Abstract
Estimation of rainfall and temperature for a desired return period is a prerequisite for planning, design and operation of various hydraulic structures and for evaluation of technical and engineering appraisal of large infrastructure projects. This can be computed through Extreme Value Analysis (EVA) by fitting probability distributions to the annual series of 1-day maximum rainfall, maximum and minimum temperature. This paper details the study on adoption of Extreme Value Type-1, Extreme Value Type-2, 2-parameter Log Normal and Log Pearson Type-3 (LP3) probability distributions in EVA of rainfall and temperature for Hissar. Based on the applicability, standard parameter estimation procedures such as method of moments, maximum likelihood method (MLM) and order statistics approach are used for determination of parameters of distributions. The adequacy on fitting of probability distributions used in EVA of rainfall and temperature is evaluated by goodness-of-fit (GoF) tests, viz. Anderson–Darling and Kolmogorov–Smirnov and diagnostic test using D-index. The GoF and diagnostic tests results suggest the LP3 (MLM) is better suited amongst four probability distributions adopted in EVA of rainfall and temperature for Hissar.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
