O A

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Advances in Natural and Applied Sciences, 5(4): 379-391, 2011
ISSN 1995-0772
This is a refereed journal and all articles are professionally screened and reviewed
ORIGINAL ARTICLE
A National-Scale Assessment of Agricultural Development Feasibility using MultiCriteria Decision Making (MCDM) Approaches
1
Mohammad Azmi, 2Shahab Araghinejad and 3Fahimeh Sarmadi
1
Phd Student of Water Resources Engineering. University of Tehran. Iran.
Assistant Professor of Water Resources Engineering. University of Tehran. Iran.
3
Master Student of Irrigation and Drainage Engineering. University of Qhazvin. Iran.
2
Mohammad Azmi, Shahab Araghinejad and Fahimeh Sarmadi: A National-Scale Assessment of
Agricultural Development Feasibility using Multi-Criteria Decision Making (MCDM) Approaches.
ABSTRACT
Problem Oriented Approach in Integrated Water Resources Management (IWRM), requires that outcomes
of water resources development be assessed based on water resources sustainability at basin level. In planning
models, assessment of options and structural and non-structural actions and plans are also assessable based on
the variations of these criteria in view of the current situation. Hence, study and prioritization of options in Iran
entails the selection and measurement of water resources sustainability criteria at basin level. Agriculture sector
as the world’s main consumer of water has a significant role in water allocation in different countries. In the
present study, three multi-criteria decision making methods of AHP, TOPSIS and ELECTRE have been used to
rank the feasibility of agricultural development in second order basins of Iran. Next, existing trend of
agricultural development will be compared with the obtained rankings of MCDM methods. Results reveal that
there are signs of agricultural disharmonious and unsustainable development in some of second order basins of
Iran.
Key words: Agricultural Development, Sustainability Criteria, MCDM, Iran.
Introduction
Precipitation is the main source of fresh water resources in Iran and no other major resources can be
considered in this regard. Because, in long-term, amount of precipitation is fixed. Therefore, amount of water
resources of a basin and or the whole country is a fixed and specified value. This value indicates potential
capacity of water resources in basin or country. At national level, water resources potential of Iran is estimated
130 billion m3 per year. Moreover, with population growth as well as increase in activities and human
interferences, a part of potential resources affected by discharge of return wastewaters may not be operational or
their operation may involve risks and dangers. Even operation capacity of groundwater resources, which have
more balanced and fixed regime comparing to surface water resources, requires careful and specialized review
of primary information. Considering dependence of groundwater on precipitation and surface flow, its
vulnerability comparing to surface water resources in view of uncontrolled operation, pollution and interaction
between them should be assessed.
Agricultural development based on modernization theory has been the center of attention in the third World
Countries during the recent decades. Agricultural modernization in Iran has been considered since 1962. It
began with the initiation of land reform and was considered as a major prerequisite in modernization of
traditional rural communities (Karami et al., 1993). Regardless all of its advantages, analysis of agricultural
development policies during the recent decade indicates occurrence of negative and damaging socio-economic
and environmental impacts (Malakouti, 2000; Karami, 1993; Yazdi-Samadi, 1989) as a result of this process.
Common agricultural development strategies show major limitations in provision of a sustainable
development in Iran (Karami, 1993; Salmanzadeh, 1996). Due to existing uncertainties in agricultural
development processes, taking into account the risk management in all development design and implementation
stages is required more than ever (Fischer et al., 2006b; Fischer et al., 2009). Multi-criteria decision analysis
(MCDA) suggests a framework for the removal of common challenges in the management of different options
in a large water system. In this framework, attempt is made to gain relative satisfaction from stakeholders and
decision makers as much as possible and to introduce and rank suitable options for implementation or
Corresponding Author: Mohammad Azmi, Phd Student of Water Resources Engineering, University of Iran.
E-mail: [email protected]; Tel: 0098-9126788113
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completion (Hajkowicz and Collins, 2007). By definition, multi-criteria decision making method (MCDM) is a
process of screening, prioritizing, ranking and selecting in which by applying ranks to different options for the
existing quantitative and qualitative compatible and incompatible criteria, the best option is extracted from
among all considered options (Larichev and Moshkovich, 1995; Raju et al., 2000). Multi-criteria decision
making methods can be divided into the following five common and applicable categories: (Hyde et al., 2004;
Hajkowicz and Collins, 2007; Lai et al., 2008).
 Multi-criteria value functions.
 Outranking approaches.
 Goal or reference point method.
 Pair wise comparisons.
 Tailored methods.
Items 2, 3 and 4 above have the most application among all the above mentioned categories in solving
water and natural resources issues. Due to the challenges challenges and complexities of a problem, planners
choose the best method for obtaining the best strategy (Figueira et al., 2005a,b; Abrishamchi et al., 2005; Saaty,
2004). The most applicable method for items 2,3 and 4 can be mentioned as ELECTRE, TOPSIS and AHP,
respectively. Zarghaami et al., (2007) state that using fuzzy multiple attribute decision making on water
resources projects can gain more reliable decisions, especially in complex and complicated systems. Moreover,
it can be possible to exploit MCDM techniques for planning water pollution control (Karamouz et al., 2003).
Population growth, increase in drinking water demand as well as the necessity for more future development in
industry sector has convinced planners to have more control over agriculture sector development and to
simultaneously improve and increase agricultural efficiency. One of the most important issues that can be
discussed at national-level is to determine water basin ranking from agricultural point of view. If countries’
senior decision-makers know that considering criteria associated with water and agriculture sector, which fields
have developmental potentials and which ones should be prevented from agricultural further development then
they can provide more accurate planning and strategies in order to achieve sustainable development.
In the present study, ranking of agricultural development feasibility is done using three multi-criteria
decision making methods, AHP, TOPSIS and ELECTRE. Current trend of agricultural development will be
compared with the obtained rankings. In continuation of this report, a brief description of multi-criteria decision
making concepts will be provided and then decision making methods will be used for the ranking of Iran’s
basins. Finally, results and conclusion of the present research will be discussed.
Approach and Methodology:
To assess the current and development situation of agricultural water resources at a national-scale, it is
unavoidable to use a logical framework as the most important step to achieve a leader map. DPSIR as a common
accepted logical framework, could be brought forth for this goal. Five bases of DPSIR include: D: Driving
forces, P: Pressures, S: States, I: Impacts, R: Responses.
In section S and I, states of system and impacts are located. finally in section R, responses of a system in
opposition of driving forces, pressures and impacts are determined in current and future states.
In figure 1. DPSIR logical framework is presented to assess the current and development situation of
agricultural water resources at a national-scale. In section D of this figure, two main criteria, climate and
development, are taken into consideration. Parallel to these two criteria, in section P, change in rainfall, water
quality and unsustainable rate of water withdrawals are considered as pressure criteria.
Because of generality of drought concept, this criterion would be used instead of change in rainfall
criterion. Fluctuations of available water during wet and drought years are significant to evaluate. This indicates
that merely depending on annual water balance will not lead to reliable decision makings. On the other hand,
indications of climate change in some main basins in Iran call for more caution in depending on the existing
information and data.
All in all, three criteria drought, water quality and unsustainable rate of water withdrawals would be used in
processes of multi criteria decision making to assess the current and development situation of agricultural water
resources at a national-scale.
Case Study:
Iran is located at southwest of Asia adjacent to countries such as Turkey, Iraq, Afghanistan, Pakistan,
Armenia, Azerbaijan and Turkmenistan. Some parts of Iran are extended from north to the Caspian Sea.
Southern border of Iran is connected to the Oman Sea. Four major mountain ranges in the north, southeast, west
and center of Iran have formed a closed basin making it disconnected from the open sea and its vast plains are
full of current erosion sediments. Iranian basins are bowl-like and are not connected to the sea. This
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disconnection has led to the increase of soil and water minerals in the basins and thus considerable amount of
salt are compiled in the basins terminals every year, which have a great role in the abuse of water resources.
Mention can be made of Namak Lake, Urmia Lake, Gavkhooni, Jazmourian and Kavir-e Markazi as the most
major terminals in Iran. Outside these terminals, precipitations are led to the Caspian Sea or the Persian Gulf,
Oman Sea and Urmia Lake. Regarding surface water flow, Iran is divided into six main water basins and
considering climatic and topographic characteristics of Iran it is divided into thirty-fold second order water
basins. Based on the estimation of a 40 year old recorded information and data in Iran (1961 to 2001), total
precipitation in Iranian heights and plains is 425 billion m3. This is while net annual precipitation (precipitation
excluding losses) is 120 billion m3, which is 28% of total precipitation in Iran. From the total precipitation
mentioned above, 70% belongs to the heights and 30% to the plains. From the total annual precipitation in the
heights and in the plains, 73.5 and 6.2 billion m3 turn into surface runoff, respectively.
Fig. 1: DPSIR logical framework of A National-Scale Assessment of Agricultural Development Feasibility
using Multi-Criteria Decision Making (MCDM) Approaches.
Fig. 2: Display of supply-demand balance index and criterion in thirty-fold Iranian second order basins.
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In addition to the surface runoff due to precipitation, some surface runoff enters Iran from outside the
country. Total inflow to Iran is about 5.55 billion m3 per year that is associated with Aras and Urmia basins
(from Turkey), Atrak (from Turkmenistan), Hirmand (via Hirmand River from Afghanistan) and Garahghom
(via Harirood River from Afghanistan). Inside Iran there is surface flow transfer from one basin to another that
is considered in their balance.
Volume of Surface flows that leave the country through Rivers and mainly lead to the Caspian Sea and the
Persian Gulf is about 51 billion m3 per year. Volume of evaporation from natural lakes and dams’ lakes, pools
and surface waters is about 12 billion m3 per year. From the total precipitation in Iran and in Iranian plains, 32.2
and 8.7 billion m3 is infiltrated into ground water, respectively. Only an insignificant volume of ground water
resources enters Iran from outside. Total volume of ground water resources flowing into Iran is about 0.2 billion
m3, mainly inflowing from Aras and Urmia basins and from Turkey. Total ground water outflow is about 0.8
billion m3, major part of which flows into the Caspian Sea and the Persian Gulf. Hence, there is a total of 431
billion m3 inflow comparing to 434 billion m3 outflow per year, the difference of which (nearly 3 billion m3) is
experienced in water resources decrease, especially in ground waters.
Net annual water consumption in Iran is 61.9 billion m3, 92% of which involves agriculture sector
consumption. Average agricultural efficiency in Iran is about 30% that is increasing in the recent years due to
the attempt of authorities in replacing traditional irrigation methods by high efficient modern methods. In the
recent decade, climate change is happening because of global warming. This issue is also being studied in Iran.
Using 50-year timeseries of indicators of 25 meteorological stations in different locations in Iran and also
benefitting from the results obtained from Mann-Kendall Trend Test for all stations and seasonal situations as
well as applying geostatistics methods, annual amount of fluctuation precipitation in Iran has been provided.
Annual precipitation in northwest, south, southeast, east, center and some parts of north and west of Iran have a
decreasing trend with a minimum probability of 95%. Annual precipitation in southwest, parts of the west,
center, north and northeast of Iran have an increasing trend with a probability of less than 90%.
Criteria and Indices:
1.
2.
3.
Criteria employed for the ranking of agricultural development feasibility include:
Unsustainable rate of water withdrawals index.
Agricultural water quality index.
Drought index.
The above criteria will be explained in the following section:
Unsustainable Rate of Water Withdrawals Index:
Water resources development is also estimated by global sustainability criteria According to this criterion,
development does not refer to the maximum extraction of water resources. As recommended by the United
Nations, the threshold of a sustainable extraction of fresh water is considered as 40% of total water resources of
a region (GEO, 1999). this threshold can be calculated using follow equation:
WS 
WE
 100
TWR
(1)
Where WE: water extraction, TWR: total water resources of the basin and WS: water stress index in percent.
Removal of water resources more than this threshold is an index of water stress. Figure 1 shows the percentage
of fresh water withdrawal in different basins of Iran. Averaged water withdrawal in the entire country is 62%.
According to the mentioned international criterion, Iran is considered among the countries with water tension.
According to this criterion only 4 out of 30 basins in Iran lay in the appropriate zone. Also it is demonstrated by
the figure that 13 out of 30 basins withdraw more than 70 percent of their fresh water resources so are
categorized as basins with a potential high water stress.
Agricultural Water Quality Index:
According to Iran’s water resources qualitative classification in view of irrigation, salinity limitation and
percentage of absorbable sodium, resources with CISI class enjoy sufficient desirability and classes with C2S2,
C3S3 and C4S4 levels in view of salinity and alkalinity have medium, high and very high risk, respectively. In a
general view, basins qualitative classification criterion in this study is considered as: basins in which the
percentage of ground water resources with C2S2 or better quality is 50% or more are relatively in a desirable
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condition otherwise are considered as having undesirable quality. Major factors of Iranian rivers surface waters
pollution include mineral increase due to evaporation, presence of salt domes and drainage of agricultural lands
and urban and industrial sewages. Basins having undesirable surface water resources have been estimated on
this basis and through a general estimation. Water quality index and criterion in Iranian second order basins are
represented in figure 3. Greater amounts in figure 3 legend shows higher water quality. unit of legend is
percentage.
Fig. 3: Display of agricultural water quality index and criterion in thirty-fold Iranian second order basins.
Drought Index:
In figure 4. long-lead trend of annual precipitation changes in IRAN is shown. Despite the experiences in
hydrological and meteorological designs and calculations associated with water resources that mainly benefit
from hydroclimatological variables based on average historical observations, record of Iran’s and world’s
droughts, especially in the recent decade, has proved that water resources assurance without considering the
condition of drought occurrence in basins will lead to incorrect and misleading calculations.
Drought occurrence can be viewed as a major problem against water resources sustainable development.
Two main factors intensifying drought include; first, climatic special condition, management of which is out of
human control and ability however adaptation to it decreases received and second, damages and impacts
resulting from consumptions beyond climatic potentials of a basin, which can be managed and planned. In
droughts with 10-year return period, surface water resources of 24 Iran’s basins decrease to 50% of normal
condition. Water resources supply assurance index and criterion considering drought impacts in thirty-fold
Iran’s basins are shown in figure 5.
It should be noted that quantity of water resources would not guarantee resistance to droughts, for example,
Aras basin has water resources twice more than Taalesh-Anzaly but analysis shows that the vulnerability of
Aras is definitely more than Taalesh-Anzaly. Scale of figure 5 legend is from zero to 1 and dimensionless.
Greater amounts in that figure legend shows lower drought impact.
Multi-Criteria Decision Making:
Considering limited resources and multiplicity of objectives, evaluation criteria and existing limitations in
concepts and issues of various sciences, it seems essential to make use of optimization methods in order to
achieve the best strategies. To be able to identify the best option (a combination of objectives, criteria and
limitations) among various selections and combinations and to select the option for implementation, can be a
significant help for users, modelers and especially decision makers in expediting and improving development
and scientific major projects. When problems include various complexities and different evaluation criteria,
optimization methods should be replaced by multiple criteria decision making (MCDM) methods. For having
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comprehensible and tangible basic concepts, these methods are of great help to decision makers in selecting the
best options. Multiple criteria decision making methods are divided into two major categories as follows:
1) Multiple objective decision making methods (MODM).
2) Multiple attribute decision making methods (MADM).
Fig. 4: Long-lead trend of annual precipitation changes in IRAN.
Fig. 5: Display of water resources supply assurance index and criterion considering drought impacts in thirtyfold Iranian second order basins.
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MODM methods are used for project design and MADM methods can be applied in the selection of the best
option from among different administrative and management options. In the discussion of natural resources
management, especially in IWRM in a district (at river, basin, province and national-scale), due to the
availability of various projects each having its own profits and costs, selection of the best applicable option and
project combinations can prevent financial and natural resources misuse and can reduce direct and indirect
damages of management and development projects implementation to the possible minimum. MADM methods
applied in the present research are introduced in the following section.
MCDM Techniques:
Analytic Hierarchy Process (AHP):
One of the most common methods used in pair wise comparisons in multi-criteria decision making
approach is Analytic Hierarchy Process (AHP). This method was first introduced by Saaty between 1977 and
1980 (Saaty, 1977 and 1980). Uses of this method in different sciences have made AHP as one of the most
common MCDM applicable methods (Vaidya and Kumar, 2006). Using mathematical concepts and decision
makers’ and stakeholders’ opinions, AHP provides a process to obtain the best option among other options.
Capabilities of this method have been proved in development and environment projects (Saaty, 2001 and 2005;
Ock et al., 2005). In AHP, first the problem is represented in the form of a hierarchical tree structure and then
using pair wise comparison matrixes among criteria, weighting of criteria and sub-criteria is performed. In the
next stage, different options for each sub-criterion are given a score and finally through options ranking the best
option is obtained. Criteria pair wise comparison and also options scoring will be performed with regard to
sector and intra-sector group decision making (Saaty, 1980; Eastman, 2003).
Concept of a complex system and modeling of such systems was first explained in Kolmogrov’s Theorem
(Ngugen and Kreinovich, 1997). In AHP method, a large system is divided into sub-systems for preventing
complexities and assessment activities are performed in each system. Finally, assessment conclusion is
generalized to the whole system. Because of data insufficiency and also uncertainties in weighting criteria and
scoring options in natural sciences problems, AHP method will move in an under ignorance atmosphere
(Harwell et al., 1986).
Technique for Order-Preference by Similarity to Ideal Solution (TOPSIS):
TOPSIS is the most applicable method in distance to ideal point approach. In this method, two points are
specified as reference points. The first point is the ideal point and represents the best possible (ideal) situation.
The second point is the worst (negative ideal) point. Each option is evaluated considering the best (ideal) and the
worst (negative ideal) possible situation in different criteria and the result of all distances of an option in
different criteria in relation to the reference point will be the final score of that option. Finally ranking is done
through comparing the scores of all options. Ultimate objective of TOPSIS process is represented in the
following relations:
k
1
min d p  ( ( f ( xt )  f ( xt* )) p ) p
(2)
t 1
1
f ( xt )  f ( xt* ) p p
min d p  ( (
) )
f ( xt* )
t 1
k
(3)
f ( xt ) : Current point of option f in xt criterion.
f ( xt* ) : location of option f in ideal point of xt criterion.
k : Number of assessment or evaluation criteria for each option.
p: The importance of deviation from the ideal situation.
dp: Distance of an option from ideal situation.
United Nation Environmental Program (UNEP) has provided different methodologies depending on project
type, situation and existing limitations for multi-criteria analysis using TOPSIS. In addition, it describes
different stages of a project’s analysis in an applicable manner (UNEP, 1987).
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Eliminate ET Choice Translating Reality (ELECTRE):
Different applications of this method in environment and water sciences indicate its high efficiency. The
main objective of ELECTRE method is to rank the options and obtaining the best option among all options is
not its main concern (Tecle et al., 1988; Hobbs et al., 1992; Roy et al., 2002; Raju and Duchstein, 2004). In this
method, an option in different criteria is assessed in relation to others and is ranked based on the number of its
outranking in the criteria. ELECTRE does not value the amount of outranking in each criterion and it is only the
number of outranking that is a criterion for assessment. Researchers show that outranking of two options to one
another depends on the comparison between the value of concordance and disconcordance indices (Belton and
Stewart, 2003). Concordance index for testing the outranking of A to B is as shown in the following relation:
w  w
C ( A, B )  
w  w  w
(4)
w+, is the sum of criteria weights where A is superior to B.
w-, is the sum of criteria weights where B is superior to A.
w=, is the sum of criteria weights where there is no superiority between the two options. Discordance index
is stated in the following relation:
D ( A, B )  max( iB   iA )
(5)
viB, refers to the value function of impact of option B considering criterion i and viA addresses the value
function of impact of option A considering criterion i. In order to prove the outranking of option A to option B,
value of C (A,B) must be higher than D (A,B), both indices must be in between the two low (q) and high (p)
thresholds and finally the value of w+ must be greater than w-.
Results and Discussion
Scenarios:
Planning for water resources should be done for possible scenarios. One of the possible scenarios can be
considered is the current trend of operation and water resources consumption. Other scenarios can be prepared
based on different priorities. For the projection of possible scenario of the continuation of the current situation, it
is necessary to study and review previous trend of water use and removal. Average annual rate of operation from
water resources during the recent years has been 1.4 percent that indicates increase in the operation from
resources. Basins of the Caspian Sea (Talesh-Anzali Lagoon, Gharahsoo, Gorgan Rood, Haraz and Atrak) and
Central basin have experienced a growth above the average value in the country. This is while, basins at south of
Iran, especially Karkheh show significant growth in operation from surface water resources the reason of which
lies in the development of related infrastructures.
It should be noted that the majority of basins in Iran have experienced increase in operation from
groundwater resources. South and South-east basins have had an increase above the average due to climatic
limitations in operating from surface waters. If the abovementioned cases are seen as the main trend of the
current situation then the scenario of continuation of this trend does not indicate a clear vision of water
resources development, since, presently most of basins are being operated in an unsustainable situation. Thus,
increase in operation according to the previous pattern, increases the deviation from sustainability criterion more
than before.
Threat:
Continuation of water resources pollution, especially due to municipal and industrial wastewaters,
uncontrolled development along with unnecessary use of groundwater resources, finding unsuitable locations for
spatial development of population and economic areas are considered among the major threats to the sustainable
balance of supply and demand in the current situation of Iran’s basins. It is projected that these threats will
increase more during the coming years in some basins such as Caspian Sea basin and East and Central basins of
Iran. One of the external factors that can make the water resources sustainability indices worse than the current
situation is climate change. Although no comprehensive and integrated studies have been conducted regarding
the occurrence of climate change in Iran, however, there are signs such as temperature increase, change in the
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number of rainy days and freezing periods in different basins that indicate the possibility of the occurrence of
this phenomenon in Iran. Mention can be made of changes observed in Central and Northern basins of Iran.
Studies reveal that climate change and temperature enhancement not only increase the frequency and intensity
of drought but also by changing precipitation pattern augment the chance of the occurrence of damaging water
floods. Climate change as the main factor for decreasing the existing water resources and changing major
patterns is among the threats that must be studied in the form of possible scenarios.
Opportunities:
Making use of wastewater is one of the opportunities that should be benefitted from to the maximum. Decrease
in desalination plants has increased the possibility of using wastewaters more than before. More than two third
of water consumed in houses, industry and mines return to the environment in the form of wastewater and
somehow pollute soil resources. On the other hand, after performing necessary processes, these waters can be
utilized for different purposes, especially for agriculture. Hence, making use of these resources not only satisfies
demands but also can have a role in decreasing environmental and water quality issues. It is worth mentioning
that volume of domestic and industrial wastewaters in Iran is currently estimated 4066 and 579 million m3,
respectively. According to forecasts, this volume will reach to about 1.3 and 4 times in the next two decades.
Presently, nearly 500 million m3 of municipal wastewaters are being treated and by Regional Water Companies
are being planned to reuse. Considering the projects under execution by water and wastewater authorities in
provinces of Iran, volume of wastewaters being used from municipal wastewaters is estimated relatively high
comparing to other countries. In general, making use of this capacity not only decreases the threats pertaining to
pollution sources but also if managed properly can reduce lack of balance in supply and demand, especially in
urban areas in the Caspian Sea, West and Central basins of Iran.
Results of MCDM Techniques:
Weighting the criteria has been obtained with regard to entropy weighting concepts. Each abovementioned
criterion and index is produced as an information layer in GIS environment (figure 2, 3 and 5) and then the
multi-criteria decision making methods mentioned earlier in this report will be applied to these information
layers. Results of ranking in view of agricultural development feasibility from water resources perspective are
represented in figures 6, 7 and 8. Comparison of figures 6, 7 and 8 reveals that although rankings of thirty-fold
second order basins are not exactly similar, however a general view indicates that center and east of Iran has the
most undesirable condition with regard to agricultural development, the reason of which is severe scarcity of
water resources and precipitation in these regions of Iran. Most desirable parts of Iran regarding agricultural
development include parts of Iran’s north, northwest and west side. Other basins are in conditions ranging from
having water tension to relative desirability. According to the results, agricultural development priorities in Iran
can be divided into two following group:
Group 1: Basins with maximum 51% of whole water resources in IRAN. (7 basins).
Group 2: Basins with maximum 28% of whole water resources in IRAN. (10 basins).
Group 3: Basins with maximum 21% of whole water resources in IRAN. (13 basins).
In figure 9. ranking of basins based on before mentioned analysis in three main groups is shown. vertical axe of
this figure shows priority of agricultural development, greater amounts indicate lower priorities to develop.
Summary and Conclusion:
Volume of water removal and study of three criteria of supply and demand sustainability, water quality and
water supply assurance (drought occurrence) in the form of a planning model with a problem-oriented approach
for IWRM in Iranian second order basins indicate that not only Iranian irrigation systems facilities cannot be
developed but also if the previous trend of operations, as one of possible scenarios, is continued in the future, a
critical condition will be encountered.
Currently, some basins cannot even supply drinking water and industry water demands, i.e. they have
surpassed maximum water use for agricultural demands for which necessary and prompt measures are required.
In the present research, attempt has been made to provide a clear view of the situation using values and figures
and to show its future intensification with regard to the existing forecasts. Based on the available information
and data, it seems that a specific classification can be achieved for the ranking of basins and for the forecast of
more serious measures regarding some of these basins.
Primary analyses reveal that climate change impact is a thinkable scenario affecting agricultural condition
in Iran. Considering the impacts of climate change on water resources, Iranian basins can be divided into the
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following categories. First category includes basins with higher priority in the study of climate change, second
one is involved with moderate priority and third category consists of basins with the least priority. Further more,
another classification can be considered for these basins based on limitation removal priorities. Hence, basins
can be divided into three groups of: basins with removal limitation priority, quality issue removal and provision
of strategies for fighting against drought.
Fig. 6: Results of thirty-fold Iranian second order basins rankings considering agricultural development in view
of water resources using AHP multi-criteria decision making method.
Fig. 7: Results of thirty-fold Iranian second order basins rankings considering agricultural development in view
of water resources using TOPSIS multi-criteria decision making method.
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Fig. 8: Results of thirty-fold Iranian second order basins rankings considering agricultural development in view
of water resources using ELECTREC multi-criteria decision making method.
1
0.9
Group 3
Development Priorities
0.8
0.7
Group 2
0.6
0.5
0.4
0.3
Group 1
0.2
0.1
Daranjir Desert
Hamon-Hirmand
Dogh-sorkh
Abargho Desert
Loot Desert
Dogh-Petergan
Hamon-Meshkil
Mehran
Grah Ghom
Central Desert
Haleh
Hamon-Jazmorian
Aras
Tashk-Bakhtegan
Mond
Sedij rivers
Atrak
Salt Lake
Southern Balochestan
Gavkhoni
Urmia Lake
Haraz till Gharasoo
Gharasoo till Gorganrud
Zohreh and Jarahi rivers
Krakheh
West border
Sefidrud
Karoon
Between Sefidrud till Haraz
Talesh-mordabe Anzaly
0
Fig. 9: Ranking of basins in IRAN based on development priorities of irrigation water resources (vertical axe
shows priority of agricultural development, greater amounts indicate lower priorities).
It should be accepted that the existing beliefs and insights regarding mere attention to supply-side and
structural plans and measures must be modified with regard to demand-side management and management
based on the balance between water supply and demand, especially in basins with high demand. Although one
of the opportunities is to use nonstandard waters, however it is in no way sufficient. Demand management
measures based on sustainable development theory, creation and expansion of natural potentials, improvement
of administrative and legal structures for administration of new responsibilities towards water saving,
maintaining water resources value proportionate to consumption type and stating required new rules and
regulations and their sanctions are considered as the main approach. These cases should be studied and provided
in a strategic planning in the form of more weighed and deliberate scenarios in order to obtain a more real
knowledge of balance between water demands in the sectors of health, drinking water, environment, industry
and agriculture demand in different scenarios and its requirements.
390
Adv. in Nat. Appl. Sci., 5(4): 379-391, 2011
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