2. Methods
2.1 Study areas
The research took place in two forested semiarid areas (Figure 1). The
Caatinga experimental area is located inside the Aiuaba Ecological
Station (ESEC, 117 km²), a Federal preservation area located in the
Brazilian Northeast. This space has been fully preserved since 1978 and
monitored since 2003 by the Semiarid Hydro-Sedimentological Research
Group (http://www.hidrosed.ufc.br/index.php).
The Caatinga experimental area is part of the Jaguaribe River basin.
According to the Köppen classification, the local climate is Bsh (hot
semiarid) with potential annual evaporation of 2,500 mm, average annual
precipitation of 549 mm, and average annual temperature of 26 ºC
(Pinheiro et al., 2016). The rainy season is concentrated from January
to April. The predominant lithology is the crystalline complex of
metasedimentary formation.
Soils in the region
are generally shallow and originated from a crystalline substrate. The
predominant soil types are Luvisols, Latosols, and Argisols (de Araújo
& Piedra, 2009; Farias, Medeiros, Navarro-Hevia, & de Araújo, 2019).
The Pinares forest (106 km2) is located in Tierra de
Pinares, in the province of Valladolid, Spanish Northern Plateau. Local
vegetation there is formed mainly by stone pine (Pinus pinea L),
but the maritime pine (Pinus pinaster ) and holm oak
(Quercus ilex ) can also be found (Bello, 2004). The soil is deep
and sedimentary, with a sandy texture (more than 90% sand) and low
water-holding capacity (Calama et al., 2019). Pinares forest has a
continental Mediterranean climate which, according to the Köppen
classification, is Bsk (cold semiarid). The annual rainfall is 400 mm,
the annual mean temperature 11 °C (Moreno-Fernández, Montes,
Sánchez-González, Gordo, & Cañellas, 2018) and the potential annual
evapotranspiration 1,100 mm (Vicente-Serrano et al., 2014). In the area,
the confluence of the rivers Pisuerga and Duero takes place.
2.2 Satellite Imagery and Meteorological data
Actual evapotranspiration was estimated for the two experimental areas
by using the imagery of Landsat 5 and Landsat 8. Landsat 5 captured
images from March 1984 to January 2012 on six 30-m visible bands and a
120-m thermal band. Landsat 8 was launched in February 2013 and is still
operating. Landsat 8 OLI images have eight 30-m bands, two 100-m thermal
bands and a 15-m panchromatic band. In this study, all the available
cloudless images between 1995 and 2019 were used (Figure 2): 37 images
of the Caatinga forest and 74 of the Pinares forest, totalling 111
images. The imaging time was 12:00 UTC (path 217 and row 65) for
Caatinga, and 11:00 UTC (path 202 and row 31) for Pinares.
The Caatinga forest usually is excessively cloudy during the rainy
season, so that practically no image was cloudless. During the rainy
months, were used images with up to 10% cloud coverage, but the
specific areas covered by clouds were disregarded.
Shuttle Radar Topography Mission (SRTM) images were employed to generate
the Digital Elevation Model (DEM). Both Landsat and SRTM data were
provided by the United States Geological Survey (USGS)
(https://earthexplorer.usgs.gov/).
Daily and hourly field data of wind speed, temperature, relative
humidity, solar radiation, air pressure and precipitation were obtained
from the National Institute of Meteorology (INMET) and the Ceará
Foundation of Meteorology and Water Resources (FUNCEME) for the
Brazilian forest, and from the State Meteorological Agency (AEMET) for
the Spanish forest. Table 1 shows the stations and periods of available
data.
In the Caatinga forest, meteorological data were obtained from one of
the four stations close to the area, depending on data availability on
the analysis day (Figure 1): the BEA station is located inside the
experimental area and provided 27% of the data; IBAMA, 8%; Campos
Sales, 62%; and Tauá, 3%. In the case of the Pinares forest, data
concerning air temperature, wind speed and relative humidity were used
from the Villanubla station, which is located outside the city of
Valladolid and suffers less influence of urbanization effects. All other
data were provided by the Valladolid station, which is closest to the
area.
2.3 Surface Energy Balance
Algorithm for Land (SEBAL) model
The SEBAL model, applied in this work for having been used with success
in many scientific research, calculates the components of the surface
energy balance (Liaqat & Choi, 2015), so that the ET for each image
pixel can be estimated using Eq. 1 (Bastiaanssen, Menenti, Feddes, &
Holtslag, 1998):