Today, considering the limitation of water resources and the growing population, countries around the world have been driven to increase agricultural production per unit area and maximize the use of these resources, and the growth of the population and the increase in living standards have increased the demand for food. In this regard, it is important to identify and understand the parameters that have an effect on agricultural production. In this regard, the optimal use of water and soil is one of the most important factors, so knowing the potential of agricultural land and supplying the water they need is one of the most important factors for increasing production. For these reasons, planners are encouraged to use the fuzzy analysis hierarchy process tool in combination with GIS to integrate and process different factors (Albaji et al., 2015; Turkish Statistical Institute, 2018; Hoseini, 2019) . These methods have provided a structured and explicit assessment framework (Karimi et al., 2018) and facilitated judgments based on soil characteristics regarding agricultural land use management practices (Roy et al., 2018). Lu et al. (2009) investigated the land and soil characteristics of 972 hectares of the Black Sea region of Turkey and prepared a land suitability map for surface and sprinkler irrigation methods for Charsamba Delta. The results showed that the fuzzy method for land evaluation is more flexible and sensitive, and this method reflected the real conditions of the region more accurately than the parametric method. Determining the suitability of land for irrigation requires evaluating the properties and topography of agricultural land. Therefore, for the optimal use of water and soil resources, methods that more accurately consider the suitability of the land for the type of irrigation should be used. In recent years, fuzzy inference structures have been used in many sciences. These methods take advantage of the linguistic power of fuzzy structures and this method can be used to research very complex processes. Fuzzy methods are one of the effective methods in the field of forecasting and modeling (Akbarzadeh et al., 2009). According to reports, fuzzy methods also use language and human experience (Karatalopoulos, 2000). Sys et al. (1991) proposed a parametric grading technique for land grading based primarily on soil properties. Based on this technique, the measurable characteristics of soil suitability for irrigation are divided into four. Miháliková and Dengiz (2019) used parametric evaluation to compare drip and rain irrigation methods in a farm in the south of Ankara. In this study, using geographic information system (GIS), soil physical properties, topography, salinity, alkalinity, and drainage capacity were analyzed and relevant maps were presented. The results showed that 31% of the lands in the study area are suitable for sprinkler irrigation and 51% of the lands are suitable for drip irrigation. The results showed that sprinkler irrigation is better than drip irrigation in more than half of the areas. Studies have shown that the use of GIS in parametric evaluation can provide special benefits for easier selection of irrigation methods, saving data analysis time (Hoseini and Delavari, 2015). Naseri et al. (2009) studied the parametric method in Lari plain and considered six factors including soil texture, lime, soil depth, salinity, slope and drainage. Their findings showed that 1732 hectares (48.5%) of the land surface were suitable for all three types of irrigation methods (drip, sprinkler and surface) and 384 hectares (10.8%) of the land were unsuitable for drip irrigation only. Calderon et al. (2005) studied the qualitative assessment of soil suitability for surface and drip irrigation in Shuang County, China. They used the parametric method of Sys et al. (1991) and GIS software to prepare land suitability maps for surface and drip irrigation. benefited The results showed that increasing the land slope with decreasing soil depth and increasing soil sand percentage is one of the limiting factors of irrigation in the region. The studied area, which has an area of 5175 hectares, is a part of Oltan plain, about 35 km southwest of Mughan city and 225 km northwest of Ardabil province. The geographical coordinates of the region are 47° 35' 57" to 47° 43' 22" east longitude and 39° 25' 13" to 39° 28' 27" north latitude and Fath-Ali village in the north of Ardabil province. It is located in the northwest of Iran. The height of the land above the sea level in this area is 158-254 meters, the average annual rainfall is 284 mm and the average annual temperature is fortheen degrees Celsius. The studied area is classified as a temperate climate based on the Emberger method and as a semi-arid climate based on the De Martonne method (Hosseini, 2019). Also, the moisture regime of semi-arid soil is dry subtype (Hosseini and Kamrani, 2017, Albaji & Hamadi, 2017). Figure 1 shows the location of Fath-Ali pressure irrigation network. In this article, the data collected from twenty stations, taken from the soil studies of the region, have been used (Hosseini, 2018). Also, according to the characteristics of the soil and the profile of land units, soil series were identified. To measure the physical parameters, intact samples were taken from different soil depths and the required parameters were determined in the laboratory.
Today, there is a need to use new evaluation strategies to evaluate irrigation methods to improve the performance of water use in agriculture. In this study, the Fuzzy Analysis Hierarchy Process (FAHP) has been studied to check the qualitative suitability of the soil in drip irrigation and compared with conventional parametric approaches. The assessment based on the parametric approach identified areas with an area of approximately 2,941 ha (57%) as "very suitable (S1)". This method assigned an area of about 247 ha (5%) of the areas to "somewhat suitable (S2)" and about 798 ha (15%) to "almost suitable (S3)". Also, "permanently unsuitable (N2)" areas were about 452 hectares (9%), and "unsuitable in current conditions (N1)" areas were estimated to be about 737 hectares (14%). According to the Fuzzy Analysis Hierarchy Process (FAHP), suitability (S1) covers an area of about 2873 hectares (56%) and parts with suitability (S2) also covers an area of about 2100 hectares (41%) and an area of about 130 hectares (3 %) were assigned to "almost fair (S3)" quality areas. The results showed that some of the southwestern and western parts of the plain are in "unsuitable current conditions (N1)", which included an area of about 72 hectares (1%). Also, according to the FAHP method, there was no "permanently unsuitable (N2)" quality in the area. As a result, there was no significant difference between the two methods in terms of "very suitable land", but in the case of areas with evaluation (S2), the difference between the two methods was large, and the FAHP method allocated more area to these areas. Therefore, it should be considered that in FAHP assessment, taking into account gradual changes in soil properties, such as nature, it can provide more accuracy than traditional parametric methods for assessing soil suitability. In this method, by using different weights of the indicators affecting the evaluation, the unusual influence of the factors on determining the final characteristics is reduced and the evaluation is closer to its real value.