Drought vulnerability assessment of maize in Sub-Saharan Africa: Insights from physical and social perspectives

Abstract

Drought as a slow-onset phenomenon inflicts important losses to agriculture where the degree of vulnerability depends not only on physical variables such as precipitation and temperature, but also on societal preparedness. While the scopes of physical and social vulnerability are very different in nature, studies distinguishing these two aspects have been lacking. In this study we address the physical and social aspects of drought vulnerability of maize (CDVI phy and CDVI soc) in Sub-Saharan Africa (SSA). To quantify vulnerability, we applied a probabilistic framework combining a Drought Exposure Index (DEI) with a physical or social Crop Failure Index, CFI phy or CFI soc , respectively. DEI was derived from the exceedance probability of precipitation. Maize yields, simulated using the Environmental Policy Integrated Climate (EPIC) model, were used to build CFI phy , whereas the residual of simulated and FAO recorded yields were used to construct CFI soc. The results showed that southern and partially central Africa are more vulnerable to physical drought as compared to other regions. Central and western Africa, however, are socially highly vulnerable. Comparison of CDVI phy and CDVI soc revealed that societal factors cause more vulnerability than physical variables in almost all SSA countries except Nigeria and South Africa.. We conclude that quantification of both drought vulnerabilities help a better characterization of droughts and identify regions where more investments in drought preparedness are required.

Spatial assessment of maize physical drought vulnerability in sub-Saharan Africa: Linking drought exposure with crop failure

“…Five classifications could be defined between 0 and 1: wet, near normal, mild to moderate drought, severe to extreme drought, and exceptional drought (Svoboda et al 2002) (table 2). More details on the procedure to calculate DEI are explained in Kamali et al (2018b). Different probability distribution functions can be fitted to P and PCP-PET.…”

Disentangling the contribution of socioeconomic pathways to future climate-related risks : The case of heat stress

“…Conversely, the benefits of ambitious mitigation strategies could be annihilated by socioeconomic pathways comparable to the ones depicted in SSP3EU or in SSP4EU. This ability of varying levels of socioeconomic development to reduce (or increase) future heat-related challenges is due primarily to their impact on vulnerability -changes in population exposure being only of secondary importance -, confirming recent results in the field of hunger risk in which social vulnerability plays a major role (Davenport et al, 2017;Kamali et al, 2018). We therefore emphasize here that socioeconomic development pathways should not be viewed solely as potential means to reach a given level of radiative forcing, but also as key determinants of future climate risks, particularly when considering their impact on future populations' vulnerability -and not only on exposure.…”

Vulnerability Assessment of West African Countries to Climate Change and Variability

“…This con- socioeconomic factors that can enhance or reduce vulnerability of a system or country to climate change and variability. Several studies have reported that socioeconomic factors must be considered when analysing vulnerability to climate change and its extremes (Antwi-Agyei et al, 2012;IPCC, 2014;Kamali et al, 2018). High incidence of poverty is a major contributing factor to vulnerability in many countries in West Africa (Acheampong et al, 2014).…”