7th ASAE Conference, Hanoi Year: 2011 Prioritize the use of Kashmar plain agricultural lands by using multi criteria programming (VIKOR)

Somayeh Shirzadi Laskookalayeh1 , Mahmood Sabouhi Sabuni*2

Abstract

The drought Phenomena and its consequences reduce the level of groundwater, lack proper nutrition, dry surface water resources and more harvest of the groundwater resources substantially the sum of these cases is Cause transfer the salty waters to ground water table and will limit capacity required harvest from aquifer and quality of the water. The VIKOR method was applied to determine the best feasible solution according to the selected criteria including the region rainfall situation during different years, soil permeability, land slope and water quality indicators, including SAR, RSC, salinity for determine of groundwater resources quality and land- use restrictions in Kashmar plain in east-north of Iran. The results of sampling in the Kashmar Plains showed that water quality decreased in move path from north to south the groundwater table of Kashmar plains. The use of groundwater resource excessively, downfall of the groundwater level and followed to salinity increased, has been caused to decrease of agriculture water quality and the land- use restriction. Furthermore, the results of the model in years 2008 and 2010 showed that to continue the current form indiscriminate harvesting of groundwater resource due to is the advancing front of salinity to upstream regions with low salinity. Therefore, it is necessary for sustainable management of groundwater resources, control the indiscriminate harvesting and minimizing damage to the groundwater table of the county, experts perform limits the use of agricultural land with the modified cultivated model, the use of deficit irrigation methods.

Keyword: Agricultural land use, Ground water table protection, Quality, VIKOR

1 . PhD Student of Agricultural Economics Department of University of Zabol Iran. Email: [email protected]

2 . Associate Professor of Agricultural Economics Department of University of Zabol Iran. Email: [email protected]

Introduction

The 90 percent of agricultural water use is devoted to the world (Rahman et al, 2004). This figure is in Iran's 93 to 94 percent (http://ict.moe.org.ir, 2004). Due to climatic conditions, rainfall distribution, the slope of the land, location and position of Iran in the row of arid countries, water shortages are enumerated, one of the developing limiting factors in Iran. Severe restrictions and declining of water quality in one hand, population increase, urban development, agriculture, industry and increased demand for water on the other hand, these are challenges that If the inattention to its development in the country is facing with serious bottlenecks and obstacles in the near future. Hence to prevent the critical situation of water and the consequences reduce the overuse of groundwater resources in these areas, more attention to these issues seems necessary. The Kashmar county areas with a shortage of water resources are a problem region in Iran and gradually are increasing the amount of problems. This county has located in southwestern of Khorasan Razavi province and the eastern periphery of Kavir plain. Amount of rainfalls is 680 Mm3 in year That about 483 Mm3 (71%) is evaporated directly and about 156 Mm3 (23%) as surface runoff and 41 Mm3 (6%) to infiltrate the groundwater aquifers. A large variety of agricultural products is high in this county and are cultivated various products of subtropical regions and moderate (Kashmar Agricultural Jihad (KAJ, 2010). The groundwater is included dominant source of water in agriculture and the amount of water discharged is higher than the charged rate, so that the average decline in groundwater levels in the county of Kashmar is reported in more than one meter in each year (KAJ, 2010). The effective factors of ground water table charged is included the infiltration of rainfall in the basin, the surface flows of input from adjacent basins, the entrance amount of ground water, transfer water from other basins, Infiltration of flood, the return water from farms and urban and industrial wastewater that their value depends on different regions conditions of the Kashmar plains (Kashmar regional water office, 2010).

In this study, about 700 hectares of agricultural land was considered plain Kashmar subsection 8 of deep wells was divided. This subsection is to change the quality of underground water resources for irrigation of lands to be harvested. For this purpose, Eight wells in the north to south along the plains were selected each of the wells,

land located in the north west, west, south west and south of the irrigated plains are Kashmar.

These wells according to area under irrigation in the north-south direction of plains is including Kalate Khan, Haji Abad, Argha, Shoorab Noghab, Ali Abad Barkal, Gharbe Shoorab, Shargh Sad Al-din, Jafar Abad, respectively. According to source of groundwater table witch has emanated from mountains of north west of the county of Kashmar, the well is located in the Kalate Khan subdivision is well closest to the watershed that was selected as the sample source. The other wells distance to the watershed has measured to obtain water quality standards and salinity. And with sampling of water wells in this path (north to south) was investigated. The water quality, water quantity, discharge, physical and chemical changes in water, and water quality impacts on surrounding agricultural land (irrigated with water). Weather of Kashmar plain, rainfall, permeability, soil characteristics, slope and excess harvesting from the groundwater resources due to the population increasing has affected environmental quality of using natural resource and consequently, it has effected on region people life, efficiency and sustainability of water resources and agriculture. Therefore, protect of groundwater resources with application of agricultural land use restrictions is appropriate strategies that should be considered further. Accordingly, it is necessary to will be planned land use restrictions strategies ranking for various Subdivision of Kashmar watershed that emanate from the northern mountains with varying degrees of potential effects on environmental quality of groundwater sources (wells) and agricultural land. Since the investigation of destruction and potential harm to groundwater resources due to excess using of agriculture land to measure and is expressed on based of several criteria, The multi-criteria analysis method was used as technical for loss quality problem and damage to groundwater resources. The VIKOR method was used in this study, this method expand Multi-criteria optimization of complex systems to find alternative compromised ranking according to criteria selection (Opricov and Tzeng, 2003, 2004). In recent years, Multi-criteria optimization is widely used in environmental resource management (Bryan and Crossman, 2008 & Chung and Lee, 2009). In used field of multi-criteria decision methods used making (MCDM) via Vikor method have not been done many studies in agriculture. But some studies which have used the VIKOR method

in other research areas are included: Krystbal (2011) studied the selection of renewable energy projects in Spain using VIKOR method. In this study, was used via Analysis Hierarchical Process (AHP) for determination of weights and degree of different criteria importance. The results showed that plant biomass, according to the considered options in the model, are the best choice. Liu et al (2010), used the VIKOR modified multi-criteria decision method to improve the quality of airline passenger services to families in Taiwan and ultimately, it was expressed to improve of different programs for customer satisfaction increase. Koo and Liang (2011) studied the combined VIKOR method and analysis of Gray relationship to assess the quality of service in seven north east Asia international airports. The results showed that the method is effective and applicable to multi-criteria decision making problems and includes the unique quality traits in the fuzzy environment. Kaya and Ghahraman (2010) proposed the planning for multi-criteria renewable energy via hierarchical combined method and fuzzy VIKOR in Istanbul for the best selection and location of energy policy. Results showed that among the considered options by for creation of wind turbines, the wind energy is a renewable and important energy in Katalka in Istanbul. Sanai et al (2010), studied the group decided method to choose their supplier via fuzzy VIKOR method. In this study, the main purpose is determination of problem region ranking to achieve sustainable agriculture. the area of each irrigated agriculture region by wells have considered between 50 to 100 acres and crops products is including wheat, barley, melons, grapes, pomegranates, saffron. Groundwater samples obtained from the wells is only water supplier resource for these products. Data for the study were collected from Agricultural Jihad and regional water office of Kashmar county during the years 2008 and 2010 and Kashmar meteorological office during the years 2008 to 2010.

Material and Method Multi Criteria analysis via the VIKOR method

For priority determine of the agriculture problem areas there are several criteria which are conflict together, so it is preferred the determinant of one compromise solution than an optimal solution. the Vikor method is a tool applicable to multi-criteria analysis, can used by selecting and ranking from a set of alternatives the conflicting criteria in

recognition solution adaptive weights and criteria (Opricovic,1998., Opricovic and Tzeng, 2004., Tzeng et al, 2005., Tong et al, 2007).

Alternatives in this study are included the 8 of agricultural area with known examples well such as Kalate Khan, Haji Abad, Argha, Shoorab noghab, Ali Abad Barkal, Gharbe shoorab, Shargh Saad Eddin and Jafar Abad. The considered criteria for each subsection are included low quality of water for assess of environmental potential effects of Kashmar Plains, rainfall, permeability, land slope, distance of any alternatives until of original watershed. Since factors such as slope, rainfall, the distance of each subdivision until original watershed can play an important role in the transmission no quality. Therefore, these factors were selected as measures of quality of each subsection. The water quality criteria based on six factors, electrical conductivity(EC), sodium adsorption ratio (SAR), acidity (PH), chlorine (CL), total residual solids(TDS) and excess carbonate(RSC) was determined. Which of these factors, two factors that represent the electrical conductivity total soluble salts in water (SAR) as the ratio of sodium ions to calcium and magnesium ions are effective more than other qualitative factors for agricultural. In addition to salinity problem, the extra carbon in water is another limiting factor that is displayed as RSC and it is inclusive the excess of carbonate and bicarbonate per liter to milligrams of calcium and magnesium on the Meq. If the RSC in this ranking is over the 2/5 Meq, water use in agriculture is limited (Alizadeh, 2000). Since the factors listed to determine the importance of quality criteria and standards for multi-criteria analysis, different scales are used between 1 to 3 are normalized (Chang and Chung, 2009). Equation 1 is Normalized indicator of rainfall (R), Slope (S), permeability (F), Total demand solid (TDS), electrical conductivity (EC), the chlorine (CL), Sodium Adsorption Ratio (SAR), acidity (PH) and excess carbonate (R.S.C) criteria. It set the values of these indicators between 0 and 1.

The distance criteria (DI) and water loss quality (PI) are normalized by using the equation 2 and 3. The PI is the mean of index Total demand solid in water, electrical conductivity,

the amount of chlorine, sodium adsorption ratio, PH and excess carbonate (Chang and Chung, 2009).

The Vikor approach prioritize algorithm is included the following steps (Chang and Chung, 2009):

1 - Determine the minimum and maximum value for the 5 criteria considered in whole subsection: m, represents subdivision or any area of agriculture and n, represents the criteria in each subsection. In this study were considered m = 8 and n = 5.

2 - Compute of the criteria optimal values ( ) and the unfavorable values ( ) for each subdivision.

is amount criteria i in the subsection j and the weight of each criterion. In this study it was assumed that all criteria has a similar effect on ranking importance the of each subsection. Thus, the weight of each criterion was 0.2. i.e w1=w2=………wn=1/n=0.2

3 - Compute the value as a measure of priority for each subsection

(8)

γ is the weight strategy for the maximum desirable and ( ) unique weight for the undesirable values that is considered in studies 0/5, generally.

4 - Compute the amount for each subsection is as an indicator of the restriction of using agricultural land which has been normalized by equation 13. The largest amount for this indicator is represents of farms use restriction ranking strategy performance for each subsection.

Results and discussion

Figure 1 show the study area rainfall situation during the different years.

70

60 Monthly rainfall average 2010 Monthly rainfall average 2009 50 Monthly rainfall average 2008 Monthly rainfall average 2007 40

30

20

10

0 Feb Jan Dec Nov Oct Sep Aug Jul Jun May Apr Mar

Chart 1: condition of rainfall in different months and years of Kashmar Source: Meteorological Office of Kashmar

As can be seen in Figure1, according to the annual rainfall, the Kashmar plain has not appropriate condition and average annual rainfall has decreased in 2010 compared to 2008.

Table 1: Irrigation water quality guide Amount of water harvesting water quality criteria Unit No problem Problem Dangerous EC ds/m <0.7 0.7-3 >3 Salinity TDS mg/L <450 450-2000 >2000 SAR <3 3-9 >9 Ion toxicity CL Meq/L <4 4-10 >10 PH Normal range 6/5 – 8/4 Restriction of water consumer for agricultural R.S.C Meq/L when R.S.C> 2.5 Source: Alizade, 2008

In tables 2 and 3 are presented different factors of ground water qualitative criteria survey for deferent subdivision in years 2008 and 2010. Due to table 2 and on based presented irrigation water quality guide in table 1, all subsections have EC greater than 0.7 (ds / m) tolerance threshold except Haji Abad and Argha and three final subdivision are (Gharbe

shoorab, Shargh Saad Eddin and Jafar Abad) the problem region because of groundwater loss quality. Also, evaluation of sodium adsorption ratio (SAR) in various subsections showed that due to the high SAR greater than 3, all subsection are in the range of salinity problem except Kalate Khan. All regions have less amount of water extra carbon than 2.5 except subsection Argha that are desirable. Based on presented amounts of water quality standards in table 1, the evaluation amount of chlorine (water toxicity) and TDS showed that Gharbe Shoorab, Shargh Saad Eddin, Jafar Abad are highest problem regions and water loss quality. Also PH for all subsection is the threshold levels of problem.

Table 2: Different factors of agricultural water loss quality standards in the different subdivision of the Kashmar plains in crops year 2010

Factor EC SAR PH CL TDS R.S.C subsection Kalate khan 0.838 2.86 8.2 4 527.94 0.51 Haji Abad 0.591 4.2 8.3 0.8 372.33 1.65 Argha 0.539 6.08 8.2 1 339.57 2.8 Shorab Noghab 0.783 5.53 8.4 1.8 493.29 1.64 Aliabad Barkal 26 12.54 8.1 17 16.38 0.31 Garb Shoorab 9.85 24.71 8.4 68 6205.5 0.18 Shargh Saad 13 21.11 8 80 8190 0.1 Eddin Jafar Abad 14.060 25.85 7.9 94 8857.8 0.1 Source: Regional water county of Kashmar

Table 3: Different factors of agricultural water loss quality criteria in the different subdivision of Kashmar plain in crops year 2008 Factor EC SAR PH CL TDS R.S.C subsection Kalate khan 0.703 3.21 8 2 442.89 0.71 Haji Abad 0.525 4.97 8.3 0.7 330.75 2.13 Argha 0.501 8.03 8.4 1.2 351.63 3.67 Shorab Noghab 2.080 9.77 8.2 14.2 1310.4 0.58 Aliabad Barkal 2.403 9.62 8.2 12.8 1530.9 0.26

Garb Shoorab 1.103 22.19 7.7 80 6948.9 0.11 Shargh Saad 12.460 23.83 8.1 81 7849.8 0.1 Eddin Jafar Abad 13.010 24.5 7.6 90 8196.3 0.1 Source: Regional water office of Kashmar county

In addition to, comparing of tables 2 and 3 show that the factors quantities of water loss quality criteria increased in 2010 than to 2008 that expression of an additive trend of groundwater loss quality increase and salinity is due to excess use of agricultural lands and agricultural land use restrictions are more apparent.

Factors of the groundwater loss quality criteria after normalized using the equation 3, as a criteria of loss quality, along with other effective normalized criteria on land use restrictions ranking is considered for determine of the priority of the subdivision of agricultural. The results of this study have showed in table 4.

Table 4: Restriction of use of agricultural land (Q ') method for each subsection VIKOR Distance Rainfall permeability Slope PI Q Q' Kalate khan 0 10 10 10 2.25 0.5 0.2 1 Haji Abad 1 7.12 6.79 10 3.16 0.43 0.2 8 Argha 1.21 6.44 5.53 7 3.07 0.52 0.2 Shorab Noghab 2.31 5.76 5.05 7 3.61 0.28 1 Aliabad Barkal 2.93 4.30 3.44 1 3.60 0.79 0.1 Garb Shoorab 5.84 2.66 2.40 4 7.12 0.37 0.3 8 Shargh Saad 6.67 1.73 1.41 1 7 0.78 0.1 Eddin Jafar Abad 10 1 1 1 6.53 0.72 0.1 1 Source: research findings

As can be seen in table 4, according to the normalized criteria of rainfall, infiltration, the agricultural lands slope and distance of each subdivision from watershed, subsection Argha than to other subsection has higher degree of importance for performance of land use restrictions considered to the highest value of Q '. Thus, according to the results, ranking of subdivision for performance of land use restriction are such as: Argha, Gharbe shoorab, Haji Abad, Kalate Khan, Ali Abad, Shargh Saad Eddin, Jafar Abad and Shoorab noghab, respectively.

For observation of salt front advancing and loss quality of ground water resources, VIKOR method performance according to dataset of 2008 in different subdivision of the Kashmar plains and the normalized amount of land use restriction ranking (Q ')on basis of dataset 2008. And the compared results of it with obtained results of 2010 crop year are expressed in table 5.

Table 5: Comparison of agricultural land constraints Q ' Crop year 2008 Crop year 2010 Kalate khan 0.19 0.21 Haji Abad 0.34 0.28 Argha 1 1 Shorab Noghab 0.1 0.1 Aliabad Barkal 0.22 0.2 Gharb Shoorab 0.33 0.38 Shargh Saad Eddin 0.12 0.11 Jafar Abad 0.11 0.1 Source: research findings

As can be seen in table 5, the obtained results of restriction situation comparison of agriculture land use of Kashmar plain in different subdivision in line of north to south in 2008 and 2010 years, express that Gharbe shoorab has arrived to third and second rank in, respectively.

Also, Kalate Khan subdivision has been in fifth rank of land use restrictions at 2008 that has located in priority fourth rank at 2010 that represents a salinity front progressive and an increase of water loss quality from south to north of Kashmar plain.

Therefore, it is necessary to prevent the destruction of agricultural areas, reduce of groundwater loss quality, appropriate and optimal use of groundwater resources of Kashmar plain and perform requirement emprises to achieve sustainable agriculture.

Conclusion

Multi Criteria analysis via the VIKOR method was performed for about 700 hectares of agricultural land of Kashmar plain. The study results showed to achieve sustainable agriculture in the plains of Kashmar, salinity Reduce, water loss quality, reduce of groundwater decline and damage to groundwater table, it is necessary to performance of ranking of agricultural land use restrictions and changing of crop. Also, on basis of results, at Argha subdivision is faced with risk of salinity and groundwater loss quality due to excessive harvesting. It is necessary to revision in crop programs for achieve to sustainable agriculture and water resources of this subsection. Also, the comparison of water quality criteria and factors in 2008 and 2010 showed that salinity front and loss quality is advancing because of neglect to agriculture sustainability and groundwater resources.

Therefore, if is been extended this trend, in the near future, in addition to the effects of drought will be faced with water resources crisis and its consequences. The continuous harvesting of these groundwater resources will gradually increase water salinity, and reduces quality that also, was caused to soil salinity. Thus, for removing this problem in addition to groundwater table nutrition should be propertied amount of harvesting and to compensate has been used form the low-irrigation method and increase of irrigation efficiency.

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