Multi-covariate non-stationary flood frequency analysis for assessing flood hazard over the Mahanadi River basin, India

Due to climate change and anthropogenic activities, the river's peak flow is changing, which prompts exploring the non-stationary flood frequency analysis. Most of the past studies modelled the non-stationarity of floods, considering time and/or a single dominant covariate influencing the flood flows, but they are inadequate. This study proposes a multi-covariate non-stationary flood frequency model (MC-NSFFM) and investigates the influence of different covariates, such as rainfall, modified reservoir index (MRI), and climate indices, for the Mahanadi River basin in India. The models' performances are evaluated by comparing them with the results of stationary and single-covariate non-stationary flood frequency models (SC-NSFFMs) using standard performance measures and return period analysis. The study showed that the MC-NSFFMs performed better than stationary and SC-NSFFMs. The flood return levels corresponding to the MC-NSFFMs are 4% to 22% higher than the stationary models, indicating the rise in flood risks due to climate change and anthropogenic activities.