| dc.description.abstract | Integrating timely and accurate climate forecasts specifically rainfall based information
is crucial in the development of strategies aimed at improving and stabilizing crop yields
for rain dependent agriculture in Uganda. Timely and accurate climate forecasts
information are also vital for the mitigation of the negative impacts on agriculture and
food security. The limitation of such information has been quite devastating to the
dominant rain dependent agriculture activities in Uganda.
The overall objective of the study was to derive optimum cropping calendars for Uganda
based on rainfall information as a viable and sustainable option for up grading rain-fed
agriculture for crop yield stability/improvement. The specific objectives included
derivation, quantification and characterization of rainfall based information needed in the
formulation of optimum cropping calendars; Investigation of the level of yield
sustainability resulting from understanding crop phenology and effective utilization of
rainfall information and make recommendations for yield improvement; and
development of rainfall information based crop yield forecasting tools. The datasets
used in the study included observed daily/pentad rainfall, daily soil water balance, daily
maximum and minimum temperature and sunshine hours together with observed field
crop data.
The statistical methods used in the study included use of mass curves for data quality
control; Principal Component Analysis and cluster analysis for harmonization of
selected stations with homogeneous zones from past studies and use of mass curves,
soil moisture balance model and frequency distribution and probability of occurrence of
rainfall events during the season for derivation of seasonal characteristics such as
onset, withdrawal and duration of rains. Field crop experimental methods were used for
analysis of crop phenological stages, crop genetic coefficients and crop water
requirements. Also obtained from field experiments were growth and yield data for
investigation of the level of yield sustainability. A minimum data set on the phenological
evolution of the cereal crops was assembled and used as a genotype file in adapting
cereal (maize, millet, sorghum) crops growth model tool for crop yield forecasting.
The results obtained from quality control including correlation and regression tests
indicated that only single straight lines could be fitted to rainfall records from most of the
stations and this was indicative of the acceptable quality of rainfall records data used in
the study. Spatial mode Principle Component Analysis factor solutions and cluster
analysis results confirmed that the homogenous zones delineated during this study
compare very well with those from past studies with slight differences probably
attributed to the use of pentads rather than monthly or seasonal timescales that smooth
out the pentad effects. Seventeen zones, fifteen zones and sixteen zones were
delineated for March to May, June to August and October to December seasons
respectively. The regions derived from cluster analysis were generally consistent with
those obtained using Principle Component Analysis.
The results obtained from mass curves revealed that spatial/temporal progress of onset
of rains in Uganda exhibits a South to North orientation for March to May season with
cessation dates generally uniform across the country. The Onset and cessation results
of the October to December season revealed reverse trends to the March to May
season with a uniform onset acrossthe country and progress in cessation exhibiting
north eastern to south western orientation. Results indicated that early/late onset do
not normally signal good/bad rainfall seasons. Results obtained from the soil moisture
balance model for the same seasonal characteristics were similar to those obtained
using rainfall data. It was however evident that use of soil moisture balance added more
clarity. Results from frequency/probability analysis revealed that one day rainfall events
were higher and the frequency/probability of the lonqer spell lengths decreased
exponentially with the number of days of spells.
The results from Crop phenological stages analysis and genetic coefficients indicated
that the physiological cycle of the cereal crops used in the study exhibited consistent
similarity trends before flowering with the highest differences becoming real at flowering
and physiological maturity stages. A similar trend was observed from results of the
genetic coefficient analysis with genetic coefficients performing considerably better in
estimating crop stage duration.
The results from crop water requirement analysis revealed that the level at which crop
water requirements are met during the physiological cycle ·of the crop has a decisive
influence on crop yield. The results further indicated that the seasonal characteristics
defined for the locations in the study especially average onset dates of the season,
provide the best options in matching crop water requirements with the possibilities
offered by the season. The level at which crop water requirements 'are met specifically
during the grain setting and filling period plays a crucial role in yield formation. The
results obtained from crop water requirements analysis indicated elaborate skill in
providing guidelines for the formulation of optimum cropping calendars with the average
onset season registering consistently higher crop yields.
This study has for the first time regionalized Uganda into onset, cessation and length of
growing period zones using rainfall and soil moisture availability data. The soil moisture
balance technique improved skills in detecting onset and cessation dates in areas that
had poor skills with rainfall data.
It is the first time that a study has developed guidelines for optimum cropping calendars
based on rainfall/soil moisture availability that can be used for improvement/stabilizing
crop yields in the country. The study further highlights the vital need for use of
knowledge of crop water requirements for individual crops and phenological stages of
crop development. Finally, it is the first time a study has validated a crop growth model
tool for yield forecasting in the country that would enable optimum use of rainfall
information to address crop yield improvement/stability and thus contribute to
sustainable development in the region | en |
