- Long-term meteorological drought is the leading driver of groundwater drought.
- Groundwater drought can lag behind weather conditions by 12 to 24 months.
- Human activity, particularly overextraction, exacerbates groundwater depletion.
- Future climate scenarios indicate wider and longer drought conditions, particularly under extreme warming conditions.
Monday, July 7, 2025 — Earlier this month, researchers released a study using machine learning to investigate the evolution and causes of groundwater drought in China’s West Liao River Plain—a semi-arid region where agriculture heavily depends on groundwater irrigation. The results, published in Scientific Reports
, shed new light on how meteorological patterns, soil conditions, and human activities converge to create long-lasting groundwater shortages.
The team evaluated eight machine learning models to predict groundwater drought, ultimately identifying one as the most reliable: an eXtreme Gradient Boosting (XGBoost) model enhanced by a search algorithm inspired by sparrow foraging behavior. This optimized model demonstrated high accuracy, with an area-under-the-curve score of 0.922 and an F1-score of 0.84, indicating strong performance in identifying drought conditions.
Identifying the Key Drivers.
To explain how specific environmental factors influenced predictions, the researchers used a method called Shapley Additive Explanations (SHAP). This technique revealed that the two most influential predictors were the 12- and 24-month Standardized Precipitation Evapotranspiration Indices. These long-term indicators reflect prolonged weather-related droughts and were more significant than short-term indices. Precipitation and soil moisture also played major roles, while human-related factors such as population density and the human footprint accounted for over 14 percent of the model’s predictions.
Drought Lingers Even After Rain Returns.
The research confirmed a delayed response between meteorological drought and groundwater drought, often spanning one to two years. Even when wet conditions returned, groundwater levels remained low due to the slow recharge rates of deeper aquifers. This lag means that regions may face persistent drought effects well after weather patterns appear to improve.
The Human Factor.
Human activities further worsen the situation. In the study area of the West Liao River Plain, groundwater is heavily overdrawn for agriculture and urban development. Despite government interventions, these pressures remain high. The study found that extraction during summer months, when irrigation and evaporation both peak, can trigger groundwater drought even during years of adequate rainfall.
Forecasting.
Looking ahead, the study applied the model to two climate change scenarios through the year 2100. Both scenarios predicted an increase in drought-affected areas, but the more extreme warming pathway showed earlier and more prolonged drought conditions. In the future, rising temperatures will likely reduce aquifer recharge regardless of precipitation levels.
By combining interpretable machine learning with decades of data, this research provides a new framework for early warning systems and resource planning. It also highlights the importance of long-term meteorological monitoring and careful water management, particularly in regions where groundwater serves as a vital resource.
Source:
Gan, Z., Xie, X., Su, C., Ge, W., Pan, H., & Yang, L. (2025). Understanding the evolutionary processes and causes of groundwater drought using an interpretable machine learning model. Scientific Reports. https://www.nature.com/articles/s41598-025-05316-2
