Spatiotemporal variability of trend in extreme precipitations using fuzzy clustering over Northwest Iran

Autor: Shahnaz Rashedi, Farahnaz Khoramabadi, Ahmad Reza Ghasemi, Marziyeh Esmaeilpour
Rok vydání: 2021
Předmět:
Zdroj: Earth Science Informatics. 14:2123-2132
ISSN: 1865-0481
1865-0473
DOI: 10.1007/s12145-021-00680-9
Popis: In recent decades, global warming has triggered precipitation extremes. Extreme Precipitations have many negative consequences on agriculture productions, water resources and ecosystems on the earth and cause several hydro-meteorological disasters. This research was conducted to analyze the spatiotemporal variability in nine extreme precipitation indices over a 30-year period (1987–2016) at identified clusters in Northwest Iran. The Mann Kendal test, Sen's slope estimator and fuzzy c-mean clustering were applied for this purpose. The findings showed that the spatial variation of most extreme precipitation indices (except wet dry days, CWD) is decreasing from the southwest to the north of the study area. The fuzzy c-mean clustering technique identified 2 and 5 categories with similar extreme precipitation indices. In the next step, the trends and Sen's slope estimator were calculated in the clusters. The results of MK test in a regional scale showed both downward and upward trend in all studied extreme precipitation indices. However, most of them were insignificant. Only two indices including annual wet day precipitation (PRCPTOT) and the Simple Daily Intensity Index showed significant negative and positive trend over the Northwest Iran, respectively.
Databáze: OpenAIRE
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