Thesis

Thesis Title: Spatio-temporal Variability and Trend Analysis of Rainfall in East Gojjam, Upper Central Blue Nile Basin, Ethiopia

Mon, 01 Jun 2026 00:00:00 GMT

Thesis Title: Spatio-temporal Variability and Trend Analysis of Rainfall in East Gojjam, Upper Central Blue Nile Basin, Ethiopia Jemberu, Bire Rainfall variability affects rain-fed agriculture, which relies on rainfall. But evidence of sitespecific spatio-temporal rainfall variability and trend remains limited in the study area. Therefore, this study examines the spatio-temporal variability and trends of rainfall in the Upper Central Blue Nile Basin from 1981 to 2024 using the CHIRPS v2 dataset. Coefficient of Variation, Precipitation Concentration Index, Standardized Rainfall Anomaly Index, and Standardized Precipitation Index were used to examine rainfall variability and drought events. Furthermore, the Mann-Kendall, Modified Mann-Kendall test, Sen’s slope estimator, and Innovative Trend Analysis were employed for trend analysis. The Inverse Distance Weighted method was used for spatial analysis in ArcGIS v10.8. The results show highest annual rainfall occurs during the Kiremt season. However, CV values of Belg rainfall indicated greater spatio-temporal variability than Kiremt and annual totals. Also, LGP shows variability over the onset and cessation dates. The PCI results suggest a heterogeneous rainfall distribution in the annual, Kiremt, and Belg seasons. The SRAI result indicates periodic fluctuation of wet and dry years. In addition, SPI values indicated the presence of dry and wet periods with temporal consistency across all study locations in 2015. MK trend test revealed that annual, Kiremt, and Belg rainfall show a significant increasing trend (p<0.05) at 5, 4, and 1 locations with 3.5- 4.1, 2.3-3.7, and 1.3 mm/ year, respectively. The ITA revealed, at the lower cluster, 5 study locations demonstrated a significant upward trend in annual and Kiremt, while downward at Mota in Belg season. At the medium cluster, the majority of locations showed upward trends. In the Belg high cluster, a significant upward trend (p<0.05) was observed in 7 study locations. Therefore, despite insignificant upward trends being dominant, rainfall shows a typical shift and highlights the necessity of localized adaptation measures to protect rain-fed agriculture and improve its resilience in the face of future rainfall variability.

Impact of Rainfall Variability on Crop Yields and Its Relationship With Sea Surface temperature of Eastern Pacific ocean in Different Agro-Ecology Zone of South Wollo Amhara Ethiopia

Mon, 01 Apr 2024 00:00:00 GMT

Impact of Rainfall Variability on Crop Yields and Its Relationship With Sea Surface temperature of Eastern Pacific ocean in Different Agro-Ecology Zone of South Wollo Amhara Ethiopia GETAHUN, SISAYNEW Title: Impact of Rainfall Variability on Crop Yield and its Relationship with Sea Surface Temperature of Pacific Ocean in Different Agro-Ecology Zone of South Wollo Amhara Ethiopia By Sisaynew Getahun, supervised by Dr Dejena sahlu and Dr Dessalegn chania Agriculture in Ethiopia is the backbone of the economy, because more than 85% of the population is depend on rain-fed agriculture. However, most parts of the country, especially south Wollo is vulnerable to recurrent drought and crop failure due to rainfall variability. This study examines the impacts of rainfall variability on crop yield and its relation to Nino 3.4 SST in different agro-ecology zones of south Wollo, Ethiopia. Rainfall data obtained from the Ethiopian meteorological institute, Nino 3.4 regions of the Pacific Ocean SST were downloaded from NOAA and major crop yield data were obtained from the South Wollo Central Statistical Agency. Mean, Coefficient of variation, precipitation concentration index, and standardized anomaly were employed to describe Crop yield and rainfall variability. INSTAT software used to determine onset and cessation dates of Kiremet season. R-Studio and Mann-Kendall trend test, used trend significance test. Correlation analysis to examine the relationship between rainfall characteristics with SST and crop yields, regression analysis to explain the impact of rainfall variability on crop yield. The analysis revealed that seasonal rainfall is moderate to highly variable in all Agro-Ecology Zones. Correlation between Kiremet rainfalls with SST lag 0, 2 shows negative significance in all Agro-Ecology Zones, and Belg rainfall with SST lag 0, shows positive significance in the Midland area. Rainfall characteristics correlated less to high with selected crop yields (Maize, Sorghum, Teff, Wheat, and Barley) in the study area. The result of Regression revealed that variability of Sorghum crop yield in the lowland area is explained by 88% of Rainfall characteristics. Maize, Sorghum, and Teff crop yield in the Midland area is explained by 69%, 69%, and 53% Rainfall characteristics respectively, Barley and Wheat crop yield in the Highland area is explained by 91% and 75% Rainfall characteristics respectively. Variability of Barley crop yield in the Upper Highland area is explained by 36% Rainfall characteristics. This shows that crop yields are highly variable due to Variability of Rainfall characteristics, so important adaptation strategies will be implemented for the study area to cope with the risks, sustain farming, and improve crop variety. So it is better further study investigated future projection of climate variability in the study area.

the Psycho-Social Resilience of People With Physical Disabilities in the Context of Conflict in Bahir Dar City, Ethiopia

Fri, 01 Nov 2024 00:00:00 GMT

the Psycho-Social Resilience of People With Physical Disabilities in the Context of Conflict in Bahir Dar City, Ethiopia Gizachew, Meseret Ethiopia, especially the Amhara Region and Bahir Dar City, contends with substantial socioeconomic challenges that disproportionately impact individuals with physical disabilities, increasing their vulnerability. This research aims to explore the psychosocial resilience of people with physical disabilities in Bahir Dar City. A mixed-methods design was employed, utilizing both quantitative and qualitative approaches. Quantitative data were collected through structured questionnaires, while qualitative data were obtained from participants through key informant interviews, focus group discussions, and observations using a checklist. A systematic sampling method was used to select 134 participants. Qualitative data were analyzed through thematic analysis, and quantitative data were analyzed using descriptive statistics. Sociodemographic variables were presented using frequencies and percentages, and the Brief Resilience Scale (BRS) was utilized to measure psychosocial resilience. The Coping Inventory for Stressful Situations (CISS) was employed to assess coping mechanisms, categorized into task-oriented, emotion-oriented, and avoidance-oriented strategies. A binary logit regression model was employed to identified determinant factors influencing resilience. The findings revealed that 64.18% of participants exhibited low resilience, while 35.82% showed normal resilience. Task-oriented coping mechanisms were moderately utilized (mean = 2.9), emotion-oriented strategies were more prevalent (mean = 3.9), and avoidance-oriented coping was the least common (mean = 2.4). Individuals with low resilience used a broader range of coping strategies (mean total score = 22.1) compared to those with normal resilience (mean = 21.5). Key determinants of psychosocial resilience included sex (-2.93, p < 0.001), type of physical impairment (2.40, p < 0.001), duration of impairment (0.19, p < 0.001), employment status (0.51, p = 0.052), annual income (0.0000593, p = 0.008), and marital status (-0.89, p < 0.001). The study concludes that psychosocial resilience is influenced by various demographic and socioeconomic factors, emphasizing the need for targeted interventions to improve resilience. Recommendations include enhancing infrastructure accessibility, providing socioeconomic support, strengthening community networks, and implementing gender-sensitive interventions. Finally, further research is encouraged to investigate the experiences of individuals with diverse disabilities in conflict-affected contexts.

Comparative analysis of Household Vulnerability to Food insecurity Between High-Yield and low-Producing Woredas: the Case of Yilmana Densa and Lay Gayint Woredas, Ethiopia

Fri, 01 Nov 2024 00:00:00 GMT

Comparative analysis of Household Vulnerability to Food insecurity Between High-Yield and low-Producing Woredas: the Case of Yilmana Densa and Lay Gayint Woredas, Ethiopia Amsalu, Habtamu Many studies in Ethiopia, particularly in the Amhara region, lack comparative analyses household vulnerability to food insecurity across areas with varying agricultural productivThis study investigates food insecurity levels, vulnerability to food insecurity, and determinants in two woredas: Lay Gayint, characterized by low agricultural productivity, and Yilmana Densa, a high-yielding area. Employing a mixed-method research design, the study utilized multi-stage samplitechniques, including purposive, stratified, and systematic sampling, to select households. Outof an initial sample of 549 households, 493 were successfully interviewed due to securitconcerns. Data were collected by trained enumerators using the ODK toolbox on smartphones. The analysis applied the Consolidated Approach to Reporting Indicators of Food Securit(CARI) model for measuring food security, the Value at Risk (VaR) model for assessingvulnerability, and binary logistic regression to identify determinants of vulnerability. The results indicate a higher proportion of severely food-insecure households in Lay Gay(69.2%) compared to Yilmana Densa (48.15%). Vulnerability analysis revealed that 59.6%households in Lay Gayint fall into a medium-risk category, while 67.9% in Yilmana Densa areclassified as low-risk. Coping strategies also differ, with households in Lay Gayint employing more extreme measures. In Lay Gayint, determinants of vulnerability include age (-0.0024, p<0.001), education level (-0.0143, p<0.05), homeownership (0.0971, p<0.01), cultivated land (0.0573), total production (-9.28e-06), cash expenditure (-0.0000183), and livelihood assets (0.0248, p<0.01). In Yilmana Densa, key factors include age (0.0058), household size0.0769), marital status (-0.1115, p<0.1), access to treated water (0.2857), and total livestockunits (TLU) (-0.0509). The findings reveal that severe food insecurity and high vulnerabilities persist in both woredas, indicating that vulnerability is influenced by factors beyond agricultural production. The studemphasizes the need for multisectoral targeted interventions, including sustainable farmingpractices, community education, social protection, and enhanced economic resiliencCollaborative efforts from government and non-government actors are crucial in tackling barriers to food insecurity.