Investigating the Effect of Meteorological Parameters on Heavy Rainfall Events in Different Climates of Iran using Quantile Regression

Subject Areas : Water resources management

Sedigheh Bararkhanpour Ahmadi ¹ , Mohammad Ali Gholami Sefidkouhi ² , Mojtaba Khoshravesh ³

1 - PhD student of Agricultural Meteorology, Water Engineering Department, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
2 - Associate Professor, Water Engineering Department, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
3 - Associate Professor, Water Engineering Department, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

Received: 2022-07-31 Accepted : 2022-12-19 Published : 2023-03-21

Keywords: Quantile regression, Climatic Parameters, Extreme Values, Precipitation, Trend,

Abstract :

Background and Aim: Climate changes caused by the progress and industrialization of human societies have caused changes in the intensity and frequency of heavy precipitation and floods, which have caused irreparable damages. In order to reduce these damages, it is necessary to identify the changes in the threshold values ​​of precipitation and factors affecting it each region. Quantile regression methods are able to examine the trends not only in the median, but also in different ranges of the data series. Therefore, the purpose of this research is to investigate the seasonal trend of different amounts of precipitation and also to investigate the relationship between the climatic parameters of minimum temperature, maximum temperature, minimum relative humidity, maximum relative humidity and wind speed on different amounts of precipitation in different climates of Iran. Method: In the first step, the daily time series of climate data including precipitation, minimum and maximum temperature, minimum and maximum relative humidity and wind speed for a period of 45 years in different seasons for 5 synoptic stations of Babolsar, Shiraz, Bandar Abbas, Khorram Abad and Torbat Heydarieh were formed. In the selection of study stations, we tried to select stations with different climates and with appropriate statistical period. Then, to investigate the trend of seasonal changes of different amounts of precipitation in different quantiles (quantiles 0.01, 0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95 and 0.99) was analyzed using the quantile regression method in all study stations. In the next step, the relationship between the climatic parameters on different amounts of precipitation (low to very high amounts of precipitation) in different seasons was investigated for each of the stations using the quantile regression method. Then the results were analyzed. Results: The results of examining the changes trend of daily precipitation are showed that the high amounts of precipitation in the spring season in Bandar Abbas, Shiraz, and Torbat Heydarieh stations were reduced significantly, but very high amounts of precipitation (0.95 and 0.99 troughs) in the station Babolsar and Khorramabad have increased. Also, very high daily precipitation amounts in summer have decreased in Bandar Abbas station but increased in Torbat Heydarieh and Khorram Abad stations, significantly. While in the winter season, different amounts of precipitation in all seasons have a decreasing trend and there was only a significant positive slope in very high amounts of precipitation (slope of 0.99) in Babolsar station. In the investigation of the parameters affecting the extreme precipitation, the results showed that the amount of impact on the occurrence of heavy rainfall was relatively higher than low to median rainfall. The parameters of minimum temperature, minimum humidity, maximum humidity and wind speed have a positive effect and the maximum temperature parameter has a negative effect on heavy rainfall in different seasons and stations. The highest positive effect coefficients were in spring for wind speed in Babolsar (1.8), in summer for wind speed in Babolsar (3.8), minimum and maximum temperature in Bandar Abbas (-4.03 and 1.53), in Autumn season for maximum humidity and wind speed in Babolsar (2.57 and 2.99) and wind speed in Khorram Abad (1.54) and in winter, for wind speed in Babolsar and Bandar Abbas (1.94 and 6. 2), and minimum temperature in Torbat Heydarieh (0.96). Also, the highest negative effect coefficients of maximum temperature were in autumn and winter seasons (-0.88 and -0.72) in Babolsar and autumn season (-0.63) in Shiraz. Conclusion: The significant changes in increasing and decreasing precipitation are mostly related to the amounts of heavy precipitation, which are different in different seasons and climates. Also, the precipitation of the stations near the north and south coasts have been influenced by climatic parameters to a greater extent. In general, it can be said that flood precipitations are influenced by climatic parameters such as wind speed, humidity and temperature in order of importance and this effect is different depending on the location and time and the influence of different factors. Therefore, it is necessary to apply accurate planning for the correct use of received rainfall and optimal management in the target area using the results of such studies.

References:

Abbasi, F., Bazgeer, S., Kalehbasti, P. R., Oskoue, E. A., Haghighat, M., & Kalehbasti, P. R. (2022). New climatic zones in Iran: A comparative study of different empirical methods and clustering technique. Theoretical and Applied Climatology, 147(1), 47–61.‏

Abbasi, F., Kouhi, M., Javanshiri, Z., Malbousi, S., Habibi Nokhandan, M., Babaeian, I., & Falamarzi, Y. (2020). Climate change detection update over Iran during 1958-2017. Journal of Climate Research, 1399(42), 137–153. [In Persian]

Ahmadi, M., Lashkari, H., Azadi, M., & Keykhosravi, Gh. (2015). Detection of climate change with extreme precipitation indices in great Khorasan. Researches in Earth Sciences, 6(3), 34–52. [In Persian]

Asakereh, H., Masoodian, S., & Tarkarani, F. (2021). Variation in the Spatial Factors Affecting Precipitation in Relation to the Decadal Changes of Annual Precipitation in Iran. Geography and Environmental Planning, 32(3), 129–146. [In Persian]

Bahram, M., Tavakolsadrabadi, M., & Zarei, A. R. (2015). Analysis of Intensity- Duration and Frequency of Drought and Trend of Precipitation Changes in the Shiraz Synoptic Station (Iran). Irrigation and Water Engineering, 6(1), 59–74. [In Persian]

Benoit, D. F,. & Poel, D. V. (2018). BayesQR: a Bayesian approach to quantile regression. Journal of Statistical Software, 76(7), 2–32.

Bolouki, H., Fazeli, M., & Sharifzadeh, M. (2021). Investigating the trend of some climatic parameters in three south coast provinces of Iran, and identifying the areas most affected by climate change. Climate Change Research, 2(6), 47–62. [In Persian]

Chen, W., Cui, H., & Ge, Q. (2021). The spatial and seasonal dependency of daily precipitation extremes on the temperature in China from 1957 to 2017. International Journal of Climatology, 42(3), 1560–1575.

Eblaghian, A., Akhondali, A., Radmanesh, F., & Zarei, H. (2019). Trend Analysis of Temperature, Precipitation, and Relative Humidity Changes in Iran. Irrigation Sciences and Engineering, 42(3), 197–212. [In Persian]

Ghasemifar, E., & Naserpour, S. (2017). Synoptic analysis of heat and cold waves over southern coastal of Caspian Sea. Scientific- Research Quarterly of Geographical Data (SEPEHR), 26(103), 137–146. [In Persian]

Jaya, I. G. N. M., Ruchjana, B. N., Abdullah, A. S., & Toharudin, T. (2020). A relationship between temperature and precipitation over the contiguous Bandung city, Indonesia. Communications in Mathematical Biology and Neuroscience.

Jyothy, S. A., Murthy, D. S., & Mallikarjuna, P. (2021). Climate Change Impacts On Seasonal Rainfall Trends in the Regions of Andhra Pradesh and Telangana States, India. Journal of The Institution of Engineers (India): Series A, 1–13.‏

Kalisa, W., Igbawua, T., Ujoh, F., Aondoakaa, I. S., Namugize, J. N., & Zhang, J. (2021). Spatio-temporal variability of dry and wet conditions over East Africa from 1982 to 2015 using quantile regression model. Natural Hazards, 106, 2047–2076.

Kendall, M. G. (1975). Rank Auto-correlation Methods. Charles Griffin, London.

Khazaei, M., Khazaee, H., & Saghafian, B. (2020). Climate Change Impact on Extreme Rainfalls in Arid Region of Iran. Journal of Environmental Science and Technology, 22(9), 31–42. [In Persian]

Khosravi, U., Balyani, S., & Bayat, A. (2018). Temporal Survey of Annual Precipitation of Shiraz using Time Series Analysis. Water Resources Engineering, 11(38), 1–14. [In Persian]

Koenker, R. (2005). Quantile Regression. first ed, New York, Cambridge University Press, 1–25.

Koenker, R. (2006). Quantile regression in R: A vignette. [Available online at http://www.econ.uiuc.edu/~roger/research/rq/vig.pdf.]

Koenker, R., & Bassett, G. (1978).  Regression Quantils. Econometrica, 46, 33–50.

Koenker, R., & D’Orey, V. (1978). Algorithm AS 229: Computing regression quantiles. Journal of the Royal Statistical Society, 36, 383–393. https://doi.org/10.2307/2347802.

Lausier, A. M., & Jain, S. (2018). Overlooked trends in observed global annual precipitation reveal underestimated risks. Scientific Reports, 8, 16746.

Mann, H. B. (1945). Nonparametric Tests Against Trend, Econometrica. Journal of the Econometric Society, 245–259.

Mirhashemi, H. (2021). Identification of structural breaks and change points of rainfall time series in mountainous areas (Case study: Khorramabad Synoptic Station). JGSMA, 1(4), 1–16. [In Persian]

Mohsenipour, M., Shahid, S., Ziarh, G. F., & Yaseen Z. M. (2020). Changes in monsoon rainfall distribution of Bangladesh using quantile regression model. Theoretical and Applied Climatology, 142(3), 1329–1342.

Nouri, M., Homaee, M., & Bannayan, M. (2018). Analyzing the Trends of Precipitation and Drought in Some Semi-Arid toHumid Regions of Iran. JWSS, 22(1), 45–60. [In Persian]

Pérez Bello, A., Mailhot, A., & Paquin, D. (2021). The Response of Daily and Sub‐Daily Extreme Precipitations to Changes in Surface and Dew‐Point Temperatures. Journal of Geophysical Research: Atmospheres, 126(16), e2021JD034972.

Sharafi, S., & Karim, N. M. (2020). Investigating trend changes of annual mean temperature and precipitation in Iran. Arabian Journal of Geosciences, 13(16), 1–11.‏

Solaimani, K. (2021). Analysis of the Trend of Changes in Some Synoptic Parameters Using Quantile Regression in Babolsar. Irrigation and Water Engineering, 11(3), 236–252. [In Persian]

Wu, X., Meng, F., Liu, P., Zhou, J., Liu, D., Xie, Liu, D., Xie, K., Zhu, Q., Hu, J., Sun, H., & Xing, F. (2021). Contribution of the Northeast Cold Vortex Index and Multiscale Synergistic Indices to Extreme Precipitation Over Northeast China. Earth and Space Science, 8(1), e2020EA001435.

Yong, Z., Xiong, J., Wang, Z., Cheng, W., Yang, J., & Pang, Q. (2021). Relationship of extreme precipitation, surface air temperature, and dew point temperature across the Tibetan Plateau. Climatic Change, 165(1), 1–22.