Main Article Content
The estimation of magnitude and frequency of extreme rainfall has immense importance to make decisions about hydraulic structures like spillways, dikes and dams etc The main objective of this study is to get the best fit distributions for annual maximum rainfall data on regional basis in order to estimate the extreme rainfall events (quantiles) for various return periods. This study is carried out using index flood method using L-moments by Hosking and wallis (1997). The study is based on 23 sites of rainfall which are divided into three homogeneous regions. The collective results of L-moment ratio diagram, Z-statistic and AWD values show the GLO, GEV and GNO to be best fit for all three regions and in addition PE3 for region 3. On the basis of relative RMSE, for region 1 and region 2, GLO, GEV and GNO are producing approximately the same relative RMSE for return periods upto 100. While GNO is producing less relative RMSE for large return periods of 500 and 1000. So for large return periods GNO could be best distribution. For region 3 GLO, GEV, GNO and PE3 are having approximately the same relative RMSE for return periods upto 100. While for large return periods of 500 and 1000 PE3 could be best on basis of less relative RMSE.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).