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Agriculture in West Africa is constrained by several yield-limiting factors, such as poor soil fertility, erratic rainfall distributions and low input systems. Projected changes in climate, thus, pose a threat since crop production is mainly rain-fed. The impact of climate change and its variation on the productivity of cereals in smallholder settings under future production systems in Navrongo, Ghana and Nioro du Rip, Senegal was assessed in this study. Data on management practices obtained from household surveys and projected agricultural development pathways (through stakeholder engagements), soil data, weather data (historical: 1980–2009 and five General Circulation Models, mid-century time slice 2040–2069 for two Representative Concentration Pathways, 4.5 and 8.5) were used for the impact assessment, employing a crop simulation model. Ensemble maize yield changes under the sustainable agricultural development pathway (SDP) were −13 and −16%, while under the unsustainable development pathway (USDP), yield changes were −19 and −20% in Navrongo and Nioro du Rip, respectively. The impact on sorghum and millet were lower than that on maize. Variations in climate change impact among smallholders were high with relative standard deviations (RSD) of between 14% and 60% across the cereals with variability being higher under the USDP, except for millet. Agricultural production systems with higher intensification but with less emphasis on soil conservation (USDP) will be more negatively impacted by climate change compared to relatively sustainable ones (SDP).

The yield gap and variability in maize under smallholder systems in two agroecologies in northern Ghana were evaluated using a decision support system for agrotechnology transfer (DSSAT). The model...

The productivity of smallholder farming systems is held back by poor soil fertility, low input levels and erratic rainfall distribution in the sorghum-based cropping systems of the Sudano-Sahelian zone of West Africa. We assessed the sensitivity of current agricultural practices to climate change and to improved management practices: (i) increased fertilizer application combined with increased plant populations and (ii) use of improved sorghum varieties. We applied the Decision Support Systems for Agro-Technological Transfer (DSSAT) Cropping Systems Model, and the Agricultural Production Systems sIMulator (APSIM), for a multiple-farm assessment (i.e. diverse types of management and soils) in Koutiala (Mali) and Navrongo (Ghana), which are representative sites for West African sorghum production systems. Baseline climate data from observed weather (1980–2009) and future climates from five Global Circulation Models (GCMs: 2040–2069) in two Representative Concentration Pathways (RCP 4.5 and 8.5) were used as inputs for crop models. In Navrongo, under current management, sorghum yields either decreased or increased compared to the baseline, depending on the crop models and the GCMs; changes in management options induced a yield increase of up to 256%. The addition of genetic improvement resulted in further yield increases (24%). In Koutiala, sorghum yield changes for future climates ranged from −38 to +8% assuming current management. Shifting to an improved cultivar had a marginal effect on grain yields, while increased fertilizer rates resulted in grain yield increases ranging of 20% and 153% for DSSAT and APSIM, respectively, assuming the current climate. We conclude that in the Sudano-Sahelian zone of West Africa sorghum, as it is cultivated today, appears moderately vulnerable to climate change, while doubling fertilizer inputs with an adjusted planting density, in the current climate, would more than double yields. However, by exploring farm diversity we established that, under certain conditions, the effect of the future climate might be as important as the effect of management changes in the current climate, hinting at the importance of locally-relevant management practices.

To reduce the risks of climate change, governments agreed in the Paris Agreement to limit global temperature rise to less than 2.0 °C above pre-industrial levels, with the ambition to keep warming to 1.5 °C. Charting appropriate mitigation responses requires information on the costs of mitigating versus associated damages for the two levels of warming. In this assessment, a critical consideration is the impact on crop yields and yield variability in regions currently challenged by food insecurity. The current study assessed impacts of 1.5 °C versus 2.0 °C on yields of maize, pearl millet and sorghum in the West African Sudan Savanna using two crop models that were calibrated with common varieties from experiments in the region with management reflecting a range of typical sowing windows. As sustainable intensification is promoted in the region for improving food security, simulations were conducted for both current fertilizer use and for an intensification case (fertility not limiting). With current fertilizer use, results indicated 2% units higher losses for maize and sorghum with 2.0 °C compared to 1.5 °C warming, with no change in millet yields for either scenario. In the intensification case, yield losses due to climate change were larger than with current fertilizer levels. However, despite the larger losses, yields were always two to three times higher with intensification, irrespective of the warming scenario. Though yield variability increased with intensification, there was no interaction with warming scenario. Risk and market analysis are needed to extend these results to understand implications for food security.

Maize (Zea mays) has traditionally been a major cereal staple in southern Ghana. Through breeding and other crop improvement efforts, the zone of cultivation of maize has now extended to the northern regions of Ghana which, hitherto, were the home to sorghum and millet as the major cereals. Maize yield in the northern Ghana is hampered by three major biophysical constraints, namely, poor soil fertility, low soil water storage capacity and climate variability. In this study we used the DSSAT crop model to assess integrated water and soil management strategies that combined the pre-season El-Niño-Southern Oscillation (ENSO)-based weather forecasting in selecting optimal planting time, at four locations in the northern regions of Ghana. It could be shown that the optimum planting date for a given year was predictable based on February-to-April (FMA) Sea Surface Temperature (SST) anomaly for the locations with R2 ranging from 0.52 to 0.71. For three out of four locations, the ENSO-predicted optimum planting dates resulted in significantly higher maize yields than the conventional farmer selected planting dates. In Wa for instance, early optimum planting dates were associated with La Nina and El Niño (Julian Days 130-150; early May to late May) whereas late planting (mid June to early July) was associated with the Neutral ENSO phase. It was also observed that the addition of manure and fertilizer improved soil water and nitrogen use efficiency, respectively, and minimized yield variability, especially when combined with weather forecast. The use of ENSO-based targeted planting date choice together with modest fertilizer and manure application has the potential to improve maize yields and also ensure sustainable maize production in parts of northern Ghana.

The CERES-sorghum module of the Decision Support System for Agro-Technological Transfer (DSSAT) model was calibrated for sorghum ( Sorghum bicolor (L.) Moench) using data from sorghum grown with adequate water and nitrogen and evaluated with data from several N rates trials in Navrongo, Ghana with an overall modified internal efficiency of 0.63. The use of mineral N fertilizer was found to be profitable with economically optimal rates of 40 and 80 kg N ha −1 for more intensively managed homestead fields and less intensively managed bush fields respectively. Agronomic N use efficiency varied from 21 to 37 kg grain kg −1 N for the homestead fields and from 15 to 49 kg grain kg −1 N in the bush fields. Simulated grain yield for homestead fields at 40 kg N ha −1 application was equal to yield for bush fields at 80 kg N ha −1 . Water use efficiency generally increased with increased mineral N rate and was greater for the homestead fields compared with the bush fields. Grain yield per unit of cumulative evapo-transpiration (simulated) was consistently higher compared with yield per unit of cumulative precipitation for the season, probably because of runoff and deep percolation. In the simulation experiment, grain yield variability was less with mineral N application and under higher soil fertility (organic matter) condition. Application of mineral N reduced variability in yield from a CV of 37 to 11% in the bush farm and from 17 to 7% in the homestead fields. The use of mineral fertilizer and encouraging practices that retain organic matter to the soil provide a more sustainable system for ensuring crop production and hence food security.

Crop simulation models afford the opportunity to study and understand underlying processes that impact on crop yield, hence, helps in designing appropriate strategies to improve crop production. The response of maize to N fertilization in a sub-humid environment was evaluated using DSSAT (crop simulation model). Two field experiments were conducted in the major and minor seasons in 2007. One was conducted under limited water and nutrient stress conditions and data collected used to calibrate model. The second independent experiments were conducted with different levels (0, 40, 80 and 120 kg N ha–1) of N fertilizer. Grain and biomass yields were predicted with an index of agreement of between 0.64 and 0.95 in both major and minor seasons. Biomass N content and crop phenology were also adequately simulated. Model simulations were better with higher rates of N fertilization and lesser water stress conditions. Water stress during the reproductive stage significantly affected grain yield. Sensitivity of selected soil parameters to grain yield indicated more sensitivity when no N fertilizer was applied. The DSSAT model has been satisfactorily calibrated and evaluated for the study area and hence, can be used to aid decision making in respect of farm management options.