Volume 10, Issue 1 (5-2023)
Journal of Spatial Analysis Environmental Hazards 2023, 10(1): 143-156 |
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hashemi ana S K. Evaluating changes seasonal in the length of dry spells with the step-by-step assessment method SWARA in Iran. Journal of Spatial Analysis Environmental Hazards 2023; 10 (1) :143-156
URL: http://jsaeh.khu.ac.ir/article-1-3367-en.html
URL: http://jsaeh.khu.ac.ir/article-1-3367-en.html
university of yasouj , k.hashemi@yahoo.com
Abstract: (1730 Views)
Abstract
Introduction and issue: In today's century when the effects of climate change on different sectors are undeniable, investigating and analyzing the behavior during dry spells is always of special importance and basic priority. On the other hand, the occurrence of extreme events such as precipitation can accelerate the occurrence of climate change. In Iran, rainfall is one of the basic variables for evaluating the potential availability of water resources, but its temporal and spatial distribution is very uneven. The change of dry Spells depending on precipitation always have different fluctuations in different seasons of the year. It seems that this is due to the inherent behavior of precipitation, which generally shows itself as an unstable and unruly variable. This feature causes changes and differences in the temporal and spatial distribution of precipitation in arid and semi-arid regions such as Iran. This inconsistency will face fundamental challenges to regularize dry spells on a seasonal and monthly scale. With a detailed understanding of the behavioral mechanism of dry spells, it is possible to know more precisely the climatic condition of different regions in order to plan in sectors such as; Water resources, agriculture, health, transportation and etc we able to do basic and preventive measures compatible with climate change. It is hoped that this research and related studies will be a positive step towards a more accurate understanding of the climate and its behavior in different seasons of the year.
Data and method: In order to investigate the seasonal behavior of the duration of dry spells, we used daily precipitation data for 44 synoptic stations of Iran and a 30-year statistical period (1988-2018). To reveal the behavior of dry spells, the precipitation data after validation and temporal integration were classified on a seasonal scale.
After the statistical integration of the data, dry spells related to precepitation were extracted and long-term periods lasting more than 20 days were the basis of the study. In the next step, to determine the seasonal weight of courses was used, the step-by-step evaluation method of Swara's fuzzy-numerical logic (SWARA). Thus, in the first step, the longest and most frequent periods are sorted based on relative importance. In the second step, the initial weights of the courses are determined, and in the third and fourth steps, the final and normalized weights of the courses in different seasons are determined, and unrealistic results are removed from the final analysis for proper explanation.
Findings and Results: The effectiveness and weight of each of the criteria with the Swara method in the fuzzy environment showed that in the western and northern regions of the country, winter and spring seasons and criteria such as reversibility and percentage of probability of occurrence have the most initial weight in explaining the periods. In the final explanation, these two season,s had a high weight. These two seasons explain more than 65% of the weight of courses in these regions. In the southern regions and parts of the center (Isfahan, East Fars and West Kerman), winter and autumn explain more than 71% of the weight of periods. Among the criteria explaining the weight of the courses, the reversibility criterion and the probability of occurrence have taken more than 55% of the weight. The northern and humid regions of the country vary in criteria from periods such as; Reversibility, continuity and probability of occurrence are more apparent and this indicates that the border of dry areas in the future of Iran's climate will move towards northern areas. It can be acknowledged that the behavior of long-term dry periods is more a function of two criteria of reversibility and probability of their occurrence. The weighting of the criteria affecting dry periods showed that the return period and the continuation of periods in the cold seasons of the year in dry areas have a more irregular behavior than in wet areas and have more weight in explaining the periods. By determining the weight of seasons in explaining dry periods, we can have better planning and management in related sectors such as water and agriculture.
Key words: dry spells, weighing, precipitation, climate, Swara method, Iran.
Type of Study: Research |
Subject:
Special
Received: 2023/02/14 | Accepted: 2023/06/22 | Published: 2023/10/4
Received: 2023/02/14 | Accepted: 2023/06/22 | Published: 2023/10/4
References
1. انصاری، حسین و کامران داوری. 1386. پهنه‌بندی دوره خشک با استفاده از شاخص بارندگی استانداردشده در محیط GIS مطالعه موردی: استان خراسان، پژوهش‌های جغرافیایی، 39 (8): 12-21.
2. ذوالفقاری، حسن و حسن میرزایی. 1397. تحلیل فضایی و پهنه‌بندی دوره‌های خشک اقلیمی در ایران بر اساس شاخص DDSLR، مخاطرات محیط طبیعی،6(12): 1-18.
3. صادقی نیا، علیرضا. 1391. بررسی و مقایسه دوره‌های تر و خشک در بخش‌های مختلف اقلیمی ایران. جغرافیای طبیعی لار، 5(18): 91-81.
4. محمودی، پیمان؛ نادر پروین و رضا جباری. 1392. پهنه‌بندی ایران بر اساس طول دوره‌های خشک، مطالعات جغرافیایی مناطق خشک، 4(13): 106-85.
5. مسعودیان، سید ابوالفضل. 1390. آب‌وهوای ایران، انتشارات شریعه توس، چاپ اول.
6. مفیدی، عباس؛ آذر زرین و میثم کارخانه .1393. بررسی الگوی گردش جو در طول دوره‌های خشک و مرطوب در سواحل جنوبی دریای خزر، مجله ژئوفیزیک ایران، 8(1): 176-140.
7. هاشمی عنا، سید کرامت .1400. طبقه‌بندی تغییرات طول دوره‌های خشک وابسته به بارش در ایران. مجله جغرافیای طبیعی لار، 14(53): 39-55.
8. هاشمی عنا، سید کرامت. 1397. دورنمای اقلیم ایران با تأکید بر دوره‌های خشک. چاپ اول، انتشارات مینو فر، مشهد.
9. هاشمی عنا، سید کرامت. 1401. ارزیابی اثر تغییر اقلیم بر برنامه‌ریزی تخصیص بهینه منابع آب در استان کهگیلویه و بویراحمد. مخاطرات محیط طبیعی، 12(35).
10. Adane, G. B., Hirpa, B. A., Lim, C. H., & Lee, W. K. 2020. Spatial and temporal analysis of dry and wet spells in upper Awash River Basin, Ethiopia. Water, 12(11): 3051.
11. Ansary, A. H, , and Sanaei-Nejad, S. H. 2018. Analyzing drought history using Fuzzy Integrated Drought Index (FIDI): a case study in the Neyshabour basin, Iran. Arabian Journal of Geosciences, 11(14): 1-10.
12. Breinl K and Van Loon A F. 2018. Water shortages worsened by reservoir effects, Nat. Sustain. 1:22.
13. Douguedroit, A. 2018 .The variations of dry spells frequency and validaty in daily Rain’, J. Climatol., :7 541–555.
14. Escalante-Sandoval, C., and Nunez-Garcia, P. 2017 Meteorological drought features in northern. and northwestern parts of Mexico under different climate change scenarios. Journal of Arid Land, 65-.75:(1)9
15. Escalante-Sandoval, C., and Nunez-Garcia, P. 2017. Meteorological drought features in northern and northwestern parts of Mexico under different climate change scenarios. Journal of Arid Land, 9(1): 65-75.
16. Feng, T., Tipton, Z., Xia, L., and Chang, Y.,. .2020. Evaluation of CORDEX regional climate models in simulating extreme dry spells in Southwest China. Frontiers in Earth Science,2 294:.
17. Grace RA, Eagleson PS.1988. The synthesis of shorttime-increment precipitation sequences, Hydrodynamics Laboratory, Massachusetts of Cambridge, USA No. 91: Report,56.
18. Kendon, E. J., Stratton, R. A., Tucker, S., Marsham, J. H., Berthou, S., Rowell, D. P., and Senior, C. A.2019. Enhanced future changes in wet and dry extremes over Africa at convection-permitting scale. Nature communications, 10(1): 1-14.
19. Keršuliene, V., Zavadskas, E. K., and Turskis, Z. 2010. Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (SWARA). Journal of business economics and management, 11(2), 243-258.
20. Ratan R and Venugopal. 2013. Wet and dry spell characteristics of global tropical rainfall Water Resour. Res.49. (2): 30-40.
21. Sánchez, E., Domínguez, M., Romera, R., de la Franca, N. L., Gaertner, M. A., Gallardo, C., & Castro, M. 2011. Regional modeling of dry spells over the Iberian Peninsula for present climate and climate change conditions. Climatic change, 107(3): 625-634.
22. Sanchi, I. D. 2021. Critical Review of the Causes and Effects of Dry Spell in Rainy Season in Danko Wasagu Local Government, Kebbi State, Nigeria. Cross Current Int J Agri Vet Sci, 3(8): 66-75.
23. Selvaraj RS, Selvis T . 2010. Stochastic modelling of daily precipitation at Aduthurai in india. International journal of climatology, 11(3): 20-29.
24. Thoithi, W., Blamey, R. C., and Reason, C. J. 2021. Dry spells, wet days, and their trends across Southern Africa during the summer rainy season. Geophysical Research Letters, 48(5): 20-34.
25. Tichavský, R., Ballesteros-Cánovas, J. A., Šilhán, K., Tolasz, R., and Stoffel, M. 2019. Dry Spells and extreme precipitation are the Main trigger of Landslides in central Europe. Scientific reports, 9(1): 10.
26. Wilks D S. 2018. “The stippling shows statistically significant grid points” how research results are routinely overstated and over interpreted, and what to do about it Bull. Am. Meteorol. Soc. 97:22
27. Yihdego, Y., Vaheddoost, B., & Al-Weshah, R. A. 2019. Drought indices and indicators revisited. Arabian Journal of Geosciences, 12, 69.
28. Zhang, C., Ren, Y., Cao, L., Wu, J., Zhang, S., Hu, C., and Zhujie, S. 2022. Characteristics of dry-wet climate change in China during the past 60 years and its trends projection. Atmosphere, 13(2): 275.
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