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Drought assessment through multiple indicators for Karnataka state, India.

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Summary
This summary is machine-generated.

This study compared drought indices like SPI and ESI to assess crop production impacts. SPI-6 and ESI best correlated with crop anomalies, aiding drought monitoring.

Keywords:
Area under droughtCorrelationDrought monitoringFoodgrain productionIndices

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Area of Science:

  • Agricultural Science
  • Environmental Science
  • Remote Sensing

Background:

  • Drought indices are crucial for assessing drought's impact on agriculture and society.
  • Selecting appropriate indices is vital for understanding crop stress conditions.
  • This study evaluates multiple drought indicators for agricultural applications.

Purpose of the Study:

  • To conduct a comparative analysis of various drought indices.
  • To examine the spatio-temporal patterns of these indices and their relationship with crop production anomalies.
  • To identify the most effective drought indicators for monitoring agricultural drought.

Main Methods:

  • Compared Standardized Precipitation Index (SPI), Water level Index (SWI), Reservoir Level Index (SRLI), MODIS NDVI, NDVI Anomaly, VCI, and ESI.
  • Analyzed spatio-temporal patterns from 2001-2019 for Kharif crop growing seasons.
  • Correlated index data with detrended Kharif foodgrain production anomaly (DPA).

Main Results:

  • The region experienced 15 drought events between 2001 and 2019.
  • SPI-6 (correlation coefficient: 0.76) and ESI (0.74) showed the strongest correlation with DPA.
  • SPI-3, SPI-6, VCI, and ESI effectively captured drought extent, with correlations ranging from 0.62 to 0.82.

Conclusions:

  • SPI-6 and ESI are highly effective indicators for monitoring drought impacts on crop production.
  • The findings aid in selecting critical drought monitoring indicators for agricultural regions.
  • Comparative analysis provides valuable insights for drought management strategies.