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\setlength{\itemindent}{0pt}% \setlength{\parskip}{0pt}% \setlength{\itemsep}{0pt}% \setlength{\parsep}{2pt}% \def\makelabel##1{\upshape ##1}}% } {\end{list}\end{raggedright}} \newenvironment{specHead}[2]% {\vspace{20pt}\hrule\vspace{10pt}% \phantomsection\label{#1}\markright{#2}% \pdfbookmark[2]{#2}{#1}% \hspace{-0.75in}{\bfseries\fontsize{16pt}{18pt}\selectfont#2}% }{} \def\TheFullDate{2014-01-15 (revised: 15 January 2014)} \def\TheID{\makeatother } \def\TheDate{2014-01-15} \title{Application of AHP Model in Selection of Most Appropriate Area to Establish Soil Damp for Artificial Recharge of Underground Aquifers (Case Study: Tabas Basin)} \author{}\makeatletter \makeatletter \newcommand*{\cleartoleftpage}{% \clearpage \if@twoside \ifodd\c@page \hbox{}\newpage \if@twocolumn \hbox{}\newpage \fi \fi \fi } \makeatother \makeatletter \thispagestyle{empty} \markright{\@title}\markboth{\@title}{\@author} \renewcommand\small{\@setfontsize\small{9pt}{11pt}\abovedisplayskip 8.5\p@ plus3\p@ 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\definecolor{GJMediumGrey}{HTML}{6D6E70} \definecolor{GJLightGrey}{HTML}{929497} \renewenvironment{abstract}{% \setlength{\parindent}{0pt}\raggedright \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt \textcolor{GJBlue}{\large\bfseries\abstractname\space} }{% \vskip8pt \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt } \usepackage[absolute,overlay]{textpos} \makeatother \usepackage{lineno} \linenumbers \begin{document} \author[1]{Alireza Arabameri} \affil[1]{ Islamic Azad University} \renewcommand\Authands{ and } \date{\small \em Received: 10 December 2013 Accepted: 3 January 2014 Published: 15 January 2014} \maketitle \begin{abstract} In recent years, water exploitation has become greater for many reasons such as population growth, industrial development, urbanization growth and consequently increased demand for food products. Hence the rate of exploitation and consumption ground water become greater than recharge of them, in other words input of ground water system is less than its output and system with negative balance sheet has positive feedback and it is collapsing. Thus it is very significant to determine the suitable position for Artificial Recharge of ground water. One of the management methods for water resources is Multi Criteria Decision Making. The analytic hierarchy process (AHP) is a structured technique for dealing with complex decisions that was developed by Thomas L. Saaty in the 1980 year. It provides a comprehensive and rational framework for structuring a decision problem, for representing and quantifying its elements, for relating those elements to overall goals, and for evaluating alternative solutions. The base of this model is comparing variables by pair wise by Matrix relationship. In this way, pair wise of the effective variables on the concrete Pavement were considered and based on relative weights the output was extent. In the present research, combination of Indexing system Method with Analytical Hierarchy Process has been applied to assess the Selection of most appropriate area to establish soil damp for artificial recharge of underground aquifers. The findings of the research show that zone 3 with 0/3606 points promotes in first rank among 5 studied zones and thus it is the most appropriate zone for Artificial Recharge of ground waters, in contrast zone 5 with 0/1731 point goes down to the last rank and so it isn`t suitable for Artificial Recharge and zones (2,4,1) are located in next ranks. \end{abstract} \keywords{AHP Model, soil damp, artificial recharge.} \begin{textblock*}{18cm}(1cm,1cm) % {block width} (coords) \textcolor{GJBlue}{\LARGE Global Journals \LaTeX\ JournalKaleidoscope\texttrademark} \end{textblock*} \begin{textblock*}{18cm}(1.4cm,1.5cm) % {block width} (coords) \textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}} \end{textblock*} \let\tabcellsep& \section[{I. Introduction}]{I. Introduction}\par ran is one of the arid countries in second world arid continent means Asia The average of world annual rain is almost 860 millimeter. While this numbe in our country is almost 250 millimeter and in Yazd province is almost 61.2 millimeter that means less of ¼ average Iran's rain and less of ¼ average world rain \hyperref[b0]{(Ahmadi, 2006)} .of course, this amount in consecutive years wouldn't access in steady process and this irregularity in frame work of arid and torrential rains cause wore damage to human and physical environment relative to quantity. Yazd province as a third province content of critic focus for windy erosion after Kerman and Khorasan for reason of region abnormality such as decreasing rainfall and increasing temperature Severely involved with this phenomenon and desert consecutive such as subsidence of underground water sources. Thus it is necessary satiable program which in this way could control one of the biggest obstacles developments \hyperref[b1]{(Ali zadeh, 2003)}. Drought is a generally occurring phenomenon which its effects intensify gradually. In some cases drought continues for longer time and causes destructive damages to human communities. During recent years climate change impacts have been combined with drought effects and caused serious problems in different parts of the World. Characteristics of a drought event are not often easily known until it occurs. During 1967 to 1992, about 50\% of the 2.8 billion people who suffered from all natural disasters, have been affected by relatively sever drought. From 3.5 million people who were killed by disasters, about 1.3 million were victims of the drought {\ref (Obasi, 1994)}. About 50\% of the World intensive populated regions containing the most agricultural lands are very vulnerable to the drought (USDA, 1994). Since these resources are 99\% of whole available fresh water, it is necessary to determine and exploit the ground water {\ref (Kouthar, 1986-19)}. Furthermore, it includes 80\% of being used resources in arid and semi-arid areas in most countries {\ref (Sedaghat, 1994)}. Due to Iran`s situation in desert and semi-desert area and its average annual rainfall about 250 mm, so there were many ways to prepare fresh water for agriculture, drinking and industry in different parts of country from a long time ago. Therefore, determination and zoning the most appropriate area for artificial recharge of underground aquifers should be considered in this plain. There are many examples of applications of artificial recharge of ground water in literature For instance: Saraf and Choudhury (1998) used remote sensing capabilities in extracting different layers like land usage, geomorphology, vegetation, and their integration in GIS environment to determine the most suitable area for artificial recharge of ground water. {\ref Mahdavi (1997, 16}) investigated water management and artificial recharge of ground water in Jourm city and indicated that controlling usage and recharge of water tables by the watershed management is the main management technique. Abdi and Ghayoumian (2001, 86) prioritized the suitable areas for storing surface water and reinforcing ground water based on geophysics data, land usage, topography, their integration and analysis in GIS environment. The purpose of this study is Application of AHP Model in Selection of most appropriate area to establish soil damp for artificial recharge of underground aquifers. \section[{II. Methods and Materials}]{II. Methods and Materials}\par a) Mathematical situation of studied area Tabas Basin with 5056/9 KM2 Being situated in the Yazd Province, Tabas Basin is bounded by 33º, 15' latitude to 33º, 57' north latitude and 56º, 25' to 57º and 23' longitude (Figure \hyperref[fig_0]{1}). Firstly, studied area was investigated by the satellite images of Google Earth and its limitations were determined. Then digital elevation model of area was separated from its digital elevation model in Iran in the environment of soft ware Global Mapper and the output was received. Required data layers for zoning in the environment of software Arc GIS 9.3 was prepared as following: First, digital elevation model classified in to 5 elevation classes based o natural breaks in the heights of the area. Mentioned classes represent the studied zones in the area and subsequent calculations were done in each of these classes. Slope layer prepared base on digital elevation model on the area by surface analyses tool in 3D analyses. There were different processes to prepare drainage density layer and habitual density such as digitizing main and minor waterways layers on the topographical map1:50000 of the area, digitizing main and minor fault on geological map 1:100000 of area and density tool in Spatial Analyses.\par Iso-Precipitation layer prepared by interpolating method like cringing technique and linear relationship between rain-height using Interpolate tools in 3D analyses . Second, the investigated criteria for each height zones were calculated and their layers prepared separately. After achieving a few numbers in each layer, the numbers were analyzed by AHP method. Then considered watershed was ranked to select the best area for establishing soil damp. The Analytic Hierarchy Process (AHP) is an approach that is suitable for dealing with complex systems related to making a choice from among several alternatives and which provides a comparison of the considered options. This method was first presented by Saaty (Saaty, 1980). The AHP is based on the subdivision of the problem in a hierarchical form. The AHP helps the analysts to organize the critical aspects of a problem into a hierarchical structure similar to a family tree. By reducing complex decisions to a series of simple comparisons and rankings, then synthesizing the results, the AHP not only helps the analysts to arrive at the best decision, but also provides a clear rationale for the choices made. The objective of using an analytic hierarchy process (AHP) is to identify the preferred alternative and also determine a ranking of the alternatives when all the decision criteria are considered simultaneously (Saaty, 1980). Process steps are as follows:\par Step 1 : building a hierarchy. Step 2: determining the coefficients of the importance standards and sub-criteria: To determine the coefficients (weights) of the criteria and sub-criteria to compare the two to two. Judgment based on the quantitative comparison table below (Table \hyperref[tab_0]{1}). Step 3: Preparation of paired comparisons matrices and normalization factors: Then the values for each pairwise comparison matrix columns together and each element in matrix paired comparisons were divided into the sum of a column that normalized the paired comparison matrix normalized (Equation \hyperref[formula_0]{1}). Then calculate mean of the elements in each row of the matrix that results in is created normalized weight vector (Equation \hyperref[formula_1]{2}).r ij = a ij ? a ij m i=1\textbf{(1)}W i = ? r ij n i=1 n\textbf{(2)}\par In these equations m: number of columns, n: number of rows, aij: paired comparison of matrix elements rij: Options for normalization of matrix elements i, j index i, and Wi: weight of i-th item.\par Step 4: Determine the final score factors (preferences and priorities): At this stage, the fusion coefficients are determined by the final score of each of the options. For this purpose, can be used the hierarchical composition of the resulting priority vector with respect to all judges at all levels of the hierarchical (Bertolini et al, 2006; Moreno-Jiminez et al, 2005) .\par In other words, the final score of each of the routes be determined of the sum of the coefficients of integration options and criterion (Equation {\ref 3}).V H = ? W k ?g ij ? n k=1\par In this respect is: VH: My final choice j, WK: The weight of each criterion and gij: weighing the options regarding the criteria.\par Step 5: Calculate the compatibility or incompatibility system: To calculate the rate of adaptability must first paired comparison matrix (A) of the weight vector (W) is multiplied to obtain a good approximation of ? max W ? max W that is A × W = ? max W. Dividing the ? max value of ? max W of W is calculated. Then inconsistency index is calculated of the equation ( {\ref 4} \section[{IV. Discussion}]{IV. Discussion}\par The analytical hierarchy procedure (AHP) is proposed by Saaty {\ref (Saaty, 1980)}. AHP was originally applied to uncertain decision problems with multiple criteria, and has been widely used in solving problems of ranking, selection, evaluation, optimization, and prediction decisions. The AHP method is expressed by a unidirectional hierarchical relationship among decision levels. The top element of the hierarchy is the overall goal for the decision model. The hierarchy decomposes to a more specific criterion in which a level of manageable decision criteria is met {\ref (Mianabadi \& Afshar, 2008]}. Under each criteria, sub-criteria elements related to the criterion can be constructed. The AHP separates complex decision problems into elements within a simplified hierarchical system {\ref (Limon \& Martinez, 2006)}. The AHP usually consists of three stages of problem solving: decomposition, comparative judgment, and synthesis of priority. The decomposition stage aims at the construction of a hierarchical network to represent a decision problem, with the top level representing overall objectives and the lower levels representing criteria, subcriteria and alternatives. With comparative judgments, expert users are requested to set up a comparison matrix at each hierarchy by comparing pairs of criteria or sub-criteria. Finally, in the synthesis of priority stage, each comparison matrix is then solved by an eigenvector method for determining the criteria importance and alternative performance. The purpose of the AHP Method in this paper is Application of AHP Model in Selection of most appropriate area to establish soil damp for artificial recharge of underground aquifers. The results of AHP method for This Purpose showed in tables (3) to (13) and figures \hyperref[b6]{(7,}\hyperref[b7]{8)}. \section[{V. Conclusion}]{V. Conclusion}\par Decision making problem is the process of finding the best option from all of the feasible alternatives. In almost all such problems the multiplicity of criteria for judging the alternatives is pervasive. That is, for many such problems, the decision solve a multiple criteria decision making (MCDM) problem. A survey of the MCDM methods has been presented by Hwang and Yoon \hyperref[b9]{(Hwang, 1981)}. The analytic hierarchy process (AHP) is one of the extensively used multi-criteria decision-making methods One of the main advantages of this method is the relative ease with which it handles multiple criteria. In addition to this, AHP is easier to understand and it can effectively handle both qualitative and quantitative data. The use of AHP does not involve cumbersome mathematics. AHP involves the principles of decomposition, pairwise comparisons, and priority vector generation and synthesis. Though the purpose of AHP is to capture the expert's knowledge, the conventional AHP still cannot reflect the human thinking style. Therefore, fuzzy AHP, a fuzzy extension of AHP, was developed to solve the hierarchical fuzzy problems. In the fuzzy-AHP procedure, the pairwise comparisons in the judgment matrix are fuzzy numbers that are modified by the designer's emphasis. The findings of the research show that zone 3 with 0/3606 points promotes in first rank among 5 studied zones and thus it is the most appropriate zone for Artificial Recharge of ground waters, in contrast zone 5 with 0/1731 point goes down to the last rank and so it isn`t suitable for Artificial Recharge and zones (2,4,1) are located in next ranks. \begin{figure}[htbp] \noindent\textbf{1}\includegraphics[]{image-2.png} \caption{\label{fig_0}Figure 1 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{2}\includegraphics[]{image-3.png} \caption{\label{fig_2}Figure 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{4}\includegraphics[]{image-4.png} \caption{\label{fig_3}Figure 4 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{6}\includegraphics[]{image-5.png} \caption{\label{fig_4}Figure 6 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{}\includegraphics[]{image-6.png} \caption{\label{fig_5}}\end{figure} \begin{figure}[htbp] \noindent\textbf{5}\includegraphics[]{image-7.png} \caption{\label{fig_6}( 5 )}\end{figure} \begin{figure}[htbp] \noindent\textbf{7}\includegraphics[]{image-8.png} \caption{\label{fig_8}Figure 7 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{8}\includegraphics[]{image-9.png} \caption{\label{fig_9}Figure 8 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{1} \par \begin{longtable}{P{0.15093457943925231\textwidth}P{0.6990654205607476\textwidth}} Numerical values\tabcellsep Preferences (judging verbal)\\ 9\tabcellsep Extremely preferred\\ 7\tabcellsep Very strongly preferred\\ 5\tabcellsep Strongly preferred\end{longtable} \par {\small\itshape [Note: © 2014 Global Journals Inc. (US) -]} \caption{\label{tab_0}Table 1 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{2} \par \begin{longtable}{P{0.7186363636363636\textwidth}P{0.007727272727272727\textwidth}P{0.007727272727272727\textwidth}P{0.019318181818181818\textwidth}P{0.015454545454545453\textwidth}P{0.019318181818181818\textwidth}P{0.019318181818181818\textwidth}P{0.019318181818181818\textwidth}P{0.02318181818181818\textwidth}} n\tabcellsep 1\tabcellsep 2\tabcellsep 3\tabcellsep 4\tabcellsep 5\tabcellsep 6\tabcellsep 7\tabcellsep ...\\ I.I.R\tabcellsep 0\tabcellsep 0\tabcellsep 0/58\tabcellsep 0/9\tabcellsep 1/12\tabcellsep 1/24\tabcellsep 1/32\tabcellsep ...\\ \multicolumn{5}{l}{If the inconsistency rate less than or equal to}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{5}{l}{0.1, system consistency is acceptable, If more than 0.1}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{5}{l}{is better to reconsider its decision on the judgment (Dey}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \& Ramcharan , 2000).\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_1}Table 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{3} \par \begin{longtable}{P{0.25575221238938056\textwidth}P{0.027581120943952802\textwidth}P{0.037610619469026545\textwidth}P{0.04764011799410029\textwidth}P{0.017551622418879056\textwidth}P{0.07020648967551622\textwidth}P{0.03510324483775811\textwidth}P{0.06769911504424779\textwidth}P{0.025073746312684365\textwidth}P{0.08525073746312684\textwidth}P{0.09026548672566372\textwidth}P{0.09026548672566372\textwidth}} According to Purpose\tabcellsep slope\tabcellsep Altitude\tabcellsep Density\tabcellsep Stream\tabcellsep Fault Density\tabcellsep Area\tabcellsep Density\tabcellsep Habitate\tabcellsep Rainfall\tabcellsep Temperature\tabcellsep Wij\\ slope\tabcellsep 1\tabcellsep 3\tabcellsep \multicolumn{2}{l}{0.20}\tabcellsep 0.25\tabcellsep 5\tabcellsep \multicolumn{2}{l}{0.17}\tabcellsep 0.14\tabcellsep 0.20\tabcellsep 0.06\\ Altitude\tabcellsep \tabcellsep 1\tabcellsep \multicolumn{2}{l}{0.25}\tabcellsep 0.33\tabcellsep 2\tabcellsep \multicolumn{2}{l}{0.20}\tabcellsep 0.13\tabcellsep 0.33\tabcellsep 0.04\\ Stream Density\tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 2\tabcellsep 5\tabcellsep \tabcellsep 3\tabcellsep 2\tabcellsep 6\tabcellsep 0.27\\ Fault Density\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 3\tabcellsep \multicolumn{2}{l}{0.50}\tabcellsep 0.25\tabcellsep 5\tabcellsep 0.12\\ Area\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep \multicolumn{2}{l}{0.25}\tabcellsep 0.17\tabcellsep 0.50\tabcellsep 0.03\\ Habitate Density\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 3.00\tabcellsep 0.15\\ Rainfall\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 4\tabcellsep 0.26\\ Temperature\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.07\\ Sum\tabcellsep 27.53\tabcellsep 27.50\tabcellsep \multicolumn{2}{l}{3.15}\tabcellsep 10.12\tabcellsep 28.00\tabcellsep \multicolumn{2}{l}{8.45}\tabcellsep 4.27\tabcellsep 20.03\tabcellsep 1\end{longtable} \par \caption{\label{tab_2}Table 3 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{4} \par \begin{longtable}{P{0.25660377358490566\textwidth}P{0.044103773584905664\textwidth}P{0.07216981132075471\textwidth}P{0.08419811320754718\textwidth}P{0.10023584905660378\textwidth}P{0.11627358490566037\textwidth}P{0.17641509433962266\textwidth}} According to Rainfall\tabcellsep Region 1\tabcellsep Region 2\tabcellsep Region 3\tabcellsep Region 4\tabcellsep Region 5\tabcellsep Wij\\ Region 1\tabcellsep 1\tabcellsep 0.33\tabcellsep 0.20\tabcellsep 0.14\tabcellsep 0.11\tabcellsep 0.034137\\ Region 2\tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 0.20\tabcellsep 0.14\tabcellsep 0.066919\\ Region 3\tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.20\tabcellsep 0.33\tabcellsep 0.141229\\ Region 4\tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 0.258897\\ Region 5\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.498817\\ Sum\tabcellsep 25\tabcellsep 16.33\tabcellsep 9.53\tabcellsep 4.54\tabcellsep 1.92\tabcellsep 1\end{longtable} \par \caption{\label{tab_3}Table 4 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{5} \par \begin{longtable}{P{0.30357142857142855\textwidth}P{0.056377551020408166\textwidth}P{0.07372448979591836\textwidth}P{0.09107142857142857\textwidth}P{0.07372448979591836\textwidth}P{0.06505102040816327\textwidth}P{0.18647959183673468\textwidth}} According to Stream Density\tabcellsep Region 1\tabcellsep Region 2\tabcellsep Region 3\tabcellsep Region 4\tabcellsep Region 5\tabcellsep Wij\\ Region 1\tabcellsep 1\tabcellsep 0.33\tabcellsep 0.20\tabcellsep 3\tabcellsep 5\tabcellsep 0.13435\\ Region 2\tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 5\tabcellsep 7\tabcellsep 0.260232\\ Region 3\tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 7\tabcellsep 9\tabcellsep 0.502819\\ Region 4\tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 3\tabcellsep 0.067778\\ Region 5\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.034821\\ Sum\tabcellsep 9.53\tabcellsep 4.68\tabcellsep 1.79\tabcellsep 16.33\tabcellsep 25\tabcellsep 1\end{longtable} \par \caption{\label{tab_4}Table 5 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{6} \par \begin{longtable}{P{0.265625\textwidth}P{0.04869791666666666\textwidth}P{0.07526041666666666\textwidth}P{0.09296875\textwidth}P{0.08411458333333333\textwidth}P{0.09296875\textwidth}P{0.19036458333333334\textwidth}} According to Area\tabcellsep Region 1\tabcellsep Region 2\tabcellsep Region 3\tabcellsep Region 4\tabcellsep Region 5\tabcellsep Wij\\ Region 1\tabcellsep 1\tabcellsep 0.14\tabcellsep 0.11\tabcellsep 0.20\tabcellsep 0.33\tabcellsep 0.034821\\ Region 2\tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 3\tabcellsep 5\tabcellsep 0.260232\\ Region 3\tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 5\tabcellsep 7\tabcellsep 0.502819\\ Region 4\tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 3\tabcellsep 0.13435\\ Region 5\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.067778\\ Sum\tabcellsep 25\tabcellsep 4.68\tabcellsep 1.79\tabcellsep 9.53\tabcellsep 16.33\tabcellsep 1\end{longtable} \par \caption{\label{tab_5}Table 6 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{7} \par \begin{longtable}{P{0.2860975609756098\textwidth}P{0.05804878048780488\textwidth}P{0.07048780487804879\textwidth}P{0.08707317073170731\textwidth}P{0.07878048780487805\textwidth}P{0.08707317073170731\textwidth}P{0.1824390243902439\textwidth}} According to Fault Density\tabcellsep Region 1\tabcellsep Region 2\tabcellsep Region 3\tabcellsep Region 4\tabcellsep Region 5\tabcellsep Wij\\ Region 1\tabcellsep 1\tabcellsep 0.14\tabcellsep 0.11\tabcellsep 0.20\tabcellsep 0.33\tabcellsep 0.037844\\ Region 2\tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 3\tabcellsep 5\tabcellsep 0.205806\\ Region 3\tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 5\tabcellsep 7\tabcellsep 0.530032\\ Region 4\tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 3\tabcellsep 0.149469\\ Region 5\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.076849\\ Sum\tabcellsep 18.14\tabcellsep 4.68\tabcellsep 1.79\tabcellsep 9.53\tabcellsep 16.33\tabcellsep 1\end{longtable} \par \caption{\label{tab_6}Table 7 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{8} \par \begin{longtable}{P{0.27146596858638744\textwidth}P{0.06230366492146596\textwidth}P{0.0756544502617801\textwidth}P{0.09345549738219895\textwidth}P{0.08900523560209424\textwidth}P{0.06675392670157068\textwidth}P{0.1913612565445026\textwidth}} According to Slope\tabcellsep Region 1\tabcellsep Region 2\tabcellsep Region 3\tabcellsep Region 4\tabcellsep Region 5\tabcellsep Wij\\ Region 1\tabcellsep 1\tabcellsep 0.20\tabcellsep 0.14\tabcellsep 0.33\tabcellsep 3\tabcellsep 0.067778\\ Region 2\tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 3\tabcellsep 7\tabcellsep 0.260232\\ Region 3\tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 5\tabcellsep 9\tabcellsep 0.502819\\ Region 4\tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 5\tabcellsep 0.13435\\ Region 5\tabcellsep \tabcellsep \tabcellsep \tabcellsep 0\tabcellsep 1\tabcellsep 0.034821\\ Sum\tabcellsep 16.33\tabcellsep 4.68\tabcellsep 1.79\tabcellsep 9.53\tabcellsep 25\tabcellsep 1\end{longtable} \par \caption{\label{tab_7}Table 8 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{9} \par \begin{longtable}{P{0.2661214953271028\textwidth}P{0.043691588785046725\textwidth}P{0.07149532710280374\textwidth}P{0.08341121495327103\textwidth}P{0.09929906542056074\textwidth}P{0.11518691588785045\textwidth}P{0.17079439252336448\textwidth}} According to Temperature\tabcellsep Region 1\tabcellsep Region 2\tabcellsep Region 3\tabcellsep Region 4\tabcellsep Region 5\tabcellsep Wij\\ Region 1\tabcellsep 1\tabcellsep 0.33\tabcellsep 0.20\tabcellsep 0.14\tabcellsep 0.11\tabcellsep 0.034821\\ Region 2\tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 0.20\tabcellsep 0.14\tabcellsep 0.067778\\ Region 3\tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 0.20\tabcellsep 0.13435\\ Region 4\tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 0.260232\\ Region 5\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.502819\\ Sum\tabcellsep 25\tabcellsep 16.33\tabcellsep 9.53\tabcellsep 4.68\tabcellsep 1.79\tabcellsep 1\end{longtable} \par \caption{\label{tab_8}Table 9 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{10} \par \begin{longtable}{P{0.28186528497409324\textwidth}P{0.0616580310880829\textwidth}P{0.07487046632124351\textwidth}P{0.09248704663212434\textwidth}P{0.08367875647668394\textwidth}P{0.06606217616580311\textwidth}P{0.1893782383419689\textwidth}} According to Altitute\tabcellsep Region 1\tabcellsep Region 2\tabcellsep Region 3\tabcellsep Region 4\tabcellsep Region 5\tabcellsep Wij\\ Region 1\tabcellsep 1\tabcellsep 0.20\tabcellsep 0.14\tabcellsep 0.33\tabcellsep 3\tabcellsep 0.067778\\ Region 2\tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 3\tabcellsep 7\tabcellsep 0.260232\\ Region 3\tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 5\tabcellsep 9\tabcellsep 0.502819\\ Region 4\tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 5\tabcellsep 0.13435\\ Region 5\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.034821\\ Sum\tabcellsep 16.33\tabcellsep 4.68\tabcellsep 1.79\tabcellsep 9.53\tabcellsep 25\tabcellsep 1\end{longtable} \par \caption{\label{tab_9}Table 10 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{11} \par \begin{longtable}{P{0.3\textwidth}P{0.05416666666666666\textwidth}P{0.049999999999999996\textwidth}P{0.07916666666666666\textwidth}P{0.09166666666666667\textwidth}P{0.09583333333333333\textwidth}P{0.17916666666666667\textwidth}} According to Habitate Density\tabcellsep Region 1\tabcellsep Region 2\tabcellsep Region 3\tabcellsep Region 4\tabcellsep Region 5\tabcellsep Wij\\ Region 1\tabcellsep 1\tabcellsep 9\tabcellsep 7\tabcellsep 3\tabcellsep 5\tabcellsep 0.502819\\ Region 2\tabcellsep \tabcellsep 1\tabcellsep 0.33\tabcellsep 0.14\tabcellsep 0.20\tabcellsep 0.034821\\ Region 3\tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.20\tabcellsep 0.33\tabcellsep 0.067778\\ Region 4\tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 3\tabcellsep 0.260232\\ Region 5\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 1\tabcellsep 0.13435\\ Sum\tabcellsep 1.79\tabcellsep 25\tabcellsep 16.33\tabcellsep 4.68\tabcellsep 9.53\tabcellsep 1\end{longtable} \par \caption{\label{tab_10}Table 11 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{12} \par \begin{longtable}{P{0.12773224043715847\textwidth}P{0.08825136612021858\textwidth}P{0.09986338797814208\textwidth}P{0.07896174863387978\textwidth}P{0.09754098360655737\textwidth}P{0.06967213114754098\textwidth}P{0.09521857923497268\textwidth}P{0.08825136612021858\textwidth}P{0.10450819672131147\textwidth}} Criteria\tabcellsep Rainfall\tabcellsep Stream\tabcellsep Area\tabcellsep Fault\tabcellsep Slope\tabcellsep Temperature\tabcellsep Altitute\tabcellsep Habitate\\ Options\tabcellsep \tabcellsep Density\tabcellsep \tabcellsep Density\tabcellsep \tabcellsep \tabcellsep \tabcellsep Density\\ Region 1\tabcellsep 0.0341\tabcellsep 0.1344\tabcellsep 0.0348\tabcellsep 0.0378\tabcellsep 0.067\tabcellsep 0.0348\tabcellsep 0.0678\tabcellsep 0.5028\\ Region 2\tabcellsep 0.0669\tabcellsep 0.2602\tabcellsep 0.2602\tabcellsep 0.2058\tabcellsep 0.260\tabcellsep 0.0678\tabcellsep 0.2602\tabcellsep 0.0348\\ Region 3\tabcellsep 0.1412\tabcellsep 0.5028\tabcellsep 0.5028\tabcellsep 0.5300\tabcellsep 0.502\tabcellsep 0.1344\tabcellsep 0.5028\tabcellsep 0.0678\\ Region 4\tabcellsep 0.2589\tabcellsep 0.0678\tabcellsep 0.1344\tabcellsep 0.1495\tabcellsep 0.134\tabcellsep 0.2602\tabcellsep 0.1344\tabcellsep 0.2602\\ Region 5\tabcellsep 0.4988\tabcellsep 0.0348\tabcellsep 0.0678\tabcellsep 0.0768\tabcellsep 0.034\tabcellsep 0.5028\tabcellsep 0.0348\tabcellsep 0.1344\end{longtable} \par {\small\itshape [Note: © 2014 Global Journals Inc. (US) -]} \caption{\label{tab_11}Table 12 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{13} \par \begin{longtable}{P{0.12035398230088495\textwidth}P{0.15044247787610618\textwidth}P{0.15044247787610618\textwidth}P{0.14292035398230088\textwidth}P{0.14292035398230088\textwidth}P{0.14292035398230088\textwidth}} Indexes\tabcellsep Region 1\tabcellsep Region 2\tabcellsep Region 3\tabcellsep Region 4\tabcellsep Region 5\\ point\tabcellsep 0/1743\tabcellsep 0/1770\tabcellsep 0/3606\tabcellsep 0/1750\tabcellsep 0/1731\\ Rank\tabcellsep Fourth\tabcellsep Second\tabcellsep First\tabcellsep Third\tabcellsep Fifth\end{longtable} \par \caption{\label{tab_12}Table 13 :}\end{figure} \footnote{© 2014 Global Journals Inc. (US)} \backmatter \begin{bibitemlist}{1} \bibitem[Dyer ()]{b6}\label{b6} ‘A clarification of 'Remarks on the Analytic Hierarchy Process’. 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