The design of effective flood risk mitigation strategies and their subsequent implementation is crucial for sustainable development in mountain areas. The assessment of the dynamic evolution of flood risk is the pillar of any subsequent planning process that is targeted at a reduction of the expected adverse consequences of the hazard impact. This study focuses on riverbed cities, aiming to analyze flood occurrences and their influencing factors. Through an extensive literature review, five key criteria commonly associated with flood events were identified: slope height, distance from rivers, topographic index, and runoff height. Utilizing the network analysis process within Super Decision software, these factors were weighted, and a final flood risk map was generated using the simple weighted sum method. 75% of the data was used for training, and 25% of it was used for testing. Additionally, vegetation changes were assessed using Landsat imagery from 2000 and 2022 and the normalized difference vegetation index (NDVI). The focus of this research is Qirokarzin city as a case study of riverbed cities, situated in Fars province, with Qir city serving as its central hub. Key rivers in Qirokarzin city include the Qara Aghaj River, traversing the plain from north to south; the primary Mubarak Abad River, originating from the east; and the Dutulghaz River, which enters the eastern part of the plain from the southwest of Qir, contributing to plain nourishment during flood events. The innovation of this paper is that along with the objective to produce a reliable delineation of hazard zones, a functional distinction between the loading and the response system (LS and RS, respectively) is made. Results indicate the topographic index as the most influential criterion, delineating Qirokarzin city into five flood risk zones: very low, low, moderate, high, and very high. Notably, a substantial portion of Qirokarzin city (1849.8 square kilometers, 8.54% of the area) falls within high- to very-high flood risk zones. Weighting analysis reveals that the topographic humidity index and runoff height are the most influential criteria, with weights of 0.27 and 0.229, respectively. Conversely, the height criterion carries the least weight at 0.122. Notably, 46.7% of the study area exhibits high flood intensity, potentially attributed to variations in elevation and runoff height. Flood potential findings show that the middle class covers 32.3%, indicating moderate flood risk due to changes in elevation and runoff height. The low-level risk is observed sporadically from the east to the west of the study area, comprising 12.4%. Analysis of vegetation changes revealed a significant decline in forest and pasture cover despite agricultural and horticultural development, exacerbating flood susceptibility. 

The objective of the study was to analyze green marketing in the promotion of environmentally responsible and sustainable practices in the development of resilient infrastructure in Peru. The methodology used was qualitative and interpretative, the documentary design based on the systematic review of scientific literature. The PRISMA model was applied for the selection of units of analysis, resulting in 36 articles out of an initial total of 950. Content analysis was used to examine the documents, following a detailed procedure that included the use of Grounded Theory to categorize and analyze the data. The results highlighted the importance of integrating green marketing and sustainable practices into resilient infrastructure planning and development. Key strategies were identified that include promoting environmental responsibility, adopting sustainable technologies in construction, and implementing policies that foster urban resilience and sustainability. The findings highlight the adoption of a comprehensive approach that combines green marketing with resilient infrastructure planning and development to address environmental challenges and promote sustainable development in Peru.

This paper highlights the complex relationship between entrepreneurship, sustainable development, and economic growth in 41 European countries, using a reliable K-Means cluster analysis. The research thoroughly evaluates three key factors: the SDG Index for sustainable development, GDP per capita for economic well-being, and the New Business Density Rate for entrepreneurial activity. Our methodology reveals three distinct narratives that embody varying degrees of economic vitality and sustainability. Cluster 1 comprises the financially stable and sustainability-oriented countries of Western and Northern Europe. Cluster 2 showcases the variegated economic and sustainability initiatives in Central and Southern Europe. Cluster 3 envelopes the economic titans with noteworthy business expansion but with the potential for better sustainable practices. The analysis reveals a favourable association between economic prosperity and sustainable development within clusters, although with nonlinear intricacies. The research concludes with a series of strategic imperatives specifically crafted for each cluster, promoting economic variation, increased sustainability, invention, and worldwide collaboration. The resulting findings highlight the crucial need for policy-making that considers the specific context and the potential for combined European resilience and sustainability.

The article considers an actual problem of organizing a safe and sustainable urban transport system. We have examined the existing positive global experience in both infrastructural and managerial decisions. Then to assess possible solutions at the stage of infrastructure design, we have developed the simulation micromodels of transport network sections of the medium-sized city (Naberezhnye Chelny) with a rectangular building type. The models make it possible to determine the optimal parameters of the traffic flow, under which pollutant emissions from cars would not lead to high concentrations of pollutants. Also, the model allows to obtain the calculated values of the volume of emissions of pollutants and the parameters of the traffic flow (speed, time of passage of the section, etc.). On specific examples, the proposed method’s effectiveness is shown. Case studies of cities of different sizes and layouts are implementation examples and possible uses proposed by the models. This study has shown the rationality of the suggested solution at the stage of assessing infrastructure projects and choosing the best option for sustainable transport development. The proposed research method is universal and can be applied in any city.

This research examines the intricate connection between tourism and environmental destruction in 28 Asian countries, concentrating on the non-linear impacts of tourism. Moreover, this study contemplates how tourism can mitigate the effects of economic growth on environmental decline. Westerlund, Johansen-Fisher, and Pedronico-integration tests are necessary to detect the co-integration connection between the proposed factors. The research also uses the Augmented Mean Group; the dynamic system generalized method of moments, and fully changed Ordinary Least Squares (OLS). These tools help address econometric and economic problems such as co-integration, dynamism, variation, inter-sectional dependence, and endogeneity. The results demonstrate a U-shaped non-linear connection between ecological footprint and Tourism in Asian nations. Primarily, the tourism industry can initially decrease environmental damage. However, as it increases in size, it can worsen the harm. Additionally, the study suggests that tourism negatively influences how economic growth affects ecological footprint. This research contributes to the existing literature on tourism’s effects on the environment. The research suggests that tourism significantly impacts the environment; therefore, initiatives to reduce damage should be aimed at tourism.