Abstract
Up to 95 % of food production in Tanzania depends on rainfall, whose timing, quantity and distribution is highly affected by climate variability and will highly likely change as a result of global warming. Several analyses have been done on the response of several crops in different agro-ecological zones and cropping systems to the impacts of changing climate and interactions of several climate variables have been highlighted. Many of the previous efforts have based on aggregations at sub-national and national scales, and have not considered the impacts and adaptation initiatives on individual fields, where the impacts will be directly felt. In this study, we quantify climate change impacts and adaptation for coping with future climate by individual farm fields in the Wami River sub-basin in Tanzania. The assessment was based on two RCPS and five downscaled GCMs with two time periods up to year 2100, involving a total of 168 farm fields. Maize yield change was projected to be in the negative direction for all the GCMs in both RCPs and periods. Organic matter application was an important climate change adaptation option whereas nitrogen fertilizer would only be suitable in more humid, rather than in semi-arid sections of the study area. We conclude that farm level climate change impacts quantification and adaptation assessment is key in designing sound adaptation strategies based on biophysical and socioeconomic endowments.
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Acknowledgement
Authors of this study wish to acknowledge Agricultural Model Inter-comparison Project (AgMIP) and Enhancing Climate Change Adaptation in Agriculture and Water Resources (ECAW) Project through the Soil Water Management Research Programme at Sokoine University of Agriculture (SUA) for technical and financial support for implementing this study.
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Mourice, S.K., Mbungu, W., Tumbo, S.D. (2017). Quantification of Climate Change and Variability Impacts on Maize Production at Farm Level in the Wami River Sub-Basin, Tanzania. In: Ahmed, M., Stockle, C. (eds) Quantification of Climate Variability, Adaptation and Mitigation for Agricultural Sustainability. Springer, Cham. https://doi.org/10.1007/978-3-319-32059-5_13
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