The dehesa, the most widespread agroforest ecosystem in Europe (≈ 3 million ha), is recognized as an example of
sustainable land use and for its importance in rural economy. It is characterized by widely-spaced oak trees (mostly
Quercus Ilex L.), combined with crops, pasture and shrubs in the sub-canopy region. The estimation of the ecosystem
evapotranspiration (ET) using remote sensing may assist the monitoring of its state from local to regional scales,
improving the management and the conservation of the ecosystem. Thermal-based energy balance techniques which
distinguish soil/substrate and vegetation contributions to the radiative temperature and radiation/turbulent fluxes have
proven to be reliable in the estimation of the energy surface fluxes, and therefore in the estimation of ET. In particular,
the two-source energy balance (TSEB) model of Norman et al. and Kustas and Norman has shown to be robust for
semi-arid sparse canopy-cover landscapes. With the objective of evaluating the model over this environment, an energy
flux measurement system has been used. It was installed in a dehesa located in Southern Spain (38°12′ N; 4°17′ W, 736m a.s.l) with 1 km homogeneous fetch in wind direction. The quality of the measured data fluxes has been tested with the energy-balance closure criterion yielding an average closure of 86% which is within the error range found in similar studies. The TSEB model was evaluated in the area for 2012 summer season, using images from MODIS (Moderate
Resolution Imaging Spectroradiometer) sensor and ground measured meteorological data. The half-hourly estimates
were compared with the flux tower measurements, obtaining a RMSD between modeled and measured energy fluxes
within the closure balance error.
A two-source energy balance model that separates surface fluxes of the soil and canopy was applied to a drip-irrigated
vineyard in central Spain, using a series of nine Landsat-5 images acquired during the summer of 2007. The model
partitions the available energy, using surface radiometric temperatures to constrain the sensible heat flux, and computing ET as a residual of the energy balance. Flux estimations from the model are compared with half-hourly and daily values obtained by an eddy covariance flux tower installed on the site during the experiment. The performance of the twosource model to estimate ET under the low vegetation cover and semiarid conditions of the experiment, with RMSD between observed and model data equal to 49 W m-2 for half-hourly estimations and RMSD=0.5 mm day-1 at daily scale, is regarded as acceptable for irrigation management purposes. Model results in the separation of the beneficial (transpiration) and non-beneficial (evaporation from the soil) fractions, which is key information for the quest to improve water productivity, are also reported. However, the lack of measures of these components makes it difficult to draw conclusions about the final use of the water.
Evapotranspiration (ET) is a critical variable in hydrological processes and an accurate estimation of the rate of
evapotranspiration is required if we wish to apply integrated management procedures to water resources. This study
offers new insights into remote sensing-based models that estimate ET at basin scale, evaluating the combination of a
surface energy balance based on thermal remote sensing and the use of the crop coefficient (Kc), a simple operational method that is widely used in irrigated agriculture. The study area is the Guadalfeo river basin in southern Spain, a large watershed with major topographical and landscape contrasts. Reference evapotranspiration (ETo) surfaces were generated by applying the FAO56-PM [1] equation, and real ET surfaces were estimated following a two-source energy balance model [2] [3]. Crop and vegetation coefficients were obtained as the ratio between ET and ETo. Kc maps were analysed in terms of vegetation type and development. The resulting coefficients generally ranged between 0.1 and 1.5, and could be directly related to vegetation ground cover for the main vegetation types, including natural vegetation and crops, with the determination coefficient (r2) lying between 0.77 and 0.97 in both humid and dry seasons. Relationships based on these coefficients are proposed as a simple proxy to monitor the water use of the basin on a regular basis by means of optical remote sensors alone, providing data with higher frequency and spatial resolution than can be obtained by thermal measurements; data that could complement thermal sensors whenever these were available.
The integrated water resource management required to face the water scarcity situation in semiarid regions relies on the
ability to obtain accurate information about the use of water by crops and natural vegetation. Thermal remote sensing
provides key data about the vegetation water status. The integration of this remotely sensed data into water and energy
balance models help to better estimate evapotranspiration under heterogeneous cropping and natural vegetation patterns,
extending the field of application of these models from point to basin and regional scales.
In this work, we present an approach to estimate spatially distributed surface energy fluxes using a series of Landsat TM
satellite images combined with simulation modeling and ground-based measurements. A physically-based method for the
energy budget partitioning following the Two Source Model [1, 2] has been applied over an heterogeneous agricultural
area located in southern Spain. The study was performed during 2009 crop growing season and the results were validated
with field data collected with an eddy covariance system installed over a corn field during the season. The instantaneous
and daily estimations were compared to the measured data, obtaining a general good adjustment at both scales and
setting the basis for a larger scale application that may assist a decision - making tool for water resources planning in the
region.
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