• Energy Research

Land degradation poses a major threat to agricultural production and food security in Ethiopia, and sustainable land management (SLM) is key in dealing with its adverse impacts. This paper examines the covariates that shape rural livelihood diversification and examines their effects on the intensity of adoption of SLM practices. Household-level data were collected in 2017 from 270 households in three drought-prone watersheds located in northwestern Ethiopia. We used the Herfindahl–Simpson diversity index to explore the extent of livelihood diversification. A stochastic dominance ordering was also employed to identify remunerative livelihood activities. A multivariate probit model was employed to estimate the probability of choosing simultaneous livelihood strategies, and an ordered probit model was estimated to examine the effect of livelihood diversification on the adoption intensity of SLM practices. In addition to mixed cropping and livestock production, the production of emerging cash crops (e.g., Acacia decurrens for charcoal, and khat) dominated the overall income generation of the majority of farmers. Stress/shock experience, extent of agricultural intensification, and agro-ecology significantly affected the probability of choosing certain livelihood strategies. Livelihood diversification at the household level was significantly associated with the dependency ratio, market distance, credit access, extension services, membership in community organizations, level of income, and livestock ownership. A greater extent of livelihood diversification had a significant negative effect on adopting a greater number of SLM practices, whereas it had a positive effect on lower SLM adoption intensity. Overall, we found evidence that having greater livelihood diversification could prompt households not to adopt more SLM practices. Livelihood initiatives that focus on increasing shock resilience, access to financial support mechanisms, improving livestock production, and providing quality extension services, while also considering agro-ecological differences, are needed. In addition, development planners should take into account the livelihood portfolios of rural households when trying to implement SLM policies and programs.

Pour mieux comprendre l'application mondiale des modèles de prédiction de l'érosion des sols, nous avons examiné de manière approfondie la littérature de recherche pertinente évaluée par des pairs sur la modélisation de l'érosion des sols publiée entre 1994 et 2017. Nous avons cherché à identifier (i) les processus et les modèles les plus fréquemment abordés dans la littérature, (ii) les régions dans lesquelles les modèles sont principalement appliqués, (iii) les régions qui restent non traitées et pourquoi, et (iv) la fréquence des études menées pour valider/évaluer les résultats des modèles par rapport aux données mesurées. Pour mener à bien cette tâche, nous avons combiné les connaissances collectives de 67 scientifiques spécialistes de l'érosion des sols de 25 pays. La base de données résultante, intitulée « Global Applications of Soil Erosion Modelling Tracker (GASEMT) », comprend 3030 enregistrements de modélisation individuels provenant de 126 pays, englobant tous les continents (à l'exception de l'Antarctique). Sur les 8471 articles identifiés comme potentiellement pertinents, nous avons examiné 1697 articles appropriés et systématiquement évalué et transféré 42 attributs pertinents dans la base de données. Cette base de données GASEMT fournit des informations complètes sur l'état de l'art des modèles d'érosion des sols et des applications de modèles dans le monde entier. Cette base de données vise à soutenir la prochaine évaluation mondiale de l'érosion des sols par les Nations Unies basée sur les pays, en plus d'aider à éclairer les priorités de recherche sur l'érosion des sols en construisant une base pour de futures analyses ciblées et approfondies. GASEMT est une base de données open-source à la disposition de l'ensemble de la communauté des utilisateurs pour développer la recherche, corriger les erreurs et faire des extensions futures. Para comprender mejor la aplicación global de los modelos de predicción de la erosión del suelo, revisamos exhaustivamente la literatura de investigación relevante revisada por pares sobre modelos de erosión del suelo publicada entre 1994 y 2017. Nuestro objetivo fue identificar (i) los procesos y modelos abordados con mayor frecuencia en la literatura, (ii) las regiones dentro de las cuales se aplican principalmente los modelos, (iii) las regiones que permanecen sin abordar y por qué, y (iv) con qué frecuencia se realizan estudios para validar/evaluar los resultados del modelo en relación con los datos medidos. Para realizar esta tarea, combinamos el conocimiento colectivo de 67 científicos de erosión de suelos de 25 países. La base de datos resultante, denominada 'Global Applications of Soil Erosion Modelling Tracker (GASEMT)', incluye 3030 registros de modelado individuales de 126 países, que abarcan todos los continentes (excepto la Antártida). De los 8471 artículos identificados como potencialmente relevantes, revisamos 1697 artículos apropiados y evaluamos y transferimos sistemáticamente 42 atributos relevantes a la base de datos. Esta base de datos GASEMT proporciona información integral sobre el estado del arte de los modelos de erosión del suelo y las aplicaciones de modelos en todo el mundo. Esta base de datos tiene la intención de apoyar la próxima evaluación mundial de la erosión del suelo de las Naciones Unidas basada en los países, además de ayudar a informar las prioridades de investigación de la erosión del suelo mediante la creación de una base para futuros análisis específicos y en profundidad. GASEMT es una base de datos de código abierto disponible para toda la comunidad de usuarios para desarrollar investigaciones, rectificar errores y realizar futuras expansiones. To gain a better understanding of the global application of soil erosion prediction models, we comprehensively reviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and 2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the regions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv) how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To perform this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. The resulting database, named 'Global Applications of Soil Erosion Modelling Tracker (GASEMT)', includes 3030 individual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471 articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluated and transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insights into the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to support the upcoming country-based United Nations global soil-erosion assessment in addition to helping to inform soil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is an open-source database available to the entire user-community to develop research, rectify errors, and make future expansions. للحصول على فهم أفضل للتطبيق العالمي لنماذج التنبؤ بتآكل التربة، قمنا بمراجعة شاملة للأدبيات البحثية ذات الصلة التي استعرضها الأقران حول نمذجة تآكل التربة المنشورة بين عامي 1994 و 2017. كنا نهدف إلى تحديد (1) العمليات والنماذج التي يتم تناولها بشكل متكرر في الأدبيات، (2) المناطق التي يتم فيها تطبيق النماذج في المقام الأول، (3) المناطق التي لا تزال دون معالجة ولماذا، و (4) عدد المرات التي يتم فيها إجراء دراسات للتحقق من صحة/تقييم نتائج النموذج بالنسبة للبيانات المقاسة. لأداء هذه المهمة، جمعنا المعرفة الجماعية لـ 67 عالمًا في مجال تآكل التربة من 25 دولة. تتضمن قاعدة البيانات الناتجة، المسماة "التطبيقات العالمية لتتبع نمذجة تآكل التربة (GASEMT )"، 3030 سجل نمذجة فردي من 126 دولة، تشمل جميع القارات (باستثناء القارة القطبية الجنوبية). من بين 8471 مقالة تم تحديدها على أنها ذات صلة محتملة، قمنا بمراجعة 1697 مقالة مناسبة وقمنا بتقييم ونقل 42 سمة ذات صلة بشكل منهجي إلى قاعدة البيانات. توفر قاعدة بيانات GASEMT هذه رؤى شاملة حول أحدث نماذج تآكل التربة وتطبيقات النماذج في جميع أنحاء العالم. تهدف قاعدة البيانات هذه إلى دعم التقييم العالمي المقبل لتآكل التربة الذي تجريه الأمم المتحدة على المستوى القطري بالإضافة إلى المساعدة في توجيه أولويات أبحاث تآكل التربة من خلال بناء أساس للتحليلات المتعمقة المستهدفة في المستقبل. GASEMT هي قاعدة بيانات مفتوحة المصدر متاحة لمجتمع المستخدمين بأكمله لتطوير البحث وتصحيح الأخطاء وإجراء التوسعات المستقبلية.

The drought-prone Ethiopian Somali region has a long history of pastoralism (livestock grazing), which is a major source of livelihoods. However, it suffers from poor rangeland management and a lack of research and information. The objectives of this study were to develop a method for forecasting forage biomass and to quantify production of and spatial variation in forage from satellite imagery. We downloaded Sentinel-2 images and processed spectral information in the blue, red, and near-infrared bands, and calculated the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). Combining ground sampling (on 55 plots) with remote sensing data, we developed a forage forecasting model for the area. Forage (biomass) was significantly correlated with both EVI (R 2 = 0.87; P < 0.001) and NDVI (R 2 = 0.81; P < 0.001). Both gave good predictions of forage biomass in the district. We estimated the annual biomass in each grassland pixel at the peak of the growing season. Models based on each index revealed close estimates: NDVI indicated an average of 0.76 t/ha and a total of 38 772 t/year; EVI indicated an average of 0.78 t/ha and a total of 39 792 t/year. The estimated rangeland biomass showed high spatial variability of 0.22-4.89 t/ha.year. For future rangeland management in the area, the proposed approach and models can be used to estimate available forage biomass from satellite imagery in the middle of the grass growing season (2 months after the rains start), before the grass matures and is harvested.

AbstractProduction of value-added outputs from biomass residues represents an opportunity to increase the supply of renewable energy in Ethiopia. Particularly, agroforestry could provide biomass residues for improved bioenergy products. The aim of this study was to characterize the interest of growers to provide biomass residues to a hypothetical biomass feedstock market. This study relied on a survey conducted on a sample of 240 farmers. Although the awareness of potential biomass products was generally quite low, a majority of farmers expressed interest in supplying biomass residues, but the level of interest depended on certain individual socio-economic and demographic characteristics. For example, younger and female household heads were found to be more interested in participating in the hypothetical biomass market, as were households with an improved biomass stove, larger land holdings, and higher income levels. In addition, larger households and those that felt less vulnerable to firewood scarcity also expressed more interest. As a whole, the results imply that farmers, particularly those with younger and female heads of households, should be supported with programs tailored to ensure their inclusion in biomass supply chains. Respondents generally preferred farm-gate sales of biomass, so the collecting, baling, and transporting of woody residues need to be properly incentivized or new actors need to be recruited into the supply chain. Providing households with energy-efficient tools such as improved stoves would not only increase demand for biomass products, but also increase the amount of biomass residues that could be supplied to the market instead of used at home.

The use of anionic polyacrylamide (PAM) as a soil conditioner could help prevent soil loss by water. In this study, we determined the effective granular PAM rate that best reduces runoff and soil loss from Oxisols. Furthermore, the effectiveness of the selected PAM rate was tested by applying it in a mixture with gypsum (G) or lime (L). The study was conducted in two phases: (i) Dry PAM rates of 0 (C), 20 kg ha−1 (P20), 40 kg ha−1 (P40), and 60 kg ha−1 (P60) were applied onto soil surface and run for six consecutive rainfall storms of 70 mm h−1 intensity for 1 h duration, and the effective PAM rate was selected; and (ii) G (4 t ha−1) or L (2 t ha−1) were applied alone or mixed with the selected PAM rate. The P20 was found to be effective in reducing runoff in the beginning while P40 and P60 were more effective starting from the third storm through the end of the consecutive storms, but with no statistically significant difference between P40 and P60. Hence, P40 was selected as the most suitable rate for the given test soil and rainfall pattern. On the other hand, the mixed application of P40 with G or L increased infiltration rate (IR) in the first two storms through improving soil solution viscosity. However, effectiveness of the mixtures had diminished by various degrees as rain progressed, as compared to P40 alone, which could be attributed to the rate and properties of G and L. In conclusion, the variation in effectiveness of PAM rates in reducing runoff with storm duration could indicate that the effective rates shall be selected based on the climatic region in that lower rates for the short rains or higher rates for elongated rains. Moreover, combined application of PAM with L could offer a good option to both fairly reduce soil erosion and improve land productivity especially in acidic soils like Oxisols, which requires further field verification.