Abstract
The rainfall patterns are no longer stationary due to changing climate. The non-stationary extreme rainfall resulted in the high flood risk in the urban area such as Surat city. In the current study, non-stationary extreme rainfall of Surat city is analysed using 68-years (1951–2018) observed daily rainfall data. Total five (physical processes) covariates namely, Local temperature anomaly (LT), Global temperature anomaly (GT), IOD-Dipole mode index (ID), ENSO-Sea surface temperature Index (ES) and Time is used. Firstly, the stationary Generalised Extreme Value (GEV) model is developed using extreme daily rainfall. Secondly, non-stationary GEV model using location parameter is developed with aforesaid covariates. Thirdly, non-stationary GEV model using location and scale parameters are developed using aforementioned covariates. A total of 27 GEV based models are developed and the significant covariate and best non-stationary model for extreme precipitation is evaluated using likelihood ratio test. Out of 27 constructed GEV models 13 models are showing significant effect of covariate on extreme precipitation analysis. The combination of LT-ES based GEV model using non-stationary location and scale parameter gives the best model with lowest AIC, and extreme daily rainfall for corresponding return levels are compared with stationary GEV model. The 2-year, 5-year, 10-year, 25-year, 50-year, and 100-year return period extreme daily rainfall are 146 mm (162 mm), 200 mm (247 mm), 235 mm (305 mm), 283 mm (381 mm), 319 mm (440 mm), and 356 mm (500 mm) respectively for GEV stationary (Non-stationary LT-ES) model for the Surat city. Moreover, the trend analysis using Modified-Mann Kendall (MMK) test and Innovative trend test analysis (ITA) shown the non-significant increasing trend in the extreme daily rainfall for Surat city. The current study can be useful in designing hydrologic infrastructure of Surat city under changing climate.
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.
