2. 2 Data Sources

The meteorological data that are necessary to drive CLM5 including precipitation, air temperature, atmospheric pressure, wind speed, relative humidity, and incoming solar radiation, were acquired from three meteorological stations located at different altitudes within the PHO (Figure 1) as well as two stations located in the orchards S09 and S10. For the agricultural plain, detailed soil texture and organic matter information was collected during an extensive soil sampling campaign. In total, 116 locations were sampled with one sample from the topsoil (0-50 cm) and a second sample from the subsoil (50-100 cm) (Figure 2). In addition to the point measurements, the LUCAS topsoil physical properties for Europe soil map [Ballabio et al. , 2016] and the European Soil Database (ESDB) derived data product [Hiederer , 2013] provide soil information for the area at a resolution of 500x500 and 1000x1000 m, respectively (Table 2). These data sources were combined to create soil texture (point measurements+LUCAS) and soil organic carbon (point measurements+ESDB) maps for model input (Figure 2). In a first step, for the unsampled regions, data points were extracted from the map products in a sampling density equal to the average density of the soil sampling locations (~580x580 m). Next, the extracted points were combined with the sampled points to a single set of data points (Figure 2). Then, the points were interpolated to the target resolution of 100x100 m using ordinary kriging and a spherical variogram model with a radius that included 30 measurements around an estimation point. Topographic information was available through the European Digital Elevation Model (EU-DEM) [Copernicus , 2016], version 1.1 at a spatial resolution of 25x25 m (Figure 1). Detailed maps of the agricultural fields and orchards were provided by the Hellenic Payment and Control Agency for Guidance and Guarantee Community Aid while the land use of the remaining area was digitized from satellite imagery, using ArcGIS® software by Esri (Figure 1).
Orchard scale SM data were retrieved from S09 and S10, which were equipped for extensive monitoring in September 2020 (Figure 1). SM was monitored via a SoilNet wireless sensor network [Bogena et al. , 2010; Bogena et al. , 2022] with 12 nodes per orchard. Each node had six SMT100 SM sensors (Truebner GmbH, Neustadt, Germany) divided into two separate profiles which were installed at 5, 20, and 50 cm depth as well as two TEROS21 soil matric potential (SMP) sensors (METER Group Inc., Pullman, USA) installed at 20 cm depth. Irrigation amounts were recorded with TW-N flowmeters (TECNIDRO, Genova, Italy), installed at different irrigation sectors within the orchards. Meteorological data was collected by the cost-effective but reliable all-in-one Atmos41 weather station (METER Group Inc., Pullman, USA) installed above the canopy in each orchard [O. Dombrowski et al. , 2021]. A more detailed description of the instrumentation and setup used to monitor SM dynamics, irrigation, and meteorological variables is given inBrogi et al. [2023]. Additionally, S10 was equipped with six SFM-1 sapflow sensors (ICT International Pty Ltd, Armidale, Australia) to estimate whole-tree transpiration. The sapflow sensors were installed on the trunk of six trees to represent, as much as possible, the orchards’ trees in terms of height, perimeter, and vigor covering all five varieties. The installation and data correction followed the procedure outlined in Burgess [2018]. Phenology of the three main apple varieties was monitored using six phenocams (SnapShot Cloud 4G, Dörr GmbH, Germany) installed in S10.
Table 2: Main characteristics of the different soil data products used for the surface file creation of the regional case.