Drought is one of the major constraints to rain-fed agricultural production, especially under climate change conditions. Plants evolved an array of adaptive strategies that perceive stress stimuli and respond to these stress signals through specific mechanisms. Abscisic acid (ABA) is a premier signal for plants to respond to drought and plays a critical role in plant growth and development. ABA triggers a variety of physiological processes such as stomatal closure, root system modulation, organizing soil microbial communities, activation of transcriptional and post-transcriptional gene expression, and metabolic alterations. Thus, understanding the mechanisms of ABA-mediated drought responses in plants is critical for ensuring crop yield and global food security. In this review, we highlighted how plants adjust ABA perception, transcriptional levels of ABA- and drought-related genes, and regulation of metabolic pathways to alter drought stress responses at both cellular and the whole plant level. Understanding the synergetic role of drought and ABA will strengthen our knowledge to develop stress-resilient crops through integrated advanced biotechnology approaches. This review will elaborate on ABA-mediated drought responses at genetic, biochemical, and molecular levels in plants, which is critical for advancement in stress biology research.

Yunnan Province, as a critical ecological security barrier in China, has long been highly susceptible to drought events. Characterizing the spatiotemporal distributions of drought and identifying its driving factors is crucial. Due to the complexity of drought occurrence, linear correlation analysis alone is insufficient to quantify drought drivers and their interactions. This study used the Standardized Precipitation Evapotranspiration Index (SPEI) as a drought indicator to analyze the spatiotemporal trends of drought across Yunnan and its six major river basins. The geographic detector model (GDM) and random forest (RF) were utilized to quantify the impacts of meteorological, topographical, soil, and human activities on drought, as well as the interactions among these factors. The results showed that 63.61% of the study area exhibits a significant drying trend (p-value < 0.05), with the Jinsha River Basin (JSRB) experiencing the highest frequency of extreme drought events. Precipitation (PRE), temperature, potential evapotranspiration (PET), vapor pressure deficit (VPD), and relative humidity (RH) were identified as the primary controlling factors of drought, with factor interactions displaying nonlinear enhancement effects. PRE plays a dominant role in driving drought across Yunnan, whereas elevation primarily influenced drought severity in the JSRB, Lancang River Basin (LCRB), and Nujiang River Basin (NJRB). The RF-based SPEI prediction model demonstrated superior performance in simulating short-term drought (SPEI_1, R² > 0.931, RMSE < 0.279), particularly in the JSRB (R² = 0.947 RMSE = 0.228). These findings provide a scientific basis for regional water resource management applications and drought early warning systems, offering a robust framework for understanding and mitigating drought impacts in ecologically sensitive regions.