In order to improve land-use efficiency and solve traffic congestion, in recent years, many cities in China have focused on developing urban underground space resources and urban rail transit projects. However, there are various hidden risks for the sustainable development of the ecological environment and water resources. In this paper, a comprehensive investigation and analysis of spring water resources are carried out using the example of the karst area of Jinan, which is known as ‘spring city’. The engineering geological and hydrogeological conditions in Jinan are introduced in detail, and the geological causes of springs are analyzed. In addition, the causes of spring flow attenuation are revealed based on the investigation of the flow dynamics of spring water. Based on the current situation of traffic congestion in Jinan, the necessity and development statuses of rail transit construction are analyzed. Then, according to the different stratigraphic structure, limestone roof depth and karst water head depth, the Jinan spring area is divided into three research regions including the shallow limestone area, concentrated spring water area and deep limestone area. The spring protection problems faced by each region during the construction of urban railways are systematically described. In addition, the countermeasures and suggestions for spring protection are presented. This study aims to reduce the impact of urban rail transit construction on Jinan spring water so as to protect the Jinan spring. It also provides the water resources protection experience for urban rail transit construction in similar karst areas.

Accurate and quick acquisition of hydrogeological parameters is the critical issue for groundwater numerical simulation and sustainability of the water sources. A novel intelligent inversion method of hydrogeological parameter, based on the global optimization algorithm called the disturbance-inspired equilibrium optimizer (DIEO), is developed. Firstly, the mathematical model and the framework of DIEO are reported. Several types of mathematical benchmark functions are used to test the performance of the DIEO. Furthermore, the intelligent inversion of hydrogeological parameters of pumping tests is transformed into the global optimization problem, which can be solved by meta-heuristic algorithms. The objective function for hydrogeological parameter inversion is constructed, and the novel inversion method based on DIEO is finally proposed. To further validate the competitiveness and efficiency of the proposed intelligent inversion method, three types of case studies are carried out. The results show that the proposed intelligent inversion method is reliable for obtaining the hydrogeological parameters accurately and quickly, providing a reference for the inversion of parameters in other fields.

Asphalt mixtures exhibit complex mechanical behaviors due to their multiphase internal structures. To provide better characterizations of asphalt pavements under various forms of potential distress, a two-dimensional (2D) finite element simulation based on images of asphalt mixtures can be used to increase computational efficiency and reduce labor consumption. Nonetheless, using a representative image to eliminate the influence of dimension reduction from three dimensions to two dimensions is of great significance for attaining a reliable simulation result. Therefore, in this study, we investigated the consequence of dimension reduction for open-graded asphalt mixtures (denoted as OGFC-16), including a comprehensive characterization of these 2D models in terms of their morphologies and the similarities between them. This study aimed to reveal the variation in a 2D finite element simulation when applied to open-graded asphalt mixtures. Structural compositions, gradations, the aspect ratios of aggregates, and aggregate orientations were counted and calculated. In addition, the cosine similarity and structural similarity index measure (SSIM) were also calculated. Consequently, we performed a statistical analysis on the aforementioned indicators to quantitatively identify the discrepancy in the 2D images caused by dimension reduction. The results demonstrate that this 2D simulation might not be sufficient for representing the realistic mechanical performance of asphalt mixtures due to the remarkable variations in the image morphologies in different 2D images. However, the basic rules of stress behavior within structures can be accurately simulated. A compensative methodology for conducting a 2D simulation of open-graded asphalt mixtures should be based on a morphological characterization, considering structural compositions and the structural similarity index measure.