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PCA–based composite drought index for drought assessment in Marathwada region of Maharashtra state, India

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Abstract

This paper presents a composite approach for drought characterization and monitoring using in situ and remote sensing-based drought indicators. The study was carried out on one of the most drought-prone areas of India, i.e., the Marathwada region of Maharashtra. Meteorological, hydrological, and agricultural drought indices, namely standardized precipitation index (SPI), streamflow drought index (SDI), and vegetation condition index (VCI), respectively, were integrated to develop the composite drought index (CDI) using principal component analysis (PCA). SPI and SDI were computed using in situ precipitation and streamflow data, respectively, for 35 years (1980–2014), whereas VCI was computed using MODIS satellite data (500-m resolution) for 15 years (2000–2014) at 1-, 3-, and 5-month time scales. The time scales of drought indices were evaluated using historical drought years and foodgrain production of the region. The drought areas observed by SPI, SDI, and VCI at different time scales were correlated with foodgrain production during the kharif crop growing season for 15 years (2000–2014). The maximum correlation of foodgrain production was observed with 3-month SPI (r =  − 0.72), 5-month SDI (r =  − 0.40), and 5-month VCI (r =  − 0.81) for meteorological, hydrological, and agricultural drought, respectively. Three-month SPI, 5-month SDI, and 5-month VCI were selected from each drought category to develop CDI. These drought indices were combined using weights derived through the PCA technique. The maximum weight was obtained for 3-month SPI (45.4%) followed by 5-month VCI (42.8%) and 5-month SDI (11.8%). The developed CDI products showed a strong relationship (r =  − 0.85) with foodgrain production. The drought years observed by CDI were also closest to drought years declared by the State Government. The time series trend of the drought-affected area observed by CDI, 3-month SPI, and 5-month VCI resembled the drought patterns very closely, especially during the drought years. The spatio-temporal analysis of individual drought indices and CDI with foodgrain production deviation showed that CDI was better for capturing drought conditions than individual indicators. The study suggested that an individual or single indicator is not sufficient to capture the actual drought severity and its magnitudes; therefore, using a composite approach could be a good choice for effective drought assessment and monitoring in the region.

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Acknowledgements

Authors would like to appreciate and profusely acknowledge Dr. M. Hayes from School of Natural Resources, University of Nebraska-Lincoln; Dr. C. M. U. Neale from Daugherty Water for Food Global Institute, University of Nebraska, Lincoln, NE, USA; and Dr. M. Svoboda from National Drought Mitigation Center, School of Natural Resources, University of Nebraska-Lincoln for their contributions and supports. Authors highly acknowledge data providers: Department of Hydrology, Nashik, Maharashtra, India; satellite data providers (MODIS, NASA, USA; CartoDEM, Bhuvan Geo-Portal, India); Department of Agriculture, Government of Maharashtra; and Ministry of Agriculture & Farmers Welfare (MoA & FW), Government of India for providing data to conduct this study. The financial support provided by the Department of Science and Technology (DST), Government of India, through the Inspire fellowship is highly acknowledged. The authors also would like to acknowledge the National Drought Mitigation Centre (NDMC), University of Nebraska-Lincoln, USA, and the financial support provided by USIEF under US-India 21st Century Knowledge Initiative Awards.

Funding

This research did receive a grant from USIEF under US-India 21st Century Knowledge Initiative Awards.

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Authors and Affiliations

  1. Water Technology Centre, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India

    V. K. Prajapati, M. Khanna, M. Singh, R. Kaur & D. K. Singh

  2. Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India

    R. N. Sahoo

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  1. V. K. Prajapati
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  3. M. Singh
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Contributions

All authors were involved in the conceptualization and design of this study. Data collection and data analysis were performed by V. K. Prajapati, M. Khanna, and R. N. Sahoo. M. Singh, R. Kaur, and D. K. Singh were also involved in interpreting results. V. K. Prajapati and M. Khanna wrote the first draft of the manuscript, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to M. Khanna.

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Prajapati, V.K., Khanna, M., Singh, M. et al. PCA–based composite drought index for drought assessment in Marathwada region of Maharashtra state, India. Theor Appl Climatol 149, 207–220 (2022). https://doi.org/10.1007/s00704-022-04044-1

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