Despite the implications of meteorological drought propagation to agricultural, hydrological, and groundwater droughts, the focus of previous studies has been primarily on meteorological droughts in India. We use the well‐calibrated and evaluated Variable Infiltration Capacity‐ Simple Groundwater Model (VIC‐SIMGM) to simulate soil moisture, runoff, and groundwater storage variability in India for the 1951–2016 period. The Integrated Drought Index (IDI) that combines meteorological, agricultural, hydrological, and groundwater droughts was developed for the 1951–2016 period for India. Using a spatial clustering algorithm based on the traditional interpoint distance metric, eight homogeneous clusters based on IDI were identified. The majority of clusters in India experience the onset and termination of droughts during the summer monsoon season (June–September). The analysis of moisture back trajectories using the Hybrid Single‐Particle Lagrangian Integrated Trajectory (HYSPLIT) model showed that the Arabian Sea and Bay of Bengal are the two major moisture sources for the identified clusters in India. We performed the Empirical Orthogonal Function (EOF) and Maximum Covariance Analysis (MCA) using monthly IDI and Sea Surface Temperature (SST) to evaluate the influence of long‐term climate variability on droughts in India. Droughts based on 1‐month IDI that affect a majority of drought clusters are associated with the positive phase of El Nino Southern Oscillations (ENSO) and Indian Ocean Dipole (IOD). On the other hand, drought clusters in the Gangetic Plain and peninsular India are affected by the SST warming over the Indian Ocean. Overall, drought clusters based on IDI, their moisture source, and large‐scale teleconnection can assist in drought management and assessment in India.

中文翻译：

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印度的干旱发作和终止

尽管气象干旱传播对农业，水文和地下水干旱具有影响，但以前的研究重点主要是印度的气象干旱。我们使用经过良好校准和评估的可变渗透能力-简单地下水模型（VIC-SIMGM）来模拟1951–2016年印度土壤的水分，径流和地下水储量的变化。印度在1951年至2016年期间开发了综合干旱指数（IDI），该指数综合了气象，农业，水文和地下水干旱。使用基于传统的点间距离度量的空间聚类算法，确定了八个基于IDI的同质聚类。印度的大多数集群在夏季风季节（6月至9月）经历干旱的发作和终止。使用混合单颗粒拉格朗日综合轨迹（HYSPLIT）模型对水分回溯轨迹进行的分析表明，阿拉伯海和孟加拉湾是印度确定的星团的两个主要水分来源。我们使用每月的IDI和海面温度（SST）进行了经验正交函数（EOF）和最大协方差分析（MCA），以评估印度长期干旱对干旱的影响。基于1个月IDI的干旱影响了大多数干旱集群，这与厄尔尼诺南方涛动（ENSO）和印度洋偶极子（IOD）的积极阶段有关。另一方面，印度洋SST变暖影响恒河平原和印度半岛的干旱集群。总体而言，基于IDI，其水分源和大规模远程连接的干旱集群可以帮助印度进行干旱管理和评估。