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Prioritization of watersheds in order to perform administrative measures using fuzzy analytic hierarchy process.

Abstract: Prioritization of watersheds in order to perform administrative measures is necessary and inevitable. Determining areas of top priority for flood control projects is a managerial decision that should be approved by studies of physical, social and economic status of the region of interesrt and by assessing the outcomes of the past operations. Therefore, the aim of this research was to study morphological and physiographic characteristics, and to use geographic information systems (GIS) and multi-criteria decision-making methods (MCDM), to identify the critical sub-basins which have the tendency to be destructed, in Galikesh watershed, Golestan province. This watershed is important, yet critical, in terms of land use change, erosion and flooding in the Golestan Province, Iran. In total, nine morphological parameters were used to prioritize sub-watersheds using fuzzy analytic hierarchy process (FAHP). The morphological parameters were by some means linked to watershed drainage system. Based on FAHP approach, sub-basins, as vulnerable zones, have been evaluated and cetegorized in five priority levels (very low, low, medium, high and very high levels). The results showed that 44.44% and 22.22% of sub-basins were categorized respectively under average, and high to very high levels, suggesting that the conservation and management measures are essential in order to maintain stability in the region. Thus, the FAHP technique is a practical and convenient method to show potential zones in order to implement effective management strategies, especially in areas where data availability is low and soil diversity is high. Finally, it can be said that without having to encounter high costs and a waste of time, sub-basins could be categorized by means of morphometric parameters in order to implement conservational measures to simutaneously conserve soil and the environment.

Keywords: Watersheds priority, FAHP, GIS, multi-criteria decision making, Galikesh watershed

Su havzalarinda idari tedbirlerin bulanik analitik hiyerarsi yontemi kullanilarak onceliklendirilmesi

Ozet: Idari tedbirleri gerceklestirmek icin havza onceliklendirilmesi gerekli ve kacinilmazdir. Taskin kontrolu projeleri icin oncelikli alanlari belirleme yonetimsel bir karardir ve bu karar; soz konusu bolgenin fiziksel, sosyal ve ekonomik statusu ile gecmisteki islemlerinin sonuclarini degerlendirerek alinmalidir. Bu nedenle, calismanin amaci cografi bilgi sistemleri (CBS) ve coklu kriterleri karar verme yontemleri (MCDM) kullanarak Gulistan eyaleti- Galikesh havzasinda tahrip edilme riski tasiyan havzalarin morfolojik ve fizyografik ozelliklerini incelemektir. Iran'in Gulistan Eyaleti icerisinde bulunan bu havza kritik bir sekilde erozyon ve taskin riski tasimaktadir. Toplamda, dokuz morfolojik parametre bulanik analitik hiyerarsi sureci (FAHP) icin kullanildi ve bu morfolojik parametreler havza drenaj sistemiyle dogrudan iliskiliydi. Bu yontemde alt havzalar; hassas bolgeler olarak, degerlendirilmis ve bes oncelik duzeyi (cok dusuk, dusuk, orta, yuksek ve cok yuksek seviyelere) seklinde kategorize edilmistir. Sonuclar; koruma ve alinacak yonetim tedbirlerinin bolgede istikrarin saglanmasi icin gerekli oldugunu gostermis; alt havzalarin sirasiyla % 44.44 oraninda ortalama altinda ve % 22.22 oraninda cok yuksek duzeyde korunmasi gerektigini vurgulamistir. Bulanik analitik hiyerarsi yontemi, ozellikle teknik veri kullanilabilirligi dusuk ve toprak cesitliligi yuksek olan bolgelerde, etkin yonetim stratejilerinin uygulanmasi icin potansiyel bolgeleri gosterme acisindan pratik ve kullanisli bir yontemdir. Son olarak, yuksek maliyetler ve zaman kaybi ile karsilasmaya gerek kalmadan, alt havzalar morfometrik parametreler kullanilarak toprak ve cevre korumasi acisindan kategorize edilebilmesini saglamaktadir.

Anahtar Kelimeler: Su havzalari onceligi, FAHP, CBS, cok kriterli karar verme, Galikesh havzasi

1.INTRODUCTION

Watershed is a suitable management unit, demanding multi-purpose approach in the management of resources to ensure continued benefits. Watersheds are the primary units for land management which require an interdisciplinary approach for their utilization and ensuring continued use. Therefore, the key issues of natural resources such as water scarcity, land degradation, drought, floods, etc., are resolved through the management of developed areas or sub-units, (Syrvastava et al., 2010). Analysis of Drainage network characteristics such as morphometric features, hydrogeology, etc. playes a pivotal role in the allocation, design and implementation of protective measures in small-scale hydrological units. Having knowledge of physiographic features of a catchment area with an awareness of climatic conditions can provide a fairly accurate picture of the qualitative and quantitative functioning of the hydrological system (Aher et al., 2013). Physiographic characteristics of the basin, in addition to the direct impact on the hydrological regime, flood intensity, soil erosion, and sedimentation, indirectly affects climate, ecology and vegetation (Fazelniya et al, 2012). In most watersheds, floods and its consequences are likely to increase in the upcoming years, and thus determining flood inducing areas of the basin and the prioritization of sub-basins are necessary for flood control projects and integrated watersheds management (Bakhtiarifar et al, 2011). GIS Techniques, remote sensing (RS), and Multiple Criteria Decision Making (MCDM) tools are useful for morphometric indexing and prioritization of sub-basins (Singh, 1994; Grohmann, 2004; Sreedevi et al, 2009; Aher et al, 2010; Rao and colleagues, 2011).

Prioritization of the watersheds has been of interest to many researchers in various fields. Aher and colleagues (2013) prioritized the Pim Palagon watershed in India through 9 morphometric parameters based on the FAHP. The results showed that 60.85% of the area fell into the middle to very high class showing the need for the protective measures. Mishra and colleagues (2007) through morphometric parameters via the Soil and Water Assessment Tool (SWAT) prioritized sub-basins of a semi-humid tropical ecosystems in India through morphometric indices. Vivien et al. (2011), applied the fuzzy MCDM method for selecting the best watershed environmental initiatives. Kaya and Kahraman (2011) by adopting VIKOR and fuzzy AHP approaches, developed a decision-making framework for forest management.

In other pieces of research, socio-economic aspects (Patil, (2007), Gosain and Rao (2004), Newbold and Siikamaki (2009), Kanth and Hassan (2010)) and land degradation and land use change, have been evaluated as the leading parameters of scoring landscape zones (Adinarayana, 2003; Deb and Talukda, 2010; Kanth and Hassan, 2010; Javed and colleagues, 2011; Sarma and Saikia, 2011).

The Galikesh watershed is an important, yet critical, basin in terms of land use change, erosion and flooding in the Golestan province. One of the principles of carrying out any project, whether theoretic or executive in various fields, is to prioritize. In order to apply watershed management practices, sub-basins prioritization would be a considerable effort due to limitations of time and resources. In this study, we tried to prioritize sub-basins through natural drainage network (the drainage system parameters), which is an innovative approach. Therefore, in this study to line up the morphological parameters, fuzzy analytic hierarchy process (FAHP) was used, to finally be able to identify and rank order sub-basins, evaluate the consequences and achieve the best accuracy.

2. MATERIAL AND METHOD

2.1 Study Area

Galikesh, as a sub-basin of the Gorganroud River, is located in Golestan province. This basin has an area of 404.8 square kilometers and an environment of 88.6 km. Figure 1 illustrates the location of the Galikesh basin in Golestan province. The maximum elevation reaches up to as much as 2461 meters, and its minimum height drops down to 378 m with an average height of 1295 meters above sea level. It has an average slope of 23.3 percent. The Oghan river lies in this basin, eventually joining the Gorganroud River and draining into the Golestan Dam. The main tributary of the river is 26.2 km long with 3.5 percent net slope. Concentration and lag time, using the Kirpich method, have been calculateded 3.9 and 2.3, respectively.

2.2 Research Methodology

In this study, prioritization of sub-basins was carried out using morphometric parameters and fuzzy analytical hierarchy process. First morphometric parameters were calculated in each sub-basin. Afterwards, by comparing the results of these indicators, sub-basins were placed in order based on watershed management practices by using the fuzzy analytic hierarchy process. A total of 9 morphometric parameters were used for sub-basins prioritization.

These parameters comprise the compression factor, form factor, elongation factor, streams frequency, drainage density, Bifurcation Ratio, drainage texture, concentration time and basin shape, all of which corresponding to the drainage network of the basin. Thus, this method is also called the Analysis of the natural drainage system. Morphometric parameters, used in the study; are provided in Table 1. In this study, in order to carry out the calculations and estimations of parameters, ARCGIS, Arc Hydro, XTools, Expert Choice and Excel softwares were used.

2.3 Prioritization of sub-basins

Once the morphometric parameters estimated, the Fuzzy Analytic Hierarchy Process (FAHP) was used in order to prioritize sub-basins.

AHP, as one of the most popular multi-criteria decision-making techniques, was developed in the 1980s by Thomas Saaty. AHP method relies on pairwise comparisons. The decision-maker initiates the analysis by providing a decision tree hierarchy. This tree illustrates the indicators and options of the decision. In an attempt to measure the Fuzzy concepts in a numerical manner, at least it has been tried to define numbers that compatibly describe the possible fuzzy concepts. Therefore, in this study, after drawing hierarchical tree (Figure 2), in order to make pairwise comparisons, triangular fuzzy numbers in the form of (li, mi, ui) were used. Then, pairwise comparison matrix was produced. For each row of the matrix of pairwise comparison, the value of Si, which is a triangular fuzzy number, was calculated using the following formula:

[mathematical expression not reproducible] (1)

[mathematical expression not reproducible] (2)

[mathematical expression not reproducible] (3)

[mathematical expression not reproducible] (4)

Where "g" represents row number; "i" and " j" denote indicators and options. After calculating "Si", their comparative magnitude was calculated so that if M1 and M2 are two triangular fuzzy numbers, M1 to M2 magnitude ratio was defined as follows:

[mathematical expression not reproducible] (5)

To calculate the index weight in pairwise comparison matrix, following formula holds:

W'{([x.sub.i])=min{V([S.sub.i]>[S.sub.k])} k=1,2,...,n, k=I (6)

Thus, the weight vector of the indices was calculated by the following equation, which is the non-normal vector of coefficients in fuzzy AHP.

W'=[(W'([x.sub.1]), W'([x.sub.2]),..., W'([x.sub.n])).sup.t] (7)

After normalizing eq. (7), the number of non-fuzzy (W) was determined by the following equation:

W=[(W([x.sub.1]), W([x.sub.2]),..., W([x.sub.n])).sup.t] (8)

In consequence, priority of all of sub-basins in the Galikesh watershed was estimated following the Fuzzy Analytic Hierarchy Process (FAHP).

3. RESULTS

Morphometric parameters calculated for each sub-basins are provided in Table 2. These values were obtained via formulas and softwares described in the Materials and Methods section. These values were used to form a pairwise comparison matrix in AHP.

For prioritizing sub-watersheds, 9 morphometric evaluation indices were used in the form of a hierarchical tree shown in Figure 2.

According to the FAHP method, each standard morphometric criterion was evaluated through a pairwise comparison matrix, based on the weight scale obtained by normalized fuzzy calculations (Table 3). In addition, the ratings resulting from the proposed weight and morphometric parameters were introduced into the ARCGIS software environment, to map a comprehensive risk assessment for the implementation of protective measures (Figure 3).

In this study, FAHP analysis values ranged between 0.661 and 0.364 (Table 3). The priority of each index was obtained from the FAHP analysis, with the first priority having the largest value in the given drainage network. Therefore, the SW6 sub-basin received the highest priority by the numerical value of 0.661, and the SW3 received the lowest priority by the value of 0.364. other sub-basins falls somewhere in between. Based on the multi-criteria decision analysis, priority of the sub-basins as well as comprehensive vulnerability assessment map consisting of 9 sub-basins were caluculated as given in Figure 4. Accordingly, high-priority areas of SW6 and SW4 (priority 1 and 2) were determined. These areas must be placed under proper management principles due to the extent of degradation of natural resources. In addition, sub-basins were grouped under five classes of very low to very high, based on the total weight and the classification of morphometric parameters using MCDM method FAHP (Table 4). Compared with the classification above, it was found that 44.4% of the region, falls under the average class.

The purpose of the application of multi-criteria decision-making techniques, is to exercise a proper approach to identify areas of high-priority to management. The best decisions are made through completing management activities such as soil and water conservation engineering measures, afforestation and so on.

4. DISCUSSION AND CONCLUSIONS

This research underlines the capabilities of remote sensing, GIS and multi-criteria decision in the prioritization of sub-basins for planning and managing natural resources. In this study, a new approach and logical process comprised of MCDM, in other words the FAHP analysis, has been successfully implemented for sub-basins prioritization. MCDM and GIS techniques have displayed their capabilities in the prioritization of sub-basins. When used together, they compensate each other's shortcomings in order to better inform management planning. This is in agreement with the results Fazelnia et al. (2012) and Ghafari Gilandeh et al. (2014). This technique is very effective in the watershed the case lack of data. Also when there exist complications due to a number of qualitative and quantitative criteria, MCDM plays an important role. The results show that the FAHP technique can be beneficial in the planning for the potential zones to implement effective management strategies at the watershed level, to various stakeholders such as farmers, rural communities, natural resource managers, and so forth. Watershed behaviour varies according to the morphometric characteristics for conservation factors. For that reason, the prioritization of critical areas for the implementation of conservation measures was determined. The watershed shape and other morphometric parameters were respectively, positively and negatively, correlated with risk assessement factors including runoff, and soil erosion. This agrees to the findings of Thakkar and Dhiman (2007). Integrated multi-criteria decision making (MCDM) and GIS have high capabilities in addressing spatial issues. Because on the one hand, in this method, multi-criteria decision approach can be used to establish a systematic framework for including influential criteria of spatial issues and their relative scoring. on the other hand, with a prevailing analytical tool such as GIS, huge quantities of data can be analyzed which is consistent with Bakhtiarifar studies (2011).

Finally, it can be argued that, sub-basins could be prioritized based on morphometric parameters without needing remarkable cost and time to implement watershed protection measures and to seek to protect natural resources. This is consistent with the results of Aher and colleagues (2013). However, due to high capacity of multi-criteria decision-making methods and GIS in the prioritization of sub-basins, the stronger the experts' opinions are and more accurate and updated the data, the more welcome and positive outcomes are to be expected.

REFERENCES (KAYNAKLAR)

Adinarayana, J., 2003. Spatial decision support system for identifying priority sites for Watershed management schemes. In Proc. First Interagency Conference on Research in the Watersheds (ICRW), 405-408. Benson, Arizona, USA: U. S. Department of Agriculture, Agricultural Research Service, 27-30 October.

Aher, P.D., Adinarayana, J., Gorantivar, S.D., 2013. Prioritization of Watersheds using multi-criteria evaluation through fuzzy analytical hierarchy process. Agricultural Engineering Int: CIGR Journal 15(1): 11- 18.

Aher, P.D., Singh K.K., Sharma, H.C., 2010. Morphometric characterization of Gagar Watershed for management planning. In Twenty Third National Convention of Agricultural Engineers and National Seminar. Rahuri, India: Mahatma Phule Agril. University 6-7 February.

Bakhtiarifar, M., Mesgari, M., Karimi, M., Chehreghani, A., 2011. Land use change modeling using multi-criteria decision analysis and GIS. Journal of Environmental Studies 37(58): 43-52.

Deb, D., Talukda, B., 2010. Remote Sensing and Geographic Information System for Assessment, Monitoring, and Management of Flooded and Waterlogged Areas, North District of Tripura State, India. Watershed Management 2010: Innovations in Watershed Management under Land Use and Climate Change, 1013-1024. Madison, USA, August 23-27.

Fazelniya, Gh., Kiani, A., Mahmodian, H., 2012. Locate and prioritize urban parks using GIS and TOPSIS model (The Case Study: Alashtar City). Human Geography Research Quarterly 43(78): 20-22.

Ghafari Gilandeh, A., Kamelifar, Z., Yazdani, M.H., 2014.. Prioritization of urban green land suitability in the process of switching places with MCDM techniques. Journal of Geographical Sciences 14(32): 251-270.

Gosain, A.K., Rao, S., 2004. GIS-based technologies for watershed management. Current Science 87(7): 948-953.

Grohmann, C.H., 2004. Morphometric analysis in Geographic Information Systems: applications of free software GRASS and R star. Computers and Geosciences 30(10): 1055-1067.

Javed, A., Khanday, M.Y., Ahmed, R., 2011. Watershed prioritization using morphometric and land use/land cover parameters: a remote sensing and GIS based approach. Journal Geological Society of India 78(1): 63-75.

Kanth, K.A., Hassan, Z.U., 2010. Prioritization of Watersheds in Wular catchment for sustainable development and management of natural resources. Recent Research in Science and Technology 2(4): 12-16.

Kaya, T., Kahraman, C., 2011. Fuzzy multiple criteria forestry decision making based on an integratedVIKOR and AHP approach. Journal of Expert Systems with Applications 38: 7326-7333.

Mishra, A., Kar, S., Singh, V.P., 2007. Prioritizing structural management by quantifying the effect of land use and land cover on Watershed runoff and sediment yield. Water Resources Management 21(11): 1899-1913.

Newbold, S.C., Siikamaki, J., 2009. Prioritizing conservation activities using reserve site selection methods and population viability analysis. Ecological Applications 19(7): 1774-1790.

Patil, G.P., 2007. Statistical geoinformatics of geographic hotspot detection and multicriteria prioritization for monitoring, etiology, early warning and sustainable management for digital governance in agriculture, environment, and ecohealth. Journal of the Indian Society of Agricultural Statistics 61(2): 132-146.

Rao, L.A.K., Rehman,A.Z., Alia, Y., 2011. Morphometric analysis of drainage basin using remote sensing and GIS techniques: a case study of Etmadpur Tehsil, Agra District, U.P. International Journal of Research in Chemistry and Environment 1(2): 36-45.

Saaty, T.L., 1980. The Analytical Hierarchy Process, New York, McGraw-Hill.

Sarma, S., Saikia,T., 2011. Prioritization of Sub-Watersheds in Khanapara--Bornihat area of Assam--Meghalaya (India) based on land use and slope analysis using remote sensing and GIS. Journal of the Indian Society of Remote Sensing 40(3): 435-446.

Singh, N., 1994. Remote sensing in the evaluation of morphohydrological characteristics of the drainage basin of Jojri catchment. Annals of Arid Zone 33(4): 273-278.

Sreedevi, P.D., Owais,S., Khan, H.H., Ahmed, S., 2009. Morphometric analysis of a Watershed of South India using SRTM data and GIS. Journal Geological Society of India 73(4): 543-552.

Srivastava, R.K., Sharma, H.C., Raina, A.K., 2010. Suitability of soil and water conservation measures for Watershed management using geographical information system. Journal of Soil and Water Conservation 9(3): 148-153.

Thakkar, A.K., Dhiman, S.D., 2007. Morphometric analysis and prioritization of mini-Watersheds in a Mohr Watershed, Gujarat using remote sensing and GIS techniques. Journal of the Indian Society of Remote Sensing 35(4): 313-321.

Vivien, Y.C., Hui, P.L., Chui, H.L., James, J.H.L., Gwo, H.T., Lung, S.Y., 2011. Fuzzy MCDM approach for selecting the best environment-watershed plan. Journal of Applied Soft Computing 11: 265-275.

Seyyed Abdolhossein Arami (1,*), Ehsan Alvandi (1), Mahtab Frootandanesh (2), Nasser Tahmasebipour (3), Ebrahim Karimi Sangchini (2)

(1) Gorgan University of Agricultural Sciences and Natural Resources, Departments of Watershed Management and Arid Zone Management, Gorgan, Iran

(2) Sari University of Agricultural Sciences and Natural Resources, Department of Watershed Management, Sari, Iran

(3) Lorestan University, Department of Watershed Management, Lorestan, Iran

(*) Corresponding author e-mail (Iletisim yazari e-posta): arami1854@gmail.com

Received (Gelis): 28.01.2016 - Revised (Duzeltme): 17.02.2016 - Accepted (Kabul): 24.02.2016

To cite this article (Atif): Arami, S.A., Alvandi, E., Frootandanesh, M., Tahmasebipour, N., Sangchini, E.K., 2017. Prioritization of watersheds in order to perform administrative measures using fuzzy analytic hierarchy process. Journal of the Faculty of Forestry Istanbul University 67(1): 13-21.
Table 1. Results and formulae adopted for computation of morphometric
parameters
Tablo 1. Morfometrik parametrelerin hesaplanmasi icin kabul edilen
sonuclar ve formuller

Morphometric Parameters  Formula

                         [mathematical expression not reproducible]
Compression Ratio        Where, P is the basin's circumference in km
                         A= Area of the Basin([km.sup.2])
                         CC = Gravelius Compression Ratio
                         Rg=A/L[b.sup.2]
                         Where, Rf=Form Factor
Form Factor              A=Area of the Basin([km.sup.2])
                         L[b.sup.2]=Square of Basin length
                         Rt=Nu/P
                         Where, Rt = Drainage Texture
Drainage Texture (Rt)    Nu=Total no. of streams of all orders
                         P=Perimeter (km)
                         D=Lu/A
                         Where, D=Drainage Density
Drainage Density(D)      Lu=Total stream langth of all orders
                         A=Area of the Basin([km.sup.2])
                         Fs=Mu/A
                         Where, Fs= Stream Frequency
Stream Frequency(Fs)     Mu= Total on. Of streams of all orders
                         A= Area of the Basin([km.sup.2])
                         Re=2v (A/Pi/Lb)
                         Where, Re=Elongation Ratio
Elongation Ratio         A=Area of the Basin (km 2)
                         Pi='Pi ' value i.e. 3.14
                         Lb=Basin length
                         Rb= Nu/Nu+ 1
                         Where, Rb = Bifurcation Ratio
                         Nu = Total no. of stream segments of order 'u'
                         Nu + 1 = Number of segments of the next higher
                         order
                         [mathematical expression not reproducible]
Concentration Time       Where, [S.sub.0] = The main channel slope
                         (m/m)
                         L= The main channel length(m)
                         L1=[(L*[L.sub.ca]).sup.0.3]
Basin Shape              Where, L = Basin length
                         [L.sub.ca]= Centroid Basin

Morphometric Parameters     Reference



Compression Ratio        Strahler (1964)




Form Factor               Horton (1932)



Drainage Texture (Rt)     Horton(1945)



Drainage Density(D)       Horton(1932)



Stream Frequency(Fs)      Horton(1932)



Elongation Ratio          Schumn (1956)









Concentration Time
                         Kirpich (1940)


Basin Shape              Birkowski(1989)


Table 2. Comparison matrix of morphometric components in the Galikesh
watershed, Golestan
Tablo 2. Galikesh, Golestan havzasindaki morfometrik bilesenlerin
karsilastirma matrisi

Sub basin      Area      compressi   roufness    Form    Elongatio
  Name     ([Km.sup.2])  on ratio   coefficient  factor  n ratio

SW1        38.07        1.36        0.53      0.40    0.71
SW2        23.76        1.62        0.37      0.18    0.47
3A         48.05        1.46        0.45      0.45    0.76
4A         44.84        1.61        0.37      0.26    0.57
5A         48.5         1.33        0.55      0.39    0.71
6A         37.2         1.81        0.29      0.19    0.49
7A         60.94        1.28        0.59      0.48    0.78
8A         25.99        1.37        0.52      0.39    0.7
9A         72.67        1.47        0.45      0.31    0.63

Sub basin  Drainage  Bifurcatio  Basin  Drainage  Overland flow
  Name     density   n ratio     Shape  texture      length

SW1     1.07      2.58        0.19    1.13         0.46
SW2     0.98      4.16        0.18    0.7          0.5
3A      1.02      2.87        0.09    0.99         0.48
4A      0.99      5.5         0.23    0.95         0.5
5A      0.99      3.33        0.12    1.29         0.5
6A      1.11      5.58        0.27    0.96         0.44
7A      1.03      3.46        0.15    1.55         0.48
8A      1.15      4.33        0.14    0.84         0.43
9A      1.09      3.52        0.20    1.31         0.45

Sub basin  Concentration
  Name     Time

SW1        1.86
SW2        1.52
3A         2.09
4A         3.05
5A         2.73
6A         4.35
7A         2.34
8A         1.35
9A         3.40

Table 3. Priority ranking of the sub-basins
Tablo 3. Althavzalarin oncelik siralamasi

Sub basin Name  Score based on FAHP  Prioritization Ranks

SW1               0.411                   8
SW2               0.501                   4
SW3               0.364                   9
SW4               0.532                   2
SW5               0.473                   5
SW6               0.661                   1
SW7               0.431                   7
SW8               0.459                   6
SW9               0.510                   3

Table 4. FAHP scores for different priorities
Tablo 4. Farkli oncelikler icin FAHP degerleri

S. No.  Priority Types  Priority Levels    Sub-watersheds

1       Very High     >0.568                  SW6
2          High        0.567 - 0.514          SW4
3         Medium       0.513 - 0.454   SW2, SW5, SW8, SW9
4          Low         0.453 - 0.397        SW7, SW1
5        Very Low      0.396 - 0.057          SW3

S. No.  Percentage of Area

1            11.11
2            11.11
3            44.44
4            22.22
5            11.11
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Title Annotation:Research Article / Arastirma Makalesi
Author:Arami, Seyyed Abdolhossein; Alvandi, Ehsan; Frootandanesh, Mahtab; Tahmasebipour, Nasser; Sangchini,
Publication:Journal of the Faculty of Forestry Istanbul University
Article Type:Report
Date:Jan 1, 2017
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