http://ir.haramaya.edu.et//hru/handle/123456789/24 2026-04-20T12:32:56Z http://ir.haramaya.edu.et//hru/handle/123456789/8343 PLANT DIVERSITY AND DETERMINANT OF FARMER PREFERENCE OF SPECIES IN SMALLHOLDER HOMEGARDEN AGROFORESTRY: THE CASE OF HABRO DISTRICT OF WEST HARARGHE ZONE, OROMIA REGIONAL STATE, ETHIOPIA Abdela Mohammed; (PhD) Tessema Toru; (Assist. Prof.) Dargo Kebede Homegarden agroforestry (HGAF) has the potential to support diverse multipurpose plant species; however, the diversity of plant species and the factors influencing farmers' their preferences in smallholder homegardens are poorly understood. This study investigated plant diversity and the determinants of farmer preference for species in smallholder HGAF in Habro District. A total 149 households were selected following specify for the household survey. All trees, shrubs, and herbaceous plants were counted and recorded in 10mx10m, 5mx2m, and 1mx1m size quadrats, respectively. For Household survey a questionnaire usedand focus group discussion. The recorded data were organized and analyzed using Statistical Package for Social Sciences (SPSS) version 20 employing descriptive statistics and econometric models, specifically Multinomial logistic regression models. A total of 1,286 individual plants belonging to 60 species and 33 families, with 30% trees and 28% shrubs, were recorded. There was Significant differences (P < 0.05) in woody and herbaceous plant species richness and abundance observed among the study sites. Accordingly, Melka Balo kebele had the highest values and Gadisa kebele with the lowest. There were also significant differences in the mean Shannon index (H'), Simpson index, and evenness (E) of woody species between Melka Bello and the other two sites (Gadisa and Lugo), were the highest values in Melka Bello. The mean H'and Simpson index of herbaceous species showed significant differences (P < 0.05) only between Gadisa and the other two sites (Melka Bello and Lugo), with lower values observed in Gadisa. Mean evenness of herbaceous species showed a significant difference between Melka Bello and the other two sites (Lugo and Gadisa), with the lower value in Melka Bello. Catha edulis was the most frequent species, followed by M. paradisiaca, C. arabica, and Casimiroa edulis. The analysis of the IVI of woody species shows the dominance of only a few species in the HG. Farmers most preferred four plant species in order of Catha edulis > C. arabica > Casimiroa edulis > M. paradisiaca. Household wealth class, education, and age have a significant positive influence (p < 0.1) on farmers preference of species. Household wealth class, education, and age had a significant positive influence on the preference for planting C. edulis to C. arabica. Household wealth class and education level had a significant positive influence on the preference for Casimiroa edulis. Education had a significant positive influence on M. paradisiaca preference, while agroecology and Household experience had a significant negative influence. Promoting them while considering socio-economic factors and enhancing agro-ecological knowledge is crucial 102p. 2024-09-01T00:00:00Z http://ir.haramaya.edu.et//hru/handle/123456789/8262 MODELING THE IMPACT OF LAND USE/COVER, CLIMATE CHANGE, AND SOIL MANAGEMENT PRACTICE’S ON SOIL ORGANIC CARBON STOCK IN NORTHWEST AND CENTRAL RIFT VALLEY OF ETHIOPIA Bethel Geremew Shefine; Prof. Tsegaye Tadesse (PhD); D.rBobe Bedadi (PhD) The stock of soil organic carbon (SOC) has been impacted by changes in land use and land cover (LULC), climate change (CC), and soil management (SM) practices. Soil organic carbon loss increases when forest converted to agricultural land, and likewise SM practice like crop rotation increase SOC while tillage decrease, but the impact of CC on SOC stock is not direct. To monitor and predict the dynamics of SOC stock at various scales, soil carbon models (SCM) are essential. In Ethiopia, SCM were not validated well due to lack of skill and adequate data to use the model. In other word, SCM were not explicitly utilized in the context of CC, LULC changes, and SM practices. Thus, the objective of this study is Evaluate the likely impacts of LULCC, changing Climate, and Soil Management Practices on SOC stock of Anjeni Watershed using a modeling approach. RothC and CQESTR models were used for this study. to assess the impact of CC, LULC change, slope gradient, and the RothC model performance on SOC stock of Anjeni watershed (AW) i.e., northwest Ethiopia as well as evaluate the CQESTR model for estimating SOC response to tillage and residue removal in Melkasa agricultural research center (MARC) i.e., in central rift valley. Current and historical soil carbon, bulk density, clay content, land use, crop yield, crop residue and climate data were used as inputs to evaluate the performance of RothC and CQESTR models. The RothC model was calibrated using long-term SOC, land management, and climatic data from the AW, while CQESTR used tillage and crop residue management data from MARC. The RothC correlation coefficient between simulated and observed SOC in 1997 and 2021 were 0.77 and 0.86, respectively, whereas CQESTR model was able to simulate SOC change with correlation coefficient value of 0.89 and mean square deviation of 0.008, indicating that both models effectively characterized the SOC. The RothC model simulated higher current and projected SOC for grass/fallow land as compared to the cultivated land. The RothC model predicted/simulated slightly different SOC stock under different slope gradients, with values ranging from 4.15 ton/ha, in the lower slope gradient to 2.1 ton/ha in the upper slope gradient. xx xx The projected temperature for the year (2022-2052) indicated rising that result in increasing of SOC from the baseline for e.g., in upper slope gradient of GFDL by 0.64 and 2.1 ton/ha using IPSL (SSP5-8.5) and MPI (SSP5-2.6), respectively. The CQESTR model result in MARC indicated a declining trend of SOC under CP both in topsoil layer (0-15) and lower layer (15-30) cm soil depths, which is due to practices of tillage and crop residue removal from cultivated land in maize bean intercropping. Variations in SOC concentration was noted in the lower layer soil depths under CA, while the topsoil layer SOC for CA increased over time. The predicted SOC under CP decrease to less than 1% by 2030 from about 1.25% in the 2000s. Overall, improved SM practices including CA, soil water conservation, and the expansion of fallow lands are responsible for the anticipated SOC stock increase in both locations, which is beneficial for increasing agricultural productivity. The models tested simulated the SOC under different land use, climate scenario and soil management practices reasonably well, and hence can be used as decision support tools under Ethiopia context. However, calibration and validation of other models would be crucial and more has to be done to resolve critical shortage of long-term data across locations in the country. Without such data, the use of such decision-support tools can’t be possible. 137 2024-12-01T00:00:00Z http://ir.haramaya.edu.et//hru/handle/123456789/7607 THE EFFECT OF SEASONAL RAINFALL VARIABILITY ON WATER QUALITY IN LAKE MUTANDA CATCHMENT, SOUTHWESTERN UGANDA Turyasingura Benson; Dr. Deribachew Bekana; Dr. Charles B. Niwagaba Despite the vital importance of reliable data sets on the current effect of seasonal rainfall variability on water resources in Lake Mutanda catchment of southwestern Uganda, little is known about the status of this phenomenon. Lake Mutanda and its catchment provide water for domestic use, and irrigation. This study was aimed to assess the effects of seasonal rainfall variability on physicochemical and bacteriological water quality of Lake Mutanda and its catchments, and to suggest the water management strategies for local farmers in response to rainfall variability. Physicochemical quality parameter such as turbidity, temperature, calcium, electrical conductivity, pH, chemical oxygen demand, and nitrate was analyzed using standard method. A mixed research designs utilizing both qualitative and quantitative data collection methods was used regarding agricultural water management practices. A total of 397 respondents were selected to participate in the study using simple random and multistage sampling techniques. Survey questionnaires and key informant interview methods of data collection was also used. In terms of physicochemical quality, nitrates (7.50±0.71 mg/L), calcium (70.50±0.71 mg/L), pH (7.33±0.04), electrical conductivity (188.00±5.66 uS/cm), chemical oxygen demand (4.50±0.71 mg/L) were within the WHO guidelines during wet and dry seasons. However, turbidity (38.0±2.940 NTU), temperature was (19.20±0.14 °C), magnesium (138.5±6.36 mg/L), phosphates (9.00±0.00 mg/L), and dissolved oxygen (5.85±0.64 mg/L) were above the permissible limits (WHO, 2017) in both seasons. The study revealed that water samples from all the sampling sites contains high level of fecal coliforms (4.00±0.07 CFU/100 mL), total coliforms (16.00±1.41 CFU/100 mL), and total bacterial account (16.00±1.41 CFU/100 mL), and were not within the acceptable WHO permissible level (0/100 mL). The obtained results show poor lake water management but people use it untreated. However, there is moderate understanding of agricultural practices as reported by farmers: Mulching (38%), terracing (20%), and contour farming (15%) which would be imperative in the conservation of water quality in Lake Mutanda. Therefore, there is need for considering continuous public training, protection of water catchment areas, monitoring of water quality and treatment of water in Lake Mutanda by policy makers before the water is supplied to the public for domestic use 107 2023-06-01T00:00:00Z http://ir.haramaya.edu.et//hru/handle/123456789/7595 CLIMATE SMART CROP PRODUCTION TECHNOLOGY OPTIONS FOR ADAPTATION TO AND MITIGATION OF CLIMATE CHANGE IN GREAT RIFT VALLEY REGION OF ETHIOPIA THEODROSE SISAY HAILU; Nigussie Dechassa (Professor); Mengistu Ketema (Professor); Mezegebu Getnet (PhD) Climate variability and change have serious direct and indirect consequences for crop production and nitrous oxide (N2O) emission in rainfed agriculture-based developing countries in general and in semi-arid environments like the Great Rift Valley (GRV) of Ethiopian particular. Agriculture is a sector that is vulnerable to the effects of climate change while it is contributing both as a sink and source to anthropogenic N2Oemission. Therefore, applying Climate Smart Crop Production (CSCP) technologies and practices (referred hereafter as CSCP technologies) that can increase crop productivity, improve resilience, and lower N2O emission are crucial for current climate variability and future changes in climate conditions. This study aimed at analyzing and understanding current climate variability and future changes and associated risks in crop production and N2O emissions as well as identifying and evaluating CSCP technologies used by farmers and factors that influence their decisions to adopt the technologies, The study also aimed at calibrating, evaluating and applying crop model to explore CSCP technology options and trade-offs for current and future climate periods adaptation and mitigation of the agriculture, with particular focus on maize-based cropping system. The study was conducted in cereal-based farming systems of the semi-arid environment of the GRV of Ethiopia, known for low average crop productivity and high environmental degradation. Climate analysis, empirical statistical analyses, household survey, econometric model, field experiment and crop simulation modelling were used to achieve the objectives of the study. The spatio-temporal dynamics of rainfall and temperature were analyzed for the baseline (1988-2017) and projected periods of 2040 and 2060 based on 6 General Circulation Models (GCMs) under two new emission scenarios called Shared Socioeconomic Pathways (SSP245 and SSP585). A cross-sectional survey was carried out to gather information from 384 farmers. The survey data were analysed using chi-square test, t test, and the multivariate probit model. The CERES-Maize and CROPGRO-Dry bean Crop Simulation Models of the Decision Support System for Agrotechnology Transfer (CSMs-DSSAT) were calibrated and evaluated. The CSMs-DSSAT was applied to simulate and explore CSCP technology options for maize and common bean crop yields and trade offs with N2O emission to the atmosphere. For the model simulation study, seven treatments varying in tillage, residue management, fertilizer and water management were evaluated. The treatments were farmers’ current practice (FCP), and other 6 CSCP technology options: conservation agriculture with low amount of fertilizer (CSCP-1); conservation agriculture with low amount of fertilizer and with supplemental irrigation (CSCP-2); conservation agriculture system (CSCP-3); conservation agriculture system with supplemental irrigation (CSCP-4); conservation agriculture with high amount of fertilizer (CSCP-5); conservation agriculture with high amount of fertilizer and with supplemental irrigation (CSCP-6). Climate simulations were conducted for the 3 climate periods (baseline, 2040 and 2060) based on 6 GCMs under SSP245 and SSP585 emission scenarios. The result generally indicates that there is a high spatio-temporal variability across the GRV. The result also shows that a positive but not significant trend in rainfall amount and a positive and significant trend in maximum and minimum temperatures across xxi in most locations. Compared to the baseline and SSP245, amount of rainfall and temperature would be increased in the future climate periods and under the SSP585 emission scenario, respectively. The growing period would also be increased in the future climate periods under both emission scenario relative to the baseline. The increase in annual and seasonal rainfall amounts and growing period generally provide opportunities for increasing yield and reducing emissions but increasing temperature will have considerable negative consequences on crop production and N2O emission reduction. Results of the survey study showed that crop diversification, agroforestry, and integrated soil fertility management were the most widely practiced technologies. The multivariate probit regression model result showed that age, sex, and education of the head; farmland size; livestock ownership; income; access to credit; access to climate information; training; and extension contact influenced the adoption of CSCP technologies. The model calibration and evaluation showed that the CSM-DSSAT reasonably reproduced observations for days to anthesis, days to physiological maturity and grain yields, with values for the index of agreement of 0.97,0.88 and 0.61 for CERES-Maize and 0.84, 0.75 and 0.51 for CROPGRO-Dry bean, respectively. Similarly, root mean square errors were moderate for days to anthesis (1.2 and 1.2 days), maturity (4.1 and 1.6 days), and yield (0.8 and 1.1 t/ha) for CERES-Maize and CROPGRO-Dry bean, respectively. The results suggest that simulation for future climate scenarios projected slight increases in the average yield (1.2% - 2.7%) across climate periods and SSPs. However; compared to the baseline climate there would be an increase in the average N2O emissions (41.8% - 44.3%) from the cropping system under the SSPs and climate periods. Compared to the FCP, options (CSCP-2, CSCP-4, CSCP-5 and CSCP-6) gave significantly higher yield and options (CSCP-2, CSCP-3 and CSCP-4) perform in minimizing N2O emissions. Although most of the CSCP options had a positive yield implication across the SSPs and climate periods, only CSCP-4 perform in both yield improvement and emission reduction. The study helps to develop site-specific adaptation and mitigation options that minimize the negative effects of climate variability and change while maximizing the opportunities. Therefore, designing location and season specific climate smart agriculture technology options is important to counter the negative effects of climate change and variability on sustainable food production systems and N2O emission reduction in the GRV. In addition, considering barriers to the adoption of CSCP technologies in policy and action is necessary to support smallholder farmers in adapting to climate variability and change while lowering N2O emission. The CSMs-DSSAT have been successfully calibrated and evaluated for maize and common bean crop varieties and taken for further applications in evaluating various crop and soil management options including CSCP technologies and climate change impact studies. It is also concluded that decisions of implementing the CSCP options need to consider future climate change mitigation without compromising productivity 171 2023-11-01T00:00:00Z