<p>Amid the digital-ecological convergence, it is vital to investigate the spatiotemporal differences in China’s provincial water resource carrying capacity (WRCC) and explore the enabling pathways of digital ecology. This study focused on 30 Chinese provinces and used the technique for order of preference by similarity to ideal solution (TOPSIS) method, particle swarm optimization (PSO), and extreme learning machine (ELM) to estimate WRCC and analyze its spatiotemporal evolution. Grounded in institutional logic theory and integrating necessary condition analysis (NCA) with panel qualitative comparative analysis (panel-QCA), the institutional configurations that enable the digital ecology to enhance WRCC were investigated. WRCC in China demonstrated a fluctuating upward tendency over time, characterized by a spatial pattern in which the eastern region surpassed the central and western regions, with marked intra-regional disparities. WRCC exhibited a clear positive spatial autocorrelation. Digital infrastructure, government, economy, capability, and society did not serve as necessary conditions for distinguishing between high and low WRCC; rather, improvements in WRCC arise from the synergistic effects of multiple institutional logics. Three configurations linked to high WRCC included the government-market-society-, the market-society-, and the government-society-driven models. One configuration associated with low WRCC was characterized as the government-market-society-absence type. The consistency of these configurations showed some fluctuations accompanied by marked regional disparities in their distributions. The digital society has emerged as a critical factor in enhancing WRCC. These conclusions deepen our understanding of provincial water resources across China and offer insights into the optimization of regional digital-ecological environments to foster high-quality water resource development.</p>