The rapid urbanization of Abha and its surrounding cities in Saudi Arabia’s mountainous regions poses challenges for sustainable and secure development. This study aimed to identify suitable sites for eco-friendly and safe building complexes amidst complex geophysical, geoecological, and socio-economic factors, integrating natural hazards assessment and risk management. Employing the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP), the study constructed a suitability model incorporating sixteen parameters. Additionally, a Deep Neural Network (DNN) based on eXplainable Artificial Intelligence (XAI) conducted sensitivity analyses to assess the parameters’ influence on optimal location decision making. The results reveal slope as the most crucial parameter (22.90%), followed by altitude and land use/land cover (13.24%), emphasizing topography and environmental considerations. Drainage density (11.36%) and rainfall patterns (9.15%) are also significant for flood defense and water management. Only 12.21% of the study area is deemed “highly suitable”, with “no-build zones” designated for safety and environmental protection. DNN-based XAI demonstrates the positive impact of variables like the NDVI and municipal solid waste generation on site selection, informing waste management and ecological preservation strategies. This integrated methodology provides actionable insights for sustainable and safe residential development in Abha, aiding informed decision making and balancing urban expansion with environmental conservation and hazard risk reduction.

The linear construction model is characterized by resource-intensive processes that generate significant waste, whereas adopting circular economy principles facilitates sustainable, adaptable, and recyclable building practices to mitigate waste and conserve resources. The primary objective of this study is to empirically analyze the impact of barriers and drivers on sustainable construction practices and to evaluate the role of organizational culture in moderating this relationship. This study, grounded in Circular Economy theory, distributed 210 questionnaires using simple random sampling to large contractors (501–3000 employees) in Saudi Arabia’s Eastern Region, yielding 154 acceptable responses and a 73% completion rate. Data analysis was conducted using SmartPLS software, revealing that barriers, drivers and organizational culture positively impact sustainable construction practices, with organizational culture also positively moderating the connection among drivers and sustainable construction practices. However, organizational culture was not observed to substantially influence the connection between barriers and sustainable practices. The results highlight the main contribution of organizational culture in supporting sustainable development, offering significant theoretical contributions and practical implications for industry leaders and policymakers to develop regulatory framework and implement strategies that support sustainability.

Saudi Arabia’s construction industry is greatly impacted by rising costs and delays, causing project overruns and high financial pressures. In construction, blockchain technology is a decentralized and secure system that promotes transparency, trustworthiness and effective management of project data and transactions. This research is based on the Technology–Organization–Environment (TOE) framework, which develops and tests a conceptual model to investigate how supply-chain management, smart contracts, transparency and traceability, regulatory compliance and building information modeling (BIM) integration influence blockchain technology adoption, with organizational culture as a moderator. Data from 291 professionals in large Saudi contracting firms were analyzed employing a quantitative, cross-sectional design using SmartPLS. Results confirm all hypothesized factors significantly drive blockchain technology adoption. Organizational culture, acting as a key amplifier, positively moderates all relationships. The model explains 71.1% of the variability in blockchain technology adoption. In order to overcome project challenges and meet Vision 2030’s goals, the results present a validated roadmap for Saudi’s construction sector. The findings show that technical investments and promoting a culture of innovation, collaboration across departments and strong leadership are important for adoption blockchain technology.

Several studies have been conducted to identify the potential impact of landfills on groundwater resources. This study evaluates the impact of landfills on groundwater resources in Mohammedia prefecture, Morocco. The groundwater was analysed from 2015 to 2022. The groundwater quality was evaluated based on electrical conductivity, pH, biological oxygen demand, chemical oxygen demand, total Kjeldahl nitrogen, phosphate, suspended solids, dissolved oxygen, ammonia, and total hydrocarbon, aluminium, iron, cadmium, chromium, copper, iron-nickel, zing, and mercury. The assessment was based on the water quality index, leachate pollution index, non-carcinogenic risk assessment, and carcinogenic risk assessment. A leachate pollution index <5 indicates that it poses a severe risk to groundwater resources. The non-carcinogenic risk HQ was determined to be <1, which infers no potential risk. The carcinogenic risk index value of 10-4 indicated that it is within the threshold of acceptable limit. The current study concludes that leachate from the analysed landfills does not infiltrate the groundwater resources of Mohammedia prefecture. However, the leachate pollution, even though it varies, is increasing over time. This is validated by the fact that the landfill is protected with a membrane covering the ground, which inhibits any possible infiltration of soil or water resources. Hence, this study calls for continuous monitoring of groundwater resources in the region. Future studies are required to investigate the groundwater in Mohammedia prefecture in terms of emerging pollutants to identify any potential risk.