Multi-satellite precipitation products for meteorological drought assessment and forecasting in Central India

Varsha Pandey, Prashant K. Srivastava, R. K. Mall, Francisco Munoz-Arriola, Dawei Han

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


In this study, a comparative analysis of three satellite precipitation products including the Tropical Rainfall Measuring Mission (TRMM-3B43 V7), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS V2) with ground-measured Indian Meteorological Department (IMD) precipitation data were performed to estimate the meteorological drought in the Bundelkhand region of Central India. The high-resolution CHIRPS data showed the closest agreement with the IMD precipitation and well captured the drought characteristics. The Standardized Precipitation Index (SPI) identified seven major droughts events during the period of 1981 to 2016. Appropriate calibration and validation were performed for drought forecasting using the Auto-Regressive Integrated Moving Average (ARIMA) model. The forecasting result showed a reasonably good agreement with the observed datasets with the one-month lead time. The outcomes of this study have policy level implications for drought monitoring and preparedness in this region.

Original languageEnglish (US)
Pages (from-to)1899-1918
Number of pages20
JournalGeocarto International
Issue number7
StatePublished - 2022


  • ARIMA model
  • Meteorological drought
  • SPI
  • forecasting
  • precipitation

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Water Science and Technology


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