Water data for climate resilience

Financial inclusion is recognized as a vital driver of sustainable development and serves as a fundamental pillar of climate action. It is crucial to enhance the climate resilience of smallholder farmers in the face of severe and unpredictable climate shocks, which disproportionately affect them. However, the level of financial inclusion in Ethiopia remains low, and its impact on the climate resilience of smallholder farmers has not been thoroughly examined using rigorous model and comprehensive dataset. This study investigates the impact of financial inclusion on the climate resilience of rural households, using a large data set from the Ethiopian Socio-Economic Survey. The principal component analysis was applied to construct a climate resilience index. The financial inclusion was measured using an index that encompasses three dimensions: penetration, availability, and usage. In order to address the endogenous nature of financial inclusion, an instrumental variable approach was employed, using the distance to the nearest financial institution and religion as instrumental variables. The results demonstrated a positive and significant impact of financial inclusion on the climate resilience of rural households. Therefore, the government should strengthen the provision of essential financial and related infrastructures in rural Ethiopia to improve access to financial products and services. Furthermore, it is essential for policymakers to initiate and implement financial sector reforms that ensure the availability of affordable and tailored financial services. These reforms should also prioritize the development of climate-resilient agricultural finance, thereby contributing to the achievement of climate action goal of sustainable development.

Greenhouse gas (GHG) emission from tropical large hydropower reservoirs (LHRs) is the highest among all climatic zones due to the combinatory effect of elevated content of flooded organic matter and high temperatures. Traditional methods for GHG emission estimation involve extensive fieldwork, topographic surveys, hydrological analyses, and environmental assessments with high-end instrument requirements. In a country like India, where the hydropower sector is mushrooming rapidly, implementing these techniques on such a large scale is challenging. Alternatively, cloud-based tools like Google Earth Engine (GEE), G-res, and Earth Observation (EO) data related to biophysical and climatic conditions with in-situ reservoir water levels provide an opportunity to quantify GHG emissions from LHRs efficiently. In the present study, Maithon, one of the oldest LHRs in India, situated in a tropical climatic zone, has been studied by integrating site-specific parameters to estimate GHG emissions. The results from this study, which show that at the mean operating level (146.31 m) of the reservoir, net GHG emission is 1,024 - 1,271 gCO2e/m2/yr (with a 95% confidence interval), are of significant importance. This study highlights the GHG emissions varying greatly between the full reservoir level (786 gCO2e/m2/yr) and near the dead storage level (3,855 gCO2e/m2/yr), indicating the role of reservoir operating level in mitigating GHG emissions to achieve global goals like net zero emissions. There has been limited work globally using the G-res tool, and this is the first comprehensive study of initial GHG emission estimation of a tropical reservoir using G-res and GEE incorporating updated high-resolution land use land cover and Sentinel-1 images.

Climate change remains a significant threat to farm households, especially in developing countries. It exacerbates their vulnerability to food insecurity by reducing agricultural productivity and raising agricultural production costs. Adoption of climate smart-agricultural (CSA) practices is a promising alternative to build resilient farm households. In this study, we assessed the impacts of adopting CSA practices on climate resilience and vulnerability among farm households in Bale-Eco Region, Ethiopia. A power calculation was used to determine the sample size, and 404 farm households were randomly selected to collect data using structured questionnaire. We estimated household climate resilience index using categorical principal component analysis, and vulnerability index using vulnerability as expected poverty approach. Endogenous switching regression model, which is conditional on the adoption of multiple CSA practices and used to control selection bias and unobserved heterogeneity, was used to assess the impacts of CSA practices on household climate resilience and vulnerability. We employed counterfactual approaches to assess the impacts. The results show that the average treatment effects for most CSA practices are statistically significant and positive for resilience, but negative for vulnerability. This provides empirical support for interventions in climate-smart agriculture, which can help farm households build resilience and reduce vulnerability. We, therefore, suggest that agricultural policies should encourage the adoption of CSA practices and provide incentive packages to farm households that promote this.

According to the United Nations (n.d.), climate change is the long-term shift in temperatures and weather patterns due to natural changes, such as the sun’s activity and significant volcanic eruptions, or human activities, such as burning fossil fuels like coal, oil, and gas. The effects of and challenges caused by climate change on farmers’ ability to manage mixed farming systems in sub-Saharan Africa are well documented in the literature. However, the synergies among mixed farming systems’ components and farmers’ innovation demands and responses to climate change impacts remain fragmented. Using a case of mixed crop-livestock-tree (MCLT) systems in northern Ghana, this paper examined farmers’ responses, their innovation needs, and how these innovations can be catalyzed to enable more farmers to adopt similar climate change adaptations. Our findings show that climate change impacts mixed farming systems in several domains, with these impacts being more visible in some domains. Significant productivity declines are observed in crops, livestock, and the whole mixed farming system. Productivity declines lead to decreased incomes, food availability, and household food security. Female farmers’ access to production factors, resource management, and market participation is reduced. Farmers make technical, managerial, and business changes in response to climate change impacts. Such changes are dominated by technical changes, including using highyielding, disease-resistant, and early-maturing crop varieties, crop and animal pest and disease management, agricultural water and land management, and wind and bush fire control. Interconnections between the MCLT system components include cross-component investments, additional income generation, animal feeding and healthcare improvement, nutrition exchanges, and family nutrition improvement. These interconnections generate income and cash flow and support food and nutrition security, enabling farmers’ adaptation. Climate-resilient innovation bundles to enable farmers’ adaptation include good agricultural practices, circular farming techniques, irrigation packages, information services, and value-chain linkages. Scaling climate-resilient innovations in northern Ghana and other sub-Saharan African contexts require multiple pathways, including innovation platforms, innovation bundling, multi-actor partnerships, inclusive finance, and multistakeholder dialogues to support farmers’ adaptation to climate change.