Analysis of stationary and non-stationary hydrological extremes under a changing environment: A systematic review

Research on hydrological extremes has increased due to their increasing frequency and destructive power, with their non-stationarity attributed to human activities and climate change. To understand current advances in analyzing extremes, a systematic review of online literature was conducted using PRISMA framework. The review covered several aspects of analysis considered in literature like time series types, non-stationarity detection techniques, frequency analysis (FA) category, probability distribution types, covariates used, parameter estimation and model selection techniques. Results indicate that AMS (71.7 %), Mann-Kendall non-stationarity detection test (70.8 %), GEV distribution (41.4 %), ML parameter estimation (34.6 %) and model selection AIC (30.0 %) were mostly applied. Non-stationary alongside stationary FA was carried out most (82 %) and non-stationary models outperformed the stationary ones. Time was used as a covariate in most studies (50.5 %) compared to anthropogenic (7.1 %), local-scale (11.4 %) and large-scale (31.0 %) climate covariates. Effective hydrological extremes management requires an understanding of their non-stationarity in a changing environment. • Understanding non-stationarity in hydrological extremes is vital for water resources management. • Non-stationary frequency analysis models perform better than stationary ones in a non-stationary environment. • Choice of appropriate covariates is vital in non-stationary frequency analysis. • Estimation of uncertainty yields reliable results in non-stationary frequency analysis.