Heidi Webber

Farming in the West African Sudan Savanna: Insights in the context of climate change

Farming is the main livelihood activity in semi-arid rural West Africa, involving the largest portion of the population, contributing significantly to the regional economy and intimately intertwined with current environmental problems. Key vulnerabilities of the Sudan Savanna include its ecological fragility, institutional weakness, high levels of poverty and food insecurity, and political and economic instability, now aggravated by climate change. The characterization of current farming and cropping systems in the Sudan Savanna is the key for understanding and proposing meaningful adaptation strategies at the field, farm, local and national levels. This review begins by examining the agroecological (biophysical) profile, detailing climatic, edaphological and hydrological qualities. Next, the main socioeconomic features: demography, culture, and organizational and economic institutions are summarized, followed by a characterization of the main farming and cropping systems and associated management. The paper concludes by offering an outlook on targeted activities, interventions and strategies for cropping and farming systems to cope and adapt to climate change and variability, as well as soil fertility challenges within the current socio-ecological context.

Adapting the CROPGRO model for saline soils: the case for a common bean crop

Water scarcity and severe environmental degradation are causing water managers in the Fergana Valley, Uzbekistan to re-evaluate irrigation water use. Crop models could play an important role in helping farmers decide which systems (crops and irrigation technologies) are feasible. CROPGRO is a physiologically robust agronomic model, although the current version does not consider the effects of soil salinity on crop water use or growth. CROPGRO was modified to include a salinity response function and was tested for gypsiferous soils. A qualitative analysis of the model indicated the model performed as expected under a range of atmospheric, irrigation and crop tolerance scenarios. Model simulations compared very favourably for common bean (Phaseolus vulgaris) to results obtained in the greenhouse for yield and seasonal crop evapotranspiration with values of the Willmott agreement index (i) of 0.98 for both variables evaluated at different levels of salinity and deficit irrigation. Final biomass predictions were less satisfactory, although the modified model performed as well as the original model. The modified model was successfully tested with field data on common bean from an experiment in the Fergana Valley (i of 0.75 for ET and 0.74 for final yield), although the sensitivity of the model to a soil fertility function and relative nodule number made it difficult to assess the model performance.

Uncertainty in future irrigation water demand and risk of crop failure for maize in Europe

While crop models are widely used to assess the change in crop productivity with climate change, their skill in assessing irrigation water demand or the risk of crop failure in large area impact assessments is relatively unknown. The objective of this study is to investigate which aspects of modeling crop water use (reference crop evapotranspiration (ET0), soil water extraction, soil evaporation, soil water balance and root growth) contributes most to the variability in estimates of maize crop water use and the risk of crop failure, and demonstrate the resulting uncertainty in a climate change impact study for Europe. The SIMPLACE crop modeling framework was used to couple the LINTUL5 crop model in factorial combinations of 2–3 different approaches for simulating the 5 aspects of crop water use, resulting in 51 modeling approaches. Using experiments in France and New Zeland, analysis of total sensitivity revealed that ET0 explained the most variability in both irrigated maize water use and rainfed grain yield levels, with soil evaporation also imporatant in the French experiment. In the European impact study, net irrigation requirement differed by 36% between the Penman and Hargreaves ET0 methods in the baseline period. Average EU grain yields were similar between models, but differences approached 1–2 tonnes in parts of France and Southern Europe. EU wide esimates of crop failure in the historical period ranged between 5.4 years for Priestley–Taylor to every 7.9 years for the Penman ET0 methods. While the uncertainty in absolute values between models was significant, estimates of relative changes were similar between models, confirming the utility of crop models in assessing climate change impacts. If ET0 estimates in crop models can be improved, through the use of appropriate methods, uncertainty in irrigation water demand as well as in yield estimates under drought can be reduced.

Response of Maize to Different Nitrogen Application Rates and Tillage Practices Under Two Slope Positions in the Face of Current Climate Variability in the Sudan Savanna of West Africa

An experiment managed by an on-farm researcher was conducted in Sudan Savanna of three West African countries, Ghana (Vea), Benin Republic (Dassari), and Burkina Faso (Dano), in 2012. The experiment evaluated the effects of tillage practices and nitrogen fertilizer regimes on the yield of short-season maize Dorke SR variety for two landscape positions (upslope and footslope). A stripe-split plot design with four replicates at each of the three sites was used. Tillage practices (contour and along-slope ridges) were applied in the main plots, whereas nitrogen treatments (no nitrogen, 0 kg N ha−1; moderate nitrogen, 60 kg N ha−1; and high nitrogen, 120 kg N ha−1) were applied in the subplots of each landscape position. Both potassium and phosphorus fertilizers were applied at optimum rates. Grain yield and growth parameters showed diverse responses to the treatments across sites. The effects of slope position and nitrogen fertilizer regime on grain yield were significant (p < 0.05) across sites; the grain yield at the footslope position was 25% higher than that at the upslope, and the high nitrogen treatment resulted in a 140% increase in grain yield compared to no nitrogen condition. An insignificant (p < 0.05) increase in grain yield was observed for sites with contour tillage compared to sites with along-slope ridges. Leaf area index was not significantly (p < 0.05) affected by the treatments during tasseling across sites, and the values were consistent with increasing nitrogen levels. These results suggest that to optimize maize yield under subhumid conditions, farmers should concentrate maize cultivation in low-lying areas and follow the recommended fertilizer application regimes given current climate variability.

Diverging importance of drought stress for maize and winter wheat in Europe

Understanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984–2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO2 offering no yield benefit in these years.Drivers of crop yield variability require quantification, and historical records can help in improving understanding. Here, Webber et al. report that drought stress will remain a key driver of yield losses in wheat and maize across Europe, and benefits from CO2 will be limited in low-yielding years.

Using reanalysis in crop monitoring and forecasting systems

Weather observations are essential for crop monitoring and forecasting but they are not always available and in some cases they have limited spatial representativeness. Thus, reanalyses represent an alternative source of information to be explored. In this study, we assess the feasibility of reanalysis-based crop monitoring and forecasting by using the system developed and maintained by the European Commission- Joint Research Centre, its gridded daily meteorological observations, the biased-corrected reanalysis AgMERRA and the ERA-Interim reanalysis. We focus on Europe and on two crops, wheat and maize, in the period 1980–2010 under potential and water-limited conditions. In terms of inter-annual yield correlation at the country scale, the reanalysis-driven systems show a very good performance for both wheat and maize (with correlation values higher than 0.6 in almost all EU28 countries) when compared to the observations-driven system. However, significant yield biases affect both crops. All simulations show similar correlations with respect to the FAO reported yield time series. These findings support the integration of reanalyses in current crop monitoring and forecasting systems and point to the emerging opportunities linked to the coming availability of higher-resolution reanalysis updated at near real time.