چكيده لاتين :
Severe drought events can endanger part of the community, it is important to develop a comprehensive and spatial framework for mapping drought-prone areas and reducing risk systems (Beyaztas et al., 2018). Drought is related to hydrology and meteorology. Various environmental parameters and activities related to agriculture, vegetation, human life, wildlife, and local and national economies are affected, and the effects are often intensified by agricultural, livestock, industrial and other human activities. There are various studies conducted in the field of drought, which can be found in Aher et al., 2017; Azevedo Reis et al., 2020; and Sivakumar et al., 2020. Studies have used only climatic parameters to study droughts in these studies. Other parameters such as vegetation, soil, and topography are also affected by drought. Thus, the purpose of this study is to analyze drought using these factors in the south and east of Fars province using fuzzy methods and hierarchical analysis models. Using the Geomorphon mapping method, the topography and landforms within the study area are determined. After that, the relationship between the amount of drought and the type of landform is determined. Using a relationship between landform and the amount of drought, it is possible to determine which Delandforms will be vulnerable to drought. So, the objective of this study is to determine the degree of drought in the eastern and southern parts of Fars province and to determine the type of landforms within this region by using the geomorphon method. One of the innovations of this study is how it predicted a relationship between the type of landform and the amount of drought.
Materials and methods
The study area is between longitudes 52 degrees and 66 minutes and 54 degrees and 18 minutes and latitudes 28 degrees and 1 minute and 30 degrees and 18 minutes. The study area covers an area of 23139.98 square kilometers. The maximum and minimum heights of the study area are respectively 3235 and 765 meters.
For this study, the landforms in the region were mapped using a geomorphon method. The fuzzy method and hierarchical analysis model were also used to determine the drought status of the study area. The incremental membership functionwere used to prepare a fuzzy map for each of the parameters. The incremental membership function was used to prepare the fuzzy map for the parameters Altitude, slope, groundwater depth, land use, precipitation days, precipitation, soil texture. So values greater than the critical limit n get one and values less than m get 0, and between m and n they get x-m / n-m. For the aridity index, erosion, PET, soil salinity, and distance to river parameters, the reduction membership function was used. The values above the critical limit n were 0 and below the critical limit m were 1. The values between m and n were n-x / n-m.
Then each layer was weighed using the AHP method. Weighting was done using the AHP method because each characteristic has a different effect on drought. The AHP method makes it easy to weigh parameters. AHP relies on pairwise comparisons of each parameter. Each of the factors is in the range of 1 to 9 that (Saaty & Vargas, 2001).
Results and discussion
The results of this study showed that most areas are at risk of erosion, and most of the land use in the study area is for pasture. There is more rainfall in the western part of the study area and the drought index is higher in the eastern part. Elevations are highest in the northern half of the region while evaporation is highest in the southern parts. In the southern part, groundwater depth is highest, and rainiest days are in the western part. The soil texture in most areas is loamy clay. Using pairwise comparisons of each parameter, the results revealed rainfall and groundwater depth with weights of 0.28 and 0.01 are the most and least important parameters in determining drought-prone areas in the study area, respectively. Based on the results of fuzzy and AHP methods, areas to the east and southeast are prone to drought.
Conclusion
Drought forecasting is important because the annual drought causes a lot of damage in arid and semi-arid regions of Iran and leads to reduced yields of agricultural products as well as reduced drinking water and irrigation. Thus, when identifying the vulnerable areas, including the Eastern parts (eastern regions), the necessary measures must be considered, including the cultivation of low water plants, management of dams, etc.
Keywords: Drought, Landform, Fuzzy, Hierarchical Analytical Model, Geomorphon Method, East and South of Fars Province
