## 3 Results
### Soil Moisture Estimation  
The spatial distribution of the soil moisture, represented as the relative water content, in the 3 rd modelled layer of the soil, i.e., at 25 cm of soil depth, is highlighted in Figure 8. Each image is a snapshot of the layer's relative water content for the last time increment of \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & \multicolumn{4}{c}{**CMRSET**} & \multicolumn{2}{c}{**ETLook**} \\ \hline
**Month** & **Rain** & **Use** & **Demand** & **Deficit** & **Demand** & **Deficit** \\ \hline July 2017 & 182 & 10 & 261 & 79 & 197 & 15 \\ August 2017 & 248 & 8 & 302 & 53 & 272 & 24 \\ September 2017 & 31 & 37 & 624 & 593 & 591 & 560 \\ October 2017 & 828 & 372 & 520 & \(-\)308 & 299 & \(-\)529 \\ November 2017 & 731 & 212 & 621 & \(-\)111 & 292 & \(-\)439 \\ December 2017 & 399 & 620 & 906 & 507 & 380 & \(-\)18 \\ January 2018 & 456 & 1278 & 942 & 486 & 554 & 98 \\ February 2018 & 435 & 721 & 771 & 336 & 785 & 350 \\ March 2018 & 457 & 71 & 725 & 268 & 385 & \(-\)72 \\ April 2018 & 210 & 18 & 562 & 353 & 215 & 5 \\ May 2018 & 128 & 75 & 293 & 164 & 58 & \(-\)70 \\ June 2018 & 34 & 22 & 162 & 128 & 22 & \(-\)12 \\ \hline Total & 4139 & 3444 & 6687 & 2548 & 4052 & \(-\)87 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Water balance (m\({}^{3}\) ha\({}^{-1}\)) for study sites **a** based on CMRSET and ETLook estimates of AET (Demand). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & \multicolumn{4}{c}{**CMRSET**} & \multicolumn{2}{c}{**ETLook**} \\ \hline
**Month** & **Rain** & **Use** & **Demand** & **Deficit** & **Demand** & **Deficit** \\ \hline July 2017 & 189 & 24 & 258 & 68 & 87 & \(-\)103 \\ August 2017 & 246 & 20 & 285 & 39 & 199 & \(-\)47 \\ September 2017 & 34 & 87 & 606 & 572 & 357 & 323 \\ October 2017 & 839 & 873 & 532 & \(-\)307 & 195 & \(-\)644 \\ November 2017 & 745 & 497 & 655 & \(-\)89 & 198 & \(-\)547 \\ December 2017 & 4 each simulated month. The relative water content scales the actual soil moisture between 0 (very dry) and 1 (saturated). October 2017 indicated the highest spatial variability in soil moisture (Figure 8). This is most likely due to the high rainfall in October (Tables 2 and 3) combined with the spatial variation in the predicted evapotranspiration. This is not as visible in Figures 5 and 6 as the AET in those figures is the cumulative monthly AET, while in the soil moisture we observed a snapshot of the storage at the end of the month. The high rainfall for the month explains the overall higher water content across the domain's grid. September and December 2017 had an overall lower soil moisture across the grid following lower rainfall during August and September (Tables 2 and 3), while the relative soil water content in December 2017 can be associated with the higher rate of evapotranspiration during that month. For an even more local analysis and a detailed time series view, three grid cells with different crop coefficient values are highlighted (Figure 9). The time series of the simulated relative water content at 25 cm depth for the selected study points is highlighted in Figure 10, combined with the precipitation (rainfall) time series. This matches the common scale used to observe crop water productivity [4, 31]. However, in this case the results are based on a landscape level gridded model, rather than a point scale model, which ignores any lateral flow effects. Figure 10 shows a detailed view of the relative water content increases and decreases as a response to wet and dry periods. The declines in relative water content followed typical exponential declines related to the soil water-retention characteristics in MOHID Land. Figure 7: Top: image time series of the water surface in the reservoir at site **b**. Bottom: mean modeled reservoir volume time series (dashed line) in study site b and associated uncertainties (grey shading for 68% confidence interval). The top figure indicates time snapshots of the satellite data showing the different surface water coverages in the reservoir.