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Economic damages of hurricanes and tropical cyclones are increasing faster than the populations and wealth of many coastal areas. There is urgency to update priorities of agencies engaged with risk assessment, risk mitigation, and risk communication across hundreds or thousands of water basins. This paper evaluates hydrology and social vulnerability factors to develop a risk register at a subbasin scale for which the priorities of agencies vary by storm scenario using publicly available satellite-based Earth observations. The novelty and innovation of this approach is the quantification and mapping of risk as a disruption of system order, while using social vulnerability indices and sensor data from disparate sources. The results assist with allocating resources across basins under several scenarios of hydrology and social vulnerability. The approach is in several parts as follows: first, a baseline order of basins is defined using the CDC/ATSDR social vulnerability index (SVI). Next, a set of storm scenarios is defined using Earth Observations and modeled data. Next, a swing-weight technique is used to update factor weights under each scenario. Lastly, the importance order of basins relative to the baseline order is used to compare the risk of scenarios across the study area. The risk is thus quantified (by least squares difference of order) as a disruption to the ordering of basins by social and hydrologic factors (i.e., SVI, precipitation, wind speed, and soil moisture), with attention to the most disruptive scenarios. An application is described with extensive mapping of hydrologic basins for Hurricane Ian to demonstrate a versatile method to address uncertainty of scenarios of storm nature and extent across coastal mega-regions.