In Table 3, we list the input maps used in order to run Benfratello's method within a GIS framework, which are monthly precipitation, monthly average, maximum and minimum temperature, field capacity and land-cover, needed to modulate the maximum evapotranspiration demand. In order to obtain these maps, we proceeded as follows. Field capacity maps, for different land-cover scenarios, were obtained by multiplying the map of water content at field capacity by the map of the hydrologically active soil layer. The latter was obtained by assigning a rooted depth to each land-cover class, according to Foxx et al. (1984) and Walker (1989). In the nearby Gargano area, despite the deep rooted depth obtained by the referred literature, we preferred to assign a shallow hydrologically active soil layer according to Ancona et al. (2010) (Figure 5). Monthly precipitation maps were generated from measured precipitation data by means of Thiessen–Voronoi tessellation (see, e.g. Figure 6, top-right map). Monthly temperatures available at the micrometeorological stations were interpolated by a linear function of the elevation in order to provide the temperature maps (see, e.g. Figure 6, top-left map).
Table 3

Summary of the input layers

ContentTypeResolution (m)Ellipsoid and projectionSource
DEM raster 250 WGS84–UTM32N INGV 
 raster 250 WGS84–UTM32N ESDAC 
CLC 1990 vector – ETRS89–LAEA Europe GRP 
CLC 2000 vector – ETRS89–LAEA Europe ISPRA 
CLC 2006 vector – ETRS89–LAEA Europe ISPRA 
CLC 2011 vector – ETRS89–LAEA Europe GRP 
MS vector – Roma40–Gauss Boaga East – 
 raster 250 WGS84–UTM32N – 
 raster 250 WGS 84 UTM 32N – 
 raster 250 WGS84–UTM32N – 
ContentTypeResolution (m)Ellipsoid and projectionSource
DEM raster 250 WGS84–UTM32N INGV 
 raster 250 WGS84–UTM32N ESDAC 
CLC 1990 vector – ETRS89–LAEA Europe GRP 
CLC 2000 vector – ETRS89–LAEA Europe ISPRA 
CLC 2006 vector – ETRS89–LAEA Europe ISPRA 
CLC 2011 vector – ETRS89–LAEA Europe GRP 
MS vector – Roma40–Gauss Boaga East – 
 raster 250 WGS84–UTM32N – 
 raster 250 WGS 84 UTM 32N – 
 raster 250 WGS84–UTM32N – 

Note: DEM, Digital Elevation Model; INGV, Istituto Nazionale di Geofisica e Vulcanologia (http://tinitaly.pi.ingv.it); , Water content at field capacity; ESDAC, European Soil Data Centre (https://esdac.jrc.ec.europa.eu/resource-type/datasets); CLC, Corine Land Cover; GRP, Geoportale Regione Puglia (http://sit.puglia.it); ISPRA, Istituto Superiore per la Protezione e la Ricerca Ambientale (https://www.isprambiente.gov.it/it/attivita/suolo-e-territorio/copertura-del-suolo/corine-land-cover); MS, Meteorological stations location; , average monthly precipitation; , average, maximum and minimum monthly temperature; , Field capacity.

Figure 5

Maps of the land-cover classification and of the resulting field capacity U of the Bonifica della Capitanata district, according to two different databases made available by the Apulia region administrative authority.

Figure 5

Maps of the land-cover classification and of the resulting field capacity U of the Bonifica della Capitanata district, according to two different databases made available by the Apulia region administrative authority.

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Figure 6

Maps of the input layers required to run the simulations. As an example, the month of March, at the very beginning of the dry season in some areas of the district, is reported. From top left to bottom right: average monthly temperature T, cumulated monthly precipitation P and maximum evapotranspiration , flag to identify the dry areas, i.e. the areas where . Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/nh.2023.081.

Figure 6

Maps of the input layers required to run the simulations. As an example, the month of March, at the very beginning of the dry season in some areas of the district, is reported. From top left to bottom right: average monthly temperature T, cumulated monthly precipitation P and maximum evapotranspiration , flag to identify the dry areas, i.e. the areas where . Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/nh.2023.081.

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