Abstract
Groundwater depletion in agricultural-dominated regions is attributed to climate and irrigation withdrawals that support crop production. However, despite decades of effort, knowledge gaps remain in understanding the relative influence of drought and crop production on groundwater levels at the continental scale. Here, utilizing empirical observations, we simultaneously track how long-term trajectories of groundwater levels, crop production of seven crops, and drought have evolved over time, and then integrate these observations with a causality-based attribution framework to unravel the relative impact of drought and crop production on groundwater levels across the contiguous United States (CONUS). We find a dominant pattern of decreases in groundwater levels with increases (25–61%) or no change (1–15%) in crop production across the CONUS. We estimate a significant (P < 0.1) causal influence of crop production and drought on groundwater levels in ∼32% (n = 101) and ∼20% (n = 62) of counties, respectively. Further, the extent of impact of crop production on groundwater varies with region and is most pronounced for cotton (42%, n = 18) and wheat (17%, n = 39). The memory effects of crop production (median: 7 years) and drought (median: 3 years) on groundwater levels imply that their impact could last much longer than the annual crop production cycle or the drought exposure period. Further, these findings allude to circular causality between groundwater and crop production, where both entities depend on each other at different time scales. Our work builds on past work and contributes to the growing understanding of food security and groundwater availability to manage these commodities to meet future demands.
| Original language | English |
|---|---|
| Article number | pgaf129 |
| Journal | PNAS Nexus |
| Volume | 4 |
| Issue number | 5 |
| DOIs | |
| State | Published - May 1 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 2 Zero Hunger
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SDG 13 Climate Action
Keywords
- causality modeling
- drought
- food security
- groundwater decline
- water sustainability
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