## 5 Conclusions  
A hydraulic model of a large-scale irrigation pipeline network was developed using EPANET, and the hydraulic reliability of the network was analyzed under three water supply modes: segmented, uniform, and random water supply. The key findings are as follows:  
(1) In the large-scale irrigation pipeline network, the traditional segmented water supply mode leads to significant pressure head fluctuations and flow deviations among branch pipes, with flow velocities generally exceeding the economic flow rate. Additionally, the pressure head node fails to meet the minimum required node head (\(H_{min}\)). In the uniform water supply mode, pressure head fluctuations and flow deviations among branch pipes are reduced, and flow rates generally align with their economic flow rate. However, many nodes still do not reach \(H_{min}\). In the random water supply mode, the proportion of nodes meeting \(H_{min}\) is higher than that in the uniform water supply mode. Pressure head fluctuations and flow deviations in the pipeline network are not significantly different from those in the uniform water supply mode, although the actual flow rates of some branch pipes slightly deviate from their economic flow rate. (2) In the segmented water supply mode, the reliability of water supply uniformity, node pressure head, and flow velocity in the pipeline network are 4.04, 0.84, and 0.64, respectively. In the uniform water supply mode, the reliability of water supply uniformity and flow rate is the highest, with values of 4.76 and 4.49, respectively. However, the reliability of node pressure head is lower than in the segmented water supply mode, at 0.94. In the random water supply mode, the node pressure head reliability is the highest, at 1.54, while the reliabilities of water supply uniformity and flow rate are 3.99 and 2.50, respectively. Overall, the hydraulic reliability of the pipeline network is highest in the uniform water supply mode (2.83), followed by the random water supply mode (2.49), with the segmented water supply mode exhibiting the lowest reliability (1.79). The innovations of this study lie in the following aspects: First, while previous research has primarily focused on small-scale pipeline systems, this study addresses large-scale irrigation pipeline networks characterized by longer pipe lengths and larger diameters. Second, conventional pipeline systems typically operate with a constant water supply and pressure. In contrast, this study introduces different water supply modes based on crop water requirements, dynamically adjusting water delivery according to varying demands. The results of this study provide valuable insights for the selection of water supply modes and the hydraulic reliability assessment of large-scale irrigation pipeline networks. This research represents an initial exploration of a large-scale self-pressure head drip irrigation pipeline network system in Xinjiang, China. In practical applications, it is essential to consider various pipeline network configurations, as well as factors such as water quality and economic considerations. To enhance the hydraulic performance of water distribution networks, a comprehensive strategy integrating cutting-edge technologies can be implemented. Guided by methodologies such as artificial intelligence and recommendations from DeepSeek [46], the optimization process begins with intelligent network design and management. By synergizing Geographic Information Systems (GIS) and Supervisory Control and Data Acquisition (SCADA) systems, dynamic zoning adjustments can be achieved through real-time analysis of water consumption patterns. Hydraulic modeling tools like EPANET further enable precise simulation of pressure distribution and topology optimization. For intelligent control, variable-frequency pump stations can be deployed to adjust pump speeds based on real-time pressure feedback, balancing energy efficiency with stability, while pressure-reducing valves (PRVs) installed at critical nodes mitigate leakage risks and stabilize pressure.