Effect of Global Warming on Intensity and Frequency Curves of Precipitation, Case Study of Northwestern Iran

Gholamreza Roshan (), AbdolAzim Ghanghermeh (), Touraj Nasrabadi () and Jafar Meimandi ()

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2013, vol. 27, issue 5, 1563-1579

Abstract: Predicting natural phenomena like flood and drought and consequently presenting an appropriate solution for fighting such natural hazards in northwestern Iran is considered in this study through clustering the precipitation regime. To compare the reference period (past) with the simulated data, the statistics of daily precipitation in six stations of Ardebil, Ghazvin, Hamedan, Kermanshah, Sanandaj, and Tabriz, have been provided for a 30-year period (1961–1990) and compared with the simulated data of 2021–2050. The simulated data was generated by general atmosphere circulation model HADCM3, A1scenario and was downscaled using the LARS-WG model. The method for comparing precipitations was done based on clustering in the form of 5 clusters for all the stations and study periods. One of the results of this research is the greater concentration of precipitation for the cold periods of the year (winter and fall) and the increase of annual precipitation by the amount of 20.62 mm for future period. Furthermore, the normality of two coordinates of precipitation and cluster frequency percentage was evaluated. The outputs of this section demonstrate that the precipitations of cluster 3 which have the features of light rain with average intensity, fall on this normal line for most of the stations and study periods. On the other hand, precipitations of cluster 1 indicating very heavy and intense precipitations, have the most distance to the normal line in most cases. Therefore, the precipitations of the third cluster need optimal exploitation management while those of the first cluster need required risk and crisis management. Copyright Springer Science+Business Media Dordrecht 2013

Keywords: Climatic change; Clustering; Downscaling; Scenario (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s11269-013-0258-7

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