CLIMATE SMART CROP PRODUCTION TECHNOLOGY OPTIONS FOR ADAPTATION TO AND MITIGATION OF CLIMATE CHANGE IN GREAT RIFT VALLEY REGION OF ETHIOPIA

Abstract:

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
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APA

HAILU, T (2024). CLIMATE SMART CROP PRODUCTION TECHNOLOGY OPTIONS FOR ADAPTATION TO AND MITIGATION OF CLIMATE CHANGE IN GREAT RIFT VALLEY REGION OF ETHIOPIA. Afribary. Retrieved from https://afribary.com/works/climate-smart-crop-production-technology-options-for-adaptation-to-and-mitigation-of-climate-change-in-great-rift-valley-region-of-ethiopia

MLA 8th

HAILU, THEODROSE "CLIMATE SMART CROP PRODUCTION TECHNOLOGY OPTIONS FOR ADAPTATION TO AND MITIGATION OF CLIMATE CHANGE IN GREAT RIFT VALLEY REGION OF ETHIOPIA" Afribary. Afribary, 12 Apr. 2024, https://afribary.com/works/climate-smart-crop-production-technology-options-for-adaptation-to-and-mitigation-of-climate-change-in-great-rift-valley-region-of-ethiopia. Accessed 20 May. 2024.

MLA7

HAILU, THEODROSE . "CLIMATE SMART CROP PRODUCTION TECHNOLOGY OPTIONS FOR ADAPTATION TO AND MITIGATION OF CLIMATE CHANGE IN GREAT RIFT VALLEY REGION OF ETHIOPIA". Afribary, Afribary, 12 Apr. 2024. Web. 20 May. 2024. < https://afribary.com/works/climate-smart-crop-production-technology-options-for-adaptation-to-and-mitigation-of-climate-change-in-great-rift-valley-region-of-ethiopia >.

Chicago

HAILU, THEODROSE . "CLIMATE SMART CROP PRODUCTION TECHNOLOGY OPTIONS FOR ADAPTATION TO AND MITIGATION OF CLIMATE CHANGE IN GREAT RIFT VALLEY REGION OF ETHIOPIA" Afribary (2024). Accessed May 20, 2024. https://afribary.com/works/climate-smart-crop-production-technology-options-for-adaptation-to-and-mitigation-of-climate-change-in-great-rift-valley-region-of-ethiopia