## 1 Introduction  
Droughs are among the most complex natural phenomena worldwide and are caused by various factors, including relative humidity, temperature, precipitation scarcity, and wind speed [1]. With the intensification of global climate change, various extreme events are becoming increasingly severe and frequent. Droughs are a particularly serious risk to natural ecosystems and the sustainable development of human society [2]. For ecosystems, the impact of a drought is evident: vegetation withers, and ecosystem structures are disrupted, further leading to a reduction in ecosystem service functions [3, 4]. Subsequently, ecosystems accelerate or mitigate climate change through feedback mechanisms [5]. Most future climate projections in the Intergovernmental Panel on Climate Change's Sixth Assessment Report (IPCC-AR6) indicate increased heatwaves, intensification of evaporation, and scarcity of precipitation, leading to more severe regional drought [6, 7, 8]. Previous research has indicated that water availability significantly affects vegetation growth in most temperate regions [9; 10]. The growth of vegetation in temperate regions is significantly reduced by droughs, which affects ecosystem productivity. However, due to the diversity of tropical ecosystems, there is still no consistent conclusion regarding the effects of droughs on tropical vegetation growth. Therefore, the extreme droughs of 2005 and 2010 in the Amazon region have garnered widespread attention [11; 12]. Through long-term monitoring observations [13], field manipulation experiments [14], eddy covariance-based carbon flux observations [15], and large-scale remote sensing inversion [16], it was concluded that changes in hydrothermal conditions leading to drought events are one of the key factors causing variations in carbon cycling in tropical forests [17]. Tropical forest ecosystems are also inevitably expected to suffer from drought impacts [18]. However, field experiments and investigations require a lot of manpower and time [14; 19]. Moreover, tropical regions experience high cloud cover throughout the year, limiting remote sensing methods [20]. Consequently, models have been essential tools for understanding and forecasting the responses of tropical forests to climate change [21; 22]. Completed studies have focused on carbon fluxes, water fluxes, biomass, and the productivity of rubber forests, such as using the soil vegetation atmosphere transfer (SVAT) model to simulate CO\({}_{2}\) and H\({}_{2}\)O fluxes in the canopy of rubber trees and the process-based Land Use Change Impact Assessment tool (LUCIA) to simulate the biomass and rubber yield of rubber plantations at the scale of individual trees, plots, and landscapes [23; 24]. The community Land Model Version 5 (CLM5) has also been used to simulate rubber and has achieved excellent results in terms of rubber yield and carbon flux simulation, and has also been shown to capture the seasonal fluctuations of rubber production well. However, the cross-validation period is relatively short, which fails to reflect simulation accuracy for natural rubber plantation ecosystems under a longer time scale or during climate change [25]. As a significant component of terrestrial ecosystem productivity and surface carbon cycling, gross primary productivity (GPP) represents the expression of photosynthesis at the ecosystem level, determining the total initial carbon input into the ecosystem [26]. As the largest carbon reservoir in terrestrial ecosystems, tropical forests exchange the most carbon dioxide with the atmosphere, constituting about two-thirds of the terrestrial vegetation biomass and playing an important role in the global carbon cycle [27; 28; 29]. However, due to the complex habitats, community composition, and abundant biodiversity of tropical natural forests, research on these areas is relatively challenging and associated with significant uncertainties.