Drought Awareness over Continental United States

Understanding the relationship between droughts and drought awareness is vital towards decision making and policy for water management and conservation strategies, and socioeconomic outcomes. We used computer vision (UNet models) to analyze nonlinear, heterogeneous, lagged correlations between Standardized Precipitation Evapotranspiration Index (SPEI) and Google Trends Search Interest within the Continental United States (CONUS). The most important drivers of the relationship between drought occurrence and drought awareness are the variability and ranges of drought trends and severity, as well as extreme drought conditions. This relationship was the strongest for Western states, followed by Northeastern, Southeastern, and Central regions. Search interest tends to lag droughts by a period of ̃1-3 months. We also found evidence that reductionist linear approaches, such as a Principal Component Analysis, might not be as effective as UNet models in capturing the nuanced relationship between droughts and drought awareness at various dimensions and scales. • The relationship between drought occurrence and people’s awareness of droughts over CONUS is nonlinear, heterogeneous, and tends to lag by ̃1-3 months. • The most important drivers of this relationship are the variability and ranges of drought trends and severity, as well as drought extremes. • This relationship is the strongest for Western states, followed by Northeastern, Southeastern, and Central regions.

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Publication Details

Journal
Journal of Hydrology
Published
2024-08-26
DOI
https://doi.org/10.1016/j.jhydrol.2024.131868
Citations
1
Primary Topic
Hydrology and Drought Analysis
Type
article
Field-Weighted Citation Impact
0.28

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Drought Awareness over Continental United States

Mahmoud Saeedimoghaddam, Samuel Sandoval-Solís, Niv Efron, Mashrekur Rahman et al.
1 citations
Journal of Hydrology
Hydrology and Drought Analysis
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article

Drought Awareness over Continental United States

Mahmoud Saeedimoghaddam, Samuel Sandoval-Solís, Niv Efron, Mashrekur Rahman, Grey Nearing, Thomas Harter
article en
1 citations

Abstract

Understanding the relationship between droughts and drought awareness is vital towards decision making and policy for water management and conservation strategies, and socioeconomic outcomes. We used computer vision (UNet models) to analyze nonlinear, heterogeneous, lagged correlations between Standardized Precipitation Evapotranspiration Index (SPEI) and Google Trends Search Interest within the Continental United States (CONUS). The most important drivers of the relationship between drought occurrence and drought awareness are the variability and ranges of drought trends and severity, as well as extreme drought conditions. This relationship was the strongest for Western states, followed by Northeastern, Southeastern, and Central regions. Search interest tends to lag droughts by a period of ̃1-3 months. We also found evidence that reductionist linear approaches, such as a Principal Component Analysis, might not be as effective as UNet models in capturing the nuanced relationship between droughts and drought awareness at various dimensions and scales. • The relationship between drought occurrence and people’s awareness of droughts over CONUS is nonlinear, heterogeneous, and tends to lag by ̃1-3 months. • The most important drivers of this relationship are the variability and ranges of drought trends and severity, as well as drought extremes. • This relationship is the strongest for Western states, followed by Northeastern, Southeastern, and Central regions.

Journal of HydrologyVol. 642
Google (United States) (US), University of California, Davis (US)
Google
Climate action
Openalex Percentile: Top 43%
Hydrology and Drought Analysis
0.28
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