## 2 Materials and Methods  
### Data Collection  
Data for three sites in Portugal, collected over a period of 7 to 10 years, were used for the training. Datasets were retrieved from the stations Estacao Povoa de Atalaia, Estacao Borralheira and Direcao Regional de Agricultura e Pesca do Centro, Portugal. Table 1 shows details of these sites. The soils of Loc. 1 ana Loc. 3 are of light texture (sandy) or more often of medium texture (sandy loam), permeable, with low to medium organic matter content, with low acid to neutral reaction, rich in phosphorus and potassium, and without salt effects. Climatically, these are areas with mild winters, with precipitation falling mostly in autumn and winter and occasionally in the spring. Usually, temperatures increase significantly from May onwards, peaking in July and occasionally in August, with the registration of several days of maximum temperatures above 40 \({}^{\circ}\)C being common. It has also been noted that registered temperatures reach progressively higher values in September, extending the summer period into October. In the Loc. 2, soils are similar, although soils with medium texture (loam) are more common. Climatically, the regions differ mainly in spring and summer with lower temperature values and higher relative humidity. In terms of precipitation, the values are always higher, and the number of days recorded with precipitation is higher. These plots are covered with fruit trees such as pears, nectarines, cherry, and peach trees. Datasets Loc. 1 and Loc. 2 were recorded daily, and the Loc. 3 record was recorded every 15 min. These datasets included minimum, maximum, and average temperature; minimum, maximum, and average relative humidity; average solar radiation; minimum and average wind speed; and precipitation. Table 1 in the Appendix A shows the details of these variables. Figure 1 shows the amount of precipitation at each site, which translates to the soil water content in the surface layer of the soil. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Location** & **Póvoa de Atalaia** & **Borralheira** & **Fadagosa** \\  & **(Loc. 1)** & **(Loc. 2)** & **(Loc. 3)** \\ \hline Longitude & 40\({}^{\circ}\)4’15.43′′ N & 40\({}^{\circ}\)19’14.14′′ N & 40\({}^{\circ}\)17’46.55′′ N \\ Latitude & 7\({}^{\circ}\)24’26.02′′ W & 7\({}^{\circ}\)25’23.67′′ W & 7\({}^{\circ}\)26′36.27′′ W \\ Start date & 19 September 2013 & 19 September 2013 & 16 May 2020 \\ End date & 16 May 2020 & 07 January 2010 & 23 March 2020 \\ Temporal resolution & daily & daily & 15 min \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Details of the locations in the datasets. The ETo calculator is software developed by the Land and Water Division. The ETo calculator estimates ETo from meteorological data using FAO Pemman-Monteith equation [6]. This calculator was used to calculate the daily ETo at these three locations. The amount of soil water content at the end of the day was collected from the ECMWF dataset (ERA5) [24]. ERA5-Land is a reanalysis dataset that provides a consistent view of the evolution of land variables over several decades with improved resolution compared to ERA5. ERA5-Land was created by reproducing the land component of the ECMWF ERA5 climate reanalysis. In particular, ERA5-land runs at a higher resolution (9 km compared to 31 km in ERA5). The reanalysis combines model data with observations from around the world to produce a globally complete and consistent dataset using the laws of physics. The temporal frequency of the output is hourly. ERA5-Land is generated in a single simulation without coupling to the atmospheric module of ECMWF Integrated Forecasting System (IFS) or to the ocean wave model of IFS. It runs without data assimilation, making it computationally affordable for relatively rapid updates. The core of ERA5-Land is the Tiled ECMWF Scheme for Surface Exchanges over Land, which incorporates land surface hydrology (H- TESSEL). It uses the CY45R1 version of the IFS [25].