In project network planning, the correlation complexity of the processes is not only related to the immediately preceding and following processes, but also closely related to indirect adjacent processes. In the existing relevant studies, many scholars have considered the influence of direct adjacent processes but ignored the influence of indirect adjacent processes. In addition, the three-point time estimation method and Monte Carlo simulation are mostly used in the current research for the estimation of process duration, while less research exists on the estimation of process optimal duration under multi-objective constraints. Therefore, this paper proposes a buffer calculation model of critical chain based on adjacency information entropy. This methodology provides comprehensive consideration of the relationship between cost, quality, safety, environment and process duration, the influence of process’s resource demand intensity, resource constraints and process duration on the buffer size, the influence of the relay potential of mutual cooperation and cross construction between processes, as well as the influence of adjacent complexity of processes on the project construction schedule. The calculation example analysis shows that this method can improve the accuracy of the calculation of process safety time, reduce the influence of the complexity of process adjacency correlation on the project construction schedule, reasonably control the buffer size, and effectively shorten the planned project duration.

Based on Grey System Theory and the inverted normal quality gain-loss function, the inverted normal grey quality gain-loss function model is put forward. According to the constant compensation and hyperbolic tangent compensation, the grey quality gain-loss function model with nominal-type characteristics, larger-the-better characteristics and smaller-the-better characteristics is built. A multivariate grey quality gain-loss function model with multiple sub quality indexes and the concept of grey quality gain-loss cost are proposed. Case analysis is applied to the quality control of dam concrete construction, which verifies the applicability of the model and provides an important reference for research on the new theory of dam concrete construction quality control.

In view of the fact that the target values of some quality characteristics are grey, the grey quality gain-loss function model was applied in the analysis of the quality characteristics. At the same time, based on the analysis of engineering specifications and process capability, an optimization model of engineering specifications was proposed to minimize the expected total loss of each product and maximize the expected compensation with inspection costs, scrap costs and grey quality gain-loss into consideration. The optimal engineering specification can be obtained by using the optimization model. Through the example analysis and its application in dam concrete construction, the practicability of the model is verified, which provides an important reference for the research of the new theory of dam concrete construction quality control.

Inter-basin water transfer projects (IBWTPs) play a crucial role in addressing the uneven spatial and temporal distribution of water resources and ensuring water security in the receiving areas. However, these projects are subject to various risk factors during their operation. While risk management is critical, current research in this field lacks a systematic and dynamic approach. A three-dimensional measurement model for probability, loss, and risk value, based on Dempster–Shafer (DS) evidence theory, Bayesian networks, and the equivalence method, was established in this study and, in consideration of the engineering characteristics of the IBWTP, a dynamic transmission evolution model for risk is constructed. The applicability and effectiveness of the model are demonstrated through a case study of the Central Line Project of South-to-North Water Diversion (CLPSNWD). The results indicate that the system risk of the CLPSNWD is in an unstable state, with the key influencing factors being channel engineering risk, flood disaster risk, pipeline engineering risk, and water transfer (discharge) cross-structure risk. The research findings offer a novel approach to the quantitative analysis and evolution of risk and contribute to the further development of engineering risk management theory.

Extreme conditions will cause the water level of high fill canal segment to change suddenly, which will affect the velocity and pore pressure of the slope. In this paper, numerical method is used to study the influence of water level sudden change on seepage characteristics of high fill canal segment. HyperMesh software is used to establish the finite element model of typical high fill canal segment under complex foundation conditions. Through the combination of secondary development program and fluid-structure coupling calculation method, the fluid structure cou-pling effect of canal under sudden change of water level is analyzed in ABAQUS. The results show that when the water level changes suddenly, the pore pressure below the free water surface and the velocity near the free surface will be greatly affected.

In China, the water network project plays a pivotal role in optimizing water resources allocation, enhancing regional water resources carrying capacity, and bolstering high-quality economic development. This study is grounded in the spatial interconnection of water resources, serving as the foundation for constructing a spatial measurement model. Leveraging data from 558 panel samples encompassing 31 provinces (including municipalities and districts) in China between 2003 and 2020, this research unveils the inherent correlation between the establishment of the water network and economic as well as social development. The findings indicate the following: (1) Considering inputs, outputs, and nonconsensual outputs, regional disparities in the SBM (slacks-based measure) value of the water network exist, demonstrating an overall increasing trend annually. In 2020, the nationwide average benefit level of input–output in water network construction reached 0.603. (2) Moran’s I test, predicated on the weight matrix of spatial water transfer information, reveals a spatial positive autocorrelation. All tests pass the significance threshold of 5%, affirming the presence of spatial agglomeration due to project construction, operation, and the interconnectedness of water resources. (3) SDM (spatial Durbin model) regression analysis elucidates that per capita GDP, resource endowment, technological innovation level, consumption index, and average wage significantly influence the growth of water network efficiency. Specifically, per capita GDP and the consumption index exert negative influences. Moreover, aspects such as regional resource endowment, technological innovation level, industrial and agricultural water demand, average wage, and other spatial dependencies exhibit a notable positive spatial spillover effect. (4) The SDM model suggests that per capita GDP growth fails to yield a significant spatial spillover effect on neighboring regions. Instead, it highlights a substantial indirect effect and spatial dependence of government attention among regions. These analyses are instrumental in optimizing the water resources allocation network system and enhancing investment efficacy.