Footprints of El Niño Southern Oscillation on Rainfall and NDVI-Based Vegetation Parameters in River Basin in Central India
Publication: Journal of Hydrologic Engineering
Volume 21, Issue 12
Abstract
Assessing the impacts of El Niño Southern Oscillation (ENSO) on hydrological cycle is critical for irrigation scheduling and water resources management. The ENSO-rainfall teleconnections in Venna River Basin in Maharashtra, India, and its impacts on vegetation have been identified in this study by using rainfall data, moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and geographic information system (GIS) techniques. Spatiotemporal analysis indicates correlation of rainfall with ENSO. Spatial variation in rainfall harmonizes with topography of the region, and a respective decrement and increment of 200–400 mm of rainfall at higher and lower elevations are seen to be associated with El Niño and La Niña events. This study also records the impacts of varying intensities of ENSO, causing inconsistencies in parameters, namely, premonsoon and postmonsoon vegetation growth, phenological parameters, and crop water requirements. The correlation of NDVI-precipitation studied by mean square error (MSE) and lagged correlation analyses shows a time-lag effect of 2 months. It is estimated that the percentage area of dense vegetation is maximum in La Niña (15.6% in 2011) and minimum in El Niño (1.2% in 2009). A “20% threshold graphical method” introduced in the study reveals that El Niño and La Niña are associated with late (July) and early (June) start of season (), respectively. This study also reveals that crop coefficient and water requirements are more for the ENSO cold phase than for the warm phase.
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Published In
Journal of Hydrologic Engineering
Volume 21 • Issue 12 • December 2016
Copyright
© 2016 American Society of Civil Engineers.
History
Received: Feb 9, 2016
Accepted: Jun 10, 2016
Published online: Aug 1, 2016
Published in print: Dec 1, 2016
Discussion open until: Jan 1, 2017
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