This study is global in scope, providing a framework with regional applicability. We validate the methodology across 40 river basins and Lakes Victoria and Nasser, ensuring broad relevance under diverse hydrological conditions. This study aims to evaluate the performance of traditional spatial-domain decorrelation filters at the basin scale. We proposed a collaborative filtering framework to integrate and enhance filter stability while addressing the boundary issues inherent in conventional filters. We summarized the operational principles of the collaborative filter and provided filtering recommendations across different latitudes, offering more robust solutions for small-scale regions. Our analysis reveals that the synergistic architecture effectively overcomes boundary effects inherent in traditional filters through a latitude-dependent strategy. The proposed YAV mode is critical for low-latitude regions, effectively mitigating high-frequency striping noise to recover masked tropical signals and enable the monitoring of small-scale lakes. Conversely, the SAY and SAV modes ensure signal stability in mid-to-high latitudes by avoiding leakage. Quantitative results demonstrate that this framework improves the proportion of high signal-to-noise ratio results by 10 %–15 % in noise-prone areas. Ultimately, this approach enhances the detection of extreme hydrological events and offers a robust, extendable baseline for future gravity missions. • A synergistic framework integrates spatial filters for robust noise removal. • Latitude-dependent strategy overcomes boundary effects for basin signals. • Effective destriping enables monitoring signals in small-scale lakes. • Synergistic architecture is extendable to future gravity missions.
Wu et al. (Tue,) studied this question.