پهنهبندی تعداد روز طوفانی در کشور ایران با استفاده از روشهای زمینآماری و ریاضی
محورهای موضوعی : سیستم اطلاعات جغرافیاییحسن فتحی زاد 1 , علی خنامانی 2 , محمد زارع 3
1 - دکتری بیابانزدایی، دانشکده منابع طبیعی و کویرشناسی، دانشگاه یزد.
2 - دکتری بیابانزدایی، دانشکده منابع طبیعی و کویرشناسی، دانشگاه یزد.*(مسوول مکاتبات)
3 - دانشیار دانشکده منابع طبیعی و کویرشناسی، دانشگاه یزد.
کلید واژه: گرد و غبار, ایران, میانیابی, کریجینگ, قابلیت دید,
چکیده مقاله :
زمینه و هدف: تعداد روز طوفانی به وسیله عوامل گوناگونی مانند سرعت وزش باد، میزان بارش، رطوبت خاک و غیره قرار دارد. بررسی این شاخص در کشور می تواند در برنامه ریزی های گوناگون مورد توجه قرار گیرد. هدف از انجام این تحقیق پهنه بندی تعداد روزهای طوفانی در کشور و انتخاب بهترین مدل بر اساس داده های 150 ایستگاه هواشناسی در دوره آماری 25 ساله 2010-1986میلادی است. روش بررسی: بعد از تعیین ایستگاه ها با پراکندگی مناسب، داده های تعداد روز طوفانی در کشور ایران مربوط به دوره ی زمانی 2010-1986 در سال 1395 جمع آوری شد. به منظور بررسی نرمال بودن داده ها از روش کلموگروف- اسمیرنف استفاده گردید. جهت نشان دادن همبستگی مکانی بین داده های تعداد روز طوفانی از واریوگرام استفاده شد. وایروگرام گوسین با میزان همبستگی 96/0، بهترین همبستگی بین داده ها را مدل سازی نمود و برای درون یابی از روش کریجینگ استفاده گردید. سپس با استفاده از روش های مختلف زمین آماری و ریاضی، نقشه تعداد روزهای طوفانی در کشور ترسیم شد. به این منظور از روش های درون یابی ریاضی شامل روش عکس فاصله (IDW)، درون یاب چند جمله ای جهانی (GPI)، تابع شعاعی (RBF)، درون یاب موضعی (LPI) و روش زمین آماری کریجینگ استفاده شد. جهت انتخاب بهترین روش درون یابی از شاخص های آماری ریشه میانگین مربعات (RMS) و میزان همبستگی داده های مشاهداتی و پیش بینی شده استفاده گردید. یافته ها: نتایج نشان داد که پیش بینی روش کریجینگ شاخص (Kriging Indicator) دارای بیشترین میزان همبستگی با داده های مشاهداتی است (R2=0.74). همپنین مناطق جنوب شرقی و جنوب غربی کشور دارای بیشترین میزان تعداد روز طوفانی در کشور می باشند. بحث و نتیجه گیری: بالا بودن این شاخص در جنوب شرق ناشی از خشک شدن دریاچه هامون و وجود بادهای 120 روزه ی سیستان و در جنوب غرب کشور ناشی از گرد و غبار ورودی از کشورهای عربی است. نوار شمالی کشور نیز دارای کمترین میزان شاخص تعداد روز طوفانی در کشور است.
Background and Objective: The number of stormy days is determined by various factors such as wind speed, rainfall, soil moisture and so on. The study of this index in the country can be considered in various plans. The purpose of this research is mapping of the number of dusty stormy days in Iran and selecting the best model based on the climatic data of 150 meteorological stations for the period of 25 years (1986-2010). Method: Dust stormy days’ data of the studied stations were analyzed using variogram curves to represents their spatial correlation. Gaussian variogram (R2=0.96) shows the highest correlation between the data. Then, map of the number of dust stormy days in Iran were prepared using different geostatistical and mathematical methods. For this purpose, several mathematical interpolation methods including Inverse Distance Method (IDW), Global Polynomial Interpolation (GPI), Radial Basis Function (RBF), Local Polynomial Interpolation (LPI), and geostatistical method of Kriging were used. To select the best interpolation method among several geostatistical and mathematical methods, statistical indicators of Root Mean Square (RMS) and correlation coefficient between observed and predicted data were used. Findings: Results show that the highest correlation between predicted and observed data (R2 = 0.74) was found in kriging indicator method. The southeast and southwest of the country have the highest number of dust storm days. Discussion and Conclusion: High number of dust stormy days in the southeast is resulting from drying of Hammon lakes and blowing of 120-day winds in Sistan plain, and entering of dust from Arabic countries form the direction of southwest. North part of the country has the lowest number of dust storm days.
- Di, M., Lu, X., Sun, L., Wang, P., 2008. A Dust-Storm Process Dynamic Monitoring with Multi-Temporal MODIS Data.21st, International Society for Photogrammetry and Remote Sensing. Journal of Photogrammetry and Remote Sensing, Vol 37: pp 965-970.
- Mattsson, J. O., Nihlén, T., 1996. The transport of Saharan dust to southern Europe: a scenario. Journal of Arid Environments, Vol 32: pp 111-119.
- Squires, V. R., 2002. Mitigating and preventing sand-dust storms: problems and prospects. In Yang Youlin, Victor Squires & Lu Qi (Eds.), Global Alarm: Dust and Sandstorms from the World's Drylands, (pp. 15-73). New York: United Nations.
- Zanganeh, M., 2014. Meteorology of Dust Storms in Iran, Applied Meteorology Quarterly, No. 1, pp 1-12. (In Persian)
- Lamb, P. J., Leslie, L. M., Timmer, R., Speer, M. S., 2009. Multidecadal variability of Eastern Australian dust and Northern New Zealand sunshine: associations with Pacific climate system. Journal of Geophysical Research, [Atmos.] Vol 114, D09106. http://dx.doi.org/ 10.1029/2008JD011184.
- Sajjadi, A., 2013. Environmental Impacts of Pollutions (Air Pollution, Sound Pollution, Dust), First National Conference on Environmental Engineering and Sustainable Development. (In Persian)
- Farajzadeh Asl, M, and Alizadeh, Kh., 2011. Temporal and Spatial Analysis of Dust Storms in Iran, Space Planning and Preparation, No. 15, pp. 65-84. (In Persian)
- Hosseini, E., Gallichand, J. and Caron, J., 1993. Comparison of several interpolators for smoothing hydraulic conductivity data in southwest Iran. ASAE, Vol 36: pp 1687-1693.
- Corwin, D. L., Sorensen, M. and Rhoades, J. D., 1992. Using GIS to locate salinity on irrigated soils. Proc. 8th Conf. Computing in Civil Engineering in Conjunction with A/E/C system ‘92, TCCP/ASCE-Dallas, TX, June 7: pp 468-485.
- Karimiznar, M., Fakhirah, A., Feyznia, S., Rashki, A, and Mir-Soleiman, J., 2009. Evaluation of Some Geostatistical Methods for Estimating Wind Erosion Threshold Speed in Sistan Plain, Rangeland and Watershed Management (Iranian Natural Resources), No. 62. Pp 417-405. (In Persian)
- Shabani, A., Matinfar, H. R., Arekhi, S. and Rahimi, S., 2011. Modeling of Rainfall Erosion Factor Using Geostatistical Method (Case Study: Ilam Dam Watershed), Remote Sensing and Geographic Information System in Natural Resources, No. 2, pp. 66-55. (In Persian)
- Matinfar, H. R., Shabani, A. and Azizi Ghalati, S., 2010. Investigation of Spatial Changes of Some Soil Nutrients Using Geostatistical Methods (Case Study of Silakhor Plain), Second National Conference on Agriculture and Sustainable Development (Opportunities and Challenges). (In Persian)
- Mahdian, M., 2002. Determination of Optimization Interpolation Methods to Estimate Rainfall and Temperature in Arid, Semiarid and Humid Regions (IRAN). Project Report Soil Conservation and Watershed Management Research Institute.
- Mirmousavi, Sh., Mazidi, A., Khosravi Y., 2010. The determination of optimum geostatistics method for estimating precipitation distribution using GIS (case study of Esfahan province), Geographic Space, Vol 10: pp 105-120.(In Persian).
- Gohardost, A., Azimi, F. and Zohourian, M., 2011. Synoptic Investigation and Analysis of Khuzestan Dust Peak Days, First International Congress on Dust Phenomena and its Impacts, pp 709-718. (In Persian)
- Vali, A. and Roostae, F., 2017. A Survey of Wind Erosion Trends in Central Iran Using the Dust Storm Index in the Recent Fifty Years, Journal of Water and Soil Science (Agricultural Science and Technology). pp 200-189 (In Persian).
- Hohn, M. E., 1998. Geostatistics and petroleum geology, Kluwer Academic Publisher, Netherlands.
- Lu, G. Y., Wong, D. W., 2008. An Adaptive Inverse-Distance Weighting Spatial Interpolation Technique. Computers & Geosciences, Vol 34: pp 1044-1055.
- Hirsche, K., Boerner, S., Kalkomey, C., Gastaldi, C., 1998. Avoiding pitfalls in geostatistical reservoir characterization: A survival guide: The leading Edge, Vol 17, pp 493-504.
- Johnston, K., Ver Hoef, J. M., Krivoruchko, K., Lucas, N., 2001. Using Geostatistical Analyst, Environmental Systems Research Institute, Inc (ESRI).
- Bohling, G., 2005. Introduction to GeoStatistics and Variogram Analysis, Assistant Scientist Kansas Geological Survey Ferro, V., Giordano, G. and Lovino, M. 1991. Isoerosivity and erosion risk map for Sicily. Hydrology Sciences Journal, Vol 36: pp 549–564.
- Hassani Pak, A. S., 2007. Geostatistics. Tehran University Press.
- Webster, R., Oliver, M. A., 2000. Geostatistics for environmental scientists. Wiley press, 271 pp.
_||_
- Di, M., Lu, X., Sun, L., Wang, P., 2008. A Dust-Storm Process Dynamic Monitoring with Multi-Temporal MODIS Data.21st, International Society for Photogrammetry and Remote Sensing. Journal of Photogrammetry and Remote Sensing, Vol 37: pp 965-970.
- Mattsson, J. O., Nihlén, T., 1996. The transport of Saharan dust to southern Europe: a scenario. Journal of Arid Environments, Vol 32: pp 111-119.
- Squires, V. R., 2002. Mitigating and preventing sand-dust storms: problems and prospects. In Yang Youlin, Victor Squires & Lu Qi (Eds.), Global Alarm: Dust and Sandstorms from the World's Drylands, (pp. 15-73). New York: United Nations.
- Zanganeh, M., 2014. Meteorology of Dust Storms in Iran, Applied Meteorology Quarterly, No. 1, pp 1-12. (In Persian)
- Lamb, P. J., Leslie, L. M., Timmer, R., Speer, M. S., 2009. Multidecadal variability of Eastern Australian dust and Northern New Zealand sunshine: associations with Pacific climate system. Journal of Geophysical Research, [Atmos.] Vol 114, D09106. http://dx.doi.org/ 10.1029/2008JD011184.
- Sajjadi, A., 2013. Environmental Impacts of Pollutions (Air Pollution, Sound Pollution, Dust), First National Conference on Environmental Engineering and Sustainable Development. (In Persian)
- Farajzadeh Asl, M, and Alizadeh, Kh., 2011. Temporal and Spatial Analysis of Dust Storms in Iran, Space Planning and Preparation, No. 15, pp. 65-84. (In Persian)
- Hosseini, E., Gallichand, J. and Caron, J., 1993. Comparison of several interpolators for smoothing hydraulic conductivity data in southwest Iran. ASAE, Vol 36: pp 1687-1693.
- Corwin, D. L., Sorensen, M. and Rhoades, J. D., 1992. Using GIS to locate salinity on irrigated soils. Proc. 8th Conf. Computing in Civil Engineering in Conjunction with A/E/C system ‘92, TCCP/ASCE-Dallas, TX, June 7: pp 468-485.
- Karimiznar, M., Fakhirah, A., Feyznia, S., Rashki, A, and Mir-Soleiman, J., 2009. Evaluation of Some Geostatistical Methods for Estimating Wind Erosion Threshold Speed in Sistan Plain, Rangeland and Watershed Management (Iranian Natural Resources), No. 62. Pp 417-405. (In Persian)
- Shabani, A., Matinfar, H. R., Arekhi, S. and Rahimi, S., 2011. Modeling of Rainfall Erosion Factor Using Geostatistical Method (Case Study: Ilam Dam Watershed), Remote Sensing and Geographic Information System in Natural Resources, No. 2, pp. 66-55. (In Persian)
- Matinfar, H. R., Shabani, A. and Azizi Ghalati, S., 2010. Investigation of Spatial Changes of Some Soil Nutrients Using Geostatistical Methods (Case Study of Silakhor Plain), Second National Conference on Agriculture and Sustainable Development (Opportunities and Challenges). (In Persian)
- Mahdian, M., 2002. Determination of Optimization Interpolation Methods to Estimate Rainfall and Temperature in Arid, Semiarid and Humid Regions (IRAN). Project Report Soil Conservation and Watershed Management Research Institute.
- Mirmousavi, Sh., Mazidi, A., Khosravi Y., 2010. The determination of optimum geostatistics method for estimating precipitation distribution using GIS (case study of Esfahan province), Geographic Space, Vol 10: pp 105-120.(In Persian).
- Gohardost, A., Azimi, F. and Zohourian, M., 2011. Synoptic Investigation and Analysis of Khuzestan Dust Peak Days, First International Congress on Dust Phenomena and its Impacts, pp 709-718. (In Persian)
- Vali, A. and Roostae, F., 2017. A Survey of Wind Erosion Trends in Central Iran Using the Dust Storm Index in the Recent Fifty Years, Journal of Water and Soil Science (Agricultural Science and Technology). pp 200-189 (In Persian).
- Hohn, M. E., 1998. Geostatistics and petroleum geology, Kluwer Academic Publisher, Netherlands.
- Lu, G. Y., Wong, D. W., 2008. An Adaptive Inverse-Distance Weighting Spatial Interpolation Technique. Computers & Geosciences, Vol 34: pp 1044-1055.
- Hirsche, K., Boerner, S., Kalkomey, C., Gastaldi, C., 1998. Avoiding pitfalls in geostatistical reservoir characterization: A survival guide: The leading Edge, Vol 17, pp 493-504.
- Johnston, K., Ver Hoef, J. M., Krivoruchko, K., Lucas, N., 2001. Using Geostatistical Analyst, Environmental Systems Research Institute, Inc (ESRI).
- Bohling, G., 2005. Introduction to GeoStatistics and Variogram Analysis, Assistant Scientist Kansas Geological Survey Ferro, V., Giordano, G. and Lovino, M. 1991. Isoerosivity and erosion risk map for Sicily. Hydrology Sciences Journal, Vol 36: pp 549–564.
- Hassani Pak, A. S., 2007. Geostatistics. Tehran University Press.
- Webster, R., Oliver, M. A., 2000. Geostatistics for environmental scientists. Wiley press, 271 pp.