سنجش ابعاد آسیب‌پذیری استان‌ها نسبت به خشکسالی، راهکاری به سوی مدیریت ریسک در سطح کشور

مجله اقتصاد و توسعه کشاورزی

مقاله 3، دوره 29، شماره 4، دی 1394، صفحه 359-373   

نوع مقاله: مقالات پژوهشی

شناسه دیجیتال (DOI): 10.22067/jead2.v29i4.47932

نویسندگان

فاطمه نصرنیا^* ؛ منصور زیبایی

دانشگاه شیراز

چکیده

خشکسالی یکی از پر هزینه‌ترین بلایای طبیعی در ایران می‌‌باشد. به نظر می‌رسد گام ضروری برای مقابله با خشکسالی و تعدیل تبعات آن، شناخت و درک دقیق ابعاد آسیب‌پذیری هر منطقه است که متأسفانه در کشور ما مورد غفلت واقع شده است. این امر ضرورت مطالعه در زمینه تعیین آسیب‌پذیری و شناسایی عوامل اثرگذار بر آندر مناطق مختلف کشور را مشهود می‌سازد. در مطالعه حاضر، به منظور ارزیابی آسیب‌پذیری نسبت به خشکسالی در استان های مختلف کشور، از روش سلسله مراتبی فازی (Fuzzy AHP ) استفاده شد. آسیب‌پذیری شامل ابعاد آسیب‌پذیری اقتصادی، آسیب‌پذیری اجتماعی و آسیب‌پذیری فیزیکی می‌باشد. نتایج این مطالعه نشان داد اهمیت آسیب‌پذیری فیزیکی بیش از آسیب‌پذیری اقتصادی و اجتماعی و اهمیت آسیب‌پذیری اقتصادی و اجتماعی یکسان است. در معیار آسیب‌پذیری اقتصادی زیر معیار GDP سرانه، در معیار آسیب‌پذیری اجتماعی زیر معیار تراکم جمعیت و در معیار آسیب‌پذیری فیزیکی زیر معیار تراکم جاده بیشترین اهمیت را به خود اختصاص داده اند.طبق نتایج این مطالعه استان های سمنان، کرمان، یزد، سیستان و بلوچستان و هرمزگان به ترتیب آسیب پذیرترین استان‌ها نسبت به خشکسالی به شمار می‌آیند. با توجه به این واقعیت که استان‌های مختلف چه در زمینه آسیب‌پذیری نسبت به خشکسالی و چه در زمینه ابعاد مختلف آسیب‌پذیری اقتصادی، اجتماعی و فیزیکی تفاوت قابل ملاحظه ای دارند، در راستای نیل به مدیریت خشکسالی بر مبنای مدیریت ریسک، پیشنهاد می‌گردد در تدوین برنامه‌ها و سیاست‌ها به اثرات متفاوت خشکسالی در استان‌های مختلف توجه کافی شود.

کلیدواژه‌ها

آسیب‌پذیری اجتماعی؛ آسیب‌پذیری اقتصادی؛ آسیب‌پذیری فیزیکی و روش سلسله مراتبی فازی

مراجع

1- Adger W. N. 2006. Vulnerability. Global Environmental Change. 16(3):268–281.

2- Allen RG, Pereira LS, Raes D et al. 1998. Crop evapotranspiration: Guidelines for computing crop water requirement. Rome: FAO Irrigation and Drainage Paper. 56.

3- Allen K. 2003. Vulnerability reduction and the community-based approach, in Pelling (ed)., Natural Disasters and Development in a Globalising World, 170-184.

4- Anderson W. A. 2005. Bringing children into focus on the social science disaster research agenda. International Journal of Mass Emergencies and Disasters 23(3): 159-175.

5- Arab D., And Mhdykhany H. 2005. The transition from crisis management towards risk management, drought management strategies. Proceedings of the First International Conference on crisis management in disasters. 9-10February, Tehran. (in Persian)

6- Ashok K.R., Sasikala C. 2012. Farmers’ vulnerability to rainfall variability and technology adoption in rain-fed tank irrigated agriculture, agricultural economics Research Review. 25(2) : 267-278.

7- BadriM. A.2001. A combined AHP-GP model for quality control systems.InternationalJournalof Production Economics, 72:27-40.

8- BirkmannJ. 2006. Measuring vulnerability to natural hazards: towards disaster resilient societies. New York: United Nations Publications.

9- Boender C.,Graan J.,andLootsma F.A. 1989.Multicriteria decision analysis withfuzzy pairwise comparisons. Fuzzy Sets Systems.29:133–43.

10- Bordi I., Fraedrich K., and Petitta M.2006. Large-scale assessment of drought variability based on NCEP/NCAR and ERA- 40 re-analyses. Water Resources Management, 20(6): 899–915.

11- Bozdag C. E., Kahraman, C., andRuan D. 2003. Fuzzy group decision making for selection among Computer, Integrated Manufacturing Systems,Computer in Industry 51:13-29.

12- BrooksN., W. N. Adger and KellyP. M.2005. The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation. Global Environmental Change, 15(2): 151-163.

13- BuckleyJ.1985. Fuzzy hierarchical analysis. fuzzy Sets Syst. 17: 233–247.

14- Buyukozkan G., Kahraman C., andRuan D. 2004. A fuzzy multi-criteria decision approachforsoftwaredevelopment strategy selection. International Journal of GeneralSystems, 33:259–80.

15- Chan F., Jiang B., and Tang N. 2000. The development of intelligent decision supporttools to aid the design of flexible manufacturing systems. International Journalof Production Economics, 65:73–84.

16- Chang D.Y. 1996. Applications of the extent analysis method on fuzzy AHP. EuropeanJournalofOperational Research, 95:649–55.

17- ChenS. J., and HwangC. L. 1992. Fuzzy multiple attribute decision making. SpringerVerlage Berlin Heidelberg.

18- Cheng C., Yang K., and Hwang C.L. 1999. Evaluating attack helicopters by AHP basedon linguistic variable weight. European Journal of Operational Research, 116:423–35.

19- Cheng C. 1996. Evaluating naval tactical missile systems by fuzzy AHP based onthegradevalue of membership function. European Journal of OperationalResearch, 96:343–50.

20- Cheng. J. 2011. A study on agricultural drought hazard vulnerability and risk management: a case of Xiaogan city in Hubel province. PHD Dissertation. HuaZhong agricultural university. Wuhan, China.

21- Csutora R., and Buckley, J.J., 2001. Fuzzy hierarchical analysis: TheLambda–Maxmethod. Fuzzy Sets Syst. 120:181–195.

22- Deressa T. 2010. Assessing of vulnerability in Ethiopian agriculture to the climate change and adaption strategies, PhD thesis, environmental economics, university of Pretoria.

23- Downing T.E., andBakker K.2000. Drought discourse and vulnerability. In: Wilhite DA (ed) Drought: a global assessment, natural hazards and disasters series. Routledge Publishers, UK, p 2000.

24- Easter C. 1999. Developing small countries: A commonwealth vulnerability index. AwayTable, 351 (1) :403-422.

25- Felixchan T. S., and Niraj K. 2007. Global supplier development considering risk factors using fuzzy extended AHP-based approach. Omega, 35:417-431.

26- Füssel H. 2007. Vulnerability: A generally applicable conceptual framework for climate change research. Global Environmental Change, 17(2): 155-167.

27- Han P., Wang P. X., Zhang S.Y., and Zhu D.H. 2010. Drought forecasting based on the remote sensing data using ARIMA models. Mathematical and Computer Modeling, 51: 1398-1403.

28- He B.,Wu J.,LuA.,Cui X., Zhou L., LiuM.,andZhao L.2013. Quantitative assessment and spatial characteristic analysis of agricultural drought risk in China. Nat Hazards, 66:155–166.

29- Heinz Center.2002. Human links to coastal to coastal disasters. Washington, DC, H. John Heinz III Center for Science, Economics, and the Environment.

30- Hewitt K.1997. regions of risk: A geographical introduction to disasters. England: Addison Wesley Longman Harlow, 365–382.

31- Hufschmidt G. 2011. A comparative analysis of several vulnerabilityconcepts. Natural hazards, 58(2): 621-643.

32- IPCC .2007. Climate Change (2007): Impacts, adaptation and vulnerability. Report of the Working Group II. Cambridge University Press, UK, 973.

33- Islamic Parliament of Iran Research Center.2011. Review of recent droughts the country with an emphasis on consequences and efficient management requirements. Research Infrastructure (Department of Water and Environment). Islamic Parliament of Iran Research Center.

34- Islamic Parliament of Iran Research Center.2013. http://rc.majlis.ir (visited February 2013).

35- Kaly U., L. Briguglio, H. McLeod, S. Schmall, C. Pratt, and R. Pal. 1999. Environmental vulnerability index (EVI) tosummarise national environmental vulnerability profiles. SOPAC Tech. Rep. 275. Suva, Fiji: South Pacific Applied Geoscience Commission.

36- Kaly U. and Pratt C. 2000. Environmental vulnerability index: Development and provisionalIndices and profiles for Fiji, Samoa, Tuvalu and Vanuatu. Reported Phase II NZODA .SOPAC Technical Report 306, Suva, Fiji.

37- Kar N. 2009. Psychological impact of disasters on children: review of assessment and interventions. World Journal of Pediatrics 5(1): 5-11.

38- Keshavarz M., Karami E., and Vanclay F. 2013. The social experience of drought in ruralIran. Land Use Policy, 30: 120–129.

39- Kheiz Z. 2013. The effects of drought on the Iran economy: computable ceneral equilibrium analysis. Master Thesis in Agricultural Economics, Shiraz University. (in Persian with English abstract)

40- Khoshnodifar. Z., Sookhtanlo, M.and GholamiH. 2012. Identification and measurement of indicators of drought vulnerability among wheat farmers in Mashhad County, Iran. Scholars Research Library. Annals of Biological Research, 3 (9):4593-4600 (available: http://scholarsresearchlibrary.com/archive.html).

41- Lee M., Pham H., and Zhang X. 1999. Amethodology for priority settingwith application tosoftware development process. European Journal of Operational Research, 118:375–89.

42- Leichenko R.M. and O-Brien K.L.2001. Dynamics of rural vulnerability to globalTo change. South Africa, Mitigation and Adaptation Strategies for GlobalChange, 7 (1):1-18.

43- Leung L.C., and Cao D. 2000.On consistency and ranking of alternatives in fuzzy AHP.European Journal of Operational Research, 124:102–13.

44- LotfeiZadeh A. 1965.Fuzzy sets, Information and Control, 8:338–353.

45- Me-Bar Y., and Valdez J. 2005. On the vulnerability of the ancient Maya society to naturalthreats. Journal of Archaeological Science, 32: 813–825.

46- Moreid S., and Moghadasei M. 2005. Moving from crisis management to drought risk management in the US and our business horizons. Proceedings of the First International Conference on Water Crisis in disaster management. 10-9 February, Tehran. (in Persian)

47- Moss R., Brenkert A., and Malone E. 2001. Vulnerability to climate change: aMulti-criteria decision analysis. Global environmental change, 18 (1):112-127.

48- Ngo E. B. 2001. When disasters and age collide: Reviewing vulnerability of the elderly. Natural Hazards Review, 2(2): 80-89.

49- PhillipsB. D., and P. L. Hewett. 2005. Home alone: Disasters, mass emergencies and children in self care. J. Emergency Management, 3(2): 31-35.

50- Saaty T. 1980. The analytic hierarchy process. 1st Ed. New York: McGraw-Hill.

51- Saaty T. 1994. Fundamentals of decision making and priority theory with the analytic hierarchy process, RWS Publications, Pittsburgh. 2nd edition.

52- Shahid S., andBehrawan H. 2007. Drought risk assessment in the west part of Bangladesh. Nat Hazards, 46:391–413

53- Sivakumar M., and Wilhite, D.A. 2002. Drought preparedness and drought management. Drought Mitigation and Prevention of Land Desertification, University of Ljubljana, Slovenia, 21-25 April.

54- Smit B., and Wandel J. 2006. Adaptation, adaptive capacity andvulnerability. Global environmental change, 16(3):282-292.

55- Song L.C., Deng Z .Y., and Dong A .X. 2003. Drought. China Meteorological Press, Beijing. 22.

56- Stam A., Sun M., and Haines M. 1996.Artificial neural network representations forhierarchical preference structures. Computers & Operations Research, 23:1191–201.

57- Statistical Center of Iran, Provincial Information. Available at http://www.amar.org.ir.

58- Statistical Yearbook of Agricultural. 2012. Ministry of mgriculture, Planning and economic department, center for information and communication technology. Available at http://www.maj.ir

59- Statistical yearbook of population.2012. Population and migration office of statistics and information, Available at, National Organization for Civil Registration. Available at http: //WWW.sabteahval.ir

60- Statistical Yearbook of Road Maintenance and Road Transport. 2012. Planning, Office of the Information and Communication Technology. Available at http://www.rmto.ir

61- Sun.Z., Zhang J., Zhang Q., Hu Y. Yan D., andWangC. 2014. Integrated risk zoning of drought and waterlogging disasters based on fuzzy comprehensive evaluation in Anhui Province, China. Natural Hazards, 71:1639–1657.

62- UNISDR: United Nations International Strategy for Disaster Reduction, United Nations, United Nations, Geneva, 2000.

63- Vargas L. G. 1990. An overview of the analytic hierarchy process and it application. European Journal of Operational Research, 48: 2-8.

64- Vincent K. 2004. Creating an index of social vulnerability to climate change for Africa.Technical Report 56, Center Tyndall Climate Change Research, University of EastAnglia, Norwich.

65- Walter J.2004. World disasters report 2004: focus on community resilience. Kumarian, Bloomfield.

66- Wang T.C., and Chen Y.H. 2007. Applying consistent fuzzy preference relations to partnership selection. International Journal of Management Science, 35:384-388.

67- Wang Y.M.andElhag T.2006. On the normalization of interval and fuzzy weights.Fuzzy Sets and Systems, 157:2456–71.

68- Wilhite D.A.2000. Drought as a natural hazard: concepts and definitions, chapter 1. In: Wilhite DA (ed) Drought: a global assessment, natural hazards and disasters series. Routledge Publishers, UK.

69- Wu J., He B., Lu¨ A., Zhou L., Liu M., and Zhao L.2011. Quantitative assessment and spatial characteristics analysis of agricultural drought vulnerability in China. Nat Hazards, 56:785–801.

70- Xiao-Chen Y., Yu-Liang Z.,Ju-Liang J., and Yi-Ming W.2013. Risk analysis for drought hazard in China: a case study in Huaibei Plain. Nat Hazards, 67:879–900.

71- Zhang F., Wang D., Qiu B .1987. China’s agricultural phrenology atlas. Science Press, Beijing.

72- Zhu K.J., Jing Y., and Chang D.Y. 1989. A discussion on extent analysis method andapplicationsoffuzzy AHP. European Journal of Operational Research, 116:450–6.