Optimizing Satellite Mission Requirements to Measure Total Suspended Solids in Rivers

Human modification of the landscape affects total suspended solid (TSS) concentrations in water. The quantitative extent of these changes remains poorly understood, partly because of the challenges associated with observing TSS dynamics in inland waters over large scales. While many current missions and sensors provide usable data to estimate inland water quality (e.g. Landsat series, VIIRS, and Sentinel-2), future missions present the opportunity to increase transferability and accuracy of TSS estimation. Here, we degrade assumed ideal spectral data to evaluate the optimal data quality for TSS retrieval using an optical sensor configuration. We also perform wavelet analysis and a river size distribution analysis to study temporal and spatial data quantity requirements, respectively. We find that while the highest resolution data always gives the best retrieval accuracy, some factors are more essential in TSS estimation than others and can simplify mission design. Specifically, fine hyperspectral resolution is key in improving retrieval accuracy and a finer spatial resolution allows exponentially more river surface area to be observed. A revisit period of approximately five days or less best captures TSS pulse events, such as floods. Understanding the optimal mission specifications for observing inland water quality, especially TSS, will assist in developing and proposing future optical satellite missions.