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Title: | 5-Drought Forecasting Using Standardized Precipitation Index. |
Authors: | Desai, V. R. Mishra, A. K. |
Keywords: | Kansabati River Basin Neural networks Standardized precipitation index Drought indices |
Issue Date: | 2006 |
Publisher: | National Institute of Hydrology |
Abstract: | Drought forecasting plays an important role in the planning and management of natural resources including water resource-systems of a river basin, since drought has severe effect when it persists over a longer period Modeling and forecasting of droughts, which are nonlinear and non-stationary, is a complex exercise. During the last decade neural networks have shown great ability in modeling and forecasting nonlinear and non- stationary time series. In this study an application of the back propagation feed forward recursive ANN models are presented to forecast droughts., The models were applied to forecast droughts using standardized precipitation index series_as 'drought indices in the Kansabati River Basin, which lies in the Purulia District of West Bengal. The resulting trained network is capable of forecasting with satisfactory results upto 2-months of lead time. The model can be used for water resource management in the river basin |
URI: | http://117.252.14.250:8080/jspui/handle/123456789/6864 |
Appears in Collections: | 26-Jal Vigyan Sameeksha Vol.-21(1-2)-2006 |
Files in This Item:
File | Description | Size | Format | |
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5-Drought Forecasting Using Standardized Precipitation Index..pdf | 18.51 MB | Adobe PDF | View/Open |
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