Arid
DOI10.1016/j.jhydrol.2010.10.025
Forecasting of rainfall using ocean-atmospheric indices with a fuzzy neural technique
Srivastava, Gaurav2; Panda, Sudhindra N.1; Mondal, Pratap1; Liu, Junguo3
通讯作者Panda, Sudhindra N.
来源期刊JOURNAL OF HYDROLOGY
ISSN0022-1694
EISSN1879-2707
出版年2010
卷号395期号:3-4页码:190-198
英文摘要

Forecasting of rainfall is imperative for miffed agriculture of and and semi-arid regions of the world where agriculture consumes nearly 80% of the total water demand Fuzzy-Ranking Algorithm (FRA) is used to identify the significant input variables for rainfall forecast A case study is carried out to forecast monthly rainfall in India with several ocean-atmospheric predictor variables Three different scenarios of ocean-atmospheric predictor variables are used as a set of possible input variables for rainfall forecasting model (1) two climate indices i e Southern Oscillation Index (SOI) and Pacific Decadal Oscillation Index (PDOI) (2) Sea Surface Temperature anomalies (SSTa) in the 5 degrees x 5 degrees grid points in Indian Ocean and (3) both the climate indices and SSTa To generate a set of possible input variables for these scenarios we use climatic indices and the SSTa data with different lags between 1 and 12 months Nonlinear relationship between identified inputs and rainfall is captured with an Artificial Neural Network (ANN) technique A new approach based on fuzzy c-mean clustering is proposed for dividing data into representative subsets for training testing and validation The results show that this proposed approach overcomes the difficulty in determining optimal numbers of clusters associated with the data division technique of self-organized map The ANN model developed with both the climate indices and SSTa shows the best performance for the forecast of the monthly August rainfall in India Similar approach can be applied to forecast rainfall of any period at selected climatic regions of the world where significant relationship exists between the rainfall and climate indices (c) 2010 Elsevier B V All rights reserved


英文关键词Artificial Neural Network Fuzzy Ranking Algorithm Sea Surface Temperature Fuzzy c mean clustering Ocean atmospheric predictor variables
类型Article
语种英语
国家India ; Peoples R China
收录类别SCI-E
WOS记录号WOS:000285856500006
WOS关键词SOUTHERN-OSCILLATION INDEX ; INDIAN MONSOON RAINFALL ; NETWORKS ; SYSTEM ; IDENTIFICATION ; PREDICTION ; EXTENSION ; PACIFIC ; EVENTS ; MODELS
WOS类目Engineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向Engineering ; Geology ; Water Resources
来源机构北京林业大学
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/165312
作者单位1.Indian Inst Technol, Sch Water Resources, Kharagpur 721302, W Bengal, India;
2.Indian Inst Technol, Dept Agr & Food Engn, Kharagpur 721302, W Bengal, India;
3.Beijing Forestry Univ, Sch Nat Conservat, Beijing 100083, Peoples R China
推荐引用方式
GB/T 7714
Srivastava, Gaurav,Panda, Sudhindra N.,Mondal, Pratap,et al. Forecasting of rainfall using ocean-atmospheric indices with a fuzzy neural technique[J]. 北京林业大学,2010,395(3-4):190-198.
APA Srivastava, Gaurav,Panda, Sudhindra N.,Mondal, Pratap,&Liu, Junguo.(2010).Forecasting of rainfall using ocean-atmospheric indices with a fuzzy neural technique.JOURNAL OF HYDROLOGY,395(3-4),190-198.
MLA Srivastava, Gaurav,et al."Forecasting of rainfall using ocean-atmospheric indices with a fuzzy neural technique".JOURNAL OF HYDROLOGY 395.3-4(2010):190-198.
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