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Published December 2021 | Supplemental Material
Journal Article Open

Persistent impact of spring floods on crop loss in U.S. Midwest

Abstract

Climate extremes threaten global food security, and compound events, such as late spring heavy and warmer rainfall over snow and subsequent flooding, exacerbate this vulnerability. Despite frequent occurrences in recent years, a quantitative understanding of the compound weather events' impacts remains elusive. Here, we use Synthetic Aperture Radar data from Sentinel-1 and normalized difference vegetation index data from MODIS satellites to map the spring 2019 U.S. Midwest flood extent and evaluate its impact on crop loss. We find a statistically significant association between flooded counties and those with plant greenup delay, while the correlation between flood area percent and amount of green-up delay remains weak, albeit reliable. An analysis of the stream gage time series and crop loss records shows that during the past ∼70 years, ∼43% of spring large discharges are associated with widespread crop loss. We also find an increase in streams' discharge frequency and magnitude across the Midwest, indicating the possibility of a future increase in crop loss due to spring flooding. This study highlights the importance of Earth-observing satellite data for developing climate adaptation and resilience plans.

Additional Information

© 2021 The Authors. Published by Elsevier Under a Creative Commons license - Attribution 4.0 International (CC BY 4.0) Received 4 January 2021, Revised 2 October 2021, Accepted 19 October 2021, Available online 20 October 2021. M.S. and S.S. are supported by the National Aeronautics and Space Administration (NASA) grant 80NSSC170567. C.O., G.C., and S.W. are supported by the NASA grant NNX17AD98G. H.K. is supported by NASA grant 80NSSC18M0039. J.L. is supported by the National Science Foundation grant EAR-1735630. G.Z. is supported by the Department of Energy Grant DE-SC0019307. We thank two anonymous reviewers for their insightful comments and suggestions. SAR datasets are obtained from Alaska Satellite Facilities (www.asf.alaska.edu). Crop yield and NDVI data are obtained from the USDA. Prevent plant acres are obtained from the FSA. Discharge data are obtained from the USGS. This GEE script is publicly available at https://code.earthengine.google.com/?scriptPath=users%2Fhkerner_umd%2Fndvi_midwest%3Amodis_ndvi_export. The generated flood maps for each SAR frame are available at https://drive.google.com/drive/folders/1UmqkZ_RoP8CMCxWXzdIotdjDIxhvcLhq?usp=sharing, which includes two folders called 'index' and 'figs'. The index folder includes 15 index maps, each showing the approximate center location of each flood map using a number between 1 and 463 for a period of ∼10 days. The figs folder includes the flood maps associated with each date and location shown in the index maps. The generated NDVI maps are provided at https://drive.google.com/drive/folders/1yXeG_RahehjklG-qxrO-nsZZ0mKh6s55?usp=sharing. All authors made significant and extensive contributions to the work presented in this manuscript. M.S. designed the experiment. M.S., C.O., S.S., and G.Z. processed the SAR dataset and generated the flood maps. M.K., S.W., and G.C. analyzed the stream gage data and generated plots. M.S. and H.K. analyzed the NDVI and prevent plant data and plotted them. J.L. developed codes and plotted the flood maps provided in the online repository. S.W. analyzed and plotted precipitation data. M.S. performed correlation analyzes and developed the first draft of the manuscript. All authors reviewed and edited the manuscript, figures, and supplement. The authors declare that they have no competing interests.

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Additional details

Created:
August 22, 2023
Modified:
October 23, 2023