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Title

The occurrence probability estimation of climatic factors affected on rainfed autumn wheat and barley in agricultural lands of Aq-Qala, Kalale and Gonbad Kavous by spatial analysis of GIS

Pages

  1-16

Abstract

 The occurrence probability estimation of climatic factors in drylands of Aq-Qala, Kalale and Gonbad Kavous townships by spatial analysis of GIS in order to development of autumn cereals cropping Abstract Background and adjectives: The climate potential of agricultural lands for crop production is mainly influenced by the amount and distribution of rainfall and crop water requirement. Evaluation of environmental variables and predict climate phenomena can be help to determine suitable areas for rainfed agriculture. In dryland farming, there is a significant correlation between grain yield and soil moisture, that the soil moisture content can be affected on all phenological processes in crop especially grain filling and it leads a reduce in economic yield. In order to estimate the occurrence probability of climatic factors in agricultural lands of Aq-Qala, Kalale and Gonbad Kavous townships, were used the statistical distribution analysis of Smada software program and spatial analysis of Geographic Information System (GIS). Materials and methods: This research was carry out in the agricultural lands of Aq-Qala, Kalale and Gonbad Kavous townships in Golestan province, during 2015. Studied environmental variables were as annual, autumn, spring and May precipitations, optimum temperature of germination, suitable temperature in heading stage and suitable temperature in grain filling stage. In this research, the Occurrence possibility of these climate variables were predicted in the return period of 25 years and at 95% probability level, using Distrib 2. 0 of Smada software. Then map the spatial distribution of each of the climatic variables in the 95% probability level was prepared using various methods of geostatistical and interpolation methods and classified in GIS media. The performance criteria for evaluation were Mean Absolute Error (MAE), Mean Bias Error (MBE), Root Mean Square Error (RMSE) and Cross Validation method. Results: The results of occurrences probability of climatic variables such as annual, spring and May precipitations, and temperatures showed that these variables are suitable for rainfed cultivation of wheat and barley in these townships. But, the autumn precipitation can be a limiting factor for some studied areas, in the return period of 25 years and at the 95% probability level. Conclusion: Despite supplying water requirements of wheat and barley in autumn season in the extensive areas of studied region, there is limitation in the north and northeast lands of Gonbad Kavous township. This zone covers about 7. 40 % of the total area with 68. 76-80 mm rainfall that it is classified to semi-suitable zone. The results of this research can be used in agricultural planning and future management of dryland farming in Golestan province. Keywords: Occurrence possibility, Geostatistical methods, rainfed wheat and barley, Smada.

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    APA: Copy

    Farhadian Azizi, Shiva, KAZEMI, HOSSEIN, & SOLTANI, AFSHIN. (2019). The occurrence probability estimation of climatic factors affected on rainfed autumn wheat and barley in agricultural lands of Aq-Qala, Kalale and Gonbad Kavous by spatial analysis of GIS. ELECTRONIC JOURNAL OF CROP PRODUCTION, 12(2 ), 1-16. SID. https://sid.ir/paper/361385/en

    Vancouver: Copy

    Farhadian Azizi Shiva, KAZEMI HOSSEIN, SOLTANI AFSHIN. The occurrence probability estimation of climatic factors affected on rainfed autumn wheat and barley in agricultural lands of Aq-Qala, Kalale and Gonbad Kavous by spatial analysis of GIS. ELECTRONIC JOURNAL OF CROP PRODUCTION[Internet]. 2019;12(2 ):1-16. Available from: https://sid.ir/paper/361385/en

    IEEE: Copy

    Shiva Farhadian Azizi, HOSSEIN KAZEMI, and AFSHIN SOLTANI, “The occurrence probability estimation of climatic factors affected on rainfed autumn wheat and barley in agricultural lands of Aq-Qala, Kalale and Gonbad Kavous by spatial analysis of GIS,” ELECTRONIC JOURNAL OF CROP PRODUCTION, vol. 12, no. 2 , pp. 1–16, 2019, [Online]. Available: https://sid.ir/paper/361385/en

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