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In this study, the Land Use Dynamic Simulator model was applied to investigate the impact of farm credit as an adaptation strategy to cope with effects of climate variability on agricultural land‐use change and crop production in the Vea watershed in Ghana. The authors identified the determinants of crop choices within the landscape (e.g., farm household and biophysical characteristics of farm plot). The crop choice sub‐model was then linked to the crop yield sub‐model to determine the yields of selected crops. In adapting to the impacts of climate variability, the maize credit adoption sub‐model under the maize cultivation credit scenario was integrated into decision‐making. This was simulated for a 20‐year period, and compared with the business‐as‐usual scenario. Under the simulated maize credit scenario, maize adopters increased from about 20 per cent to about 50 per cent and the area allocated for maize cultivation significantly increased by about 266 per cent. Consequently, the average annual aggregated household crop yield increased by 6.3 per cent higher than in the business‐as‐usual scenario. This simulation study shows that access to maize credit can significantly influence agricultural land‐use change and food availability in the study area. However, although access to farm credit may translate into food availability, the sustainability of this strategy is questionable. [ABSTRACT FROM AUTHOR]

This study determined the social vulnerability index (SoVI) of households to climate change impacts for three identified locations (upper, mid and lower) in the Vea catchment, semi-arid Ghana. This study adapted the social, economic and demographic indicator approach. The data used were obtained from a survey of 186 randomly sampled farm households and direct field measurements of 738 farm plots belonging to the same sampled farm households. Information from the literature, expert judgement and principal component analysis were useful for computing and analysing the SoVI. The variables were normalized, weighted and subsequently recombined to determine the index of the three locations towards climate change. Although the SoVI to climate change was highest (0.77) for the upper part of the catchment, the mid- and lower parts of the catchment show a high SoVI of 0.72 each. The overall SoVI for the catchment is 0.73. The study re-emphasizes the high vulnerability level of dry areas to climate change. Moreover, it shows there is variability at micro-scale. There is a need to put appropriate measures to address the vulnerability of households to climate change in the semi-arid areas of West Africa. Factors aggravating dry land’s vulnerability towards climate change should be prevented with implementable policies. Furthermore, it is important to identify conditions that have made some areas less vulnerable to climate change, and then, we can work out the possibility of adapting such to the vulnerable places. [ABSTRACT FROM AUTHOR]