Unequal Burdens: Land Tenure and Agricultural Losses in the 2019 Lower Mississippi River Floods

The 2019 Mississippi River floods were among the most severe in recent U.S. history, impacting 11 states and driven by multiple tributary flood events rather than a single episode. This study focuses on the Lower Mississippi River Basin in Mississippi, examining how flood frequency interacts with land ownership patterns to influence agricultural losses in the Yazoo–Mississippi Delta. Using Sentinel-2 imagery within Google Earth Engine, land use and land cover were classified with a random forest algorithm, followed by change detection and a flood recurrence–persistence modeling framework to map and characterize inundation. Results indicate that mid-year floods (April–July) caused the greatest crop losses, particularly in soybeans (4475 ha), cotton (501 ha), and corn (546 ha). Most impacts were associated with short-duration, low-recurrence floods, which affected many structures (1812) and extensive agricultural areas due to their broad spatial reach. Small agricultural parcels (≤48 ha) experienced the highest proportional exposure across flood zones, while medium and large parcels showed comparatively lower vulnerability. These findings highlight the importance of targeted resilience and mitigation strategies that account for flood frequency, land use, and land ownership patterns across the Delta.

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Publication Details

Journal
Remote Sensing
Published
2026-06-17
DOI
https://doi.org/10.3390/rs18122022
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Unequal Burdens: Land Tenure and Agricultural Losses in the 2019 Lower Mississippi River Floods

Shrinidhi Ambinakudige, Jephthah Nimoh Marfo
Remote Sensing
Flood Risk Assessment and Management
article

Unequal Burdens: Land Tenure and Agricultural Losses in the 2019 Lower Mississippi River Floods

Shrinidhi Ambinakudige, Jephthah Nimoh Marfo
article en

Abstract

The 2019 Mississippi River floods were among the most severe in recent U.S. history, impacting 11 states and driven by multiple tributary flood events rather than a single episode. This study focuses on the Lower Mississippi River Basin in Mississippi, examining how flood frequency interacts with land ownership patterns to influence agricultural losses in the Yazoo–Mississippi Delta. Using Sentinel-2 imagery within Google Earth Engine, land use and land cover were classified with a random forest algorithm, followed by change detection and a flood recurrence–persistence modeling framework to map and characterize inundation. Results indicate that mid-year floods (April–July) caused the greatest crop losses, particularly in soybeans (4475 ha), cotton (501 ha), and corn (546 ha). Most impacts were associated with short-duration, low-recurrence floods, which affected many structures (1812) and extensive agricultural areas due to their broad spatial reach. Small agricultural parcels (≤48 ha) experienced the highest proportional exposure across flood zones, while medium and large parcels showed comparatively lower vulnerability. These findings highlight the importance of targeted resilience and mitigation strategies that account for flood frequency, land use, and land ownership patterns across the Delta.

Remote SensingVol. 18(12)
Mississippi State University (US)
Openalex Percentile: Top 8%
Flood Risk Assessment and Management
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