Preprints
https://doi.org/10.5194/essd-2022-81
https://doi.org/10.5194/essd-2022-81
 
12 Jul 2022
12 Jul 2022
Status: this preprint has been withdrawn by the authors.

Enhancing drought monitoring and assessment capability in India through high-resolution (250 m) data

Anukesh Ambika1 and Vimal Mishra1,2 Anukesh Ambika and Vimal Mishra
  • 1Earth Sciences, Indian Institute of Technology (IIT) Gandhinagar
  • 2Civil Engineering, Indian Institute of Technology (IIT) Gandhinagar

Abstract. Drought poses a tremendous challenge to India's socioeconomic development, livelihood, agriculture, and water management. While existing drought monitoring systems have characterized drought impact at different scales, policymaking and management require drought assessment at sub-district or taluka (sub-district) levels. Here, we develop high-resolution (250 m) agriculture drought indices for the Indian region to overcome the shortcomings of the coarse resolution datasets. We used the co-kriging to downscale the Land Surface Temperature (LST) from 1000 m to 250 m. The LST and Enhanced Vegetation Index (EVI) are obtained at 8-day intervals at 250 m spatial resolution. The high-resolution datasets show significant improvement in identifying the severity and coverage of drought. Soil Moisture Agriculture Drought Index (SMADI), which accounts for water stress and vegetation lag response, shows high reliability in drought detection. We evaluated drought extent and severity using the newly developed dataset and found that the high-resolution dataset can be used to separate the irrigation impact on drought alleviation. The high-resolution drought indices from SMADI and the Normalized Vegetation Supply Water Index (NVSWI) effectively represent the drought conditions at district and taluka levels that can be used in drought impacts assessments in India.

This preprint has been withdrawn.

Anukesh Ambika and Vimal Mishra

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-81', Anonymous Referee #1, 31 Jul 2022
  • RC2: 'Comment on essd-2022-81', Anonymous Referee #2, 13 Aug 2022

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-81', Anonymous Referee #1, 31 Jul 2022
  • RC2: 'Comment on essd-2022-81', Anonymous Referee #2, 13 Aug 2022

Anukesh Ambika and Vimal Mishra

Data sets

High-resolution (250 m) dataset for drought assessment in India Anukesh Krishnankutty Ambika; Vimal Mishra https://doi.org/10.5281/zenodo.6798442

Anukesh Ambika and Vimal Mishra

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This preprint has been withdrawn.

Short summary
Understanding the impacts of drought on agriculture is hampered due to the lack of high-resolution data in India. Moreover, most of the existing drought monitoring system do not account for the influence of irrigation on drought mitigation. To fill these crucial gaps in drought assessment capability, we develop a high-resolution (250 m) dataset of land surface temperature (LST) and enhanced vegetation index (EVI) for India for 2000–2017 period.