http://ir.bdu.edu.et/handle/123456789/14024 2026-10-13T01:51:16Z 2026-10-13T01:51:16Z Getahun, Betremiwos http://ir.bdu.edu.et/handle/123456789/17392 2026-09-24T10:59:11Z 2024-02-01T00:00:00Z

Effect of Land Use Type on Selected Soil Physio-Chemical Property and Soilorganic Carbon Stock in Kesa Chewsa Kebele,Northwest Highlands of Ethiopia Getahun, Betremiwos Land degradation has become an important global concern because of its adverse impactonfood security and the environment.This study was conducted to effect of land use types on selected soil physiochemical properties and soil organic carbon stockat Kesa Chewsa Kebele, in the northwest highlands of Ethiopia. Field experiment was conducted under three land use types namely cultivated land use, Acacia decurrens plantation land use, and eucalyptus plantation land use with three replications.Eighteen soil samples about 1kg were taken from the experimental land use type integrated withtwo depths(0-20cm) and (20-40cm).The collected data were subjected to two-way ANOVA analysis. The result showed that the investigated soil physio-chemical properties were influenced by land use types. The highest value of SOCS, OC, TN, OM, AvP were recorded in the acacia plantation land use, and the highest value of BD, soil pH, were recorded under cultivated land use. OC, TN, OM, AvP were higher fromsurfaceof the soil (0-20 cm). Soil pH, BD, SMC were higher under sublayer of the soil (20-40 cm).In order to improve the soil conditions and advance sustainable land use and agricultural productivity, there is a need to expand acacia decurrens plantation in similar Agro ecology.

2024-02-01T00:00:00Z Seide, Fentaye http://ir.bdu.edu.et/handle/123456789/17391 2026-09-24T10:55:41Z 2024-06-01T00:00:00Z

Evaluating Bias Correction Methods for Downscaling Cmip6 Global Climate Models Precipitation Simulations in Selected Stations of Ethiopia Seide, Fentaye Bias correction techniques have shown great promise in climate modelling and impact assessment studies in recent years. The climate model data should be corrected /downscaled for inaccuracies and prediction uncertainties using efficient bias correction techniques. Therefore, this study was focused on evaluating bias correction methods for downscaling CMIP6 global climate models precipitation simulations in selected stations of Ethiopia. The five precipitation bias correction methods that were applied in this study include linear scaling (multiplicative), delta change correction (multiplicative), precipitation local intensity scaling, power transformation of precipitation and distribution mapping of precipitation. Daily precipitation data for the selected stations were obtained from the National Meteorological Service Agency (NMSA) of Ethiopia, whereas the CMIP6 GCM data was a historical CNRM CM6 1 (Centre National de Recherches Météorologiques) model obtained from 1995 to 2014. The model data was extracted and bias corrected with observation at CMhyd tools. The bias correction methods were evaluated with their CRI (comprehensive rating index) values and several statistical measures. This study revealed that, delta change correction (multiplicative) was performed better than the other bias correction methods for all selected stations at alltime scales. It has perfect correlation of 1, a bias of zero percent, and low errors in simulation. Power transformation and distribution mapping were the best preferable methods next to delta change correction in daily and monthly simulations. All bias correction techniques were adequately downscaled the GCM in mean monthly precipitations simulations for almost all selected stations. The power transformation and linear scaling techniques were effective to adjust the annual GCM simulation. Whereas precipitation local intensity scaling and linear scaling multiplicative bias correction methods were less preferable than the above methods at daily and monthly period. The distribution mapping of precipitation method led to underestimating and overestimating the given observed precipitation in all periods,

2024-06-01T00:00:00Z Awoke, Simegnew http://ir.bdu.edu.et/handle/123456789/17390 2026-09-24T10:52:31Z 2024-11-01T00:00:00Z

Evaluating the Performance of Cmip6 Gcms for Simulation of Rainfall Climatologyover Ethiopia Awoke, Simegnew Rainfall is one of the most crucial climatic elements to examine and investigate the effects of the changing climate. Simulations of Global Climate Models (GCMs) have become the most useful and commonly used tools for examining changing in climate systems and simulating future climate. This study evaluated the performance of Coupled Model Inter-comparison Project Phase 6 Global climate models (CMIP6 GCMs) for simulations of rainfall climatology over Ethiopia. The study evaluated the rainfall simulation performance of eight CMIP6 GCMs at daily, monthly, and annual temporal scale over five Argo Ecology Zones (AEZs) of Ethiopia for the period 1995-2014 using station data as reference. The performance evaluation was carried out using continuous statistical metrics like Root mean square error (RMSE), Percent bias (PBIAS), and Pearson Correlation Coefficient (r) and line graphs. The performance of each GCM over different AEZs was ranked based on Critical Rating Index (CRI). The result revealed that; models have different simulation performance of daily to annual rainfall total over AEZs of Ethiopia. In addition, they have both overestimation and underestimation problem. For better simulation of daily rainfall total, Ec-Earth3-veg (over tropical, sub-tropical, and temperate AEZ s),MRI-CSM2-0 (over desert AEZ),and MPI-ESM-1-2-LR (over alpine AEZ) is high ranked and p referable.BCC-CSM-2-MR performed well over tropical, sub-tropical, temperate, and alpine AEZs,butMRI-ESM2-0 has better performance over desert AEZ. For simulation of annual rainfall total, MRI-ESM2-0 (over desert and tropical AEZs), BCC-CSM-2-MR (over temperate and alpine AEZs), and Ec-Earth3-veg (over sub-tropical AEZ) is preferable and acceptable. EcEarth3 is the worst climate model to reproduce mean monthly rainfall of Ethiopia. The performance of models is not consistent in reproducing rainfall distributions at different statistical metrics and timeframes. Since the performance of CMIP6 GCMs different from place to place and time to time, I recommend to evaluate the performance of models to use for specific place and application and apply appropriate bias correction. The author also further recommen ds, evaluating the performance of CMIP6 GCMs rainfall simulation capability over rainfall regimes of Ethiopia.

2024-11-01T00:00:00Z Mulat, Abaynew http://ir.bdu.edu.et/handle/123456789/17389 2026-09-24T10:49:14Z 2024-03-01T00:00:00Z

Smallholder Farmer’s Perception and Their Adaptation Strategies To Climate Change and Variability in the Dangila District of Awi Zo Ne, Ethiopia Mulat, Abaynew Climate change is a global phenomenon. Its impact on agricultural activities and the livelihoo d of the population in developing countries has increased dramatically. Understanding howfarmers perceive climate change and how they adapt to it is very important to the implementat ion of adequate and relevant adaptation strategies. This study was conducted in the Dangila district to investigate farmers’ perception and the trend of rainfall and temperature, theadaption strategies, and the factors that impact their choice to adapt by sampling 138 farmhouseholds. Both primary and secondary data sources were used in the study. The survquestionnaire, FGD, and KII were used to gather the data. The Mann-Kendall trend test anSen’s Slope estimator were used to analyze the trend and magnitude of climate changeFurthermore, descriptive statistics and a multinomial logit model were used to identifadaptation strategies and determine factors that influence the choice of adaptation strategierespectively. The rainfall showed a non-significant increasing trend in winter (Bega), summ(June – September), and annually. However, there is a non-significant decreasing trend rainfall in the spring (Belg) season. From 1991-2022, the annual maximum and minimumtemperatures have shown a statistically significant increasing trend, with recorded increment s of 0.3 O C decadal with a 0.03 O C yearly increasing rate. Farmers perceived an increase annual temperature and a decrease in rainfall trend with low variability. Among theinterviewed farmers chi-square test showed a significant variation in the perception temperature and rainfall over Agroecology and Sex. The descriptive statistics results that themain adaptation strategies used by farmers include the use of improved variety, soil andwater conservation, planting trees & agroforestry, and use of irrigation & water harvesting.The multinomial logit model revealed determinant factors such as gender, age, family sizeducational level, farming experience, access to extension service, access to climateinformation, lack of infrastructure, farmland size, agroecological zone, Tropical livestockUnit, and financial interest which has a positive and negative impact on different adaptatiostrategies in the study district. Given the main study outcomes, it is recommended that ruraldevelopment approaches should be put into practice to support farmers in adapting to the climate-related impact and the risks they encounter more effectively.

2024-03-01T00:00:00Z