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Updated: Jun 12, 2025

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Modelling drought in South Africa: meteorological insights and predictive parameters.

Nnaemeka Onyeuwaoma1, Venkataraman Sivakumar2,3, Mahesh Bade2

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Keywords:
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Area of Science:

  • Environmental Science
  • Meteorology
  • Artificial Intelligence

Background:

  • South Africa faces persistent drought challenges, causing significant economic impact.
  • The Western Cape experienced a severe drought from 2015-2018, leading to national disaster status and strict water rationing in Cape Town.
  • Recurring droughts necessitate improved prediction models for water resource management.

Purpose of the Study:

  • To develop and evaluate Artificial Neural Network (ANN) models for drought prediction in South Africa.
  • To assess the efficacy of various meteorological variables and aerosol parameters in drought simulation.
  • To identify key parameters and location-specific factors influencing drought prediction accuracy.

Main Methods:

  • Utilized Artificial Neural Network (ANN) for drought prediction simulations.
  • Employed the Standard Precipitation Index (SPI) as the primary drought indicator, following WMO guidelines.
  • Incorporated meteorological data (relative humidity, temperature, soil wetness, evapotranspiration, evaporation, sea surface temperature) and aerosol optical depth across four South African locations over 21 years.

Main Results:

  • ANN models demonstrated significant predictive capabilities, with R² values varying by location and SPI timescale (SPI3 and SPI6).
  • Evapotranspiration (et) was identified as a crucial parameter for accurate drought simulation.
  • Predictive accuracy varied considerably across different locations, indicating no universal drought prediction scheme.

Conclusions:

  • Artificial Neural Networks (ANN) are effective tools for drought studies and simulations in South Africa.
  • Location-specific factors significantly influence drought prediction models.
  • The study provides valuable insights for simulating future drought scenarios across South Africa, aiding water resource planning.