پژوهش های اقلیم شناسی

پژوهش های اقلیم شناسی

آسیب پذیری و تاب آوری اقلیمی مناطق شیرآباد و دانشگاه با تاکید بر ریزگردها و خشکسالی

نوع مقاله : مقاله پژوهشی

نویسندگان
1 دانشجوی دکترا، دانشگاه زنجان،ایران.
2 دکترای تخصصی، دانشیار، عضو هیات علمی دانشگاه، دانشگاه زنجان،ایران.
3 دکترای تخصصی، استادیار، عضو هیات علمی دانشگاه، دانشگاه سیستان و بلوچستان،ایران
10.22034/jcr.2025.489436.1673
چکیده
ایران، به دلیل قرارگیری در کمربند خشکسالی، به‌شدت در معرض خسارات ناشی از این پدیده قرار دارد. این آسیب‌ها در ابعاد اقتصادی، محیطی و اجتماعی به شیوه ‌های مختلف بروز می‌کنند. ارزیابی تاب‌آوری جمعیت و مناطق درگیر، اقدامی کلیدی برای پیشگیری از وقوع بحران در نواحی پرخطر محسوب می‌شود. این پژوهش با هدف ارزیابی تاب‌آوری اقلیمی شهر زاهدان انجام شده است و در این راستا از پرسش‌نامه، نرم افزار SPSS و و روش‌های آماری، به‌ ویژه روش تصمیم‌گیری چند شاخصه تاپسیس، بهره گرفته شده است این پژوهش با روش توصیفی-تحلیلی انجام شده و جامعه‌ی آماری آن شامل مدیران محلی، اعضای شوراهای شهر و کارشناسان شهرداری است. حجم نمونه با استفاده از فرمول کوکران 384 نفر تعیین شده و نمونه‌گیری به‌صورت تصادفی ساده انجام شده است. نتایج حاصل از سنجش میزان تاب آوری شهر زاهدان با تاکید بر مخاطرات ناشی از ریزگردها و خشکسالی نشان داد ، نوسان شاخص خشکسالی SPI طی ۱۰ سال اخیر دچار نوسانات شدیدی بوده است، به نحوی که از سال ۲۰۱۶ تا ۲۰۲۲ این منطقه با خشکسالی‌های متناوب و مداوم مواجه بوده است. این شرایط منجر به کاهش قابل ‌توجه رطوبت خاک، تضعیف پوشش گیاهی و در نتیجه افزایش شدت و تراکم ریزگردها شده است. تکنیکTOPSIS (تاپسیس) نشان داد که محله دانشگاه از نظر تاب‌آوری اجتماعی و کالبدی در رتبه نخست و محله شیرآباد در رتبه دوم قرار دارد. محله دانشگاه به دلیل زیرساخت‌های بهتر و رضایت اجتماعی بالاتر، وضعیت مطلوب‌تری دارد، در حالی که محله شیرآباد به دلیل مشکلات اقتصادی و کمبود زیرساخت‌ها، آسیب‌پذیری بیشتری نشان می‌دهد. در نهایت، تحلیل تفاوت‌های تاب‌آوری اجتماعی و کالبدی بین دو محله نشان می‌دهد که محله دانشگاه از زیرساخت‌های بهتری برخوردار بوده و میزان رضایت اجتماعی در آن بالاتر است. این رضایت می‌تواند ناشی از دسترسی مطلوب‌تر به خدمات عمومی، امکانات تفریحی و اجتماعی، و کیفیت زندگی بالاتر باشد.
کلیدواژه‌ها

عنوان مقاله English

Climatic vulnerability and resilience of Shirabad and University areas with emphasis on micro-pollens and drought

نویسندگان English

fatemeh yadegarifar 1
Hossein mirmosavi 2
Mohammad Reza Poodineh 3
1 univercity zangan
2 Faculty of Geographical Sciences, Zanjan University,
3 , Faculty of Geographical Sciences, University of Sistan and Baluchistan
چکیده English

Introduction

Climate change and environmental hazards have intensified droughts and dust storms in many arid and semi-arid regions, severely affecting water resources, agricultural productivity, and public health. Sistan and Baluchestan province, particularly the city of Zahedan, faces substantial climate-related challenges, exacerbated by poor infrastructure and socio-economic inequalities. Among the most pressing issues in this region are persistent drought conditions, which reduce water availability, degrade land quality, and disrupt livelihoods, as well as dust storms, which increase health risks and infrastructural damage. Given these challenges, assessing resilience and vulnerability at the neighborhood level is crucial for effective urban planning and disaster risk management. This study evaluates the climate resilience of two neighborhoods in Zahedan-Shirabad and Daneshgah-by examining economic, social, environmental, and infrastructural dimensions. The goal is to identify disparities in resilience levels between these two areas and to propose practical strategies for enhancing sustainability, reducing vulnerability, and improving adaptive capacity in the face of climate hazards.

Materials and Methods

This study adopts a mixed-method approach, combining meteorological analysis with a survey-based assessment of neighborhood resilience. To analyze drought conditions, the Standardized Precipitation Index (SPI) was calculated using precipitation data from Zahedan’s synoptic weather station, covering the period from 1994 to 2022. The SPI, widely used for drought assessment, classifies periods of dryness and wetness based on deviations from long-term precipitation averages, helping to quantify climate variability and drought severity over different time scales. In addition to meteorological analysis, a structured questionnaire was used to evaluate economic, social, environmental, and infrastructural resilience in the two neighborhoods. The questionnaire was designed based on prior studies and expert opinions, employing a Likert scale to measure respondents’ perceptions of different resilience factors. The sample size was determined using Cochran’s formula, resulting in 384 respondents, evenly distributed across the two neighborhoods. To analyze and rank the resilience levels of the neighborhoods, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was applied. TOPSIS, a widely used multi-criteria decision-making (MCDM) method, ranks alternatives based on their relative proximity to an ideal solution. This technique ensures a systematic comparison of neighborhood resilience based on multiple dimensions. The reliability of the questionnaire was confirmed using Cronbach’s alpha coefficient, which demonstrated a high level of internal consistency. Statistical analysis, including a one-sample T-test, was conducted to compare the resilience levels of Shirabad and Daneshgah, testing whether the observed differences were statistically significant. This test provided a rigorous assessment of whether neighborhood resilience varied systematically based on socio-economic and infrastructural conditions.

Results and Discussion

Findings indicate a significant disparity in resilience between Daneshgah and Shirabad neighborhoods. Daneshgah, characterized by better infrastructure, stable employment, and higher education levels, demonstrated higher resilience across all four dimensions. In contrast, Shirabad faced greater vulnerability, with residents experiencing economic hardship, inadequate infrastructure, and lower awareness of climate-related risks. Economic conditions in Shirabad, where most residents rely on informal employment, create higher economic vulnerability, as income loss during crises significantly impacts their livelihoods. Conversely, Daneshgah residents, benefiting from stable jobs and access to financial resources, demonstrated greater adaptive capacity. Social factors such as education levels and community awareness were notably lower in Shirabad, reducing their ability to prepare for and respond to climate-related disasters. Daneshgah, with a more educated population, showed higher social resilience, as residents were more informed about climate adaptation measures. Environmental factors, including inadequate infrastructure, poor water management, and lack of green spaces, further exacerbated vulnerability in Shirabad, while Daneshgah had better environmental planning and resource management, contributing to greater climate resilience. Weak urban planning in Shirabad resulted in housing instability, water supply issues, and inefficient public services, increasing exposure to climate risks, whereas Daneshgah's robust infrastructure, including proper water distribution networks and effective waste management, enhanced its resilience. Statistical analysis using a one-sample T-test confirmed that resilience indicators were significantly higher in Daneshgah than in Shirabad (p < 0.05), validating the vulnerability classification. The TOPSIS ranking further emphasized Shirabad’s position as the more vulnerable neighborhood, requiring urgent policy intervention.

Conclusion

The study underscores the importance of socio-economic and infrastructural factors in shaping climate resilience at the neighborhood level. While Daneshgah exhibits greater resilience, Shirabad remains highly vulnerable, requiring immediate policy interventions to enhance its adaptive capacity. Addressing economic vulnerabilities through employment programs and financial support mechanisms can improve household stability and crisis recovery in Shirabad. Infrastructure investments, such as upgrading housing conditions, improving water management systems, and expanding public services, are crucial for reducing climate-related risks. Enhancing public awareness through education and community engagement programs is another vital strategy for strengthening resilience. By increasing knowledge of climate risks and adaptation measures, residents can take proactive steps to mitigate impacts and participate in local disaster risk management initiatives. Strengthening social networks and community-based resilience programs can also improve adaptive capacity, ensuring that vulnerable populations receive adequate support during crises. For urban policymakers, these findings emphasize the need for differentiated resilience strategies that address the specific vulnerabilities of each neighborhood. Shirabad requires urgent investment in infrastructure, economic development, and climate education, while Daneshgah can serve as a model for resilient urban planning. Sustainable urban development policies should prioritize climate adaptation measures, particularly in low-income and informal settlements, to build long-term resilience. Future research should explore additional dimensions of urban resilience, such as governance and institutional capacity, to provide a more comprehensive understanding of climate adaptation in arid cities. Continued monitoring of climate trends and resilience indicators will be essential for evaluating policy effectiveness and guiding future adaptation efforts. Given the increasing frequency and severity of climate hazards, a proactive and inclusive approach to urban resilience is necessary to ensure sustainable development and protect vulnerable communities.

Keywords: Dust Storm, Resilience, Zahedan, Vulnerability, Drought.

کلیدواژه‌ها English

Dust Storm
Resilience
Zahedan
Vulnerability
Drought
1-       Bery Abarkouyi, H., Badaq Jamali, J., & Tavakoli, M. (2003). Application of some meteorological statistical indices to assess drought severity on a national scale. Geographical Research Quarterly, (69), 1178-1198.
2-       Baluchi, Z., Mahmoudi, P., & Hamidianpour, M. (2021). Analysis of local and regional droughts in Iran using circulation theory and the Standardized Precipitation Index (SPI). Geographical Studies of Arid Regions, 12(46), 53-75.
3-       Beyravand, M. (2010). The impact of drought on groundwater resource changes using GIS in Qareh Bagh plain (1993-2008). Master's thesis, Faculty of Geography and Environmental Planning, University of Sistan and Baluchestan.
4-       Hafeznia, M. R. (2003). Introduction to research methodology in humanities. SAMT Publications.
5-       Khosravi, M. (2010). Vertical distribution of dust storms in the Middle East using the NAAPS model in the Sistan region of Iran. Proceedings of the Fourth International Congress of Geographers of the Islamic World, Zahedan, Iran.
6-       Khosravi, M., & Akbari, M. (2009). Analysis of drought characteristics in South Khorasan province. Geography and Development Quarterly, (14), 51-69.
7-       Rakhshani, Z. (2012). Analysis of climatic elements of architecture, wind, and solar radiation in Zahedan (Case study: Professors' district of the University of Sistan and Baluchestan). Master's thesis in Physical Geography - Climate Change Planning, University of Sistan and Baluchestan.
8-       Rafieian, M., Rezaei, M. R., Asgari, A., Parhizkar, A., & Shayan, S. (2010). Explaining the concept of resilience and its indicators in community-based disaster management (CBDM). Spatial Planning and Management, 15(4), 20-41. 
9-       Saeimi Pour, H., Ghorbani, M., Melkian, A., & Ramezan Zadeh Lasboei, M. (2017). Assessment of local stakeholders' resilience in dealing with drought (Case study: Nardin village, Mayamey County, Semnan Province). Rangeland Scientific and Research Journal, 12(1), 62-72.
10-   Tavousi, T., Khosravi, M., & Raeespour, K. (2009). Synoptic analysis of dust storms in Khuzestan province. Geography and Development Quarterly, (20), 32-48.
11-   Araqizadeh, M., & Masoudian, S. A. (2021). Climatic analysis and study of dust storms in Razavi Khorasan. Research on Physical Geography, 53(3), 305-318. 
12-   Alijani, B., & Babaei, O. (2009). Spatial analysis of short-term droughts in Iran. Geography and Regional Planning Journal, (1), 109-121.
13-   Farajzadeh, M. (2004). Drought: From concept to solutions. Geographical Organization of Armed Forces, Tehran.
14-   Kord, B., Rahati, A., Mahmoudi, P., Khosravi, P., & Bidar, H. (2020). Prioritization of Sistan and Baluchestan counties during droughts for optimal drought budget management. Spatial Analysis of Environmental Hazards, 7(2), 1-20.
15-   Montaseri, M., Noorjou, A., & Akbari, M. (2018). Study of meteorological droughts and wet periods in Lake Urmia basins (Case study: Zarrineh Rood and Simineh Rood watersheds). Ecohydrology Journal, 5(1), 189-202.
16-   Negarish, H., & Latifi, L. (2007). Geomorphological analysis of the progression of sand dunes in eastern Sistan plain in recent droughts. Geography and Development Quarterly, (6), 43-60.
17-   Noori, G. R., Khosravi, M., Hamidianpour, M., Mahmoudi, P., Poudineh, M. R., Ehsanzadeh, N., & Alimoradi, M. R. (2017). Comprehensive study of dust storm mechanisms originating from Hamoun wetlands and proposing long-term management solutions. Environmental Protection Organization, 1-255.
18-   Yadegari Far, F., Poudineh, M. R., & Esmaeil Nejad, M. (2023). Resilience assessment of Zahedan County against water crisis and drought. Applied Research in Geographic Sciences, 23(68), 345-364.
19-   Adger, W.N.; Hughes, T.P.; Folke, C.; Carpenter, S.R. and Rockström, J. (2005). Social-ecological resilience to coastal disasters. Science, 309(5737):1036-1039. 
20-   Byun, H. R., Wilhite, D. A. (1999). Objective quantification of drought severity and duration. J. Clim., 12, 27–27.
21-   Cutter –s. l .et al 2008. A place –based model for understanding community resilience to natural disasters. GIobal Environmental change –pp.1-9. doi:10.1017/j. gloenvcha.
22-   Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334.
23-   Davis, I. & Y. Izadkhah, "Building resilient urban communities", Article from OHI, 31, 1, Pp. 11-21, 2006.
24-   Hayes M J, Svoboda M D, Wilhite D A, Vanyarkho O V (1999) Monitoring the 1996 drought using the standardized precipitation index, National Drought Mitigation Center, Ling coln, Nebraska.80(3), 429–438.
25-   Loukas A, Vasiliades L (2004) Probabilistic analysis of drought spatio-temporal characteristics in Thessaly Region, Greece. Nat Hazards Earth Syst Sci 4(5–6):719–731.
26-   Likert, R. (1993). A technique for the measurement of attitudes. Archives of Psychology, 140, 1–55
27-   McKee, T. B., Doesken, N. J., Kleist, J. (1995). Drought monitoring with multiple time scales. Preprints, Ninth Conf. on Applied Climatology, Dallas, TX, Amer. Meteor. Soc., 233–236.
28-   Michaelides, S., Pashiardis, S. (2008). Monitoring drought in Cyprus during the 2007-2008 hydrometeorological year by using the standardized precipitation index (SPI). Eur. Water, 23/24, 123-131.
29-   Mondol, M. A. H., Ara, I., Das, S. C. (2017). Meteorological drought index mapping in Bangladesh using Standardized Precipitation Index during 1981-2010. Adv. Meteorol. 2017, 1-23.
 
30-   Moried, S., Moghaddasi, M., Paemozd, SH., and Ghaemi, H. 2005. Designing drought monitoring system of Tehran province, Applied research report ministry Energy, 253p.
31-   Norris, F.H., S.P. Stevens, B. Pfefferbaum, K.F. Wyche and R. L. Pfefferbaum. 2008. "Community Resilience as a Metaphor, Theory, Set of Capacities, and Strategy for Disaster Readiness." American Journal of Community Psychology 41: 127-150.
32-   Parry, M.L. (2009). Assessing the costs of adaptation to climate change: a review of the UNFCCC and other recent estimates. Iied. 
33-   Prathumchai, K., Honda, K., and Nualchawee, K. 2001. Drought Risk Evaluation Using Remote Sensing and GIS: A case study in Lopburi Province. P 1-12, 22th Asian Conference on Remote Sensing.
34-   Seiler RA, Hayes M, Bressan L (2002) Using the standardized precipitation index for flood risk monitoring. Int J Climatol 22(11):1365–1376.
35-   Smakhtin VU, Hughes DA (2007) Automated estimation and analyses of meteorological drought characteristics from monthly rainfall data. Environ Environ Model Softw 22(6):880–890.
36-   Tegent I, Lacis AA, Fung I, (1996). The influence of climate forcing of mineral aerosols from disturbed soils. Nature 380:419–422.
37-   Türkeș, M., & Tatli, H. (2009). Use of the Standardized Precipitation Index (SPI) and a modified SPI for drought monitoring in Turkey. Theoretical and Applied Climatology, 98(3–4), 295–309.
38-   Tzeng G., and Huang J. 2011. Multiple Attribute Decision Making Methods and Applications. CRC Press, Taylor and Francis Group, A Chapman and Hall Book, Boca Raton.
39-   Vafaeinejad A. 2016. Cropping Pattern Optimization by Using of TOPSIS and Genetic Algorithm Based on the Capabilities of GIS. Iranian Journal of Ecohydrology 3(1): 69-82.
40-   van Rooy, M. P. (1965). A rainfall anomaly index independent of time and space, Notos, 14, 43.
41-   Wilhite, D.A., and Glantz, M.H. 1985. Understanding the drought phenomenon: the role of definition. Water Int. 10: 111-120.