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Early warning systems development for agricultural drought assessment in Nigeria

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Abstract

The existing drought monitoring mechanisms in the sub-Saharan Africa region mostly depend on the conventional methods of drought monitoring. These methods have limitations based on timeliness, objectivity, reliability, and adequacy. This study aims to identify the spread and frequency of drought in Nigeria using Remote Sensing/Geographic Information Systems techniques to determine the areas that are at risk of drought events within the country. The study further develops a web-GIS application platform that provides drought early warning signals. Monthly NOAA-AVHRR Pathfinder NDVI images of 1 km by 1 km spatial resolution and MODIS with a spatial resolution of 500 m by 500 m were used in this study together with rainfall data from 25 synoptic stations covering 32 years. The spatio-temporal variation of drought showed that drought occurred at different times of the year in all parts of the country with the highest drought risk in the north-eastern parts. The map view showed that the high drought risk covered 5.98% (55,312 km2) of the country’s landmass, while low drought risk covered 42.4% (391,881 km2) and very low drought risk areas 51.5% (476,578 km2). Results revealed that a strong relationship exists between annual rainfall and season-integrated NDVI (r2 = 0.6). Based on the spatio-temporal distribution and frequency of droughts in Nigeria, drought monitoring using remote sensing techniques of VCI and NDVI could play an invaluable role in food security and drought preparedness. The map view from the web-based drought monitoring system, developed in this study, is accessible through localhost.

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Authors and Affiliations

  1. Department of Strategic Space Applications, National Space Research and Development Agency (NASRDA), Abuja, Nigeria

    Oluwatola Adedeji, Godstime James & Halilu Ahmad Shaba

  2. Department of Geography, University of the Free State, Bloemfontein, South Africa

    Adeyemi Olusola & Samuel Adelabu

  3. Centre for Environmental Management, University of the Free State, Bloemfontein, South Africa

    Israel Ropo Orimoloye

  4. Department of Geography and Environmental Science, University of Fort Hare, Alice, South Africa

    Israel Ropo Orimoloye

  5. K. Banerjee Centre of Atmospheric & Ocean Studies, IIDS, Nehru Science Centre, University of Allahabad, Prayagraj, Uttar Pradesh, 211002, India

    Sudhir Kumar Singh

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Adedeji, O., Olusola, A., James, G. et al. Early warning systems development for agricultural drought assessment in Nigeria. Environ Monit Assess 192, 798 (2020). https://doi.org/10.1007/s10661-020-08730-3

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