## 1 Introduction
Ecosystem GPP is fundamentally governed by the amount of absorbed photosynthetically active radiation (APAR) and the efficiency with which this radiation is utilized, known as light use efficiency (LUE) [25]. Consequently, remote sensing approaches for estimating GPP predominantly employ models based on the LUE framework [26]. Among the currently available remote sensing GPP datasets, the most extensively utilized and regularlyupdated are the GOSIF GPP dataset--derived from global OCO-2-based solar-induced chlorophyll fluorescence measurements--and the MODIS GPP product (MYD17A2H) from the Moderate Resolution Imaging Spectroradiometer. Empirical studies have demonstrated that the GOSIF dataset exhibits superior accuracy in GPP estimation [27]. This enhanced performance is attributed to GOSIF's capacity to directly capture photosynthetic activity variations via solar-induced fluorescence signals, which are not discernible through conventional vegetation indices based on apparent canopy characteristics [28]. In arid and semi-arid areas where vegetation exhibits relatively uniform and indistinct apparent characteristics, the GOSIF dataset proves particularly effective for characterizing GPP variation patterns across China's drylands. Recent investigations into global dryland ecosystems have substantially enhanced our comprehension of the relationships between moisture availability and GPP. In Central Asia, [PERSON] et al. utilized solar-induced fluorescence (SIF) data to demonstrate that RSM predominantly drives reductions in GPP during severe drought episodes, with pronounced effects observed in grasslands and sparsely vegetated areas [29]. [PERSON] et al. reported that temperature exerts a greater influence than RSM on GPP across approximately 60% of global vegetated areas; however, this trend reverses in arid and semi-arid areas, where RSM assumes greater importance [18]. [PERSON] et al. identified the vapor pressure deficit (VPD) as the principal limiting factor for GPP at 60% of global flux measurement sites, although RSM becomes the dominant constraint under extreme drought conditions [24]. Furthermore, [PERSON] et al. established that RSM critically regulates both PRE partitioning and E processes, thereby exerting dominant control on water use efficiency across more than 60% of terrestrial ecosystems worldwide [19]. Despite these advances, significant knowledge gaps persist regarding the coupled hydrological controls on GPP within China's distinctive arid and semi-arid ecosystems, which exhibit wetting trends contrary to the global pattern of drying. Unlike the widespread global drying observed since 2000, arid and semi-arid areas in China have experienced increasing moisture availability accompanied by concurrent rises in GPP, despite inherent variability in PRE [30; 31]. This study concentrates on key water resource variables--RSM, PRE, E, and root-zone soil moisture (RUM)--within China's arid and semi-arid areas. Employing a data binning approach to constrain variations in E and RUM, the research disentangles the interactions between RSM and PRE to assess their respective impacts on summer GPP from 2000 to 2022. To mitigate confounding effects of RUM and E, their standardized anomaly values were restricted within the range of \(-1\) to \(1\). The central hypothesis posits that if RSM predominantly governs GPP variability, elevated RSM levels would promote GPP enhancement irrespective of PRE fluctuations; conversely, if PRE primarily drives GPP changes, increased PRE would stimulate GPP growth independently of RSM conditions. The principal objectives of this research are (1) to elucidate the relationships between RSM or PRE and GPP and determine their influence on GPP variability; (2) to decouple the interdependence between RSM and PRE and examine their isolated effects on GPP; and (3) to investigate GPP dynamics across varying aridity gradients and assess the independent impacts of RSM and PRE on GPP under these differing conditions.