Disruptive Innovations and Disruptive Assurance: Assuring Machine Learning and Autonomy

Autonomous and machine learning-based systems are disruptive innovations and thus require a corresponding disruptive assurance strategy. We offer an overview of a framework based on claims, arguments, and evidence aimed at addressing these systems and use it to identify specific gaps, challenges, and potential solutions

Multispectral in Situ Measurements of Organic Matter and Chlorophyll Fluorescence in Seawater: Documenting the Intrusion of the Mississippi River Plume in the West Florida Shelf

We performed multispectral, in situ fluorescence measurements of detrital colored organic matter (COM) and chlorophyll a (Chl a) in surface waters of the West Florida Shelf using the Wet Labs spectral absorption and fluorescence instrument (SAFIre). Continuous underway measurements allowed simultaneous mapping of the dispersal pattern of riverine organic material and Chl a on the shelf. We used two fluorescence emission ratios to differentiate between riverine and marine COM. The data showed unusually high concentrations of COM offshore. These were attributed to an offshore extension of the Mississippi River plume. Comparisons between in situ Chl a concentrations measured with the SAFIre and Chl a values obtained from the sea-viewing wide field-of-view sensor (SeaWiFS) satellite data using OC4 and MODIS algorithms showed that, although both algorithms overestimated Chl a, MODIS performed better than OC4, particularly in areas with high COM concentrations. Analysis of the relationship between Chl a and COM concentrations within the study area showed regional variability probably caused by differences in river source

Mobile Device Application for Monitoring Cyanobacteria Harmful Algal Blooms Using Sentinel-3 Satellite Ocean and Land Colour Instruments

Cyanobacterial harmful algal blooms (cyanoHAB) cause human and ecological health problems in lakes worldwide. The timely distribution of satellite-derived cyanoHAB data is necessary for adaptive water quality management and for targeted deployment of water quality monitoring resources. Software platforms that permit timely, useful, and cost-effective delivery of information from satellites are required to help managers respond to cyanoHABs. The Cyanobacteria Assessment Network (CyAN) mobile device application (app) uses data from the European Space Agency Copernicus Sentinel-3 satellite Ocean and Land Colour Instrument (OLCI) in near real-time to make initial water quality assessments and quickly alert managers to potential problems and emerging threats related to cyanobacteria. App functionality and satellite data were validated with 25 state health advisories issued in 2017. The CyAN app provides water quality managers with a user-friendly platform that reduces the complexities associated with accessing satellite data to allow fast, efficient, initial assessments across lakes

Towards Integrated Modeling of the Long-term Impacts of Oil Spills

Although great progress has been made to advance the scientific understanding of oil spills, tools for integrated assessment modeling of the long-term impacts on ecosystems, socioeconomics and human health are lacking. The objective of this study was to develop a conceptual framework that could be used to answer stakeholder questions about oil spill impacts and to identify knowledge gaps and future integration priorities. The framework was initially separated into four knowledge domains (ocean environment, biological ecosystems, socioeconomics, and human health) whose interactions were explored by gathering stakeholder questions through public engagement, assimilating expert input about existing models, and consolidating information through a system dynamics approach. This synthesis resulted in a causal loop diagram from which the interconnectivity of the system could be visualized. Results of this analysis indicate that the system naturally separates into two tiers, ocean environment and biological ecosystems versus socioeconomics and human health. As a result, ocean environment and ecosystem models could be used to provide input to explore human health and socioeconomic variables in hypothetical scenarios. At decadal-plus time scales, the analysis emphasized that human domains influence the natural domains through changes in oil-spill related laws and regulations. Although data gaps were identified in all four model domains, the socioeconomics and human health domains are the least established. Considerable future work is needed to address research gaps and to create fully coupled quantitative integrative assessment models that can be used in strategic decision-making that will optimize recoveries from future large oil spills