Detecting river pollution incidents is challenging for wastewater management, especially with spatially sparse monitoring and transient events. This study introduces a framework using remote sensing, ground-based data, and social media/news data, in a complementary approach. Satellite remote sensing enables frequent, spatial observation of river systems to inform future-ready strategies. The approach evaluates each data source against 10 criteria, such as timeliness and coverage, for effective pollution management in UK rivers. The framework is demonstrated through a documented pollution incident on the River Sheppey. High-resolution PlanetScope imagery was analysed using spectral indices for turbidity (NDTI), chlorophyll-a (NDCI), and surface water dynamics (NDWI). Statistical testing determined whether the reported incident produced a detectable satellite signal. These results were evaluated alongside Environment Agency observations and Met Office data, to examine temporal alignment and uncertainty. Social media and online news provide early alerts and track the recurrence of pollution events within a broader data fusion approach, triggering targeted interrogation of remote sensing and regulatory datasets. Initial results indicate that satellite-derived indices can detect measurable changes associated with the reported incident, while also highlighting limitations. The study shows how integrated data approaches strengthen incident identification, regulatory oversight, and operational response by regulators and water companies.