A head loss model for pressureless mesh filters used in farmland irrigation was developed by integrating the four basic test factors: irrigation flow, filter cartridge speed, self-cleaning flow, and initial sand content. The model’s coefficient of determination was found to be 98.61%. Among the basic factors, the total irrigation flow accounted for only 17.20% of the relatively small self-cleaning flow. The contribution of initial sand content was found to be the smallest, with a coefficient of only 0.0166. Furthermore, the contribution rate of the flow term was significantly higher than that of the initial sand content, with a value of 159.73%. In terms of quadratic interaction, the difference between the interaction term of flushing flow and filter cartridge speed, and the interaction term of filter cartridge speed and self-cleaning flow was 38.42%. On the other hand, the difference within this level for the interaction term between initial sand content and filter cartridge speed, as well as the interaction term between irrigation flow and self-cleaning flow, was 2.82%. Finally, through joint optimization of the response surface and model, the optimal values for the irrigation flow rate, filter cartridge speed, self-cleaning flow rate, and initial sand content were determined to be 121.687 m³·h⁻¹, 1.331 r·min⁻¹, 19.980 m³·h⁻¹, and 0.261 g·L⁻¹; the measured minimum head loss was found to be 21.671 kPa. These research findings can serve as a reference for enhancing the design of farmland filters and optimizing irrigation systems.

Mesh filters are frequently employed in water-saving irrigation fields. Studies addressing the method of cake formation and the characteristics of the cake during the mesh filter’s growing phase are still missing. One-way and orthogonal experiments were carried out using mesh filters with 220 μm and 320 μm aperture sizes as the research objects, taking particle concentrations, inlet flow, and growth phases as experimental factors. According to the variation rule of seed pressure drop in the formation process of filter cake, the growth process of filter cake is divided into four stages, which are as follows: slow blockage first and second stages (M1, M2), fast blockage stage (M3), and filter cake filtration stage (M4). Moreover, the size distribution, porosity (ε), pore-to-particle ratio (K_P), and median size (d₅₀) of the filter cake were used to represent the structural characteristics. The results show that the growth of filter cake was a process that started with the filling of mesh pores by intercepted particles and progressed to the filling of large-particle skeleton pores by subsequently filtered particles. During this process, the proportion of intercepted particles gradually decreased, while the proportion of filtered particles increased incrementally, and the median size (d₅₀) and porosity (ε) decreased. Meanwhile, the smaller the aperture size of the screen, the smaller the filter cake’s median size (d₅₀) was, but the larger the pore-to-particle ratio (K_P) was. As the flow rate increased, the porosity (ε) was augmented in the M1 and M2 stages; however, it decreased in the M3 and M4 stages. The concentration had a minor influence on the filter cake’s porosity. Lastly, the regression model for filter cake porosity under two aperture size conditions was established, based on factors such as flow rate, concentration, and growth stage. The coefficients of determination, R², for the model were 90.33% and 80.73%, indicating a good fit.

To investigate the movement characteristics of fish eggs and to clarify their movement behavior as flow conditions transition from slow to rapid, a hydrodynamics-based fish egg movement model was proposed. Indoor flume experiments under slow-flow conditions conducted previously by the research group were used as a basis. Twenty-three operating conditions with different water depths and discharges were designed, including fifteen rapid-flow conditions and eight slow-flow conditions. Numerical simulations were performed to examine the influence of flow velocity on fish egg movement under different flow conditions. The results show that fish eggs drift with the flow under different flow conditions, and their longitudinal velocity lags behind the flow velocity. At low flow velocities, the vertical velocity distribution of fish eggs is relatively concentrated. With increasing flow velocity, the vertical velocity becomes more dispersed in the high-velocity range. A power–law relationship exists between flow velocity and the trajectory slope of fish egg movement. When the flow velocity is lower than 0.5 m/s, the trajectory slope varies significantly with flow velocity; when it exceeds 1.2 m/s, the slope approaches a constant value. Water depth has a limited influence on fish egg velocity and trajectory slope under both slow-flow and rapid-flow conditions. By combining the relationships among flow velocity, trajectory slope, and suspension rate, a flow velocity of 0.3 m/s is identified as the critical flow velocity for maintaining the safe drifting of fish eggs. The findings provide technical support for ecological operation strategies aimed at fishery resource conservation.

The Jiahezi Reservoir is a typical plain reservoir constructed on a sediment-laden river in the mountainous region of Xinjiang. After 58 years of operation, it faces critical challenges—particularly insufficiently characterized sediment size distribution and siltation behavior—that continue to undermine its long-term operational performance. This study investigates particle-size distribution and depositional trends through integrated field sampling and two-dimensional (2D) numerical sediment modeling, using the Jiahezi Reservoir as a case study. Results show that the median particle size (d₅₀) is 0.027 mm, with 76.48% of the particles ranging from 0.005 to 0.25 mm, indicating predominantly fine-grained sediment. Particle size gradually decreases both downstream and laterally from the channel. Hydrodynamic sorting produces distinct spatial distribution patterns, with fine particles occupying more extensive areas than coarse ones. The sedimentation patterns within the reservoir area can be broadly categorized into four distinct zones. By analyzing sediment transport mechanisms and depositional characteristics, this study establishes a foundation for developing targeted strategies to enhance the reservoir’s operational longevity.

This study conducted physical model experiments based on a Box-Behnken response surface design to systematically evaluate the interactive effects of cutterhead rotational speed, tooth quantity, and operational depth on sediment disturbance and suction concentration across silt, clay, and sand. Results demonstrate that silt is highly sensitive to mechanical disturbance, clay exhibits a marked increase in yield near 225 r/min (based on the fitted response surface), and sand yield is speed-dominated but constrained by mechanical shielding effects. Integrating the entropy weight method with a soil-specific sensitivity coefficient, we propose the Soil-Modified Dredging Performance Index (SMDPI), Notably, the SMDPI model achieves a reliable engineering approximation, with the relative error between the predicted and physically measured SMDPI values strictly constrained below 10%. This research elucidates multi-factor coupled mechanisms of sediment disturbance and extraction, providing a theoretical and empirical framework for the intelligent regulation and dynamic parameter optimization of eco-friendly dredging operations across diverse soil conditions. From a management perspective, these findings translate into soil-specific operational guidelines and a potential conceptual framework for decision-support for reservoir operators seeking to balance dredging throughput against turbidity-related environmental compliance.