Abstract: Rainfall is a major climatic parameter affecting
many sectors such as health, agriculture and water resources. Its
quantitative prediction remains a challenge to weather forecasters
although numerical weather prediction models are increasingly being
used for rainfall prediction. The performance of six convective
parameterization schemes, namely the Kain-Fritsch scheme, the
Betts-Miller-Janjic scheme, the Grell-Deveny scheme, the Grell-3D
scheme, the Grell-Fretas scheme, the New Tiedke scheme of the
weather research and forecast (WRF) model regarding quantitative
rainfall prediction over Uganda is investigated using the root mean
square error for the March-May (MAM) 2013 season. The MAM
2013 seasonal rainfall amount ranged from 200 mm to 900 mm over
Uganda with northern region receiving comparatively lower rainfall
amount (200–500 mm); western Uganda (270–550 mm); eastern
Uganda (400–900 mm) and the lake Victoria basin (400–650 mm). A
spatial variation in simulated rainfall amount by different convective
parameterization schemes was noted with the Kain-Fritsch scheme
over estimating the rainfall amount over northern Uganda (300–750
mm) but also presented comparable rainfall amounts over the eastern
Uganda (400–900 mm). The Betts-Miller-Janjic, the Grell-Deveny,
and the Grell-3D underestimated the rainfall amount over most
parts of the country especially the eastern region (300–600 mm).
The Grell-Fretas captured rainfall amount over the northern region
(250–450 mm) but also underestimated rainfall over the lake Victoria
Basin (150–300 mm) while the New Tiedke generally underestimated
rainfall amount over many areas of Uganda. For deterministic rainfall
prediction, the Grell-Fretas is recommended for rainfall prediction
over northern Uganda while the Kain-Fritsch scheme is recommended
over eastern region.
Abstract: A cross sectional study design and standard
microbiological procedures were used to determine the prevalence
and antimicrobial susceptibility patterns of Escherichia coli,
Salmonella enterica serovar typhimurium and Vibrio cholerae O1
isolated from water and two fish species Rastrineobola argentea and
Oreochromis niloticus collected from fish landing beaches and
markets in the Lake Victoria Basin of western Kenya. Out of 162
samples analyzed, 133 (82.1%) were contaminated, with S.
typhimurium as the most prevalent (49.6%), followed by E. coli
(46.6%), and lastly V. cholerae (2.8%). All the bacteria isolates were
sensitive to ciprofloxacin. E. coli isolates were resistant to ampicillin,
tetracycline, cotrimoxazole, chloramphenical and gentamicin while
S. typhimurium isolates exhibited resistance to ampicillin,
tetracycline, and cotrimoxazole. The V. cholerae O1 isolates were
resistant to tetracycline and ampicillin. The high prevalence of drug
resistant enteric bacteria in water and fish from the study region
needs public health intervention from the local government.