پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 127 |
| تعداد شمارهها | 7,238 |
| تعداد مقالات | 77,638 |
| تعداد مشاهده مقاله | 161,181,861 |
| تعداد دریافت فایل اصل مقاله | 120,828,209 |
ارزیابی ریسک عوامل اقلیمی محدودکننده در مراحل مختلف فنولوژی محصول کلزا در استان گلستان تحت شرایط اقلیم فعلی و تغییر اقلیم آینده | ||
| تحقیقات آب و خاک ایران | ||
| دوره 57، شماره 5، مرداد 1405، صفحه 1229-1247 اصل مقاله (1.46 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/ijswr.2026.414532.670142 | ||
| نویسندگان | ||
| سیده فاطمه عرب1؛ جواد بذرافشان* 2 | ||
| 1گروه مهندسی آبیاری و آبادانی، دانشکده مهندسی و فناوری کشاورزی، دانشگاه تهران | ||
| 2گروه مهندسی آبیاری و آبادانی، دانشکدگان کشاورزی و منابع طبیعی دانشگاه تهران، کرج، ایران. | ||
| چکیده | ||
| این مطالعه با هدف ارزیابی تأثیر تغییر اقلیم آینده بر ریسک وقوع عوامل محدودکننده اقلیمی در طی دوره رشد کلزا در استان گلستان انجام شده است. دادههای هواشناسی موردنیاز این مطالعه شامل بارش، دمای حداقل و دمای حداکثر روزانه از 10 ایستگاه هواشناسی استان گلستان دریافت گردید. نیاز حرارتی مراحل چهارگانه فنولوژی کلزا (سبزشدن، رویشی، زایشی و رسیدن دانه) از تحقیقات قبلی استخراج گردید. پس از بررسیهای اولیه دادههای هواشناسی و تکمیل نواقص آماری با استفاده روشهای آماری، با استفاده از مدل LARS-WG اقدام به ریزمقیاسنمایی خروجی دو مدل اقلیم جهانی تحت سناریوی میانی SSP2-4.5 برای آینده نزدیک (2023-2053) گردید. در مرحله بعد، به کمک مدل درجه-روز رشد، مراحل چهارگانه فنولوژی محصول کلزا (سبزشدن، رویشی، زایشی و رسیدن دانه) در دوره پایه (1992-2022) و دوره آینده تحت شرایط تغییر اقلیم تعیین گردید. سپس، هشت نمایه اقلیم کشاورزی تعریف گردید و مقادیر این نمایهها در طی دوره پایه و آینده برای هر یک از مراحل فنولوژی محاسبه گردید. نتایج نشان داد که در سرجمع ایستگاهها، بارش در 9 ماه و دمای حداقل و حداکثر تقریباً در تمام ماههای سال نسبت به دوره پایه افزایش مییابد. در شرایط تغییر اقلیم، طول دوره سبزشدن و رویشی کلزا کاهش و طول دوره زایشی و رسیدن افزایش مییابد که بهترتیب، متناظر با تغییرات افزایشی (کاهشی) و کاهشی (افزایشی) دمای هوا (بارش) در این دورههاست. افزایش احتمال وقوع یخبندان در مرحله زایشی، کاهش احتمال تأمین نیاز سرمایی در مرحله رویشی، افزایش احتمال بیبارشی و همچنین، افزایش احتمال بارشهای سنگین در همه مراحل فنولوژی کلزا از دیگر نتایج این مطالعه است. این یافتهها بر لزوم تدوین راهبردهای کشاورزی تطبیقی برای کاهش اثرات نامطلوب تغییر اقلیم و تضمین امنیت غذایی در منطقه مطالعاتی تأکید میکند. | ||
| کلیدواژهها | ||
| تغییر اقلیم؛ ریسک؛ فنولوژی؛ کلزا؛ استان گلستان | ||
| عنوان مقاله [English] | ||
| Risk Assessment of Climatic Constraints During Different Phenological Stages of Canola in Golestan Province Under Current and Future Climate Change | ||
| نویسندگان [English] | ||
| Seyyedeh Fatemeh Arab1؛ Javad Bazrafshan2 | ||
| 1Department of Irrigation & Reclamation Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran | ||
| 2Department of Irrigation and Reclamation Engineering, College of Agricultural and Natural Resources, University of Tehran, Karaj, Iran. | ||
| چکیده [English] | ||
| This research investigates the projected impacts of future climate change on the vulnerability to climate-related constraints during the canola cultivation cycle within Golestan Province, Iran. Daily meteorological observations, encompassing precipitation, minimum temperature, and maximum temperature, were procured from ten synoptic weather stations operating in the region. The thermal thresholds for the four principal phenological phases of canola—specifically germination, vegetative growth, reproductive development, and seed maturation—were rigorously established based on prior investigations. Following meticulous data quality assessment and the statistical imputation of any identified gaps, outputs from two representative global climate models, simulated under the intermediate Shared Socioeconomic Pathway (SSP2 4.5) scenario, were downscaled for the near term future (2023–2053) utilizing the LARS WG statistical downscaling model. Subsequently, the phenological progression of canola through its four developmental stages was delineated for both the historical baseline period (1992–2022) and the projected future climate, employing a growing degree day (GDD) model. A suite of eight key agroclimatic indices was then formulated, and their temporal variations were quantified across both the baseline and future scenarios for each phenological phase. Our findings reveal a discernible trend towards increased annual precipitation in nine months and statistically significant warming across nearly all months for both minimum and maximum temperatures when compared to the baseline. Under the projected climate change scenario, a notable shortening of the canola emergence and vegetative phases is anticipated, while the reproductive and maturation periods are expected to lengthen. These temporal shifts are intrinsically linked to the projected directional changes in temperature (warming) and precipitation (drying trends) during these respective developmental periods. Furthermore, the analysis highlights an augmented risk of frost damage during the critical reproductive stage, a diminished likelihood of satisfying the necessary vernalization (chilling) requirements in the vegetative phase, alongside an elevated probability of both extreme drought conditions and intense precipitation events throughout the entire canola phenological cycle. These findings underscore the critical need for adaptive agricultural strategies to mitigate the adverse impacts of projected climate change and ensure food security in the study area. | ||
| کلیدواژهها [English] | ||
| Climate change, Risk, Phenology, Canola, Golestan province | ||
| مراجع | ||
|
Ababaei, B., Mirzaei, F., & Sohrabi, T. (2011). Assessment of LARS-WG Performance in 12 Coastal Stations of Iran. Iranian Water Research Journal, 5(2), 217-222. (In Persian) Abdi, S., Abedi, R., Kazemirad, L., & Abedi, T. (2022). Investigation of climatic factors affecting Canola production using TOPSIS multicriteria decision making approach in Ahar region. Journal of Agricultural Meteorology, 10(1), 55-69. (In Persian) Abdulsahib, S.M., Zubaidi, S.L., Almamalachy, Y., Dulaimi, A. (2024). Temperature and precipitation change assessment in the North of Iraq using LARS-WG and CMIP6 models. Water (Switzerland), 16(19), 1-25. Abshenas, M., Kamkar, B., Soltani, A., & Kazemi, H. (2023). Predicting the Effect of Climate Change on the Suitability of Canola (Brassica napus L.) Cultivation Land using SDSM and Lars-WG Models in Mazandaran Province. Journal Of Agroecology, 15(4), 843-862. (In Persian) Akbari, M., Ownegh, M., Asgari, H., Sadoddin, A., & Khosravi, H. (2016). Drought Monitoring Based on the SPI and RDI Indices under Climate Change Scenarios (Case Study: Semi-Arid Areas of West Golestan Province). ECOPERSIA 4, 1585-1602. C.C.C. (2017). ERA5: Fifth Generation of ECMWF Atmospheric Reanalyses of the Global Climate. Copernic. Clim. Change Serv. Clim. Data Store (CDS). 15, 2020. Chen, H., Guo, J., Zhang, Z., Xu, C.Y. (2013). Prediction of temperature and precipitation in Sudan and South Sudan by using LARS-WG in future. Theoretical and Applied Climatology, 113(3–4), 363–375. Dehghan, Z., Fathian, F., & Eslamian, S. (2015). Comparative Assessment of SDSM, IDW and LARS-WG Models for Simulation and Downscaling of Temperature and Precipitation. Water and Soil, 29(5), 1376-1390. (In Persian) Dehghani, N., Goodarzi, M., & Karimi, M. (2025). Performance Analysis of LARS-WG and SDSM Models in Downscaling the Output of CMIP6 Models in The Urmia Lake Watershed. Environment and Interdisciplinary Development, 10, 98-111. Disasa, K.N., Yan, H., Zhang, J., Wang, G., Zhang, C., Zhang, D., Wang, B., & Hao, B. (2026). Comprehensive review of drought characteristics and intensification under climate change: implications for agriculture and water resources. Journal of Hydrology, 664, 134571. Dolatparast, B., Hosseinpanahi, F., Mansouri, H., & Siosemardeh, A. (2023). Effect of climate change on growth and seed yield of canola (Brassica napus L.) in Dehgolan plain of Kurdistan province in Iran using the DSSAT program. Iranian Journal of Crop Sciences, 25(2), 101-118. (In Persian) Faraji, A. (2015). Evaluation the effect of temperature and photoperiod on growth and development periods of two canola cultivars. Journal of Crops Improvement, 17(4), 1049-1062. (In Persian) Fenta Mekonnen, D., & Disse, M. (2018). Analyzing the future climate change of Upper Blue Nile River basin using statistical downscaling techniques. Hydrology and Earth System Sciences. 22, 2391-2408. FAO (2024). FAOSTAT: Crops and livestock products [Internet]. Rome: FAO. [Available from: https://www.fao.org/faostat/en/#data/QCL] GhorbaniMinaei, L., Mosaedi, A., Zakerinia, M., Kalbali, E. & Ghabaei Soogh, M. (2024). Study of future climate change on the temperature and precipitation trends in Qarasu basin based on the CMIP6 models. Iranian Journal of Soil and Water Research, 55(2), 245-268. (In Persian) Hatfield, J.L., Sivakumar, M.V.K., & Prueger, J.H. (2019). Agroclimatology: Linking Agriculture to Climate. Agronomy Monograph 60. USA. Heidarybeni, M. , Yazdanpanh, H. and Mehnatkesh, A. (2018). Impacts of Climate Change on Canola Yields and Phenology (Case Study: Chahrmahal Va Bakhtiari, Iran). Physical Geography Research, 50(2), 373-389. (In Persian) IPCC (2022). WGI Interactive Atlas: Regional information. Intergovernmental panel on climate change. https://interactive-atlas.ipcc.ch/. Accessed 10/03/2024. Khan, S.F., Naeem, U.A. (2023). Future climate projections using the LARS-WG6 downscaling model over Upper Indus Basin, Pakistan. Environmental Monitoring Assessment, 195(7). Kutcher, H.R., Warland, J.S., & Brandt, S.A. (2010). Temperature and precipitation effects on canola yields in Saskatchewan, Canada. Agricultural and Forest Meteorology, 150, 161-165. Lotfi, M., Kamali, G.A., Meshkatee, A.H., & Varshavian, V. (2022). Performance analysis of LARS-WG and SDSM downscaling models in simulating temperature and precipitation changes in the West of Iran. Modeling Earth System Environment, 8(4), 4649–4659 Majnoon Hosseini, N. (2024). Agriculture, production and processing of industrial and fodder plants. Tehran University Press. (In Persian) Markie, E., Khoddami, A., Liu, S. Y., Chen, S., & Tan, D. K. Y. (2025). The Impact of Heat Stress on Canola (Brassica napus L.) Yield, Oil, and Fatty Acid Profile. Agronomy, 15(7), 1511. Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R. & Roeckner, E. (2019). Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1. 2) and its response to increasing CO2. Journal of Advances in Modeling Earth Systems, 11(4), 998-1038. Mehan, S., Guo, T., Gitau, M.W., & Flanagan, D.C. (2017). Comparative study of different stochastic weather generators for long-term climate data simulation. Climate, 5(2), 26. Ministry of Agricultural Jihad. (2025). Agricultural Statistics: Crops for the Crop Year 1402-1403. Deputy for Statistics, Information and Communication Technology Center. Tehran, Iran. (In Persian) Mohammed, Z.M., & Hassan, W.H. (2022). Climate change and the projection of future temperature and precipitation in southern Iraq using a LARS-WG model. Modeling Earth System Environment, 8(3), 4205–4218. Omidvar, K., Mazidi, A. & Doostmoradi, S. (2014). Climatic feasibility of rapeseed cultivation in Kermanshah province. Geography and Development, 12(35), 97-116. (In Persian) Pullens, J.W.M., Sharif, B., Trnka, M., Balek, J., Semenov, M.A., & Olesen, J.E. (2019). Risk factors for European winter oilseed rape production under climate change. Agricultural and Forest Meteorology, 272-273, 30-39. Punyawansiri, S., & Kwanyuen, B. (2020). Forecasting the future temperature using a downscaling method by LARS-WG stochastic weather generator at the local site of Phitsanulok province, Thailand. Atmospheric and Climate Sciences, 10(4), 538-552. Qian, B., Jing, Q., Bélanger, G., Shang, J., Huffman, T., Liu, J. & Hoogenboom, G. (2018), Simulated canola yield responses to climate change and adaptation in Canada. Agronomy Journal, 110, 133-146. Radmanesh, Y., Tabrizi, M.S., Etedali, H.R., Azizian, A., & Babazadeh, H. (2023). Comparative evaluation of the accuracy of re-analysed and gauge-based climatic data in Iran. Journal of Earth System Science, 132, 190. Rahban, S., Torabi, B., Soltani, A., & Zeinali, E. (2021). Using SSM-iCrop model to predict phenology, yield, and water productivity of canola (Brassica napus L.) in Iran condition. Journal of Agroecology, 13(1), 157-177. (In Persian) Rathke, G.W., & Diepenbrock, W. (2006). Energy balance of winter oilseed rape (Brassica napus L.) cropping as related to nitrogen supply and preceding crop. European Journal of Agronomy, 24, 35-44. Salahi, B., Goudarzi, M., & Hosseini, S.A. (2016). Predicting the temperature and precipitation changes during the 2050s in Urmia Lake Basin. Watershed Engineering and Management, 8(4), 425-438. (In Persian) Secchi, M.A., Fernandez, J A., Stamm, M. J., Durrett, T., Prasad, P.V.V., Messina, C.D., & Ciampitti, I.A. (2023). Effects of heat and drought on canola (Brassica napus L.) yield, oil, and protein: A meta-analysis. Field Crops Research, 293, 108848. Sekhavati-Far, S., Rahemi Karizaki, A., Nakhzari Moghaddam, A., & Mollashahi, M. (2020). Identification of rapeseed limiting factors using performance comparison analysis. Journal of Crops Improvement, 22(1), 13-25. (In Persian) Semenov, M., Brooks, R., Barrow, E., Richardson, C. (1998). Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates. Climate Research, 10, 95–107 Semenov, M.A., Barrow, E.M. (2002). LARS-WG a stochastic weather generator for use in climate impact studies. User Manual, Hertfordshire Semenov, M.A., Senapati, N., Coleman, K., & Collins, A.L. (2024). A dataset of CMIP6-based climate scenarios for climate change impact assessment in Great Britain. Data Brief, 55,110709. Semenov, M.A., Stratonovitch, P. (2010). Use of multi-model ensembles from global climate models for assessment of climate change impacts. Climate Research, 41, 1–14. Semenov, M.A., Stratonovitch, P. (2015). Adapting wheat ideotypes for climate change: accounting for uncertainties in CMIP5 climate projections. Climate Research, 65, 123–139. Shen, Z., Ding, M., Huang, R., Wu, H., & Yong, B. (2026). Modeling and characterizing errors in satellite and reanalysis precipitation estimates using a two-step decomposition procedure. Journal of Hydrology, 669, 135009. Shirani-Rad, A.H., Ahmadi, M. (1995). The effect of planting date and plant density on agronomic traits of two winter rapeseed cultivars. Seed and Plant, 11(2), 9-20. (In Persian) Silakhori, E., Dahmardeh Ghaleno, M.R., Meshram, S.G. et al. (2022). To assess the impacts of climate change on runoff in Golestan Province, Iran. Natural Hazards 112, 281–300. Torabi, B., Habibpour-Kashefi, E., Soltani, A., & Zeinali, E. (2024). Assessment of Adaptation Strategies for Canola to Future Climate in Iran. Journal of Plant Production Research. (Articles in Press) (In Persian) Wang, Y., Fan, J., & Shao, M.A. (2007). Adaptability of climate generator of LARS-WG on the Loess Plateau. Science of Soil Water Conservation, 5(3), 24–27. Weymann, W., Böttcher, U., Sieling, K., & Kage, H. (2015). Effects of weather conditions during different growth phases on yield formation of winter oilseed rape. Field Crops Research, 173, 41-48. Xu, Y. (2023). hyfo: Hydrology and Climate Forecasting R Package for Data Analysis and Visualization. Retrieved from https://yuanchao-xu.github.io/hyfo/ Zhang, Z., Lu, J., Cong, R., Ren, T., & Li, X. (2017). Evaluating agroclimatic constraints and yield gaps for winter oilseed rape (Brassica napus L.) – A case study. Scientific Reports, 7, 7852. Ziehn, T., Chamberlain, M. A., Law, R. M., Lenton, A., Bodman, R. W., Dix, M., & Srbinovsky, J. (2020). The Australian earth system model: ACCESS-ESM1. 5. Journal of Southern Hemisphere Earth Systems Science, 70(1), 193-214. | ||
|
آمار تعداد مشاهده مقاله: 42 تعداد دریافت فایل اصل مقاله: 31 |
||
سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب