Analysis of drought characteristics and their relationship with crop yield in northwestern Nigeria

Ismaila Aliyu, Ifatokun Paul Ifabiyi, Toluwalope Mubo Agaja

Abstract


Drought is a temporary and recurring meteorological event, and the agricultural sector is the main victim of this natural but  least understood of all natural hazards in  Northwestern Nigeria Timely information about the onset of drought, extent, intensity, duration and impacts can reduced from planting to post harvesting stage. This study examines the relationship between drought characteristic and crop yield estimation. Secondary data were used in this study. Monthly rainfall (mm), monthly mean minimum and maximum temperature (Degree Celsius) were collected from Nigeria Meteorological Agency (NIMET) (1980 to 2021). Estimation of crop yield per hectare of rice, millet, and maize (2009–2021) were provided by National Agricultural Extension and Research Liaison Services (NAERLS). Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were use compute drought characteristics. Correlation and regression analyses were performed with SPI SPEI and crop yield anomaly. Results of correlation and regression analysis shows the behavior of drought indices varies: SPEI better predict yield at Kaduna (R 2= 80.3%) and Kano (R2 = 56.7%), while SPI perform better at Jigawa (R2 = 66.6%) and Kano (R2 = 66.6%) SPEI captured higher cases of drought occurrences than SPI. Hence, it is sensitive to drought quantification than SPI can be used as an indicator of regional crop production. Crop yield anomaly maize  has  positive linear correlation with  SPEI in Kaduna and Kebbi these  factors  can  be  effectively  used  for  monitoring  and  assessing  the  food  grain production,  and thereby  appropriate agricultural practices can be adopted to minimize drought effects.

 

Received: 15 October 2025

Accepted: 14 April 2026

Published: 10 May 2026


Keywords


Key word: Drought, Crop yield, SPI, SPEI, Relationship

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References


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DOI: https://dx.doi.org/10.21622/MACI.2026.03.1.1731

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Copyright (c) 2026 Ismaila Aliyu, Ifatokun Paul Ifabiyi, Toluwalope Mubo Agaja

Multidisciplinary Adaptive Climate Insights

E-ISSN: 3009-6332

P-ISSN: 3009-7924

 

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