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Location, Location, Location: The Role of Elevation in Flood Models

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Location, Location, Location: The Role of Elevation in Flood Models

 

Katie Towey and Matthias Kemter
September 17, 2024

In a recent blog post, we discussed how floods are among the costliest hazards worldwide. To fully understand flooding risks, institutional investors need to think in multiple dimensions. Knowing the location of your asset is important, but so is knowing its elevation. We found that overestimating elevation by just 20 centimeters can overlook flood risk in over a quarter of global locations.

With so much at stake, investors need high-quality data to build confidence in their climate-risk assessments. Assessing asset exposure to flood risk is contingent on multiple datasets, and projecting the potential financial impacts of flood risk can be highly sensitive to the accuracy of the underlying data.

Flood maps rely on high spatial resolution for accuracy, but vertical accuracy of elevation data is also critical to understanding the potential costs from flooding.1 Lower-resolution elevation models can result in a misrepresentation of flood risk and subsequently the potential financial impacts to institutions.

We looked at the possible impact of inaccurate elevation data2 on flood exposure at asset locations across the MSCI GeoSpatial Asset Intelligence dataset.3 As the elevation bias increases (i.e., the higher the estimated elevation of a surface is compared to our benchmark), the number of asset locations exposed to floods decreases.4 While overestimating elevation by 20 centimeters reduces the number of global assets exposed to floods from 35% to 9%, a more extreme overestimation of 1.65 meters reduces the number of assets exposed to just 1%.

Flood exposure by flood type for different elevation biases

Data as of Aug. 12, 2024. Analysis covers all assets in MSCI GeoSpatial Asset Intelligence database. Locations are considered exposed if they have an estimated flood depth above zero for the 1-in-100-year flood event (annual exceedance probability of 1%). Source: MSCI ESG Research


1 “Does (Element) Size Really Matter? The Effect of Grid Scale on Flood Model Quality,” Fathom, May 20, 2024.

2 Michael Meadows, Simon Jones and Karin Reinke, “Vertical accuracy assessment of freely available global DEMs (FABDEM, Copernicus DEM, NASADEM, AW3D30 and SRTM) in flood-prone environments,” International Journal of Digital Earth 17, no. 1.

3 As of August 2024, the MSCI GeoSpatial Asset Intelligence database contains physical-hazard data for 912,142 individual, globally distributed company assets belonging to 61,906 public and private companies.

4 The benchmark elevation model used in this analysis is FABDEM+, which is used in MSCI’s flood-risk assessment. “The New Standard for a Globally Consistent Multi-Source Digital Elevation Model: Meet FABDEM+,” Fathom, Oct. 3, 2023.

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