Evidence map›Paper›PMID 37914805›Full record

ArticleScientific reports2023

Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk.

Georgina M Sanchez, Anna Petrasova, Megan M Skrip, Elyssa L Collins, Margaret A Lawrimore, John B Vogler, Adam Terando, Jelena Vukomanovic, Helena Mitasova, Ross K Meentemeyer

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Georgina M SanchezCenter for Geospatial Analytics, North Carolina State University, Raleigh, NC, USA. gmsanche@ncsu.edu.
Anna PetrasovaCenter for Geospatial Analytics, North Carolina State University, Raleigh, NC, USA.
Megan M SkripCenter for Geospatial Analytics, North Carolina State University, Raleigh, NC, USA.
Elyssa L CollinsCenter for Geospatial Analytics, North Carolina State University, Raleigh, NC, USA.
Margaret A LawrimoreCenter for Geospatial Analytics, North Carolina State University, Raleigh, NC, USA.
John B VoglerCenter for Geospatial Analytics, North Carolina State University, Raleigh, NC, USA.
Adam TerandoSoutheast Climate Adaptation Science Center, U.S. Geological Survey, Raleigh, NC, USA.
Jelena VukomanovicCenter for Geospatial Analytics, North Carolina State University, Raleigh, NC, USA.
Helena MitasovaCenter for Geospatial Analytics, North Carolina State University, Raleigh, NC, USA.
Ross K MeentemeyerCenter for Geospatial Analytics, North Carolina State University, Raleigh, NC, USA.

Funding

U.S. Department of Agriculture, National Institute of Food and Agriculture, McIntire-Stennis 7002978U.S. Geological Survey Southeast Climate Adaptation Science Center G19AC00083U.S. National Science Foundation 1737563
6 · The paper itself

Abstract

Impacts of sea level rise will last for centuries; therefore, flood risk modeling must transition from identifying risky locations to assessing how populations can best cope. We present the first spatially interactive (i.e., what happens at one location affects another) land change model (FUTURES 3.0) that can probabilistically predict urban growth while simulating human migration and other responses to flooding, essentially depicting the geography of impact and response. Accounting for human migration reduced total amounts of projected developed land exposed to flooding by 2050 by 5%-24%, depending on flood hazard zone (50%-0.2% annual probability). We simulated various "what-if" scenarios and found managed retreat to be the only intervention with predicted exposure below baseline conditions. In the business-as-usual scenario, existing and future development must be either protected or abandoned to cope with future flooding. Our open framework can be applied to different regions and advances local to regional-scale efforts to evaluate potential risks and tradeoffs.

Identifiers

PMID37914805
PMCPMC10620417

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.