Remote sensing of aquatic nutrients from proxy estimation to integration with process models

Leveraging its capability for large-scale, repeated monitoring, remote sensing has increasingly supported nitrogen and phosphorus estimation in surface waters. However, the evolution of this field from proxy-based nutrient retrieval to integration with process-based models remains insufficiently synthesized. Here we review remote sensing approaches for estimating aquatic nutrients, with emphasis on their roles in supporting process-based modeling, and compare their methodologies, applications, and limitations. At the watershed scale, remote sensing supports land use mapping and pollution load estimation, identifying nutrient sources and constraining transport simulations. At the lake scale, it provides continuous observations and water quality products that inform hydrodynamic and water quality models. At the field and interface scales, remote sensing helps identify hotspots of nutrient loss by capturing the heterogeneity of management practices. Despite these advances, nutrient estimation remains constrained by proxy relationships and spatial scale. Future research should integrate remote sensing with hydrodynamic and biogeochemical models to constrain nutrient fluxes and improve mechanistic understanding of aquatic nutrient cycling. At the watershed scale, remote sensing maps land use and estimates pollution loads; at the lake scale, it provides water quality data for models; at field and interface scales, it identifies nutrient-loss hotspots, based on a review of remote sensing to approaches aquatic nutrients.