http://oar.icrisat.org/id/eprint/10089 2018-03-06T07:14:02Z info:eu-repo/semantics/descriptiveMetadata http://oar.icrisat.org/10089/ Adapting Nyando smallholder farming systems to climate change and variability through modeling Tobias, O R Gachene, C K K Claessens, L Smallholder Farmers Smallholder Agriculture Farming Systems Climate Change This study was done in Nyando, Kenya to model maize production under different climate scenarios and project the yields up to 2030 and 2050 using Decision Support System for Agrotechnology Transfer (DSSAT) under rain fed conditions. Three maize varieties were used; Katumani Comp B as early maturing variety, Hybrid 511 as a medium maturing variety and Hybrid 614 as a late maturing variety. Global coupled model Hadley Centre Global Environment Model version 2 (HadGEM2-ES) under representative concentration pathways (RCP) 4.5 and 8.5 was used to downscale Nyando’s climate data for the years 2030 and 2050. Past climate data for 53 years and current data was obtained from Kisumu Meteorological station while crop growth and farm management data was obtained from 70 farmers in Nyando. Results showed a decrease in yields across the years from 2015, 2030 and 2050 under both RCP 4.5 and 8.5. Average simulated yields for 2015 were 2519 kg ha-1 while projected yields under RCP 4.5 were 2212 and 2081 kg ha-1 in 2030 and 2050 respectively. Average yield projections under RCP 8.5 were 2184 and 1806 kg ha-1 for the years 2030 and 2050 consecutively. The study found out that temperatures will increase and rainfall duration will reduce. In addition, Katumani Comp B maize variety was not very much affected by these changes in temperatures and rainfall compared to H511 and H614. Academic Journals 2017 Article PeerReviewed application/pdf en http://oar.icrisat.org/10089/1/4D7E0A964989.pdf Tobias, O R and Gachene, C K K and Claessens, L (2017) Adapting Nyando smallholder farming systems to climate change and variability through modeling. African Journal of Agricultural Research, 12 (26). pp. 2178-2187. ISSN 1991-637X http://dx.doi.org/10.5897/AJAR2017.12421 10.5897/AJAR2017.12421 info:eu-repo/semantics/objectFile info:eu-repo/semantics/humanStartPage