Assessment of Modern Approach of Water Governance in the Development of Water Exploitation Systems in Sistan Region

Journal of Applied Research in Water and Wastewater 14 (2020) 127-136

Original paper Assessment of modern approach of water governance in the development of water exploitation systems in Sistan region

Farzaneh Shahbakhsh, Mahdi Safdari*, Ali Sardar Shahraki

Department of Agricultural Economics, University of Sistan and Baluchestan, Sistan and Baluchestan, Iran.

GRAPHICAL ABSTRACT

Development of water exploitation Modern Water governance systems approach

MADM approach

ARTICLE INFO ABSTRACT Article history: Water is the basis of life, the foundation of nature, and the pillar of social, economic, Received 27 July 2020 and cultural development of societies. So, the supply of safe and consumable water Reviewed 1 October 2020 has always been a concern. On the other hand, a major challenge of modern Received in revised form 5 November 2020 societies is the lack of precipitation and frequent droughts. Thus, the present paper Accepted 7 November 2020 assesses the principles of water governance in the Sistan region with respect to the development of water exploitation systems with an environmental approach and Keywords: presents an integrated multi-attribute decision-making model with a water Water governance governance approach in the Sistan region. The simple additive weighting (SAW) Economic assessment method that is used here is one of the multiple attribute decision making (MADM) Water resources methods. The indicators of water governance principles were derived from the Exploitation system development opinions of 30 water experts, faculty members, and water users in the Sistan region Drought by the SAW method, and weights were assigned to them to form MADM matrices.

According to the results, six indicators were derived as the indicators determining

the principles of water governance. ‘Traditional users’ was selected as the strongest system and ‘irrigation and drainage networks exploitation companies’ as the weakest system. Also, according to the results of water experts, the first rank was assigned to ‘irrigation and drainage networks exploitation companies’ (A2) with the final crisp score of 6.818 followed by ‘water user cooperatives’ (A4) with the final crisp score of 6.515 in the second rank and ‘private firms’ (A6) with the final crisp score of 6.308 in the third rank. ©2020 Razi University-All rights reserved.

1. Introduction that was once estimated at 130 billion m3 per year has declined to about 120 billion m3 (Sardar Shahraki et al. 2016; Sardar Shahraki. 2016). Water is a necessary element of life. Socioeconomic development Even when the recent five-year statistics are considered, this has been has always tied to water (Ahmadi and Badisar. 2017). Water is the main about 105 billion m3, implying a significant decline of per capita factor of prosperity and no prosperity can be imagined without it. On the renewable water (Sardar Shahraki et al. 2016). To complicate the other hand, water is a precious economic commodity that cannot be problem of water loss, the population has grown too. The result is that replaced (Sardar Shahraki et al. 2016). A deeper look at water and presently there is less than 1500 m3 of water available for each Iranian related crises implicate inappropriate, non-expertise, and precipitous and it has been projected that this may fall to below 1000 m3 in the next decisions for some problems of water (Afsari et al. 2018; Sardar 10 years (Hajimoradi et al. 2014; Sardar Shahraki and Karim. 2018). Shahraki et al. 2018). The amount of renewable water resource of Iran Water scarcity, especially the drawbacks in drinking water supply and

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| Please cite this article as: F. Shahbakhsh, M. Safdari, A. Sardar Shahraki, Assessment of modern approach of water governance in the development of water 127 exploitation systems in Sistan region, Journal of Applied Research in Water and Wastewater, 7 (2), 2020, 127-136.

Shahbakhsh et al. / J. App. Res. Wat. Wast. 7 (2020) 127-136

hygienic facilities, essentially emanates from incompetent management year. This is also responsible for its hot and dry weather. The rainfalls and inefficient regulations and institutions. Good governance is an in Southeastern Iran mainly originate from the Mediterranean systems element that can lay the ground for the implementation of integrated that come with western winds in cold seasons. The combination of water resource management (Jamali. 2017). In water resource different systems in cold seasons causes the regional rainfall to vary management issues, drought is a natural disaster that has a lot of across the years and exhibit substantial variations (Razeie et al. 2007). harmful impacts on ecological environments (Yaqob et al. 2015). The Sistan plain, which has been formed from the alluvium of the Drought is a transient and reversible status of climate that is mistakenly Hirmand river, is located to the north of the province. The plain in perceived to be a rare random phenomenon (Kariminazar et al. 2011). intermediate desert climate group has annual precipitation of less than Drought is more hazardous than other natural disasters in terms of 50 mm, but its evaporation exceeds 5000 mm. This has caused severe frequency of occurrence, intensity, duration, extensiveness, casualties, physical dryness of the region. In addition, when the input water of the socioeconomic losses, and severe long-term impacts, so it needs Hirmand river drops, fatal droughts develop in this region (Piri et al. special attention in decision-making (Nosrati and Kazemi. 2010; Sardar 2013; Sardar Shahraki. 2016). The water conditions of the Sistan region Shahraki et al. 2018). calls for a kind of integrated water resource management that considers Iran is located in the arid and semi-arid zone of the world and has management constraints of the region in terms of water. Water always been struggling with the challenge of water scarcity. Droughts governance and its principles can consider the special water conditions in this country have been aggravated in recent years, calling for special of the region with a modern approach and can take the necessary plans for water consumption (Afroozeh et al. 2011; Sardar Shahraki. measures. In this respect, the present study aims: Survey measures 2019). On the other hand, due to particular climatic location of the and policies in place for water governance in the Sistan region. Study country and inappropriate temporal and spatial distribution of of impacts the decision-making approach and integrated water precipitation (Daliri et al. 2009), the scarcity of surface water is more resource management with a water governance attitude have on water severe in central and eastern parts of Iran where officials should resources in the Sistan region. Accordingly, the objectives of the carefully consider the sound management of underground water present study can be summarized as the assessment of water resources (Gaedi et al. 2015; Sardar Shahraki. 2018). governance principles in the Sistan region with respect to the Covering an area of 181,785 km2, the province of Sistan and development of water consumption systems and the presentation of an Baluchistan is the largest province of Iran lying within the latitudes of integrated model of multi-attribute decision-making (MADM) systems 25°03' and 31°27' N. and the longitudes of 58°50' and 63°21' E. Since with an economic-environmental approach in the Sistan region (See the province is located in lower latitudes, it has a hot and arid climate Fig. 1). and is dominated by high-pressure tropical systems in over half of the

Fig. 1. Study area in research

As a major parameter influencing water resources, human being 2005). To use these water bodies correctly, appropriate managerial plays a decisive role in the sustainability of this complex system (REF). measures should be adopted (Gaedi et al. 2015). Below is a review of The conventional definitions stress out the political nature of water the literature that is related to our research topic. governance on the one hand since governance cannot be separated In a study of an institutional and structural framework for the from politics (Pahl-Wostl. 2015) and consider water governance within implementation of integrated water resource management in Iran and a wide range of political-social-economic-official systems involved in in the studied watershed of Lake Urmia, Hashemi (2012) concluded that decision making about the development of water resource the efficiency of the water governance system had been enhanced by management and the supply of services at different levels of the society a participatory process, but the effectiveness and efficiency of water on the other hand. The water governance system determines who can allocation will be diminished unless an adaptive approach is adopted have access to water and enjoy its benefits and related services and for water allocation and measures are taken to increase water use when and how one can access it (Allan. 2001; Barker and Molle. 2004). efficiency. Safaee and Malek Mohammadi (2014) studied the history of On the other hand, droughts are extreme hydrological phenomena that water conflict over Lake Urmia and provided strategic insights for better are characterized by the long-term absence of rainfall in a vast area and decision-making by using game theory and determining the most may occur in any climatic conditions (Sardar Shahraki. 2016). This possible results. In a study entitled ‘Sustainable water governance: The phenomenon has significant effects on the economy of the environment main challenge of water crisis management in the Zayanderud River’, and water resources (Alizadeh and Mohammadi. 2015). Yousefi et al. (2013) surveyed the statistical population and found that The Sistan region in eastern Iran is one of the regions that need the most important factors responsible for the loss of the river water water resource management measures. The integrated use of surface were the decline of rainfall, the increasing rate of water use by the and underground water resources is one of the foremost methods of industry, and the increasing rate of water consumption by provinces in comprehensive water resource management (Gaedi et al. 2015; Sardar the order of importance. Saeedi and Darabi (2015) first reviewed the Shahraki et al. 2016). The problems of the Sistan region can be ecological resilience and the resilience of water resources. In a study in enumerated as high summer evaporation, low annual rainfall, severe the context of environmental strategic assessment approach and monsoon storms, poverty, and freshwater limitation. Due to the adverse drivers-pressures-state-impact-response (DPSIR) model, climate and rainfall shortage, the only source of freshwater in this region Almohammad et al. (2014) focused on identifying the causal chains of is the Sistan River flowing into the region from Afghanistan (Sardar territory degradation of Lake Urmia and developing strategies and Shahraki. 2016; Sardar Shahraki et al. 2016). In most years, the water policies to be used in planning and policy-making of governance and running into the region does not suffice to supply both drinking and sustainable development management of territory resources of Urmia irrigation water need. Farmers are severely suffering from the shortage watershed. Kahrizi (2014) explored good governance and its role in the of freshwater (Gaedi et al. 2015). The use of these types of water will improvement of water management in Iran. In mention study used the not only reduce yields, but it will also have problems for salinity-resistant models of World Bank and the UN organization for economic co-

crops by salinizing soil and impairing its quality (Abdelgawad et al. operation and development and the components of explicit policy-

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128 Please cite this article as: F. Shahbakhsh, M. Safdari, A. Sardar Shahraki, Assessment of modern approach of water governance in the development of water exploitation systems in Sistan region, Journal of Applied Research in Water and Wastewater, 7 (2), 2020, 127-136.

Shahbakhsh et al. / J. App. Res. Wat. Wast. 7 (2020) 127-136 making of the professional official system of accountability and robust B. If α is a permutation of m existing alternatives a=(A1, A2, …, Ai, Ai+1,… participatory civil community to explore the elements of good Am) that shows them in the order of preference and α(i) represents the governance and its role in improving water management in Iran. In a alternative in the ith locus of the order presented in the permutation, study on social monitoring of stakeholders network in local water then we will have for each consecutive pair of permutation with (m – 1) resource governance in Razin watershed in Kermanshah, Iran, Salari unequal relations for each pair of the alternatives: et al. (2015) concluded that weak social capital and the lack of solidarity wt ( r r )  ; i  1,2,..., m  1 among people were effective in decelerating the flow of trust and  a i a i 1 (5) cooperation, challenging good water resource governance. In a study  by Tanguay (2010) on determining the main elements of sustainable w Waa;{} W  w w  W development and the process of indicator extraction, it is revealed that localizing indicators accelerates the achievement to results. Therefore, Any vector from 푤 ∈ 푊푎 that can satisfy the order existing in the the strength of the research is the localization of indicators of water permutation of α (i.e. hold true for the above (m – 1) inequalities) should governance principles by relying on technical, managerial, social, and be neutral to DM too provided the order of preferences in α is accepted cultural issues based on the information of a technical workgroup with by DM. So, if 푤 ∈ 푊푎 is accepted by DM, then the DM should accept a focus on localization for specific problems of Khuzestan province. the orders of α as a preferred order. The ISAW method is so that DM Sternlieb et al. (2015) studied water governance context for the can change α to achieve the optimal order 훼∗ and its corresponding 푤 Colorado River as a historical monument. They report that a (in which case the space 푊푎 ∈ 푊 will be created too) (Asgharipour. complicated set of policies, legal decisions, and operational guidelines 2002). has been developed, came to be known as the Law of the River. To C. The preference order in the permutation of α should be practical. It study water governance for agricultural activities in a multi-section will be impractical if one of the corresponding constraints as below is terrain, one needs information data and processing, data integration, satisfied: data combination with geospatial information, and the availability of data for decision-makers for all activities, especially agricultural (r r )  ; i  1,2,..., m  1 (6) ai  ai 1 activities. Labajos et al. (2015) explored the approaches pertaining to water conflicts, disputes, and justice and found that water conflicts can Even if a single element of the set of constraints corresponding to the trigger social movements. The empirical evidence they collected shows inequalities is satisfied as described above, no 푤 vector can create the that social mobilization for the settlement of water challenges is an order of α because the dominated alternative cannot have a rank higher important factor for the replacement of water management and than the dominating alternative and only the alternatives for effective governance. According to Silva et al. (2015), the increased frequency pairs can be ranked in order due to the presence of different 푤. The set of severe drought events induced by climate change is not the only of the key of practical orders of α cause a partition of W as below: cause of water scarcity in semi-arid regions of Brazil, but governance is (7) very relevant too because Brazil has regions swept with huge floods in WUW aa addition to its dry parts. The authors assessed the interaction of climate W W ; a a (8) change and governance for water resources. The results reveal that aa water management deficiency can be implicated for aggravating the impacts of droughts on water users. The review of the literature shows In defining Wa, it is only necessary to consider the constraints that water governance approach has concerned many researchers as formed by adjacent pairs of the elements existing in α. So, the set of Wa it can improve integrated water resource management. Given the water is specified by the set of corresponding linear constraints, and conditions of the Sistan region, the examination of this modern especially the requirements arising from the constraints (Asgharipour. approach as integrated with decision-making models can greatly 2002). contribute to integrated water resource management. D. It is assumed that AK and A1 are two adjacent alternatives of the existing order of 훼 and that the constraint is satisfied obligatorily 2.1. Materials and methods (equality):

t w() rk  r1 (9) This is one of the oldest methods used in MADM so that assuming  the vector W (the important weights of attributes) for them, the best  wW  alternative is calculated as below (Asgharipour. 2002): Then, the change in preference from 1 < 퐾 in 훼 to 1 > 퐾 in 훼́ is wr.  j ij (1) equivalent to the movement from the space Wa to the adjacent space A*   Amx a j  푊푎́ over the borderline specified by the corresponding obligatory i i w j constraints, and if 훼 is practice, 푎́ will be practical too. Consequently, j this allows DM to change the order of A and A in 훼 and thereby 푛 K 1 And if ∑푗 푤푗 = 1 , we have: improve the permutation order to prefer 훼. By correcting the order of alternative only related to the obligatory constraints, permutation will be feasible and the process will converge to the preferred answer * (2) (Asgharipour. 2002). A{ Ai m ax w j . r ij } i  Thereby, it considers the set W derived from the following system: j a This method needs similar scales and/or “dimensionless” (10) AWa .  measurements so that they can be compared to one another n (Asgharipour. 2002). The ideal in the SAW method is that the weights (11)  w j 1 wj can be an estimate of final utility and also use a linear utility function j 1 in problem-solving given the summability conditions. The ISAW method w  (12) introduced by Kornbluth uses the ranking of the alternative to estimate j appropriate wj’s provided there is a linear (but unknown) utility function. Then, the border W is specified by the obligatory rows for each value This estimation is based on the following premises (Asgharipour. 2002): a of 푤 and consequently, a subset {w} is formed. To reach the border W , A. Assuming the linearity of the utility function, the alternative A is a j the value of the objective function in the following linear programming preferred to A if: i+1 should be set to zero (Asgharipour. 2002):

(3) w.... rj  w r   w r   w r  Min:. Aai W jA  j Aj  j ij  j ij1   i i 1 j j j j S.:. t A W  a (13) And as a vector: n  wzj 1: w t () (4) j 1 rrii1 wj ; j 1,2,..., n w W { wj w j  1 ; w j  }

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129 exploitation systems in Sistan region, Journal of Applied Research in Water and Wastewater, 7 (2), 2020, 127-136.

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F. Since we usually have 푚 > 푛, the above linear programming dual is If this problem has a practical solution with z=0, then the row Aa(i) will used to solve it i.e: represent an obligatory constraint for Wa and its corresponding pair {a(i).a(i+1)} will represent an obligatory pair (Asgharipour. 2002). In Max Z Tables 1 and 2 shows indicators of water governance principles and tt exploitation systems considered in the present study. S. t : Aa . y Z .1 Aai  (14) According to the results of water experts (in Tables 3 and 4 and Fig. 11 n1 (2)), the first rank was assigned to ‘irrigation and drainage networks y  ; exploitation companies’ (A2) with the final crisp score of 6.818 followed by ‘water user cooperatives’ (A4) with the final crisp score of 6.515 in yt  { y ,..., y } 11m the second rank and ‘private firms’ (A6) with the final crisp score of 6.308 in the third rank.

Table 1. The indicators of water governance principles in the present study. No. Indices Sub-index 1 Transparency Resource management (M1) 2 Income and cost adequacy (M2) 3 Maintenance of channels (M3) 4 Water distribution mechanism (M4) 5 Water production in drought conditions (M5) 6 Participation Asking for water price (M6) 7 Planting density (M7) 8 The amount of unauthorized exploitation (M8) 9 Sustainability Irrigation efficiency (M9) 10 Irrigation adequacy (M10) 11 System return (M11) 12 Irrigation interval (M12) 13 Standardization Irrigation infrastructure efficiency (M13) 14 Water distribution equality (M14) 15 Optimal design of network (M15) 16 Pumps’ being ready to operate (M16) 17 Efficiency of facility electricity (M17) 18 Monitoring Costs compensation (M18) 19 Lands lacking drainage (M19) 20 Average yield of lands (M20) 21 Average economic yield of lands (M21) 22 Effectiveness Crop yield (M22) 23 Land yield (M23) 24 System capability 25 Satisfaction with water distribution management (M25) 26 Physical productivity of water (M26) 27 Economic productivity of water (M27)

Table 2. Exploitation systems considered in the study. No. Alternative (exploitation system) Variable code 1 Traditional exploitation system A1 2 Irrigation and drainage networks exploitation companies A2 3 Production cooperatives A3 4 Water user cooperatives A4 5 Agricultural corporations A5 6 Private firms A6

The fourth rank was assigned to ‘agricultural corporations’ (A5) with exploitation system’ (A1) was ranked the last with the final crisp score the final crisp score of 5.794 and the fifth rank to ‘production of 4.824. In Table 5 shows matrix of mean (the aggregated opinion of cooperatives’ (A3) with the final crisp score of 5.617. ‘Traditional experts).

6.818 6.515 6.308 5.794 5.617 4.824

A1 A3 A5 A6 A4 A2 Fig. 2. Final crisp scores based on water experts.

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Shahbakhsh et al. / J. App. Res. Wat. Wast. 7 (2020) 127-136

Table 3. The matrix of mean (the aggregated opinion of experts). Index name Limit of numbers A1 A2 A3 A4 A5 A6 L 2.067 5.533 2.3 3.833 3.667 3 M1 M 3.067 7.067 3.933 5.533 5.367 4.367 U 4.1 8.233 5.733 7.133 6.9 5.933 L 2.233 4.867 2.367 5.267 2.767 4.333 M2 M 3.5 6.7 3.867 6.833 4.3 6.067 U 4.933 8.167 5.567 8.033 5.933 7.6 L 2.067 4.467 2.833 3.667 3.967 3.767 M3 M 3.467 6.3 4.5 5.4 5.533 5.133 U 4.933 8 6.267 6.967 6.9 6.467 L 3.533 3.333 3.633 3.267 3.267 3.9 M4 M 4.933 5.033 5.567 5.033 4.967 5.5 U 6.3 6.833 7.267 6.7 6.7 7.067 L 3.233 3.867 2.667 3.767 3.233 4.367 M5 M 4.533 5.567 4.467 5.433 4.9 5.933 U 5.7 7.2 6.267 6.933 6.633 7.267 L 3.3 3.867 2.7 4.033 3.333 3 M6 M 4.4 5.3 4.4 5.733 5 4.767 U 5.5 6.633 6.133 7.3 6.7 6.433 L 3.133 4.1 3.9 3.3 3.367 3.667 M7 M 3.867 5.3 5.433 4.9 5.067 5.3 U 4.767 6.433 6.8 6.467 6.733 6.867 L 2.867 4.5 3.467 3.9 3.7 3.933 M8 M 4.233 6.067 5.067 5.433 5.367 5.467 U 5.5 7.4 6.6 6.9 6.9 6.967 L 2.4 4.633 2.733 3.933 3.133 4.567 M9 M 3.567 6.367 4.367 5.633 4.667 6.133 U 4.9 7.867 6 7.133 6.3 7.467 L 2.833 4.4 3.133 4.233 2.667 4.033 M10 M 4.167 6.1 4.8 6.033 4.2 5.567 U 5.533 7.6 6.433 7.6 5.933 6.933 L 2.967 4.5 3.233 3.833 3.333 3.667 M11 M 4.167 6.233 5.033 5.5 4.933 5.233 U 5.4 7.733 6.767 7 6.5 6.733 L 2.4 5.233 2.667 4.5 2.433 4.767 M12 M 3.433 6.767 4.333 6.267 4 6.333 U 4.667 8 6.033 7.733 5.767 7.6 L 2.867 4.133 3.167 4.233 2.367 4.333 M13 M 3.967 5.867 4.933 5.967 4 6 U 5.267 7.467 6.7 7.467 5.733 7.5 L 3.2 3.8 3.4 3.9 3.733 3.9 M14 M 4.3 5.133 4.767 5.467 5.433 5.3 U 5.333 6.533 6.133 6.833 7.033 6.667 L 2.967 4.5 3.3 3.433 3.7 2.533 M15 M 4.1 6.2 4.9 5.067 5.333 3.8 U 5.367 7.7 6.533 6.633 6.867 5.233 L 2.4 5.133 2.967 3.933 3.7 2.5 M16 M 3.7 6.833 4.5 5.667 5.367 4 U 5.067 8.1 6.233 7.233 6.933 5.667 L 3.267 4.1 2.433 4.6 3.067 3.7 M17 M 4.533 5.767 4.1 6.3 4.567 5.367 U 5.833 7.233 5.933 7.767 6.133 6.933 L 3.8 2.967 3.533 3.267 3.467 4.5 M18 M 5.2 4.567 5.2 4.967 5.1 6.067 U 6.4 6.233 6.867 6.667 6.667 7.333 L 3.867 3.6 3.5 3.067 3.733 3.367 M19 M 5.167 5.067 5.2 4.667 5.533 4.967 U 6.333 6.6 6.8 6.333 7.233 6.467 L 3.6 2.967 3.8 3.933 3.367 3.867 M20 M 4.9 4.467 5.5 5.6 4.933 5.4 U 5.967 6.1 6.967 7.1 6.467 6.9 L 3.2 3.367 3.333 3.933 2.667 4.167 M21 M 4.1 4.667 5.133 5.667 4.2 5.933 U 5.1 6 6.833 7.233 5.867 7.467 L 1.767 5.333 2.533 4.567 2.833 4.333 M22 M 2.733 6.867 4.067 6.267 4.4 5.867 U 4.033 7.967 5.8 7.667 6.067 7.2 L 2.1 5.567 2.167 4.5 3.4 3.3 M23 M 3.233 7.2 3.8 6.267 5.1 5 U 4.533 8.4 5.633 7.7 6.733 6.667 L 3.033 4.5 3 3.7 3.733 3.5 M24 M 4.3 6.067 4.633 5.167 5.367 5.1 U 5.567 7.5 6.233 6.567 6.9 6.633 L 2.433 3.9 3.367 3 3.867 3.3 M25 M 3.733 5.667 4.933 4.6 5.7 4.833 U 5.067 7.333 6.533 6.2 7.333 6.4 L 3.133 3.533 3.9 3.633 3.3 3.667 M26 M 4.167 5.067 5.567 5.233 4.9 5.233 U 5.433 6.567 6.867 6.733 6.433 6.8 L 2.867 4.167 3.233 4.3 2.8 4.667 M27 M 4.133 5.733 5.033 5.967 4.3 6.233 U 5.067 7.133 6.667 7.4 5.9 7.5

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Shahbakhsh et al. / J. App. Res. Wat. Wast. 7 (2020) 127-136

Table 4. Final fuzzy scores based on water experts. Alternative L M U A1 3.414 4.814 6.252 A2 4.983 6.861 8.568 A3 3.664 5.621 7.562 A4 4.593 6.56 8.346 A5 3.875 5.797 7.705 A6 4.488 6.335 8.074

- Faculty members the third with the final crisp score of 6.564 and ‘agricultural corporations’ (A5) was ranked the fourth with the final crisp score of 6.013. The fifth According to result of Tables 5 and 6 and Fig. 3, faculty members rank was assigned to ‘irrigation and drainage networks exploitation ranked ‘water user cooperatives’ (A4) the first with the final crisp score companies’ (A2) with the final crisp score of 5.995 and the last rank of 7.269 and ‘private firms’ (A6) the second with the final crisp score of again to ‘traditional exploitation system’ (A1) with the final crisp score 6.874. According to them, ‘production cooperatives’ (A3) was ranked of 5.065. Table 5. The matrix of mean (the aggregated opinion of experts). Index name Limit of numbers A1 A2 A3 A4 A5 A6 L 1.933 4.533 3.133 4.5 3.3 3.833 M1 M 2.967 5.9 4.5 5.767 4.667 5.1 U 3.933 6.533 5.8 7.067 6.167 6.4 L 2.067 4.233 3.267 5.5 2.9 4.9 M2 M 3.4 5.5 4.4 6.767 4.133 6.1 U 4.767 6.567 5.667 7.733 5.3 7.567 L 2 3.933 3.733 4.467 3.8 4.767 M3 M 3.567 5.4 4.933 5.767 4.833 5.633 U 4.8 6.633 6.4 7.033 5.867 6.8 L 3.6 2.7 4.233 4 3.467 4.5 M4 M 5.033 3.933 5.733 5.5 4.733 5.7 U 6.433 5.433 7.1 6.6 6.133 6.867 L 3.167 3.2 3.867 4.167 3.933 4.733 M5 M 4.367 4.367 5.167 5.233 5.067 5.967 U 5.567 5.667 6.4 6.567 6.233 7.067 L 3.2 3.467 3.1 4.867 3.3 3.833 M6 M 4.167 4.567 4.433 6.3 4.7 5.2 U 5.367 5.633 5.833 7.367 5.833 6.4 L 3.233 3.6 4.267 4.167 3.6 4.2 M7 M 3.967 4.367 5.367 5.333 4.967 5.4 U 4.933 5.1 6.333 6.667 6.2 6.5 L 3.067 3.733 4.067 4.767 3.8 4.267 M8 M 4.233 5.033 5.133 5.933 4.933 5.333 U 5.433 6.067 6.467 6.933 6.067 6.467 L 2.3 4 3.5 4.633 3.533 5.033 M9 M 3.467 5.233 4.6 5.9 4.567 6.267 U 4.6 6.467 5.9 7.033 5.7 7.167 L 2.867 3.533 3.867 5.033 2.733 4.767 M10 M 4.067 4.867 5.2 6.533 3.933 6 U 5.4 5.967 6.3 7.633 5.267 7.133 L 3.1 3.633 4.433 3.9 4.167 3.867 M11 M 4.2 4.933 5.833 5 5.467 5.167 U 5.433 6.033 7.067 6.367 6.533 6.2 L 2.567 4.4 3.133 5.033 3.167 4.9 M12 M 3.533 5.533 4.333 6.533 4.433 6.033 U 4.8 6.5 5.733 7.5 5.533 7.067 L 3 3.767 3.733 4.9 2.633 4.9 M13 M 4 5.133 5.1 6.233 4 6.2 U 5.067 6.267 6.4 7.4 5.2 7.267 L 3.333 3.4 4.133 4.467 3.867 4.333 M14 M 4.6 4.333 5.133 5.633 5.267 5.167 U 5.3 5.433 6.167 6.7 6.533 6.3 L 2.8 3.967 4.167 4 4.433 3 M15 M 3.967 5.2 5.3 5.267 5.667 4.1 U 5.167 6.2 6.6 6.333 6.8 5.233 L 2.6 3.6 3.767 4.6 4.033 3.1 M16 M 3.9 5.1 5.033 5.733 5.3 4.033 U 5.2 6.233 6.3 7.067 6.367 5.533 L 3.233 3.367 3.4 5.067 3.3 4.567 M17 M 4.6 4.633 4.767 6.567 4.467 5.833 U 5.833 5.833 6.1 7.533 5.7 6.833 L 3.7 2.767 4.067 4.267 3.533 4.767 M18 M 5.033 3.9 5.333 5.4 4.767 5.833 U 6.267 5.233 6.533 6.833 6 6.833 L 3.833 2.933 4.033 4.033 4.2 3.633 M19 M 5.1 4.033 5.467 5.3 5.367 4.767 U 6.167 5.167 6.8 6.6 6.767 6.033 L 3.7 2.767 4.3 4.533 3.733 4.367 M20 M 4.867 3.833 5.7 5.8 5 5.667 U 5.9 5.067 6.967 6.967 6.033 6.7 L 3.1 3.1 3.867 4.8 3.1 4.633 M21 M 3.8 4.1 5.2 6.067 4.4 6 U 4.933 4.967 6.633 7.233 5.667 7.233 L 2.1 4.6 3.067 5.533 2.9 4.6 M22 M 2.8 5.767 4.267 6.833 4.333 5.933 U 4.167 6.667 5.667 7.867 5.6 7.1 L 2.267 4.367 3.467 4.733 3.833 3.833 M23 M 3.367 5.6 4.7 6 5 4.967 U 4.733 6.633 5.967 7.1 6.267 6.3 L 3.133 3.367 4.267 4.167 3.933 4.3 M24 M 4.4 4.533 5.467 5.167 5.2 5.5 U 5.7 5.6 6.733 6.133 6.333 6.7 L 2.367 3.9 3.667 4.167 3.867 4 M25 M 3.6 5.133 4.833 5.5 5.333 5.033 U 5 6.433 6.3 6.733 6.5 6.2 L 3.133 3.5 4.033 4.5 3.433 4.067 M26 M 4.133 4.7 5.367 5.833 4.8 5.267 U 5.3 5.833 6.567 6.833 5.967 6.433 L 2.933 3.367 4.1 4.833 2.9 5.233 M27 M 4.067 4.533 5.333 6 4.133 6.433 U 5.233 5.5 6.7 7.133 5.533 7.433

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Table 6. Final fuzzy scores based on faculty members. Alternative L M U A1 3.647 5.082 6.575 A2 4.526 6.029 7.399 A3 4.78 6.355 7.968 A4 5.718 7.305 8.75 A5 4.448 6.029 7.543 A6 5.412 6.88 8.325

A1 A4 14% 19% A2 16% A6 18% A5 16% A3 17%

A4 A6 A3 A5 A2 A1

Fig. 3. Final crisp scores based on faculty members.

C. Users of 7.574. The next ranks were assigned to ‘private firms’ (A6) with the final crisp score of 6.908, ‘agricultural corporations’ (A5) with the final According to the results derived from water users (Tables 7 and 8) crisp score of 6.569, ‘production cooperatives’ (A3) with the final crisp and Fig. (4)), ‘traditional exploitation system’ (A1) was ranked at the top score of 5.37, and ‘irrigation and drainage networks exploitation of the list with the final crisp score of 7.621 and ‘water user companies’ (A2) with the final crisps score of 4.985, respectively. cooperatives’ (A4) was given the second rank with the final crisp score

7.574 7.621 6.908 6.569

5.37 4.985

A2 A3 A5 A6 A4 A1 Fig. 4. Final crisp scores based on agricultural users.

Table 7. The matrix of mean (the aggregated opinion of experts). A1 A2 A3 A4 A5 A6 L 5.4 3.333 2.633 4.767 3.567 4.3 M1 M 5.867 4.6 3.867 5.733 4.633 5.5 U 5.867 4.8 4.967 6.733 6 6.467 L 7.567 4.033 2.8 5.733 3.6 4.933 M2 M 5.7 4.633 3.4 6.5 4.233 5.967 U 5.9 5.433 4.3 7.267 5.133 7.267 L 5.367 3.333 3.3 4.967 4.5 5 M3 M 5.667 4.467 4.067 5.767 5.067 5.5 U 5.567 5.167 5 6.833 5.667 6.433 L 5.633 2.6 3.4 5.067 4.133 4.6 M4 M 5.4 3.467 4.433 5.933 4.9 5.333 U 6.067 4.5 5.4 6.533 5.8 6.133 L 5.433 3.067 3.1 4.933 4.467 4.633 M5 M 5.333 4.1 4.133 5.6 5.267 5.667 U 5.767 5 5.033 6.467 6.167 6.533 L 5.833 2.667 2.633 5.267 4.033 4.067 M6 M 5.633 3.333 3.733 6.2 5.1 5.233 U 6.067 4.4 4.8 6.8 5.767 6.133 L 6 2.167 4.333 3.9 4.7 3.867 M7 M 5.967 2.667 5.133 4.633 5.8 4.9 U 6.067 3.2 5.767 7.4 6.6 5.8

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Table 7 (Continued) L 5.7 3.067 3.533 5.033 4.533 4.333 M8 M 5.567 3.8 4.367 5.867 5.5 5 U 7.867 4.633 5.267 6.533 6.4 5.833 L 5.367 3.5 2.833 5.233 3.867 5.233 M9 M 7.467 4.233 3.5 6.1 4.533 6 U 5.7 5.133 4.6 6.933 5.567 6.733 L 5.533 3.3 3.133 5.233 4.1 4.667 M10 M 5.433 4.2 4 6 4.967 5.667 U 5.767 4.933 4.933 7.067 5.833 6.433 L 5.833 3.167 3.6 4.5 4.867 3.933 M11 M 5.9 4.367 4.4 5.367 5.867 4.9 U 8.2 4.9 5.4 6.333 6.5 5.567 L 5.667 3.433 2.967 5.1 4.2 4.6 M12 M 5.867 4.233 3.767 6.3 5.267 5.4 U 6.1 5.067 4.733 6.8 5.733 6.067 L 5.967 3.033 3 5.367 3.5 5.033 M13 M 5.8 4 3.933 6.367 4.567 5.667 U 6.1 4.767 5.067 6.967 5.367 6.567 L 6.133 2.467 3.733 4.7 4.467 4.733 M14 M 6.5 3.033 4.267 5.6 5.467 5.567 U 6.3 3.933 5.167 6.167 6.333 6.1 L 5.5 3.333 3.567 4.6 4.767 3.533 M15 M 5.7 4.3 4.133 5.633 5.7 4.2 U 5.8 4.9 5.067 6.467 6.3 5.133 L 5.567 2.9 3.6 4.7 4.567 3.567 M16 M 5.433 3.833 4.767 5.633 5.467 4.433 U 5.833 4.7 5.4 6.567 6.233 5.333 L 5.867 3 2.633 5.7 3.533 5.1 M17 M 5.833 4.033 3.567 6.767 4.3 6 U 6.2 4.633 4.667 7.367 5.2 6.6 L 5.567 2.367 3.367 4.8 4.1 4.6 M18 M 6 3.133 4.267 5.8 4.867 5.5 U 8.3 4.2 5 6.733 5.8 6.1 L 5.733 2.2 3.433 4.633 4.633 4 M19 M 5.633 3.133 4.433 5.6 5.367 4.867 U 5.967 3.733 5.467 6.467 6.533 5.867 L 5.767 2.833 3.5 5.233 4.267 4.6 M20 M 5.733 3.7 4.433 5.9 5.033 5.633 U 5.967 4.533 5.333 6.967 5.767 6.167 L 6.3 2.533 3.633 5.033 3.967 4.433 M21 M 6.367 3.4 4.433 5.867 4.833 5.5 U 6.367 3.967 5.5 6.667 5.967 6.267 L 5.467 3.8 2.633 5.933 3.4 5.267 M22 M 5.333 4.5 3.533 6.7 4.433 6.267 U 5.633 5.067 4.433 7.467 5.333 7.2 L 5.7 3.567 3.067 4.733 4.833 3.567 M23 M 5.867 4.5 4 5.6 5.4 4.467 U 6.033 5.133 5.033 6.567 6.567 5.4 L 6.067 2.933 3.3 5 4.367 4.467 M24 M 5.933 3.867 4.167 5.767 5.433 5.4 U 6.267 4.633 5.267 6.533 6.267 6.467 L 5.7 3.3 3.2 4.767 4.133 4.533 M25 M 5.867 4.133 3.867 5.667 5.133 5.333 U 6.133 5.067 5 6.367 6.3 6.067 L 5.767 2.9 3.633 4.967 4.1 4.5 M26 M 5.8 3.7 4.6 5.667 5 5.333 U 6.067 4.5 5.3 6.433 5.933 6.067 L 5.5 2.767 3.567 4.8 4.067 4.633 M27 M 5.467 3.6 4.4 5.833 4.933 5.833 U 5.9 4.2 5.267 6.633 6.033 6.333

Table 8. Final fuzzy scores. Alternative L M U A1 7.46 7.519 7.988 A2 3.903 5.023 5.989 A3 4.22 5.344 6.57 A4 6.442 7.577 8.701 A5 5.426 6.565 7.719 A6 5.772 6.936 7.99

4. Conclusions and recommendations - Assessing the water requirement of provincial and national development plans and formulating a water-deficit development plan at Given the importance of water and droughts in the Sistan region the provincial, regional, and national levels. and the significance of water governance from an economic and - Strengthening the orientation of different agencies towards improving environmental perspective, the following recommendations can be water-related policy making. drawn from the results: - Determining the growth requirement of different water using sectors in - Avoiding temporal, hasty, and sectoral decisions and actions (without development plans to achieve sustainability. a systematic perspective) for water reforms. - Performing further research on the governance of agricultural water - Designing and planning the deployment of a participatory water resources to develop a sound management pattern with respect to the governance pattern with an emphasis on empowering the legal and studied factors. institutional authority of non-governmental organization in the - Assessing the performance of farmers by agricultural resource conservation of water resources. governance indices and motivating them to develop good management

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134 exploitation systems in Sistan region, Journal of Applied Research in Water and Wastewater, 7 (2), 2020, 127-136.

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