This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.
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Abstract
Hurricane and tropical storm-driven storm surge flooding places coastal farmlands at high risk of crop damage and soil salinization. The damage can total to millions of dollars in costs and force farmers to abandon coastal fields. Additionally, many agricultural, and often rural, areas are unable to access accurate and reliable flood-risk projection maps and analyses that can inform prevention and mitigation strategies. This study developed a simplistic methodology for cropland loss analysis that can be utilized by those in regions without advanced GIS specialists, but still wish to explore flood analysis. While similar studies have been conducted in the past, few focus on North Carolina, and most use techniques that require years of expertise and formal training to be able to execute. Soybean and corn, two crops that are critical suppliers to the state economy and have a multitude of uses, were selected to be analyzed. Soybean and corn fields in three of North Carolina’s coastal counties were evaluated under various storm surge models. Cropland maps were taken from CroplandCROS, a geospatial database maintained by the United States Department of Agriculture (USDA) for the selected counties. Storm surge models of one, three, five, and nine meters in elevation were overlaid with crop data, and total farmland area submerged by the models was calculated. Models were validated with official flood risk projections and high-risk cropland areas were identified. Under the highest storm surge model, an estimated 672,226,470 m2, or 86.775% of farmland across all three counties is at risk of flooding. Economic losses were calculated under each model, resulting in damages as high as $135,148,007.30. Further research will be conducted to include more data layers in order to produce more holistic risk projections and enhance the accessibility of flood risk assessment, as well as improving the accuracy and efficiency of the current methodology.
DOI
https://doi.org/10.31223/X5WD8N
Subjects
Earth Sciences, Environmental Sciences, Physical Sciences and Mathematics
Keywords
Flood Risk, Storm surge, GIS
Dates
Published: 2024-06-16 06:47
Last Updated: 2024-06-16 13:47
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Conflict of interest statement:
None
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