Abstract In this study, integrated drought monitoring index (IDMI) was proposed as a tool to assess and monitor the spatio-temporal dynamics of agricultural drought during the northeast monsoon season for the period from 2000 to 2016 in Tamil Nadu state, south-eastern part of Indian peninsula. The IDMI is characterized as the principal component of precipitation condition index (PCI), soil moisture condition index (SMCI), temperature condition index (TCI) and vegetation condition index (VCI) derived from time-series satellite observations of climate hazards group infra-red precipitation with stations (CHIRPS), European space agency climate change initiative (ESA-CCI) and moderate resolution imaging spectroradiometer (MODIS). The study shows that in the year 2016, about 44.4 and 17.8% of Tamil Nadu state was under extreme and severe drought condition, respectively. Sensitivity analysis of the study shows that PCI is the most influential parameter to IDMI, followed by VCI and TCI. The validation of IDMI with 3-month standardized precipitation index (SPI) by using correlation coefficient (r) shows a strong positive correlation between IDMI and 3-month SPI with r value of 0.73 and 0.77 during the wet year (2005) and dry year (2016), respectively. The study clearly demonstrates the potential of IDMI derived from time series datasets of earth observation satellites as a tool in assessment and monitoring of spatio-temporal dynamics of agricultural drought. The proposed IDMI could be effectively used as a reliable tool to monitor agricultural drought and develop drought mitigation strategies to minimise the adverse effects of drought on agriculture, water resources and livelihoods of the people.

中文翻译：

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综合干旱监测指数：利用天基地球观测卫星时间序列数据集监测农业干旱的工具

摘要 在本研究中，综合干旱监测指数 (IDMI) 被提出作为评估和监测东南部泰米尔纳德邦 2000 年至 2016 年东北季风季节农业干旱时空动态的工具。印度半岛。IDMI的特征是降水状况指数（PCI）、土壤水分状况指数（SMCI）、温度状况指数（TCI）和植被状况指数（VCI）的主成分，这些指数来自气候灾害组的时间序列卫星观测红色降水站 (CHIRPS)、欧洲航天局气候变化倡议 (ESA-CCI) 和中等分辨率成像光谱仪 (MODIS)。研究表明，在 2016 年，大约为 44.4 和 17。泰米尔纳德邦 8% 的地区分别处于极端和严重干旱条件下。该研究的敏感性分析表明，PCI 是对 IDMI 影响最大的参数，其次是 VCI 和 TCI。使用相关系数(r)对IDMI与3个月标准化降水指数(SPI)的验证显示IDMI与3个月SPI之间呈强正相关，在丰水年(2005年)和旱年，r值分别为0.73和0.77 (2016)，分别。该研究清楚地证明了源自地球观测卫星时间序列数据集的 IDMI 作为评估和监测农业干旱时空动态的工具的潜力。