Wenxin Yang

Accurately assessing and predicting vegetation dynamics is of great significance for evaluating regional hydrological and ecological environments. This study focuses on the climate-sensitive Qinghai-Tibetan Plateau (QTP), aiming to reveal the spatiotemporal patterns, underlying driving mechanisms, and future trends of vegetation dynamics. The historical turning points of greening trends were identified using the running slope difference method, and the SHapley Additive exPlanations (SHAP) method was employed to analyze the key driving factors. An Xtreme Gradient Boosting (XGBoost) prediction model was constructed and validated, and then coupled with Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model ensemble data to project seasonal vegetation changes under different Shared Socioeconomic Pathways (SSP). The main conclusions are as follows: (1) Vegetation on the QTP showed an overall greening trend with significant spatial heterogeneity. Approximately 47.25% of the area exhibited no trend shift (NS), while 29.42% experienced a shift from greening to browning (GB), with most shifts occurring between 1990 and 2010. (2) Soil moisture and precipitation were the dominant driving factors, with contributions significantly higher than those of temperature, wind speed, and other variables, and they exhibited nonlinear interactive effects with the Normalized Difference Vegetation Index (NDVI). (3) In the future, vegetation is projected to show an overall increasing trend, with stronger responses in spring and autumn. The regional average rate of change is highest in spring, especially under the SSP5-8.5 scenario (17.8% for 2030–2060 and 26.4% for 2061–2100); in autumn, although the regional average rate of change is small, the internal spatial variability is significant. The humid regions in the eastern and southeastern parts of the QTP demonstrated more active greening across all seasons except winter, and high-emission scenarios are expected to exacerbate regional and seasonal differences. This study systematically reveals the adaptive dynamics and future scenarios of vegetation dynamics on the QTP, providing scientific support for the adaptation of alpine ecosystems to global change and the management of regional ecological security barriers.

To address the issue of existing automatic irrigation systems’ excessive reliance on electrical power and communication networks, a one-inlet, four-outlet Hydraulically Actuated Irrigation Control Valve (HAICV) was designed that operates based on water pressure variations. Its hydraulic characteristics and flow field features were investigated through experimental and numerical simulation methods. The results indicated that power–function relationships exist between pressure and flow rate, as well as between flow rate and head loss. The flow coefficient and resistance coefficient were found to range within [77.46, 81.06] and [15.94, 17.46], respectively. Dynamic simulations based on User-Defined Functions (UDF) revealed that during the opening process, the internal pressure of the valve spool remains high, with the primary pressure drop concentrated in the outlet region, and the low-pressure zone shrinks as the opening degree increases. A high-velocity band forms at the outlet, with jet flow and turbulence observed at small to medium openings, while the flow field stabilizes after full opening. The unique spool shape and non-straight flow passage structure of the HAICV result in relatively high energy loss, making it suitable for self-pressure irrigation systems. This study provides a theoretical foundation for evaluating its performance and broader applications.