自1964年突水系数诞生以来，60年里尽管历经多次改良变化，但其主体一直是我国预测和评价底板突水危险性的主要方法，在保障带压开采生产安全及推动带压开采理论发展方面发挥了重要作用。回顾了突水系数法的传承与发展历程，总结突水系数法发展历史，认为突水系数法演变主要围绕“有效隔水层厚度”这一概念展开，临界突水系数无法确定限制了其他版本突水系数法的应用。从充水水源、强度、通道、时间、水质5个维度阐释了浅部与深部水害特征及异同，指出了深部开采条件下突水系数法局限所在；总结改良版本，指明深部条件下突水系数法改良方向：围绕针对性不强、隔水层厚度影响、考虑因素单一等进行改良。剖析学科概念，回归突水危险性评价命题本身，危险性评价应回答突水的可能性及突水的危害程度两部分内容；梳理突水危险性影响因素，指出突水系数法缺陷：对地质构造、含水层富水性等重要影响因素考虑不全面。展望未来，探讨了突水系数法发展方向，包括与其他理论及方法形成组合模型、选用大数据评价方法。随着信息化技术的进步及煤矿智能化建设进程的稳步推进，深度学习、机器学习以及配套方法等将成为主流评价方法，特别是物理机制约束下的大数据评价方法是未来攻关热点。

Since the birth of the water inrush coefficient in 1964, in spite of it has undergone many improvements and changes in the past 60 years, its main body has always been the main method for predicting and evaluating the danger of bottom water inrush in my country, and has played an important role in ensuring the safety of pressure mining production and promoting the development of pressure mining theory. The inheritance and development of the water inrush coefficient method was reviewed, and the development history of the water inrush coefficient method was summarized. It was considered that the evolution of the water inrush coefficient method mainly revolved around the concept of “effective aquiclude thickness”. The inability to determine the critical water inrush coefficient limited the application of other versions of the water inrush coefficient method. The characteristics and differences of shallow and deep water hazards are explained from the five dimensions of water source, intensity, channel, time and water quality, and the limitations of the water inrush coefficient method under deep mining conditions are pointed out; the improved version is summarized, and the improvement direction of the water inrush coefficient method under deep conditions is pointed out: improvements are made around the lack of specificity, the influence of the thickness of the impermeable layer, and the single consideration factors. Analyzing the concepts of the subject and returning to the proposition of water inrush hazard assessment itself, the hazard assessment should answer two parts: the possibility of water inrush and the degree of harm caused by water inrush; sorting out the factors affecting the hazard of water inrush, and analyzing the defects of the water inrush coefficient method: it does not fully consider important influencing factors such as geological structure and water-richness of aquifers. Looking into the future, the development direction of the water inrush coefficient method is discussed, including forming a combined model with other theories and methods and selecting big data evaluation methods. With the advancement of information technology and the steady progress of the intelligent construction of coal mines, deep learning, machine learning and supporting methods will become the mainstream evaluation methods. In particular, big data evaluation methods under the constraints of physical mechanisms are the future research hotspots.