## 4 Results
### Monitoring and Assessing the 2009 Drought in Victoria
Regarding crop land, GPP and SIF exhibit similar results (high levels of confidence and low RMSE) to those generated for general Victoria region. It is interpreted that both GPP and SIF variations can be explained by meteorology anomalies in crop land. aT and aW indicated by APARNDVI and APAREFVI are significant (p < 0.1) in crop land. In contrast, none of the coefficients for APARNDVI and APAREFVI are significant for evergreen broadleaf forest land. Thus, APARNDVI and APAREFVI anomalies cannot be estimated by meteorology anomalies in evergreen broadleaf forest land. For evergreen broadleaf forest land, the coefficients aT and aM indicated by SIF are not significant. aW and aP generated by SIF are more significant than those indicated by APARNDVI and APAREFVI. This result indicates that SIF can be explained by water availability and PAR to some degree in evergreen broadleaf forest land. To further explore the consistency of GPP and vegetation proxies under drought conditions, we compared the correlations between the normalized GPP anomaly and the normalized anomalies of vegetation proxies for general Victoria and different land types (Figure 7). It is shown by Figure 7 that strong correlations between the normalized SIF anomaly and the normalized GPP anomaly can be found for general Victoria, crop land area and evergreen broadleaf forest land area. Compared with SIF anomaly, APARNDVI and APAREFVI anomalies not only show worse correlations to GPP anomaly, but also exhibit lower slopes of regressions to GPP anomaly. These results indicate that SIF anomaly is more sensitive to changes in GPP anomaly than are APARNDVI and APAREFVI. In general, anomalies of vegetation proxies exhibit stronger correlation with GPP anomaly in crop land than in evergreen broadleaf forest land. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Vegetation**} & \multicolumn{6}{c}{**Parameters of the ARx Model for General Victoria Region**} \\ \cline{2-9}  & \(\mathbf{a^{T}}\) & \(\mathbf{a^{W}}\) & \(\mathbf{a^{P}}\) & \(\mathbf{a^{M}}\) & \(\mathbf{R^{2}}\) & RMSE & \(\boldsymbol{p}\) Value \\ \hline GPP & \(\mathbf{-0.24\ ***}\) & \(\mathbf{0.29\ ***}\) & \(\mathbf{-0.25\ ***}\) & \(\mathbf{0.23\ ***}\) & \(0.75\) & \(0.51\) & \(0.00\) \\ SIF & \(\mathbf{-0.22\ **}\) & \(\mathbf{0.28\ ***}\) & \(\mathbf{-0.25\ *}\) & \(\mathbf{0.24\ *}\) & \(0.72\) & \(0.35\) & \(0.00\) \\ APARNDVI & \(\mathbf{-0.16\ *}\) & \(\mathbf{0.26\ *}\) & \(\mathbf{-0.13\ *}\) & \(\mathbf{0.16\ *}\) & \(0.29\) & \(0.78\) & \(0.01\) \\ APAREFVI & \(\mathbf{-0.11\ *}\) & \(\mathbf{0.24\ *}\) & \(\mathbf{-0.08\ *}\) & \(0.11\) & \(0.20\) & \(0.83\) & \(0.21\) \\ \hline \multirow{2}{*}{**Vegetation variables**} & \multicolumn{6}{c}{**Parameters of the ARx Model for Crop Land in Victoria**} \\ \cline{2-9}  & \(\mathbf{a^{T}}\) & \(\mathbf{a^{W}}\) & \(\mathbf{a^{P}}\) & \(\mathbf{a^{M}}\) & \(\mathbf{R^{2}}\) & RMSE & \(\boldsymbol{p}\) Value \\ \hline GPP & \(\mathbf{-0.19\ ***}\) & \(\mathbf{0.32\ ***}\) & \(\mathbf{-0.26\ ***}\) & \(\mathbf{0.27\ ***}\) & \(0.77\) & \(0.48\) & \(0.00\) \\ SIF & \(\mathbf{-0.17\ ***}\) & \(\mathbf{0.32\ ***}\)  
vegetation productivity losses in southeastern Victoria, where evergreen broadleaf forest consists of the main land cover type. For evergreen broadleaf forest ecosystems, canopy changes are minor and GPP anomalies mainly come from the \(\epsilon_{\text{P}}\) limitations on the photosynthetic activities during drought conditions [11]. However, canopy changes are dominant for non-forest ecosystems under drought stress [11; 53]. Previous studies have shown that the leaf area index (LAI) has a good correlation with GPP under drought conditions in non-forest ecosystems [11; 53]. Thus, VIs related to the properties of vegetation canopy and leaf greenness can better reflect the vegetation productivity anomalies of crops than those of evergreen broadleaf forest [54]. The ARx model provides an indication of the short-term impacts of meteorology anomalies on vegetation productivity, including memory effects.