Articles | Volume 7, issue 2
https://doi.org/10.5194/esurf-7-429-2019
https://doi.org/10.5194/esurf-7-429-2019
Research article
 | 
15 May 2019
Research article |  | 15 May 2019

Relationships between regional coastal land cover distributions and elevation reveal data uncertainty in a sea-level rise impacts model

Erika E. Lentz, Nathaniel G. Plant, and E. Robert Thieler

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Erika Lentz on behalf of the Authors (20 Mar 2019)  Author's response   Manuscript 
ED: Publish as is (07 Apr 2019) by Paola Passalacqua
ED: Publish subject to technical corrections (11 Apr 2019) by Douglas Jerolmack (Editor)
AR by Erika Lentz on behalf of the Authors (24 Apr 2019)  Author's response   Manuscript 

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Erika Lentz on behalf of the Authors (09 May 2019)   Author's adjustment   Manuscript
EA: Adjustments approved (09 May 2019) by Paola Passalacqua
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Short summary
Our findings examine several data inputs for probabilistic regional sea-level rise (SLR) impact predictions. To predict coastal response to SLR, detailed information on the landscape, including elevation, vegetation, and/or level of development, is needed. However, we find that the inherent relationship between elevation and land cover datasets (e.g., beaches tend to be low lying) is used to reduce error in a coastal response to SLR model, suggesting new applications for areas of limited data.