## 3 Results  
### Deriving Midday Stem Water Potential for Mevo Beitar Vineyard  
Figure 2 shows daily time series of the four vegetation indices alongside the \(\Psi_{\text{stem}}\), while both VI and \(\Psi_{\text{stem}}\) were averaged over the entire vineyard area at Mevo Beitar. In general, all four VIs showed a decreasing trend similar to that of the \(\Psi_{\text{stem}}\) consequential to soil water depletion and increasing atmospheric demand for evapotranspiration. The inherent soil-background reduction capacity of SAVI is well noted in Figure 2, displaying the lowest values in comparison to the other three VIs (GNDVI, NDVI and EVI). Low VIs values in DOYs 30-50 (Pre stage) are related mainly to soil background and dry understory vegetation. Peak VI at POS is from the fully developed canopies of the vines at this time of the season, at the start of the irrigation. **MB-Reg** was significant for all four VIs (\(p\) < 0.01), with \(r\) = 0.80-0.82 (Figure 3). High VI values were generally associated with less negative \(\Psi_{\text{stem}}\) at the time when DI started, while low VI values were associated with more negative \(\Psi_{\text{stem}}\), reflecting the water stress condition of the vines towards EOS (DOY 245). Table 2 summarizes the statistics of **MB-Mult** for the four VIs. Here, again, SAVI showed a better performance than the other three indices, likely due to its higher capacity in reducing soil background effects. GNDVI, NDVI and EVI show quite similar \(r\) scores, with NDVI showing a slightly better performance than GNDVI and EVI (Table 2). The highest \(r\) scores were mostly obtained from DOY 189 towards EOS (DOY 245), although with a generally higher RMSE as well. With the exception of one week (DOY 168), models were generally statistically significant along the season with an average \(r\) score > 0.64 (Table 2). It should be noted, though, that the week corresponding to DOY 168 was particularly cloudy, which likely affected Planet-derived VI and consequently the **MB-Mult** models in this particular week. Figure 3: The correlation between the time series of VI avg and the measured \(\Psi_{\text{stem}}\) in Mevo Beitar vineyard. Regressions presented are for the four VIs: (**a**) GNDVI, (**b**) NDVI, (**c**) EVI and (**d**) SAVI. Shaded band indicates 99% confidence intervals for the regression line. Figure 4 shows high-resolution maps of \(\Psi_{\rm stem}\) in Mevo Beitar vineyard from **MB-Mult** using SAVI for selected dates. The spatial pattern of \(\Psi_{\rm stem}\) varies throughout the growing season (Figure 4). \(\Psi_{\rm stem}\) in DOY 154 was relatively high across the vineyard compared to other dates because of the DI start in DOY 131 (Figure 2) and the relatively lower atmospheric demand compared to the following weeks. Figure 5 shows the difference (\(\Delta\Psi\)) between the \(\Psi_{\rm stem}\) derived from **MB-Reg** and **MB-Mult** (both using SAVI). \(\Delta\Psi\) in Figure 5 was calculated as the absolute \(\Psi_{\rm stem}\) value from **MB-Reg** minus the absolute \(\Psi_{\rm stem}\) value from **MB-Mult**. Thus, blue colors indicate lower values of \(\Psi_{\rm stem}\) (more stressed) in **MB-Reg** than in **MB-Mult**, while red colors mean that \(\Psi_{\rm stem}\) was higher (less stressed) in **MB-Reg** than in **MB-Mult**. Most of the maps in Figure 5 show a uniform distribution of \(\Delta\Psi\) across the vineyard, which means that **MB-Reg** was able to reproduce the spatial variability in \(\Psi_{\rm stem}\) close to that predicted by **MB-Mult**, though with some differences in magnitude. Yet, at both ends of the growing season, before and after the DI start (DOY 126 and 245), \(\Delta\Psi\) across the vineyard shows a significant spatial variability. These results indicate that the measures from both models are consistent with one another for much of the season.