Introduction Studies of adaptation to current climate make it clear that farmers’ activities are not now always as well adapted to climate as they might be. The mounting losses from great natural disasters are in substantial part associated with extreme atmospheric events. However, it has been shown that these losses cannot be ascribed to these events alone, but are also due to lack of appropriate human adaptation (Burton et al., 1993). This result raises the idea that adaptation strategies employed by farmers might not reduce vulnerability to climate change; instead, they might even increase it. Consequently, this study aims to investigate how farm households’ decision to adapt to weather changes affects farm income in the Savanna region in Togo. In addition, we analysed the effect of farm size on adaptation to climate change strategies. The assessment of adaptation strategies’ impact is important to inform policy for future successful adaptation of the agricultural sector. Materials and methods The data comes from a household survey implemented within the Savanna region of Togo in the agricultural year on 450 agricultural households and from literature on the topic. After cleaning it remain 444 households. To achieve the purpose of this paper, the farm households were firstly grouped into homogenous groups using clustering technique. Then a recursive dynamic mathematical programming model (bio-economic modelling) is built based on Agricultural Household Model theory. The model is run for time planning horizon of ten years. Market imperfections are included. Climate is incorporated through the probabilities of occurrence of the state of nature related to rainfall conditions, namely good, normal, bad, disastrous due to flood, disastrous due to drought. The objective of the farmers is to maximize the discounted expected farm income from cropping and livestock. Risk is taken into account through Telser’s safety first approach (Telser 1955). After calibration the model was used for simulation experiments. Results From clustering technique, the households in the data set were grouped into 4 clusters. However, for simulation analysis only two of them were referred as wealthier farmers’ group and poor farmers’ group are considered. These two clusters were chosen for the reason that they represent extreme cases in our data set. The simulations of climate change impact results show a significant drop in farm income under the climate change scenario. The decline of average farm income compared to the baseline level is about 52% for poor farmers’ group and 46% for wealthier farmers’ group. However, the adaptations’ impact simulations depicted in figure 1 reveal that an increases of the intensity of most of the adaptation strategies mitigate the negative effects of climate change. Indeed, farmers within poor farm group would benefit from an increase in farm income of 53.78% while wealthier farmers will gain 61.59% from an increase of irrigated area by 25%. Moreover, an increase of operated land size reduces climate impact by 8.21% and 2.94% for poor farm group and wealthier farmer’s group respectively. By contrast, less fertilization appears to increase farmers’ vulnerability regardless farmers’ group. Furthermore, the simulation experiment that average increase of farm size by 15% leads to a decrease of irrigated area by 7.8% for poor farmers’ group and 9.3% for wealthier farmers’ group. In contrast, area under soil conservation increases for both groups. Indeed, on average farmers within poor farmers’ group would experience an increase of soil conservation area by 2.1% as a result of 15% increase of farm size while those in wealthier farmers’ group will experience 1.5% increase (figure 2). Conclusions The results of this study highlight the possibility of reducing climate change impact by the use of adaptation. Indeed, increase in the intensity of all the strategies used in the study site, except reduction in the use of fertilizer, has positive effect on farm income. Moreover, adoption of irrigation has a win-win outcome. It helps in coping the adverse effects and risk of climate change while increasing agricultural productivity. By contrast, reduction in the use of fertilizer appears to increase farm households’ vulnerability. Thus, prior to any adaptation strategy promotion policy, the identification of yield-enhancing adaptations among the available strategies is therefore a crucial step. The results reveal also that farm size based adaptation hypothesis should be rejected for the study area. Small farms are doing as well as large farms in terms of adoption of adaptation to climate change. Any promotion of large farms as adaptation support policy could be a blind policy. Literature cited Telser L., Safety First and Hedging : The Review of Economic Studies, Vol. 23, No. 1 Burton, I. and S.J. Cohen, 1993: Adapting to global warming: regional options. In: Proceedings of the International Conference on the Impacts of Climatic Variations and Sustainable Development in the Semi-Arid Regions, A Contribution to UNCED [Magelhães, A.R. and A.F. Bezerra(eds.)]. Esquel Brazil Foundation, Brasilia, Brazil, pp. 871–886.. Mikemina Pilo 1, Tobias Wünscher 2,Taladidia Thiombiano 3 1. Economy, University Cheickh Anta Diop, Senegal 2. Center for development research (ZEF), University of Bonn, Germany 3. Economy, Université de Ouagadougou, University de Ouagadougou Impact Of Adaptation Strategies On Farm Households’ Income: Does Farm Size Matter? Evidence From The Savanna Region in Togo Acknowledgements This paper is based on a ph.D thesis going on under African Science Service Center on Climate Change and Adapted Land Use (WASCAL) project. Figure 1: Percentage of change in average farm income Figure 2: Effect of 15% increase of farm size on irrigation and soil conservation in %