# Quantitative Analysis of Influencing Factors on Changzhou Ship Lock Capacity
## 1 Introduction  
A ship lock is a crucial navigation facility designed to overcome concentrated water level differences, enabling the passage of vessels and serving as pivotal nodes in inland waterway transportation [1, 2]. With the rapid development of the water transportation industry, freight demand has been increasing annually, revealing the growing issue of insufficient ship lock capacity [3]. For instance, the Three Gorges Lock experienced an early saturation of its designed capacity by 19 years. The overloading has become a norm, leading to substantial vessel backups [4, 5]. The Changzhou Hydraulic Complex, as the final cascade lock on the main shipping route of Xijiang River, represents the \"throat\" of this golden waterway. In 2019, its freight volume surpassed that of the Three Gorges Lock for the first time, ranking it as the world's busiest natural waterway. In recent years, it has approached saturation, and the inadequate Changzhou ship lock capacity has become a bottleneck restricting the development of Xijiang River's golden waterway [6]. Investigating the influencing factors of the ship lock capacity can provide a theoretical basis for optimizing ship lock scheduling, which would help unleash potential throughput and alleviate congestion at the ship locks [7]. Scholars have extensively studied the factors affecting the ship lock capacity through methods such as formula calculation [8, 9], factor evaluation [10, 11], simulation [12, 13, 14, 15, 16], and the analytic hierarchy process (AHP) [17, 18, 19, 20]. The \"Code for Master Design of Shiplocks\" provides a formula for calculating ship lock capacity [21]; however, most of the factors involved in the calculation are statistical data, which do not offer a direct representation of the influencing factors on ship lock capacity [22, 23]. According to the elements involvedin ship lock passage, the influencing factors of ship lock capacity can be divided into ship lock influencing factors, ship influencing factors, management factors, and environmental influencing factors [17]. [PERSON] et al. analyzed the factors affecting the cargo handling of the Three Gorges Ship Lock based on ship tonnage changes, focusing on three aspects: ship lock, ship, and the organization of ship lock operation [24]. Based on the measured hydrological data and model test results of the Changzhou ship lock, [PERSON] et al. observed that a decrease in water level leads to an overall downward trend in the tonnage of navigable ships through the ship lock [6]. Quantitative analysis of ship lock capacity mostly employs simulation and AHP. [PERSON] et al. established a traffic simulation model for single-level, inland multi-lane ship locks, incorporating traffic operation rules to quantitatively analyze the operational status and maximum ship lock capacity under various conditions [12; 13; 14; 15]. Based on AHP, [PERSON] et al. constructed a hierarchical structure model for the influencing factors of ship lock capacity, determining the weight values of each factor [17]. [PERSON] integrated fuzzy logic, AHP, and technique for order preference by similarity to an ideal solution (TOPSIS) to create a decision-making model that aids in improving ship lock capacity, mitigating potential biases that may arise from the AHP alone [18; 19; 20]. The factors influencing ship lock capacity are numerous, and existing studies have analyzed these factors from various perspectives. However, there are still some shortcomings in the quantitative analysis of ship lock capacity. They are specifically manifested in the following aspects: (1) Existing studies primarily focus on importance judgments or weight analysis, with less emphasis on the quantitative analysis of these factors. (2) Quantitative analyses are mostly based on simulation and AHP, with data derived from simulations or surveys lacking analysis based on enormous real data, thus compromising credibility.