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Integrated drought monitoring and assessment using multi-sensor and multi-temporal earth observation datasets: a case study of two agriculture-dominated states of India

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Abstract

In the current scenario of climate change, there has been a substantial increase in the frequency and severity of drought events. Therefore, it is necessary to investigate spatio-temporal characteristics of different drought events to plan for water resource utilization. The present study aims to assess and quantify the impact of meteorological, hydrological, and agricultural drought events from 2001 to 2017 over two large states of India (i.e., Maharashtra and Madhya Pradesh) using multi-temporal earth observation data at a finer resolution of 1 km. Drought indices including Standardized Precipitation Index (SPI), Standardized Water level Index (SWI), and Vegetation Health Index (VHI) were derived from precipitation, groundwater level, vegetation indices, and land surface temperature data respectively to map the spatial extent and severity of meteorological, hydrological, and agricultural drought. Assessment of individual drought indices was carried out to understand the effect of these drought events separately on the study area. Area vulnerable with multiple droughts in the region was identified by integrating multiple drought indices to derive a composite drought map. This included the locations that are hotspots in terms of the occurrence of drought events of different types. The spatial pattern captured in the composite drought map indicates that most of the study areas are prone to drought events varying from mild to extreme severity. Madhya Pradesh is more prone to meteorological and agricultural drought events compared to hydrological drought. Maharashtra state is prone to three types of drought with agricultural drought being the dominant one. This study provides an opportunity to investigate and understand the drought phenomenon in a comprehensive manner at comparatively finer spatial resolution.

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Data availability

Most of the datasets used in the study are freely available. The downscaled precipitation dataset are available from the corresponding authors upon reasonable request.

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Authors and Affiliations

  1. Department of Natural and Applied Sciences, TERI School of Advanced Studies, New Delhi, India

    Arun Murali C.M, Mohit Kesarwani & Neeti Neeti

  2. National Crop Forecasting Center, Delhi, India

    V. M. Chowdary

  3. Now at Center for Climate Change and Sustainability, Azim Premji University, Bengaluru, India

    Neeti Neeti

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  1. Arun Murali C.M
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  2. V. M. Chowdary
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  3. Mohit Kesarwani
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  4. Neeti Neeti
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Contributions

Conceptualization: Neeti Neeti, V. M. Chowdary. Methodology: Neeti Neeti, V. M. Chowdary, Arun Murali CM. Formal analysis and investigation: Arun Murali CM, Mohit Kesarwani. Writing—original draft preparation: Arun Murali CM, Mohit Kesarwani. Writing—review and editing: Neeti Neeti, V. M. Chowdary. Supervision: Neeti Neeti, V. M. Chowdary.

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C.M, A.M., Chowdary, V.M., Kesarwani, M. et al. Integrated drought monitoring and assessment using multi-sensor and multi-temporal earth observation datasets: a case study of two agriculture-dominated states of India. Environ Monit Assess 195, 1 (2023). https://doi.org/10.1007/s10661-022-10550-6

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