**3.4 Scatter plots and linear regression outputs of the relationship between fertilisers/nutrients and barley yields in Morocco**

The scatter plots depict the linear relationship between barley yield as the dependent variable and fertiliser as the independent variable. In the context of nitrogen fertilisers used in barley cultivation, it can be observed that an R2 of 0.0005 (0.05%) is obtained. This implies that only 0.05% of changes in barley yield can be explained by changes in nitrogen fertiliser application (**Figure 5a**). In terms of phosphate fertilisers used in barley cultivation, it can be observed that an R2 of 0.076 (7.6%) is obtained. This implies that only 7.6% of changes in barley yields can be explained by changes in phosphate fertiliser application (**Figure 5b**). Considering potash fertilisers used in barley cultivation, it can be observed that an R2 of 0.0002 (0.02%) is obtained. This implies that only 0.02% of changes in barley yield can be explained by changes in potash fertiliser application (**Figure 5c**). Phosphate fertilisers outbid the other nutrients as they record the highest R<sup>2</sup> of 7.6% and the lowest p-values of 0.11. Phosphate fertilisers tend to explain more of the changes in barley yield as depicted by the R<sup>2</sup> of 7.6%, a statistic that is much higher than those recorded for nitrogen and potash.

The results from the scatter plots (**Figure 5a, b** and **c**) are consistent with linear regression outputs (**Table 3**). This is observed as phosphate fertilisers tend to record the lowest p-value of 0.11 and the highest t-value of 1.64. This is followed by nitrogen (p-value = 0.63, t-value = �0.48) and lastly potash (p-value = 0.77, t-value = 0.29). Even though nitrogen represents higher levels of application in Moroccan agriculture, when it comes to barley, phosphates tend to explain more of the changes in barley yields. Still, none of these nutrients correlates significantly with barley yields. When the linear relationship between barley yields as the dependent variable and agricultural water withdrawal and fertilisers as the independent variables is considered, it is observed that agricultural water withdrawal records the lower p-value (0.15) and the highest t-value (�1.44) (**Table 4**).
