Authors: Firdos Khan; Jürgen Pilz
Addresses: Institut für Statistik, Alpen-Adria Universität, Universitätstraße 65-67, 9020 Klagenfurt, Austria ' Institut für Statistik, Alpen-Adria Universität, Universitätstraße 65-67, 9020 Klagenfurt, Austria
Abstract: Undoubtedly, it is important to model the average and extreme phenomena in earth sciences disciplines such as hydrology under uncertain and changing climate conditions. The issues become more important when we deal with reservoir management, flood forecasting and irrigation. In this paper, we model the average and extreme river flow in the Indus River at the Upper Indus Basin. For modelling average river flow, we utilised the popular classes of time series models including the autoregressive integrated moving average and autoregressive conditional heteroscedasticity models. For modelling the extremes, preference is given to probability distributions dealing with extremes in the tails. Starting with different models and distributions we finally choose the one which performs best among the competing models and distributions, respectively. Finally, when modelling extremes we noted that different probability distributions may be used for the same data, depending on whether interest is in lower or higher order moments.
Keywords: hydrological extremes; river flow; extreme value distributions; Tarbela Reservoir; Upper Indus Basin; UIB; time series models; Pakistan.
International Journal of Water, 2018 Vol.12 No.1, pp.1 - 21
Available online: 19 Feb 2018 *Full-text access for editors Access for subscribers Free access Comment on this article