Potential Climatic Zoning of Wheat (Triticum aestivum L.) Golestan Province

Document Type : Scientific - Research

Authors

• Afrough Sadat Baniaghil ¹
• ali Rahemi karizki ¹
• Abbas Biabani ¹
• hassan faramarzi ²

¹ Gonbad Kavous University

² Tarbiat Modaress

10.22067/jag.v9i3.52027

Abstract

Introduction
Crop selection based on land capabilities has been used in several studies to assess the suitability of land for specific crops in order to determine the optimal cropping system. Maize, rice, wheat, barley, cotton, soybean and canola are the major crops found in the agricultural production systems of Golestan province, Iran. Soybean (Glycine max L.; Fabaceae) is grown world-wide as an important staple and commercial crop. Kamkar et al., (2014) on assessment review of land suitability for cultivation of rapeseed and soybean in four basins over Golestan province, using GIS reported that only 11.82% of the total lands very suitable to rotate soybean after canola, used raster layers for them study were included climatic (precipitation, temperature), topographic (aspects and slope) and soil-related (texture, pH, EC). The Geographical Information System (GIS) offers a flexible and powerful tool as it can combine large volumes of different kinds of data into new datasets and display these new datasets in the form of informative and accessible thematic maps. The aim of this study was to perform land suitability assessments for wheat cultivation Golestan province, and to investigate the possibility of wheat cultivation. In this way, we used GIS and a comprehensive data set on wheat crop ecological requirements, agro climatological, topographic and soil data.
Material and Methods
Geographical Location of the Region
The province of Golestan with an area of 21,500 square kilometers, is in the southeast of the Caspian Sea. This area extends from 36_440 N to 38_50 N and from 51_530 E to 56_140 E. In general, Golestan has a moderate and humid climate known as "the moderate Caspian climate. arid and semiarid areas has occupied more than 35% of Golestan province. The study area of the research, include agricultural lands and rangelands of Golestan province is present. Using 1: 50,000 maps of the national cartographic center of Iran, we created a 20 m digital elevation model (DEM) with a topo-to-raster function.
Method of study
In this study, the first agro-ecological requirements and of wheat were determined based on scientific resources. Studied climatic variables were included average, minimum and maximum temperatures, precipitation in the date planting and during growth season of crop. Data of the last 10 years were collected and recorded from 25 stations located within the study area. The standardization of data was used from fuzzy method and Analytic Hierarchy Process (AHP) was used for weighting the criteria. Finally, using weighted linear combination (WLC) in the software IDRISI, wheat cultivation potential map was prepared.
Results and Discussion
The results showed that the weighted criteria of AHP, the amount of precipitation during the growing season had the highest amount with 0.3407 and minimum temperature in the emergence stage with 0.0306 had the lowest coefficient in the rankings. The digital environmental layers overlaid and integration in GIS media then zoning of lands carried out in 4 classes (high suitable, suitable, less suitable and unsuitable). The results showed that 9.54% and 54.53% of this area were high suitable and suitable for wheat cropping, respectively.
Conclusion
In the output map from weighted linear combination, the located lands in East, Southeastern, South and Southwest had the lowest potential production for wheat. These areas were consisted of steep slopes, highest elevation, less precipitation and less favorable area in terms of areas which had unfavorable climate areas and other areas that located in the Northeastern, center and Northwest of the province had the best potential for wheat production which can be said cause of sufficient amount precipitation, low slope and elevation, favorable soil and temperature.

Keywords

• Environmental variables
• Fuzzy method
• Geographic Information System
• and Weighted linear combination

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