The effect of slope steepness and antecedent moisture content on interrill erosion, runoff and sediment size distribution in the highlands of Ethiopia

Soil erosion is a two-phase process consisting of the detachment of individual particles and their transport by the flowing water. This study discusses the results of laboratory experiments in which for three soils, the runoff depth, sediment yield, splash erosion and sediment size were measured. Rainfall intensity, slope and antecedent moisture contents were varied in the experiment. The soil types ranged from clay to sandy clay loam (Alemaya Black soil, Regosols and Cambisols). Rainfall was applied for six sequential 15-min periods with rainfall intensities varying between 55 and 120 mm h<sup>−1</sup>. The three slopes tested were 9, 25, and 45 %. Results show that as slope increased from 9 to 25 %, splash erosion and sediment yield increased. An increase in slope from 25 to 45 % generally decreases in splash erosion. Sediment yield for one soil increased and one soil decreased with slope and for the third soil the trend was different between the two initial moisture contents. Sediment yield was correlated (<i>r</i> = 0.66) with runoff amounts but not with splash erosion. Interrill erosion models that were based on the flowing water and rainfall intensity fitted the data better than when based on rainfall intensity solely. Models that assume a positive linear relationship between erosion and slope may overestimate sediment yield

The effect of women's nutrition knowledge and empowerment on child nutrition outcomes in rural Ethiopia

Child malnutrition remains widespread in Ethiopia. Women’s nutrition knowledge and empowerment are emphasized as key impact pathways for nutrition sensitive programs and interventions. This paper examines effects of women’s nutrition knowledge and empowerment on child nutrition outcomes using survey data from rural Ethiopia. Employing econometric strategies that account for potential endogeneity concerns, nutrition knowledge, and empowerment are found to have strong and significant effects on children’s dietary diversity and stunting. Their interaction is significantly correlated only with stunting, perhaps suggesting the importance of the interaction between nutrition knowledge and empowerment for long-term nutrition outcomes.Adisaggregated analysis of empowerment reveals that empowering women in household agricultural decisions and increasing their access to and control of economic resources are more promising for improving child nutrition.Overall, the findings suggest that efforts targeting to improve child nutrition in Ethiopia need to be complemented by efforts to improve women’s nutrition knowledge and empowerment

Networks, incentives and technology adoption: evidence from a randomised experiment in Uganda

We use data from a randomised experiment in Uganda to examine effects of incentives on the decision to adopt drought-tolerant maize varieties (DTMVs) and mechanisms through which effects occur. We find that social recognition (SR) incentives to a random subset of trained farmers – disseminating farmers (DFs) – increase knowledge transmission from DFs to their co-villagers and change information networks of both DFs and their neighbours. SR also increases DFs’ likelihood of adopting DTMVs. However, the corresponding results for private material rewards are not conclusively strong. We find no evidence that incentives for knowledge diffusion increase the likelihood of co-villagers adopting DTMVs

A Coupled Remote Sensing and Simplified Surface Energy Balance Approach to Estimate Actual Evapotranspiration from Irrigated Fields

Accurate crop performance monitoring and production estimation are critical for timely assessment of the food balance of several countries in the world. Since 2001, the Famine Early Warning Systems Network (FEWS NET) has been monitoring crop performance and relative production using satellite-derived data and simulation models in Africa, Central America, and Afghanistan where ground-based monitoring is limited because of a scarcity of weather stations. The commonly used crop monitoring models are based on a crop water-balance algorithm with inputs from satellite-derived rainfall estimates. These models are useful to monitor rainfed agriculture, but they are ineffective for irrigated areas. This study focused on Afghanistan, where over 80 percent of agricultural production comes from irrigated lands. We developed and implemented a Simplified Surface Energy Balance (SSEB) model to monitor and assess the performance of irrigated agriculture in Afghanistan using a combination of 1-km thermal data and 250-m Normalized Difference Vegetation Index (NDVI) data, both from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. We estimated seasonal actual evapotranspiration (ETa) over a period of six years (2000-2005) for two major irrigated river basins in Afghanistan, the Kabul and the Helmand, by analyzing up to 19 cloud-free thermal and NDVI images from each year. These seasonal ETa estimates were used as relative indicators of year-to-year production magnitude differences. The temporal water-use pattern of the two irrigated basins was indicative of the cropping patterns specific to each region. Our results were comparable to field reports and to estimates based on watershed-wide crop water-balance model results. For example, both methods found that the 2003 seasonal ETa was the highest of all six years. The method also captured water management scenarios where a unique year-to-year variability was identified in addition to water-use differences between upstream and downstream basins. A major advantage of the energy-balance approach is that it can be used to quantify spatial extent of irrigated fields and their water-use dynamics without reference to source of water as opposed to a water-balance model which requires knowledge of both the magnitude and temporal distribution of rainfall and irrigation applied to fields

Access to credit and heterogeneous effects on agricultural technology adoption: Evidence fromlarge rural surveys in Ethiopia

Modern agricultural technologies hold huge potential for increasing productivity and reducing poverty in developing countries. However, adoption levels of these technologies have remained disappointingly low in Africa. This paper analyzes the effect of access to credit on the likelihood of adoption and use intensity of chemical fertilizers using data from large rural surveys in Ethiopia. Using a heteroscedasticity-based identification strategy to address the endogenous nature of access to credit, we find that access to credit has significant positive effects on adoption and intensity of use of chemical fertilizers. However, important heterogeneities are observed. Credit obtained from formal sources is more important for the intensity of use than for the decision to adopt chemical fertilizers. Credit taken with the primary purpose of financing agricultural inputs is more likely to promote adoption of chemical fertilizers than credit taken per se. Furthermore, reported credit effects are larger when estimated against the sample of credit-constrained non-users as compared with the pool of the whole sample of credit non-users. The results remain robust to several sensitivity analyses. Our results yield useful implications for the design, promotion, and targeting of credit services to leverage their effect on adoption of agricultural technologies

Consumer Nutrition Knowledge and Dietary Behavior in Urban Ethiopia: A Comprehensive Study

This paper studies the association between nutrition knowledge and consumer dietary behavior using large survey data from 996 respondents in Addis Ababa, Ethiopia. We find that health was the most important factor in individuals’ food choice. However, most consumers were found to have imperfect understanding of the link between food and health. Especially, the causes and consequences of obesity were poorly understood. A considerable proportion of respondents also endorsed harmful food taboos. We found that nutrition knowledge was positively associated with more diversified diets and healthy eating attitudes and practices. Individuals with higher levels of nutrition knowledge were also more likely to reject harmful food taboos

Runoff Estimation and Water Demand Analysis for Holetta River, Awash Subbasin, Ethiopia Using SWAT and CropWat Models

This chapter discusses the hydrology of Holetta River , Ethiopia , its seasonal variability and water management in the watershed. Soil and Water Assessment Tool (SWAT) modeled the rainfall–runoff process of the watershed. Statistical [coefficient of determination (R 2), Nash–Sutcliffe efficiency coefficient (NSE), and index of volumetric fit (IVF)] and graphical methods were used to evaluate the performance of the model. The result showed that R 2, NSE and IVF were 0.85, 0.84 and 102.8, respectively, for monthly calibration and 0.73, 0.67 and 108.9, respectively, for monthly validation. These indicated that SWAT model performed well for simulation of the hydrology of the watershed. After modeling the rainfall runoff relation, the water demand of the area was assessed. CropWat model was applied and survey analyses were performed to calculate the water demand in the area. The total water demand for the three major users was 0.313, 0.583, 1.004, 0.873, and 0.341 million cubic meters (MCM) from January to May, respectively. The average flow obtained from SWAT simulation was 0.749, 0.419, 0.829, 0.623, and 0.471 MCM from January to May, respectively. From 5 months, the demand and the supply showed a gap during February, March, and April with 0.59 MCM. To solve the gap created by the demand, alternative source of water supply should be studied and integrated water management systems should be implemented

Understanding Farmers’ Trait Preferences for Dual-Purpose Crops to Improve Mixed Crop–Livestock Systems in Zimbabwe

Competition over land between food and fodder production, along with recurrent droughts and increasing population, has put mixed crop–livestock farming systems in the drylands of sub- Saharan Africa under pressure. Dual-purpose crops hold huge potential to ease this pressure and simultaneously improve food and fodder availability in these systems. We investigated farmers’ preferences for dual-purpose maize, sorghum, and groundnut traits, and analyzed linkages of stated trait preferences with production of dual-purpose crops and adoption of improved varieties involving 645 households from two districts in Zimbabwe. The three target crops cover more than 75% of households’ cropping lands. Highly preferred stated traits of dual-purpose crops include yield, disease resistance, and drought tolerance. Highly appreciated feed attributes encompass stover yield and digestibility. The adoption of improved varieties is high for maize but low for sorghum and groundnut. Trait preferences are correlated with the production of dual-purpose crops and the adoption of improved varieties of the crops. However, the strengths of these correlations differ for maize, sorghum, and groundnuts. We discuss these linkages and suggest why crop improvement programs should reconcile trade-offs between grain and feed attributes to support mixed crop– livestock systems in Zimbabwe successfully

Empowering local partners for inclusive and sustainable agricultural development — experiences from the Tropical Legumes Project in Africa

The importance of strong local partnerships and alliances for the sustainability and long-term success of agricultural development efforts cannot be overemphasized. This is supported by its inclusion as a standalone goal (goal 17) in the Sustainable Development Goals (SDGs), but also by increasing calls to make local partnerships and alliances integral components of development projects and programmes. Strong local partnerships are critical not only for identifying development needs, setting priorities, and driving the implementation of validated development interventions but also for scaling and sustaining impacts of such interventions

SWPT: An automated GIS-based tool for prioritization of sub-watersheds based on morphometric and topo-hydrological factors

© 2019 China University of Geosciences (Beijing) and Peking University The sub-watershed prioritization is the ranking of different areas of a river basin according to their need to proper planning and management of soil and water resources. Decision makers should optimally allocate the investments to critical sub-watersheds in an economically effective and technically efficient manner. Hence, this study aimed at developing a user-friendly geographic information system (GIS) tool, Sub-Watershed Prioritization Tool (SWPT), using the Python programming language to decrease any possible uncertainty. It used geospatial–statistical techniques for analyzing morphometric and topo-hydrological factors and automatically identifying critical and priority sub-watersheds. In order to assess the capability and reliability of the SWPT tool, it was successfully applied in a watershed in the Golestan Province, Northern Iran. Historical records of flood and landslide events indicated that the SWPT correctly recognized critical sub-watersheds. It provided a cost-effective approach for prioritization of sub-watersheds. Therefore, the SWPT is practically applicable and replicable to other regions where gauge data is not available for each sub-watershed