气候变化领域集成服务门户(CCPortal): Exploring the multiscale changeability of precipitation using the entropy concept and self-organizing maps

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DOI	10.2166/wcc.2019.097
	Exploring the multiscale changeability of precipitation using the entropy concept and self-organizing maps
	Roushangar K.; Alizadeh F.; Adamowski J.; Saghebian S.M.
发表日期	2020
ISSN	20402244
起始页码	655
结束页码	676
卷号	11 期号:3
英文摘要	This study utilized a spatio-temporal framework to assess the dispersion and uncertainty of precipitation in Iran. Thirty-one rain gauges with data from 1960 to 2010 were selected in order to apply the entropy concept and study spatio-temporal variability of precipitation. The variability of monthly, seasonal and annual precipitation series was studied using the marginal disorder index (MDI). To investigate the intra-annual and decadal distribution of monthly and annual precipitation values, the apportionment disorder index (ADI) and decadal ADI (DADI) were applied to the time series. The continuous wavelet transform was used to decompose the ADI time series into time-frequency domains. The decomposition of the ADI series into different zones helped to identify the dominant modes of variability and the variation of those modes over time. The results revealed the high disorderliness in the amount of precipitation for different temporal scales based on disorder indices. Based on the DI outcome for all rain gauges, a self-organizing map (SOM) was trained to find the optimum number of clusters (seven) of rain gauges. It was observed from the clustering that there was hydrologic similarity in the clusters apart from the geographic neighborhood. © IWA Publishing 2020.
英文关键词	Disorder index (DI); Entropy; Iran; Precipitation; Self-organizing map
语种	英语
scopus关键词	Conformal mapping; Entropy; Rain gages; Self organizing maps; Time series; Uncertainty analysis; Wavelet transforms; Annual precipitation; Continuous Wavelet Transform; Entropy concept; Hydrologic similarity; Spatio temporal; Spatiotemporal variability; Temporal scale; Time frequency domain; Rain; dispersion; entropy; machine learning; precipitation (climatology); raingauge; spatial variation; temporal variation; time series analysis; uncertainty analysis; wavelet; Iran
来源期刊	Journal of Water and Climate Change
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/147923
作者单位	Department of Water Resources Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran; Department of Bioresource Engineering, McGill University, 21 111 Lakeshore Road, Ste. Anne de Bellevue, QC H9X 3V9, Canada; Department of Civil Engineering, Ahar Branch, Islamic Azad University, Ahar, Iran
推荐引用方式 GB/T 7714	Roushangar K.,Alizadeh F.,Adamowski J.,et al. Exploring the multiscale changeability of precipitation using the entropy concept and self-organizing maps[J],2020,11(3).
APA	Roushangar K.,Alizadeh F.,Adamowski J.,&Saghebian S.M..(2020).Exploring the multiscale changeability of precipitation using the entropy concept and self-organizing maps.Journal of Water and Climate Change,11(3).
MLA	Roushangar K.,et al."Exploring the multiscale changeability of precipitation using the entropy concept and self-organizing maps".Journal of Water and Climate Change 11.3(2020).