To promote sustainable hierarchical management, it is essential to understand the complex relationships within and underlying causes of supply–demand changes in water-related ecosystem services (WESs) across different spatial scales and landscape patterns. Consequently, the Optimal Parameters-based Geographical Detector (OPGD) and Multi-Scale Geographically Weighted Regression (MGWR) are used to analyze the factors influencing changes in WESs supply–demand. The findings indicate that (1) at the macroscale, population size, and economic activity are the main driving factors, while at the microscale, precipitation becomes the primary factor influencing fluctuations in WESs supply–demand. (2) Furthermore, over time, the influence of social factors becomes increasingly significant. (3) The explanatory power of a single factor typically increases as it interacts with other factors. (4) Abundant precipitation helps in the generation and maintenance of WESs, but intense human activities may have negative impacts on them. Therefore, we have made significant progress in identifying and analyzing the natural and human-induced driving forces affecting changes in WESs by deeply integrating long-term multi-source remote sensing data with the OPGD and MGWR models.