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...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Science Publishing Corporation
2018
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/22702/ 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 |
Internet
http://umpir.ump.edu.my/id/eprint/22702/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