Identifying homogeneous rainfall catchments for non-stationary time series using TOPSIS algorithm and bootstrap K-sample Anderson-Darling test

Identifying homogeneous rainfall catchments for non-stationary time series using TOPSIS algorithm and bootstrap K-sample Anderson-Darling test

The reliability of extreme estimates of hydro-meteorological events such as extreme rainfalls may be questionable due to limited historical rainfall records. The problem of limited rainfall records, however, can be overcome by extrapolating information from gauged to ungauged rainfall catchments, wh...

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Bibliographic Details
Main Authors: Chuan, Zun Liang, Noriszura, Ismail, Wan Nur Syahidah, Wan Yusoff, Soo-Fen, Fam, Mohd Akramin, Mohd Romlay
Format: Article
Language:English
Published: Science Publishing Corporation 2018
Subjects:
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/22702/
http://umpir.ump.edu.my/id/eprint/22702/1/Identifying%20homogeneous%20rainfall%20catchments%20for%20non-%20stationary%20time%20series%20using%20tops%20is%20algorithm%20and%20bootstrap%20k-sample%20Anderson%20darling%20test.pdf

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