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• Highlights the limitation of existing NFFA approaches in differentiating the mechanism of frequent versus rare flood quantiles. • Proposes a novel NRFFA approach to capture the variation of flood quantiles with different return periods in a changing climate. • Use regional information to ascertain the design flood quantiles and provide plausible changes in design flood extremes in the year 2100. There now exists clear evidence of the impact of climate change on flooding, creating need for new methodologies for design flood estimation that account for warming induced nonstationarity. Current alternatives for nonstationary flood frequency analysis require the specification of a nonstationary probability model (often with time-varying parameters) that requires sufficient data to be stable. Reliance on the trend in observed data often ignores the dissimilar behaviour of frequent and rare quantiles under a warming climate. This, in turn, results in the direction of change to be consistent across both rare and frequent projected flood quantiles. However, results of multiple recent studies suggest that rarer floods are likely to increase while more frequent floods may decrease in magnitude into the future. In this study, we highlight this limitation of existing nonstationary flood frequency approaches and propose a novel nonstationary regional flood frequency analysis approach that captures the differing behaviour of more frequent and rare flood quantiles under a warming climate. The need for longer flood data to model nonstationarity is accommodated by pooling regional information which makes the projections more precise. Data for 105 Australian catchments are used to validate our proposed approach. Results show the effectiveness of the proposed method in capturing the variation of flood quantiles with varying average recurrence intervals in a changing climate. Finally, a few important statistics of future projections are also presented. [ABSTRACT FROM AUTHOR]

• Highlights the limitation of existing NFFA approaches in differentiating the mechanism of frequent versus rare flood quantiles. • Proposes a novel NRFFA approach to capture the variation of flood quantiles with different return periods in a changing climate. • Use regional information to ascertain the design flood quantiles and provide plausible changes in design flood extremes in the year 2100. There now exists clear evidence of the impact of climate change on flooding, creating need for new methodologies for design flood estimation that account for warming induced nonstationarity. Current alternatives for nonstationary flood frequency analysis require the specification of a nonstationary probability model (often with time-varying parameters) that requires sufficient data to be stable. Reliance on the trend in observed data often ignores the dissimilar behaviour of frequent and rare quantiles under a warming climate. This, in turn, results in the direction of change to be consistent across both rare and frequent projected flood quantiles. However, results of multiple recent studies suggest that rarer floods are likely to increase while more frequent floods may decrease in magnitude into the future. In this study, we highlight this limitation of existing nonstationary flood frequency approaches and propose a novel nonstationary regional flood frequency analysis approach that captures the differing behaviour of more frequent and rare flood quantiles under a warming climate. The need for longer flood data to model nonstationarity is accommodated by pooling regional information which makes the projections more precise. Data for 105 Australian catchments are used to validate our proposed approach. Results show the effectiveness of the proposed method in capturing the variation of flood quantiles with varying average recurrence intervals in a changing climate. Finally, a few important statistics of future projections are also presented. [ABSTRACT FROM AUTHOR]

The article titled "Forecasting the Landslide Blocking River Process and Cascading Dam Breach Flood Propagation by an Integrated Numerical Approach: A Reservoir Area Case Study" has been retracted by the journal Remote Sensing. The retraction was prompted by concerns raised by the authors themselves regarding the ownership of several figures in the article. An investigation confirmed that the ownership of these figures belonged to a third party and that appropriate permission had not been obtained. As a result, the article has been retracted in accordance with MDPI's retraction policy and the guidelines of the Committee on Publication Ethics. The authors have agreed to this retraction. [Extracted from the article]