Seasonal rainfall is an important source of water for rainfed farming in the semi-arid
regions of the world, where rainfall is marginal and variable. However, as rains are
unpredictable in terms of onset, amount and distribution, there is a need to
understand the variability and other basic rainfall features in order to use the
information in agricultural decision making. More specifically, combining the seasonal
rainfall prediction with crop water requirement and soil water information is the core
component to successful agriculture. The ultimate objective of this study was to
characterize and obtain a better understanding of the most important rainfall features
that form the basis for classifying the areas into homogenous rainfall zones and then
to develop a seasonal rainfall prediction model for the Central Rift Valley (CRV) of
Ethiopia.
The source data for the analyses was primarily obtained from the National
Meteorological Services Agency (NMSA) and partly from Melkassa Agricultural
Research Centre (MARC) and the web site of the International Research Institute for
Climate and Society (IRI). Rainfall variability and time series analyses were done using
INSTAT 2.51 and coded time method, respectively. Rainfall onset and March-April-
May (MAM) rainfall totals are the two most variable features both at Miesso and
Abomssa. For both stations, rainfall end date displays the least variability.
Rainfall onset date at Miesso ranges from the lower quartile (25 percentile) of DOY 61
to the upper quartile (75 percentile) of DOY 179 with a 42% coefficient of variation
(cv). At Miesso, the main rainy season terminates during the last days of September (DOY 272 - 274) once in four years and terminates before DOY 293 in three out of
four years. At Abomssa, the c.v for the lower quartile (DOY 61) to the upper quartile
(DOY 134) was found to be 40.5%. At both locations, planting earlier than 15 March
(DOY 75) only proves successful once in every four years. Further, at Miesso this
upper quartile statistic can extend up to the DOY 179, whereas at Abomssa planting
earlier than 15 April (DOY 134) is possible in three out of four years (75 percentile). At
Abomssa, rainfall terminates by DOY 286 and the end of October (DOY 305) for the 25
and 75 percentile points respectively. From the time series analyses, there was no
conclusive evidence for the existence of a trend for both Miesso and Abomssa,
information which is useful for long-term research and development planning, as well
as seasonal rainfall prediction for the study area.
The classification study for the spatial rainfall pattern resulted in four homogenous
rainfall zones that form distinct development and research units, using the FORTRAN-
90 based NAVORS2 program. The south facing Alem Tena-Langano zone has a better
rainfall pattern than drier zones and thus formed zone 1. The southern, southwestern
and southeastern area has formed the wet zone (zone 2), the northwestern to
northeastern facing part (Debre-Zeit-Nazerth-Dera) that receives a higher rainfall
amount than zone 1 has formed zone 3 and finally, the drier northeastern part
constituted zone 4. Twenty seven seasonal rainfall prediction models with varied
performance skills that can be used for the operational farming were developed for the
March-September monthly rainfall using the Climate Predictability Tool (CPT v.4.01)
from IRI. It was understood that with increased observing networks and data
availability, useful operational climate prediction could be achieved for a smaller
spatial unit and with a short lead-time.
The tempo-spatial water requirement satisfaction pattern analyses were conducted
using AGROMETSHELL v.1.0 of the FAO. Fourteen concurrent sorghum-growing
seasons that give a general picture of crop water requirement satisfaction were
mapped. The southern, southwestern and southeastern parts (zone 2) of the CRV
constitute the most favourable location for growing a range of sorghum maturity
groups. The northwestern and central (zone 3) parts constitute the next most suitable
zone. The wide northeastern drylands (zone 4) of the study area, except the pocket
area of Miesso-Assebot plain, does not warrant economic farming of sorghum under
rainfed conditions. From the growth stage-based Water Requirement Satisfaction Index (WRSI) analyses,
mid-season / flowering stage of the sorghum cultivars was found to be three times
more sensitive to changes in sorghum yields for both cultivars and experimental sites
as compared to the WRSI from the rest of growth stages. The results from the water
production function analyses (WPF) also indicated the potential of WRSI for prediction
of the long-term sorghum yields.
The cumulative density function (CDF) and stochastic dominance analyses for the
120-day grain sorghum cultivar grown at Miesso show the June planting to be the
most efficient set by first degree stochastic dominance (FSD), while May was found
efficient for Melkassa. The CDF for Arsi Negele shows April planting date to be the
best set. Therefore, these planting dates are to be preferred by farmers seeking âmoreâ
yield at the respective locations, regardless of their attitude towards risk.
The sensitivity analyses conducted using different levels of the seasonal rainfall
related input variable combinations (sorghum planting date, maturity date, number of
rainy days and WRSI) for Miesso, Melkassa and Arsi Negele provide useful
information. By keeping input variables other than WRSI at the most preferred level
(i.e. early planting date, extended maturity date, and greater number of rainy days)
and only changing WRSI from 100% to 75% resulted in a 49.7% yield reduction in
case of Miesso, 40.8% in case of Melkassa and 24.3% in case of Arsi Negele. Further,
when WRSI was reduced down to 50%, there was a total crop failure in the case of
Miesso and Melkassa, while the reduction was 48.6% for the Arsi Negele case. Similar
results were found when WRSI was varied across other input level combinations.
Visual Basic v.6.0 was used to write the algorithm for the decision support tool (DST)
relating sorghum planting dates in CRV, to which the name ABBABOKA 1.0 was
given. By using the rainfall prediction information from three different sources (the
new prediction model developed in chapter 3, NMSA and ICPAC), ABBABOKA
suggests the best possible planting alternatives for a given homogenous rainfall zone
and planting season. When decision making under this predictive information alone is
not sufficient, soil water parameters need to be consulted for more reliable decision
making. This simple and briefly constructed ABBABOKA is expected to provide a suite
of guidelines to the users. Certainly, this constitutes a significant departure from the
fixed âbest betâ recommendations I learned from research systems in the past. It is recommended that the time-space classification of agricultural areas into
homogeneous zones needs to be extended to the rest of the country together with the
tailored rainfall prediction information. Research needs to be geared towards crop
water requirements, climate risks and simulation modelling aspects. A network of
weather stations and soil database needs to be developed in order to promote the soilcrop-
climate research in Ethiopian agriculture. More importantly, the use of decision
support tools and the well-established models (like APSIM) need to be included in
agricultural research and development efforts.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ufs/oai:etd.uovs.ac.za:etd-07302007-114824 |
| Date | 30 July 2007 |
| Creators | Diga, Girma Mamo |
| Contributors | Prof S Walker |
| Publisher | University of the Free State |
| Source Sets | South African National ETD Portal |
| Language | en-uk |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.uovs.ac.za//theses/available/etd-07302007-114824/restricted/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University Free State or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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