River vegetation radically modifies the flow field and turbulence characteristics. To analyze the vegetation effects on the flow, most scientific studies are based on laboratory tests or numerical simulations with vegetation stems on smooth beds. Nevertheless, in this manner, the effects of bed sediments are neglected. The aim of this paper is to experimentally investigate the effects of bed sediments in a vegetated channel and, in consideration of that, comparative experiments of velocity measures, performed with an Acoustic Doppler Velocimeter (ADV) profiler, were carried out in a laboratory flume with different uniform bed sediment sizes and the same pattern of randomly arranged emergent rigid vegetation. To better comprehend the time-averaged flow conditions, the time-averaged velocity was explored. Subsequently, the analysis was focused on the energetic characteristics of the flow field with the determination of the Turbulent Kinetic Energy (TKE) and its components, as well as of the energy spectra of the velocity components immediately downstream of a vegetation element. The results show that both the vegetation and bed roughness surface deeply affect the turbulence characteristics. Furthermore, it was revealed that the roughness influence becomes predominant as the grain size becomes larger.
Many complex problems require a multi-criteria decision, such as the COVID-19 pandemic that affected nearly all activities in the world. In this regard, this study aims to develop a multi-criteria decision support system considering the sustainability, feasibility, and success rate of possible approaches. Therefore, two models have been developed: Geo-AHP (applying geo-based data) and BN-Geo-AHP using probabilistic techniques (Bayesian network). The ranking method of Geo-APH is generalized, and the equations are provided in a way that adding new elements and variables would be possible by experts. Then, to improve the ranking, the application of the probabilistic technique of a Bayesian network and the role of machine learning for database and weight of each parameter are explained, and the model of BN-Geo-APH has been developed. In the next step, to show the application of the developed Geo-AHP and BN-Geo-AHP models, we selected the new pandemic of COVID-19 that affected nearly all activities, and we used both models for analysis. For this purpose, we first analyzed the available data about COVID-19 and previous studies about similar virus infections, and then we ranked the main approaches and alternatives in confronting the pandemic of COVID-19. The analysis of approaches with the selected alternatives shows the first ranked approach is massive vaccination and the second ranked is massive swabs or other tests. The third is the use of medical masks and gloves, and the last ranked is the lockdown, mostly due to its major negative impact on the economy and individuals.
There are many types of Nature-Based Solutions (NBS), such as intensive/extensive green roofs, green walls, retention ponds, Bioretention cells, treatment wetlands, river restoration, urban parks, and infiltration trenches. Each could contribute to one or more sustainable development goals as some can improve the ecosystem, some improve water resources, or mitigate urban flooding. Implementing the most suitable NBS in each area needs multidisciplinary perspective analysis by considering circular economy principles and the available resources that exhibit the importance of ranking the possible NBS that could be geo-based. Therefore, the main purpose of this study is to develop a novel ranking method for selecting the best NBSs in each area, which depends on plenty of geo-based variables such as climate type, water resource, economy, environment, Sustainable Development Goals (SDGs) and so forth. The developed dynamic geo-based ranking method has been validated through case-based assessment in different regions, confirming the proposed method’s effectiveness. In conclusion, the developed method could rank the selected NBS in each location, and according to geo-based information, it could show the implementation of the most suitable NBS, thus improving their role in the circular city.
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