Identifying drought- and flood-prone areas based on significant changes in daily precipitation over Iran

Mohammad Darand () and Mohammad M. Sohrabi
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Mohammad Darand: University of Kurdistan
Mohammad M. Sohrabi: University of California

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 90, issue 3, No 18, 1427-1446

Abstract: Abstract Variations in frequency and intensity of extreme events have substantial impact on water resources and environment, which in turn are reflected on agriculture, society, and economy. We assessed spatiotemporal changes in pattern of daily precipitation to identify drought- and flood-prone areas of Iran. To do this, we generated gridded daily precipitation for the period of 1962–2013 over Iran using measured daily precipitation and the Kriging approach. We applied 11 precipitation indices that were stated by the Expert Team on Climate Change Detection and Indices (ETCCDI) to identify significant changes in frequency and intensity of extreme precipitation events. According to significant changes of these 11 precipitation indices, drought- and flood-prone areas of Iran were, then, detected. We observed significant changes in pattern of daily precipitation over more than half of the country. 40% of the country, which were located in the elevated regions of Iran, particularly along Zagros Mountain, was identified as flood-prone areas. As a result, in these regions, there is a need for flood risk management based on changes in stormwater events such as runoff generated from rain on snow and snowmelt events. In addition, we detected drought-prone areas in large portion of the northwest of Iran and in the low elevated regions of the country that have semiarid or arid climate. This suggests that it is necessary to prepare a long-term drought plan to mitigate impacts of severe drought events.

Keywords: Extreme precipitation events; Flood-prone areas; Drought-prone areas; Mann–Kendall test; Iran; ETCCDI (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11069-017-3107-9

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