104.9 92.5 93.2 97.5

30.3 23.5 23.7 28.4 26.0 21.6

220.1 117.3 117.7 117.6 101.7 73.2

11.6 11.4 8.6 5.9 4.9 4.0

429 351 338 366 391 283

220.0 222.5 339.9 259.9 332.4 135.0

107 55 110 40 28 21

3.20 2.63 2.64 3.57 3.78 2.99

B2

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

7.76 7.81 7.31 7.56 7.74 7.34

62 66 39 72 83 60

850 460 810 620 707 540

68.4 41.8 42.3 44.3 63.5 67.5

22.8 17.8 24.7 32.9 38.2 29.5

56.6 18.6 91.9 55.4 37.0 25.0

9.5 3.3 4.8 6.8 5.1 3.1

339 180 371 300 348 270

145.0 177.5 192.5 131.0 187.5 110.0

25 12 26 12 1 7

2.32 1.10 1.52 1.75 1.86 1.74

B3

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

7.86 7.46 7.33 7.24 7.59 7.70

69 46 36 54 74 81

1455 1017 790 998 1499 871

77.2 96.7 107.5 102.4 108.9 85.8

16.6 18.9 20.0 23.8 20.9 18.3

165.8 77.9 92.8 116.4 95.6 51.3

8.7 9.7 6.9 5.6 4.2 3.1

385 307 337 357 370 304

220.0 172.5 307.4 282.4 304.9 365.4

83 38 105 43 35 27

3.69 2.56 2.82 4.05 4.55 3.01

B4

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

7.41 7.50 7.24 7.20 7.58 7.15

44 49 35 52 74 49

3400 2250 1920 1844 1503 1465

141.7 124.7 136.6 108.5 118.2 120.6

35.9 30.7 33.1 34.5 31.6 29.7

326.5 223.0 207.0 204.1 159.3 143.7

13.4 11.5 10.0 8.0 6.6 6.4

333 307 351 378 408 421

572.4 324.9 562.4 542.4 539.9 405.4

165 100 145 80 53 43

4.36 3.73 3.86 4.09 4.47 4.55

B5

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

7.68 7.88 6.97 7.07 7.18 7.24

58 67 21 45 50 54

655 1299 810 655 752 825

89.9 110.1 158.8 138.7 131.3 115.1

5.0 3.7 5.2 5.6 6.0 14.6

30.8 13.0 31.1 46.9 56.6 93.7

1.7 1.4 1.9 6.1 1.9 4.3

255 245 334 352 360 347

175.0 120.0 227.4 242.4 272.4 125.4

27 14 13 12 13 23

3.49 2.49 2.85 2.50 2.44 3.44

B6

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

7.84 7.14 7.01 6.86 7.09 7.48

67 30 23 32 45 68

804 999 1150 1229 1126 1058

108.4 154.9 170.8 146.9 134.2 119.0

4.7 8.2 12.9 20.5 23.0 21.1

57.2 42.9 66.8 110.9 102.8 81.3

1.2 2.2 2.3 4.2 3.2 3.1

268 260 381 405 401 361

167.5 155.0 334.9 252.4 324.9 379.4

27 27 25 15 27 27

3.74 3.26 3.38 4.02 4.53 5.00

B7

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

7.89 7.26 7.06 6.97 7.07 NA

70 37 25 38 44 NA

1220 1176 1160 1043 957 NA

131.0 145.0 152.2 130.2 123.1 NA

13.4 17.8 17.7 23.6 27.0 NA

96.0 79.0 76.0 98.1 84.1 NA

1.1 2.1 2.6 2.4 2.1 NA

310 364 399 402 422 NA

202.5 162.5 339.9 307.4 334.9 NA

62 45 37 31 43 NA

4.25 4.24 4.72 5.14 5.49 NA

B8

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

7.14 7.12 6.95 7.03 7.45 7.18

29 29 20 41 66 54

1290 1240 1410 1290 957 1279

154.9 173.4 178.8 138.7 115.9 138.3

17.9 17.8 20.8 25.0 21.1 21.0

97.2 76.1 109.7 118.8 63.2 88.3

3.9 2.8 2.8 3.4 2.9 3.4

400 378 418 418 370 359

200.0 185.0 417.9 289.9 397.4 369.9

24 25 27 29 6 27

6.08 5.51 6.13 5.73 4.96 5.18

B9

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

7.38 7.05 7.04 7.04 7.30 7.01

43 25 24 42 58 40

2100 1625 1600 1417 948 1507

140.9 161.5 160.5 126.5 113.9 150.0

17.9 25.0 28.4 31.2 19.2 27.8

203.2 144.1 140.2 132.1 64.2 125.2

7.4 6.3 6.5 5.7 3.0 3.9

310 453 453 410 369 353

354.9 244.9 429.9 284.9 422.4 501.9

82 40 20 40 35 33

3.58 6.35 6.58 6.34 4.45 6.20

B10

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

7.73 7.16 6.94 7.07 7.56 7.26

63 31 19 42 72 60

1193 1218 1070 799 501 1221

163.5 171.3 153.8 117.7 123.6 144.4

14.2 17.5 15.3 15.6 18.4 18.6

68.2 75.7 60.3 53.3 71.2 87.1

4.3 4.5 4.0 3.7 3.7 3.7

345 362 359 336 371 357

204.0 197.5 329.9 294.9 327.4 374.9

21 22 22 24 20 21

9.63 9.04 8.79 7.71 7.66 9.51

7.31 6.86 7.89 0.29 6.5–8.5 0

48.4 83.0 19.0 16.89 NA –

1181.69 460.00 3400.00 480.32 1500 16.95

120.42 41.80 178.80 33.50 200 0

20.95 3.70 38.20 8.22 150 0

99.00 13.00 326.50 57.79 200 10.17

4.96 1.10 13.40 2.92 NA –

354.42 180.00 453.00 52.84 NA –

288.22 110.00 572.40 116.53 250 55.93

39.78 1.00 165.00 33.45 250 0

4.39 1.10 9.63 1.98 NA –

Mean Minimum Maximum Std. deviation WHO limits Violation (%)


33

Fig. 6. Elevated Mg2+ in B1, B2, B6, and B7 can be explained by the incongruent dissolution of magnesium calcite deposits in the vicinity whereas enrichment of Mg2+ in B4 was mainly contributed by seawater components.

of fresh water derived from the high elevation area is believed to be relevant with the flushing process. This evolution trend of hydrochemistry appears to be governed by the interplay between both denser seawater and overlying freshwater lens in the shallow aquifer. In an unconfined aquifer of small island, such balance between freshwater and seawater interface are closely related to the Ghyben–Herzberg relation. The Ghyben–Herzberg relation can be expressed by the formula derived from the following equation:

qs gzs ¼ qf gðz þ hf Þ

ð3Þ

where qs denotes the density of saline water, qf refers to the density of freshwater, g is the acceleration of gravity and hf is the height of freshwater above sea level. Thus, solving for z yields

z¼

qf qs qf

! hf

ð4Þ

For qf = 1.000 g cm3 and qs = 1.025 g cm3, so that

z ¼ 40hf

ð5Þ

Eq. (5) is recognized as the Ghyben–Herzberg relation. Further explanations and function were reviewed in Freeze and Cherry (1979) and Todd (1980), hence will not be reiterate here. Obviously, there were no extreme values identified during the sampling periods, indicated a rather well mixed (homogeneous) groundwater condition in the shallow aquifer. In fact, it signified that a weak seawater/freshwater interface might have been developed in the small island’s shallow aquifer. The lower triangular diagram clearly showed that most groundwater samples were plotted close to the HCO 3 –Cl line. Therefore, the groundwater of Manukan Island is concluded to be influenced by the mixing from seawater which can be envisaged by a shift from Ca–HCO3 facies to Ca–Cl or Na–HCO3 facies. Hypothetically, a number of concurrent chemical reactions were suggested to account for the chemical evolution of shallow groundwater in the study site. These include: (a) Dissolution of carbonate minerals due to algebraic effects result from the mixing between seawater and freshwater, (b) contribution of substantial amount of dissolved solids from the seawater, and; (c) cation exchange between the aquifer matrixes with the surrounding solute.

3.5. Statistical analysis 3.5.1. Analysis of variance (ANOVA) A total of 59 groundwater samples were tested with one-way ANOVA (Table 4). Temporal trend is evidently noticeable in certain elements such as Al, Be, Fe, and Pb (p < 0.01). It is understood that Al and Fe were mainly of terrigeneous origin (mostly as sesquioxides). Meteoric waters thus react, dissolute, leach and illuviate these elements from the surface soil into the groundwater saturated horizon, eventually, influencing the groundwater chemistry as time passes. The remaining parameters conversely displayed a minute temporal trend. Besides, output of ANOVA likewise indicated that tidal activity played a major role in controlling the concentration of certain elements in the shallow aquifer, notably Be, Se, and Pb with significance level of p < 0.01. Eh and marine derived elements (K and SO4) also showed good response towards tidal activity, but in a lesser extent (p < 0.05). F-values were shown to determine which elements best distinguished the independent factor (Grunsky et al., 2009). For sampling events, it appears that Pb, Be, and Al were the best discriminators. Whereas, Pb, Be, and Se were recognized as the best discriminators for the tidal factor. The high discrimination power of Pb and Be attained in both independent factors is most probably due to their relative mobility and delicate characters towards environmental changes. These elements can be considered as responsive and sensitive towards tidal and temporal variability. 3.5.2. R-mode factor analysis Table 5 presents the varimax factor loadings matrix for each variable. The extraction of five factors were based on the proportion of variance accumulated which comprised a percentage superior to 80%. The computed data shown these five factors well explained 78.29% of the total variance. Based on the ‘‘scree test’’, five factors with different factor loadings suggest that five different pronounced contributions were involved in controlling the groundwater chemistry in the aquifer. Communality is an indicator of error where (1-communality) or random noise (Jayakumar and Siraz, 1997). In this study, the communalities for most variables were close to 1, thus FA was considered to have produced output with good reliability as mentioned by Ruiz et al. (1990). Analysis revealed the Kaiser–Meyer–Olkin measure of sampling adequacy was 0.689, suggesting that the patterns of correlation were relatively compact thereby yielded distinct and reliable factors. Like-

34


Table 3 Groundwater minor elements data (in lg l1) recorded in the study area. It is noted that Mn, Pb, and Se violated the WHO limit (WHO, 2004), while other elements remain trace or otherwise no limit was established. (n = 59)

Date

Al

Ba

Be

Fe

Li

Mn

Pb

Se

Sr

B1

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

2.78 5.92 3.32 2.50 5.55 6.66

8.45 7.75 9.10 10.87 11.53 11.79

0.69 0.89 1.15 2.09 0.14 0.70

8.73 22.52 19.65 35.40 31.85 37.40

9.93 4.90 4.39 5.31 4.01 4.25

25.03 9.67 3.11 11.59 16.91 26.16

4.43 5.74 3.99 7.95 11.18 9.77

16.42 9.89 9.80 36.67 34.13 28.67

796.96 787.20 933.84 1037.49 1088.47 1008.87

B2

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

2.91 2.74 2.59 4.55 8.02 4.21

4.99 3.65 3.89 5.21 7.15 6.43

0.52 1.01 1.19 2.33 0.11 0.71

15.05 18.92 22.07 38.70 33.17 11.29

5.23 1.23 2.45 2.70 2.04 1.63

8.33 4.91 3.50 4.66 8.82 10.69

5.31 5.98 7.15 2.36 7.42 5.67

15.32 5.18 12.20 16.95 27.27 16.50

588.11 351.36 357.57 437.60 643.83 614.85

B3

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

9.59 9.76 6.05 5.94 6.35 7.99

8.94 10.81 11.42 13.98 14.61 11.21

0.19 0.80 0.89 2.10 0.34 0.72

30.74 21.90 25.17 38.98 30.42 23.04

7.66 5.26 4.44 4.80 3.77 2.52

22.05 13.54 7.72 19.76 10.12 17.94

5.08 5.48 4.79 4.14 8.41 4.85

6.95 13.83 19.33 36.59 19.02 49.44

735.08 931.07 1026.35 1207.75 1320.40 1014.48

B4

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

6.61 2.99 6.56 10.17 3.69 0.42

24.04 19.26 20.40 21.87 22.14 21.10

0.77 1.15 1.18 2.56 0.55 0.65

20.13 21.93 22.82 36.43 25.30 24.04

17.11 11.44 10.04 10.19 7.92 7.11

99.22 81.82 85.23 89.81 88.97 86.94

4.85 5.69 7.56 5.69 13.11 6.27

5.12 3.79 12.34 27.88 24.77 39.05

1377.98 1188.16 1302.83 1336.69 1409.71 1371.55

B5

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

1.34 3.10 1.91 10.48 5.69 5.65

11.61 12.83 15.22 18.84 16.46 17.78

0.66 1.09 1.11 2.36 0.46 0.69

22.62 24.51 20.53 38.09 35.19 18.92

1.42 0.72 1.31 2.40 2.28 2.79

55.92 7.85 1.31 1.75 1.67 8.93

3.67 5.72 3.28 1.35 7.81 10.18

11.41 12.50 12.79 33.05 27.44 27.95

1244.78 1624.94 2360.27 2742.58 2546.23 2410.00

B6

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

9.56 6.67 2.77 13.79 3.48 1.28

22.00 19.86 21.04 24.51 22.06 21.05

0.82 0.76 1.02 2.40 0.61 0.74

19.16 19.85 24.55 41.28 35.74 9.20

3.09 2.91 2.67 3.76 3.94 4.26

53.01 15.93 39.70 11.90 6.30 11.33

2.44 4.79 4.02 3.39 8.78 4.57

21.59 15.30 12.18 32.08 20.11 31.83

1685.87 2200.50 2433.95 2512.16 2199.76 2013.82

B7

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

3.51 8.49 3.43 15.03 6.61 NA

24.08 16.06 15.25 16.53 14.46 NA

0.73 1.00 1.19 2.28 0.63 NA

20.95 21.08 20.25 39.65 22.31 NA

4.24 4.01 3.56 4.39 4.00 NA

80.77 51.02 100.63 15.76 7.20 NA

4.66 3.94 3.69 2.26 7.96 NA

11.04 19.63 18.43 41.76 22.25 NA

1659.05 1693.54 2143.12 2172.80 1907.72 NA

B8

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

2.75 5.13 6.22 14.12 7.25 6.88

20.31 21.40 20.80 22.30 19.32 21.55

0.90 1.17 1.25 2.37 0.73 0.66

21.86 15.92 26.41 34.56 27.23 24.04

3.76 2.53 5.00 5.79 3.58 4.03

22.22 32.02 28.16 46.07 40.37 169.95

6.13 4.46 2.69 2.73 6.50 8.23

6.96 13.53 3.58 37.07 27.29 34.67

1503.45 1604.63 1614.58 1585.10 1362.61 1599.51

B9

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

12.46 4.49 6.11 11.05 3.69 6.91

21.87 22.60 21.21 23.39 21.55 26.88

0.95 1.28 1.31 2.36 0.52 0.80

18.54 13.49 23.59 39.10 33.54 25.69

3.62 6.36 6.08 6.16 3.60 6.47

123.98 117.66 154.91 162.77 67.79 152.02

5.42 14.03 6.37 2.21 14.26 5.28

2.80 12.02 7.82 28.01 27.26 9.92

1373.49 1512.89 1497.66 1463.99 1348.08 1694.28

B10

15/10/2008 14/11/2008 15/12/2008 17/01/2009 13/02/2009 16/03/2009

5.63 8.49 3.85 14.10 3.23 1.03

26.27 25.07 23.37 22.86 23.98 27.40

0.69 0.77 0.86 2.21 0.71 0.82

13.12 23.45 20.39 38.78 31.01 17.06

8.52 8.18 6.54 5.17 4.74 7.80

360.36 268.03 333.62 544.56 328.65 553.37

5.56 6.31 2.43 3.73 8.47 7.69

20.93 9.06 8.54 22.30 32.19 32.10

1628.61 1607.44 1537.97 1413.03 1425.87 1710.32

6.00 0.42 15.03 3.50 200 0

17.16 3.65 27.40 6.50 700 0

1.06 0.11 2.56 0.63 NA –

25.38 8.73 41.28 8.33 2000 0

4.92 0.72 17.11 2.88 NA –

80.24 1.31 553.37 122.13 500 3.39

5.90 1.35 14.26 2.81 10 8.47

20.25 2.80 49.44 11.15 10 79.66

1455.98 351.36 2742.58 563.35 NA –

Mean Minimum Maximum Std. deviation WHO limits Violation (%) NA = not available.


35

Fig. 7. Temporal and spatial variations of minor elements (a) Ba; (b) Li; (c) Mn; (d) SiO2; (e) Sr; and (f) Se. These elements did not exhibit noticeable temporal variations with exception to Se. However, spatial variations are quite perceptible in most boreholes as each borehole’s sample recorded a rather distinct chemical character.

wise, significant output (p < 0.001) was obtained for Barlett’s test of sphericity, explaining the presence of particular relationship between variables. Thus, this analysis could be regarded as fairly appropriate. High positive loadings of Na, EC, SO4, Li, K, Mg, and Cl in Factor 1 (F1) indicated that the groundwater chemical composition was largely influenced by marine signature as these ions were found to be preponderant in seawater (Trabelsi et al., 2007; Voudouris et al., 2000). Therefore, factor 1 could be associated with seawater intrusion into the shallow aquifer, which posed substantial control in affecting the groundwater chemistry in the lowland aquifer. Also, this factor is considered to reflect the ion-exchange reactions between groundwater and aquifer matrix corresponded to the positive loadings between Na, Mg, and K. This factor accounted for 26.17% of the variance with eigenvalues of 5.31, which presented the highest percentage in relation to the other factors. Factor 2 (F2) explained 16.62% of the variance and was mainly associated with Sr, Ca, Ba, and HCO3, represented the second high-

est percentage subsequent to F1. Such relatively high loadings strongly elucidate that the groundwater in the shallow aquifer is primarily controlled by calcite (represented by Ca) and aragonite (represented by Sr, Ba, and Ca) dissolution (Allison, 1996; Aris et al., 2007; Celle-Jeanton et al., 2009; Dowling et al., 2003; Jeevanandam et al., 2007). In this case, dissolution of aragonitic shell appears to be more coherent as aragonite crystal structure comprised a higher affinity towards Ba and Sr. Negative loading of pH in this factor was deemed reasonable as pH usually attained an inverse relationship with these ions of carbonate origin (Sr, Ca, Ba, and HCO3). In most carbonate environments, groundwater with high pH and elevated Ba concentration may results in the precipitation of Ba as witherite (BaCO3). However, the dissolved Ba concentration in our study was rather low, thus, suggests that precipitation of witherite was unlikely. Under normal circumstances, Ba released by dissolution or weathering would eventually be sorbed onto oxides and hydroxides (Kabata-Pendias and Pendias, 2005; Murray, 1975; Takesue et al., 2008). The ability of Ba in displacing other

36


Fig. 8. Overall Piper plot of groundwater samples collected during the study periods. Piper plots implied a re-freshening process which can be elucidated by a shifting route originated from (1) to (2) and finally to (3).

Fig. 9. Time series graph with sampling events plotted against EC and tidal level. The re-freshening process can be observed.

sorbed alkaline earth metals from oxides (MnO2, TiO2) further denotes the significance of minor element geochemistry in a carbonate-enriched aquifer. Factor 3 (F3) was corresponded to high positive loadings of H4SiO4 and Mn, which explained 13.09% of the total variance. This component is believed to be separated by two partial contributions, the first was related to weathering reactions; and the latter, derivatives from organic matter. Dissolved Mn appears to form complexes with low weight organic acids at the high elevation area and eventually migrated along the flow path due to regional head

gradients (Alloway, 1995; Lin et al., 2011). Both elements were grouped under a same component, probably attributed to the extensive occurrence of these ions in the inland area. Mn is believed to be originated from the inland area where organic matter predominates, whereas, H4SiO4 can be accounted for the occurrence of intensive silicates weathering notably kaolinite, micas, sodic-plagioclase and potassic-feldspars (supported by the results obtained from XRD analysis, not reported here) in the inland region. Dissolved H4SiO4 may be available from incongruent weathering of clay, quartz to a smaller extent, or dissolution of silicates,

C.Y. Lin et al. / Journal of Hydrology 432–433 (2012) 26–42 Table 4 Output of analysis of variance (ANOVA) for two independent factors. Based on the results, it is clear that tidal effect shows a stronger influence on groundwater chemistry over sampling events. Elements (n = 59)

pH Eh EC Ca Mg Na K HCO3 Cl SO4 H4SiO4 Al Ba Be Fe Li Mn Pb Se Sr * **

Sampling events

Tidal influence

F-values

Sig. (p)

F-values

Sig. (p)

1.155 1.068 0.667 0.527 0.030 1.912 1.061 0.080 1.757 1.077 0.073 6.093 0.120 10.579 3.406 1.357 0.464 11.417 0.293 0.117

0.322 0.351 0.517 0.593 0.971 0.157 0.353 0.923 0.182 0.348 0.930 0.004** 0.887 0.000** 0.040* 0.226 0.631 0.000** 0.747 0.890

0.277 16.996 3.014 1.063 1.461 1.801 4.555 0.472 3.209 5.263 0.106 2.448 0.281 20.189 0.224 1.513 0.041 28.447 17.338 0.255

0.601 0.000* 0.088 0.307 0.232 0.185 0.037* 0.495 0.079 0.025* 0.746 0.123 0.598 0.000** 0.638 0.224 0.840 0.000** 0.000** 0.616

Significance value p < 0.05. Significance level p < 0.01.

Table 5 Varimax rotated R-mode factor loading matrix. Five components were extracted from the rotated component matrix. (Variance and cumulative variance in %.) Variables

Na EC SO4 Li K Mg Cl Sr Ca pH Ba Mn H4SiO4 Be Al Fe Pb Se HCO3 Variance C. variance Eigenvalues

Componenta 1

2

3

4

5

0.957 0.887 0.872 0.867 0.826 0.648 0.587 0.244 0.088 0.083 0.147 0.016 0.049 0.058 0.058 0.128 0.052 0.306 0.306 26.168 26.186 5.307

0.118 0.252 0.053 0.015 0.315 0.277 0.303 0.876 0.872 0.657 0.657 0.002 0.360 0.125 0.093 0.005 0.047 0.006 0.512 16.620 42.788 4.081

0.006 0.104 0.102 0.373 0.131 0.046 0.236 0.077 0.379 0.025 0.644 0.947 0.874 0.004 0.093 0.066 0.041 0.058 0.080 13.086 55.874 2.431

0.041 0.037 0.031 0.008 0.044 0.056 0.037 0.120 0.012 0.282 0.056 0.037 0.011 0.848 0.764 0.660 0.619 0.293 0.028 12.198 68.072 1.693

0.071 0.127 0.195 0.028 0.016 0.530 0.350 0.058 0.155 0.317 0.019 0.008 0.105 0.070 0.036 0.481 0.575 0.664 0.575 10.221 78.294 1.364

Rotation converged in eight iterations. a Loadings greater than |0.5| were bold.

such as feldspars and other alumino-silicates minerals (Banks et al., 1998; Goldschmidt, 1970). Moderate to high positive loadings of Be, Al, and Fe were corresponded to Factor 4 (F4) with variance representing of 12.20%. Al and Fe were mainly derived from sesquioxides (Al2O3 and Fe2O3). Whereas, Be is commonly originates from terrestrial environment and appears to be associated with micas, which recorded of appreciable amount in most argillaceous soils and shales (Goldschmidt, 1970; Kabata-Pendias and Pendias, 2005). Hence, the groupings (Be, Al, and Fe) in this component well corroborated with the supposition of meteoric influence. In sequence of sedimentary rocks,

37

the behavior of Be strictly follows Al due to their similarity in ionic potentials (Goldschmidt, 1970; Kabata-Pendias and Pendias, 2005). As such, Al and Be were classified under the same component. During rock weathering, Be remains in the residuum and tends to resemble Al in its geochemical nature (Goldschmidt, 1970). Therefore, this factor can be implied as ‘‘meteoric driven lithogeneous components’’. Factor 5 (F5) was positively loaded with Pb, Se, and HCO3, explaining 10.22% of variance and 1.36 eigenvalues, reflecting dissolution process contributed from parent materials (probably shale and carbonaceous debris of sandstone), overlying calcareous deposits (Alloway, 1995; Kulp and Pratt, 2004) and tidal influence elements (Pb and Se in ANOVA test) to a smaller extent. In sedimentary rocks, high concentrations of Se, are frequently associated with the clay fraction of soils because of the abundance of free iron oxides and other strong absorbents. Se (IV) may form highly insoluble iron compounds such as ferric selenite (Fe2(OH)4SeO3) or iron selenide (FeSe) (Plant et al., 2005). Thus, soil with low sesquioxides and highly calcareous content tends to have high Se in the groundwater as Se became readily soluble (Kabata-Pendias and Pendias, 2005). Such statement is well reflected in the case of Manukan Island, where substantial amount of Se was found in the groundwater. Whereas, the geochemical characteristics of Pb somewhat resembled the divalent alkaline-earth group of metals; thus, Pb has the ability to replace K, Ba, Sr, and even Ca, both in minerals and in sorption sites (Kabata-Pendias and Pendias, 2005). In addition, argillaceous soil and shales commonly comprised prolific amount of Pb (Alloway, 1995; Kabata-Pendias and Pendias, 2005). Such implication evidently explains the condition in Manukan Island, where parent materials are mainly composed of interbedded sandstone and shales. In certain cases, Pb are found to be highly concentrated in calcareous soil due to the high affinity of Pb in replacing Ca, thereby constituted an appreciable percentage in most aragonite minerals (Hem, 1970; Alloway, 1995). Therefore, dissolution of Pb and Se from calcareous and parent materials were capable of explaining this factor. 3.5.3. Relationships among factor loadings The relationships between factor loadings (Fig. 10) were disclosed in a loading plot in order for one to better define the contribution of each variables to the factors listed above, so as to provide a complete information where inter-factorial relationship can be easily interpreted (Giammanco et al., 1998; Lambraski et al., 2004). Incidental grouping of variables were observed in Fig. 10a, b, c and d, respectively. The first graph (Fig. 10a) demonstrates two distinct groups, represented by variables derived from F1 (EC, Na, Li, SO4, Mg, and K) and F2 (Ca, Sr, Ba, and HCO3) as clustered up by two circles. The positive loadings between components F1 and F2 implied that both factors were closely related and interacted with each other. Positive loadings of Ca, Ba, HCO3, EC, and Na from both factors suggest that EC and Na played a substantial role in controlling the behavior of Ca, Ba, and HCO3 in the shallow aquifer, whereby an increase in groundwater salinity (represent by EC and Na) may in turn rendered dissolution reactions that liberate Ca, Ba, and HCO3. Conversely, the occurrence of negative loadings between Sr, Mg, and K clearly explained the affinity of displacement or cation substitution between these ions. Overall, both factors displayed negative loadings with respect to pH, suggesting pH did exert considerable effects in controlling those variables, yet, in an inverse behavior. The second graph (Fig. 10b) was corresponded by F3 and F4 which clearly revealed the weathering effects or contributions originate from the inland area. They were primarily accounted for H4SiO4, Mn (F3), and Al, Be, Fe (F4), indicating silicate weathering and organic matter decomposition for the former group and weathering of shales or sesquioxides for the latter. Other variables

38


Fig. 10. Relationships of factor score between different components were illustrated in loading plots. The relationships between components were depicted in (a) F1 and F2; (b) F3 and F4; (c) F4 and F5; and (d) F2 and F5, respectively.

depicted weak loadings thus were plotted adjacent to both axes. As a result, three explicit groupings were observed. Seawater components comprise distinctive characteristics and do not exhibit significant control in both factor loadings. Therefore, the variables (such as K, SO4, Mg, Na, EC, and Cl) were mostly distributed near to the interception point (axis). Similar distributions were observed for carbonate materials, e.g. Sr, HCO3 and Ca. In this graph (F3 against F4), pH contributed only minor effect on the weathering of terrigeneous materials such as alumino-silicates, sesquioxides, and organic matter. Positive loadings of HCO3, Mg, Se, Fe, Al, and Be explained the relationship between F4 and F5 (Fig. 10c). As discussed earlier, Al, Be and Fe were derived from sesquioxides and shale weathering; whereas, high positive loadings for Pb, HCO3, Mg, and Se were explained by multiple-sources derivation of shale, carbonaceous and argillaceous materials. Apart from that, the non-conservative behavior of these ions may also explained the occurrence of positive relationship between both factors to a limited extent (Aiuppa et al., 2003). Comparatively high loadings of Fe and Se suggested that both elements may be derived from the same origin (possibly geogenic) notably seleniferous soil from the inland area (Lin et al., 2011). High loadings of HCO3 was found in both factors (F2 and F5) implied that this anion is likely to control the behavior of other variables in the carbonate aquifer (Fig. 10d). Interpretations made based on the graph where carbonate minerals dissolution, particularly that of aragonite (constitutes of Ca, Sr, Ba, and HCO3), was considered as the main reactions with minor extent of soluble products resulting from high magnesium calcite (Mg and HCO3) (Jeevanandam et al., 2007) and shale dissolution (Se, Fe, and SO4). Accordingly, pH remains to exert considerable effects in governing the behavior and concentrations of these variables in the shallow aquifer (Lin et al., 2011).

Thus, by interpreting the plots among factor loadings, one could clearly distinguish the provenance of each component in the shallow groundwater. Apparently, elements in F1 explained the highest factor loadings of 26.17%, could be considered as completely distinct to the other components such as F2, F3, F4, and F5. These components (F2, F3, F4, and F5) can be elucidated by weak or negative loadings of marine derived components, notably Na, EC, SO4, Li, K, Mg, and Cl. F2 component reflected the dissolution of marine based materials, possibly from aragonitic coral fragments, relics of shells, authigenic as well as allogenic carbonate soils found in the coastal area. Consequently, this factor could be regarded as an independent factor that did not interfere by other factors. On the contrary, F3, F4, and F5 were mostly loaded with non-marine components or specifically geogenic elements. In fact, these components appear to display distinctive patterns and trends because they were primarily derived from inland sources, where interpretations may become complex and problematic attributed to masking effects from multiple sources such as silicate weathering. The general reaction for incongruent weathering of silicate minerals can be written as (Eq. (6)) (Ramanathan, 2007):

ðNa; K; Mg; CaÞsilicate þ H2 CO3 ! Na þ K þ Mg þ Ca þ H4 SiO4 þ HCO3

ð6Þ

In order to ascertain and classify sampling boreholes with different influential sources for management purposes, HCA was performed using averaged data with sampling locations considered as sole factor. 3.5.4. Hierarchical cluster analysis (HCA) The utilization of HCA has been proven to be coherent in groundwater chemistry studies by distinguishing data that behaves differently. Using HCA, the boreholes with comparable hyd-


39

Fig. 11. Dendrogram generated from cluster analysis based on the sampling boreholes to understand the major hydrogeochemical characteristic in the lowland area. Three main groups were differentiated namely Group 1 (B1, B2, B3); Group 2 (B5, B6, B7); and Group 3 (B8, B9, B10, B4).

rochemical characteristics were clustered into the same group. The visual compendiums of the clustering processes in current study were presented as a dendrogram. Based on the dendrogram, boreholes with similarities are mainly categorized into three distinguishable groups (Fig. 11). The first group (cluster 1) was constituted of boreholes B1, B2, and B3 which situated in proximal distance to the coast. The mineralogy of these soils were primarily a mixture of quartz sand, fine fraction of corals and biogenic shell fragments. Cluster 2 was located at the middle section of the transect which encompasses B5, B6, and B7. Whereas, third cluster was assorted with sampling boreholes B8, B9, B10, and B4. Station B4 was belonged to this group for its relatively similar hydrochemical nature with the inland stations. Generally, the first group sample boreholes were characterized by high K and Mg, indicated that these sampling sites were greatly affected by seawater intrusion, despite a lower concentration in Ca, Mn, Ba, Si, and Sr. Locations with moderate concentration of K, Ca, Ba, Mn, H4SiO4 and high Sr were included in the second cluster. Whereas, the third group was marked by locations with enriched Al, Ca, Ba, Mn, H4SiO4 and moderate K and Sr in response to considerable contribution from terrigeneous sources. Despite both clusters 2 and 3 being referred as inland boreholes, B5, B6, and B7 demonstrated relatively distinct groundwater chemistry as compared to B8, B9, and B10.

its close location to a pumping well. Continuous abstraction of groundwater from the operating well eventually lowered the groundwater level, thus resulted in the formation of cone of depression beneath the well (El-Kashouty and El-Sabbagh, 2005; Praveena et al., 2010). Seawater may have been drawn into the shallow aquifer from beneath and reached location even further inland. Comparable patterns were observed for other major seawater components such as Mg (Fig. 12d) and Ca (Fig. 12g), where B4 and B9 comprised remarkably higher concentration of these elements than the surrounding boreholes. Isoplethic maps (Fig. 12g–k) also depicted identical distribution patterns of Ca, Ba, Mn, H4SiO4, and Al across transect. These elements were characterized by gradual increase of dissolved concentration towards the vicinity of inland boreholes, suggesting substantial influence of these elements on the inland’s groundwater chemistry. Boreholes B5, B6, and B7 were found to be highly enriched with Sr, indicating plausible deposition of clastic aragonite shells or remnant coral fragments in locations with relatively sluggish water gradient, thereby promotes dissolution. Conversely, no appreciable trend was observed for Fe, Pb, and Se along transect, owing to the fact that these elements were much controlled by the temporal variability and tidal influences (p < 0.05).

3.7. Implications on groundwater potability in small islands 3.6. Geostatistical isoplethic map In small islands, particularly those with heavy pumping wells, it is especially essential to gain an understanding on the groundwater’s major and minor elements distribution in micro-scale level to visually delineate the effects of seawater on the shallow aquifer. This is salient when the groundwater in the aquifer is shallow and experienced periodical fluctuation of hydrodynamic components (groundwater level) in response to seawater intrusion (Edmunds and Shand, 2008). In order to provide a clear and simplified presentation, simple mapping using geostatistical tool warrants the best technique in observing the spatial variation of groundwater chemistry attributed to seawater intrusion (Fig. 12). At a micro-scale level (Fig. 12a, c, e, g, h, k, and m), the illustrated patterns corroborated well with the groupings generated by HCA. A substantial increase of EC, Na, Cl, and SO4 concentration provided a good indication of seawater signature. The distribution patterns of Na (Fig. 12b) and SO4 (Fig. 12f) evinced elevated concentration of these ions in B4 and B9 as a consequence to seawater intrusion. Despite the distal location from coast, B9 exhibited comparatively high Na and SO4. Such discrepancy can be explained by

Safe and potable groundwater is the most concern yet problematic issues in small islands among tropical countries, where influx of tourists are prolific. Hence, limits stipulated by World Health Organization (WHO, 2004) were included as comparison for the elements listed in this study (Table 1 and 2). It is assessed that 16.95%, 10.17%, and 55.93% of samples analyzed for EC, Na, and Cl, respectively, exceeded the permissible limit stipulated by WHO (Table 1). As mentioned previously, these elevated readings were mainly caused by the seawater intrusion into the shallow aquifer attributed to indiscriminate groundwater pumping activities. To prevent the saline condition from becoming worse, it is suggested that pumping activities should be halt promptly. Alternatively, usage of other freshwater resources such as collection of rainwater and importing freshwater from mainland should be taken into considerations. Present study showed that several samples analyzed for Mn, Pb, and Se have exceeded the WHO recommended guideline values, while other minor element remain trace. This is plausible because in shallow carbonate aquifer, these elements are prone to solubilization as carbonate-containing species (Suh, 2004). In fact, the

40


Fig. 12. Kriging isoplethic maps of selected parameters at the lowland area, (a) EC; (b) Na; (c) K; (d) Mg; (e) Cl; (f); SO4; (g) Ca; (h) Ba; (i) Mn; (j) H4SiO4; (k) Al; (l) Fe; (m) Pb; (n) Se and (o) Sr were presented in a micro-scale level. Units for EC: lS cm1; Na, K, Mg, Cl, SO4, Ca, H4SiO4: mgl1; Ba, Mn, Al, Fe, Pb, Se, Sr: lgl1. These maps are capable of assisting in identification of sources that control the groundwater chemistry.

dissolved Se derived from shale weathering was augmented by the low composition of sesquioxides which capable of adsorbing free

Se ions. Thus, elevated concentration of Se in groundwater of most sedimentary small island with sandy aquifer is common. The con-


41

centration of Se in Manukan Island ranged from 2.80 to 49.44 lg l1 with a mean value of 20.25 lg l1. There are as much as 79.66% of the groundwater samples exceeded the WHO limits of 10 lg l1. For Mn, it appears that only two samples were found to have exceeded the WHO limits (500 lg l1). Almost all samples showed the concentration of Pb falls below the WHO permissible limit of 10 lg l1, with exception to five samples. Overall, it is evident that the groundwater in Manukan Island was highly enriched with respect to EC, Na, Cl, Mn, Pb, and Se, thus, making the groundwater a potential health hazard if utilized as primary drinking water resource.

temporal and spatial variability of shallow groundwater chemistry on a small tropical island. Such effort made not only enabled the generation of holistic and reliable information for effective management of sustainable groundwater resources, but to enhance the understanding of seawater intrusion mechanism, specifically its influences in a small island’s aquifer. Hence, we fervently hope that the results from this study will spur others to adopt a comparable approach in their future research, especially those in a small island setting.

4. Conclusions

This research is financially supported by the Ministry of Science, Technology and Innovation, Malaysia (under Science Fund Grant No 04-01-10-SF0065). The first author (Chin Yik Lin) also would like to thank WFS (World Federation of Scientists) for providing his scholarship. Permission from the Sabah Park Trustees for the study site is highly appreciated. The authors would also like to thank anonymous reviewers for their useful comments and enlightened ideas. Lastly, the authors would like to thank Dr. Ahmad Zaharin Aris, Ms. Bibi Noorarlijannah Bt. Mohammad Ali, Ms. Chua Li Ying, Mr. Ng Lim Kuan Leang, Mr. Ong Jay Jim and Mr. Neldin Jeoffrey for their field assistance. Special acknowledgment is also due to Ms. Soon Wai Ping for her help during the period of sampling and samples analysis.

We studied the factors that influencing the groundwater’s spatial and temporal variability in an aquifer of a small tropical island. The results obtained in this study increase one’s knowledge on the occurrence of major and minor elements and their plausible sources in the shallow groundwater of a small island specifically within sedimentary setting. General conclusions are: 1. Most sampling locations exhibit gradual freshening over each sampling campaign, which can be explained by the sluggish flushing processes of freshwater from high relief area towards the shore. 2. Output from ANOVA implied that neither changes of tide level nor rainfall volume significantly influenced the major groundwater chemistry in the small island’s shallow aquifer. Only several minor elements such as Be, Se, and Pb were responsive towards tidal activity, while Al, Be, Fe, and Pb behave similarly towards rainfall volume. 3. Based on the multivariate analysis, it is suggested that marine intrusion, cation exchange reactions, carbonate and silicate weathering are the primary factors governing the major ion chemistry of the shallow aquifer. 4. The results of multivariate analysis showed that EC, Na, Cl, and SO4 had close association. Consensus obtained between FA and HCA further verified the aptness of multivariate techniques in describing the groundwater chemistry of the shallow sedimentary aquifer. Plotting concentrations of individual elements on an isoplethic map enabled the construction of a visualized spatial pattern of groundwater hydrochemistry in corroborating with the statistically defined HCA. 5. Current results suggested that the hydrographic, seawater intrusion and influence of terrigeneous materials were, in part, deterministic functions in generating a distinctive groundwater chemistry and evolution water types in a small island aquifer. Thus, present study conveyed understanding and meaningful information of general groundwater chemistry in a small island with sedimentary settings. Furthermore, current finding also contributes in improved mechanistic interpreting of seawater intrusion into an island aquifer with regards to spatial and temporal variability, thereby warrants a greater achievement in tackling such inherent problem. 6. The concentration of most minor elements emerged to be remained trace, with exception to elements such as Mn, Pb, and Se. Hence, the groundwater of many sampling locations within the shallow aquifer is not suitable for drinking purposes with regard to its high salinity and elevated concentration of several minor elements (Mn, Pb, and Se). Otherwise, chronic health problems might be expected with prolonged consumption. In conclusion, this study highlights the usefulness of combined statistical techniques in delineating factors that governing the

Acknowledgments

References Abdullah, M.H., Mokhtar, M.B., Tahir, S., Awaluddin, A., 1997a. Do tides affect water quality in the upper phreatic zone of a small oceanic island, Sipadan Island, Malaysia? Environ. Geol. 29 (1–2), 112–117. Abdullah, M.H., Musta, B., Tan, M.Md., 1997b. A preliminary geochemical study on Manukan Island. Sabah. Borneo Sci. 3, 43–51. Abdullah, M.H., Praveena, S.M., Aris, A.Z., Lin, C.Y., Musta, B., 2009. Numerical Modeling of Seawater Intrusion into Manukan Island’s Aquifer. Universiti Malaysia Sabah. Adams, S., Titus, R., Pietersen, K., Tredoux, G., Harris, C., 2001. Hydrochemical characteristics of aquifers near Sutherland in the Western Karoo, South Africa. J. Hydrol. 241, 91–103, PII: S0022-1694(00)00370-X. Aishah, A.W., Zauyah, S., Anuar, A.R., Fauziah, C.I., 2010. Spatial variability of selected chemical characteristics of paddy soils in sawah sempadan, Selangor. Malaysia. Malays. J. Soil. Sci. 14, 27–39. Aiuppa, A., Bellomo, S., Brusca, L., D’Alessandro, W., Federico, C., 2003. Natural and anthropogenic factors affecting groundwater quality of an active volcano (Mt. Etna, Italy). Appl. Geochem. 18, 863–882, PII: S0883-2927(02)00182-8. Allison, N., 1996. Geochemical anomalies in coral skeletons and their possible implications for paleoenvironmental analyses. Mar. Chem. 55, 367–379. Alloway, B.J., 1995. Heavy Metal in Soils. John Wiley and Son, Inc., New York. Andre, L., Franceschi, M., Pouchan, P., Atteia, O., 2005. Using geochemical data and modeling to enhance the understanding of groundwater flow in a regional deep aquifer, Aquitaine Basin, South-west of France. J. Hydrol. 305, 40–62. doi:10.1016/j.jhydrol.2004.08.027. APHA, (American Public Health Association), 1995. Standard Methods for the Examination of Water and Wastewater, 19th ed. American Water Works Association, Water Environment Federation, Washington. Appelo, C.A.J., Postma, D., 2005. Geochemistry, Groundwater and Pollution, second ed. Balkema, Rotterdam. Aris, A.Z., Abdullah, M.H., Kim, K.W., 2007. Hydrogeochemistry of groundwater in Manukan Island. Sabah. Malays. J. Anal. Sci. 11 (2), 407–413. Banks, D., Reimann, C., Skarphagen, H., 1998. The comparative hydrochemistry of two granitic island aquifers: the isle of Scilly, UK and the Hvaler Islands, Norway. Sci. Total. Environ. 209, 169–183, PII S0048-9697(97)00310-0. Basir, J., Sanudin, T., Tating, F.F., 1991. Late Eocene planktonic foraminifera from the Crocker Formation, Pun Batu. Sabah. Warta Geologi. 14 (4), 1–15. Brassington, R., 2007. Field Hydrogeology: The Geological Field Guide Series, third ed. John Wiley and Sons, Ltd., England. Celle-Jeanton, H., Huneau, F., Travi, Y., Edmunds, W.M., 2009. Twenty years of groundwater evolution in the triassic sandstone aquifer of lorraine: impacts on baseline water quality. Appl. Geochem. 24, 1198–1213. doi:10.1016/ j.apgeochem.2009.03.005. Ceron, J.C., Espinosa, R.J., Bosch, A.P., 2000. Numerical analysis of hydrogeochemical data: a case study (Alto Guadalentin, southeast Spain). Appl. Geochem. 15, 1053–1067, PII: S0883-2927(99)00105-5. Davison, C.C., Vonhof, J.A., 1978. Spatial and temporal hydrochemical variations in a semi-confined buried channel aquifer: Esterhazy, Saskatchewan, Canada. Ground Water 16 (5), 341–351.

42


Dogramaci, S.S., Herczeg, A.L., Bone, Y., 1998. 87Sr/86Sr in groundwater as indicators of carbonate dissolution. In: Arehart, G.B., Hulston, J.R. (Eds.), Water Rock Interaction. Francis and Taylor, Balkema, Rotterdam. Dou, L., Zhou, Y.Z., Ma, J., Li, Y., Cheng, Q.M., Xie, S.Y., Du, H.Y., You, Y.H., Wan, H.F., 2008. Using multivariate statistical and geostatistical methods to identify spatial variability of trace elements in agricultural soils in Dongguan City, Guangdong, China. J. China. Univ. Geosci. 19 (4), 343–353. Dowling, C.B., Poreda, R.J., Basu, A.R., 2003. The groundwater geochemistry of the Bengal basin: weathering, chemsorption, and trace metal flux to the oceans. Geochim. Cosmochim. Acta 67 (12), 2117–2136. doi:10.1016/S00167037(02)01306-6. Dykes, A.P., Gunn, J., 2006. Hoga Island, Sulawesi, Indonesia: geomorphology and groundwater resources of a small tropical carbonate island. Cave. Karst. Sci. 33 (1), 21–28. Edmunds, W.M., Shand, P., 2008. Natural Groundwater Quality. Blackwell Publishing, Ltd., USA. El-Kashouty, M., El-Sabbagh, A.A., 2005. Hydrogeology and hydrogeochemistry of the quaternary aquifer in the middle Nile delta area, Egypt. In: Ninth International Water Technology Conference, IWTC9 2005. Sharm El-Sheikh, Egypt. pp 395–414. Fernandes, P.G., Carreira, P., da Silva, M.O., 2008. Anthropogenic sources of contamination recognition – sines coastal aquifer (SW Portugal). J. Geochem. Explor. 98, 1–14. doi:10.1016/j.gexplo.2007.10.003. Freeze, R.A., Cherry, J.A., 1979. Groundwater. Prentice Hall, USA. Giammanco, S., Ottaviani, M., Valenza, M., Veschetti, E., Principio, E., Giammanco, G., Pignato, S., 1998. Major and trace elements geochemistry in the groundwaters of volcanic area: Mount Etna (Sicily, Italy). Water Res. 32 (1), 19–30, PII: S00431354(97)00198-X. Goldschmidt, V.M., 1970. Geochemistry. Oxford University Press, England. Grunsky, E.C., Drew, L.J., Sutphin, D.M., 2009. Process recognition in multi-element soil and stream-sediment geochemical data. Appl. Geochem. 24, 1602–1616. doi:10.1016/j.apgeochem.2009.04.024. Helena, B., Pardo, R., Vega, M., Barrado, E., Fernandez, J.M., Fernandez, L., 2000. Temporal evolution of groundwater composition in an alluvial aquifer (Pisuerga River, Spain) by principal component analysis. Water Res. 34, 807–816, PII: S0043-1354(99)00225-0. Hem, J.D., 1970. Study and interpretation of the chemical characteristics of natural waters. Geological Survey Water-Supply Paper 1473. Imrie, C.E., Korre, A., Munoz-Melendez, G., Thornton, I., Durucan, S., 2008. Application of factorial kriging analysis to the FOREGS European topsoil geochemistry database. Sci. Total. Environ. 393, 96–110. Isa, N.M., Aris, A.Z., 2012. Preliminary assessment on the hydrogeochemistry of Kapas Island. Terengganu. Sains Malaysiana. 41 (1), 23–32. Jayakumar, R., Siraz, L., 1997. Factor analysis in hydrogeochemistry of coastal aquifers – a preliminary study. Environ. Geol. 31 (3/4), 174–177. Jeevanandam, M., Kannan, R., Srinivasalu, S., Rammohan, V., 2007. Hydrogeochemistry and groundwater quality assessment of Lower Part of the Ponnaiyar River Basin, Cuddalore District, South India. Environ. Monit. Assess. 132, 263–274. doi:10.1007/s10661-006-9532-y. Kabata-Pendias, A.K., Pendias, H., 2005. Trace Elements in Soils and Plants. CRC Press, USA. Kulp, T.R., Pratt, L.M., 2004. Speciation and weathering of selenium in Upper Cretaceous chalk and shale from South Dakota and Wyoming, USA. Geochim. Cosmochim. Acta. 68 (18), 3687–3701. doi:10.1016/j.gca.2004.03.008. Lambraski, N., Antonakos, A., Panagopoulos, G., 2004. The use of multicomponent statistical analysis in hydrogeological environmental research. Water Res. 38, 1862–1872. doi:10.1016/j.watres.2004.01.009. Lin, Y.P., 2002. Multivariate geostatistical methods to identify and map spatial variations of soil heavy metals. Environ. Geol. 42, 1–10. Lin, Y.B., Lin, Y.I., Liu, C.W., Tan, Y.C., 2006. Mapping of spatial multi-scale sources of arsenic variation in groundwater on ChiaNan floodplain of Taiwan. Sci. Total. Environ. 370, 168–181. Lin, C.Y., Abdullah, M.H., Aris, A.Z., Praveena, S.M., 2009. A baseline study on groundwater quality of the tourist island, Pulau Tiga, Sabah, Malaysia. Mod. Appl. Sci. 3 (5), 62–74. Lin, C.Y., Abdullah, M.H., Musta, B., Aris, A.Z., Praveena, S.M., 2010. Assessment of selected chemical and microbial parameters in groundwater of Pulau Tiga, Sabah, Malaysia. Sains Malaysiana. 39 (3), 337–345.

Lin, C.Y., Abdullah, M.H., Musta, B., Aris, A.Z., Praveena, S.M., 2011. Stability behavior and thermodynamic states of iron and manganese in sandy soil aquifer, Manukan Island, Malaysia. Nat. Resour. Res. 20 (1), 45–56. doi:10.1007/s11053011-9136-2. Malaysian Meteorological Department, 2009. Rainfall data for KKIA from 1995 to 2009. Malaysian Meteorological Department Ministry of Science, Technology and Innovation, Kota Kinabalu, Sabah. Murray, J.W., 1975. The interaction of metal ions at manganese dioxides–solution interface. Geochim. Cosmochim. Acta. 39, 505–519. National Hydrographic Center, 2009. Tide Tables Malaysia 2009, vol. 2. (Sabah, Sarawak and Brunei). Ong, J., Aguda, N., Jaraula, C., Mateo, Z., Pascua, C., Foronda, J., 2000. Tidal effects on groundwater in a very small tropical island: a study on the groundwater resources of Pag-asa Island, Kalayaan Island Group. Sci. Diliman. 12 (2), 33–44. Panagopoulos, G., Lambrakis, N., Katagas, C., Papuolis, D., Tsolis-Katagas, P., 2005. Water-rock interaction induced by contaminated groundwater in a karst aquifer, Greece. Environ. Geol. 49, 300–313. doi:10.1007/s00254-005-0090-3. Plant, J.A., Kinniburgh, D.G., Smedley, P.L., Fordyce, F.M., Klinck, B.A., 2005. Arsenic and selenium. In: Lollar, B.S. (Ed.), Environmental Geochemistry. Elsevier, Amsterdam, Netherlands, p. 47. Praveena, S.M., Lin, C.Y., Aris, A.Z., Abdullah, M.H., 2010. Groundwater assessment at Manukan Island, Sabah: multidisplinary approaches. Nat. Resour. Res. 19 (4), 279–291. doi:10.1007/s11053-010-9124-y. Raju, N.J., 2006. Seasonal evaluation of hydrogeochemical parameters using correlation and regression analysis. Curr. Sci. 91 (6), 820–826. Ramanathan, A.A.L., 2007. Seasonal variation in the major ion chemistry of Pandoh Lake, Mandi District, Himachal Pradesh, India. Appl. Geochem. 22, 1736–1747. doi:10.1016/j.apgeochem.2007.03.045. Reghunath, R., Sreedhara Murthy, T.R., Raghavan, B.R., 2002. The utility of multivariate statistical techniques in hydrogeochemical studies: an example from Karnataka, India. Water Res. 36, 2437-2442. PII: S0043-1354(01)00490-0. Ruiz, F., Gomis, V., Blasco, P., 1990. Application of factor analysis to the hydrochemical study of a coastal aquifer. J. Hydrol. 119, 169–177. Sabbagh Yazdi, S.R., 2004. Numerical modeling of Persian Gulf salinity variations due to tidal effects. Int. J. Environ. Sci. Tech. 1 (1), 39–44. Saleh, A., Al-Ruwaih, F., Shehata, M., 1999. Hydrogeochemical processes operating within the main aquifers of Kuwait. J. Arid. Environ. 42, 195–209. Article No. jare. 1999.0511. Shyu, G.S., Cheng, B.Y., Chiang, C.T., Yao, P.H., Chang, T.K., 2011. Applying factor analysis combined with Kriging and information entropy theory for mapping and evaluating the stability of groundwater quality variation in Taiwan. Int. J. Environ. Res. Pub. Health 8, 1084–1109. doi:10.3390/ijerph8041084. Subba Rao, N., Prakasa Rao, J., John Devadas, D., Srinivasa Rao, K., Krishna, C., 2001. Multivariate analysis for identifying the governing factors of groundwater quality. J. Environ. Hydrol. 9 (14), 1–9. Suh, J.Y., 2004. Hydrogeochemical studies of groundwater from reclaimed land adjacent to Rozelle Bay, Sydney, Australia. Geosci. J. 8 (3), 301–312. doi:10.1007/BF02910249. Takesue, R.K., Bacon, C.R., Thompson, J.K., 2008. Influences of organic matter and calcification rate on trace elements in aragonitic estuarine bivalve shells. Geochim. Cosmochim. Acta. 72, 5431–5445. doi:10.1016/j.gca.2008.09.003. Todd, D.K., 1980. Groundwater Hydrology, second ed. John Wiley and Sons, USA. Trabelsi, R., Zairi, M., Dhia, H.B., 2007. Groundwater salinization of Sfax superficial aquifer, Tunisia. Hydrogeol. J. 15, 1341–1355. doi:10.1007/s10040-007-0182-0. Usui, T., Koike, I., Ogura, N., 1998. Tidal effect on dynamics of pore water nitrate in intertidal sediment of a Eutrophic Estuary. J. Oceanogr. 54, 205–216. Varol, M., Gökot, B., Bekleyen, A., Sßen, B., 2012. Spatial and temporal variations in surface water quality of the dam reservoirs in the Tigris River basin, Turkey. CATENA 92, 11–21. doi:10.1016/j.catena.2011.11.013. Voudouris, K., Panagopoulos, A., Koumantakis, J., 2000. Multivariate statistical analysis in the assessment of hydrochemistry of the Korinthia prefecture alluvial aquifer system (Peloponnese, Greece). Nat. Resour. Res. 9 (2), 135–146. doi:10.1023/A:1010195410646. WHO (World Health Organization), 2004. Guidelines for Drinking-Water Quality, Recommendations, third ed., vol. 1. Geneva, WHO. Xun, Z., Chuanxia, R., Yanyan, Y., Bin, F., Yeecheng, O., 2006. Tidal effects of groundwater levels in the coastal aquifers near Beihai, China. Environ. Geol. 51, 517–525. doi:10.1007/s00254-006-0348-4.