Blue-green roofs as nature-based solutions for urban areas: hydrological performance and climatic index analyses.

The water-regulating capacity of nature-based solutions (NBSs) plays a crucial role in providing a full range of ecosystem services and enhancing the resilience of urban systems. This work focuses on the hydrological performance of a particular NBS, the so-called blue-green roof (BGR). The BGR is designed to collect infiltrated rainfall in a water storage layer beneath the soil to support vegetation maintenance, enhance evapotranspiration and cooling, and minimize runoff and drainage system load. The study aims to evaluate the hydrological performance of the BGR at global and event scale and, for the first time, to model climatic factors (easy to measure using common sensors) that affect its stormwater retention capacity. The data collected over 2 years and 2 months at a 5-min resolution from a pilot study in Central Italy were analysed. Additionally, a new climatic index called AWWP-x (Antecedent Wet Weather Period index) was introduced and calculated. Results show that the BGR has an overall relevant retention rate (67.1%), although the value depends on the rainfall of the observed period. Approximately 50% of the rainfall events did not produce any runoff, and during the dry season, all events were totally absorbed by the BGR. Four climatic variables were identified as significant factors for predicting BGR retention performance (R2 = 0.50). The results suggest that AWWP-130 (number of days to reach 130 mm cumulative precipitation) could be a possible proxy for the BGR stormwater retention rate. In general, this study demonstrates the potential for evaluating, planning, and designing NBSs by considering the annual and interannual climatic variability of the investigated specific location.

Integrating spatially-and temporally-heterogeneous data on river network dynamics using graph theory.

The study of non-perennial streams requires extensive experimental data on the temporal evolution of surface flow presence across different nodes of channel networks. However, the consistency and homogeneity of available datasets is threatened by the empirical burden required to map stream network expansions and contractions. Here, we developed a data-driven, graph-theory framework aimed at representing the hierarchical structuring of channel network dynamics (i.e., the order of node activation/deactivation during network expansion/retraction) through a directed acyclic graph. The method enables the estimation of the configuration of the active portion of the network based on a limited number of observed nodes, and can be utilized to combine datasets with different temporal resolutions and spatial coverage. A proof-of-concept application to a seasonally-dry catchment in central Italy demonstrated the ability of the approach to reduce the empirical effort required for monitoring network dynamics and efficiently extrapolate experimental observations in space and time.

[Traumatic motherhood in Covid-19 times]. / Maternités traumatiques en temps de Covid-19.

In the context of maternal vital emergency due to Covid-19, dire situations of birth questioned the health practitioners of a neonatal intensive care unit. How can mothers take care of their baby when their own life has been threatened ? The analysis of two clinical cases underlines the importance of talking for these mothers who have been through disastrous experiences, which could lead to a post-traumatic stress disorder. Restoring a connection to outside reality thanks to psychological care in the acute post-trauma period helps these mothers take care of their child.