Articles | Volume 385
https://doi.org/10.5194/piahs-385-163-2024
https://doi.org/10.5194/piahs-385-163-2024
Post-conference publication
 | 
18 Apr 2024
Post-conference publication |  | 18 Apr 2024

Developing Non-Stationary Frequency Relationships for Greater Pamba River basin, Kerala India incorporating dominant climatic precursors

Arathy Nair, Adarsh Sankaran, Meera Geetha Mohan, and Sreedevi Vijayalakshmi

Cited articles

Adarsh, S. and Janga Reddy, M.: Analysing the hydroclimatic teleconnections of summer monsoon rainfall in Kerala, India using Multivariate Empirical Mode Decomposition and time dependent intrinsic Correlation, IEEE Geosci. Remote Sens. Lett. 13, 1221–1225, 2016. 
Adlouni, S. E., Ouarda, T. B. M. J., Zhang, X., Roy, R., and Bobée, B.: Generalized maximum likelihood estimators for the nonstationary generalized extreme value model, Water Resour. Res., 43, W03410, https://doi.org/10.1029/2005WR004545, 2007. 
Akaike, H.: A new look at the statistical model identification, IEEE T. Automatic Control, 19, 716–23, 1974. 
Alexandersson, H. and Moberg, A.: Homogenization of Swedish Temperature data. Part I: homogeneity test for linear trends, Int. J. Climatol., 17, 25–34, 1997. 
Anandalekshmi, A., Panicker, S. T., Adarsh, S., Siddik, M. A., Aloysius, S., and Mehjabin, M.: Modeling the concurrent impact of extreme rainfall and reservoir storage on Kerala Floods 2018: A Copula approach, Model. Earth Syst. Environ., 5, 1283–1296, 2019. 
Download
Short summary
Increasing frequency of hydrologic extremes under changing climate warrants a revisit to the design practices considering non-stationarity to safeguard the hydro-systems. This study proposes a novel method integrating wavelet based selection of dominant climatic oscillations with extreme value formulations for developing non-stationary frequency relations of rainfall, temperature and streamflow of Greater Pamba river basin in Kerala, India, which successfully captured the extremes of 2018.