As extreme climate events become more common with global warming, groundwater is increasingly vital for combating long-term drought and ensuring socio-economic and ecological stability. Currently, the mechanism of meteorological drought propagation to groundwater drought is still not fully understood. This study focuses on the North China Plain (NCP), utilizing statistical theories, spatiotemporal kriging interpolation, and the Mann–Kendall trend test to examine the spatial and temporal distribution characteristics of groundwater from 2005 to 2021. Based on drought theory, the characteristics and propagation process of drought are further quantified. Key findings reveal the following: (1) Shallow groundwater depths in the NCP follow a zonal pattern from the western mountains to the eastern plains and coastal areas. Over two-thirds of this region showed an increase in groundwater depth at a rate of 0–0.05 m/a; (2) Groundwater drought frequency typically ranges from 3 to 6 times, with an average duration of 10 to 30 months and average severity between 10 and 35; (3) Delayed effects last between 0 to 60 months, with attenuation effects varying from 0 to 3 and prolonged effects extending from 0 to 16. Additionally, delayed effects intensify with increasing time scales, while prolonged effects weaken. Notably, both delayed and prolonged effects in the north of the NCP are more pronounced than in the south of the region. This study quantifies the process by which meteorological drought propagates to groundwater drought, offering a new perspective for understanding the interaction between groundwater and meteorological drought. It holds significant scientific importance for monitoring drought and managing water resources in the context of global climate change.

Meteorological drought, especially when influenced by human activities, significantly impacts agriculture. We assessed the Yangtze River Basin (YRB)’s crop ecosystem resilience during the 2022 southern China drought. Using the elasticity framework, we quantified crop Leaf Area Index (LAI) changes with meteorological factors and human activities (irrigation) in the YRB. Our study covered maize, wheat, early and late‐season rice, evaluating model accuracy with and without irrigation. Results indicate high accuracy (R² > 0.8, p < 0.05) in simulating LAI changes, notably improved with irrigation. Irrigation emerged as the primary driver of LAI changes in the past two decades, except for solar radiation’s impact on maize. In 2022, irrigation crucially influenced LAI changes, particularly in rice varieties. Early‐season rice and late‐season rice saw over 40% contribution from irrigation, while maize and wheat responded mainly to precipitation and radiation. Overall, 2022 yields remained stable, with late‐season rice showing an apparent increase. Drought timing correlated with maize, wheat, and early‐season rice yields, consistent with natural patterns. Conversely, late‐season rice exhibited the opposite pattern due to artificial irrigation, impacting 58% of the growing areas in 2022. The study offers insights into investigating farmland ecosystems responding to extreme droughts.