Evaluating and Zoning of the Extreme Rainfalls Occurrence Risk in West of Iran

Document Type : Complete scientific research article

Authors

1 M.Sc Graduated student of Climatology, Climatology Department, Faculty of Natural Resources, University of Kurdistan, Ira

2 Water science and Engineering, University of Kurdistan

3 Assistant Professor, Climatology Department, Faculty of Natural Resources, University of Kurdistan, Iran

Abstract

Background and Objectives: Occurrence of extreme rainfalls specifically in short-time scales causes heavy damages to human communities, municipal crowd regions and natural ecosystems. Studying and precise identifying of extreme rainfalls is essential and crucial in different agriculture and natural resources, meteorology and hydrology, engineering and natural environment aspects. The damage intensity of extreme rainfalls does not equally act in different regions and it is essential to assess the risk extent of such hazardeous rainfalls in regions with different climatic conditions. Therefore, the aim of this study is to identify and zoning of extreme rainfall occurrence risk in different 6, 12 and 24-hour time scales for West parts of Iran, which has a noticeable diversity in terms of the climatic and topographic conditions.
Materials and Methods: to perform this research, a number of 27 synoptic stations located in five provinces including Kurdistan, Kermanshah, Hamedan, Ilam and Lorestan were selected and the maximum annual values of extreme rainfalls in three time scales of 6, 12 and 24-hours in a 25 year time period (1992-2016) were extracted and by fitting different statistically distributions to each of these time series and by adopting the Chi-square test, the statistical distributions with best fit were regoized and were used to performing propabilitistic analyses. The 30, 40 and 50 mm thresholds were used to defining the torrential extreme rainfalls in 6, 12 and 24-hours time scales, respectively and after calculating the risk extents of the mentioned torrential extreme rainfalls for all of the studied stations, the risk zoning of torrential extreme rainfalls occurrence was performed by applying the multiple linear regression models between the risk extents and geographical properties (longitude, latitude and elevation) for all of the studied region. To enhancing the models accuracy, the long-term average of the number of days per year with precipitation greater than 1 mm was employed in the structure of the regression models as auxiliary variable in some cases and to achieve higher accuracy of regression models, the studied region was divided into three distinct regions.

Results: The results showed that among different fitted statistical distributions to the time series of extreme rainfalls of 6, 12 and 24-hours in the studied region, three distributions including Log-Logistic, Pearson and Gama were recognized as the best fit distributions. In terms of the accuracy of the multiple linear regression models, the results showed the high accuracy of these models for all of the three distinct regions and whole of three time scales of 6, 12 and 24-hours. The overall results of this research showed that the risk occurrence of the torrential extreme rainfalls in West of Iran has a notable diversity so that this risk is very low in some centarl parts and very high in some west and south parts of the studied region.
Conclusion: The overall results of this research revealed that the general applied algorithm of this research to estimating spatial distribution of torrential extreme rainfalls ocuurence risk was led to obtaining the appropriate and acceptable accuracy in regional estimating and generalizing the stational point results to the regional scale. Therefore, it is essential to adopt appropriate tasks and more attention in contrast to the negative consequences of the extreme rainfalls in the parts with higher degree of risk occurence.

Keywords


1.Alijani, B., Brien, J., and Yarnal, B. 2008. Spatial analysis of precipitation intensityand concentration in Iran. Theor. Appl.Climatol. 94: 1. 107-124.
2.Anagnostopouloul, Ch., and Tolika, K.2011. Extremeprecipitation in Europe:statistical threshold selection based onclimatological criteria, J. Theor. Appl.Climatol. 15: 479-489.
3.Azhdary Moghaddam, M., and Heravi, Z.2018. Evaluation of IDF curve productionmethods by relationship based on nature ofcombination of fractal of precipitation. J.Water Soil Cons. 24: 6. 271-282. (In Persian)
4.Below, R., Wirtz, A., and Sapir, D.2009. Disaster Category Classificationand Peril Terminology for Operational -Kanchebe, D.E. and Abudu, K.R. 2012.Vulnerability of crop production to heavy
precipitation in north- eastern Ghana. Int.J. Clim. Chang. Str. Manag. 4: 1. 36-53.
5.Borzoi, F., and Azizi, Gh. 2015.Suggesting a Simple Criterion to EstimateHeavy Rainfall in Iran. NaturalGeographic Researches. 47: 3. 347-365.(In Persian)
6.Darand, M. 2015. Recognition ofhomogeneous regions of heavy and superheavy precipitation in Iran by intergroupvariance quality control indices. J. Agric.Meteorol. 3: 1. 40-57. (In Persian)
7.IPCC. 2007. Climate Change. 2007.The Physical Science Basis, AContribution of Working Groups. I, to theForth Assessment Report of theIntergovernmental Panel on ClimateChange, Solomon and the Core WritingTeam (eds). Cambridge Universitypress. Cambridge United Kingdom andNew York, USA. 333p.
8.Kanchebe, D.E., and Abudu, K.R. 2012.Vulnerability of crop production to heavyprecipitation in north- eastern Ghana. Int.J. Clim. Chang. Str. Manag. 4: 1. 36-53.
9.Karamooz, M., and Araghinezhad, Sh.2005. Advanced Hydrology. AmirkabirUniversity Press. 468p. (In Persian)
10.Khalili, A. 2015. Quantifying the risk ofheavy rainfall and its damage toagriculture in Iran. J. Agric. Meteorol.3: 2. 24-33. (In Persian)
11.Khoshkhoo, Y., and Abdi, Ch.2016. Risk potential of heavy rainfalloccurrence at some selected stations atWest and Northwest of Iran. 2st NationalConference on Semi-Arid Hydrology.
19-20 October. Sanandaj. Iran. (In Persian)
12.Matinzadeh, M., Fattahi, R.Shayannejad, M., and Abdollahi, Kh.2011. Reconstruction of Annual
Maximum 24-h Rainfall Data usingFuzzy Regression in CH&B Province.Journal of Water Research of Iran.8: 179-186. (In Persian)
13.Mozafari, Gh.A., Mazidi, A., and Shafie,Sh. 2017. Analysis and determining thethreshold of extreme precipitation ofWestern Iran through using generalextreme value distribution. J. Water SoilCons. 24: 2. 107-25. (In Persian)
14.Nazari Samani, A.A., Abbasi Jondani, Sh.2016. Evaluation of efficiency of CligenGenerator for producing of climate datafor using in WEPP model (Case study:Zidasht station, Alborz province). J. WaterSoil Cons. 23: 2. 43-62. (In Persian)
15.Skakun, S., Kussul, N., Shelestov, A.and Kussul, O. 2014. Flood hazard andflood risk assessment using a time seriesof satellite images: a case study inNamibia. Risk Anal. 34: 8. 1521-1537.
16.Sotoodeh, F., and Alijani, B. 2015.Relationship between spatial distributionof heavy precipition and pressurepatterns in Gilan. J. Spatial Anal. Natur.Hazard. 1: 63-73. (In Persian)
17.Vörösmarty, C.J., Guenni, L.B.,Wollheim, W.M., Pellerin, B., Bjerklie,D., Cardoso, M., D'Almeida, C., Green,P., and Colon, L. 2013. Extreme rainfall,vulnerability and risk: a continentalscale assessment for South America.Philos. Trans. A Math. Phys. Eng. Sci.371: 1-17.
18.WMO. 2016. Commission forclimatology: open programmme panelon climate monitoring and assessment(opace-2). Task team on definitions ofextreme weather and climate events(tt-dewce). Report item: 3.3 (3). 61.