Author(s): Saba Mirza Alipour, João Bento Leal

Linked Author(s): Saba Mirza Alipour, João Bento Leal

Keywords:

Abstract: River flood return period estimation plays an important role in the engineering practices of water resources and flood management, but there are many parameters that accompany the calculation process. Typically, several return levels and return periods (e.g. 100, 200, etc.) are used to describe and quantify river flood discharge. Classical river flood modelling techniques assume a stationary climate. In the stationary case it is assumed that, there is a one-to-one relationship between the m-year return level and T-year return period which is defined implicitly as the reciprocal of the probability of an exceedance in any 1 year. However, in recent years, it has become increasingly evident that, magnitude and frequency of peak flow can no longer be assumed to be stationary due to the climate change effect. This paper aims to investigate the probabilistic behavior of the return period and reliability of 100-year return period peak flow under stationary and nonstationary conditions. For this purpose, we focused on stationary and non-stationary scenarios. Using existing annual maximum daily discharge data and annual maximum daily precipitation data various GEV models were developed and return levels under stationary and nonstationary scenarios were estimated. The results revealed the existence of a clear climate signal in flood water level and its return period. Also, the comparison of the results showed a significant difference between calculated return level in each scenario. As a result, return periods and return levels reliability should be assessed under climate change and the uncertainty associated with them should be quantified.

DOI: https://doi.org/10.3850/38WC092019-1230

Year: 2019