Abstract: The water resources–socio-economic–ecological environment system involves complex interactions among the water resources, socio-economic, and ecological environment subsystems. Quantitative research on the coordination degree of this system provides an important basis for understanding the operational state of composite systems, identifying weak links in coordination, and supporting regional sustainable development. Focusing on this field, this paper systematically reviews existing studies in terms of research needs, research evolution and key issues, as well as method classification and applicability. The review shows that the development of quantitative research on the coordination degree of the water resources–socio-economic–ecological environment system can be broadly divided into three stages: the stage of theoretical foundation and conceptual formation, the stage of methodological diversification and horizontal expansion, and the stage of methodological deepening and vertical breakthroughs. The first stage was mainly characterized by the proposal of composite system theory and the formation of the concept of coordinated development, gradually establishing a theoretical framework covering social, economic, natural ecological, and water resources composite systems. In the second stage, relevant methods expanded from fuzzy identification, comprehensive evaluation, and harmony degree evaluation to multiple directions, including distance coordination degree modeling, synergetics-informed system analysis, matching degree measurement, projection pursuit evaluation, and dynamic relationship identification, with continuously broadened methodological sources and application scenarios. The third stage shows a transition from the expansion of model applications to a greater emphasis on model standardization, conceptual deepening, methodological integration, and mechanism interpretation. Studies in this stage increasingly emphasize the standardization of model formulation, the clarification of conceptual boundaries, and the integrated application of different methods. On this basis, this paper argues that current research still faces several key issues, mainly including the need to further clarify the conceptual boundaries related to coordination degree, balance the universality and regional adaptability of indicator system construction, improve the robustness of weight determination and parameter setting, and clarify the applicability conditions, output forms, result interpretation, and selection criteria of quantitative methods. Taken together, these issues may reduce the comparability of research findings and may also weaken the explanatory capacity, robustness, and regional applicability of the methods used. Based on this understanding, the review organizes existing quantitative approaches to coordination degree measurement and coordination state diagnosis into three groups: multi-indicator comprehensive evaluation methods, coordination degree models and their extended evaluation methods, and coordination state measurement and diagnostic methods. Functionally, the three groups correspond to indicator integration, coordination measurement, and state diagnosis, and together they support the assessment of both coordination degree and coordination state in composite systems. The comparison of representative models, applicability, functional boundaries, and key considerations further suggests that these methods should not be regarded as interchangeable choices. Rather, their roles are often complementary, depending on research objectives, data conditions, and regional contexts, and they can jointly support multi-level and multi-objective coordination evaluation. Although the literature has established a substantial methodological foundation, further refinement is still needed in conceptual framing, indicator design, weight assignment, method selection and adaptation, and interpretation of results. Future research should strengthen conceptual clarification related to coordination degree, improve indicator systems that integrate universality and regional adaptability, enhance the transparency and robustness of weight determination and parameter setting, and clarify the applicability conditions, output forms, and interpretive boundaries of different quantitative methods. It should also promote the integration of multi-source data and the application of remote sensing monitoring, explore the combination of artificial intelligence and traditional evaluation models, and use these tools to support indicator redundancy identification and scenario projection. The findings of this review can provide references for method selection, comparative analysis, and framework construction in subsequent quantitative studies on the coordination degree measurement and coordination state diagnosis of the water resources–socio-economic–ecological environment system.