Flood Seasonality Analysis in Iran: A Circular Statistics Approach
Publication: Journal of Hydrologic Engineering
Volume 28, Issue 2
Abstract
Flood seasonality (FS) analysis is a key to delineating hydrologically homogenous regions and better understanding flood risk, especially for arid regions. Although Iran has undergone heavy floods in current decades, a quantitative spatially distributed overview of the flood seasonality and the its affected mechanisms is currently unavailable. This study aimed in seasonality analysis of annual maximum flood with average recurrence of 2 to 500 years in 291 continuous hydrometric stations across Iran having sufficient recorded flood data (, total of 9,565 events) using a circular statistics approach. Moreover, the relationships of recurrence season of floods with eight natural and human-induced factors including catchment area, catchment perimeter, mean catchment slope, normalized difference vegetation index (NDVI), elevation of station, mean slope of river, and latitude were examined. Findings showed that flooding in Iran presents strong seasonality, with 32% and 41% of the total events occurring during winter and spring, and mostly during April (24%). Although summer floods () are more frequent in the northern parts, winter floods present higher percentages in the south. A significant difference in flood seasonality (2 to 500 years) was identified between the northern and southeastern regions. This study suggests that the geographical location (especially latitude) of the hydrometric station in Iran seems to be more significant than other considered factors in shaping flood seasonality. Results can serve as a foundation for enhancing the scientific understanding of the flood seasonality across Iran, which can provide useful insights for flood prevention planning and future changes projected by models.
Practical Applications
Flooding is one of most damaging phenomena around the globe that affect humans’ life and economy. So, in order to decrease the dire consequences of flooding, especially in arid zones like Iran, we should increase our knowledge about flood risk by using advanced techniques like flood seasonality analysis. This research is a specific survey at a nationwide scale for enhancing the scientific understanding of the flood timing across Iran, which can provide useful insights for future planning and practical engineering designs. The purpose of this research is the study of seasonality analysis of annual maximum flood in 291 continuous hydrometric stations across Iran with a total of 9,565 events using a circular statistics approach. Owing to the prominent role of humanity and nature on flooding, eight natural and human-induced factors have been surveyed. The results of this study illustrated that 32% and 41% of the total events occurred during winter and spring, mostly during April (24%). What is further noticeable is that a significant difference in flood seasonality was identified between the northern and southeastern regions. Among considered factors in shaping seasonality of flooding, the geographical location (especially latitude) of the hydrometric station in Iran seems to be more significant than other factors.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
All initial data or MATLAB codes generated or used during the study are available from the corresponding author by request.
Acknowledgments
The authors wish to thank Iran’s Water Resources Management Company and Iran’s Meteorological Organization for providing the requested data. The authors would like to thank Sarem Norouzi for generously dedicating his valuable time to help for preparing the MATLAB codes required for statistical analysis.
References
Alijani, B. 2000. Iran climatology, 250. Tehran, Iran: Payam Nour Publication.
Arheimer, B., and G. Lindström. 2015. “Climate impact on floods: Changes in high flows in Sweden in the past and the future (1911–2100).” Hydrol. Earth Syst. Sci. 19 (2): 771–784. https://doi.org/10.5194/hess-19-771-2015.
Baratti, E., A. Montanari, A. Castellarin, J. L. Salinas, A. Viglione, and A. Bezzi. 2012. “Estimating the flood frequency distribution at seasonal and annual time scales.” Hydrol. Earth Syst. Sci. 16 (12): 4651–4660. https://doi.org/10.5194/hess-16-4651-2012.
Beedel, R., and S. A. Masoodian. 2014. “Recognition of Iran air masses by spatial synoptic classification: Geography and development.” Iran. J. 12 (35): 1–18.
Berghuijs, W. R., S. Harrigan, P. Molnar, L. J. Slater, and J. W. Kirchner. 2019. “The relative importance of different flood-generating mechanisms across Europe.” Water Resour. Res. 55 (6): 4582–4593. https://doi.org/10.1029/2019WR024841.
Beven, K. 2014. “A framework for uncertainty analysis.” In Applied uncertainty analysis for flood risk management, 39–59. London: Imperial College Press.
Bezak, N., M. Brilly, and M. Šraj. 2014. “Comparison between the peaks-over-threshold method and the annual maximum method for flood frequency analysis.” Hydrol. Sci. J. 59 (5): 959–977. https://doi.org/10.1080/02626667.2013.831174.
Black, A. R. 1995. “Flood seasonality and physical controls in flood risk estimation.” Scott. Geog. Mag. 111 (3): 187–190. https://doi.org/10.1080/00369229518736965.
Black, A. R., and A. Werritty. 1997. “Seasonality of flooding: A case study of north Britain.” J. Hydrol. 195 (1–4): 1–25. https://doi.org/10.1016/S0022-1694(96)03264-7.
Blöschl, G., et al. 2017. “Changing climate shifts timing of European floods.” Science 357 (6351): 588–590. https://doi.org/10.1126/science.aan2506.
Bomers, A., R. M. Schielen, and S. J. Hulscher. 2019. “Decreasing uncertainty in flood frequency analyses by including historic flood events in an efficient bootstrap approach.” Nat. Hazards Earth Syst. Sci. 19 (8): 1895–1908. https://doi.org/10.5194/nhess-19-1895-2019.
Braden, C. D. 2011. “Analysis of weather station data and impacts of SPAW based designs of dairy Lagoons in New Mexico.” In Proc., 2011 Louisville, 1. Louisville, KY: American Society of Agricultural and Biological Engineers.
Burn, D. H. 1997. “Catchment similarity for regional flood frequency analysis using seasonality measures.” J. Hydrol. 202 (1–4): 212–230. https://doi.org/10.1016/S0022-1694(97)00068-1.
Cassalho, F., S. Beskow, C. Rogério de Mello, L. F. Oliveira, and M. Sanchotene de Aguiar. 2019. “Evaluation of flood timing and regularity over hydrological regionalization in southern Brazil.” J. Hydrol. Eng. 24 (8): 05019022. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001815.
Chen, L., V. P. Singh, S. Guo, B. Fang, and P. Liu. 2013. “A new method for identification of flood seasons using directional statistics.” Hydrol. Sci. J. 58 (1): 28–40. https://doi.org/10.1080/02626667.2012.743661.
Collins, M. J. 2019. “River flood seasonality in the Northeast United States: Characterization and trends.” Hydrol. Processes 33 (5): 687–698. https://doi.org/10.1002/hyp.13355.
Cunderlik, J. M., T. B. M. J. Ouarda, and B. Bobée. 2004. “On the objective identification of flood seasons.” Water Resour. Res. 40 (1): W01520. https://doi.org/10.1029/2003WR002295.
Dash, P., and J. Sar. 2020. “Identification and validation of potential flood hazard area using GIS-based multi-criteria analysis and satellite data-derived water index.” J. Flood Risk Manage. 13 (3): e12620. https://doi.org/10.1111/jfr3.12620.
Devlin, A. T., J. Pan, and H. Lin. 2021. “Extended water level trends at long-record tide gauges via moving window averaging and implications for future coastal flooding.” J. Geophys. Res. Oceans 126 (10): e2021JC017730. https://doi.org/10.1029/2021JC017730.
Dhakal, N., and R. N. Palmer. 2020. “Changing river flood timing in the Northeastern and upper Midwest United States: Weakening of seasonality over time?” Water 12 (7): 1951. https://doi.org/10.3390/w12071951.
Diakakis, M. 2014. “An inventory of flood events in Athens, Greece, during the last 130 years. Seasonality and spatial distribution.” J. Flood Risk Manage. 7 (4): 332–343. https://doi.org/10.1111/jfr3.12053.
Diakakis, M. 2017. “Flood seasonality in Greece and its comparison to seasonal distribution of flooding in selected areas across southern Europe.” J. Flood Risk Manage. 10 (1): 30–41. https://doi.org/10.1111/jfr3.12139.
Dickinson, J. E., T. M. Harden, and G. J. McCabe. 2019. “Seasonality of climatic drivers of flood variability in the conterminous United States.” Sci. Rep. 9 (1): 1–10. https://doi.org/10.1038/s41598-019-51722-8.
Farhadian, M., O. Bozorg-Haddad, and H. A. Loáiciga. 2021. “Fulfillment of river environmental flow: Applying Nash theory for quantitative-qualitative conflict resolution in reservoir operation.” Water Environ. J. 35 (2): 486–499. https://doi.org/10.1111/wej.12645.
Fattahi, E., and K. Noohi. 2008. “Monitoring the occurrence of frost through an analysis of air masses in south west basins of Iran.” Desert 13 (2): 137–146. https://doi.org/10.22059/JDESERT.2008.36297.
Fustos, I., R. Abarca-del-Rio, A. Ávila, and R. Orrego. 2017. “A simple logistic model to understand the occurrence of flood events into the Biobío River Basin in central Chile.” J. Flood Risk Manage. 10 (1): 17–29. https://doi.org/10.1111/jfr3.12131.
Gai, L., J. E. M. Baartman, M. Mendoza-Carranza, F. Wang, C. J. Ritsema, and V. Geissen. 2018. “A framework approach for unravelling the impact of multiple factors influencing flooding.” J. Flood Risk Manage. 11 (2): 111–126. https://doi.org/10.1111/jfr3.12310.
Geravand, F., S. M. Hosseini, and B. Ataie-Ashtiani. 2020. “Influence of river cross-section data resolution on flood inundation modeling: Case study of Kashkan River Basin in western Iran.” J. Hydrol. 584 (May): 124743. https://doi.org/10.1016/j.jhydrol.2020.124743.
Golian, M., H. Katibeh, Z. Najafi, H. Saadat, A. Saffarzadeh, A. Ahmadi, M. Khazaei, and E. Sametzadeh. 2021. “Large-scale replenishment of groundwater depletion by long-lived extreme rainstorms in arid regions: Case study of the 2019 floods in Iran.” Hydrogeol. J. 29 (6): 2171–2186. https://doi.org/10.1007/s10040-021-02370-8.
Guo, E., J. Zhang, X. Ren, Q. Zhang, and Z. Sun. 2014. “Integrated risk assessment of flood disaster based on improved set pair analysis and the variable fuzzy set theory in central Liaoning Province, China.” Nat. Hazards 74 (2): 947–965. https://doi.org/10.1007/s11069-014-1238-9.
Haghizadeh, A., S. Siahkamari, A. H. Haghiabi, and O. Rahmati. 2017. “Forecasting flood-prone areas using Shannon’s entropy model.” J. Earth Syst. Sci. 126 (3): 1–11. https://doi.org/10.1007/s12040-017-0819-x.
Hajian, F., A. P. Dykes, and S. Cavanagh. 2019. “Assessment of the flood hazard arising from land use change in a forested catchment in northern Iran.” J. Flood Risk Manage. 12 (4): e12481. https://doi.org/10.1111/jfr3.12481.
Haktanir, T., and H. B. Horlacher. 1993. “Evaluation of various distributions for flood frequency analysis.” Hydrol. Sci. J. 38 (1): 15–32. https://doi.org/10.1080/02626669309492637.
Hall, J., and G. Blöschl. 2018. “Spatial patterns and characteristics of flood seasonality in Europe.” Hydrol. Earth Syst. Sci. 22 (7): 3883–3901. https://doi.org/10.5194/hess-22-3883-2018.
Hawkes, P. J. 2008. “Joint probability analysis for estimation of extremes.” Supplement, J. Hydraul. Res. 46 (S2): 246–256. https://doi.org/10.1080/00221686.2008.9521958.
Heydarizad, M., E. Raeisi, R. Sori, L. Gimeno, and R. Nieto. 2018. “The role of moisture sources and climatic teleconnections in northeastern and south-central Iran’s hydro-climatology.” Water 10 (11): 1550. https://doi.org/10.3390/w10111550.
Heydarizad, M., E. Raeisi, R. Sorí, and L. Gimeno. 2019. “Developing meteoric water lines for Iran based on air masses and moisture sources.” Water 11 (11): 2359. https://doi.org/10.3390/w11112359.
IPCC (Intergovernmental Panel on Climate Change). 2012. Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge, MA: Cambridge University Press.
Khalili, K., M. N. Tahoudi, R. Mirabbasi, and F. Ahmadi. 2016. “Investigation of spatial and temporal variability of precipitation in Iran over the last half century.” Stochastic Environ. Res. Risk Assess. 30 (4): 1205–1221. https://doi.org/10.1007/s00477-015-1095-4.
Khojeh, S., B. Ataie-Ashtiani, and S. M. Hosseini. 2022. “Effect of DEM resolution in flood modeling: A case study of Gorganrood River, northeastern Iran.” Nat. Hazards 112 (1): 1–21. https://doi.org/10.1007/s11069-022-05283-1.
Kousky, C., and M. Walls. 2014. “Floodplain conservation as a flood mitigation strategy: Examining costs and benefits.” Ecol. Econ. 104 (Aug): 119–128. https://doi.org/10.1016/j.ecolecon.2014.05.001.
Li, J., M. Thyer, M. Lambert, G. Kuzera, and A. Metcalfe. 2016. “Incorporating seasonality into event-based joint probability methods for predicting flood frequency: A hybrid causative event approach.” J. Hydrol. 533 (Feb): 40–52. https://doi.org/10.1016/j.jhydrol.2015.11.038.
Macdonald, N., I. D. Phillips, and G. Mayle. 2010. “Spatial and temporal variability of flood seasonality in Wales.” Hydrol. Processes 24 (13): 1806–1820. https://doi.org/10.1002/hyp.7618.
Magilligan, F. J., and B. E. Graber. 1996. “Hydroclimatological and geomorphic controls on the timing and spatial variability of floods in New England, USA.” J. Hydrol. 178 (1–4): 159–180. https://doi.org/10.1016/0022-1694(95)02807-2.
Mardia, K. V. 1975. “Statistics of directional data.” J. R. Stat. Soc.: Ser. B (Methodol.) 37 (3): 349–371. https://doi.org/10.1111/j.2517-6161.1975.tb01550.x.
Masina, M., A. Lamberti, and R. Archetti. 2015. “Coastal flooding: A copula based approach for estimating the joint probability of water levels and waves.” Coastal Eng. 97 (Mar): 37–52. https://doi.org/10.1016/j.coastaleng.2014.12.010.
Masoodian, A. 2005. “Identification of Iran’s rainfall regime by cluster analysis.” Geog. Res. Iran. J. 37 (52): 47–59.
Masoudian, A., and H. Ataei. 2005. “Identification of rainfall seasons in Iran by cluster analysis.” J. Humanities Res. Univ. Isfahan (18): 1–12.
Mitosek, H. T., W. G. Strupczewski, and V. P. Singh. 2006. “Three procedures for selection of annual flood peak distribution.” J. Hydrol. 323 (1–4): 57–73. https://doi.org/10.1016/j.jhydrol.2005.08.016.
Mohammadzadeh, H., and B. Delkhahi. 2016. “Determining the origin of raining air masses in Iran and the Middle East countries using isotopic composition (18O and 2H) of precipitations.” In Proc., JESIUM 2016. Ghent, Belgium: Environmental Science & Technology.
Nyikadzino, B., M. Chitakira, and S. Muchuru. 2020. “Rainfall and runoff trend analysis in the Limpopo river basin using the Mann Kendall statistic.” Phys. Chem. Earth Parts A/B/C 117 (Jun): 102870. https://doi.org/10.1016/j.pce.2020.102870.
Panahi, M., et al. 2022. “Large-scale dynamic flood monitoring in an arid-zone floodplain using SAR data and hybrid machine-learning models.” J. Hydrol. 611 (1): 128001. https://doi.org/10.1016/j.jhydrol.2022.128001.
Papaioannou, G., L. Vasiliades, and A. Loukas. 2015. “Multi-criteria analysis framework for potential flood prone areas mapping.” Water Resour. Manage. 29 (2): 399–418. https://doi.org/10.1007/s11269-014-0817-6.
Paprotny, D., A. Sebastian, O. Morales-Nápoles, and S. N. Jonkman. 2018. “Trends in flood losses in Europe over the past 150 years.” Nat. Commun. 9 (1): 1–12. https://doi.org/10.1038/s41467-018-04253-1.
Parizi, E., M. Bagheri-Gavkosh, S. M. Hosseini, and F. Geravand. 2021. “Linkage of geographically weighted regression with spatial cluster analyses for regionalization of flood peak discharges drivers: Case studies across Iran.” J. Cleaner Prod. 310 (Mar): 127526. https://doi.org/10.1016/j.jclepro.2021.127526.
Raziei, T. 2018. “A precipitation regionalization and regime for Iran based on multivariate analysis.” Theor. Appl. Climatol. 131 (3): 1429–1448. https://doi.org/10.1007/s00704-017-2065-1.
Rigge, M., C. Homer, B. Wylie, Y. Gu, H. Shi, G. Xian, D. K. Meyer, and B. Bunde. 2019. “Using remote sensing to quantify ecosystem site potential community structure and deviation in the Great Basin, United States.” Ecol. Indic. 96 (Jan): 516–531. https://doi.org/10.1016/j.ecolind.2018.09.037.
Rottler, E., A. Bronstert, G. Bürger, and O. Rakovec. 2021. “Projected changes in Rhine River flood seasonality under global warming.” Hydrol. Earth Syst. Sci. 25 (5): 2353–2371. https://doi.org/10.5194/hess-25-2353-2021.
Rutkowska, A., S. Kohnová, and K. Banasik. 2018. “Probabilistic properties of the date of maximum river flow, an approach based on circular statistics in lowland, highland and mountainous catchment.” Acta Geophys. 66 (4): 755–768. https://doi.org/10.1007/s11600-018-0139-9.
Sarhadi, A., and R. Modarres. 2011. “Flood seasonality-based regionalization methods: A data-based comparison.” Hydrol. Processes 25 (23): 3613–3624. https://doi.org/10.1002/hyp.8088.
Slater, L. J., and G. Villarini. 2016. “Recent trends in US flood risk.” Geophys. Res. Lett. 43 (24): 12–428. https://doi.org/10.1002/2016GL071199.
UNISDR (United Nations Office for Disaster Risk Reduction). 2015. “Making development sustainable: The future of disaster risk management. Global assessment report on disaster risk reduction.” Accessed March 29, 2022. https://www.unisdr.org/we/inform/publications/42809.
Villarini, G. 2016. “On the seasonality of flooding across the continental United States.” Adv. Water Resour. 87 (Jan): 80–91. https://doi.org/10.1016/j.advwatres.2015.11.009.
Wang, C. 2016. “A joint probability approach for coincidental flood frequency analysis at ungauged basin confluences.” Nat. Hazards 82 (3): 1727–1741. https://doi.org/10.1007/s11069-016-2265-5.
Ye, S., H. Y. Li, L. R. Leung, J. Guo, Q. Ran, Y. Demissie, and M. Sivapalan. 2017. “Understanding flood seasonality and its temporal shifts within the contiguous United States.” J. Hydrometeorol. 18 (7): 1997–2009. https://doi.org/10.1175/JHM-D-16-0207.1.
Yuan, J., K. Emura, C. Farnham, and M. A. Alam. 2018. “Frequency analysis of annual maximum hourly precipitation and determination of best fit probability distribution for regions in Japan.” Urban Clim. 24 (Jun): 276–286. https://doi.org/10.1016/j.uclim.2017.07.008.
Yue, S., T. B. Ouarda, B. Bobée, P. Legendre, and P. Bruneau. 1999. “The Gumbel mixed model for flood frequency analysis.” J. Hydrol. 226 (1–2): 88–100. https://doi.org/10.1016/S0022-1694(99)00168-7.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 28 • Issue 2 • February 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Mar 23, 2022
Accepted: Sep 28, 2022
Published online: Nov 28, 2022
Published in print: Feb 1, 2023
Discussion open until: Apr 28, 2023
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.