DOI: 10.1016/j.gloplacha.2016.07.013
论文题名: Projection of climate change impacts on precipitation using soft-computing techniques: A case study in Zayandeh-rud Basin, Iran
作者: Kouhestani S. ; Eslamian S.S. ; Abedi-Koupai J. ; Besalatpour A.A.
刊名: Global and Planetary Change
ISSN: 0921-8181
出版年: 2016
卷: 144 起始页码: 158
结束页码: 170
语种: 英语
英文关键词: Climate change
; Downscaling
; Supervised learning
; Supervised PCA
Scopus关键词: Artificial intelligence
; Climate models
; Learning systems
; Object oriented programming
; Soft computing
; Supervised learning
; Surface water resources
; Surface waters
; Water resources
; Climate change impact assessments
; Climate model simulations
; Coupled Model Intercomparison Project
; Down-scaling
; Relevance Vector Machine
; Statistical transformation
; Supervised PCA
; Support vector regression (SVR)
; Climate change
英文摘要: Due to the complexity of climate-related processes, accurate projection of the future behavior of hydro-climate variables is one of the main challenges in climate change impact assessment studies. In regression-based statistical downscaling processes, there are different sources of uncertainty arising from high-dimensionality of atmospheric predictors, nonlinearity of empirical and quantitative models, and the biases exist in climate model simulations. To reduce the influence of these sources of uncertainty, the current study presents a comprehensive methodology to improve projection of precipitation in the Zayandeh-Rud basin in Iran as an illustrative study. To reduce dimensionality of atmospheric predictors and capture nonlinearity between the target variable and predictors in each station, a supervised-PCA method is combined with two soft-computing machine-learning methods, Support Vector Regression (SVR) and Relevance Vector Machine (RVM). Three statistical transformation methods are also employed to correct biases in atmospheric large-scale predictors. The developed models are then employed on outputs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) multimodal dataset to project future behavior of precipitation under three climate changes scenarios. The results indicate reduction of precipitation in the majority of the sites in this basin threatening the availability of surface water resources in future decades. © 2016 Elsevier B.V. URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979917150&doi=10.1016%2fj.gloplacha.2016.07.013&partnerID=40&md5=77c412de06a1aec1917df48c69ec8104
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/11640
Appears in Collections: 全球变化的国际研究计划 气候变化与战略
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作者单位: Department of Water Engineering, College of Agriculture, Isfahan University of Technology, Isfahan, Iran
Recommended Citation:
Kouhestani S.,Eslamian S.S.,Abedi-Koupai J.,et al. Projection of climate change impacts on precipitation using soft-computing techniques: A case study in Zayandeh-rud Basin, Iran[J]. Global and Planetary Change,2016-01-01,144.