China’s Grand Canal was the world’s most extensive civil engineering project before the Industrial Revolution. This interview explores how the process of applying for and achieving World Heritage status has led to the improvement of the environment surrounding the Grand Canal and encouraged collaboration among canal cities spanning eight provincial administrations. It highlights the role of water heritage as a catalyst for improving the protection of historic landscapes and waterscapes as well as the Grand Canal’s cultural heritage. It also addresses how these efforts have supported the integrated development of canal cities. The Grand Canal remains a vital link that promotes balanced cultural, ecological and economic development, contributing to the sustainability of various canal cities across northern and southern China.

Data assimilation is an analysis technique which aims to incorporate measured observations into a dynamic system model in order to produce accurate estimates of the current state variables of the system. Although data assimilation is conventionally applied in continuous system models, it is also a desired ability for its discrete event counterpart. However, data assimilation has not been well studied in discrete event simulations yet. This paper researches data assimilation problems in discrete event simulations, and proposes a rollback based implementation of the Sequential Monte Carlo (SMC) method – the rollback based SMC method. To evaluate the accuracy of the proposed method, an identical-twin experiment in a discrete event traffic case is carried out and the results are presented and analyzed.