Adjusting Historical Rainfall Data for agricultural Research: A case Study of Makindu

Abstract

There is much concern worldwide about how climate change would impact '-' rainfed agriculture in developing countries, since many in their farming population are small scale and depend on rain. Farmers get information about the risk of cultivating in the expected weather from meteorologists. Their governments also contribute by advising on farming practices and subsidizing the cost of fertilizers. The governments use credible information from researchers, one such is the International Crop Rresearch Institute for the Semi-Arid Tropics (ICRISAT). In 2008, ICRISAT researchers conducted a research project on how to mitigate and adapt to climate change and concluded that with improved practices, there was hope for rain fed agriculture even under climate change. One of their Kenyan sites used in the ICRISAT research was Makindu, approximately 170 km South East of Nairobi. In this thesis, using climate data for Makindu, a test was conducted to see the difference in rainfall amount, start of rains and resultant yield when rainfall amount and pattern were changed. Since climate was the variable under investigation, fifty years of rainfall data was collected from the Kenya Meteorological Department for use. After cleaning up the data, GenStat was used to create climate change scenarios by adjusting the number of rainy days, spells and rainfall amount by 10%. The analysis showed that changing pattern would result in varying rainfall but delayed the start in rains. The four climate scenarios were then entered into APSllv1 (Agricultural Production System sllv1u1ator)which simulated crop yield. Overall, change in amount of rain had the most effect on yield. However when looking at the long rains and short rains, change in patterns had more effect than when the change was affecting only the amount.