Spatial modeling of rainfed wheat yield using agroclimaticmicrozonation in Kurdistan
Wheat is the main focus of the economy of Kurdistan province in which the annual fluctuation of wheat yield is 4/11 times as affected by the climatic elements of the site. This study investigated the role of agro-climatic variables and indices on rainfed wheat yield in Kurdistan province. The data o...
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Kharazmi University
2018-03-01
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| Series: | تحقیقات کاربردی علوم جغرافیایی |
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| Online Access: | http://jgs.khu.ac.ir/article-1-2776-en.pdf |
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| author | Naseh Qaderi Bohloul Alijani zahra hejazizadeh mohammad saligheh |
| author_facet | Naseh Qaderi Bohloul Alijani zahra hejazizadeh mohammad saligheh |
| author_sort | Naseh Qaderi |
| collection | DOAJ |
| description | Wheat is the main focus of the economy of Kurdistan province in which the annual fluctuation of wheat yield is 4/11 times as affected by the climatic elements of the site. This study investigated the role of agro-climatic variables and indices on rainfed wheat yield in Kurdistan province. The data of planting area, amount of production, damages and yield of wheat of 31-year in 10 regions of Kurdistan along with the hourly, daily, decade, monthly, seasonal and yearly levels data of 22 synoptic stations were collected. The correlation between wheat yield and 128 independent variables was calculated. The effect of variables on yield evaluated by multivariate regression. The spatial analysis of variables was performed and the spatial model of wheat yield was introduced for province and regions. The results showed that climatic elements in various regions are different, in a 99% confidence. Most of the independent variables alone have a significant effect on wheat yield, but in the stepwise model, 7 variables such as: the number of rainy days of the year, the sum of the degree hours (of temperature less than -11 ° C) in germination and tilling stage, annual precipitation and the precipitation of November are determinants of the yield. Yield and effective independent variables have significant spatial differences even in a cluster climate type. The highest and lowest coefficient of variation of wheat yield is related to Bijar and Kamyaran areas, respectively. Kamyaran and Sanandaj regions have the highest and lowest yield, respectively. Bijar is the highest risk region of the province for wheat production.
The results of this study showed that with a 99 percent confidence, climatic elements (variables) vary in different regions. Most of the independent variables have a significant effect on wheat yield in simple linear regression, but in Stepwise method, due to the internal correlation between variables, just variables entered that have insignificant correlation with each other and have more effects than other variables. The variables affecting the performance are differentin various regions, and from the point of view of effectiveness, the arrangement of the variables in different areas vary too. In other words, even in two regions with a climatic type (based on the Modified De Martonne method), both agro-climatic indices and wheat yield are significantly different. The impact of effective variables on yield at any time and place depends on the time of year and the phonological stage of wheat. At one time the environmental conditions of different regions in terms of temperature, humidity and precipitation differ, based on phonological stages of the regions. The time of the vulnerability of wheat varies from place to place. Wheat vulnerability at flowering stage is more than other stages. The effect of independent variables on yield at different times of year is proportional to the phonological stage in years Different and different in different regions. In Kurdistan province, the number of rainy days of the year, total degree hours the temperature reaches below -11 °C (sum of hours with below -11 °C temperature) from germination to tillering stage, the annual precipitation, the rainfall in the fifth decade of the water year (the precipitation of 11-20 of November), annual relative humidity and total degree hours the temperature reaches above 30°Ctemperature (sum of hours with above 30 °C temperature) in milky and dough stage is the determinants of the production of rainfed wheat. In Baneh and Marivan areas, the coefficient of variation (CV) is lower and in Bijar and Divandareh regions CV is more than other regions. Kamyaran region has the highest yield, Baneh and Marivan were ranked secondjointly. Sanandaj and then Bijarhave the lowest yield. Each region has a model for wheat yield and determinant factors vary from region to region. Although the annual production of Bijar is higher than other areas, wheat production in the Bijar region has a higher risk than other areas. |
| format | Article |
| id | doaj-art-cb150cd5618349f0b969c419ce0cb47b |
| institution | Kabale University |
| issn | 2228-7736 2588-5138 |
| language | fas |
| publishDate | 2018-03-01 |
| publisher | Kharazmi University |
| record_format | Article |
| series | تحقیقات کاربردی علوم جغرافیایی |
| spelling | doaj-art-cb150cd5618349f0b969c419ce0cb47b2025-01-31T17:24:18ZfasKharazmi Universityتحقیقات کاربردی علوم جغرافیایی2228-77362588-51382018-03-011848119Spatial modeling of rainfed wheat yield using agroclimaticmicrozonation in KurdistanNaseh Qaderi0Bohloul Alijani1zahra hejazizadeh2mohammad saligheh3 PhD student at climatology, Kharazmi University, Tehran Full Professor of Climatology, Kharazmi University, Tehran Full Professor of Climatology, Kharazmi University, Tehran. Associate professor of Climatology, Kharazmi University, Tehran Wheat is the main focus of the economy of Kurdistan province in which the annual fluctuation of wheat yield is 4/11 times as affected by the climatic elements of the site. This study investigated the role of agro-climatic variables and indices on rainfed wheat yield in Kurdistan province. The data of planting area, amount of production, damages and yield of wheat of 31-year in 10 regions of Kurdistan along with the hourly, daily, decade, monthly, seasonal and yearly levels data of 22 synoptic stations were collected. The correlation between wheat yield and 128 independent variables was calculated. The effect of variables on yield evaluated by multivariate regression. The spatial analysis of variables was performed and the spatial model of wheat yield was introduced for province and regions. The results showed that climatic elements in various regions are different, in a 99% confidence. Most of the independent variables alone have a significant effect on wheat yield, but in the stepwise model, 7 variables such as: the number of rainy days of the year, the sum of the degree hours (of temperature less than -11 ° C) in germination and tilling stage, annual precipitation and the precipitation of November are determinants of the yield. Yield and effective independent variables have significant spatial differences even in a cluster climate type. The highest and lowest coefficient of variation of wheat yield is related to Bijar and Kamyaran areas, respectively. Kamyaran and Sanandaj regions have the highest and lowest yield, respectively. Bijar is the highest risk region of the province for wheat production. The results of this study showed that with a 99 percent confidence, climatic elements (variables) vary in different regions. Most of the independent variables have a significant effect on wheat yield in simple linear regression, but in Stepwise method, due to the internal correlation between variables, just variables entered that have insignificant correlation with each other and have more effects than other variables. The variables affecting the performance are differentin various regions, and from the point of view of effectiveness, the arrangement of the variables in different areas vary too. In other words, even in two regions with a climatic type (based on the Modified De Martonne method), both agro-climatic indices and wheat yield are significantly different. The impact of effective variables on yield at any time and place depends on the time of year and the phonological stage of wheat. At one time the environmental conditions of different regions in terms of temperature, humidity and precipitation differ, based on phonological stages of the regions. The time of the vulnerability of wheat varies from place to place. Wheat vulnerability at flowering stage is more than other stages. The effect of independent variables on yield at different times of year is proportional to the phonological stage in years Different and different in different regions. In Kurdistan province, the number of rainy days of the year, total degree hours the temperature reaches below -11 °C (sum of hours with below -11 °C temperature) from germination to tillering stage, the annual precipitation, the rainfall in the fifth decade of the water year (the precipitation of 11-20 of November), annual relative humidity and total degree hours the temperature reaches above 30°Ctemperature (sum of hours with above 30 °C temperature) in milky and dough stage is the determinants of the production of rainfed wheat. In Baneh and Marivan areas, the coefficient of variation (CV) is lower and in Bijar and Divandareh regions CV is more than other regions. Kamyaran region has the highest yield, Baneh and Marivan were ranked secondjointly. Sanandaj and then Bijarhave the lowest yield. Each region has a model for wheat yield and determinant factors vary from region to region. Although the annual production of Bijar is higher than other areas, wheat production in the Bijar region has a higher risk than other areas.http://jgs.khu.ac.ir/article-1-2776-en.pdfagroclimateclimate elementmicrozonationyieldwheat |
| spellingShingle | Naseh Qaderi Bohloul Alijani zahra hejazizadeh mohammad saligheh Spatial modeling of rainfed wheat yield using agroclimaticmicrozonation in Kurdistan تحقیقات کاربردی علوم جغرافیایی agroclimate climate element microzonation yield wheat |
| title | Spatial modeling of rainfed wheat yield using agroclimaticmicrozonation in Kurdistan |
| title_full | Spatial modeling of rainfed wheat yield using agroclimaticmicrozonation in Kurdistan |
| title_fullStr | Spatial modeling of rainfed wheat yield using agroclimaticmicrozonation in Kurdistan |
| title_full_unstemmed | Spatial modeling of rainfed wheat yield using agroclimaticmicrozonation in Kurdistan |
| title_short | Spatial modeling of rainfed wheat yield using agroclimaticmicrozonation in Kurdistan |
| title_sort | spatial modeling of rainfed wheat yield using agroclimaticmicrozonation in kurdistan |
| topic | agroclimate climate element microzonation yield wheat |
| url | http://jgs.khu.ac.ir/article-1-2776-en.pdf |
| work_keys_str_mv | AT nasehqaderi spatialmodelingofrainfedwheatyieldusingagroclimaticmicrozonationinkurdistan AT bohloulalijani spatialmodelingofrainfedwheatyieldusingagroclimaticmicrozonationinkurdistan AT zahrahejazizadeh spatialmodelingofrainfedwheatyieldusingagroclimaticmicrozonationinkurdistan AT mohammadsaligheh spatialmodelingofrainfedwheatyieldusingagroclimaticmicrozonationinkurdistan |