Insight into the water resource carrying capacity of the central water tower in China: Integrating the driving-pressure-state-impact-response frame and obstacle degree recognition

Water resource carrying capacity (WRCC) is crucial to regional development and sustainable growth. The Qinling Mountain (QLM) is an important area for water source protection and conservation of the Yangtze River and the Yellow River. Therefore, it is vital to investigate the WRCC in the QLM region to preserve the ecosystem. This study established a driving force-pressure-state-impact response (DPSIR) model and coupled it with the ideal solution similarity ranking technique (TOPSIS) to evaluate the WRCC of the QLM, the driving factors affecting the WRCC of the QLM were identified by establishing a obstacle degree (OD) model. The results indicated that the WRCC in the QLM region exhibited an overall upward trend in the period, with four phases identified: the initial growth phase, rapid development phase, stable rising phase, and steady fluctuation phase. Since the promulgation of the relevant ecological protection policy in 2007, industrial development in the southern Qinling Mountains has been restricted, and the rapid recovery of the ecological environment has made the change trend of WRCC in the southern QLM is 8.23 % faster than that in the northern. Moreover, all subsystems demonstrated a declining trend through the obstacle degree model, with the impact subsystem displaying the most significant reduction, ranging from 65.3 to 3.8. This suggested that ecological protection measures achieved notable results. Reassigning the weighted calculations based on the obstacle degree model, the factors affecting WRCC exhibited significant temporal differences. The development of an extensive economy characterized by high energy consumption, high pollution, high cost, and low efficiency was the primary constraint from 2000 to 2009, while the expansion of urbanization became the main obstacle from 2010 to 2021. This study provides new insights into the spatiotemporal changes in WRCC in the QLM region, revealing the mechanisms driving regional WRCC, and also provides a reference for the evaluation of WRCC in other regions.