*3.2. Effects of Spatiotemporal Rainfall Variability on Pearl Millet Grain Yield*

The average yields of pearl millet were 360.53 and 637.66 kgDWha−<sup>1</sup> for SES1 and SES2, respectively (Table 3). In both seasons, the spatial intraseasonal yields were significantly different among farmers. Higher variability was observed in SES2 than SES1 (Figure 8), with higher yields also recorded in SES2 than in SES1. The maximum grain yields for individual locations were 912 kgDWha−<sup>1</sup> and 1633 kgDWha−<sup>1</sup> for SES1 and SES2, respectively (Table 4). The rainfall pattern observed in Figure 6 is correlated with the yield pattern in Figure 8, indicating that, for the two seasons, the pearl millet yield was correlated with the recorded amount of seasonal rainfall.


**Table 3.** Standard deviation, mean, CV, and *p*-values for pearl millet yield (kgDWha<sup>−</sup>1).

Note: Statistically significant at 0.05 level is denoted by a star (\*). For each of the 38 rain gauge positions, we collected samples from a minimum of two plots to a maximum of four plots with flat cultivation and with tied ridges cultivation.

From the correlation analysis, we found that rainfall was moderately weakly but positively correlated with yield in terms of both rainfall amount and rainfall events (Figure 9). However, the rainfall events were more correlated with yield than the total seasonal rainfall amounts in both seasons. In low rainfall SES1, the yield was found to have a small but positive correlation with the rainfall events (*r* = 0.37). A moderately low but positively correlated coefficient (*r* = 0.34) was found between the yield and rainfall amount in SES1. In the wetter SES2, the yield was found to have a low but positive correlation to both events (*r* = 0.03) and seasonal rainfall amount (*r* = 0.02), which means that if the rainfall (during crop growth) is well-distributed, a considerable amount of rainfall can be used by the crops to enhance the yields. We observed a yield increase with better rainfall distribution in SES1; however, the trend appeared negligible or nonsignificant in SES2, which is attributed to a more uniform spatiotemporal seasonal rainfall and event distribution than SES1. Although the variability in seasonal rainfall during SES2 was significant, the rainfall amount was enough to meet most of the pearl millet crop water requirement. The crop water requirement was estimated to be approximately 366.2 mm in Dodoma, which is less than most of the recorded seasonal rainfall amounts. The seasonal rainfall amounts and events were moderately weakly but positively correlated with the pearl millet yield (*r* = 0.43 and 0.44, respectively) (Figure 9). The regression lines for combined seasons showed much stronger correlations than individual seasonal correlations. Thus, apart from variability in rainfall amount and timing, factors other than rainfall may contribute to yield variability.

**Figure 8.** Spatial distribution of pearl millet yield (kgDWha<sup>−</sup>1) for (**a**) SES1 and (**b**) SES2.

**Figure 9.** Combined relationships between two seasons of yields (kgDWha<sup>−</sup>1), seasonal rainfall (mm) amounts, and number of events.
