Electronic Thesis and Dissertation Repository

Degree

Master of Engineering Science

Program

Civil and Environmental Engineering

Supervisor

Dr. Tim Newson

Abstract

Climate change is anticipated to have significant effects on agricultural production in sub-Saharan Africa as the magnitude of weather events increase in severity. Smallholder farmers in western Tanzania are potentially vulnerable to climate change impact as crops rely on precipitation as the only source of water. It is prudent to evaluate different modes of agricultural adaptations, such as agroforestry, that these farmers can easily adopt to improve their resiliency to the effects of climate change. System dynamics modelling is a cost-effective tool to simulate the long-term behaviour of agroforestry systems under future climate conditions. Water, Nutrient, and Light Capture in Agroforestry Systems (WaNuLCAS) is a system dynamics model developed by the World Agroforestry Centre that was selected to investigate long-term bio-physical interactions of maize and Acacia trees. This model was calibrated to data from field research on rotational woodlots conducted in Tabora, Tanzania from 1996 to 2002 by the World Agroforestry Centre.

Four sets of experimental simulations were conducted with the WaNuLCAS model to determine the response of the agroforestry system to changes. Firstly, the model was calibrated to the “baseline” field research in Tabora. Secondly, management practices were systematically applied to the baseline to study changes in maize and wood yields and the net present value of the system. Thirdly, changing climatic conditions were applied to the model. The climate change scenarios for this study were produced by selecting a number of global climate models and emission scenarios, downscaling that data, and generating a broad set of futures by means of a stochastic weather generator. The climate variables used in this research were daily precipitation, maximum temperature and minimum temperature. The baseline period for observed days was from 1975 to 2005. Mid-term and long-term climate change scenarios were generated for 2035 to 2065 and 2065 to 2095 respectively. Finally, climate change mitigation for the agroforestry system was tested using the extreme “hot-dry” scenario from the 2035-2065 time slice; three management practices from the second set of experiments were applied to evaluate the management practices for loss prevention in maize yields and agroforestry system value.

The application of fertilizers and flexible planting dates were determined to be the most effective management practices to improve yields for the baseline scenario. The climate ensemble for each time slice shows a range of attainable maize and wood yields. The baseline scenario 6 year maize yield was 5.47 Mg ha-1. The 6 year maize and wood yield ranges for 2035 to 2065 are 3.98 to 8.15 Mg ha-1 and 37.1 to 38.0 Mg ha-1, respectively. The 6 year maize and wood yield ranges for 2065 to 2095 are 6.45 to 7.71 Mg ha-1 and 36.2 to 39.1 Mg ha-1, respectively. These results indicate that most climate scenarios will positively impact maize production in this region as the mean growing season temperatures will approach optimal conditions, however, crop yields will continue to be erratic inter-annual variability of rainfall. Flexibility in crop calendar planting dates was the most important management practice in climate change mitigation. Earlier planting dates reduced maize losses by 50% and increased the net present value of the system by 90% over a 10 year period. The results of this research may be informative for policy makers for food security, climate change, and agriculture in Eastern Africa.

Additional Files
Downscaled GCMs for Eastern Africa.zip (266894 kB)
Maximum and minimum temperature and precipitation for 14 weather stations across Eastern Africa.
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