Coastal systems are subject to water quality degradation through excessive anthropogenic nutrient loading and climate change. Common problems include hypoxia (low dissolved oxygen) and harmful algal blooms that threaten ecosystems, recreation, and fisheries. While multiple organizations are tasked with monitoring such systems, sampling is often sparse and disjointed, limiting our ability to assess water quality trends and to infer or verify mechanistic linkages. This forum will highlight recent research synthesizing large-scale spatial datasets to enhance our understanding of water quality dynamics. First, space-time geostatistics will be employed to synthesize data from multiple monitoring programs to characterize hypoxia in the northern Gulf of Mexico and cyanobacteria bloom dynamics in Lake Erie. Second, hierarchical modeling will be used to assess water quality and nutrient loading dynamics across North Carolina watersheds. In each study area, implications for watershed management and probabilistic forecasting will be discussed.