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Investigating extreme rainfall non-stationarity of upper Tapi river basin, India
The present study takes into consideration the daily rainfall series and annual maximum rainfall series of 28 rain gauge stations of the Upper Tapi basin for investigation of extreme rainfall stationarity. The Mann-Kendall (MK) trend test and Autocorrelation coefficient function (ACF) plots are applied to the daily rainfall series. The Mann-Kendall rank statistic method and the CUSUM test are applied to the annual maximum rainfall series. The shortfall in the trend of daily rainfall time series has been assessed through Mann-Kendall trend analysis. Auto Correlation Function plots show non-stationarity. Mann-Kendal rank statistics and CUSUM tests indicate non-homogeneity in the time series of rainfall. The analysis has been carried out by using the high-resolution daily gridded (1° latitude x 1° longitude) datasets. The shortfall in the trend of daily rainfall-gridded datasets is observed. Nonstationarity is observed by ACF plots. Change point analysis shows nonhomogeneity. It is also observed from the analysis between gridded data stations and their adjacent rain gauge stations that there is variability in findings of stationarity tests. Rain gauge station data offer accurate results.
Investigating extreme rainfall non-stationarity of upper Tapi river basin, India
The present study takes into consideration the daily rainfall series and annual maximum rainfall series of 28 rain gauge stations of the Upper Tapi basin for investigation of extreme rainfall stationarity. The Mann-Kendall (MK) trend test and Autocorrelation coefficient function (ACF) plots are applied to the daily rainfall series. The Mann-Kendall rank statistic method and the CUSUM test are applied to the annual maximum rainfall series. The shortfall in the trend of daily rainfall time series has been assessed through Mann-Kendall trend analysis. Auto Correlation Function plots show non-stationarity. Mann-Kendal rank statistics and CUSUM tests indicate non-homogeneity in the time series of rainfall. The analysis has been carried out by using the high-resolution daily gridded (1° latitude x 1° longitude) datasets. The shortfall in the trend of daily rainfall-gridded datasets is observed. Nonstationarity is observed by ACF plots. Change point analysis shows nonhomogeneity. It is also observed from the analysis between gridded data stations and their adjacent rain gauge stations that there is variability in findings of stationarity tests. Rain gauge station data offer accurate results.
Investigating extreme rainfall non-stationarity of upper Tapi river basin, India
Baria, Paresha M. (Autor:in) / Yadav, S. M. (Autor:in)
ISH Journal of Hydraulic Engineering ; 27 ; 521-529
02.11.2021
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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