Hefang Jing

Velocity distributions in curved open-channel flows exhibit strong three-dimensionality and nonlinear behavior, posing challenges to both accurate prediction and physical interpretation. Using measured velocity data from nine discharge–water-depth combinations in a laboratory 180° open-channel bend, this study developed an integrated eXtreme Gradient Boosting (XGBoost)–SHapley Additive exPlanations (SHAP) framework, with multiple linear regression (MLR), random forest (RF), and a back-propagation neural network (BPNN) used for comparison. Leave-one-condition-out cross-validation was used to evaluate the predictive accuracy and stability of the four models. A stratified sampling strategy was then adopted to construct the training dataset, allowing information from all flow regimes to contribute to robust parameter calibration; the two data-partitioning strategies yielded broadly comparable predictive performance. Using models trained with stratified sampling, multidimensional model evaluation was further conducted using global statistical metrics, segment-wise predictive performance, held-out extreme-condition tests, and measured–predicted agreement, among other criteria, with XGBoost consistently showing the best performance. Multilevel SHAP analyses quantified global feature importance, pairwise interactions, streamwise variations in feature contributions, SHAP–PDP dependence relationships, and condition-specific attribution. The SHAP results indicate a two-level attribution structure in the model: hydraulic variables jointly define the global velocity baseline, and their contribution signs can switch between positive and negative. Spatial variables characterize cross-sectional velocity redistribution. Strong discharge–depth interaction is associated with width-to-depth-ratio-dependent adjustment of the bend flow field. The proposed framework establishes a complete experiment-driven prediction–mechanism interpretation workflow for sharply curved open-channel flow and provides new quantitative insight into model-represented multifactor hydrodynamic interactions in open-channel bends.

Soil salinization commonly prevails in global arid and semi-arid areas, shrinking farmland and endangering ecological, agricultural and social sustainability. Therefore, it is essential to develop effective strategies for salinized soil remediation. In this study, soil samples were collected from Nanliang Farm in Yinchuan, China. Compound microbial strains (CMS) and humic acid (HA) were selected as soil amendments. A total of eight treatments with different application rates of CMS and HA were set up in pot cultivation experiments, where oil sunflower was planted. The results showed that both amendments effectively elevated soil water content and chlorophyll content, as well as multiple physiological indices of sunflower. Meanwhile, they decreased soil total salinity, proline content and malondialdehyde (MDA) content. For single humic acid treatments, Treatment F1 achieved the optimal amelioration effect: it reduced soil total salinity by an average of 24.34%, and increased sunflower plant height, leaf area and aboveground fresh weight by 5.84%, 95.01% and 77.40%, respectively. Among the single CMS treatments, Treatment S3 performed best, with an average reduction of 31.04% in soil total salinity, and increases of 5.66%, 2.85% and 8.16% in plant height, leaf area and aboveground fresh weight correspondingly. Notably, among all eight groups, the control group CK1 exhibited the most prominent improvement effect, which was significantly superior to F1 and S3. This finding suggests that long-term application (one year or more) of CMS can produce an especially strong ameliorative effect on salinized soil.

The sudden contraction and expansion of the Yellow River section can induce flow separation and strong vortical structures due to abrupt changes in cross-sectional geometry, leading to low-velocity stagnation zones and enhanced sediment retention. To elucidate the mechanisms of vortex control and sedimentation reduction, a generalized three-dimensional water–sediment numerical model based on the Mixture two-phase flow approach was developed and validated using the field data. A total of 36 simulation cases were designed to systematically analyze vortex evolution, flow structure adjustment, and sediment transport responses. The results show that significant mainstream deflection and large-scale coherent vortices develop under contraction–expansion conditions, forming extensive stagnation zones that promote sedimentation and flow instability. Remediation measures can effectively weaken backflow intensity and improve sediment transport pathways by modifying local flow acceleration and shear characteristics. Compared with single measures, the combined strategy, through the synergistic effects of flow diversion and vortex control, reconfigures the mainstream structure, breaks down large-scale vortices, and enhances flow stability and sediment transport capacity. The optimal scheme improves flow velocity uniformity by 32.6%, reduces the deviation angle by 31.73°, and decreases sedimentation by 35.45%. This study clarifies the vortex dynamics mechanisms in contraction–expansion river sections and provides a theoretical basis for vortex control and sedimentation reduction in complex transitional reaches.

Sustainable management of sediment-laden rivers is essential for balancing flood control, ecological protection, and socioeconomic development. The Upper Yellow River, supporting 160 million people, faces escalating challenges in maintaining channel stability under intensified water–sediment imbalances. This study investigates the Sipaikou reach in Ningxia—a representative wandering channel with multiple mid-channel shoals—through integrated UAV-USV-GNSS RTK field measurements and hydrodynamic and sediment transport modeling. Field measurements reveal that mid-channel shoal morphology coupled with bend circulation governs flow division patterns, with discharge ratios of 44.16% and 86.31% at the primary and secondary shoals, respectively. Gaussian kernel density estimation demonstrates velocity distributions evolving from right-skewed to left-skewed around shoals, while spur dike regions display strong left skewness with concentrated main flow. Numerical simulations under six discharge scenarios indicate: (1) Head loss exhibits diminishing marginal effects at the primary shoal, an inflection point at a critical discharge at the secondary shoal, and superlinear growth in the spur dike region. (2) The normal-flow period represents the critical threshold for erosion–deposition regime transition. (3) Spur dike series achieve bank protection through main flow constriction and inter-dike low-velocity zone creation. These findings provide scientific foundations for sustainable flood risk management and ecological restoration in wandering rivers. The integrated measurement–simulation framework offers a transferable methodology for adaptive river management under changing hydrological conditions.

Vertical line source irrigation is a localized water-saving technique suitable for deep-rooted crops, but the geometric structure of the wetted bulb lacks a systematic analytical modeling method. This study established a simplified three-dimensional (3D) analytical model to predict the wetted volume under vertical line source irrigation conditions. First, the model determined boundary points based on an empirical wetting-front equation and fitted the wetting profile with ellipse–parabola functions to derive analytical expressions for area and volume. Then, using aeolian sandy soil as the research object, the model predicted that during 0–250 min of irrigation, the wetted pattern area increased from 80.0 cm² to 5050.6 cm², and the wetted volume increased from 251.3 cm³ to 208,014.4 cm³. At 250 min, the lower, middle, and upper volume components accounted for 67.3%, 24.2%, and 8.4%, respectively. Finally, the model was validated using loam soil, and the results showed good agreement between the calculated and measured values. The model requires only simple input and enables fast computation. It effectively characterizes the three-dimensional spatiotemporal variation of the wetted bulb and provides a theoretical reference for the design of pipe spacing and irrigation quota.

In this paper, we first present a necessary and sufficient condition for a class of block matrices to be positive semidefinite. Second, we demonstrate the significance of a known inequality (as presented in [5]) through a norm inequality. Finally, utilizing the polar decomposition, we provide a functional version of a singular value inequality.

Desertification is a serious environmental and ecological issue. Vegetation patterns can not only reveal the distribution characteristics and growth laws of vegetation but also provide early warning signals for desertification. In arid and semi-arid regions, where rainfall is limited, improving the utilization rate of water resources is crucial for the growth and distribution of vegetation. This study, based on the Klausmeier model, establishes a vegetation-water model that includes terms for increased infiltration and reduced evaporation was developed. First, the conditions for vegetation pattern formation at equilibrium points were derived using linear stability analysis and the Turing instability theory. Second, the amplitude equation of the model was derived, and the relationship between the model parameters and pattern structures was obtained, using the multi-scale analysis method. Finally, numerical simulations validated the theoretical derivations and investigated the impact of improved water resource utilization on vegetation pattern structures. The results indicate that increasing water resource utilization can induce pattern structure transitions. As water resource utilization increases, vegetation patterns shift from spot to mixed to stripe patterns. This implies an enhancement in the robustness of the vegetation ecosystem, providing significant guidance for desertification control and vegetation restoration in arid and semi-arid regions.