| تعداد نشریات | 286 |
| تعداد نشریات سازمان | 84 |
| تعداد شماره‌ها | 3,028 |
| تعداد مقالات | 33,882 |
| تعداد مشاهده مقاله | 45,253,412 |
| تعداد دریافت فایل اصل مقاله | 60,282,082 |
بررسی اثر سناریوهای تغییر اقلیم بر مکان یابی کشت پاییزه‌ی چغندرقند (مطالعه موردی:استان خراسان جنوبی) | ||
| چغندرقند | ||
| مقاله 3، دوره 34، شماره 1، مرداد 1397، صفحه 17-29 اصل مقاله (1.75 M) | ||
| نوع مقاله: کامل علمی - پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/jsb.2018.108367.1132 | ||
| نویسندگان | ||
| فاطمه پورصالحی* 1؛ علی شهیدی2؛ عباس خاشعی سیوکی2 | ||
| 1دانشجوی دکتری مهندسی منابع آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند، ایران. | ||
| 2دانشیار گروه مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند، ایران. | ||
| چکیده | ||
| با توجه به اثر پدیدهی تغییر اقلیم بر پارامترهای اقلیمی مانند دما و بارندگی و اثر متقابل این تغییرات بر پارامترهای فیزیولوژی گیاهی به ویژه درجه روزهای رشد (GDD) و شاخص قابلیت تولید زیست توده (CBPI)، با بررسی این شاخصها میتوان، مکان مناسب کشت محصولات را تعیین نمود. این مطالعه با هدف بررسی اثر سناریوهای تغییر اقلیم B1 و A2، بر تعیین مکان مناسب کشت چغندرقند پاییزه در استان خراسان جنوبی با استفاده از پیشبینی پارامترهای اقلیمی وبا به کارگیری نرم‌افزار LARS-WG تحت مدل گردش عمومی HADCM3 و روش وزندهی ANP براساس پارامترهای اقلیمی، فیزیولوژی گیاهی، هیدروژئولوژی و توپوگرافی،در محیط نرم‌افزار ARC GIS 9.3 در دورهی کشت آن در سال 1396-1397 میلادی انجام گردید. نتایج نشان داد که به طور کلی در هر دو سناریو اکثر مناطق استان جزء مکان‌های نامناسب جهت کشت پاییزه چغندرقند محسوب می‌گردند به‌گونهای که 72/81 درصد از مساحت کل استان در سناریوی A2 و 71/13 درصد در سناریوی B1 مناسب کشت نمیباشند و تنها 24/41، 2/69 و 0/08 درصد سطح استان در سناریوی A2و همچنین 36/25، 45/3 و 05/0 درصد در سناریوی B1 به ترتیب جزء مناطق متوسط، مناسب و بسیار مناسب از لحاظ کشت برآورد گردید. همچنین بررسی روند نتایج به دست آمده از نقشهی نهایی نشان داد که سناریوی A2 و B1 در آیندهی نزدیک (2030-2011)، به طور تقریبی از دقت یکسانی بر مکان یابی کشت پاییزه چغندرقند در استان خراسان جنوبی برخوردار می‌باشند. | ||
| کلیدواژه‌ها | ||
| پارامترهای اقلیمی؛ درجه روزهای رشد (GDD)؛ شاخص قابلیت تولید زیست توده (CBPI)؛ نرم‌افزار LARS-WG؛ مدل HADCM3 | ||
| عنوان مقاله [English] | ||
| Study of the climate change scenarios effect on locating of autumn-sown sugar beet (case study: south Khorasan rovince) | ||
| نویسندگان [English] | ||
| F. Poursalehi1؛ A. Shahidi2؛ A. Khasheisiuki2 | ||
| 1PhD Student Department of Water Engineering. University of Birjand, Birjand, Iran. | ||
| 2Associate Professor, Department of Water Engineering University of Birjand, Birjand, Iran. | ||
| چکیده [English] | ||
| Considering the effect of climate change on climatic parameters such as temperature and rainfall as well as interaction of these parameters on plant physiology characteristics especially growing degree days (GDD) and capability of biomass production index (CBPI), the suitable location for crop cultivation can be determined by examining these indices. This study was performed to evaluate the effects of climate change scenarios B1 and A2 on determination of the appropriate location for autumn-sown sugar beet in South Khorasan province via the climatic parameters prediction using LARS-WG software under general circulation model HadCM3 and AHP weighting method based on climate parameters, plant physiology, hydrogeology, and topography, in ARC GIS 9.3 software during cultivation period of 2016-2017. Results showed that in general in both scenarios the majority of areas of the province are inappropriate for autumn-sown sugar beet cultivation so that based on the A2 and B1 scenarios, 72.81and 71.13% of the total area of the province are not suitable for cultivation, respectively and only 24.41, 2.69 and 0.08% of the province area based on the A2 scenario and also 25.36, 3.45 and 0.05% based on B1 the scenario were determined as medium, suitable, and very suitable in terms of cultivation. Also results of the final map showed that A2 and B1 scenarios in the near future (2011-2030), approximately have the same accuracy for locating the suitable area for sugar beet cultivation. | ||
| کلیدواژه‌ها [English] | ||
| Climate change, Growing Degree Days (GDD), capability of biomass production index (CBPI), LARS-WG software, HADCM3 model | ||
| مراجع | ||
|
Abbasi F, Malbusi SH, Babaeian A, Asmari M, Borhani R. Climate Change Prediction of South Khorasan Province During 2010-2039 by Using Statistical Downscaling of ECHO-G Data. Journal of Water and Soil. 2010; 24(2): 218-233. (in Persian, abstract in English)
Abbasi F, Babaeian E, Habibinokhandan M, Golimokhtari L, Malbusi Sh, Askari ShA. Evaluation of the impact of climate change on precipitation and temperature in the decades ahead, with the help of the MAGICC- SCENGEN model. Natural Geography Research. 2010; (72): 91-109. (in Persian)
Ahmadi M, Fathollah Taleghani D, Mahzuni SJ, Shahbazi H. Exploring the possibility of autumn sowing of sugar beet in south of the Khorasan Razavi province. Improvement Institutes and preparation of sugar beet seed, 2011; Organization of research, education and promoting of agriculture, the number of approved projects: 4-43-02-86-026. (in Persian)
Ashrafmansouri GhR, Sharifi M, Hamdi F. Study of autumn sowing of sugar beet (Beta vulgaris L.) in Fasa area. Journal of Sugar beet. 2013; 71-84.
Babaeian e, Najafinik Z. Introduction and evaluation of LARS-WG for modeling meteorological parameters Khorasan province, statistical period (1961-2003). Two-Quarterly Scientific-extension Niwar, 2006; (62-63): 49-65. (in Persian)
Daneshfaraz R, Razzaghpour H. Evaluation of Climate Change Impacts on Potential Evapotranspiration in the West Azerbaijan Province. Geographical Space. 2014; 14:199-211. (in Persian)
Dehghanipour AH, Tajrishi M, Araghinezhad SH. Quantifying the impact of climate change on rain-fed wheat cultivation in the catchment area of Urmia. 5 th national Conference on Water Resources Management; Shahid Beheshti University, Tehran, Iran; 2014. (in Persian)
De pauw E. An Agro-ecological exploration of the Arabian Peninsula. ICARDA. 2002; Aleppo, Syria, 77 pp. ISBN, 92-9127-119-5.
De Pauw E, Göbel W, Adam H. Agro-meteorological aspects of agriculture and forestry in the arid zones. Agricultural and Forest Meteorology, 2000; 103:43–58.
Faraji sabokbar HA, Nasiri H, Hamzeh M, Talebi S, Rafiei Y. Identification of suitable areas for artificial groundwater recharge using integrated ANP and pair wise comparison methods in GIS environment, (case study: Garbaygan Plain of Fasa). Geography and Environmental Planning. 2012; 44 (4): 143-166. (in Persian)
Gordon C, Cooper C, Seinor CA, Banks H, Gregory JM, Johns TG, Mitchell JFB, Wood RA. The simulation of SST, Seas ice extents and ocean heat transports in a version of the Hadley Center coupled model without flux adjustment. Climate Dynamics. 2000; 16(2):147-168.
Harvey LDD, Gregory J, Hoffert M, Jain A, Lal M, Leemans R, Raper SBC, Wigley TML, de Wolde J. An introduction to Simple Climate models used in the IPCC Second Assessment Report: IPCC Technical Paper 2 (eds J.T. Houghton, L.G. Meira Filho, D.J. Griggs and M. Noguer), Intergovernmental Panel on Climate Change, 1997; Geneva, Switzerland, pp. 50.
Houghton JT, Meira Filho LG, Callander BA, Harris N, Kattenberg A, Maskell K,eds, Climate Change 1995: The Science of Climate Change, Cambridge University Press, New York, 1996; pp. 572.
Hosseinzadeh M. Geomorphological abilities in Birjand urban development. 2005; Tehran University, Faculty of Geography. Natural Geography Department. (in Persian)
Hundal SS, Singh R, Dhaliva LK. Agro-climatic indices for predicting phonology of wheat (Triticum aestivum L.) in Punjab. Journal of Agricultural Sciences. 1997; 67: 265-268.
IPCC-DDC , 1988; http://ipcc-ddc.cru.uea.ac.uk/
IPCC-TAGCIA. Guidelines on the use of scenario data for climate impact and adaptation assessment. 1999. eds. Carter TR, Hulme M, Lal M, Version 1, 69pp. Intergovernmental Panel on Climate Change, Task Group on Scenarios for Climate Impact Assessment. Harvey LDD, Gregory J, Hoffert M, Jain A, Lal M, Leemans R, Raper SBC, Wigley TML, de Wolde J. An introduction to Simple Climate models used in the IPCC Second Assessment Report: IPCC Technical Paper 2 (eds J.T. Houghton, L.G. Meira Filho, D.J. Griggs and M. Noguer), Intergovernmental Panel on Climate Change, 1997; Geneva, Switzerland, pp. 50.
Javaheri MA, Ramrudi M, Asgharipour MR, Dehmardeh M, Ghaemi AR. Agroclimatic zonation for evaluating autumn sugar beet sowing feasibility in Khorasan Razavi and Khorasan-e-Jonobi Provinces. Journal of Sugar beet. 2015; 31(1): 17-31.
Javani Kh, Anabestani AA. Comparison analysis multi-Criteria Decision methods AHP and ANP in locating of rural green spaces Case Study: Chenar Village of Kalat city. Journal of Spatial Planning. 2015; 19(4):1-31.
Meshkati AM, Kordjazi M, Babaeian A. Review and evaluate LARS model In the simulation of meteorological data Golestan province during 1993-2007 gregorian. Journal of Applied Research of Geographic Sciences. 2011; 16(19): 81-96.
Nasirimahallati M, Kuchaki A. Effects of climate change on agro climatic indices in rainfed wheat production areas of Iran. Journal of Iranian agricultural research. 2005; 3(2): 291-303. (in Persian)
Nasirimahallati M, Kuchaki A, Kamali GH, Marashi H. effect of climate change in agroclimatic indices of iran. Journal of Agricultural Science and Technology. 2006; 20(7): 71-82. (in Persian)
Saaty TL. Decision making the analytic hierarchy and network processes (AHP/ANP). Systems Science and Systems Engineering, 2004; 13(1): 1-34.
Saeedabadi R, Najafi MS, Abkharabat SH. Land suitability evaluation in the context of climate change (case study: rapeseed cultivation in West Azarbaijan province). Physical geography research quarterly. 2015; 47(4): 563-582. (in Persian)
Samadi borujeni H, Ebrahimi AA. Drought consequences and ways to deal with it (in Chahar mahal and Bakhtiari). Water Resources Research Center (University of Shahre kord). 2010; The first edition, the second season (meteorological drought and its evaluation indicators), pp 65. (in Persian)
Semenov MA. Simulation of extreme weather events by a stochastic weather generator. Climate Research, 2008; 35, 203-212.
Semenov MA, Brooks RJ. Comparison of the WGEN and LARSWG stochastic weather generators for diverse climates. Climate Research, 1998; 10: 95-107.
Semenov MA, Barrow EM. LARS-WG A Stochastic Weather Generator for Use in Climate Impact Studies. User Manual, 2002; Version 3.0: 28.
Solaimaninanadegani M, Parsinezhad M, Araghinezhad SH, Massahbavani AR. Occurrence of climate change and its effect on sowing date, length of growing cycle and evapotranspiration of winter wheat (case study: Behshahr). Journal of Water and Soil. 2012; 6(10): 11-20. (in Persian) | ||
|
آمار تعداد مشاهده مقاله: 667 تعداد دریافت فایل اصل مقاله: 467 |
||