*5.2. Biomass, Grain Yield, and Water Use E*ffi*ciency*

The correlation between grain yield, biomass, and water productivity values for two barley genotypes showed that the observed and simulated values are closely co-related, as evidenced by the high R2 values, i.e., 0.91, 0.93, and 0.89 for grain yield, biomass, and water productivity, respectively (Figure 2).

**Figure 2.** *Cont*.

**Figure 2.** Correlation between observed and simulated (**a**) biomass yield; (**b**) grain yield; and (**c**) water productivity compared with 1:1 line.

The correlation between observed and simulated values of biomass yield for two barley genotypes at three locations showed proximity (Figure 3), which indicates the excellent ability of the AquaCrop model to predict biomass yield under different agro-climatic conditions. The results also show that the sensitive barley variety at MED produces the lowest biomass for both irrigation water qualities. Similar trends were observed for grain yield, where the tolerant barley variety performed better than the sensitive variety regardless of the location and the quality of irrigation water.

**Figure 3.** *Cont*.

**Figure 3.** Simulated and observed biomass of (**a**) tolerant and (**b**) sensitive barley genotypes (dots represent observations; simulations are represented by lines).

## *5.3. Canopy Cover (CC)*

The maximum and minimum CC were 85% and 30% in the sub-humid and arid areas, respectively. The salinity induces a 10% reduction in the CC in the sub-humid environment and 5–30% in the dry climate of MED. CC reduction under saline irrigation water is less noticeable in the tolerant variety than the sensitive variety for both salinity levels. However, in the rainfed area of Beja, the growth of both varieties was comparable.

Figure 4 shows a strong correlation between measured and simulated CC values for both varieties of barley (R<sup>2</sup> = 0.91 and R<sup>2</sup> = 0.93). In general, a good match between the observed and the simulated CC was observed in all three locations. However, the model somewhat over-estimated CC in the rainfed environment of Beja and slightly under-estimated it in the other two situations.

**Figure 4.** *Cont*.

**Figure 4.** Simulated and observed canopy cover for (**a**) tolerant and (**b**) sensitive barley varieties.

#### *5.4. E*ff*ects of Soil Salinity*

The maximum soil salinity was in the arid and semi-arid areas irrigated with saline water, respectively. The soil salinisation dynamic depends on the salinity of irrigation water. However, in the rainfed area of Beja, we noted the absence of any salty issue.

Figure 5 shows that the simulated soil salinity trend in the root zone (up to a depth of 0.7 m) corresponds very well with the measured values under different saline water regimes across different environments throughout the growing season. The observed and modeled soil salinity correlated well, with an R2 of 0.96. Figure 5 shows that the model reliably simulated average root zone salinity when the crop is irrigated with low-salinity water (2 dS m<sup>−</sup>1). However, it slightly underestimated soil salinity under higher saline water conditions (13 dS m<sup>−</sup>1), particularly for the late growing season.

**Figure 5.** Simulated and observed soil salinity in the testing-cropping season under different saline water regimes and across different environments.
