The Relationship between Changes in Hydro-Climate Factors and Maize Crop Production in the Equatorial African Region from 1980 to 2021

Author:

Nooni Isaac Kwesi1ORCID,Ogou Faustin Katchele2ORCID,Hagan Daniel Fiifi Tawiah3ORCID,Saidou Chaibou Abdoul Aziz4ORCID,Prempeh Nana Agyemang5ORCID,Nakoty Francis Mawuli6ORCID,Jin Zhongfang7ORCID,Lu Jiao1

Affiliation:

1. School of Atmospheric Science and Remote Sensing, Wuxi University, Wuxi 214105, China

2. Laboratory of Atmospheric Physics, Department of Physics, University of Abomey-Calavi, Cotonou 01 BP 526, Benin

3. Hydro-Climate Extremes Lab, Ghent University, 9000 Ghent, Belgium

4. Département de Physique, Faculté des Sciences et Techniques, Université Abdou Moumouni, Niamey BP 10662, Niger

5. School of Geosciences, Department of Atmospheric and Climate Science, University of Energy and Natural Resources, Sunyani P.O. Box 214, Ghana

6. School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China

7. School of Electronic and Information Engineering, Wuxi University, Wuxi 214105, China

Abstract

Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen’s slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson’s correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day−110a−1. Other climate variables increased at different rates: SM at 0.02 mmday−110a−1, E at 0.03 mm day−110a−1, Ep at 0.02 mm day−1 10a−1, TMIN and TMAX at 0.01 °C day−110a−1. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions.

Funder

Wuxi University Starting Project

Publisher

MDPI AG

Reference75 articles.

1. IPCC (2021). Climate Change 2021: The Physical Science Basis.

2. Zommers, Z., and Alverson, K. (2018). Resilience, Elsevier.

3. Karl, T.R., Melillo, J.M., and Peterson, T.C. (2009). Global Climate Change Impacts in the United States, Cambridge University Press.

4. Warming reduces global agricultural production by decreasing cropping frequency and yields;Zhu;Nat. Clim. Chang.,2022

5. IPCC (2014). Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects.

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