An integrated modeling approach for estimating monthly global rainfall erosivity.

Modeling monthly rainfall erosivity is vital to the optimization of measures to control soil erosion. Rain gauge data combined with satellite observations can aid in enhancing rainfall erosivity estimations. Here, we presented a framework which utilized Geographically Weighted Regression approach to model global monthly rainfall erosivity. The framework integrates long-term (2001-2020) mean annual rainfall erosivity estimates from IMERG (Global Precipitation Measurement (GPM) mission's Integrated Multi-satellitE Retrievals for GPM) with station data from GloREDa (Global Rainfall Erosivity Database, n = 3,286 stations). The merged mean annual rainfall erosivity was disaggregated into mean monthly values based on monthly rainfall erosivity fractions derived from the original IMERG data. Global mean monthly rainfall erosivity was distinctly seasonal; erosivity peaked at ~ 200 MJ mm ha-1 h-1 month-1 in June-August over the Northern Hemisphere and ~ 700 MJ mm ha-1 h-1 month-1 in December-February over the Southern Hemisphere, contributing to over 60% of the annual rainfall erosivity over large areas in each hemisphere. Rainfall erosivity was ~ 4 times higher during the most erosive months than the least erosive months (December-February and June-August in the Northern and Southern Hemisphere, respectively). The latitudinal distributions of monthly and seasonal rainfall erosivity were highly heterogeneous, with the tropics showing the greatest erosivity. The intra-annual variability of monthly rainfall erosivity was particularly high within 10-30° latitude in both hemispheres. The monthly rainfall erosivity maps can be used for improving spatiotemporal modeling of soil erosion and planning of soil conservation measures.

Analysis of Malnutrition among Children under Five Years across Contrasting Agroecosystems of Northwest Ethiopia: Application of Structural Equation Modeling.

Child malnutrition remains a public health challenge in developing countries, but a comprehensive understanding of its burden and its determinants in specific local contexts is generally lacking. This study examined the prevalence of malnutrition and its determinants among children aged <5 years across contrasting agroecosystems in northwest Ethiopia. A community-based cross-sectional study involving 400 respondents was employed. Data were collected through semi-structured questionnaires and anthropometric measurements, complemented with focus group discussions and key informant interviews. The direct and indirect effects of the determinants of malnutrition were examined using structural equation modeling (SEM). The overall prevalence of child malnutrition, measured using the Composite Index of Anthropometric Failure, was 49%, with notable variation across agroecosystems (from 36.1% [midland with red soil] to 59% [lowland and valley fragmented]). Disease experience had significant positive direct effects on malnutrition. Dietary intake had negative and significant total (direct and indirect) effects on malnutrition, partially mediated through disease experience. Serial mediation in SEM analysis revealed significant indirect relationships between malnutrition and food security, feeding and care practices, household environment, health services, maternal diet, maternal empowerment, household wealth, and nutrition-sensitive agricultural practices. In conclusion, child malnutrition was highly prevalent and higher among children in the lowland and valley fragmented agroecosystem, characterized by unfavorable agro-climatic conditions, lower wealth status, poor health services access, and higher disease (particularly malaria) exposure. This study demonstrates the dynamics and multifaceted nature of malnutrition, highlighting the importance of considering geographical differences when planning interventions for childhood malnutrition and its determinants.

An integrated framework for improving watershed management planning.

Proper land use and management (LUM) planning is pivotal to curbing land degradation and ensuring sustainable use of limited watershed resources. Despite decades of research and development efforts, land degradation remains a serious environmental problem in many parts of the world. Issues regarding the sustainability of current LUM initiatives are due to poor linkages between the ecological and socio-economic dimensions of LUM decisions, and an integrated framework allowing LUM interventions to be properly planned and implemented is lacking. In this study, we developed an integrated framework to identify, evaluate, and propose LUM alternatives with ecological and socio-economic benefits. The framework comprises six components: (i) identification of land use problems and setting of objectives, (ii) identification of the best-performing land use-based integrated solutions, (iii) formulation of LUM alternatives and modeling of key indicators, (iv) cost-benefit analysis, (v) evaluation of the LUM alternatives with stakeholders engagement, and (vi) communication of the LUM alternatives to relevant stakeholders to obtain institutional and financial support for implementation. To demonstrate the use of this framework, we conducted a case study in the Aba Gerima watershed of the Upper Blue Nile basin in Ethiopia. This study used extensive plot- and watershed-scale observations (2015-2019) obtained under both conventional and improved sustainable land management practices. We analyzed changes in runoff, soil loss, soil organic carbon (SOC) stock, and land productivity of five LUM alternatives as compared to a baseline scenario (existing farming practices). The results showed that the LUM alternatives reduced runoff by 11-71% and soil loss by 66-95%, and SOC stock and watershed-scale land productivity were improved by 36-104% and 48-134%, respectively. Evaluation of LUM alternatives by stakeholders, including land users, policy makers, and researchers, produced divergent results. In particular, land users prioritized implementation of sustainable land management practices without altering existing land uses. The integrated framework developed in this study can serve as a valuable tool for identifying, evaluating, and proposing LUM alternatives and facilitating decision-making in planning and implementation of LUM practices in watersheds experiencing land degradation.

Global rainfall erosivity database (GloREDa) and monthly R-factor data at 1 km spatial resolution.

Here, we present and release the Global Rainfall Erosivity Database (GloREDa), a multi-source platform containing rainfall erosivity values for almost 4000 stations globally. The database was compiled through a global collaboration between a network of researchers, meteorological services and environmental organisations from 65 countries. GloREDa is the first open access database of rainfall erosivity (R-factor) based on hourly and sub-hourly rainfall records at a global scale. This database is now stored and accessible for download in the long-term European Soil Data Centre (ESDAC) repository of the European Commission's Joint Research Centre. This will ensure the further development of the database with insertions of new records, maintenance of the data and provision of a helpdesk. In addition to the annual erosivity data, this release also includes the mean monthly erosivity data for 94% of the GloREDa stations. Based on these mean monthly R-factor values, we predict the global monthly erosivity datasets at 1 km resolution using the ensemble machine learning approach (ML) as implemented in the mlr package for R. The produced monthly raster data (GeoTIFF format) may be useful for soil erosion prediction modelling, sediment distribution analysis, climate change predictions, flood, and natural disaster assessments and can be valuable inputs for Land and Earth Systems modelling.

Analyzing the contribution of gully erosion to land degradation in the upper Blue Nile basin, Ethiopia.

Soil erosion has become a worldwide problem that threatens the environment and the future of economic and social development. The purpose of this study is to investigate the contribution of steep slopes and gullies to erosion in high precipitation tropical areas of the Ethiopian highlands. A trapezoidal weir was installed at the head and tail of the gully to monitor the discharge and sediment concentration from 2017 to 2020. Sediment yield and runoff are heavily influenced by the amount and timing of precipitation. The coefficients of variation for total sediment loads ranged from 65.1 to 96.1% at the head and 17.1-78.1% at the tail; the lowest coefficients were found in 2018 and the highest in 2020. Furthermore, 85% of the sediment at the tail comes from the gully, according to the four-year sediment budget. Further, a hysteretic analysis of suspended sediment concentration and runoff revealed that hilly sediment sources are limited (clockwise), then sediment can be transported through the gully via bank failures (counterclockwise). Study findings contributed to a classification of runoff patterns and an investigation of suspended sediment dynamics. In the gully tail, sediment yield was higher than in the head, suggesting gully sediment contributed more to sediment yield than large upland catchments. As a result of the study, we have been able to develop practical recommendations for managing gully erosion in the future.

Predicting runoff and sediment responses to climate-resilient land use and management scenarios.

Soil erosion is the predominant agent affecting ecosystem services in the Ethiopian highlands. However, land management interventions aimed at controlling erosion in the region are hampered, mainly by a lack of watershed-based appropriate management practices and anticipated climate changes. This study examined the effectiveness of different land use changes and management scenarios in decreasing runoff and sediment loss under current and future climates in the drought-prone humid watershed of the Ethiopian highlands. We employed a modeling approach integrating observed data at watershed and plot scales with Soil and Water Assessment Tool. In the first step, we evaluated the impact of land use changes between 2006 and 2017 on runoff and sediment loss. Then, we developed five land use and management scenarios based on watershed land capabilities and selected land management practices. Model parameters were modified based on runoff and sediment loss results obtained from experimental plots of biophysical and agronomical land management practices in the watershed. The runoff and sediment loss were simulated under current (2014-2019) and future climates (the 2050s) for each land use and management scenario. Results revealed that land use changes (mainly an increase in Acacia decurrens plantations by 206%) alone between 2006 and 2017 reduced runoff by 31% and sediment loss by 45%. Under the current climate, the five land use and management scenarios reduced runoff by 71-95% and sediment loss by 75-96% compared to the baseline scenario. Under the future climate (2050s), these scenarios decreased runoff by 48-90% and sediment loss by 54-91%. However, their effectiveness was slightly decreased (5-23%) as a result of increases in rainfall (10-46%) and mean temperature (1.7-1.9 °C) in the 2050s. The scenario of improving vegetation cover through forage production and plantations in appropriate areas plus best land management practices was the most effective and climate-resilient of the five scenarios. This study suggests that evaluating the impact of land use and management practices under future climate change shows promise for guiding effective and sustainable interventions to adapt to climate change.

Monitoring impacts of soil bund on spatial variation of teff and finger millet yield with Sentinel-2 and spectroradiometric data in Ethiopia.

Data from remote sensing devices are essential for monitoring environmental protection practices and estimating crop yields. However, yield estimates in Ethiopia are based on time-consuming surveys. We used Sentinel-2, spectroradiometeric, and ground-truthing data to estimate the grain yield (GY) of two major crops, teff, and finger millet, in Ethiopia's Aba Gerima catchment in 2020 and 2021. At the flowering stage, we performed supervised classification on October Sentinel-2 images and spectral reflectance measurement. We used regression models to identify and predict crop yields, as evaluated by the coefficient of determination (adjusted R2) and root mean square error (RMSE). The enhanced vegetation index (EVI) and normalized-difference vegetation index (NDVI) provided the best fit to the data among the vegetation indices used to predict teff and finger millet GY. Soil bund construction increased the majority of vegetation indices and GY of both crops. We discovered a strong correlation between GY and the satellite EVI and NDVI. However, NDVI and EVI had the greatest influence on teff GY (adjusted R2 = 0.83; RMSE = 0.14 ton/ha), while NDVI had the greatest influence on finger millet GY (adjusted R2 = 0.85; RMSE = 0.24 ton/ha). Teff GY ranged from 0.64 to 2.16 ton/ha for bunded plots and 0.60 to 1.85 ton/ha for non-bunded plots using Sentinel-2 data. Besides, finger millet GY ranged from 1.92 to 2.57 ton/ha for bunded plots and 1.81 to 2.38 ton/ha for non-bunded plots using spectroradiometric data. Our findings show that Sentinel-2- and spectroradiometeric-based monitoring can help farmers manage teff and finger millet to achieve higher yields, more sustainable food production, and better environmental quality in the area. The study's findings revealed a link between VIs and soil management practices in soil ecological systems. Model extrapolation to other areas will necessitate local validation.

Progress and challenges in sustainable land management initiatives: A global review.

Sustainable land management (SLM) is widely recognized as the key to reducing rates of land degradation, and preventing desertification. Many efforts have been made worldwide by various stakeholders to adopt and/or develop various SLM practices. Nevertheless, a comprehensive review on the spatial distribution, prospects, and challenges of SLM practices and research is lacking. To address this gap, we gathered information from a global SLM database provided by the World Overview of Conservation Approaches and Technologies (WOCAT) and two bibliographic databases of academic research. Over 1900 SLM practices and 1181 academic research papers from 129 and 90 countries were compiled and analyzed. Relatively better SLM dissemination was observed in dry subhumid countries and countries with medium scores on the Human Development Index (HDI), whereas dissemination and research were both lower in humid countries with low HDI values. Cropland was the main land use type targeted in both dissemination and research; degradation caused by water erosion and mitigation aimed at water erosion were also the main focus areas. Other dominant land use types (e.g., grazing) and SLM purposes (e.g., economic benefits) have received relatively less research attention compared to their dissemination. Overall, over 75 % of the 60 countries experiencing high soil erosion rates (>10 t ha-1 yr-1) also have low HDI scores, as well as poor SLM dissemination and research implying the limited evidence-based SLM dissemination in these countries. The limitation of research evidence can be addressed in the short term through integrating existing scientific research and SLM databases by adopting the proposed Research Evidence for SLM framework. There is, however, a great need for additional detailed studies of country-specific SLM challenges and prospects to create appropriate evidence-based SLM dissemination strategies to achieve multiple SLM benefits.

Land use, management and climate effects on runoff and soil loss responses in the highlands of Ethiopia.

Soil erosion by water is a major cause of land degradation in the highlands of Ethiopia and anywhere else in the world, but its magnitude and variability are rarely documented across land uses and climatological conditions. The purpose of this study was to examine runoff and soil loss responses under cropland (CL) and grazing land (GL) management practices in three climatic regions of the Ethiopian highlands: semi-arid (Mayleba), dry sub-humid (Gumara), and humid (Guder). We measured runoff and soil loss using runoff plots with and without soil and water conservation (SWC) measures (trenches, stone/soil bunds [embankments] with trenches on the upslope side, and exclosure) during the rainy season (July-September). The results revealed significant variation in runoff and soil loss amounts across land uses, SWC measures, and climatic regions. At Mayleba, seasonal runoff and soil loss in control plot were far higher from GL (280 mm, 26.5 t ha-1) than from CL (108 mm, 7.0 t ha-1) largely due to lack of protective vegetation cover and soil disruption because of intense grazing. In contrast, at Gumara and Guder, seasonal soil loss values were much higher from CL (21.4-71.2 t ha-1) than from GL (0.6-24.2 t ha-1) irrespective of runoff values. This was attributed to the excessive tillage/weeding operations involved in cultivation of teff (cereal crop) at Gumara and potato at Guder. Although SWC measures (practices) substantially reduced runoff and soil loss (decreased by 23%-86%) relative to control plot, seasonal soil loss under GL uses with trenches at Mayleba (12.6 t ha-1), CL with soil bunds and trenches at Gumara (22.1 t ha-1), and Guder (21.4 t ha-1) remained higher than the average tolerable soil loss rate (10 t ha-1 year-1) proposed for the Ethiopian highlands. This suggests that SWC measures should be carefully designed and evaluated specific to land use and climatic conditions. Overall, the results of this study can help improve SWC planning in regions where land use and climate impact on soil erosion vary across geographical areas, as they do in Ethiopia and anywhere else. However, further investigation is crucial with replication of measurements over years and locations to provide more accurate information on land use, management and climate controls on hydrological and soil erosion processes.

Seasonal and diurnal soil respiration dynamics under different land management practices in the sub-tropical highland agroecology of Ethiopia.

The temporal dynamics of soil respiration change in response to different land management practices are not well documented. This study investigated the effects of soil bunds on the monthly and diurnal dynamics of soil respiration rates in the highlands of the Upper Blue Nile basin in Ethiopia. Six plots (with and without soil bunds, three replicates) were used for measurement of seasonal soil respiration, and 18 plots were used for measurement of diurnal soil respiration. We collected seasonal variation data on a monthly basis from September 2020 to August 2021. Diurnal soil respiration data were collected four times daily (5 a.m., 11 a.m., 5 p.m., and 11 p.m.) for 2 weeks from 16 to 29 September 2021. A Wilcoxon signed-rank test showed that seasonal soil respiration rates differed significantly (p < 0.05) between soil bund and control plots in all seasons. In plots with soil bunds, seasonal soil respiration rates were lowest in February (1.89 ± 0.3 µmol CO2 m-2 s-1, mean ± SE) and highest in October (14.54 ± 0.5 µmol CO2 m-2 s-1). The diurnal soil respiration rate was significantly (p < 0.05) higher at 11 a.m. than at other times, and was lowest at 5 a.m. Seasonal variation in soil respiration was influenced by soil temperature negatively and moisture positively. Diurnal soil respiration was significantly affected by soil temperature but not by soil moisture. Further study is required to explore how differences in soil microorganisms between different land management practices affect soil respiration rates.

Use of soil spectral reflectance to estimate texture and fertility affected by land management practices in Ethiopian tropical highland.

As classical soil analysis is time-consuming and expensive, there is a growing demand for visible, near-infrared, and short-wave infrared (Vis-NIR-SWIR, wavelength 350-2500 nm) spectroscopy to predict soil properties. The objectives of this study were to investigate the effects of soil bunds on key soil properties and to develop regression models based on the Vis-NIR-SWIR spectral reflectance of soils in Aba Gerima, Ethiopia. Soil samples were collected from the 0-30 cm soil layer in 48 experimental teff (Eragrostis tef) plots and analysed for soil texture, pH, organic carbon (OC), total nitrogen (TN), available phosphorus (av. P), and potassium (av. K). We measured reflectance from air-dried, ground, and sieved soils with a FieldSpec 4 Spectroradiometer. We used regression models to identify and predict soil properties, as assessed by the coefficient of determination (R2), root mean square error (RMSE), bias, and ratio of performance to deviation (RPD). The results showed high variability (CV ≥ 35%) and substantial variation (P < 0.05 to P < 0.001) in soil texture, OC, and av. P in the catchment. Soil reflectance was lower from bunded plots. The pre-processing techniques, including multiplicative scatter correction, median filter, and Gaussian filter for OC, clay, and sand, respectively were used to transform the soil reflectance. Statistical results were: R2 = 0.71, RPD = 8.13 and bias = 0.12 for OC; R2 = 0.93, RPD = 2.21, bias = 0.94 for clay; and R2 = 0.85 with RPD = 7.54 and bias = 0.0.31 for sand with validation dataset. However, care is essential before applying the models to other regions. In conclusion, the findings of this study suggest spectroradiometry can supplement classical soil analysis. However, more research is needed to increase the prediction performance of Vis-NIR-SWIR reflectance spectroscopy to advance soil management interventions.

A leaf reflectance-based crop yield modeling in Northwest Ethiopia.

Crop yield prediction provides information to policymakers in the agricultural production system. This study used leaf reflectance from a spectroradiometer to model grain yield (GY) and aboveground biomass yield (ABY) of maize (Zea mays L.) at Aba Gerima catchment, Ethiopia. A FieldSpec IV (350-2,500 nm wavelengths) spectroradiometer was used to estimate the spectral reflectance of crop leaves during the grain-filling phase. The spectral vegetation indices, such as enhanced vegetation index (EVI), normalized difference VI (NDVI), green NDVI (GNDVI), soil adjusted VI, red NDVI, and simple ratio were deduced from the spectral reflectance. We used regression analyses to identify and predict GY and ABY at the catchment level. The coefficient of determination (R2), the root mean square error (RMSE), and relative importance (RI) were used for evaluating model performance. The findings revealed that the best-fitting curve was obtained between GY and NDVI (R2 = 0.70; RMSE = 0.065; P < 0.0001; RI = 0.19), followed by EVI (R2 = 0.65; RMSE = 0.024; RI = 0.61; P < 0.0001). While the best-fitting curve was obtained between ABY and GNDVI (R2 = 0.71; RI = 0.24; P < 0.0001), followed by NDVI (R2 = 0.77; RI = 0.17; P < 0.0001). The highest GY (7.18 ton/ha) and ABY (18.71 ton/ha) of maize were recorded at a soil bunded plot on a gentle slope. Combined spectral indices were also employed to predict GY with R2 (0.83) and RMSE (0.24) and ABY with R2 (0.78) and RMSE (0.12). Thus, the maize's GY and ABY can be predicted with acceptable accuracy using spectral reflectance indices derived from spectroradiometer in an area like the Aba Gerima catchment. An estimation model of crop yields could help policy-makers in identifying yield-limiting factors and achieve decisive actions to get better crop yields and food security for Ethiopia.

Effect of exclosure on subsurface water level and sediment yield in the tropical highlands of Ethiopia.

Grazing is a major cause of soil erosion and land degradation across many parts of Ethiopia. This study examined the effects of exclosure on subsurface water levels, soil erosion, and the relationship between daily rainfall and subsurface water levels. Piezometers were used to measure subsurface water levels in the exclosure area during 2017-2020. We found that sediment yield, runoff, and the volume of subsurface water vary greatly depending on the exclosure and temporal practices used. Exclosure of grazing land was the most effective sustainable land management practice in reducing runoff and sediment yield. In 2019 and 2020, the subsurface water level continued to rise at piezometers with exclosure, which shows that exclosure contributed to the subsurface water level rising. In addition, piezometers in grazing land and the exclosure indicate that runoff trapped by acacia decurrens trees can contribute to significant differences in subsurface water levels. Higher runoff coefficients were observed in 2017 and 2018 than in 2019 and 2020, indicating that the exclosure greatly affects runoff; therefore, its implementation is vital to reduce runoff and enhance water conservation. Sediment yields measured for 2017, 2018, 2019, and 2020 were 140.45, 133.15, 101.03, and 74.39 g L-1 day-1, respectively. In 2017 and 2018, sediment yield increased, while in 2019 and 2020 sediment yield decreased because of an exclosure around the gully's cross-section and communal grazing. This study shows that erosion is reduced by exclosure, possibly due to the restoration of protective vegetation cover. This study revealed that a minimum of human and livestock intervention during the study period considerably increased groundwater levels and decreased soil erosion. Generally, the results of this study indicated that exclosure has a considerable impact on runoff and sediment. Therefore, exclosure implementation is vital to reduce runoff and sediment and enhance water conservation, thus supporting the development of effective communal grazing land management measures on the study sites and other similar environmental settings.

Small-Scale Woodlot Growers' Interest in Participating in Bioenergy Market In Rural Ethiopia.

Production 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.

Spatial variability of soil chemical properties under different land-uses in Northwest Ethiopia.

The understanding of the spatial variation of soil chemical properties is critical in agriculture and the environment. To assess the spatial variability of soil chemical properties in the Fogera plain, Ethiopia, we used Inverse Distance Weighting (IDW), pair-wise comparisons, descriptive analysis, and principal component analysis (PCA). In 2019, soil samples were collected at topsoil (a soil depth of 0-20 cm) from three representative land-uses (cropland, plantation forestland, and grazing lands) using a grid-sampling design. The variance analysis for soil pH, available phosphorus (avP), organic carbon (OC), total nitrogen (TN), electrical conductivity (EC), exchangeable potassium (exchK), exchangeable calcium (exchCa), and cation exchange capacity (CEC) revealed significant differences among the land-uses. The highest mean values of pH (8.9), avP (32.99 ppm), OC (4.82%), TN (0.39%), EC (2.28 dS m-1), and exchK (2.89 cmol (+) kg-1) were determined under grazing land. The lowest pH (6.2), OC (2.3%), TN (0.15%), and EC (0.11 dS m-1) were recorded in cultivated land. The PCA result revealed that the land-use change was responsible for most soil chemical properties, accounting for 93.32%. Soil maps can help identify the nutrient status, update management options, and increase productivity and profit. The expansion of cultivated lands resulted in a significant decrease in soil organic matter. Thus, soil management strategies should be tailored to replenish the soil nutrient content while maintaining agricultural productivity in the Fogera plain.

Exploring the variability of soil nutrient outflows as influenced by land use and management practices in contrasting agro-ecological environments.

Improving our understanding of how different land uses and management practices affect soil nutrient outflows in sub-Saharan Africa could aid in developing sustainable practices. The objective of this study was to analyse the variation in outflows of soil total nitrogen (TN) and available phosphorus (Pav) as influenced by land use types (cropland, grazing land, and bushland) and land management practices (soil bunds for cropland and exclosures for non-croplands) in the three contrasting agro-ecological zones of the Upper Blue Nile basin, Ethiopia. Field data were collected for TN and Pav outflows by water erosion (Eo), leaching (Lo), product harvest (Ho), and gaseous emissions (Go) from 18 runoff plots (30 m × 6 m) for two years (2018-2019). TN and Pav losses significantly varied (p < 0.05, p < 0.01) among agro-ecological zones, land use types, and management practices. Losses of TN ranged from 39.6 to 55.5 kg ha-1 yr-1 and those of Pav from 4.1 to 5.9 kg ha-1 yr-1, with a total replacement cost of US$26-38 ha-1 yr-1. Nutrient losses and cost generally increased from lowland (Dibatie) to midland (Aba Gerima) to highland (Guder), although the highland and midland sites did not differ significantly (p > 0.05) in nutrient losses. Cropland showed significantly higher TN and Pav losses than other land use types, but TN loss did not differ significantly between grazing and bushland. In all land use types at all sites, the magnitude of nutrient losses was Ho >Eo >Lo >Go. In plots with land management practices, TN and Pav losses associated with Eo, Lo, and Go were reduced on average by 44-76%, 9-47%, and 1%-36%, respectively. These practices were most effective to reduce Eo nutrient losses. Further study is required to analyzing the soil nutrient balance and identify priority areas for implementing mitigation measures.

Cost-benefit analysis of on-farm grain storage hermetic bags among small-scale maize growers in northwestern Ethiopia.

Farmers continue losing substantial quantities of grain during storage due to damages from pests including insects. Hermetic bags, being promoted in Ethiopia, could be viable alternatives to traditional methods and insecticides that are commonly used by farmers to store grain. However, the economics and determinants behind farmers' decisions to use different storage methods are poorly understood. This study sought to ascertain the economics of hermetic grain storage technology among 450 representative small-scale maize farmers in northwestern Ethiopia. Gross margin (GM), and the marginal rate of return (MRR) were employed to estimate the economic costs and benefits of storage methods, while a multivariate probit regression model was employed to analyze the determinants of farmers' decision to store maize with a given storage method. The results show that farmers used a combination of different storage techniques: 19.6% did not store grain, 87.8% used traditional methods with pesticide, and 66.7% used Purdue Improved Crop Storage (PICS) hermetic bags. Farmers who used hermetic bags also used other mentioned storage techniques. PICS had the highest GM (US$21.77 100 kg-1) and MRR (3.196), indicating that they were the most profitable. Moreover, a household could obtain an additional net cash flow of US$5.02 100 kg-1 PICS bag per season after 9.6 months of storage. Farmers' decisions to use PICS bags were influenced by several factors including access to information, the initial cost, and storage capacity of the technology. Thus, increasing awareness and improving supply chain efficiency to reduce the cost of the PICS bags would improve adoption rates.

Soil erosion modelling: A bibliometric analysis.

Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper.

Soil erosion modelling: A global review and statistical analysis.

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.