Economic evaluation of sea-level rise adaptation strongly influenced by hydrodynamic feedbacks: Dataset 1

Coastal communities rely on levees and seawalls as critical protection against sea-level rise; in the U.S. alone, $300 billion in shoreline armoring costs are forecast by 2100. But despite the local flood risk reduction benefits, these structures can exacerbate flooding and associated damages along other parts of the shoreline—particularly in coastal bays and estuaries, where nearly 500 million people globally are at risk from sea-level rise. The magnitude and spatial distribution of the economic impact of this dynamic, however, are poorly understood. Here we combine hydrodynamic and economic models to assess the extent of both local and regional flooding and damages expected from a range of shoreline protection and sea-level rise scenarios in San Francisco Bay, California. We find that protection of individual shoreline segments (5-75 km) can increase flooding in other areas by as much as 36 million cubic meters and damages by $723 million for a single flood event, and in some cases can even cause regional flood damages that exceed the local damages prevented from protection. We also demonstrate that strategic flooding of certain shoreline segments, such as those with gradually sloping baylands and space for water storage, can help alleviate flooding and damages along other stretches of the coastline. By matching the scale of the economic assessment to the scale of the threat, we reveal the previously uncounted costs associated with uncoordinated adaptation actions and demonstrate that a regional planning perspective is essential for reducing shared risk and wisely spending adaptation resources in coastal bays. This dataset is associated with a github repository https://github.com/rmgriffin/OLU-flood-externalities This dataset is part of a two record data repository associated with the paper "Economic evaluation of sea-level rise adaptation strongly influenced by hydrodynamic feedbacks." This is part one.Please see Dryad dataset DOI: 10.5061/dryad.g79cnp5pt for part 2 of the data for this article containing flood depth rasters for 150cm and 200cm of sea level rise