Nowadays, increased flood risk is recognized as one of the most significant threats in most parts of the world, with recurring severe flooding events causing significant property and human life losses. This has entailed public debates on both the apparent increased frequency of extreme events and the perceived increases in rainfall intensities within climate changing scenarios. In this work, a stationary vs. Non-Stationary Analysis of annual extreme rainfall was performed with reference to the case studies of the African cities of Dar Es Salaam (TZ) and Addis Ababa (ET). For Dar Es Salaam (TZ) a dataset of 53 years (1958–2010) of maximum daily rainfall records (24 h) was analysed, whereas a 47-year time series (1964–2010) was taken into account for Addis Ababa (ET). Both gauge stations rainfall data were suitably fitted by Extreme Value Distribution (EVD) models. Inference models using the Maximum Likelihood Estimation (MLE) and the Bayesian approach were applied on EVD considering their impact on the shape parameter and the confidence interval width. A comparison between a Non-Stationary regression and a Stationary model was also performed. On this matter, the two time series did not show any Non-Stationary effect. The results achieved under the CLUVA (Climatic Change and Urban Vulnerability in Africa) EU project by the Euro-Mediterranean Centre for Climate Change (CMCC) (with 1 km downscaling) for the IPCC RCP8.5 climatological scenario were also applied to forecast the analysis until 2050 (93 years for Dar Es Salaam TZ and 86 years for Addis Ababa ET). Over the long term, the process seemed to be Non-Stationary for both series. Moreover, with reference to a 100-year return period, the IDF (Intensity-Duration-Frequency) curves of the two case-studies were estimated by applying the Maximum Likelihood Estimation (MLE) approach, as a function of confidence intervals of 2.5% and 97.5% quantiles. The results showed the dependence of Non-Stationary effects of climate change to be conveniently accounted for engineering design and management.

Nature-based solutions (NBSs) are increasingly implemented to mitigate natural risks in urban and rural contexts, from coastal to mountainous areas. Nevertheless, the lack of quantitative approaches to assess NBSs’ effectiveness limits their technical, social and cultural acceptance. Within the PHUSICOS project (EU H2020 Innovation Action; Grant Agreement nr. 776681) a comprehensive assessment framework tool (AFT) has been developed to fill this gap. This paper presents an ex-post analysis with the PHUSICOS AFT applied to the Isar River case study. The restoration of the urban reach of the Isar River, in the city of Munich, was implemented in the early 2000s and represents a successful example of ecosystem and user-friendly flood risk management plan. The performance of the NBS measures implemented to manage the flood risk and improve the ecological status of the river (NBS scenario) is assessed in comparison with an alternative scenario with traditional hard engineering measures (grey scenario, GS). Results underscore the NBS as a competitive alternative. The ex-post analysis shows the potential of the PHUSICOS AFT for NBS performance assessment, providing guidance on indicator selection, stakeholders’ management and performance assessment. The application discussed here is expected to aid professionals and researchers involved in the design, implementation, monitoring and evaluation of NBSs.