Analysis of the Climate Drought and Its Effects on Spatial Patterns of Location in Rural Settlement (Case Study Villages in Mazandaran Province)

Document Type : مقاله پژوهشی

Authors

• Yaser Hakimdost ¹
• Mousa Rastegar ²
• AliMohammad Pourzeidi ³
• Hossein Hatami ²

¹ Payam- Noor University of Tehran

² Ferdowsi University of Mashhad

³ Azad University of Chaloos

10.22067/geo.v3i3.32701

Abstract

1. Introduction

Drought is one of the most complex problems not only in the management of water resources, but also creates economic and social issues . But the problem definition, identification and prediction of unresolved. The occurrence of drought can be caused by several factors, mainly rooted in the general circulation of the atmosphere and space physics, and Earth's energy balance is sought. Continuous and prolonged drought and water shortages said. Drought indices to evaluate various aspects of the invention are wipe the index is often based on a measure of deviation from the mean long-term rainfall amounts over a specified period of time is based. .One of the most effective profiles, Standardized Precipitation Index SPI the first time by Mackay (1993 ) was used . Feature of this index is that it allows the researcher of drought and rain events occurred for each stage of defining the desired time. The drought has five main features are as follows: beginning and end of the period of persistence, intensity, frequency and scope. .These features are related to the drought is examined in each study.
2. Material and Methods
The research and application of analytical and statistical is an approach to governing. The present study is based on annual rainfall of 22 -year drought in the province from 1988 to 2010 was performed. For this purpose, using data from the Survey of precipitation is 22 synoptic stations and rain. Because some data are incomplete meteorological stations using the ratio method, incomplete statistics were estimated . The zoning of the models and methods used in kriging IDW The fitting includes three power IDW 1, 2,3 , and kriging with spherical model , circular , exponential , Gaussian and is And the use of radial basis function RBFdone . Also for spatial analysis and modeling of spatial autocorrelation Moran drought indicators and statistics will be used for general GTo the spatial pattern of drought and rural location in the province Mazandaran of space Analysis placed.
3. Result and discussion
Based on interpolation models were extracted from the optimized model for zoning drought province Spline model is quite regular . Studies show that a very dry area 284,208.5 square kilometers, 704,854 square kilometers little dry, dry, normal 483,280.5 kilometers, 535,492.1 kilometers normal wet and very wet zone and Framrtvb a total of 210,837.01 square kilometers have been allocated to The results of application Moran index on the spatial distribution of drought, this coefficient is positive and equal Moran`s I = 0.994307 good indicator of the spatial distribution of drought . Because the ratio of the number 1 indicates the focus tends to be higher. Since the Z Score = 6.9462 calculated sig.I = 0.01 confidence level greater than the expected value (EI = 2.58) is, therefore, welcome the spatial distribution of precipitation Moran coefficient is confirmed. Welcome to the spatial distribution of rainfall as a result of the Moran coefficient is confirmed. General G statistic analysis results show that parts of West and West Coast and parts of the province is a hot area, The Z score of 6.518083 , which is significant at a confidence level of 01/0 .From the results obtained , The correlation matrix of the table , we can say that the level of trust between area clusters 0/01 hot and cold , drought and rural location, there Mazandaran. However, this amount is equal to 0/914 direct (positive) population.
4. Conclusion
The results are quite regular completely regularized spline determine the best model 0/45. The results of the application of Moran's index of spatial distribution of drought, the coefficient is positive and equal Moran's = 0/99 representing the cluster spatial distribution of drought. According to Moran index can identify a variety of statistical analyzes using the general classification of spatial patterns should G This shortcoming was capped. General statistics G analysis results show that drought areas located on the other side of the cluster is focusing on drought enjoy. The area of each cluster of villages was calculated based on. Calculations show very hot clusters about% 35/21 of the land area is just over 753 villages. Slightly cool to slightly warm the total area covers 1,245 villages while clustering is % 37/17. The results indicate that the correlation between the number of clusters and villages confidence level of 99 /0% error level 004 / 0, which is a direct relationship, but much weaker .With increasing cluster size is relatively low added.

Keywords

• drought
• Spatial Analysis
• Moran
• General Statistics G
• Mazandaran

---

References

بذرافشان، ام البنین؛ محسنی ساروی، محسن؛ ملکیان، آرش؛ معینی، ابوالفضل؛ 1390. بررسی وضعیت خشک‌سالی استان گلستان با استفاده از شاخص بارش استاندارد (SPI). فصلنامه علمی-پژوهشی مرتع و بیابان ایران. جلد18. شماره3. صفحه 495-407. تهران

ژاک باوو، ژان؛ 1386. مقدمه برتحلیل فضایی. ترجمه فرید، یدالله. نشردانشگاه آزاد اسلامی واحد اهر. صص 123-145.

عساکره، حسین؛ 1387. کاربرد روش کریجینگ در میان یابی بارش. جغرافیا و توسعه. شماره12. صص 25-44.

عساکره، حسین؛ 1390. مبانی اقلیم‌شناسی آماری. انتشارات دانشگاه زنجان. صفحه 350.

غیور، حسنعلی؛ مسعودیان، ابوالفضل؛ 1376. بزرگی گستره و فراوانی خشک‌سالی در ایران. فصلنامه تحقیقات جغرافیایی. شماره پیایی45. صص 36-52. اصفهان.

کلانتری، محسن؛ قهرمانی، علی اکبر؛ خسروی، یونس؛ جباری، کاظم؛ 1386. مدیریت وتحلیل داده های بزهکاری در بخش مرکزی شهرر تهران با استفاده از تکنیک های درون یابی و سامانه اطلاعات جغرافیایی. فصلنامه مطالعات مدیریت انتظامی. شماره 4. زمستان. صص494- 502.

لشنی زند، مهران؛ 1383؛ بررسی اقلیمی خشک‌سالی های ایران و راهکارهای مقابله با آن. رساله دکتری. جغرافیای طبیعی. دانشگاه اصفهان. اصفهان. صص 123-143.

مظفری، غلامعلی؛ میرموسوی، حسین؛ خسروی، یونس؛ 1390. ارزیابی روش زمین آمار و رگرسیون خطی در توزیع مکانی بارش (مورد: استان بوشهر). جغرافیا و توسعه. شماره27. تابستان. صص63-76. زاهدان.

Asakereh, Hussein., 2009. Kriging Application in Climatic Element Interpolation A Case Study: Iran Precipitation. Geography and Development iranian jo urnal. No. 12, pp. 25-44.

Asakereh, Hussein., 2011. Fundamentals of statistical climatology. Zanjan university,p350.

Bazrafshan, O, Mohseni Saravi, M, Malekian, A. and Moeini, A., 2011. A study on drought characteristics of Golestan Province using StandardizedPrecipitation Index (SPI), Iranian journal of Range and Desert Reseach, Vol. 18 No. (3),pp407-495,Tehran.

Bordi, I. Sutera, A., 2004., Drought variability and its climatic implications, Global and Planetary Change, 40(1, 2), pp.115-127.

Clark, w.a.v. Hosking,p.l. 1986, Statistical Methods for geographers, John Wiley and sons, New York, p.379.

Edwards D.C. and McKee, TB., 1997. Characteristics of 20th century drought in the United States at multiple timescales", Colorado State University: Fort Collins. Climatology Report No. pp. 97-2.

Gayoor, Hasan Ali, Massodian, Syed Abolfazl.,1997. Great scope and frequency of drought in Iran, Geographical Research, 45.pp No. 36-52, Isfahan.

Hayes.M., 2000. Revisiting the SPI: Clarifying the Process, Drought Network News, Vol. 12, No. 1, winter 1999–Spring, p145.

Jacques Bav, Jan, Introduction to Spatial Analysis., 2007. Translation Farid, Yadu'llah, Islamic Azad University of Ahar, pp123-145.

Kalntari, Mohsen,Ghahramani,Ali Akbar, Khosravi,Younes, Jabari, Kazim., 2007. Management and analysis of crime data in the central part of Tehran using interpolation techniques and GIS, Journal of Management Studies security, No. 4, Winter, pp494- 502.

LashaniZand, Mehran., 2004. Of drought and climate strategies for coping with it, PhD thesis, Physical Geography, University of Isfahan, Pp. 123-143.

Machlica, A. Stojkovova, M., 2008. Groundwater drought in different geological conditions. XXIVth Conference of the Danubian Countries. 1-9,pp212-213.

Mozaffari, Gholam Ali, Mirmusavi, Hossein, Khosravi,Younes., 2011. The Assessment of Geostatistic Methods and Linear Regression in Order to Specify the Spatial Distribution of Annual Precipitation Case study: Boushehr Province, Geography and Development iranian jo urnal, Volume 10, Issue 27, Summer, pp 63-76.

Ole, E.T. and Wolfgang, S. (ZAMG)., 2002. Applications of spatial interpolation of climatologicaland Meteorological elements by the use of geographical information, COST 719: 1-45.

Thomas, R.W. Hug get,R J., 1980. Modeling in Geography, a mathematical approach. Harper and Row. Publisher, London.