Recent climate changes have prompted changes in the hydrological cycle at a global scale, creating instability when predicting future climate conditions and related changes. Perturbations in global climate models have created the need to concentrate consequent changes in hydro climatic factors to comprehend the regional and territorial impacts of climate and environmental changes. Syria, as a Middle East country, is exposed to extreme climate events such as drought and flood. The aim of this study is to analyze rainfall trends in Syria in response to the likely climate change. The analysis was conducted for rainfall data collected from 71 stations distributed all over the country for the period (1991–2009). The trend analysis was performed in monthly and seasonal scales using Mann–Kendall non-parametric statistical tests. The results attained from Mann–Kendall trend analysis revealed decreasing trends at most of the stations. Additionally, rainfall analysis was conducted for the stations with significant trends for wet and dry periods, which also revealed decreasing trends at almost all the stations. From the analysis of the results, it is obvious that slight increasing trends in rainfall in Syria occurred in the fall period. However, in the winter and spring periods, significant decreasing trends have been observed at almost all the stations. This reveals that the country will suffer from shortage of water, because most rainfall occurs in the winter and spring, infrequently in fall and rarely in summer. The results are consistent with the IPCC’s fifth report that predicted a decrease in rainfall in the Mediterranean and southern Asia. The results of this paper could help the management of water resources in Syria considering future climate changes.

Construction is an important sector of human activity that significantly impacts the environment. The impact of this sector can be analysed from different perspectives, such as consumption of natural resources, waste generation, energy intensity, and environmental change. The sector is increasingly promoting using renewable materials, energy-efficient practices, and planning those respects ecological processes and biodiversity. Against this background, it is important to take coordinated action across the sector and move to net-zero carbon standards through immediate action to raise awareness, implement innovation, and improve carbon management and reporting processes. Tools supporting the reduction of the adverse impacts of construction activities include artificial intelligence tools. The construction industry has long been considered a conservative and traditional industry but is now experiencing a technological revolution. Gradually, artificial intelligence (AI) principles and tools are beginning to be integrated into the various lifecycle processes of construction projects. This paper analyses the AI tools used to analyse carbon footprinting in the construction sector in terms of selected functionalities. The results of the research will form the basis for the development of a strategic plan for the development of AI within the research activities at the Faculty of Civil Engineering in Košice.

Groundwater contamination due to saltwater intrusion (SWI) has an extreme effect on freshwater quality. Analytical and numerical models could be used to investigate SWI. This study aims to develop an analytical solution to investigate SWI into coastal aquifers which was applied to a real case study at the Middle Nile Delta aquifer (MNDA). The study presented a new formula to predict the difference in depth of freshwater to seawater interface due to a change in boundary conditions. A Computer Program for Simulation of Three-Dimensional Variable-Density Ground-Water Flow and Transport (SEAWAT) is used for groundwater flow simulation and SWI and the results compared with the developed analytical solution. Four scenarios are considered in the study, including; the sea-level rise (SLR), reduction in recharge, over abstraction, and combination after 50 years (2070). The analytical solution gave good results compared to the numerical one where Equiline 1 intruded to 103 and 101.66 km respectively at the base case. The results also gave a good agreement between numerical and the analytical solution for SLR due to climate changes by 52.80 cm where the Equiline 1 reached to 105 and 103.45 km. However, the reduction in aquifer recharge by 18.50% resulted in an intrusion for the Equiline-1 to 111 and 108.25 km from the shoreline. Over pumping due to the increase in population by 89% has increased the SWI to reach 121,110.31 km, while it reached 131 and 111.32 km at a combination of the three scenarios, which represents the highest threatening scenario. Also, the difference between the two solutions reached 1.30%, 1.48%, 2.48%, 8.84%, and 15.02%, respectively for the base case and four scenarios. For the current case study, the analytical model gave good results compared to the numerical one, so that the analytical solution is recommended for similar studies, which could save the time and capabilities of computer required for the numerical solutions.

The main goal of this paper is to evaluate the effect of color changes on the interior surfaces of a selected hall on the level of daylight, represented by the DF factor. A single-story hall was chosen as the reference building, in which daylight falls through the side windows and a skylight at roof level. Measurement of the level of daylight in the real state of the building (in situ) was carried out. The measurement took place when the external boundary conditions of the measurement were met (external state of the sky). A survey was conducted among users, in which they considered the visual perception of the environment and what colors would be suitable for the walls, ceiling, and floor in the working environment of the hall. The evaluation of the respondents who considered the color of the floor was interesting, and several agreed that the floor should be brown. After debugging the model for the simulation based on the actual state of the measurement, simulation calculations were performed with selected surface colors in the interior of the hall. Computational simulations were performed for changing calculation boundary conditions. Daylight Factors (DF) (%) were evaluated, namely minimum, maximum, and average DF values for 15 selected simulations. The calculations were performed in the RADIANCE simulation program. Simulations included the change in the surface color of the simulated wall and the current ceiling surface color, the color of the simulated ceiling surface and the current wall surface color, and the color of the simulated wall and ceiling at the same time. The floor color did not change during the evaluation; it was considered brown. Based on the evaluation of AHP, evaluations of the significance and comparability of colored areas were performed. The value of the average DF was chosen as the most important, the less significant minimum DF value was chosen, and the maximum DF value was considered in the last place. The results show that white, gray, green, or yellow walls, white ceiling, and brown floor were rated as the most suitable for the interior surfaces in the considered hall.

The rapid development of digital technologies presents both a challenge and an opportunity for strengthening sustainability in construction project management. Within the broader digitalization agenda, Building Information Modelling (BIM) and Artificial Intelligence (AI) have emerged as key tools for improving environmental and economic performance through resource optimization. While traditional methods for optimizing resources, costs, and time remain relevant, the integration of BIM and AI introduces innovative capabilities that support decision-making, process automation, and data-driven sustainability strategies. The aim of this research is to analyze the extent to which BIM and AI are used for sustainable resource optimization in construction and to quantify their potential impact on the optimization of costs, resources, and time in the sector. A cross-sectional survey was conducted among construction companies operating in three European markets, Slovakia, Slovenia, and Croatia. The collected data were analyzed using descriptive statistics, correlation and regression analysis, and statistical hypothesis testing to assess the significance of relationships between technology adoption and sustainability outcomes. The results confirm that BIM adoption is positively correlated with improved sustainability management and optimization practices, with usage levels varying by company size and project scale. In contrast, AI adoption remains at a low level, indicating untapped potential for broader application. These findings contribute to understanding the role of digital tools in driving sustainable transformation in the construction sector and highlight areas for further research and practical deployment. BIM demonstrates particularly strong correlations with cost planning (r = 0.983), resource planning (r = 0.964), and schedule planning (r = 0.867), while AI shows robust associations with cost planning (r = 0.925), schedule planning (r = 0.865), and resource planning (r = 0.809). The findings indicate that maximum effectiveness is achieved when BIM and AI are deployed in a complementary manner under skilled human oversight.

Large-diameter bored piles can safely transmit loads from structures by skin friction to the surrounding soil strata and end bearing at the bedrock layer, thereby providing a high compressive capacity. High-Strain Dynamic Testing (HSDT) provides a unique alternative technique to traditional Static Load Testing (SLT) for determining the static compressive resistance of the bored piles, considering its quicker performance and significant cost reductions. This article’s main objective is to numerically explore the performance of large-diameter bored piles during the HSDT and to understand their dynamic behavior under an axial compressive impact force. This research is based on testing pile foundations for reinforced concrete mixed-use towers in the coastal zone of New Alamein City, Egypt. The tested pile is a 1.20 m diameter bored pile. Numerical modeling is performed to simulate both the HSDT and the SLT for two piles at the same site. Non-linear axisymmetric finite element modeling is employed to validate both test records and develop some sort of matching between the two tests. As lumped models, the developed numerical models use the signal-matching process, which is conducted by varying and adopting the strength parameters and deformation characteristics of the ground or soil deposit and the soil–pile interface. The predicted load-displacement curves, developed from analyzing dynamic records employing the Modified Unloading Point (MUP) method, are consistent with the field records. The verified non-linear models are utilized to accomplish a comparative parametric analysis to better understand the drop-mass system aspects. The analysis results emphasize the significance of employing adequate impact energy (i.e., dropping height and mass) to move the pile top to a sufficient extent to mobilize its full resistance. However, a longer impact duration, i.e., larger mass, is more effective for achieving a deeper high-strain wave. The impact load should be developed by a larger drop mass with a lower drop height, not a smaller drop mass with a higher drop height. The results also indicate that, for relatively longer piles, the skin friction of the upper layers surrounding the pile shaft is fully mobilized, whereas the skin resistance of the lower layers is not fully mobilized, regarding the stress wave phenomenon effect. Finally, this study’s findings can be employed to develop guidelines and design procedures for the HSDT to be effectively performed on bored piles.