Abstract: Long-distance water diversion and transfer projects are characterized by extensive longitudinal spans and complex topographic, geological, and environmental conditions along the alignment. Traditional route selection methods face challenges such as cumbersome workflows, low efficiency, and inconsistent design quality. To address these challenges, this study investigated the alignment design of long-distance water diversion and transfer projects. Firstly, a rapid construction and efficient analysis method for regional geospatial information was proposed based on low-altitude Unmanned Aerial Vehicle (UAV) photogrammetry. Secondly, to integrate expert-driven subjective judgment with the objective evaluation of key sensitive factors, while also establishing a more robust decision-making mechanism for route selection, a systematic framework of fundamental principles, constraint categories, and their associated factors applicable to long-distance water diversion and transfer projects was established. Within this framework, the relevant constraint categories and factors were identified to serve as the basis for subsequent weighting analysis. In terms of the subjective weight analysis of constraint factors, an Analytic Hierarchy Process (AHP) hierarchical structure model for alignment was developed, in which a judgment matrix was constructed from expert assessments, and the normalized eigenvector satisfying the consistency requirement was derived to obtain the subjective relative weights of the factors. In terms of the objective weight analysis, a sample selection scheme was proposed according to the three standards of feasibility, representativeness, and distinctiveness. By screening and refining feasible alternatives from the preliminary scheme library, a sample set of route options was obtained, and the entropy weight method was employed to calculate the objective relative weights of the constraint factors. On this basis, the subjective and objective weights were linearly integrated and further combined with BIM–GIS data fusion, spatial standardization of constraint factors, and a comprehensive scoring and evaluation process, thereby developing a BIM–GIS-based intelligent alignment method incorporating subjective-objective integrated weighting using AHP and the entropy weight method. Finally, an intelligent route selection platform for long-distance water diversion and transfer projects was developed and successfully applied to a case study in southwestern China. The results showed that low-altitude UAV photogrammetry enabled the rapid acquisition and processing of large-scale geospatial data, which was efficiently integrated into the intelligent route selection platform for long-distance water diversion and transfer projects. This enabled three-dimensional visualization and effectively supported the flexible utilization and multidimensional analysis of geographic data during the intelligent alignment design stage. By comprehensively considering six major route selection constraint categories—geology, environment, cost, operation, water intake conditions, and terrain—along with eight corresponding constraint factors, the platform generated multiple alignment schemes using the BIM–GIS-integrated intelligent alignment method. The results satisfied the design requirements and further supported localized three-dimensional, interactive, and dynamic route optimization. Moreover, the platform not only automated complex data processing but also enhanced decision-making transparency, thereby improving the overall reliability of the alignment results. The findings indicate that this paper integrates the subjective–objective weighting method for route selection constraint factors with the fusion and analysis of multi-source spatial data, thereby developing a standardized methodology and workflow for alignment design. The proposed approach provides methodological support for intelligent alignment in long-distance water diversion and transfer projects. Additionally, the integration of BIM and GIS offers technical support for interactive dynamic adjustment of routing schemes and the automatic calculation of key project quantities. The engineering application of the platform demonstrates that, for tasks of comparable scale, the system required only half the time of traditional manual route selection, reducing the overall design cycle by 50%. This significantly enhanced the efficiency and intelligence of route selection and design, providing a valuable digital twin solution for intelligent alignment design in long-distance water diversion and transfer projects.