**1. Introduction**

Fluorine has the highest chemical reactivity among all known elements and occurs mainly as free fluoride ions in natural waters, although some fluoride complexes also exist under specific conditions [1]. In groundwater, the natural concentration of fluoride depends on the geological, chemical and physical characteristics of the aquifer, the porosity and acidity of the soil and rocks, the temperature and the action of other chemical elements [2]. Fluoride ion in drinking water is known for both beneficial and detrimental effects on health. Fluoride in small amounts is

an essential component for normal mineralization of bones and formation of dental enamel [3]. However, excessive intake of fluoride can cause dental and skeleton fluorosis [4, 5]. Due to its strong electronegativity, fluoride is attracted by positively charged calcium in teeth and bones [6]. Fluorosis is a considerable health problem worldwide, which is afflicting millions of people in many areas of the world, for example, East Africa [7–9] and India [10–12]. According to World Health Organization (WHO) Guidelines for Drinking Water Quality [13], the limit value for fluoride is 1.5 mg/L. The value of 1.5 mg/L is a guiding value, which may be changed based on climatic conditions like temperature, humidity, volume of water intake, fluoride from other sources, etc. for different regions of the world [14]. The source of water supplies in Yemen is mostly from groundwater accumulated during previous and current times [15]. Fluorosis continues to be an endemic problem in Yemen. More areas are being affected by fluorosis in different parts of the country. Recently, a report from General Authority of Rural Water Projects (GARWP) indicates markedly increasing in fluoride content in groundwater (between 2000 and 2006) in districts of some governorates such as Sana'a, Ibb, Dhamar, Taiz, Al-Dhalei and Raimah. The highest fluoride concentration in drinking water was reported in some districts of Sana'a governorate, especially Sanhan [16]. Most Yemenis dwelling in rural areas use deep well water for drinking and household works, and a large number of these wells are contaminated with fluoride in a concentration of 2.5–32 mg [14]. The present study aims to identify the intensity and the spatial extent of the existing groundwater contamination by fluoride in the study area and tries to identify sources pollution responsible for the current pollution of the affected areas through an analytical study in the southern part of the upper Wadi Rasyan of Taiz governorate in Yemen.

5.Taking, transporting and analyzing samples.

*DOI: http://dx.doi.org/10.5772/intechopen.91329*

program software.

6.Data processing and interpreting by using arc Map GIS and Minitab 18

*GIS and Statistical Evaluation of Fluoride Content in Southern Part of Upper Rasyan Aquifer…*

groundwater for drinking in the study area as a whole.

strategies to deal with groundwater.

9.Preparing the final reports (article).

was determined using DR 2800 spectrophotometer.

**2.1 Sampling**

**125**

**2.2 Statistical methods**

7.Viewing the results of the analysis on the maps in order to know the spatial distribution of fluoride concentration in groundwater of the study area. The spatial distribution of fluoride in groundwater samples in the study area is represented as a thematic layer using IDW tool in the arc Map GIS software program that was used to the prediction of an unknown value for fluoride of the rest of the study area that was not covered by analysis and thus gave the spatial distribution of the fluoride that used in assessing the suitability of

8.Using the results of the groundwater assessment quality to propose alternative

The sampling was collected in polyethylene bottles of 1000-ml capacity after rinsed with distilled water and the water of the well, through months in August, September and October, 2014. The fluoride concentration of groundwater samples

The Fisher test was used when comparing dichotomous data separately and Pearson's correlation coefficient for continuous variables. On the other hand, after verifying the hypotheses of normality and homogeneity, we used the nonparametric Kruskal-Wallis H to test whether three or more samples were drawn from the same population, or from populations with identical characteristics (distribution with the same median). An analysis of variance was used to study the difference in means between the different samples greater than or equal to three and in the multivariate analysis between our samples two by two we chose the Bonferroni test. In the study, Al-Hawban, Al-Burayhi and Hedran and Al-Dhabab sub-basins were all different samples. After, we performed logistic regression analysis. Fluoride was included as a dichotomous variable (lower or greater than 1.5 mg/L). Other variables with p-values < 0.2 in the univariate analysis were entered into the multivariate logistic regression model, which where taken into account in the multivariate logistic analysis. We studied the cause-effect association between the fluoride (lower or greater than 1.5 g/ml) and the included variables using odds ratio (OR). In our first model (crude model), we were satisfied only on the univariate analysis between each variable (independent factors) and the dichotomous concentration of fluoride (dependent variable). In a second model, we performed a simultaneous analysis between the independent variables and the dichotomous dependent variable of fluoride. In order to assess the accuracy of the estimates, we have indicated the 95% confidence interval (IC to 95%) of the average data. A p-value of less than

0.05 at 95% confidence level was considered as statistically significant.
