Determining the relationship between temperature extreme variables and the frequency of environmental dust and evaluating the best model for predicting the FDSD index in the west of the country

Document Type : Research Paper

Authors

1 Irrigation and Development Engineering Department, College of Agriculture and Natural Resources, University of Tehran, Karaj.

2 Associate Professor, Department of Irrigation and Development Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.

Abstract

Dust has always been one of the most important environmental hazards and has adverse environmental consequences. The purpose of this study is to investigate the relationship between temperature extreme variables and dust storms and evaluate the best model for predicting the FDSD index in the west of the country. We used hourly visibility data, World Meteorological Organization codes and temperature extreme indices including maximum temperature (TXx) and minimum temperature (TNn) on a monthly basis for 14 meteorological stations located in the west of the country with a statistical period of 25 years (1990-2014) and correlation between them were considered using Tau-Kendall and Pearson correlation coefficients. Map of correlation coefficients to better display the results was prepared by spline method (base radius method) in ArcGIS software. Also, three artificial intelligence models including best neighbor algorithm (KNN), gene expression programming (GEP) and Bayesian network (BN) were evaluated to predict dust. The results showed that dust storms have a positive and significant correlation with temperature extreme indices in 14 studied stations, so that the highest Tau-Kendall correlation coefficient with FDSD index is related to the maximum temperature variable in Dogonbadan station with a value of 0.202 and with the minimum temperature at Sare-Pole-Zahab station with the correlation coefficient 0.242. Also, the highest Pearson correlation coefficient with FDSD index for the maximum temperature variable in Dogonbadan station was 0.415 and that of the minimum temperature in Islamabad station 0.211. Also, the results of the forecast indicated the proper performance of the KNN method, which is ranked first in 13 stations and the BN method had the best performance in Islamabad station. The results of this study can help to better understand the occurrence of dust storms and to studying their climatic relations, as well as to reducing the damage caused by this phenomenon in the study area.

Keywords


Abdolshahnejad, M., Khosravi, H., Nazari Samani, A. A., Zehtabian, G. R. & Alambaigi, M. (2020). Determining the Conceptual Framework of Dust Risk Based on Evaluating Resilience (Case Study: Southwest of Iran). Strategic Research Journal of Agricultural Sciences and Natural Resources, 5(1), 33-44. (In Persian)
Amini, A. (2020). The role of climate parameters variation in the intensification of dust phenomenon. Natural Hazards, DOI: 10.1007/s11069-020-03933-w.
Ansari Ghojghar, M., &, Shahab, Araghinejad, S. (2017). The study of the reaction of temperature variables to the frequency of days with dust storms (Case study of Lorestan province). Fifth International Congress of Civil Engineering, Architecture and Urban Development, Tehran. (In Persian)
Ansari Renani, M. (2011). Climatic statistical analysis of dust in Zahedan province in the period 1986-2005. The First International Congress on Dust Phenomena and Combating Its Harmful Effects, Ramin Khuzestan University of Agriculture and Natural Resources. (In Persian)
Araghinejad, S. (2013). Data-driven modeling: using MATLAB® in water resources and environmental engineering (Vol. 67). Springer Science & Business Media.
Araghinejad S, Ansari Ghojghar M, PourGholam Amigi M, Liaghat A, Bazrafshan J. (2019). The Effect of Climate Fluctuation on Frequency of Dust Storms in Iran. DEEJ, 7 (21), 13-32. (In Persian)
Asakereh, H. (2011). Fundamentals of Statistical Climatology. Zanjan University Press, First Edition, Zanjan.
Cao, R., Jiang, W., Yuan, L., Wang, W., Lv, Z., & Chen, Z. (2014). Inter-annual variations in vegetation and their response to climatic factors in the upper catchments of the Yellow River from 2000 to 2010. Journal of Geographical Sciences, 24(6), 963-979.
Danandehmehr, A. and M.R. Majdzadeh Tabatabai. (2010). Prediction of daily discharge trend of river flow based on genetic programming. Journal of Water and Soil, 24(2), 325-33 (In Persian).
Ferreira, C. (2001). Gene expression programming: a new adaptive algorithm for solving problems. Complex System, 13, 87-129.
Ferreira, C. (2006). Gene expression programming: mathematical modeling by an artificial intelligence (studies in computational intelligence). Springer-Verlag New York, Inc. Secaucus, NJ, USA.
Ghorbani, S., Moddress, R. (2019). Modelling the Relationship between the Frequency of Dust Storms and Climatic Variables in the Summer Time in Desert Areas of Iran. Journal of Soil and Water Sciences, 23(3), 125-140. (In Persian)
Goudie, A., (2014). Review Desert dust and human health disorders. Journal of Environment International, 63 (3), 101-113.
Goudie, A., Middleton, N. (2006). Desert Dust in the Global System. Springer, 288p.
Jalali, M., Bahrami, H., & Dervish Bolurani, A. (2011). Study of the correlation between climatic parameters with dust storms in Khuzestan province, the first international congress on the phenomenon of dust and dealing with its harmful effects. 26-28 February 2011. Ahvaz. (In Persian)
Jayawardena, A. W., Li, W. K. & Xu, P. (2002). Neighbor selection for local modelling and prediction of hydrological time series. J. of Hydrology, 258, 40-57.
Karlsson, M. & Yakowitz, S. (1987). Nearest-neighbor methods for nonparametric rainfall-runoff forecasting. Water Resources Research, 23(7), 1300-1308.
Kingston, G.B., Lambert, M.F. & Maier, H.R. (2005). Bayesian training of artificial neural networks used for water resources modeling. Water Resources Research, 41(12), 11. https://doi.org/10.1029/2005WR004152.
Mahdavi, M., & Taherkhani., M, (2005). Application of Statistics in Geography. Qoms Publishing, First Edition, Tehran. (In Persian)
MacKay, D.J.C. (1992). A practical Bayesian framework for backpropagation networks. Neural Computation, 4(3), 448-472.
Meshkani, A. & Nazemi, A. (2009). Introduction to data mining. Ferdowsi University of Mashhad, 456 pages. (In Persian)
Mohammadi, G, H. (2015). Analysis of Atmospheric Mechanisms in Dust Transport over West of Iran. Ph.D. thesis, Tabriz University, 142pp.
Movahedi, S., Kh. Hatami Bahman Bigloo and M. Kh. Tangerine Fred. 2014. Spatial and temporal monitoring ofclimatic phenomena related to dust in Iranian cities. Journal of Geography and Environmental Studies, (11), 37-47. (In Persian)
O’Loingsigh, T., McTainsh, G. H., Tews, E. K., Strong, C. L., Leys, J. F., Shinkfield, P., Tapper, N. J. (2014). The Dust Storm Index (DSI): a method for monitoring broadscale wind erosion using meteorological records. Aeolian Research, 12, 29-40.
Pearson, K. (1897). Mathematical contributions to the theory of evolution. on a form of spurious correlation which may arise when indices are used in the measurement of organs. Proceedings of the royal society of London, 60(359-367), 489-498.
Pourgholam-Amiji, M., Ansari Ghojghar, M., Araghinejad, S. & Babaian, I. (2020). Modeling the relationship between dust storms and limit and average temperature variables in the western half of the country. Climatological research, 1400(45), 113-126. (In Persian)
Rashki, A., Kaskaoutis, D.G., Francois, P., Kosmopoulos, P.G., & Legrand, M. )2015(. Dust-storm dynamics over Sistan region, Iran: Seasonality, transport characteristics and affected areas. Aeolian Research, 16, 35-48. (In Persian)
Saremi Naeini, M. (2016), Estimation of the Frequency of Speed and Direction of the Erosive Winds and Dust storms in the Yazd Province, by Using Windrose, Stormrose and Sandrose, Desert Management, 8, 96-106. (In Persian)
Sepahvand, A., Almasian, F. & Zand, M. (2019). Investigating the effect of climatic variables (rainfall, temperature and pressure) on the occurrence of dust in the west of the country. 7th National Conference on Rainwater Catchment Systems. Iran, 20-21 February, 178-187. (In Persian)
Shojaeezadeh, K., R. Drijani., & Heidary, F. (2013). Investigation of climate relationship and dust occurrence (Case Study: Mahshahr City). Proceeding of the Second International Conference on Environmental Hazards, Kharazmi University of Tehran. (In Persian)
Singh, V.P., Translation, M.R. Najafi. (2002). Hydrological systems for rainfall modeling. Tehran University Press, First Edition, 578 pagesM. (In Persian)
Sobhani, B., Safarian zengir, V. (2020). Analysis and prediction of Dust phenomenon in the southwest of Iran. Journal of Natural Environmental Hazards, 8(22), 179-198. (In Persian)
Su, B., Zhan, M., Zhai, J., Wang, Y., & Fischer., T. (2014). Spatio-Temporal variation of haze days and atmospheric circulation pattern in china (1961-2013). Quaternary International. 380, 14-21.
Tan, M., Li, X., Xin, L. (2014). Intensity of dust storms in China from 1980 to 2007: A new definition. Atmospheric environment, 85, 215-222.
Tanarhte, M., Hadjinicolaou, P., & Lelieveld, J. (2012). Intercomparison of temperature and precipitation data sets based on observations in the Mediterranean and the Middle East. Journal of Geophysical Research: Atmospheres, 117(D12).
Tarboton, D. G., Sharma, A., and Lall, U. (1993). The use of non-parametric probability distribution in streamflow modeling. In Proceeding of the 6 South African National Hydrological Symposium, Ed. S. A
Todeschini, R. (1989). K-nearest neighbour method: Influence of data transformations and metrics. Chemometrics and Intelligent Laboratory Systems, 6, 213-220.
Yakowitz, S. J. (1985). Nonparametric density estimation, prediction, and regression for markov sequences. J. Am. Stat. Assoc., 80, 215-221.
Yoshino, M. (2002). Climatology of yellow sand (Asian sand, Asian dust or Kosa) in East Asia. Science in china series dearth. Science, 45, 59-70.
Zanganeh, M. (2014), Climatological Analysis of Dust Storms in Iran, Applied Climatology, 1(1), 1-12. (In Persian)
Zeinali, B. (2016), Investigation of frequency changes trend of days with dust storms in western half of Iran, Natural Environment hazards, 5(7), 87-100. (In Persian)