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

نوع مقاله : مقالات پژوهشی

نویسندگان

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


عنوان مقاله [English]

Vulnerability assessment to Drought in Various Provinces, approach towards risk management in the country

نویسندگان [English]

  • F. Nasrnia
  • M. Zibaei
Shiraz university
چکیده [English]

Introduction: The water crisis is one of the main challenges of the current century. Drought is one of the most costly natural disasters in Iran. During the past 40 years, our country has experienced 27 droughts. It seems a necessary step to deal with the consequences of drought and reducing its effects, thorough understanding and knowledge of each region's vulnerability, which is neglected in our country, unfortunately. It is necessary to study the influencing factors in determining vulnerability and makes it visible. On the other hand, due to the continuing drought conditions intensified in recent years and its impact on different economic sectors, especially the agricultural sector in the country need to assess vulnerability to drought in the country will double.
Materials and Methods: Fuzzy AHP method based on the concept of fuzzy sets introduced by LotfeiZadeh. There are several ways to use fuzzy theory and hierarchical structure proposed merger. Cheng in 1996 suggested a new approach to solve problems using Fuzzy AHP calibration values within the membership and (TFNs). Extent Analysis Method proposed by Chang is one of the common ways to solve problems. In this study, we developed a method based on fuzzy analytic hierarchy Chang that has been developed by Zhu et al. and Van Alhag.
Results and Discussion: Vulnerability to drought conditions is determined by factors such as economic, social and physical sensitivity to the damaging effects of drought increases. This study is designed in the hierarchy. The purpose of this study is assessing the vulnerability of the country to drought. Vulnerability of this study includes economic vulnerability, social vulnerability and physical vulnerability. Economic vulnerability to drought indicates that the economy is vulnerable to external shocks due to drought and the inability of the economy to withstand the effects of the event and recover the situation. Social vulnerability determines the capacity to deal with drought in the community and reflect the effects of drought on people's ability to cope with the event. The physical vulnerability is related to the characteristics and the structure of society, infrastructure and services that are the result of the damage caused by drought. In the present study, the economic dimension of vulnerability, including GDP per capita, value added in agriculture, value added in industry and the impact of drought on the GDP. Under the criteria of social vulnerability, population density, population growth, the rate of literacy, vulnerable populations, the costs of health and safety and the impact of drought on employment were considered. The physical dimensions of vulnerability include the rate of irrigated land and road density since the objective of this study was to assess vulnerability to drought in various provinces of the country, the required data for all provinces except for Alborz province was collected in 1391 from intelligence sources. To determine the importance of different dimensions of vulnerability as well as the sub-phase in each dimension, the questionnaire was used for paired comparisons. As for the tens of experts, specialists and professionals who have expertise using the Delphi method is incorporated. In general, the importance of physical vulnerability is more than economic and social vulnerability. On the other hand, according to the results the economic and social vulnerability is important, too. The results of this study showed that the importance of the physical vulnerability was more than the economic and social vulnerability and economic vulnerability and social importance were the same. In the economic vulnerability sub-criteria of per capita GDP, in the social vulnerability sub-criteria of population density and in the physical vulnerability sub-criteria of road density have the most importance. These findings may reflect the fact that when drought occurs, access to infrastructure, services and markets can considerably reduce the harmful effects of drought. According to the results, Semnan, Tehran and Gilan provinces jointly are economically vulnerable. On the other hand, in terms of criteria for social vulnerability, provinces of Fars, Khuzestan and Gilan were the most social vulnerable and Isfahan, Kermanshah and Ilam are the least vulnerable. Also, according to the results the province of Khuzestan, Fars and Khorasan were the most; and Yazd, Bushehr and Kohgiluyeh Boyer were the least physical vulnerability.
Conclusion: In this study, in order to assess vulnerability to drought in various provinces, , after determining the hierarchy and collect relevant data, the importance of each criteria and sub-criteria were determined. In order to determine the importance of different aspects of vulnerability (the economic, social and physical) Fuzzy AHP method was used in each dimension. According to the results of this study, the province of Khuzestan, Fars and Khorasan are the most and Yazd, Bushehr and Kohgiluyeh Boyer were the least physical vulnerability. Since different provinces ‌have significant differences in vulnerability to drought and vulnerability in various aspects of economic, social and physical, in order to achieve drought management based on risk management, recommended in policy and planning make attention the effects of drought in the various provinces.

کلیدواژه‌ها [English]

  • Economic Vulnerability
  • Physical Vulnerability and Hierarchical Fuzzy )
  • Social vulnerability
  • Vulnerability to Drought
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.
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