## 2 Materials and Methods
### Soil Moisture Modeling  
To demonstrate how satellite information can be integrated in soil moisture modelling, simulations using MOHID land were developed, assuming no irrigation takes place. This assumption was needed as detailed information about irrigation applications were not available (only bulk water use by month). MOHID Land is part of the modelling system MOHID ([[http://www.mohid.com](http://www.mohid.com)]([http://www.mohid.com](http://www.mohid.com)) accessed on 20 February 2022) [56] and is a physically-based, spatially-distributed, continuous, and variable in time model used to estimate water cycle fluxes in watersheds. Porous media, and all related soil and aquifer physical characteristics can be integrated in a MOHID Land implementation. MOHID Land can also couple vegetation, atmosphere, and runoff processes in the overall model structure. MOHID Land runoff module calculates overland surface runoff over a grid as a function of the water column slopes between adjacent cells, described by the dynamic wave equation [57]. The Manning coefficient and the terrain's elevation are necessary data for Runoff input (Table 1). MOHID Land is a model that allows for a very small timestep for detailed modelled results. In fact, water moisture is a property that is characterised by a high variability in time due to the water balance resulting from the precipitation (rainfall) input and evaporation output. For this property, a small timestep is required for a more detailed characterisation of the water moisture behaviour during the modelled period. Although the water deficit component uses monthly aggregate precipitation datasets as input, for a MOHID Land implementation daily or hourly rainfall values are recommended. With this in mind, the GPM version 6 rainfall was used as a 30-min time series. Furthermore, the reference evapotranspiration was used as a monthly average dataset (mm per day). Because reference evapotranspiration has a lower monthly variability than rainfall, no further data time interpolation was performed for this property. The porous media module calculates water fluxes in the soil medium, including water transport due to the balance between pressure (gravity and suction) and resistance through the medium, infiltration, evaporation, and the groundwater boundary water balances [58; 59]. Therefore, the module requires physical properties of modelled soil. In MOHID Land, the equation that describes the flow through soil is the Buckingham-Darcy equation [60; 61]. For the soil moisture estimates, and in the absence of observed data, as an example, the modelling focused on site b only. The soil geometry was characterised by a constant depth of 2 m across the grid, divided between 5 layers with variable depths (Figure 2). Typically, as illustrated below, the upper soil was characterised with thinner layers and the lower soil with thicker layers. Layers can then be aggregated into soil horizons with different physical properties. The MOHID Land implementation described here, however, assumes a constant soil type for all grid cells and all layers across the soil profile. In the absence of detailed soil data, the soil here was characterised as a loam soil. Initial water moisture was set to field capacity for each layer, which, for the current implementation,meant a water content from the top layer to the bottom layer of 0.29, 0.19, 0.17, 0.16, and 0.16 m\({}^{3}\) of water per m\({}^{3}\) of soil. Initial water moisture was constant for every cell across the grid. Considering that the first layer has a high variability, due to the fast reaction to precipitation, lower depths have lower variability and slower changes. The 2D results of the simulations are presented for the 3 rd layer because tilt balances both distinct behaviours.