ارزیابی ریسک خشکسالی گندم دیم (Triticum aestivum L.) با استفاده از شاخص‌های آسیب‌پذیری و مخاطره خشکسالی (مطالعه موردی: استان‌های خراسان رضوی و خراسان شمالی)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه اگروتکنولوژی، دانشکده کشاورزی دانشگاه فردوسی مشهد، مشهد، ایران

2 بانک کشاورزی خراسان رضوی، مشهد، ایران

چکیده

مناطق خشک و نیمه‌خشک همانند سایر مناطق در معرض انواع ریسک­‌ها قرار دارند، امّا ریسک‌­هایی نظیر خشکسالی با شدت بیشتری این مناطق را تهدید می‌­نماید. در این مطالعه به بررسی شاخص‌های آسیب‌پذیری و مخاطره به‌عنوان مؤلفه‌های ریسک خشکسالی در مناطق مستعد تولید گندم دیم در شمال شرق ایران (هفت شهرستانِ استان خراسان رضوی و پنج شهرستانِ استان خراسان شمالی) طی سال‌های زراعی 89-1388 لغایت 97-1396 پرداخته شده است. شاخص آسیب‌پذیری نوعی شاخص ترکیبی است که حساسیت، در معرض قرار گرفتن و ظرفیت تطابق‌پذیری سه جزء تعیین‌کننده آن می‌باشند. در این مطالعه، ظرفیت تطابق‌پذیری تحت تأثیر دو عامل ظرفیت نگهداری آب خاک و سطح مکانیزاسیون می‌باشد. نتایج این مطالعه نشان داد که در 11 شهرستان و یا به‌عبارتی در 92 درصد از شهرستان‌های مورد مطالعه، گندم دیم با ریسک کم تا متوسط تولید می‌شود. میزان ریسک خشکسالی تولید گندم دیم در شهرستان سرخس زیاد و در شش شهرستان (فاروج، کلات، درگز، قوچان، نیشابور و تربت‌حیدریه) کم می‌باشد. شهرستان‌های مذکور از نظر شاخص آسیب‌پذیری در رده کمتر آسیب‌پذیر تا آسیب‌پذیر قرار دارند، همچنین میزان ظرفیت تطابق‌پذیری در این شش شهرستان زیاد است که دلیل عمده آن ظرفیت بالای نگهداری آب خاک می‌باشد. همچنین نتایج نشان داد که بیشتر شهرستان‌هایی که شاخص مخاطره خشکسالی در آن‌ها خیلی زیاد است، در استان خراسان شمالی واقع‌شده‌اند، ولی این شاخص در شهرستان‌های فاروج، درگز و قوچان کم می‌باشد. ارزیابی ریسک در فرآیند مدیریت ریسک و اتخاذ راهکارهای هوشمندانه در این حوزه از اهمیت ویژه­ای برخوردار بوده که پرداختن به آن می‌تواند کمک مؤثری به امنیت غذایی و توسعه پایدار نماید.

کلیدواژه‌ها

موضوعات


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  1. Ahsan, M. N., & Warner, J. (2014). The socioeconomic vulnerability index: A pragmatic approach for assessing climate change led risks–A case study in the south-western coastal Bangladesh. International Journal of Disaster Risk Reduction, 8, 32-49. (in Persian with English abstract). http://doi.org/10.1016/j.ijdrr.2013.12.009
  2. Antwi-Agyei, P., Fraser, E. D., Dougill, A. J., Stringer, L. C., & Simelton, E. (2012). Mapping the vulnerability of crop production to drought in Ghana using rainfall, yield and socioeconomic data. Applied Geography, 32(2), 324-334. http://doi.org/10.1016/j.apgeog.2011.06.010
  3. Assimacopoulos, D., Kampragkou, E., Andreu, J., Bifulco, C., De Carli, A., De Stefano, L., & Musolino, D. (2014). Future drought impact and vulnerability. Case study scale. 20.
  4. Azizi Mobaser, J., Rasoulzadeh, A., Rahmati, A., Shayeghi, A., & Bakhtar, A. (2020). Evaluating the performance of Era-5 Re-analysis data in estimating daily and monthly precipitation, Case Study; Ardabil Province. Iranian Journal of Soil and Water Research, 51(11), 2937-2951 (in Persian with English abstract). https://doi.org/10.22059/ijswr.2020.302176.668600
  5. Birkmann, J. (2008). Assessing vulnerability before, during and after a natural disaster in fragile regions: Case study of the 2004 Indian Ocean tsunami in Sri Lanka and Indonesia: WIDER Research Paper. Helsinki: UNU-WIDER.
  6. Deems, H. (2010). Vulnerability of rural communities in the Mediterranean region to climate change and water scarcity: The case of Cyprus. Spain: Universitat Autònoma de Barcelona.
  7. Dabanli, I. (2018). Drought Risk Assessment by Using Drought Hazard and Vulnerability Indexes. Natural Hazards and Earth System Sciences Discussions, 2018, 1-15. https://doi.org/10.5194/nhess-2018-129.
  8. Eslami, A., Mirisoliman, S. J., & Rashidi, M. (2021). Vulnerability analysis and identification of meteorological drought risk zones (Case research: North Khorasan province). Journal of Water and Soil Conservation, 28(3), 191-205. (in Persian with English abstract). https://doi.org/10.22069/jwsc.2022.18841.3434.
  9. Gee, G., & Bauder, J. (1979). Particle size analysis by hydrometer: A simplified method for routine textural analysis and a sensitivity test of measurement parameters. Soil Science Society of America Journal, 43(5), 1004-1007. https://doi.org/10.2136/sssaj1979.03615995004300050038x.
  10. Ghaseminejad, S., Soltani, S., & Soffianian, A. (2014). Drought risk assessment in Isfahan province. JWSS-Isfahan University of Technology, 68(18), 213-226. (in Persian with English abstract). http://dorl.net/dor/20.1001.1.24763594.1393.18.68.19.4
  11. Ghorbani, M. (2017). Agricultural Insurance Principles. Mashhad: Publications of Ferdowsi university of Mashhad. (in Persian with English abstract)
  12. Gravandi, S., & Alibeygi, A. (2011). Determinants of Farmers’ Risk Management in Kermanshah Township. Iranian Journal of Agricultural Economics and Development Research, 42(2), 255-264. (in Persian with English abstract). http://dorl.net/dor/20.1001.1.20084838.1390.42.2.10.3.
  13. Guttman, N. B. (1999). Accepting the standardized precipitation index: A calculation algorithm 1. JAWRA Journal of the American Water Resources Association, 35(2), 311-322. https://doi.org/10.1111/j.1752-1688.1999.tb03592.x
  14. Habibi, Y., Azizi, J., & Shal, F. K. (2017). Role of Insurance in broiler farms risk management (A case of Rudbar County). International Journal of Agricultural Management and Development (IJAMAD), 8(3), 321-328.
  15. Hardaker, J. B., Lien, G., Anderson, J. R., & Huirne, R. B. (2004). Coping with risk in agriculture: Applied decision analysis. London, UK: Wallingford: CABI Publishing.
  16. IranMeteorologicaOrganization. (2022). Retrieved from https://www.irimo.ir/far/index.php.
  17. Kim, H., Park, J., Yoo, J., & Kim, T. W. (2015). Assessment of drought hazard, vulnerability, and risk: A case study for administrative districts in South Korea. Journal of Hydro-Environment Research, 9(1), 28-35. http://doi.org/10.1016/j.jher.2013.07.003
  18. Kirkham, M. (2011). Water dynamics in soils. In L. Jerry Hatfield and J. Thomas Sauer (Ed.), Building a Stable Base for Agriculture (pp. 53-65): American Society of Agronomy and Soil Science Society of America.
  19. Ladányi, M. (2003). Risk methods and their applications in agriculture. Applied Ecology and Environmental Research, 6(1), 147-164.
  20. Lakzian, A., AVAL, M. B., & Gorbanzadeh, N. (2010). Comparison of pattern recognition, artificial neural network and pedotransfer functions for estimation of soil water parameters. Notulae Scientia Biologicae, 2(3), 114-120. https://doi.org/10.15835/nsb234737.
  21. Liu, X., Wang, Y., Peng, J., Braimoh, A. K., & Yin, H. (2013). Assessing vulnerability to drought based on exposure, sensitivity and adaptive capacity: A case study in middle Inner Mongolia of China. Chinese Geographical Science, 23, 13-25. https://doi.org/10.1007/s11769-012-0583-4.
  22. Lobell, D. B., Schlenker, W., & Costa-Roberts, J. (2011). Climate trends and global crop production since 1980. Science, 333(6042), 616-620. https://doi.org/10.1126/science.1204531
  23. Mathbout, S., Lopez-Bustins, J. A., Martin-Vide, J., Bech, J., & Rodrigo, F. S. (2018). Spatial and temporal analysis of drought variability at several time scales in Syria during 1961–2012. Atmospheric Research, 200, 153-168. http://doi.org/10.1016/j.atmosres.2017.09.016.
  24. McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Paper presented at the Proceedings of the 8th Conference on Applied Climatology.
  25. MinistryofAgricultureofIran. (2023). Retrieved from https://www.maj.ir/.
  26. Mirisoliman, J., Ownegh, M., & Barani, H. (2020). Zoning of meteorological drought risk in customary Kormanj nomadic territories of North Khorasan. Journal of Arid Biome, 10(1), 109-125. (in Persian with English abstract).
  27. Mishra, A. K., & Singh, V. P. (2010). A review of drought concepts. Journal of Hydrology, 391(1-2), 202-216. http://doi.org/10.1016/j.jhydrol.2010.07.012.
  28. Mohammadi Ghaleni, M., & Sharafi, S. (2022). Evaluation of CRU TS4. 05 and ERA5 Datasets accuracy to precipitation, temperature and potential evapotranspiration in different climates across Iran. Iranian Journal of Irrigation & Drainage, 16(5), 879-890. (in Persian). https://dor.isc.ac/dor/20.1001.1.20087942.1401.16.5.15.0.
  29. Murthy, C., Yadav, M., Mohammed Ahamed, J., Laxman, B., Prawasi, R., Sesha Sai, M., & Hooda, R. (2015). A study on agricultural drought vulnerability at disaggregated level in a highly irrigated and intensely cropped state of India. Environmental Monitoring and Assessment, 187, 140. http://10.1007/s10661-10015-14296-x.
  30. Parvaze, S., Khan, J. N., Kumar, R., & Allaie, S. P. (2021). Flood forecasting in the sparsely gauged jhelum river basin of greater himalayas using integrated hydrological and hydraulic modelling approach. Available at Research Square. https://doi.org/10.21203/rs.3.rs-461873/v1
  31. Pereira, L. D., Rocha, J. D., Debortoli, N., Parente, I. I., Eiró, F., Bursztyn, M., & Rodrigues-Filho, S. (2014). Integrated assessment of smallholder farming’s vulnerability to drought in the Brazilian Semi-arid: A case study in Ceará. Climatic Change, 127, 93-105. https://doi.org/10.1007/s10584-014-1116-1
  32. Rejoice, T. (2003). Rainfall reliability, drought and flood vulnerability in Botswana. Water Sa, 29(4), 389-392. https://doi.org/10.4314/wsa.v29i4.5043
  33. Şen, Z. (2015). Applied drought modeling, prediction, and mitigatio: Elsevier.
  34. Shahabfar, A., Ghulam, A., & Eitzinger, J. (2012). Drought monitoring in Iran using the perpendicular drought indices. International Journal of Applied Earth Observation and Geoinformation, 18, 119-127. https://doi.org/10.1016/j.jag.2012.01.011.
  35. Sharafi, L., Zarafshani, K., Keshavarz, , Azadi, H., & Van Passel, S. (2020). Drought risk assessment: Towards drought early warning system and sustainable environment in western Iran. Ecological Indicators, 114, 106276. http://dx.doi.org/10.1016/j.ecolind.2020.106276
  36. Subash, N., Mohan, H. R., & Banukumar, K. (2011). Comparing water-vegetative indices for rice (Oryza sativa)–wheat (Triticum aestivum L.) drought assessment. Computers and Electronics in Agriculture, 77(2), 175-187. https://doi.org/10.1016/j.compag.2011.05.001.
  37. Tatari, M., Koochekian, A., & Nassiri Mahalati, M. (2009). Dryland wheat yield prediction using precipitation and edaphic data by applying of regression models. Iranian Journal of Field Crops Research, 7(2), 357-365. (in Persian with English abstract). https://dor.isc.ac/dor/20.1001.1.20081472.1388.7.2.3.3.
  38. Unger, P. W., Kirkham, M. B., & Nielsen, D. C. (2010). Water conservation for agriculture. In T. M. a. S. Zobeck, W.F. (Ed.), Soil and water conservation advances in the United States (pp. 1-45): Soil Science Society of America.
  39. Van Wart, J., Grassini, P., & Cassman, K. G. (2013). Impact of derived global weather data on simulated crop yields. Global Change Biology, 19(12), 3822-3834 .https://doi.org/10.1111/gcb.12302.
  40. Walkley, A., & Black, I. A. (1934). An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Science, 37(1), 29-38. http://doi.org/10.1097/00010694-193401000-00003.
  41. Wilhelmi, O. V., & Wilhite, D. A. (2002). Assessing Vulnerability to Agricultural Drought: A Nebraska Case Study. Natural Hazards, 25(1), 37-58. https://doi.org/10.1023/A:1013388814894
  42. Wilhite, D. A. (2000). Drought as a Natural Hazard: Concepts And Definitions New York: Routledge Publishers.
  43. Willmott, C. J., Ackleson, S. G., Davis, R. E., Feddema, J. J., Klink, K. M., Legates, D. R., O'donnell, J., Rowe, C. M. (1985). Statistics for the evaluation and comparison of models. Journal of Geophysical Research: Oceans, 90(C5), 8995-9005. https://doi.org/10.1029/JC090iC05p08995
  44. WorldBank. (2015). World development indicators. Retrieved from http://data.worldbank.org/data-catalog/world-development-indicators.
  45. WorldBank. (2016). Agricultural sector risk assessment: methodological guidance for practitioners. Agriculture global practice discussion paper. World Bank, Washington, DC, 10.
  46. Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., & Turskis, Z. (2018). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(9), 2501-2519.
  47. Yuan, X.-C., Wang, Q., Wang, K., Wang, B., Jin, J.-L., & Wei, Y.-M. (2013). China’s regional vulnerability to drought and its mitigation strategies under climate change: data envelopment analysis and analytic hierarchy process integrated approach. Mitigation and Adaptation Strategies for Global Change, 20, 341-359. https://doi.org/10.1007/s11027-013-9494-7
  48. Zhao, J., Zhang, Q., Zhu, X., Shen, Z., & Yu, H. (2020). Drought risk assessment in China: evaluation framework and influencing factors. Geography and Sustainability, 1(3), 220-228. https://doi.org/10.1016/j.geosus.2020.06.005
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