## 3 Results  
### GPP, Spectral Indices, and SM During the Study Period  
Figure 3a shows tower-based GPP and SM at different depths for the study period in ASM. Wet pulses during late spring and summer periods were considered, given that rainfall generally occurs in these seasons (Figure 3b). Different hydrological conditions were covered, similar to those expected for the study area according to the last 20 years series--extremely wet (2016-2017, 2020-2021), normal (2017-2018, 2019-2020), moderately dry (2018-2019) periods. The summer of 2018-2019, when no wet pulses were observed, was included as a dry season to evaluate contrasting hydrological conditions. During both of the wettest periods, significant increases in SM at 60 and 100 cm depths were observed; values around 0.5 m\({}^{3}\)/m\({}^{3}\) in deep horizons are mainly due to the existence of a hardpan that favors a high degree of saturation in the soil during extreme events [33]. In the Ti Tree site, data were more limited, but a lower increase in SM in the soil profile is evident (Figure 10a) with similar rainfall amounts (Figure 10b), which can be mainly explained by the absence of a hardpan.  
Figure 3: _Cont._In general, increases in GPP are strongly related to the magnitude of wet pulses. Rainfall events (around 100-150 mm/week, according to [33]) that recharge SM in deep horizons produce significant increases in vegetation productivity (with maximum GPP values around 5 gC/m\({}^{2}\)/day). Lags between 18 and 49 days in maximum GPP in relation to peaks in subsurface SM (Figure 3a,d) were observed in ASM. Lags in the Ti Tree station were between 11 and 34 days (Figure A1a).  
Figure 3c shows the general behavior of spectral indices for the study period in ASM. It should be noted that the first wet pulse (2016-2017) was not considered because AHI Himawari 8 series was available from mid-2017. The LSWI obtained negative values, consistent with spectral signatures for semi-arid areas that frequently present non-full cover and higher values in SWIR than in NIR bands [24, 48]. The general rise in spectral indices is associated with increases in deep SM, with maximum LSWI values associated with the magnitude of wet pulses (Figure 3d). These results are consistent with previous studies carried out in other regions considering the NDVI, the LSWI, rainfall, and drought events [49, 50], although studies analyzing SM frequently focus only on SSM (e.g., [51, 52]). Low or intermediate pulses (about 0.1-0.2 m\({}^{3}\)/m\({}^{3}\)), only observed in SSM, did not produce significant increases in spectral indices (e.g., January-March 2018, September-October 2020) (Figure 3c). A comparable pattern was observed in GPP (Figure 3a), given that GPP in the  
Figure 3: Study periods, data from the ASM OzFlux station. (**a**) Daily SM at different depths and GPP; (**b**) rainfall; (**c**) in situ SM, EVI, and LSWI values from the AHI; (**d**) maximum GPP and LSWI values in function of magnitude of wet pulses expressed as m\({}^{3}\)/m\({}^{3}\). Vertical lines show the 5 analyzed wet pulses during late spring and summer: 2016–2017 and 2020–2021, the wettest seasons, and 2018–2019, the driest season.  
Mulga woodland is highly correlated with the EVI [53; 54]. Similar results were observed in the Ti Tree site, with the seasons with maximum values of the indices and GPP being associated with significant wet pulses (Figure 1c,d).