Fig 1.
Agro-ecological zones of Embu County in Kenya (inset) with locations of the meteorological stations and locations of the farmers covered by the survey.
Table 1.
Agro-ecological zone (AEZ) wise number of households covered by the household survey and the administrative divisions they belong to in Embu county.
Table 2.
Important characteristics of the representative soil profiles used with crop simulation models and the agro-ecological zones they represent.
Table 3.
Maize varieties used by farmers and the identified equivalent in the model.
Fig 2.
Relationship between maize yieids reported by farmers and simulated by APSIM (left) and DSSAT (right).
Red solid line represents 1:1.
Table 4.
Genetic coefficients for three maize varieties derived from the calibration with APSIM and DSSAT using experimental data from Embu, Kenya.
Table 5.
Kendall Tau significance test for annual and seasonal temperature at Embu and rainfall at all the four locations.
Fig 3.
Trends in annual, long rain (LR)-Season and short rain (SR)- maximum temperature (top) and minimum temperature (bottom) at Embu, Kenya with linear trend line.
Fig 4.
Ten year moving coefficient of Variation (CV) of rainfall from 1980 during the short rain (SR) season at the four sites in Embu County, Kenya.
(The analysis is limited to 1997 since the data for remaining years is gap filled with AgMERRA data).
Fig 5.
Projected changes in maximum and minimum temperatures (absolute change) and in rainfall (percent deviation from historie rainfall) by 20 GCMs under RCP 4.5 (upper) and 8.5 (lower) by End- century for Embu, Kenya.
Fig 6.
Probability density function of projections in maximum temperature by GCMs at Embu (left) and Ishiara (right) in Embu county, Kenya (red dotted line denotes observed temperature).
Table 6.
Observed (average of three seasons) and DSSAT and APSIM modeled phenology and grain and biomass yields of three maize varieties.
Fig 7.
Changes in maize yields (%) from baseline as simulateci by APSIM (above) and DSSAT (below) with future climàtic conditions from 20 GCMs by end Century under RCP 8.5 in different agro ecological zones of Embu county, Kenya without elevated C02.
Fig 8.
Impact of climate change on the performance of different maize varieties under cultivation in different AEZs in Embu county of Kenya.
Table 7.
Adaptation strategy for different agro-ecological zones with best combination of planting time, plant population, variety and fertilizer nitrogen for LR and SR seasons.
Fig 9.
Changes in maize yields (%) from baseline as simulated by APSIM (above) and DSSAT (below) with future climate projections from 20 GCMs by end Century under RCP 8.5 in different agro-ecological zones of Embu county, Kenya with elevated CO2.
Fig 10.
Projected increase in maize productivity with adaptation compared to non-adoption in different agro-ecological zones under different climate change scenarios based on APSIM (above) and DSSAT (below) simulated yields.
The deviation is the percent increase in current yields com pared to average yield with projections by 20 GCMs.
Fig 11.
Average cumulative rainfall during SR (Oct-Dec period) and LR (Mar-May) seasons at Embu, Kenya.