Spatial Distribution of Groundwater Quality Parameters in Al-Najaf City Using GIS and Geostatistics Techniques

The scarcity of water resources in arid areas, as well as the impact of agricultural and human activities on groundwater quantity and quality, need a greater emphasis on these resource quality evaluations. In this study, the groundwater quality in the governorate of Al-Najaf was investigated using geostatistical methods based on the kriging interpolation approach to interpolate values in regions where real data was not available, also groundwater samples were evaluated based on a variety of qualitative parameters. Linear Gaussian, exponential, stable, and quadratic were the semivariogram models the study examined, and archGIS software was extensively utilized to map the investigated data. The study concluded that the groundwater in this area is unsuitable neither for drinking purposes nor in most of the industries according to the Iraqi specifications. Wilcox and United States Salinity Laboratory (USSL) diagrams were used to analyse the accessible water wells in the area. The diagrams depicted that 95.8 percent of the available well water in the research region is unsuitable for irrigation due to the extremely high salinity and continued application of such water may result in the development of salt soils. Spatial examination of groundwater revealed serious problems with almost all groundwater parameters in terms of water appropriateness for drinking, irrigation, and other purposes.


Introduction
Groundwater quality is an important environmental issue that must be assessed and maintained based on its spatial distribution. Inadequate management of groundwater resources results in a decline in both quantity and quality of groundwater [1]. In Iraq, river water is the main source for drinking, agriculture or any other purpose, but in recent times, river water faces a lot of problems, particularly the lack of rainfall, industrial and runoff pollution which affect the quality of waters. Hence, there is a need to look for other sources of water or emphasize water assessment of the existing wells. Iraq is confronted with both water quality and quantity challenges, as a significant portion of its water demand is met by surface water. Groundwater resources have become increasingly significant as the world's population has grown and surface water resources have depleted for a variety of causes. Groundwater resources are extremely important in semi-arid areas of Iraq [2]. The geology of a certain place, seasonal fluctuations, and the composition of dissolved salts may all influence the quality of ground water. Ground water quality is mostly affected by severe pollution activities occurring on surface waterways [3]. Appropriate groundwater quality management measures necessitate the availability of trustworthy quantitative data on groundwater quality behaviour. The spatial behaviour of groundwater quality is urgently needed to be investigated. It is necessary to understand the spatial variation of groundwater quality to establish credible interpretations of groundwater quality and creating accurate estimations of quality at any given position in the aquifer. There are several ways for interpolating data. The samples are studied independently of their geographic position in traditional procedures; however, the samples 2 spatial location is also taken into account in geostatistics approaches. In another meaning, we have to be capable of creating a relationship between the distance and direction from one sample to another and the different quantities in samples [4]. Geostatistical analysis offers a collection of statistical models and methods for exploring data spatially and generating groundwater quality surface maps [5,6]. The Kriging interpolation approach, which is a geostatistical phrase referring to the optimum linear prediction of spatial processes, was used to interpolate values in regions where real data was not available. It is commonly used to interpolate geographical data in geology, hydrology, environmental monitoring, and other fields. ArcGIS assists in the creation of maps that provide the most accurate depiction of the data collection. It allows selecting the semivariogram type, interpolation technique, and mapping type; it makes use of the mathematical as well as statistical characteristics of the observed points [6,7]. The ArcGIS geostatistical analyst tool is useful for producing a continuous surface map based on sample point measurements saved in a point layer. The data contained in the point layer might represent water quality information, water table elevation, or depth to the water table. Geostatistical Analyst includes a number of tools for creating surfaces. These tools are useful for visualizing, analysing, and understanding spatial phenomena. Geostatistical approaches were used by many researchers to determine the spatial distribution of groundwater properties. Omran (2012) presented a simple approach for assessing the quality of groundwater and mapping its geographic Variation in irrigation appropriateness in Egypt's Southwestern Desert's Darb El-Arbaein region. The study reveals GIS's great efficiency in analysing complicated spatial data and mapping groundwater quality [8]. Eslami et al. (2013) employed interpolation techniques (IDW, Kriging, and Co-Kriging approaches) to assess spatial variations and interpolate ground water quality observed in a section of the Mianab plain. The results indicated that the kriging and Co-Kriging approaches outperformed the IDW approach [4]. Narany et al. (2014) create a new method for identifying locations with a high risk of nitrate contamination in Iran's Amol-Babol Plain. Using data from 147 monitoring wells, the indicator kriging approach was used to identify places with a high chance of nitrate contamination [9]. Sharma et al. (2015) applied ArcGIS to create water quality spatial distribution maps in Rajasthan, Tonk district. This appliance was used to analyse exploratory data. selecting the optimum semivariogram model, and cross-validation. The standard kriging interpolation methodology is used to create spatial distribution maps for all of the specified parameters [2]. The objectives of the study were to: (1) offer an overview of current groundwater quality; and (2) establish the spatial distribution of groundwater quality measures such as electrical conductivity EC, Calcium Ca +2 , Potassium K + , Magnesium Mg +2 , Sulphate SO 4 -, Total Dissolved Solids TDS, Chloride Cl − , pH, Sodium Na + , Bicarbonates HCO 3 and (3) to map irrigation water quality in the study area in order to identify places with the best quality for irrigation within the study area by using Geographical Information System GIS and Geostatistics techniques. This study will help engineers, decision-makers, and managers manage groundwater quality control operations.

Study area
The governorate of Najaf is located in southern Iraq (The Mid-Euphrates Region), It occupies 6.6 percent of Iraq, with total area of 28824 km2 and is located between latitudes 32°21 N and 29°50 N, longitudes 44°44 E and 42°50 E. Al-Najaf Governorate is divided into three qadhaas for administrative purposes (Al-Najaf, Al-Kufa and Al-Manatheria Qadhaas). Fig. 1 depicts these qadhaas [10]. The research region has a dry continental climate with a long hot dry summer with a substantial change in temperature between day and night and cold winter with little rain; this sort of environment leads to rising salt concentrations in water [11]. To make an evaluation of groundwater, twenty-four groundwater well were tested for chemical and physical parameters.

Data collection
During the years studied (2016, 2017), samples were gathered from (24) wells in the research region. The samples were analysed for chemical and physical parameters (Ca 2+ , Mg 2+ , Na + , K + , TDS, CL -, pH and the Electrical Conductivity (EC). The gathered samples were analysed by the General Authority for Groundwater using standard Methods procedures. The sampling containers had been washed at least three times with distilled water then sampling water before being used to collect samples. Pumping was performed in the wells until the temperature, conductivity, and pH levels stabilized and to avoid contaminated and stagnant water. For the collection of water samples, clean polyethylene bottles containers were used. Only the average of the measured values for the two years is taken due to lack of significant. A summary of water quality characteristics is presented in Table 1.

Phesio-chemechal analysis and water quality indices:
For the purpose of this analysis, a total of 24 groundwater sample were collected from different sites of AL-Najaf governorate. Water samples were analyzed for physical and chemical parameters to evaluate the groundwater quality for drinking, industrial, agricultural and irrigational purposes.

Geostatistical analysis:
The primary instrument employed to assess groundwater quality was the geostatistical method of analysis. To assess groundwater geographically across the state, the Kriging interpolation technique and the semivariogram modelling methodology were utilized. Initially, a test for the data normality has been done. The GIS program tools as histogram is indicted for this purpose. The data normality can be checked through the next measurement; if the mean and median are almost equal, skewness coefficient is near to zero and kurtosis is near to three then the distribution become normal distribution. Based on the previous measures none of the parameters showed normal distribution, as a result, the data has undergone a log transformation, as seen in Table 2. For the selected groundwater quality parameters, exponential, stable, linear Gaussian and quadratic semivariogram models were considered. Each parameter was investigated using all of the four semivariogram models. Following that, the most fitting semivariogram model was chosen by considering the spatial distribution of the data set as well as geostatistical properties as shown in Table  3. The Table shows  To forecast values at unknown places, both interpolation approaches employ the weights of neighbouring known values. Because stochastic approaches are statistical models, they are more flexible and allow for the investigation of data spatial autocorrelation. If the data is regularly distributed, kriging produces the most efficient results. There are two stages in kriging process: first, the data spatial structure it computed and then it generates a predicted surface. The Kriging approach uses the fitted model of a semivariogram, the spatial data relationship, and the values of known points surrounding the forecasted point to estimate an unknown value at a specific place [2].  Water quality maps for various water parameters were created, and the Kriging interpolation technique was used to interpolate surfaces. As a result, the final irrigation groundwater quality maps were created by superimposing the previously indicated grid data. The quality information of water was connected to the sample site (spatial) in ArcGIS, and maps depicting the spatial distribution were created to highlight variations in groundwater parameter concentrations at various places throughout the research region. Various water quality maps were created utilizing point data such as pH, EC, Ca 2+ , Mg 2+ , Na + , K + , TDS, CL -, HCO 3 -, SO 4 -, by using ArcMap GIS software as shown in the figs. (2 to 11) respectively.

Groundwater suitability for drinking purposes
Understanding groundwater quality is just as essential as understanding its quantity since it is the primary determinant of its usefulness for drinking, household, agricultural, and industrial applications. The extent of suitability of groundwater for drinking purposes is achieved by comparing the specifications developed by regional and international organizations and agencies. It may be unsafe to consume if it surpasses the allowed limits. The findings of the chemical properties of groundwater samples taken from the research region are shown in Table 1. Chemically, drinking water should be soft, low in dissolved salts, and devoid of harmful components. A comparison of the chemical analysis values of groundwater with the standard guidelines values recommended by (Iraqi specifications IQS 217/ 2009 and World Health Organization, 1996) was made. The pH values of groundwater range from 6.7 to 7.8; this indicates that the research area's groundwater is almost neutral in nature and within both IQS and WHO specifications. In the other hand 100% of the samples were out of specifications due to increasing concentrations of TDS, SO 4 and 95.8%, 83.3% due to total hardness (TH) and Na + respectively. The classification the groundwater quality for drinking is shown in Table 4.           Figure 10. Spatial Distribution of HCO3. Figure 11. Spatial Distribution of SO4.

Groundwater suitability for industrial use
Each industry requires specific quality of water, some industries require water of high quality equals to distilled water in purity like pharmaceutical and paper industry, others can use any type of water. The values of groundwater parameters in the study area were compared to the limits needed for each industry, results shown in Table 5. The comparison revealed that the groundwater quality tested was not suitable for most of the industries, only few wells were suitable for chemical industry and lesser (only two) for refinery industry.

Suitability of Groundwater for Animal Purposes
Almost all animals, unlike humans, can drink low-quality water. Table 6 presents a guideline of water quality characteristics for animal drinking purposes. The quality of groundwater samples from the study region was assessed, and the results demonstrates that water consider suitable for this purpose since nearly all the tested parameters were between the classes very good to good water quality limits in according to  Good water 20.8 500 Acceptable water -600 Can be use -700 Maximum limit - Acceptable water -4000 Can be use -6000 Maximum limit -

Suitability of Groundwater for Irrigation Purposes
Water chemical quality is an important aspect in determining whether or not water is suitable for irrigation. The concentration and content of dissolved chemicals in water determine its appropriateness for agricultural use. Water's suitability for irrigation is determined by the action of various mineral elements, both the soil and the plant are affected by the water. It is widely acknowledged that the types and intensity of issues caused by poor irrigation water quality varies. However, there is currently a widespread agreement that these issues may be classified into the subsequent primary categories: (a) salinity risk, (b) infiltration and permeability issues, (c) specific ion toxicity, and (d) other issues [16,17].

Salinity Hazard:
Electrical Conductivity (EC) provides adequate estimation of the salinity hazard of irrigation water on agricultural crops because of its reflection on the amount of total concentration of dissolved salts in the water [18]. As it's known, the amount of water that plants can use drops substantially as conductivity rises. In general, irrigation water with a conductivity of less than 750mhos/cm is satisfactory and causes no threat to most crops. Water with an extent of 750 to 2250mhos/cm is extensively utilized, and excellent crop development is attained under proper management and appropriate drainage conditions, but if leaching and drainage are insufficient, salty conditions will develop, while (EC) greater than 3000μmho/ cm may limit crop growth. In our study, (EC) varied in the range from 3590 to 11800μmho/ cm, Table  1. As a result, 100% of the samples have an EC greater than 2250 mho/cm, and continued application of such water may result in the development of salt soils [19]. In the current study, Wilcox and United States Salinity Laboratory (USSL) diagrams were used to analyse the accessible water wells in the area. The diagrams depicted that 95.8 percent of the available well water in the research region is unsuitable for irrigation due to the very high salinity danger (C4S1). The remaining samples (4.2 percent) are classified as high salinity hazards. In accordance with categorization methodology of USSL and Wilcox irrigation and water, 100 percent of water samples fell into the inappropriate group, the EC values of all studied wells indicate that they are unsuitable for irrigation (3590 to 11800) μS/cm, Table 8 [18,20].  [22]. Poor waters should not be utilized on clayey soils with limited permeability because it is typically unsuitable or unwanted for irrigation. However, it can have utilized to water plants with high tolerance to salt cultivated on already salty soils in order to prevent future fertility deterioration. [23,24].

Permeability and Infiltration Hazard (Sodium Hazard):
The sodium adsorption ratio, which is determined by the relative concentrations of sodium, magnesium, and calcium ions in water, is the most frequent water quality parameter that determines the standard rate of penetration of water (SAR) which is recommended by the salinity laboratory of the United States Department of Agriculture due to its direct relationship to soil adsorption. The main issue with excessive sodium levels is the influence on soil permeability and water penetration [11]. When elevated ions of sodium reduce the irrigation water arrival rate to the lowest layers of the soil, a permeability and infiltration hazard arises. When water has no permeability to the crop's roots to the degree that the crop demands, the lowered infiltration rate begins to have negative consequences. As a result, these salts begin to accumulate near the soil's surface. [16,17].
Water designed for agricultural usage should ideally have lower sodium ions concentrations and a higher percentage of calcium and magnesium ions concentrations [19,22].

Magnesium Hazard:
Soil productivity is also affected by magnesium ion concentration. Higher levels of magnesium in water will have a negative impact on crop yields as soils become more salty [19,22]. In our study, all of the groundwater samples had no magnesium hazard and these sources of water are appropriate for irrigation. When carbonates levels rise, ions of magnesium and calcium are induced to form insoluble minerals, leaving sodium as the predominate ion in solution [16]. The calcium and magnesium are precipitated as carbonates, and any residual carbonate or bicarbonate is left in solution as residual sodium carbonate (RSC).

Chloride (Toxicity Problem):
Chloride is required by plants at extremely low amounts and is usually found in waters that used for irrigation, it is harmful and at high quantities, may be toxic to some sensitive plants. Chlorides are usually soluble and participate to soil salinity (total salts content) [11]. Its harmful effects are instantly visible like burning or dying leaf tissue. Table 9 shows classifications of irrigation waters according to chloride content based on [25]. The chemical analysis of water showed that 37.5% of groundwater samples having chloride content between (141-350 ppm), as a result moderately tolerant plants harmed and 62.5% of samples exceeded the limits (more than 350), moreover, these wells water is unfit for irrigation and can cause severe troubles. Table 9. Classification of irrigation water due to chloride content [25].

Chloride (ppm)
Effects on crops samples%

Below 70
Usually harmless for all plants Nil

Above 350
Can cause severe troubles 62.5

Total Hardness (TH):
Total hardness resulted from Calcium and Magnesium Carbonates, Bicarbonates, Chlorides, and Sulphate [24]. In our study total hardness varied from 314.73 to 2904.90 mg/l, so 100% of the groundwater samples considered very hard water.

Geostatistical Analysis
The spatial distribution of groundwater quality over the research region was examined using four semivariogram models: exponential, linear Gaussian, stable, and quadratic. A visual evaluation of the maps and statistical features such as standard deviation, error percentage, and skewness presented in Table 3 were used to choose the semivariogram. For each of the four semivariograms, every groundwater quality parameter was examined with the kriging interpolation technique. Then the outcomes of the analysis were scrutinized further with the Iraqi and WHO Water Guidelines. The same procedure was conducted for all groundwater quality parameters determining the best semivariogram. Groundwater quality was spatially analysed for ten groundwater quality parameters. Variation of groundwater quality parameter concentrations was investigated and mapped in ( fig. 2 to fig 11). Spatial examination of groundwater revealed serious problems with almost all groundwater parameters in terms of water appropriateness for drinking, irrigation, and other purposes.

Conclusion
Groundwater has become a major supply of fresh water for agricultural and drinking uses in recent years, and the importance of groundwater for irrigation is growing by the day as more land is cultivated. The bulk of groundwater quality parameters have risen due to population increase and industrial expansion. The quality of groundwater and its appropriateness for drinking and agricultural uses were evaluated using the spatial interpolation techniques and hydro-chemical analysis of the available data. The results showed that 100% of the samples were out of specifications for drinking due to increasing concentrations of TDS, SO 4 and 95.8%, 83.3% due to total hardness (TH) and Na + respectively, furthermore high concentrations of TDS and large values of EC observed in the study area lead the majority of the well's water properties to be improper and unacceptable for irrigation purposes according to international irrigation criteria, and continued application of such water may result in the development of salt soils if leaching and drainage are insufficient.