Future extreme rainfall change projections in the north of Iran

Meteorological applications

article

Reza Modarres¹  Mohammad Ghadami¹  Sohrab Naderi¹  Mohammad Naderi¹ 

[1] Department of Natural Resources, Isfahan University of Technology

关键词: climate change;    extreme rainfall;    artificial neural network;    downscaling;    GEV distribution;    Iran;   

DOI  :  10.1002/met.1667

学科分类：社会科学、人文和艺术（综合）

来源: Wiley

【 摘 要 】

Future changes in extreme rainfall arising from climate change may have a significant influence on flood and water erosion control and management strategies to a great extent. The maximum daily rainfall time series were projected for 2020–2049 using six general climate models and two scenarios through artificial neural networks for 22 stations across the north of Iran. The results indicate a reduction of between −3.0 and −0.2% in maximum rainfall for the selected stations and five out of six of the general climate models. The changes in the frequency and magnitude of extreme rainfall were then investigated by fitting a generalized extreme value distribution to the historical (from 1981 to 2010) and projected maximum rainfall. The location parameter of the generalized extreme value distribution fitted to the projected maximum rainfall does not show a significant change while the scale and shape parameters exhibit significant changes compared to the historical period. Estimating the 2, 50 and 100 year return periods showed that the maximum rainfall will have a reduction in the probability of large amounts across the region compared with the base period while the number of extraordinary extreme events may show growth. As a region vulnerable to flash floods and water erosion due to rainfall characteristics and land use change from forest to agriculture, the results may send an alarm to define long term and effective strategies for future flood control management in the region.

【 授权许可】

CC BY|CC BY-NC|CC BY-NC-ND