Adding value to field-based agronomic research through climate risk assessment: A case study of maize production in Kitale, Kenya uri icon

abstract

  • In sub-Saharan Africa (SSA), rainfed agriculture is the dominant source of food production. Over the past50 years much agronomic crop research has been undertaken, and the results of such work are used informulating recommendations for farmers. However, since rainfall is highly variable across seasons theoutcomes of such research will depend upon the rainfall characteristics of the seasons during which thework was undertaken. A major constraint that is faced by such research is the length of time for whichstudies could be continued, typically ranging between three and five years. This begs the question as towhat extent the research was able to ?sample? the natural longer-term season-to-season rainfall variability.Without knowledge of the full implications of weather variability on the performance of innovations beingrecommended, farmers cannot be properly advised about the possible weather-induced risks that theymay face over time. To overcome this constraint, crop growth simulation models such as the AgriculturalProduction Systems Simulator (APSIM) can be used as an integral part of field-based agronomic studies.When driven by long-term daily weather data (30+ years), such models can provide weather-induced riskestimates for a wide range of crop, soil and water management innovations for the major rainfed crops ofSSA.Where access to long-term weather data is not possible, weather generators such as MarkSim can beused. This study demonstrates the value of such tools in climate risk analyses and assesses the value of theoutputs in the context of a high potential maize production area in Kenya. MarkSim generated weatherdata is shown to provide a satisfactory approximation of recorded weather data at hand, and the output of50 years of APSIM simulations demonstrate maize yield responses to plant population, weed control andnitrogen (N) fertilizer use that correspond well with results reported in the literature.Weather-induced riskis shown to have important effects on the rates of return ($ per $ invested) to N-fertilizer use which, acrossseasons and rates of N-application, ranged from 1.1 to 6.2. Similarly, rates of return to weed control andto planting at contrasting populations were also affected by seasonal variations in weather, but were alwaysso high as to not constitute a risk for small-scale farmers. An analysis investigating the relative importanceof temperature, radiation and water availability in contributing to weather-induced risk at different maizegrowth stages corresponded well with crop physiological studies reported in the literature

publication date

  • 2011
  • 2011