翻译：内河水路运输具有承载量大、单位成本低、占地资源少等比较优势在我国综合交通运输体系中占据了重要地位。在生态优先、绿色发展理念指导下航道资源的优化配置和综合高效利用已成为水路交通运输行业重点关注的主题之一。面向多源异构的通航要素亟需揭示其时空演化特征和趋势构建多因素耦合的航道通过能力评价体系与计算模型为内河水运高效开发利用奠定理论基础。本文以内河航道通过能力模型为目标研究了典型通航要素时空演化建

River transportation has the advantages of high carrying capacity, low unit cost, and minimal land resource usage, and occupies an important position in China's comprehensive transportation system. Under the guidance of the concept of "ecological priority and green development," the optimization and efficient utilization of waterway resources have become one of the key focuses of the water transportation industry. Facing the multi-source and heterogeneous navigation elements, it is urgent to reveal their spatiotemporal evolution characteristics and trends, and to establish a multi-factor coupled waterway capacity evaluation system and calculation model to lay a theoretical foundation for the efficient development and utilization of inland water transportation.

This article aims to develop a model for inland waterway capacity and investigates the spatiotemporal evolution modeling methods of typical navigation elements, revealing the coupling mechanism of multiple factors and forming a predictive model and evaluation method of waterway capacity under constraints. The paper focuses on three typical navigation elements: hydrological meteorology, ship traffic flow, and navigational aids. Based on data-driven and coupled system modeling methods, spatiotemporal evolution modeling research is conducted. The paper proposes a short-term water level prediction method based on neural network and local Kalman filtering, a ship trajectory data repair method based on bidirectional long short-term memory network (BLSTM-RNN) model and an evaluation and calculation method for navigational aid effectiveness. A waterway capacity evaluation system and calculation method based on "waterway conditions-ship traffic flow-navigational services" are established, revealing the short-term evolution trend of waterway capacity under constraints and providing technical support for inland waterway capacity evaluation and long-term planning. The specific research contents are as follows:

(1) Analysis and modeling of the coupling relationship of hydrological meteorological conditions. Based on typical hydrological meteorological data, the correlation theory and nonlinear modeling method are used to repair water level and visibility data through RNN and ARIMA methods, and the correlation relationship is obtained. Taking the Wuhan section of the middle reaches of the Yangtze River as an example, the accuracy and reliability of the model are verified, and the coupling coefficient of the hydrological meteorological subsystem is calculated to construct the hydrological meteorological subsystem.

(2) Modeling and feature expression of ship traffic flow. Using ship historical trajectory data as samples, a trajectory data repair model based on BLSTM-RNN is constructed, and ship trajectory data multi-point repair is realized using spatiotemporal trajectory context information, and the influence of waterway meandering on trajectory data repair accuracy is analyzed. Ship traffic flow features are extracted based on ship spatiotemporal trajectory data, and ship behavior features are mapped to the structural features of traffic flow through feature fusion. Combining the analysis of ship berthing point distribution aggregation, a relationship model between traffic flow features and ship distribution is established.

(3) Research on navigational aid effectiveness model. Based on spatiotemporal data of navigational aid operation and maintenance, the causes and mechanisms of navigational aid drift under complex conditions are revealed. Based on navigational aid environmental variables, a navigational aid risk assessment model is established, laying a theoretical foundation for improving navigational aid effectiveness.

(4) Calculation model of waterway capacity with multi-system coupling. Guided by the evaluation criteria of waterway capacity, the coupling analysis of hydrological meteorological, ship traffic flow, and navigational aid subsystems is performed to obtain the influence relationship between subsystems and the impact of subsystems on waterway capacity. Based on quantitative constraint conditions and information fusion, a multi-factor waterway capacity prediction method is proposed. Combined with the data-driven prediction mechanism of the three subsystems, short-term prediction and trend analysis of inland waterway capacity are realized.