Markov Chain Modeling of Daily Rainfall in Lay Gaint Woreda, South Gonder Zone, Ethiopia

Information on seasonal Kiremet and seasonal Belg rainfall amount is important in the rain fed agriculture of Ethiopia since more than 85% of the population is dependent on agriculture particularly on rain fed farming practices. The distribution pattern of rainfall rather than the total amount of rainfall within the entire period of time is more important for studying the pattern of rainfall occurrence. A two-state Markov chain was used to describe the characteristics of rainfall occurrences in this woreda. The states, as considered were; dry (d) and rainy (r). The overall chance of rain and the fitted curve tells us that the chance of getting rain in the main rainy season is about twice as compared to the small rainy season. The first order Markov chain model indicates that the probability of getting rain in the small rainy season is significantly dependent on whether the earlier date was dry or wet. While the second order Marko chain indicates that the main rainy season the dependence of the probability of rain on the previous two dates\u27 conditions is less as compared with the small rainy season. Rainfall amounts are very variable and are usually modeled by a gamma distribution. Therefore, the pattern of rainfall is somewhat unimodial having only one extreme value in August. Onset, cessation and length of growing season of rainfall for the main rainy season show medium variation compared to the small rainy season

Effect of curing conditions and harvesting stage of maturity on Ethiopian onion bulb drying properties

The study was conducted to investigate the impact of curing conditions and harvesting stageson the drying quality of onion bulbs. The onion bulbs (Bombay Red cultivar) were harvested at three harvesting stages (early, optimum, and late maturity) and cured at three different temperatures (30, 40 and 50 oC) and relative humidity (30, 50 and 70%). The results revealed that curing temperature, RH, and maturity stage had significant effects on all measuredattributesexcept total soluble solids

Assessing the value of climate forecast information for pastoralists: Evidence from southern Ethiopia and northern Kenya

Climatic variability exerts tremendous influence on the livelihoods and well-being of pastoralists who inhabit the arid and semi-arid lands of the Horn of Africa. Recent advances in climate forecasting technologies have raised the intriguing prospect of reasonably accurate forecasts of coming seasons' rainfall patterns. Several donors and governments in the region are keenly interested in these technologies and in developing forecast delivery channels on the assumption that this information will prove valuable to the vulnerable populations it is meant to help not only indirectly, as an input into top-down early warning systems, but also directly, as a basis for improving choice under uncertainty. We explore the value of such external climate forecast information to pastoralists in a large study area spanning southern Ethiopia and northern Kenya using original data collected using both open-ended qualitative methods to identify and understand indigenous climate forecasting methods and quantitative data collected using survey instruments fielded in two rounds, one before and one after the long rains of 2001. The data show that pastoralists rely heavily on indigenous forecasting methods — in terms of having both access to and confidence in these methods — while external forecasts are less commonly received or believed. We elicited pastoralists' subjective, probabilistic expectations of the coming season's rainfall and find that neither use of nor belief in external forecasts causes any appreciable change in respondents' seasonal rainfall expectations. Moreover, relatively few pastoralists act on their own climate expectations, no matter how formed. In sum, climate forecast information does not seem a limiting factor at present in pastoralist communities in the Horn of Africa, not least of which because of the existence of a vibrant and still-relevant tradition of indigenous forecasting

Building A High-Resolution Vegetation Outlook Model to Monitor Agricultural Drought for the Upper Blue Nile Basin, Ethiopia

To reduce the impacts of drought, developing an integrated drought monitoring tool and early warning system is crucial and more effective than the crisis management approach that is commonly used in developing countries like Ethiopia. The overarching goal of this study was to develop a higher-spatial-resolution vegetation outlook (VegOut-UBN) model that integrates multiple satellite, climatic, and biophysical input variables for the Upper Blue Nile (UBN) basin. VegOut-UBN uses current and historical observations in predicting the vegetation condition at multiple leading time steps of 1, 3, 6, and 9 dekades. VegOut-UBN was developed to predict the vegetation condition during the main crop-growing season locally called “Kiremt” (June to September) using historical input data from 2001 to 2016. The rule-based regression tree approach was used to develop the relationship between the predictand and predictor variables. The results for the recent historic drought (2009 and 2015) and non-drought (2007) years are presented to evaluate the model accuracy during extreme weather conditions. The result, in general, shows that the predictive accuracy of the model decreases as the prediction interval increases for the cross-validation years. The coefficient of determination (R2) of the predictive and observed vegetation condition shows a higher value (R2 \u3e 0.8) for one-month prediction and a relatively lower value (R2 = 0.70) for three-month prediction. The result also reveals strong spatial integrity and similarity of the observed and predicted maps. VegOut-UBN was evaluated and compared with the Standardized Precipitation Index (SPI) (derived from independent rainfall datasets from meteorological stations) at different aggregate periods and with a food security status map. The result was encouraging and indicative of the potential application of VegOut-UBN for drought monitoring and prediction. The VegOut-UBN model could be informative in decision-making processes and could contribute to the development of operational drought monitoring and predictive models for the UBN basin

Geospatial forecast model for tsetse-transmitted animal trypanosomosis in Ethiopia

The aims of this study were to develop a geographic information systems (GIS) forecast and risk assessment model for cyclically transmitted trypanosomosis in Ethiopia by matching features in the environment to available information on the preferences and limits of tolerance of the parasite and its vector, and validate and further develop the GIS model using data from current and historical prevalence survey data and habitat microenvironment studies from trypanosomosis endemic areas. Results indicate that GIS model developed for parasitic diseases based on growing degree day (GDD) concept can be applied to tsetse-transmitted trypanosomosis. GIS for animal trypanosomosis was created using Food and Agriculture Organization – Crop Production System Zones (FAO-CPSZ) database and Normalized Difference Vegetation Index (NDVI) and maximum temperature (Tmax) from the Global Land 1km dataset. The two datasets used to determine the risk of tsetse flies and consequently animal trypanosomosis in Ethiopia indicated the magnitude of the disease and possible expansion of the “fly belt” in the future. The GIS model indicated the distribution and importance of tsetse-transmitted trypanosomosis in Ethiopia. Spatial and statistical analysis verified the use of GDD concept and climate forecast system that was developed to determine the suitability of a given environment for the proliferation of a biotype, in this case tsetse and trypanosomes. Results presented here indicate the importance of GDD and the two climatic variables (NDVI and Tmax) in the development of forecast model for tsetse-transmitted trypanosomosis in Ethiopia. Key words/phrases: Ethiopia, GIS, NDVI, Tmax, trypanosomosis SINET: Ethiopian Journal of Science Vol.27(1) 2004: 1-

Factors associated with mosquito net use by individuals in households owning nets in Ethiopia

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background Ownership of insecticidal mosquito nets has dramatically increased in Ethiopia since 2006, but the proportion of persons with access to such nets who use them has declined. It is important to understand individual level net use factors in the context of the home to modify programmes so as to maximize net use. Methods Generalized linear latent and mixed models (GLLAMM) were used to investigate net use using individual level data from people living in net-owning households from two surveys in Ethiopia: baseline 2006 included 12,678 individuals from 2,468 households and a sub-sample of the Malaria Indicator Survey (MIS) in 2007 included 14,663 individuals from 3,353 households. Individual factors (age, sex, pregnancy); net factors (condition, age, net density); household factors (number of rooms [2006] or sleeping spaces [2007], IRS, women's knowledge and school attendance [2007 only], wealth, altitude); and cluster level factors (rural or urban) were investigated in univariate and multi-variable models for each survey. Results In 2006, increased net use was associated with: age 25-49 years (adjusted (a) OR = 1.4, 95% confidence interval (CI) 1.2-1.7) compared to children U5; female gender (aOR = 1.4; 95% CI 1.2-1.5); fewer nets with holes (Ptrend = 0.002); and increasing net density (Ptrend < 0.001). Reduced net use was associated with: age 5-24 years (aOR = 0.2; 95% CI 0.2-0.3). In 2007, increased net use was associated with: female gender (aOR = 1.3; 95% CI 1.1-1.6); fewer nets with holes (aOR [all nets in HH good] = 1.6; 95% CI 1.2-2.1); increasing net density (Ptrend < 0.001); increased women's malaria knowledge (Ptrend < 0.001); and urban clusters (aOR = 2.5; 95% CI 1.5-4.1). Reduced net use was associated with: age 5-24 years (aOR = 0.3; 95% CI 0.2-0.4); number of sleeping spaces (aOR [per additional space] = 0.6, 95% CI 0.5-0.7); more old nets (aOR [all nets in HH older than 12 months] = 0.5; 95% CI 0.3-0.7); and increasing household altitude (Ptrend < 0.001). Conclusion In both surveys, net use was more likely by women, if nets had fewer holes and were at higher net per person density within households. School-age children and young adults were much less likely to use a net. Increasing availability of nets within households (i.e. increasing net density), and improving net condition while focusing on education and promotion of net use, especially in school-age children and young adults in rural areas, are crucial areas for intervention to ensure maximum net use and consequent reduction of malaria transmission.Peer Reviewe

Data Mining Attribute Filtering Approach for Drought Environmental Hazard Modeling

Attribute filtering is the process of objectively searching the best subset of attributes from available multiple attribute options for improved environmental modeling. The main goal of this research was to develop an automated data-mining attribute filtering approach for objective-based feature selection in environmental modeling. Four attribute selection algorithms (correlation-based attribute selection, principal component-based attribute selection, relief attribute evaluation, and wrapper subset evaluation) were compared for their best performances. For the experimental analysis, data from climate, satellite, biophysical, oceanic and atmospheric interactions for modeling drought related environmental hazards were used. Attribute merit values for modeling the target dependent attributes were determined and compared with possible alternative attribute for objective based feature selections. The average merit values for the selected attributes were also ranked. The average merit values for the selected attributes ranged from 0.5 to 0.9 for the case study conducted. This research is complementary to the extensive review and common sense in identifying relevant attributes for a given domain; and it does not mean that the researchers have not to use their common sense and check with established truth or theory bases in the domain specific research. The methodology developed here helps to avoid the uncertainty of domain experts’ attribute selection challenges, which are usually unsystematic and dominated by somewhat arbitrary trials. Future research may evaluate the developed methodology using relevant classification techniques (such as classification and regression tree or random forest) and quantify the actual information gain from the developed approach

Improvement of Grassland Through Community Participation in the Middle AwashValley of Ethiopia

The natural resources of the grassland in the middle Awash valley of Ethiopia are subjected to competing claims: development to generate revenue for the state, conservation of wildlife and wilderness areas, as well as use for local production. The combination of climatic conditions causing drought and the over use of the natural resource can be cited as the primary cause of grassland deterioration in the area. Since the problems of the grasslands are complex and multi-dimensional, they are not amenable to quick and easy fixes. Hence, if sustainable progress is to be achieved, the responsibility for change must be in the hands of the communities and household themselves. Pastoral communities, in collaboration with CARE-Ethiopia, local government and other partner NGOs embarked on grassland improvement activities that were based on traditional activities. The objective of this study was to assess the condition of the traditionally-improved grazing lands

Analysis and sourcing of the mechanical equipment required for a ceramic pot filter production facility

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 118).Research was done into identifying and sourcing the mechanical equipment required for manufacturing ceramic pot filters, specifically for use in the Pure Home Water factory in Northern Ghana. The pieces of equipment identified were a hammer mill, a mixer, a pug mill, and a mechanical press with molds for pressing the filters. Evaluative criteria for each machine were developed, and machines available from manufacturers and machines produced locally were evaluated based on these criteria. Several machines fit the evaluative criteria and were recommended for the Pure Home Water facility. The Meadows Model 5 hammer mill was recommended for purchase from the manufacturer. Of the mixers researched, the mixer made by RDI-C, the Bluebird 24S mixer, and the mixer designed by Prof. Manny Hernandez all satisfy the requirements of Pure Home Water. The pug mill recommended for Pure Home Water was the Venco 75mm pug mill. The Mani Press and the paraboloid molds were also recommended for the Pure Home Water facility.by Julian Getachew.S.B