Optimization of Production Methods for Black Soldier Fly Larvae (Hermetia illucens L.) in Burkina Faso.

Larvae of Hermetia illucens are a valuable source of protein for animal feed that can be produced by exposing animal and agro-industrial wastes to naturally occurring flies. The objective of this study was to improve techniques for obtaining H. illucens larvae to feed livestock in Burkina Faso. An experiment was conducted to determine the most favourable substrates and seasons for larval production. The substrates used were poultry manure, local beer waste, local beer waste mixed with poultry manure, cottonseed cake, and industrial brewery waste mixed with poultry manure. The production of larvae was carried out in four different seasons. The effect of the container's oviposition area (0.07 m2, 0.09 m2, and 0.11 m2) and the type of container (terracotta, plastic, and iron) on larval production was also assessed. The produced larval biomass was high during, or just after, the rainy season but very low during the cool dry and hot dry seasons. Yields were higher with local beer waste mixed with poultry manure followed by local beer waste and cottonseed cake. The average mass of H. illucens larvae increased slightly with the oviposition area for the same amount of substrate. Iron and terracotta containers provided better results than plastic containers. The suitability of this production method for H. illucens larvae production is discussed.

Assessing groundwater salinity across Africa.

In Africa groundwater is the principal source of drinking water (https://washdata.org/) and has significant potential to improve food production as a source of irrigation water. Although volumes of stored groundwater are high when compared to surface water, not all the available groundwater is suitable for irrigation. One of the principal factors that limit the development of groundwater is salinity, but quantitative evidence regarding the scale of salinization in Africa has been lacking. This paper presents an initial analysis of the extent of groundwater salinization in Africa, bringing together groundwater salinity data (n = 12,255) from across the continent. In our dataset c.80% of the samples have electrical conductivity values less than 2000 µS/cm. Samples with high conductivity values of more than 2000 µS/cm are restricted to limited geological and climatic environments. The data reveals salinity does not affect the water security status of most countries in Africa. However, salinity compounds water insecurity issues in arid low groundwater recharge environments. The paper discusses the role of anthropogenic processes such as river valley water resources development, extensive groundwater pumping, inter-basin groundwater transfer, and irrigation in altering the salinity of groundwater bodies. The paper further elucidates the origin of groundwater salinity by critically reviewing the natural and human-induced factors that control the salinization of the various groundwater bodies across Africa. Existing case studies reveal several causes of salinization, including i) human-induced salinization, ii) climate and hydrological change-induced paleo groundwater salinity, iii) rock dissolution, and iv), saltwater encroachment.

Validating a continental-scale groundwater diffuse pollution model using regional datasets.

In this study, we assess the validity of an African-scale groundwater pollution model for nitrates. In a previous study, we identified a statistical continental-scale groundwater pollution model for nitrate. The model was identified using a pan-African meta-analysis of available nitrate groundwater pollution studies. The model was implemented in both Random Forest (RF) and multiple regression formats. For both approaches, we collected as predictors a comprehensive GIS database of 13 spatial attributes, related to land use, soil type, hydrogeology, topography, climatology, region typology, nitrogen fertiliser application rate, and population density. In this paper, we validate the continental-scale model of groundwater contamination by using a nitrate measurement dataset from three African countries. We discuss the issue of data availability, and quality and scale issues, as challenges in validation. Notwithstanding that the modelling procedure exhibited very good success using a continental-scale dataset (e.g. R2 = 0.97 in the RF format using a cross-validation approach), the continental-scale model could not be used without recalibration to predict nitrate pollution at the country scale using regional data. In addition, when recalibrating the model using country-scale datasets, the order of model exploratory factors changes. This suggests that the structure and the parameters of a statistical spatially distributed groundwater degradation model for the African continent are strongly scale dependent.

Mapping the groundwater vulnerability for pollution at the pan African scale.

We estimated vulnerability and pollution risk of groundwater at the pan-African scale. We therefore compiled the most recent continental scale information on soil, land use, geology, hydrogeology and climate in a Geographical Information System (GIS) at a resolution of 15 km × 15 km and at the scale of 1:60,000,000. The groundwater vulnerability map was constructed by means of the DRASTIC method. The map reveals that groundwater is highly vulnerable in Central and West Africa, where the watertable is very low. In addition, very low vulnerability is found in the large sedimentary basins of the African deserts where groundwater is situated in very deep aquifers. The groundwater pollution risk map is obtained by overlaying the DRASTIC vulnerability map with land use. The northern, central and western part of the African continent is dominated by high pollution risk classes and this is very strongly related to shallow groundwater systems and the development of agricultural activities. Subsequently, we performed a sensitivity analysis to evaluate the relative importance of each parameter on groundwater vulnerability and pollution risk. The sensitivity analysis indicated that the removal of the impact of vadose zone, the depth of the groundwater, the hydraulic conductivity and the net recharge causes a large variation in the mapped vulnerability and pollution risk. The mapping model was validated using nitrate concentration data of groundwater as a proxy of pollution risk. Pan-African concentration data were inferred from a meta-analysis of literature data. Results shows a good match between nitrate concentration and the groundwater pollution risk classes. The pan African assessment of groundwater vulnerability and pollution risk is expected to be of particular value for water policy and for designing groundwater resources management programs. We expect, however, that this assessment can be strongly improved when better pan African monitoring data related to groundwater pollution will be integrated in the assessment methodology.