Statistical Analysis of Winter Precipitation Values in the Dez River Basin

Document Type : Research Paper

Author

Department of Water Engineering, Lorestan University, Khorramabad, Iran.

10.22059/jwim.2025.403277.1263

Abstract

This research investigates the variations in the distribution and quantity of winter precipitation at 18 stations located in the Dez River Basin, western Iran, during the period 1975-2024. The results from the modified Mann-Kendall test indicate that 50% of the stations (9 stations, including Takht Dareh, Keshvar, and Tang Pang Bakhtiari) have experienced a significant decreasing trend at the 5% level. According to the Sen's slope estimator, the most severe decreases (more than 3 mm per year) occurred at the Tang Pang Bakhtiari, Telezang, and Keshvar stations, which collectively led to a reduction of more than 150 mm over the study period. Temporal changes were primarily concentrated around two points: 1990 and 2006, indicating the influence of large-scale climatic factors. Furthermore, the analysis of the statistical distribution of data before and after the change points revealed a change in the distribution type (Changing from Weibull to Log-Normal based on Kolmogorov-Smirnov statistics) and significant changes in statistical indices such as variance and skewness at many stations. These findings are consistent with the predictions of IPCC reports and other regional studies and demonstrate that the decrease in winter precipitation is a large-scale challenge with serious implications for the region's water resources. The results also indicate changes in the form of the distribution function and severe changes in skewness in the sub-interval after the change point.

Keywords

Main Subjects

References

  1. Ahmadi, F., Nazeri Tahroudi, M., Mirabbasi, R., Khalili, K., & Jhajharia, D. (2018). Spatiotemporal trend and abrupt change analysis of temperature in Iran. Meteorological Applications, 25(2), 314-321. https://doi.org/10.1002/met.1694
  2. Ashouri, H., Hsu, K. L., Sorooshian, S., Braithwaite, D. K., Knapp, K. R., Cecil, L. D., ... & Prat, O. P. (2015). PERSIANN-CDR: Daily precipitation climate data record from multisatellite observations for hydrological and climate studies. Bulletin of the American Meteorological Society, 96(1), 69-83. https://doi.org/10.1175/BAMS-D-13-00068.1
  3. Berger, V. W., & Zhou, Y. (2014). Kolmogorov–smirnov test: Overview. Wiley statsref: Statistics reference online. https://doi.org/10.1002/9781118445112.stat06558
  4. Darand, M., Amanollahi, J., & Zandkarimi, S. (2017). Evaluation of the performance of TRMM Multi-satellite Precipitation Analysis (TMPA) estimation over Iran. Atmospheric Research, 190, 121-127. https://doi.org/10.1016/j.atmosres.2017.02.011
  5. Fischer, G., Shah, M., N. Tubiello, F., & Van Velhuizen, H. (2005). Socio-economic and climate change impacts on agriculture: an integrated assessment, 1990–2080. Philosophical Transactions of the Royal Society B: Biological Sciences, 360(1463), 2067-2083. https://doi.org/10.1098/rstb.2005.1744
  6. Giorgi, Filippo, and Piero Lionello. "Climate change projections for the Mediterranean region." Global and planetary change 63, no. 2-3 (2008): 90-104. https://doi.org/10.1016/j.gloplacha.2007.09.005
  7. Hamed, K. H., & Rao, A. R. (1998). A modified Mann-Kendall trend test for autocorrelated data. Journal of hydrology, 204(1-4), 182-196. https://doi.org/10.1016/S0022-1694(97)00125-X
  8. Hawkins, E., & Sutton, R. (2011). The potential to narrow uncertainty in projections of regional precipitation change. Climate dynamics, 37(1), 407-418. https://doi.org/10.1007/s00382-010-0810-6
  9. IPCC. (2022). Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press.
  10. Kendall, M. G., & Stuart, A. (1963). The advanced theory of statistics: in 3 volumes. C. Griffin.
  11. Khalili, K., Tahoudi, M. N., Mirabbasi, R., & Ahmadi, F. (2016). Investigation of spatial and temporal variability of precipitation in Iran over the last half century. Stochastic environmental research and risk assessment, 30(4), 1205-1221. https://doi.org/10.1007/s00477-015-1095-4
  12. Kumar, S., Merwade, V., Kam, J., & Thurner, K. (2009). Streamflow trends in Indiana: effects of long term persistence, precipitation and subsurface drains. Journal of Hydrology, 374(1-2), 171-183. https://doi.org/10.1016/j.jhydrol.2009.06.012
  13. Kundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P., ... & Sherstyukov, B. (2014). Flood risk and climate change: global and regional perspectives. Hydrological Sciences Journal, 59(1), 1-28. https://doi.org/10.1080/02626667.2013.857411
  14. Mann, H. B. (1945). Nonparametric tests against trend. Econometrica: Journal of the econometric society, 245-259. https://doi.org/10.2307/1907187
  15. Milly, P. C., Dunne, K. A., & Vecchia, A. V. (2005). Global pattern of trends in streamflow and water availability in a changing climate. Nature, 438(7066), 347-350. https://doi.org/10.1038/nature04312
  16. Modarres, R., & Sarhadi, A. (2011). Statistically-based regionalization of rainfall climates of Iran. Global and Planetary Change, 75(1-2), 67-75. https://doi.org/10.1016/j.gloplacha.2010.10.009
  17. Nazeri Tahroudi, M. (2025). Comprehensive global assessment of precipitation trend and pattern variability considering their distribution dynamics. Scientific Reports, 15(1), 22458. https://doi.org/10.1038/s41598-025-06050-5
  18. Nazeri Tahrudi, M., Khalili, K., & Ahmadi, F. (2016). Spatial and regional analysis of precipitation trend over Iran in the last half of century. Water and Soil, 30(2), 643-654. https://doi.org/10.22067/jsw.v30i2.39130. (In Persian)
  19. Nicholson, S. E. (2013). The West African Sahel: A review of recent studies on the rainfall regime and its interannual variability. International Scholarly Research Notices, 2013(1), 453521. https://doi.org/10.1155/2013/453521
  20. Papalexiou, S. M., & Montanari, A. (2019). Global and regional increase of precipitation extremes under global warming. Water Resources Research, 55(6), 4901-4914. https://doi.org/10.1029/2018WR024067
  21. Pettit, A. N. (1979). A non-parametric approach to the change-point problem. Applied statistics, 28(2), 126-135.
  22. Piao, S., Ciais, P., Huang, Y., Shen, Z., Peng, S., Li, J., ... & Fang, J. (2010). The impacts of climate change on water resources and agriculture in China. Nature, 467(7311), 43-51. https://doi.org/10.1038/nature09364
  23. Ray, D. K., Gerber, J. S., MacDonald, G. K., & West, P. C. (2015). Climate variation explains a third of global crop yield variability. Nature communications, 6(1), 5989. https://doi.org/10.1038/ncomms6989
  24. Raziei, T., Arasteh, P. D., & Saghafian, B. (2005, May). Annual rainfall trend in arid and semi-arid regions of Iran. In ICID 21st European regional conference (pp. 15-19).
  25. Salameh, A. A. (2024). Using the precipitation concentration index for characterizing the rainfall distribution in the Levant. Journal of Water and Climate Change, 15(4), 1945-1960. https://doi.org/10.2166/wcc.2024.037
  26. Schneider, U., Becker, A., Finger, P., Meyer-Christoffer, A., Rudolf, B., & Ziese, M. (2016). GPCC full data reanalysis version 7.0: monthly land-surface precipitation from rain gauges built on GTS based and historic data.
  27. Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall's tau. Journal of the American statistical association, 63(324), 1379-1389.
  28. Tabari, H. (2020). Climate change impact on flood and extreme precipitation increases with water availability. Scientific reports, 10(1), 13768. https://doi.org/10.1038/s41598-020-70816-2
  29. Tahroudi, MN., Khashei Siuki, A., & Ramezani, Y. (2019). Redesigning and monitoring groundwater quality and quantity networks by using the entropy theory. Environmental monitoring and assessment, 191(4), 250.-261.
  30. Thiel, H. (1950, February). A rank-invariant method of linear and polynomial regression analysis, Part 3. In Proceedings of koninalijke nederlandse akademie van weinenschatpen a (Vol. 53, pp. 1397-1412).
  31. Walther, G. R., Post, E., Convey, P., Menzel, A., Parmesan, C., Beebee, T. J., ... & Bairlein, F. (2002). Ecological responses to recent climate change. Nature, 416(6879), 389-395. https://doi.org/10.1038/416389a
  32. Westra, S., Alexander, L. V., & Zwiers, F. W. (2013). Global increasing trends in annual maximum daily precipitation. Journal of climate, 26(11), 3904-3918. https://doi.org/10.1175/JCLI-D-12-00502.1
  33. Yatagai, A., Kamiguchi, K., Arakawa, O., Hamada, A., Yasutomi, N., & Kitoh, A. (2012). APHRODITE: Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bulletin of the American Meteorological Society, 93(9), 1401-1415. https://doi.org/10.1175/BAMS-D-11-00122.1
Water and Irrigation Management
Volume 15, Issue 4
March 2026
Pages 843-859

Files

Share

How to cite

Statistics