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The accuracy of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes. In fact, the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows and groundwater recharge. In this study, a comparison between statistical properties of rainfall observations and model control simulations from a Regional Climate Model (RCM) was performed through a robust and meaningful representation of the precipitation process. The output of the adopted RCM was analysed and re-scaled exploiting the structure of a stochastic model of the point rainfall process. In particular, the stochastic model is able to adequately reproduce the rainfall intermittency at the synoptic scale, which is one of the crucial aspects for the Mediterranean environments. Possible alteration in the local rainfall regime was investigated by means of the historical daily time-series from a dense rain-gauge network, which were also used for the analysis of the RCM bias in terms of dry and wet periods and storm intensity. The result is a stochastic scheme for bias-correction at the RCM-cell scale, which produces a realistic representation of the daily rainfall intermittency and precipitation depths, though a residual bias in the storm intensity of longer storm events persists. [ABSTRACT FROM AUTHOR]

A regional probabilistic model for the estimation of medium-high return period flood quantiles is presented. The model is based on the use of theoretically derived probability distributions of annual maximum flood peaks (DDF). The general model is called TCIF (Two-Component IF model) and encompasses two different threshold mechanisms associated with ordinary and extraordinary events, respectively. Based on at-site calibration of this model for 33 gauged sites in Southern Italy, a regional analysis is performed obtaining satisfactory results for the estimation of flood quantiles for return periods of technical interest, thus suggesting the use of the proposed methodology for the application to ungauged basins. The model is validated by using a jack-knife cross-validation technique taking all river basins into consideration. [ABSTRACT FROM AUTHOR]

The accuracy of ensemble streamflow forecasts (ESFs) is impacted by the propagation of uncertainty associated with quantitative precipitation forecasts (QPFs) through the physical processes occurring in the basin. In this study, we consider consistent ESFs (i.e., observations and ensemble members are equally likely) and we study the effect of basin area (A) and antecedent rainfall (AR) on the ESF dispersion, a metric of flood forecast skill. Results from a set of numerical experiments indicate that: (i) for small basins (≲180 km²), ESF dispersion is mainly dominated by the runoff generation process and does not depend on the basin size A; (ii) for larger areas, ESF dispersion decreases with A according to a log-linear relation due to the decreasing variability of ensemble QPFs and, possibly, to the channel routing process. In addition, we found that, regardless the basin size, the ESF dispersion decreases as AR increases, and that the influence of AR is larger for basins with fast response times. Physical controls (land cover, soil texture and morphometric features) on the analyzed basin response confirm these interpretations. [ABSTRACT FROM AUTHOR]

In the context of climate changes, characterized by an increase of short but intense rainfall events and rise of the average temperature, the fast population growth and consequent urbanization require the implementation of innovative solutions to mitigate pluvial floods and, at the same time, reduce the water demand. Among the different nature-based solutions, multilayer blue-green roofs have been widely recognized for their high capacity of reducing runoff generation from rooftops, and their additional storage layer enables to collect water, which could be reused for different purposes. However, the quality of the collected water in a multilayer blue-green roof and the influence that the additional storage layer has on it have not been analysed yet. Following this knowledge gap, we investigated the potential benefits of a multilayer blue-green roof installed in Cagliari, with respect to a traditional roof. The outflow triggered by artificial irrigation and natural rainfall events was analysed, both from a quantitative and qualitative perspective. Results confirm the high contribution of multilayer blue-green roofs in mitigating runoff generation, which is however influenced by antecedent soil moisture and water level conditions. The outflow from the multilayer blue-green roof presents lower suspended solids and heavy metals concentrations than from a traditional roof. On the other hand, Carbon Oxigen Demand (COD) concentrations in the multilayer blue-green roof outflow exceed the limits defined by the Italian regulations (125 mg/l) for water discharge or reuse, partially due to the high residence time in the storage layer. Specific treatments could be planned to reuse the collected water for urban purposes., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Green roofs have been extensively investigated in recent years, showing that their implementation in urban areas provides multiple benefits (e.g., pluvial flood mitigation, urban heat island reduction, energy saving, increase of biodiversity, CO 2 sequestration) and supports sustainable urban development. Although green roof benefits have been widely recognized, the perception that the community has of these nature-based solutions and the willingness to pay for their installation in urban areas is still not clear nor quantified. Societal perception and willingness to pay for green roofs are fundamental for urban planners and decision makers, since they represent the community participation in the sustainable development of urban areas. In this work, we aim to analyze how citizens perceive green roofs and how willing they are to pay for the installation and maintenance of these nature-based solutions. We used an online survey to investigate the perception and the knowledge of green roofs as a potential solution to common environmental issues (i.e., urban flood, increase of temperature, energy consumption, air pollution and lack of green spaces), and the interest and willingness to pay for green roof installation on both public and private roofs. Based on the answers of 389 respondents living in Sardinia (Italy), our analysis revealed that most citizens are aware of what green roofs are, and they are aware that, although these nature-based solutions can not completely solve environmental issues, they can greatly contribute to the mitigation of these phenomena. Results also show a higher interest in the installation of green roofs on public buildings than on private ones, due to the high installation costs. Moreover, for private roofs, the possibility to install photovoltaic panels instead of GRs is generally preferred. Most of the respondents are willing to spend less than 100 € per year for the maintenance of green roofs on public buildings and to invest less than 5000 € for the installation on their own house., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Multilayer Blue-Green Roofs are powerful nature-based solutions that can contribute to the creation of smart and resilient cities. These tools combine the retention capacity of traditional green roofs with the water storage of a rainwater harvesting tank. The additional storage layer enables to accumulate the rainwater percolating from the soil layer, that, if properly treated, can be reused for domestic purposes. Here, we explore the behavior of a Multilayer Blue-Green Roof prototype installed in Cagliari (Italy) in 2019, that have been equipped with a remotely controlled gate to regulate the storage capacity of the system. The gate installation allows to manage the Multilayer Blue-Green Roof in order to increase the flood mitigation capacity, minimizing the water stress for vegetation and limiting the roof load with adequate management practices. In this work, 10 rules for the management of the Multilayer Blue-Green Roof gate have been investigated and their performances in achieving different management goals (i.e., mitigating urban flood, increasing water storage and limiting roof load on the building) have been evaluated, with the aim to identify the most efficient approach to maximize the benefits of this nature based solution. An ecohydrological model have been calibrated based on field measurements carried out for 6 months. The model has been used to simulate the system performance in achieving the proposed goals, using as input nowdays and future rainfall and temperature time series. The analysis reveled the importance of the correct management of the gate, highthing how choosing and applying a specific management rule helps increasing the performance in reaching the desired goal., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Flooding risk in cities has been recently exacerbated by increased urbanization and climate change, often with catastrophic consequences in terms of casualties and economic losses. Rainwater harvesting systems and green roofs are recognized as being among the most effective blue-green mitigation measures. However, performances of these systems have currently been investigated only at laboratory or very-small local scales. In this work, we assess the potential benefit of the extensive installation of these solutions on all the rooftops of 9 cities, with different climatological and geographical characteristics. Both surface discharge reduction and delay between rainfall and runoff peak generation have been investigated. Green roofs ensure a larger average lag time between rainfall and runoff peaks than rainwater harvesting systems, without significant differences between intensive and extensive structures. On the other hand, the cost-efficiency analysis, considering the entire urban area, shows a higher retention capacity with a lower financial investment for rainwater harvesting rather than for green roofs in most cases. For extreme rainfall events, large-scale installation of rainwater harvesting systems coupled with intensive green roofs over the entire city have shown to be the most efficient solution, with a total discharge reduction that can vary from 5% to 15%, depending on the city characteristics and local climate., Competing Interests: The authors have declared that no competing interests exist.

The aim of this work was to develop a supercritical fluid chromatographic method to study the applicability of this emerging technique to cannabinoid analysis and showcase its advantages. During method development, the authors focused on nine phyto-cannabinoids to assess the selectivity needed to potentially perform the quantitation of each cannabinoid. After method development, robustness studies were carried out on this method to gain more information about its qualitative behavior (in terms of critical resolutions) when varying some crucial parameters (concentration of additive, column temperature, starting gradient conditions and column batch). Once the robustness was evaluated and the parameters most affecting the selected responses were individuated, the SFC method was applied for a simulated routine use to generate quantitative results concerning the concentrations of the main cannabinoids in real cannabis samples. The samples were also analyzed by means of an ultra-high-performance liquid chromatographic method currently used in the laboratory for the same objective. Finally, the results obtained with both analytical methods were compared to evaluate their accordance. The Bland-Altman method was applied as a statistical strategy to evaluate the degree of accordance between the results generated and display the data in a difference plot. The ultra-high performance supercritical fluid chromatography quantitative results were in accordance with the ultra-high performance liquid chromatography results, demonstrating the applicability of this technique for cannabinoid analysis., Competing Interests: The authors declare no conflict of interest., (© 2020 The Authors. Analytical Science Advances published by Wiley‐VCH GmbH.)