DOI: 10.1007/s11069-020-03946-5
论文题名: Monthly precipitation assessments in association with atmospheric circulation indices by using tree-based models
作者: Sattari M.T. ; Shaker Sureh F. ; Kahya E.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 102, 期: 3 起始页码: 1077
结束页码: 1094
语种: 英语
中文关键词: Atmospheric circulations
; Iran
; M5 tree model
; Meteorological variables
; Monthly precipitation
; Random forest
英文关键词: atmospheric circulation
; hydrological modeling
; machine learning
; precipitation assessment
; rainfall
; sea surface temperature
; Iran
; Lake Urmia
英文摘要: The Urmia Lake basin is one of the most important basins in Iran, facing many problems due to poor water management and rainfall reduction. Under current circumstances, it becomes critical to have an advanced understanding of rainfall patterns in the basin, setting the motivation of this study. In this research, the mean monthly meteorological data of six synoptic stations of Urmia Lake basin were used (including relative humidity, temperature, minimum–maximum temperature and pressure) and large-scale atmospheric circulation indices (Southern Oscillation Index, North Atlantic Oscillation, Western Mediterranean Oscillation, Mediterranean Oscillation-Gibraltar/Israel and Mediterranean Oscillation-Algiers/Cairo) and sea surface temperatures of the Mediterranean, Black, Caspian, Red seas and Persian Gulf in the period 1988–2016. Various combinations of these variables used as input to the M5 tree and random forest models were selected by Relief algorithm for each month in three scenarios including atmospheric circulation indices, meteorological variables and combination of both. After the implementation of two models with three different scenarios, the evaluation criteria including correlation coefficient (R), mean absolute error and root-mean-square error were calculated and the Taylor diagram for each model was plotted. Our results showed that the M5 tree model performed superior in January, February, March, April, June, September, November and December, while the random forest model did in the remaining months. In addition, the indications of this study showed that the combination of atmospheric circulation indices and meteorological variables used as input to the models mostly constituted improved results. © 2020, Springer Nature B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168723
Appears in Collections: 气候变化与战略
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作者单位: Department of Water Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran; Department of Agricultural Engineering, Faculty of Agriculture, Ankara University, Ankara, 06110, Turkey; Hydraulics and Water Resources Division, Hydrology Civil Engineering Department, Istanbul Technical University, Istanbul, Turkey
Recommended Citation:
Sattari M.T.,Shaker Sureh F.,Kahya E.. Monthly precipitation assessments in association with atmospheric circulation indices by using tree-based models[J]. Natural Hazards,2020-01-01,102(3)