Please use this identifier to cite or link to this item: https://idr.l4.nitk.ac.in/jspui/handle/123456789/9947
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBabar, S.
dc.contributor.authorRamesh, H.
dc.date.accessioned2020-03-31T06:51:48Z-
dc.date.available2020-03-31T06:51:48Z-
dc.date.issued2014
dc.identifier.citationISH Journal of Hydraulic Engineering, 2014, Vol.20, 2, pp.212-221en_US
dc.identifier.uri10.1080/09715010.2013.872353
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/9947-
dc.description.abstractIndia gets three fourths of its annual rainfall during the south-west monsoon season (June-September). The study of extreme events is significant in the stochastic behaviour of rainfall pattern. The aim of the present work is to compare different methods; and find a suitable method to study extreme rainfall trend analysis. In this study, frequency distribution method, generalized extreme value (GEV) distribution, Mann-Kendall and Sens slope estimator are used for rainfall trend analysis over the Nethravathi basin located in the southern part of India. The rainfall data during the monsoon months (June-September) were analysed for a period of 1971-2010. The comparison of all the methods had been carried out and it has been observed that there is an increasing trend of frequency in class-1 and decreasing trend in class-2 and class-3, respectively. The interpretation of the results is carried by using the GEV distribution and non-parametric trend analysis (Mann-Kendall and Sens slope estimator test). It turns out the best results to identify the extreme rainfall trend are obtained by the statistical techniques - Block Maxima (GEV) distribution, Mann-Kendall and Sens slope estimator test as compared to frequency-based method. The above results which help to study climate change will contribute towards sustainable development of the Nethravathi River basin. 2013 2013 Indian Society for Hydraulics.en_US
dc.titleAnalysis of extreme rainfall events over Nethravathi basinen_US
dc.typeArticleen_US
Appears in Collections:1. Journal Articles

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.