Assessing the Impact of Rainfall Variability on Maize Yield Potential in Sub-Saharan Africa
Water availability is the most critical factor for sustaining crop productivity in rainfed agriculture. Even if a drought-tolerant trait is introduced, water isn't available to crops when there is no water in the soil. Rainfall variability from season to season greatly affects soil water availability to crops, and thus pose crop production risks. Ideally, crop cultivations should be situated in areas with high rainfall with low variability; however, subsistence farming can be found in a wide range of environmental conditions—from very suitable to marginal lands. Variability in seasonal rainfall (i.e., the accumulated amount of rainfall from the planting to the harvest of a crop) is higher in the areas with smaller amount of rainfall (Figure 1). Overall, about 37% of maize-growing areas in the Sub-Saharan Africa (SSA) region are located in the areas with the coefficient of variation (C.V.) of seasonal rainfall higher than 0.2 (Figure 2).
Simulated Crop Yield Potential
One of the common crop modeling applications is the estimation of potential productivity under the different assumptions of biophysical constraints. To assess the seasonal rainfall variability impact on crop production and its variability, the site-specific yield potential of rainfed maize (with no nitrogen constraint) was simulated at grid-cells (10 km resolution) for 1955-2004.
When aggregated over time, the overall trend showed that more rainfall correlates with higher yield and lower yield variability (Figure 3). However, it was also noted that there is a wide range of yield even from the same amount of seasonal rainfall. For example, about 500 mm of rainfall during the crop growing season yielded about 1.5 t/ha in East Shewa, Ethiopia, whereas it was almost 10 t/ha in Kroonstad, South Africa. This is partly due to the different soil characteristics (e.g., clayey soils hold water more and longer than sandy ones), but mostly the influence of location-specific rainfall patterns throughout the season on a daily basis. That is, how the same 500 mm of rainfall is distributed is an important factor. Different crop growth stages have different sensitivity levels of development to water stress; low availability of water during a critical stage can have a higher impact on yield than others. Hence, to efficiently use water, it is important to understand “when” crop needs water the most.
A simple measure of estimating a crop’s water use efficiency is water productivity, which is the crop yield divided by the amount of water applied (i.e., crop-per-drop). If the crop is highly water-efficient, there would be a positive relationship between water (rainfall, for the rainfed systems) and water productivity. Figure 5 shows the water productivity trend increases when the seasonal rainfall amount is limited (e.g., below 400 mm), suggesting that investment in water management will be relatively more efficient in those areas. However, as discussed in the previous section, the total amount of water input does not always correlate with higher yield due to soil characteristics and rainfall patterns. Intensive rain runs the water off from the field. Figure 5 also shows the slightly decreasing water productivity trend as the seasonal rainfall amount increases.
The location-specific yield potential and variability can be used to compare the suitability of cultivation across the region. By scatter-plotting the yield potential against its variability for each grid-cell of a major maize growing area, Figure 4 provides a quick measure of which maize growing areas are more suitable for rainfed cultivation. Most high rainfall areas (those with a larger circle) have relatively high yield with low variability--and are thus well suited for rainfed cultivation. For the unsuitable areas with high variability of yield, yield potential is almost always low; Figure 6 shows where the marginal areas are located on the map.
Beyond water, crop systems models can assess the impact of multiple biotic/abiotic constraints and management practices on crop growth and yield in a systemic way. For example, Figure 8 shows location-specific changes in the relationship between yield potential and variability under a set of scenarios on crop, cultivar, fertilizer, and irrigation. Starting from the point A, the medium-maturity maize without fertilizer or irrigation yielded about 2t/ha with 0.75 of C.V. in this area. Adding fertilizer (B), irrigation (C), or fertilizer and irrigation (D) can bring various changes to the average yield and variability. Especially of note, the fertilizer and irrigation combination can more than double the average yield with 50% less variability. In addition, as the rainfall is limited, the cultivar can be changed to a shorter maturity (E); a slight increase in yield (from D) with 14% less variability. Similarly, adding fertilizer (F), irrigation (G), or both (H) can change different degrees of impact on yield and variability. Another strategy could be switching to a more drought-tolerant crops, such as sorghum (I). Compared to the same conditions of maize (A and E), sorghum can produce a yield with about 25% lower variability, although the yield level is different. When irrigated (J), sorghum’s yield variability was even lower than any other simulated cases of maize.
Rainfall variability is an important characteristic of climate in SSA that imposes crop production risks, especially on rainfed subsistence cultivation systems on marginal land. The crop systems model can help by providing information to assess the extent of cross-regional risk and potential impact, and better target interventions.