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Can the Drought/Flood Monsoon Conditions over the Indian subcontinent be forecasted using Artificial Neural Networks?

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Title Can the Drought/Flood Monsoon Conditions over the Indian subcontinent be forecasted using Artificial Neural Networks?
 
Creator Pai, Maya L.
Pramod, K. V.
Balchand, A. N.
Kumar, M. R. Ramesh
 
Subject Hydrological Zones
Monsoon Rainfall
Clustering
Artificial Neural Networks
Self-organizing Map
Standard Precipitation Index
 
Description 669-677
The Indian summer monsoon rainfall during the months June, July, August and September (JJAS) has been classified into seven climatic zones, according to standard precipitation index. Prediction of rainfall within the six hydrological zones of India was attempted with the oceanic predictors, which highly influence the terrestrial precipitation, such as Sea Surface Temperature (SST), Sea Level Pressure (SLP), Humidity and zonal and meridional components of Surface Wind (u and v) to quantify the rainfall amounts by clustering based artificial neural networks for the distinguishable dry and wet years. In the present analysis, we have used data for the period 1960 – 2012, which incidentally had several extreme events (of drought and flood conditions) over the Indian subcontinent. Next, the results indicate that the predicted values are well comparable with the actual measured values proving the usefulness of this approach. In addition, this approach has improved upon the past and recent attempts to model rainfall (including extreme cases) which in turn will have a significant impact on farmers and agriculturists.
 
Date 2017-04-05T11:10:33Z
2017-04-05T11:10:33Z
2017-04
 
Type Article
 
Identifier 0975-1033 (Online); 0379-5136 (Print)
http://nopr.niscair.res.in/handle/123456789/41112
 
Language en_US
 
Rights CC Attribution-Noncommercial-No Derivative Works 2.5 India
 
Publisher NISCAIR-CSIR, India
 
Source IJMS Vol.46(04) [April 2017]