Impact of Hydrological Regime and Temperature on Vegetation Growth Patterns in Floodplain Lakes Under Extreme Drought

Abstract The hydrological regime, particularly flooding duration and depth, is one of the primary driving factors for the vegetation pattern in floodplain lakes. Climate change‐induced droughts are extending shoal exposure times, potentially amplifying the impact of temperature on plant growth. However, the nonlinear interactive effects of hydrological and temperature factors on the vegetation growth pattern remain poorly understood. This study integrated a hydrodynamic model, an interpretable machine learning and a geographical detector to develop a robust framework for analyzing the individual and interactive impacts of these factors on the vegetation growth pattern. Applied to Poyang Lake—a Ramsar Convention conservation wetland—we found that temperature factors can exert stronger effect intensities than hydrological factors during extreme droughts. Interactive analyses revealed that flooding duration and cumulative temperature formed the strongest factor pair, with synergistic interactions exhibiting two distinct patterns—one stronger than each single factor yet weaker than their sum, the other outperforming their combined individual effects. Notably, under high‐temperature stress, the flooding duration exhibited a critical transition: its effect shifted from negative to positive as the duration increased. Furthermore, sensitivity analysis demonstrated that vegetation was more sensitive to the hydrological factor within these interactive effects, highlighting their dominant role in regulating vegetation dynamics under hydrothermal stress. By unraveling hydrothermal interaction synergies and critical threshold shifts, this study provides water resources managers with actionable insights to formulate adaptive policies for floodplain wetland conservation under climate change.