Extended fuzzy analytic hierarchy process approach in

ORIGINAL ARTICLE

Extended fuzzy analytic hierarchy process approach in waterand environmental management (case study: Lake Urmia Basin,Iran)

Ali Azarnivand • Farkhondeh Sadat Hashemi-Madani •

Mohammad Ebrahim Banihabib

Received: 16 January 2014 / Accepted: 26 May 2014 / Published online: 14 June 2014

� Springer-Verlag Berlin Heidelberg 2014

Abstract Recent researches reveal that many global

attempts have been made to protect water resources;

however, substantial environmental concerns have not yet

been sufficiently addressed. Lake Urmia in Iran is plagued

by natural and anthropogenic driving forces and its water

level has fallen by about 3 m below the minimum eco-

logical water level. To deal with the divergent interests and

multiple objectives associated with the lake’s water

resources, a multidisciplinary and flexible approach is then

required. The present research phases included: (1) deter-

mining the effective internal and external factors along

with formulating strategic alternatives for reviving the

lake’s water resources via strength–weakness–opportunity–

threat (SWOT–TOWS) matrix; (2) prioritizing the alter-

natives according to sustainable development criteria via

extended fuzzy analytic hierarchy process (FAHP) tech-

nique, and (3) applying sensitivity analysis to monitor the

robustness of the ranking. Representatives of the stake-

holders, managers and experts participated in the process of

decision making. To consider the different viewpoints and

the overall possibility distributions of fuzzy numbers, three

ranking procedures were developed through the extended

FAHP, reflecting neutral, optimistic, and pessimistic

viewpoints. According to the final prioritization, human

resources management and promotion of stakeholders’

participation stood superior to the other strategic

alternatives. In this framework, SWOT–TOWS analysis

performed as an appropriate prerequisite to formulate

practical strategies for supporting of a sustainable devel-

opment vision. The extended FAHP made a valid contri-

bution to the proposed framework and sensitivity analysis

of the results proved capability of the extended FAHP as a

robust tool for decision making in comprehensive water

problems.

Keywords Decision making � Fuzzy AHP � Lake Urmia �Stakeholders

Introduction

Crucial to human health and progress, food security, sus-

tainable development and to a protection of the environ-

ment, water resources management (WRM) constitutes an

area of policy-makers’ priority in formulating strategies on

the development (Singh et al. 2009). However, developing

countries are plagued by bad governance and unwise

allocation of natural resources (Cosgrove and Rijsberman

2000). Insufficient knowledge regarding the way aquifers,

rivers, lakes and dams function (Alley et al. 2002) along

with an overlooking of the capacity of water resources at

the time of land development planning (Mencio et al. 2010)

has resulted in substantial environmental crises associated

with water management.

In recent years, mean water level of Lake Urmia, a vast

hyper saline lake in north–west of Iran and one of the

largest Iranian Ramsar Sites, has descended to its lowest

level during the last century (Ghorbani-Aghdam et al.

2013). The lake is the main habitat for the endemic Iranian

brine shrimp, Artemia urmiana as the main food source of

host water birds (Karbassi et al. 2010). Increase in salinity

A. Azarnivand (&) � F. S. Hashemi-Madani � M. E. Banihabib

Department of Irrigation and Drainage Engineering,

College of Aburaihan, University of Tehran, Tehran, Iran

e-mail: [email protected]

F. S. Hashemi-Madani


M. E. Banihabib


123

Environ Earth Sci (2015) 73:13–26

DOI 10.1007/s12665-014-3391-6

from 170 up to 400 g/L (Zarghami 2011) is the root cause

of a severe decline of Artemia urmiana population in the

lake. Increasing salinity, water scarcity, land degradation,

biodiversity loss, a decrease of available water for the

development along with likely salt storms from the lake

constitute some series of environmental deteriorations that

would adversely affect agriculture sector, public health and

economic growth in the vast area of the region (Eimanifar

and Mohebbi 2007; Zarghami 2011; Hassanzadeh et al.

2012). Hassanzadeh et al. (2012) emphasized that overuse

of surface water resources is responsible for some 65 % of

the crisis, constructing dams has had 25 % effect on

decreasing the lake’s level, while about 10 % being related

to reduced precipitation. The continuous drop in mean

water level of Lake Urmia has started since 1996 (Ozyavas

and Khan 2012). The current water level of the lake has

fallen for about 3 m below its minimum ecological water

level (Department of Environment of Iran 2010). Under

such circumstances, the minimum annual ecological water

requirement of the lake would be 3.1 billion cubic meters

(Abbaspour et al. 2012).

The assessment as based upon the driving force–pres-

sure–state–impact–response (DPSIR) sustainability frame-

work, demonstrated that without a consideration of the

ethical, cultural and institutional indicators and as well

stakeholders’ engagement, Integrated Water Resources

Management (IWRM) plans cannot be successfully

implemented within the basin (Hashemi et al. 2010). Thus,

the demands and visions of stakeholders from different

socioeconomic backgrounds must be reflected in the

inclusive plans (D’Souza and Nagendra 2011). To hinder

the environmental deteriorations and boost public partici-

pation, an application of the strategic framework at the

regional level would be a serious action that must be taken

(Bryan et al. 2010). However, the stakeholders differ in

values, goals and socioeconomic interests (Ganoulis et al.

2008) and WRM must consider the environmental, eco-

nomic and social criteria simultaneously (Yilmaz and

Harmancioglu 2010). The complexity of WRM lies in the

root of these divergent interests and multiple objectives. As

a result, it is difficult to make a recommendation that fits all

the contexts and solves all the complex water management

and planning problems. In an addressing of the issue, the

pivotal role of prioritization approaches is highlighted.

Nowadays, utilization of multidisciplinary approaches,

particularly in developing countries where improving liv-

ing standards and human development are challenging

issues, is highly recommended (Garfi et al. 2011). Multi-

Criteria Decision Making (MCDM) models are popular

among researchers due to their capabilities in: (1) dealing

with a limitation of water, financial and human resources;

(2) considering the combination of multiple criteria; (3)

resolving conflict among the stakeholders, and (4)

simplifying the administration of the projects (Zarghami

and Szidarovszky 2011). In comparisons of techniques,

different MCDM tools can be used to determine the criteria

weights and evaluate the overall scores of alternatives

(Roman et al. 2004). Although there are no such better or

worse models, some models better suit to particular deci-

sion problems than others do (Mergias et al. 2007). The

ability to handle qualitative criteria, applicability to the

case of group decision making and synthesizing different

points of view, capacity to handle various criteria and

alternatives, low requirements on time, and consistency

and robustness of results are some vital requirements for

choosing proper MCDM model (MacCrimmon 1973).

Hence, before selecting the MCDM model, decision mak-

ers must understand the problem, the feasible alternatives,

different outcomes, conflicts among the criteria, and the

level of the data uncertainty (Salminen et al. 1998). In this

research, prioritization of strategic alternatives is a com-

plex decision making problem containing subjectivity,

uncertainty and ambiguity throughout the assessment pro-

cess. The analytic hierarchy process (AHP) developed by

Saaty is a mathematical technique of converting linguistic

assessments to a set of weights by making pairwise com-

parisons among the criteria into a hierarchical structure

(Saaty 1980). AHP allows the decision makers to incor-

porate judgments on tangible and intangible qualitative

criteria, and also provides a mechanism for analysts to

check the consistency of the results (Badri 2001). More-

over, AHP is well suited in group decision making (Lai

et al. 2002) and can accommodate both tangible and

intangible criteria, individual and shared values in the

group decision making process (Dyer and Forman 1992).

There is a large volume of published studies describing the

role of AHP in such different water and environmental

fields as water quality (Martin-Ortega and Berbel 2010),

river basin planning (Calizaya et al. 2010), environmental

assessment of water programs (Garfi et al. 2011), IWRM

(Gallego-Ayala and Juızo 2011), waste water treatment

(Pires et al. 2011), irrigation (Gallego-Ayala 2012), urban

water demands (Panagopoulos et al. 2012), assessment of

waste dumps on soil and water (Adibee et al. 2013) and

groundwater vulnerability (Sener and Davraz 2013).

On the other hand, the limited and unbalanced scale of

judgment in conventional (crisp) AHP cannot fully con-

sider the inherent uncertainty and ambiguity associated

with respondents’ judgments (Yang and Chen 2004). To

overcome the shortcoming, decision makers have found

interval judgments as more accurate than the fixed value

judgments (Nazari et al. 2012). In this regard, an integra-

tion of the fuzzy set theory with AHP has been recom-

mended by some scholars (Van Laarhoven and Pedrycz

1983; Buckley 1985; Chang 1996). The fuzzy set theory

makes it possible to incorporate the unquantifiable,

14 Environ Earth Sci (2015) 73:13–26

123

incomplete and non-obtainable information into the pro-

cess of decision making (Kulak et al. 2005). Fuzzy MCDM

and pairwise comparison play central roles in water policy

assessment, boosting of infrastructure and as well in stra-

tegic planning and management (Hajkowicz and Collins

2007). There have been lots of studies in the literature

using fuzzy analytic hierarchy process (FAHP) for the

solution of such water and environmental problems as

assessment of water management plans (Srdjevic and

Medeiros 2008), geo-environmental impact assessment

(Huang et al. 2012), flood risk evaluation (Yang et al.

2013), and groundwater pollution assessment (Aryafar

et al. 2013).

Therefore, this paper is aimed at prioritizing the strate-

gic alternatives for reviving the lake’s water resources

through a MCDM model, on the basis of strategies’ capa-

bility of satisfying sustainable development criteria. To

structure a democratic process, direct involvement of

groups of stakeholders, experts and managers is high-

lighted and weights of criteria and overall ranks of alter-

natives are evaluated as based upon respondents’ votes.

The first step would be environmental scanning and an

identification of the internal strategic factors vs. external

ones in a group decision making process. With constructing

strengths–weaknesses–opportunities–threats (SWOT–

TOWS) matrix, the fundamental internal and external

factors are determined and the alternatives containing

managerially and structurally based strategies formulated

by matching the internal strengths and weaknesses as

against external opportunities and threats. Then, the

appropriate evaluation criteria are selected based upon

compatibility with operational circumstances of the basin

with their weights evaluated through pairwise comparisons

of FAHP technique. To prioritize the strategic alternatives,

extended FAHP is employed to develop three ranking

procedures, reflecting neutral, optimistic, and pessimistic

viewpoints. Finally, sensitivity analysis is applied to

monitor the robustness of the end ranking.

Materials and methods

Case study

Located within the domains of the provinces of East and

West Azerbaijan and Kurdistan, Lake Urmia Basin covers

an area of 51,440 km2 (Ghaheri et al. 1999). The area lies

approximately between 37�400–39�290N latitude and

44�130–47�530E longitudes (Ghorbani-Aghdam et al.

2013), (Fig. 1). Lake Urmia as a National Park and its

important brackish and freshwater satellite wetlands are

recognized by UNESCO as a Biosphere Reserve (UNEP

and GEAS 2012). Average precipitation amounts to

341 mm (Djamali et al. 2008) with the mean annual tem-

perature varying between 6.5 to 13.5 �C (Department of

Environment of Iran 2010). Delju et al. (2013) analyzed

climate variability and change in the basin for the period

1964–2005. They suggested that mean precipitation had

decreased by 9.2 %, while the average maximum temper-

ature increased by 0.8 �C over the last four decades. The

average annual inflow into the lake is estimated at 5,300

million cubic meters. The largest river emptying into the

basin is Zarinneh Rood (Ghaheri et al. 1999), and apart

from the 14 rivers with permanent flows and a number of

waterways with seasonal flows; the lake receives water

from groundwater seepage flows and also from direct

precipitation over the lake (Department of Environment of

Iran 2010).

Strategic management framework

Strategic management is a process, built up of three major

components: (1) strategy formulation to determine the

future trend of the system; (2) strategy implementation for

designing the system’s structure, and (3) strategic evalua-

tion including evaluation and review of the system’s pro-

gress (Danaee Fard et al. 2011). Although a prediction of

the future is close to impossible, the range of possible

change and likely future events can be anticipated from the

strategic planning and management context [United Nation

(UN) 2004].

Group decision making is an effective approach for an

implementation of good governance in water disciplines

(Zarghami 2011). Hence, a panel of experts was gathered

to determine the key strategic factors and to develop the

strategies for the basin. All the ten members of panel of

experts are PhD holders either in water resources engi-

neering or natural resources management. They had been

invited from the Iranian academic and research institutions

for their educational and operational backgrounds in deal-

ing with challenges of Lake Urmia Basin. According to

Iran’s Department of Environment (2010), the vision

toward Lake Urmia is: ‘‘Lake Urmia will have adequate

water to sustain an attractive landscape and rich biodi-

versity where people and local communities can make wise

use of its resources, and will enhance cooperation between

the involved provincial organizations’’. The next step

would be a distinction between internal vs. external envi-

ronment. The realm is shared among east and west Azer-

baijan plus Kurdistan provinces. The factors, not in the

authority of the basin management are assumed as the

external factors. In other words, the factors that can be

controlled by basin management are considered as internal,

while those that can affect basin management but man-

agement cannot have influence on them, are classified as

the external ones.

Environ Earth Sci (2015) 73:13–26 15

123

SWOT–TOWS matrix

SWOT–TOWS matrix is a practical matching tool for

determination of the effective internal vs. external factors

of a system, creating ideal solutions and implementing

strategic management. The fundamental factors are derived

from large numbers of responses in a group decision

making process. Strategies are formulated through sys-

tematic analysis of the feasible connections between

SWOT factors in the conceptual TOWS framework. In

fact, matching the internal factors as against the external

ones formulates four groups of strategies (Weihrich 1982):

1. SO: these Maxi–Maxi strategies use the internal

strengths to take advantage of external opportunities.

2. ST: these Maxi–Mini strategies avoid impact of the

external threats by applying the internal strengths.

3. WO: these Mini–Maxi strategies aim at eliminating

internal weaknesses by an exploitation of the external

opportunities.

4. WT: these Mini–Mini strategies are defensive tactics

directed at minimizing the internal weaknesses, while

avoiding the external threats.

Although SWOT–TOWS is a helpful tool for defining

and structuring the problem and an exploration of the

present strategic position of the system, it does not reveal

any information concerning the importance of the factors.

Hence, this analysis can bear a degree of subjectivity that

may affect the formulation of the strategic plan (Gallego-

Ayala and Juızo 2011). Since a sole utilization of SWOT–

TOWS method is not sufficient, a different approach is

applied to find the most conclusive strategy. In present

research, sustainable development is the concept that links

strategic management and group MCDM together.

Assessment of TOWS-based alternatives via FAHP method

with regard to the concept of sustainable development

would enable the policy makers to draw an ideal context

for a determination of the most attractive strategy.

Sustainable development criteria

Numerous sustainable development criteria have been clas-

sified in general (economic, social, and environmental) and

technical/comprehensive categories (Zarghami and Szidar-

ovszky 2011). Appropriate criteria in water programs are

often selected based upon the compatibility with operational

circumstances of the study areas (Garfi et al. 2011). To

mention a few, the criteria in some researches as state-of-art-

review for ranking of water resources projects in Iran (Ar-

dakanian and Zarghami 2004; Zarghami and Szidarovszky

2011), sustainable agricultural development of Iran (Rezaei-

Moghaddam and Karami 2008), evaluation of strategic

urban water reuse alternatives in Thailand (Sa-nguanduan

and Nititvattananon 2011), water shortage mitigation policy

making in South Korea (Choi et al. 2012) and an assessment

of non-conventional water supply alternatives in Barcelona

(Domenech et al. 2013) are hereby presented (Table 1).

Throughout the present research, and due to the unfavorable

Fig. 1 Map of the study area


123

circumstances of the basin, a conjunction of the sustainable

development paradigm and the current strategic condition is

highlighted. On this basis, the sustainable development cri-

teria are selected by considering the effective strategic fac-

tors in SWOT framework.

Determination of criteria weights in FAHP

The following scheme expresses the steps of MCDM process

throughout the research, as follows: defining feasible alter-

natives, setting the evaluation criteria and their weights,

evaluation of the alternatives, and finally, performing the

sensitivity analysis to analyze the experimental results.

Zadeh (1965), Van Laarhoven and Pedrycz (1983),

Buckley (1985) and Kaufmann and Gupta (1985) devel-

oped different fuzzy definitions. Buckley method is hereby

applied as based on the fact that, fuzzy weights for each

fuzzy matrix are determined through the geometric mean

method that can simplify the calculations. In addition,

Buckley (1985) proved:

Considering ~A1 ¼ ~aij

h i; where ~aij ¼ ðaij; bij; cij; dijÞ and

let bij� ~aij� dij for all ij; if A1 ¼ aij

h iis consistent, then

~A1 ¼ ~aij

h iis consistent too. To check the consistency of

the comparison matrix, the consistency index (CI) can be

calculated through the following formula (Saaty 1980):

Table 1 Various criteria used for the evaluation of alternatives in

water and environmental problems (the same numbers refer to the

criteria suggested by the researchers)

Economic criteria

Priority of usages (1 & 3)

Benefit minus cost (1 & 3)

Benefit/cost ratio (1 & 3)

Extent of investments (1 & 3)

Risk of investments (1 & 3)

Development and improvement ratio in agricultural area (1 & 3)

Base for supplementary projects (1 & 3)

Diversification of financial resources (1 & 3)

Level of construction technology (1 & 3)

Capabilities of phased operation (1 & 3)

Simplicity of operation and maintenance (1 & 3)

Level of studying phases (1 & 3)

Productivity (2)

Profitability (2)

Investment cost (4)

Economic benefit (4)

Construction costs (5)

Estimated damage(5)

Capital cost (6)

Operation and maintenance cost (6)

Environmental criteria

Consistency with climate (1 & 3)

Less damages to ancient and cultural heritage (1 & 3)

Range of environmental impacts (1 & 3)

Studies of watershed conservation (1 & 3)

Studies on supply and demand management (1 & 3)

Environmental protection (2)

Wise use of resources (2)

Product quality (2)

Water consumption demand and supply in next 20 years (4)

Water consumption demand and supply in present (4)

Environmental impact (4 & 6)

Sustainability (5)

Surface water quality (5)

Energy consumption (6)

Social criteria

Employment and migration (1 & 3)

Public participation (1, 2 & 3)

Social equity (1, 2 & 3)

Recreation, tourism and additional facilities (1 & 3)

Social casualties and damages of dam project (1 & 3)

Natural disasters management ‘‘Flood and Drought’’ (1 & 3)

More settlement in border regions (1 & 3)

Priority of shared waters (1 & 3)

Reducing the conflicts among stakeholders (1 & 3)

Health impacts (4 & 6)

Public acceptance (4 & 6)

Table 1 continued

Water shortage duration (5)

Employment increase (5)

Technical criteria

Consistency with policies (1 & 3)

Consistency with logistic plan (1 & 3)

Impacts on other projects (1 & 3)

Management capacities in basin (1 & 3)

Comprehensive study in basins (1 & 3)

Quality of effluent (4)

Quantity of effluent (4)

Reliability of wastewater treatment operator(4)

Regulation/policy/support from central government (4)

Institutional cooperation (4)

Technological simplicity (6)

Reliable water supply (6)

Researchers

(1): Ardakanian and Zarghami (2004)

(2): Rezaei-Moghaddam and Karami (2008)

(3): Zarghami and Szidarovszky (2011)

(4): Sa-nguanduan and Nititvattananon (2011)

(5): Choi et al. (2012)

(6): Domenech et al. (2013)


123

CI ¼ kmax � n

n� 1; ð1Þ

where kmax is the maximum eigenvalue that can be

obtained from the priority matrix. The Consistency Ratio

(CR) illustrates the judgment concerning consistency. In

the following formula, (RI) is a Random Index set for a

randomly generated n� n matrix. The results will be

accepted if CR is less than or equal to 10 %.

CR ¼ CI

RI

� �� 100 ð2Þ

Although Buckley (1985) employed trapezoidal mem-

bership functions for fuzzifying the comparison ratios, by

accordingly selecting the parameters of membership func-

tion, trapezoidal shape can be converted to triangular. The

triangular fuzzy numbers (TFNs) are indicated as~A ¼ ða; b; cÞ, where a and c are the lower and upper bounds

of the fuzzy number and b is the midpoint (Fig. 2). A (TFN)

is defined by its basic particulars as follows (Chang 1996):

lAðxÞ ¼

x� a

b� afor a� x� b

c� x

c� bfor b� x� c

0 Otherwise

8>>><>>>:

ð3Þ

Considering two TFNs ~A1 ¼ ða1; b1; c1Þ and

~A2 ¼ ða2; b2; c2Þ, their operational laws (addition, subtrac-

tion and multiplication) would be as follows (Kaufmann

and Gupta 1985):

~A1 � ~A2 ¼ a1 þ a2; b1 þ b2; c1 þ c2ð Þ ð4Þ~A1H~A2 ¼ a1 � c2; b1 þ b2; c1 � a2ð Þ ð5Þ

~A1 � ~A2 ¼ a1 � a2; b1 � b2; c1 � c2ð Þ ð6Þ

Linguistic variables (Table 2) are variables whose val-

ues are represented by either words or sentences in a nat-

ural or artificial language (Fig. 3).

The first step would be the construction of pairwise

comparison matrices among all the criteria, within the

dimensions of the hierarchy system.

A1 ¼

1 ~a12 . . . ~a1n

1=~a12 1 . . . ~a2n

. . . . . . . ..

. . .1=~a1n 1=~a2n . . . 1

26664

37775 ð7Þ

The aggregated fuzzy judgment matrix (AFJM) for the

criteria is computed from the geometric mean evaluation of

the decision-makers’ individual fuzzy judgment matrices

(IFJM) as follows:

y

x

a b c0

1

Fig. 2 A triangular fuzzy number ~A

Table 2 Membership functions of linguistic scale

Fuzzy

number

Linguistic scales to obtain

importance

Membership

function

ðu ¼ e ¼ 1Þ

1 Equal importance (1, 1, 1)

2 Between equal and weak importance (1, 2, 3)

3 Weak importance (2, 3, 4)

4 Between weak and strong importance (3, 4, 5)

5 Strong importance (4, 5, 6)

6 Between strong and very strong

importance

(5, 6, 7)

7 Very strong importance (6, 7, 8)

8 Between very strong and absolute

importance

(7, 8, 9)

9 Absolute importance (8, 9, 10)

E

2 6 109

1

4 831 5 7

W S VS A

Fig. 3 Membership functions of linguistic values for criteria rating


123

~Aij ¼Ymk¼1

akij

!1m

;Ymk¼1

bkij

!1m

;Ymk¼1

ckij

!1m

0@

1A

8~Akij ¼ ak

ij; bkij; c

kij

� �For i; j ¼ 1; . . .; n and k ¼ 1; . . .;m;

ð8Þ

where ~Akij is a fuzzy number that represents the vote of

particular decision maker and k ¼ k1; k2; . . .; kmf g the set

of decision makers.

For the next step, consider ~A1 ¼ ðaij; bij; cijÞ and i; j ¼1; . . .; n, then:

atij ¼

Yn

j¼1

aij

!1n

; btij ¼

Yn

j¼1

bij

!1n

and ctij ¼

Yn

j¼1

cij

!1n

ð9Þ

at ¼Xn

i¼1

atij; bt ¼

Xn

i¼1

btij and ct ¼

Xn

i¼1

ctij ð10Þ

The criteria weights can be calculated from the equation

below:

~Wi ¼at

ij

ct;bt

ij

bt;ct

ij

at

� �ð11Þ

Determination of alternatives’ weights

The AFJM for the alternatives under each criterion is computed

from the IFJM suggested by decision makers. Later, ~rij, the

fuzzy weights of alternative j to criterion i, should be evaluated

through the three formulas of (9)–(11). In these formulas, TFNs

of alternatives should be alternated and the fuzzy utility cal-

culated through formula (12) (Bonissone 1982):

~Uj ¼Xn

j¼1

~wi � ~rij ð12Þ

Since prioritizing is in demand of quantifiable results,

defuzzification should be adopted. Considering two trape-

zoidal fuzzy numbers ~A1 ¼ ða1; b1; c1; d1Þ and ~A2 ¼ða2; b2; c2; d2Þ, their operational laws would be as follows

(Bonissone 1982):

~A1 � ~A2 ¼ ða1 þ a2; b1 þ b2; c1 þ c2; d1 þ d2Þ ð13Þ~Q¼ ~A1� ~A2 ¼ a1a2 L1;L2½ �b1b2;c1c2;d1d2 R1;R2½ �ð Þ ð14Þ

where L1, L2, R1 and R2 can be calculated from the fol-

lowing formulas:

L1 ¼ ðb1 � a1Þðb2 � a2Þ ð15ÞL2 ¼ a2 b1 � a1ð Þ þ a1 b2 � a2ð Þ ð16ÞR1 ¼ d1 � c1ð Þ d2 � c2ð Þ ð17ÞR2 ¼ � d2ðd1 � c1Þ þ d1ðd2 � c2Þ½ � ð18Þ

To convert trapezoidal numbers to TFNs, terms b1 ¼ c1

and b2 ¼ c2 should be assumed. If ~Q0 ¼ ~Q1 þ ~Q2, then the

membership function would be defined as:

l ~Q0ðxÞ ¼

0 If x� ða1 þ a2Þ or x ðd1 þ d2Þ1 If ðb1 þ b2Þ � x� ðc1 þ c2Þa 2 0; 1½ � If ða1 þ a2Þ � x� ðb1 þ b2Þa 2 0; 1½ � If ðc1 þ c2Þ � x� ðd1 þ d2Þ

8>>><>>>:

ð19Þ

When ða1 þ a2Þ� x�ðb1 þ b2Þ, xi would be:

xi ¼ Li1a2þLi2aþ ai for i ¼ 1; 2 ð20Þ

As a result, x can be calculated from the equation below:

x ¼ L11 þ L21ð Þa2þ L12 þ L22ð Þaþ a1þa2ð Þ ð21Þ

Similarly, when ðc1 þ c2Þ� x�ðd1 þ d2Þ, the equation

below would be used:

x ¼ R11 þ R21ð Þa2þ R12 þ R22ð Þaþ d1þd2ð Þ ð22Þ

Prioritization of the alternatives

Center of gravity (COG) is an appropriate defuzzification

operator that computes the COG of the area under the

membership function. COG can be calculated as follows

(Broekhoven and Baets 2006):

Ev~U� ¼R d

ax � l ~UðxÞdxR d

al ~UðxÞdx

ð23Þ

where Evð ~UÞ is a non-fuzzy value of ~U and l ~UðxÞ the

membership function of ~U.

This formula reflects a general/neutral viewpoint. To

consider the overall possibility distributions of fuzzy num-

bers; Lee-Kwang and Jee-Hyong (1999) suggested the fol-

lowing two ranking formulas, reflecting optimistic vs.

pessimistic viewpoints in evaluating the alternatives’ values:

Ev optimistic~U� ¼R d

ax2 � l ~UðxÞdxR d

al ~UðxÞdx

ð24Þ

Ev pessimistic~U� ¼R d

að2x� x2Þ � l ~UðxÞdxR d

al ~UðxÞdx

ð25Þ

Results and discussion

TOWS strategies and evaluation criteria

According to the environmental scanning, the panel of

experts obtained 26 relevant factors to the strategic man-

agement in the Lake Urmia Basin (Table 3). The strengths

(four factors) are categorized in the natural, organizational

and educational groups. Weaknesses (13 factors) are

derived from mismanagement and unjustified human


123

Ta

ble

3S

WO

Tm

atri

x

Inte

rnal

(str

eng

ths)

Inte

rnal

(wea

kn

esse

s)

Un

iver

siti

esan

dre

sear

chin

stit

ute

sas

clo

ud

seed

ing

cen

ter

(S1

)

Ex

iste

nce

of

inte

gra

ted

man

agem

ent

pla

nfo

rL

ake

Urm

iaB

asin

(S2

)

Imp

oss

ibil

ity

of

allo

cati

ng

the

salt

yla

ke

wat

erfo

rag

ricu

ltu

ral

wat

ersu

pp

ly(S

3)

En

vir

on

men

tal,

com

mer

cial

,in

du

stri

al,

com

mu

nic

atio

n

and

eco

tou

rism

po

ten

tial

s(S

4)

Imp

rop

ersu

per

vis

ion

on

surf

ace

wat

er’s

allo

cati

on

asw

ell

on

ov

er-e

xp

loit

atio

no

fth

eg

rou

nd

wat

erre

sou

rces

(W1

)

Wea

kH

yd

ro—

clim

ato

log

ym

on

ito

rin

gsy

stem

sal

on

gw

ith

sho

rtag

eo

fb

asic

dat

a(W

2)

Rap

idch

ang

esin

pro

vin

cial

wat

erm

anag

emen

t(W

3)

Inex

iste

nce

of

op

tim

alcr

op

pin

gp

atte

rnad

apte

dto

the

chan

gin

gcl

imat

ean

dw

ater

reso

urc

es(W

4)

Lan

du

sech

ang

e,d

egra

ded

pas

ture

san

der

osi

on

(W5

)

To

rece

de

the

lak

ean

dcr

eati

on

of

the

salt

mar

sh(W

6)

Inex

iste

nce

of

dia

lect

icco

nn

ecti

on

,co

nsu

ltat

ion

and

coo

rdin

atio

nam

on

gth

est

akeh

old

ers,

NG

Os,

acad

emic

cen

ters

and

go

ver

nm

enta

lo

rgan

izat

ion

s(W

7)

Lac

ko

fso

cial

lear

nin

gan

dp

ub

lic

edu

cati

on

con

cern

ing

effi

cien

tw

ater

use

pat

tern

s(W

8)

Sh

ort

age

of

was

tew

ater

coll

ecti

on

and

trea

tmen

tsy

stem

sin

urb

anan

dru

ral

area

s(W

9)

Ou

to

fd

ate

wat

erd

istr

ibu

tio

nn

etw

ork

sin

urb

anan

dru

ral

area

s(W

10

)

Inad

equ

acy

of

pre

ssu

rize

dir

rig

atio

nsy

stem

san

dm

od

ern

farm

mec

han

izat

ion

(W1

1)

Lac

ko

fm

ain

ten

ance

of

the

irri

gat

ion

chan

nel

s(W

12

)

Dam

san

da

hig

hw

ayco

nst

ruct

edw

ith

ou

tco

nsi

der

ing

of

the

env

iro

nm

enta

lw

ater

rig

hts

and

asw

ell

the

lak

e’s

hy

dro

dy

nam

ic(W

13

)

Ex

tern

al(o

pp

ort

un

itie

s)E

xte

rnal

(th

reat

s)

Th

ep

oss

ibil

ity

of

uti

lizi

ng

ren

ewab

leen

erg

ies

and

mo

der

nte

chn

olo

gy

(O1

)

Wat

erre

sou

rces

leg

isla

tio

ns

and

reg

ula

tio

ns

(O2

)

Fu

nd

sb

yg

ov

ern

men

t(O

3)

Wat

erre

sou

rces

inad

jace

nt

bas

ins

(O4

)

Gro

win

gin

tern

atio

nal

,n

atio

nal

and

loca

lco

nce

rns

ov

erth

ed

ryin

gu

po

fth

ela

ke

(O5

)

Inap

pro

pri

ate

spat

ial

and

tem

po

ral

dis

trib

uti

on

of

pre

cip

itat

ion

(T1

)

Dir

eim

pac

tso

fcl

imat

ech

ang

ean

dd

rou

gh

t(T

2)

Mar

ked

flu

ctu

atio

ns

inth

en

atio

nal

eco

no

my

alo

ng

wit

hin

exis

ten

ceo

f

inv

estm

ent

secu

rity

for

pri

vat

ese

cto

r(T

3)

Lac

ko

fd

yn

amic

con

nec

tio

nb

etw

een

exp

erts

and

leg

isla

tors

(T4

)


123

intervention in nature. Opportunities (five factors) are

related to facilities and budget allocation by the govern-

ment, public concerns as well as modern technology.

Finally, threats (four factors) are caused by climate change,

economic crisis and institutional conflicts. Based upon a

systematic review of several literature reports, the causes of

environmental crisis in the Lake Urmia are mainly mana-

gerially and structurally based issues (Garousi et al. 2013).

As a result, the strategic alternatives of the lake should

include both categories. The formulated strategies of

present research are summarized in Table 4.

As stated earlier, the strategic factors are effective in the

process of choosing sustainable development criteria. On

this basis, six criteria are as follows:

C1: resistance against economic fluctuations (eco-

nomic), C2: acceptability by stakeholders and desirability

of participation (social), C3: natural resources conservation

(environmental), C4: effectiveness in water supplying or

conservation (technical), C5: operational feasibility (tech-

nical) and C6: flexibility in long-term and short-term

changes (technical).

FAHP results and discussions

A questionnaire was prepared to determine the relative

weights of each criterion and of each alternative by use of

pairwise comparisons. Throughout the ongoing research,

more than 50 decision makers constituted the participants,

while a total of 38 valid and consistent questionnaires

being applied. The decision makers were chosen from the

representatives of local stakeholders, environmental

activists, water managers, university teachers and academic

researchers.

The AFJM of criteria as well as final TFNs of alterna-

tives under each criterion are presented in Table 5. The

consistency ratio of AFJM for the criteria amounts to 0.01.

The aggregated fuzzy weights (AFW) of sustainable

development criteria and consistency ratio of decision

matrices of alternatives under each criterion are also shown

in Table 5.

Prior to calculating the values of alternatives, the

required components should be determined (Table 6). As

noted earlier, three neutral, optimistic, and pessimistic

formulas (23–25) are applied to calculate the non-fuzzy

value for each alternative. The evaluated components are

alternated in the formulas below:

~Ui !

Ev neutralðAÞ ¼R b

axðL1x2 þ L2xþ aÞ dxþ

R d

cxðR1x2 þ R2xþ dÞ dxR b

aðL1x2 þ L2xþ aÞ dxþ

R d

cðR1x2 þ R2xþ dÞ dx

Ev optimisticðAÞ ¼R b

ax2ðL1x2 þ L2xþ aÞ dxþ

R d

cx2ðR1x2 þ R2xþ dÞ dxR b


R d


Ev pessimisticðAÞ

¼R b

að2x� x2ÞðL1x2 þ L2xþ aÞ dxþ

R d

cð2x� x2ÞðR1x2 þ R2xþ dÞ dxR b


R d


8>>>>>>>>>>>>>><>>>>>>>>>>>>>>:

The results related to three neutral, optimistic, and

pessimistic viewpoints are presented in Table 7. Apart

from the fact that all these aspects produced similar rank-

ings, the most striking results to emerge from the data are

as follows:

Table 4 TOWS matrix

SO WO

A1: inter-basin water transfer with an addition of the financial and legal

supports and as well employing of the operational and academic

skills (S1-O2, 3, 4)

A2: cloud seeding with an addition of the financial and legal supports

and as well employing of the operational and academic skills

(S1, 2-O2, 3)

A4: promotion, establishment, and institutionalization of integrated

system of operation, protection, monitoring and maintenance of soil

and water resources of the basin, with an addition of the financial and

legal supports, public concern and new technologies

(W1, 2, 5-O1, 2, 3, 5)

A5: promoting stakeholders’ participation in the process of training,

planning and implementation of efficient water use pattern with an

empowerment and developing of NGOs (W7, 8, 10-O5)

A6: implementation of optimal cropping pattern according to the

regional climate with employing financial and legal supports and as

well guiding of the public concerns (W4-O2, 3, 5)

A7: improvement of the efficiency and reduction of water losses in

irrigation and water distribution systems with employing financial

and legal supports and as well proper use of facilities

(W9, 10, 11, 12-O2, 3)

ST WT

A3: spatial planning with regard to environmental,

commercial and industrial potentials to overcome security,

economic, political, social and environmental conflicts (S4-T3)

A8: optimization of water resources allocation

with considering the lake’s ecological capacity to implement

climate change adaptive programs (W13-T2)


123

Promoting stakeholders’ participation in the process of

training, planning and implementation of efficient water use

pattern with an empowerment and developing of NGOs (A5)

is by far the most demanding strategy among all the for-

mulated strategies. The research of Abdullaev and Rak-

hmatullaev (2013) has demonstrated that the significant

difference between current approaches of WRM in the

Central Asia and former Soviet Communist period lies in the

participation and collaboration of stakeholders into the

processes of planning, implementation, monitoring and

decision making in WRM. Due to their research work, sus-

tainable water management is highly dependent upon the

role of water users. It is worth noting that, without an initi-

ation of social learning among responsible authorities,

NGOs and stakeholders, moving toward structuring the

involvement process is difficult. Social learning in WRM

requires the right level of expectations, considerable finan-

cial resources and a high level of time commitment (Muro

and Jeffrey 2012). The extensive, systematic and structured

participation is of a great benefit to modern water resource

governance (Lennox et al. 2011). The high rank of this

strategy indicates that the crucial role of human resources

management has been understood by the respondents.

Due to population growth, limitation of water resources,

and huge costs of water supply, efficient management and

operation of available water resources must be highlighted

(Bozorg Haddad and Marino 2007). The orientation of 2nd

to 6th ranked strategies is managerially based, with their

targets of supply and/or conservation of water resources

through:

1. Adjusting water and soil resources with the basin’s

potentials.

2. Empowering the surface and ground water

supervising.

3. Control of supply and demand relationship in agricul-

tural fields.

4. Optimization of releases from dams.

Furthermore, there is very little difference observed

among the values of these alternatives.Ta

ble

5T

he

agg

reg

ated

fuzz

yju

dg

men

tm

atri

xfo

rth

ecr

iter

iaan

dfi

nal

asse

ssm

ent

of

the

alte

rnat

ives

un

der

each

crit

erio

n

C1

C2

C3

C4

C5

C6

C1

(1,

1,

1)

(0.6

7,

0.8

9,

1.1

2)

(0.4

2,

0.4

9,

0.6

0)

(0.4

3,

0.5

0,

0.6

1)

(0.5

2,

0.5

8,

0.6

7)

(1.2

2,

1.3

7,

1.4

9)

C2

(0.8

9,

1.1

2,

1.4

9)

(1,

1,

1)

(0.4

2,

0.4

9,

0.6

0)

(0.5

0,

0.6

2,

0.8

2)

(0.6

7,

0.7

3,

0.8

2)

(1.2

2,

1.6

7,

2.0

3)

C3

(1.6

7,

2.0

3,

2.3

5)

(1.6

7,

2.0

3,

2.3

5)

(1,

1,

1)

(1.0

2,

1.5

5,

2.1

7)

(1.1

2,

1.4

9,

1.9

3)

(2.3

5,

3.1

3,

3.8

5)

C4

(1.8

1,

2.0

2,

2.1

2)

(1.2

2,

1.6

0,

2.0

0)

(0.4

6,

0.6

5,

0.9

8)

(1,

1,

1)

(0.8

2,

1.0

4,

1.2

4)

(1.3

5,

2.4

2,

3.4

5)

C5

(1.4

9,

1.7

2,

1.9

2)

(1.2

2,

1.3

7,

1.4

9)

(0.5

2,

0.6

7,

0.8

9)

(0.8

1,

0.9

6,

1.2

2)

(1,

1,

1)

(1.4

9,

2.1

0,

2.6

3)

C6

(0.6

7,

0.7

3,

0.8

2)

(0.4

9,

0.6

0,

0.8

2)

(0.2

6,

0.3

2,

0.4

2)

(0.2

9,

0.4

1,

0.7

4)

(0.3

8,

0.4

8,

0.6

7)

(1,

1,

1)

AF

W(0

.08

,0.1

2,

0.1

6)

(0.0

9,

0.1

3,

0.2

0)

(0.1

8,

0.2

7,

0.4

0)

(0.1

3,

0.2

0,

0.3

0)

(0.1

3,

0.1

9,

0.2

7)

(0.0

6,

0.0

8,

0.1

4)

C1

C2

C3

C4

C5

C6

A1

(0.0

23,

0.0

32,

0.0

40)

(0.0

45,

0.0

66,

0.0

86)

(0.0

23,

0.0

29,

0.0

35)

(0.0

39,

0.0

53,

0.0

69)

(0.0

62,

0.0

86,

0.1

17)

(0.0

25,

0.0

35,

0.0

42)

A2

(0.0

33,

0.0

43,

0.0

51)

(0.0

38,

0.0

57,

0.0

72)

(0.0

35,

0.0

42,

0.0

49)

(0.0

27,

0.0

38,

0.0

48)

(0.0

81,

0.1

08,

0.1

41)

(0.0

31,

0.0

41,

0.0

49)

A3

(0.1

40,

0.1

62,

0.1

88)

(0.0

84,

0.1

12,

0.1

37)

(0.1

26,

0.1

36,

0.1

57)

(0.1

38,

0.1

66,

0.2

05)

(0.1

37,

0.1

69,

0.2

10)

(0.1

55,

0.1

82,

0.2

17)

A4

(0.1

40,

0.1

59,

0.1

82)

(0.0

65,

0.0

90,

0.1

10)

(0.1

61,

0.1

72,

0.2

01)

(0.1

10,

0.1

31,

0.1

65)

(0.1

21,

0.1

52,

0.1

91)

(0.0

75,

0.0

90,

0.1

10)

A5

(0.2

34,

0.2

61,

0.2

96)

(0.2

53,

0.3

08,

0.3

63)

(0.1

29,

0.1

38,

0.1

52)

(0.1

44,

0.1

65,

0.1

99)

(0.1

75,

0.2

17,

0.2

73)

(0.2

24,

0.2

54,

0.2

94)

A6

(0.1

40,

0.1

59,

0.1

82)

(0.0

75,

0.1

02,

0.1

23)

(0.1

44,

0.1

50,

0.1

71)

(0.1

25,

0.1

48,

0.1

84)

(0.0

92,

0.1

18,

0.1

50)

(0.1

27,

0.1

49,

0.1

78)

A7

(0.0

75,

0.0

91,

0.1

11)

(0.1

54,

0.1

95,

0.2

30)

(0.0

87,

0.0

92,

0.1

09)

(0.0

86,

0.1

03,

0.1

29)

(0.0

71,

0.0

92,

0.1

19)

(0.1

18,

0.1

37,

0.1

62)

A8

(0.0

80,

0.0

93,

0.1

07)

(0.0

78,

0.1

09,

0.1

34)

(0.1

99,

0.2

06,

0.2

32)

(0.1

55,

0.1

83,

0.2

12)

(0.0

41,

0.0

59,

0.0

80)

(0.0

90,

0.1

11,

0.1

33)

CR

0.0

10.0

00.0

10.0

10.0

00.0

1

Table 6 The components for evaluating the alternatives

a b = c d L1 L2 R1 R2

A1 0.025 0.050 0.095 0.004 0.021 0.007 -0.051

A2 0.029 0.056 0.101 0.004 0.023 0.006 -0.051

A3 0.088 0.152 0.267 0.007 0.057 0.014 -0.129

A4 0.082 0.140 0.247 0.006 0.052 0.013 -0.120

A5 0.123 0.205 0.352 0.008 0.074 0.017 -0.163

A6 0.081 0.138 0.241 0.006 0.051 0.013 -0.116

A7 0.064 0.112 0.199 0.006 0.042 0.011 -0.098

A8 0.082 0.140 0.239 0.006 0.052 0.011 -0.111


123

Compared with other managerially based strategies, one

unanticipated finding is related to the rank of A7. Although

some 94 % of the basin available water demand is that

allocated to agriculture within a very low efficiency irriga-

tion system (Hashemi et al. 2010), Improvement of the

efficiency and reduction of water losses in irrigation and

water distribution systems with financial and legal supports

and as well proper use of facilities is the least popular

managerially based strategy throughout the basin. This

might be related to a weak performance of agricultural

education around the basin. It seems respondents are not

optimistic as regards implementation and performance of

modern agriculture. Hashemi et al. (2010) demonstrated that,

with the growing urban population, there is a remote prospect

that population of the Lake Urmia Basin would rise from 5.9

(2008) to 7.1 million by 2020. However, little progress has

been made in implementing the optimal irrigation pattern

and there is a great concern that the dry up of Lake Urmia

might face the same destiny as the Aral Sea catastrophe. Aral

Sea in the semi-arid region of Central Asia experienced an

environmental disaster caused by inefficient and non-sus-

tainable irrigation (Cai et al. 2003). Thus, to improve irri-

gation infrastructure, the environmental knowledge and

awareness of the public should be promoted and agricultural

education programs boosted to change the traditional pattern

of agriculture within the basin.

The least popular alternatives are classified in structurally

based strategies. Cloud seeding is an impact-limited strategy

(Morrison et al. 2009) with former experiences in the basin

not satisfying and not effective in mitigating the impacts of

drought. Within the realm of a sustainable development

paradigm, inter-basin water transfer is a controversial issue

that might cause population displacement, water pollution,

and salinization (Zhang 2009). In China, Ran and Lu (2013)

Table 8 Sensitivity analysis of

alternativesEv (A) neutral Rank Ev (A) pessimistic Rank Ev (A) optimistic Rank

u ¼ 0:5

A1 0.0607 8 0.1151 8 0.0037 8

A2 0.0657 7 0.1231 7 0.0042 7

A3 0.1817 2 0.3120 2 0.0303 2

A4 0.1689 3 0.2916 3 0.0261 3

A5 0.2443 1 0.4012 1 0.0533 1

A6 0.1659 5* 0.2862 4 0.0250 4

A7 0.1343 6 0.2375 6 0.0167 6

A8 0.1662 4* 0.2855 5 0.0248 5

u ¼ 1:5

A1 0.0824 8 0.1574 8 0.0074 8

A2 0.0880 7 0.1671 7 0.0083 7

A3 0.2341 2 0.4046 2 0.0590 2

A4 0.2149 3 0.3763 3 0.0496 3

A5 0.3080 1 0.5049 1 0.1019 1

A6 0.2121 4 0.3721 4 0.0483 4

A7 0.1751 6 0.3148 6 0.0330 6

A8 0.2108 5 0.3705 5 0.0477 5

Table 7 Final assessment of

the alternatives/ ¼ 1 Ev (A)

neutral

Rank Ev (A)

pessimistic

Rank Ev (A)

optimistic

Rank

A1 0.0682 8 0.1307 8 0.0049 8

A2 0.0732 7 0.1394 7 0.0056 7

A3 0.1964 2 0.3458 2 0.0394 2

A4 0.1818 3 0.3227 3 0.0337 3

A5 0.2608 1 0.4398 1 0.0688 1

A6 0.1784 4 0.3173 4 0.0324 4

A7 0.1463 6 0.2657 6 0.0219 6

A8 0.1778 5 0.3161 5 0.0321 5


123

claimed that excessive dependence on water engineering

projects had not sufficiently addressed water problems in that

country and more comprehensive environmental impact

assessments were needed. The possibilities of inter-basin

water transfer from Zab River, Aras River and as well from

the Caspian Sea to Lake Urmia have been studied (UNEP and

GEAS 2012). Also, Zarghami (2011) has applied a group

decision making method to detect the most suitable inter-

basin alternative among the four possible routes of water

transfer to the lake. Due to considerable economic costs, dire

environmental impacts on aquatic ecosystems and as well a

likely dewatering of the surface and groundwater resources

of adjacent areas (which might lead to political and social

conflicts) (Golabian 2011; UNEP and GEAS 2012), The

respondents were not of the inclination to have this strategy

implemented.

Sensitivity analysis

Sensitivity analysis was performed to examine the response

of alternatives when the membership function (u) changed.

To investigate the impact of changing this factor on the

selection of the most approved strategy, two other mem-

bership functions were tested. When u ¼ 0:5, in optimistic

and pessimistic evaluations, ranks of the alternatives were

similar to the results obtained for u ¼ 1; however, in

neutral condition, the ranks of A6 and A8 were substituted.

When u ¼ 1:5, the ranking was similar to the results when

u ¼ 1 (Table 8). To sum up, A6 and A8 are sensitive to

changes in membership functions, while A5 is a superior

alternative for all the scenarios with its top rank constant in

all conditions. Inter-basin water transfer (A1) and cloud

seeding (A2) are finally concluded as the least attractive

strategies within all the tested conditions (Fig. 4).

Conclusions

Throughout the ongoing paper, the merits of FAHP contri-

bution to SWOT–TOWS analysis in a sustainable develop-

ment context were discussed. The strategic alternatives for

reviving water resources and biodiversity rehabilitation of

Lake Urmia Basin were formulated via TOWS procedure

and prioritized by FAHP based on their capability in satis-

fying each selected sustainable development criterion.

From a technical point of view, implementation of

strategic management within the Lake Urmia Basin should

be guided mainly by following human resources manage-

ment and social learning. Effective involvement of stake-

holders in WRM is a democratic step that can promote

transparency of the evaluation process and facilitate the

achievement of compromised solutions. Such manageriallyFig. 4 Overall results of sensitivity analysis for alternatives in

a neutral, b pessimistic, c optimistic viewpoints


123

based strategies as spatial planning, empowering water

resources supervision and conservation, implementation of

optimal cropping pattern, optimization of allocations from

dams and promotion of irrigation efficiency are placed at

ranks 2nd to 6th. The low scores of two structurally based

strategies, namely inter-basin water transfer and cloud

seeding indicate these alternatives cannot satisfy sustain-

able development concept appropriately, due to limited

strategic impact, considerable economic costs, dire envi-

ronmental impacts on aquatic ecosystems and likely con-

flicts among upstream vs. downstream sectors.

From a methodological point of view and according to

the obtained results, the different viewpoints of extended

FAHP identified the same rankings among strategic alter-

natives when membership function equaled to 1 or 1.5.

When membership function decreased to 0.5, little changes

in middle-ranking alternatives were observed, but high and

low rankings were not sensitive to membership function

changes. Hence, sensitivity analysis demonstrated that

FAHP was a robust tool for decision making in compre-

hensive ecological issues. It can be concluded that FAHP

makes a valid contribution to the strategic management

framework and the application of SWOT–TOWS proce-

dure to the extended FAHP is recommended as a pragmatic

approach to deal with divergent interests, multiple objec-

tives and subjective assessments in cases of crisis water

management.

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