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The concept of reference potranspiration is widely used to support water resource management in agriculture and for irrigation scheduling, especially under arid and semi-arid conditions. The Penman-Monteith standardized formulations, as suggested by ASCE and FAO-56 papers, are generally applied for accurate estimations of ETo, at hourly and daily scale. When detailed meteorological information are not available, several alternative and simplified equations, using a limited number of variables, have been proposed (Blaney-Criddle, HargreavesSamani, Turc, Makkinen and Pristley-Taylor). In this paper, scintillometer measurements collected for six month in 2005, on an experimental plot under “reference” conditions, were used to validate different ETo equations at hourly and daily scale. Experimental plot is located in a typical agricultural Mediterranean environment (Sicily, Italy), where olive groves is the dominant crop. As proved by other researches, the comparison confirmed the best agreement between estimated and measured fluxes corresponds to FAO-56 Penman-Monteith standardized equation, that was characterized by both the lowest average error and the minimum bias. However, the analysis also evidenced a quite good performance of Pristley-Taylor equation, that can be considered as a valid alternative to the more sophisticated PenmanMonteith method. The different ETo series, obtained by the considered simplified equations, were then used as input in the FAO-56 water balance model, in order to evaluate, for olive groves, the errors on estimated actual evapotranspiration ET. To this aim soil and crop model input parameters were settled by considering previous experimental researches already used to calibrate and validate the FAO-56 water balance model on olive groves, for the same study area. Also in this case, assuming as the true values of ET those obtained using the water balance coupled with Penman- Monteith ETo input values, the Priestley-Taylor equation, requiring a limited number of input meteorological data, was characterized by the best performance if compared to the other equations used to evaluate ETo. Under environments conditions similar to those considered therefore, according to the good performance associated to the Priestley-Tailor approach, FAO-56 model can allow realistic estimation of ET, even in absence of a full meteorological dataset.

L’uso razionale della risorsa idrica in agricoltura richiede, unitamente all’adozione di tecniche irrigue avanzate che assicurino la migliore efficienza degli interventi irrigui, l’individuazione dei tempi e dell’entità dei singoli interventi. Perché questi ultimi obiettivi siano raggiunti è necessario stimare con precisione i consumi di evapotraspirazione delle colture che, nell’ambiente mediterraneo, caratterizzato da un periodo vegetativo tipicamente non in fase con quello piovoso, si manifestano sotto condizioni di stress idrico. Nel presente lavoro è descritta un’applicazione a una piantagione di oliveto della tecnica scintillometrica, che permette una stima indiretta del flusso di calore latente attraverso l’equazione del bilancio energetico. Più in particolare, lo scintillometro è uno strumento ottico, che misura il flusso di calore sensibile dal sistema suolo-pianta sulla base degli effetti che tale flusso induce sull’indice di rifrazione della luce coerente emessa da un trasmettitore; misurando contemporaneamente la radiazione netta e il flusso di calore nel suolo, è possibile dedurre il flusso di evapotraspirazione come termine residuo dell’equazione che esprime il bilancio energetico di superficie. Sono in particolare presentati i risultati di un’indagine sperimentale effettuata nel corso della stagione irrigua 2007 nell’area di Castelvetrano, tipicamente vocata alla coltura dell’olivo. I dati di evapotraspirazione giornaliera ottenuti mediante la tecnica scintillometrica sono stati quindi confrontati con i corrispondenti valori stimati utilizzando il modello Agroidrologico SWAP, la cui applicazione ha richiesto una approfondita caratterizzazione biofisica dell’area di studio. I dati di evapotraspirazione giornaliera ottenuti mediante la tecnica scintillometrica sono stati confrontati con i corrispondenti valori stimati utilizzando sia il modello agroidrologico SWAP che la procedura semplificata proposta di recente dalla FAO che prevede l’adozione di un coefficiente colturale Kc,r che tiene conto delle eventuali condizioni di stress idrico.

Actual evapotranspiration from typical Mediterranean crops has been assessed in a Sicilian study area by using surface energy balance (SEB) and soil-water balance models. Both modelling approaches use remotely sensed data to estimate evapotranspiration fluxes in a spatially distributed way. The first approach exploits visible (VIS), near-infrared (NIR) and thermal (TIR) observations to solve the surface energy balance equation whereas the soil-water balance model uses only VIS-NIR data to detect the spatial variability of crop parameters. Considering that the study area is characterized by typical spatially sparse Mediterranean vegetation, i.e. olive, citrus and vineyards, alternating bare soil and canopy, we focused the attention on the main conceptual differences between one-source and two-sources energy balance models. Two different models have been tested: the widely used one-source SEBAL model, where soil and vegetation are considered as the sole source (mostly appropriate in the case of uniform vegetation coverage) and the two-sources TSEB model, where soil and vegetation components of the surface energy balance are treated separately. Actual evapotranspiration estimates by means of the two surface energy balance models have been compared vs. the outputs of the agro-hydrological SWAP model, which was applied in a spatially distributed way to simulate one-dimensional water flow in the soil-plant-atmosphere continuum. Remote sensing data in the VIS and NIR spectral ranges have been used to infer spatially distributed vegetation parameters needed to set up the upper boundary condition of SWAP. Actual evapotranspiration values obtained from the application of the soil water balance model SWAP have been considered as the reference to be used for energy balance models accuracy assessment. Airborne hyperspectral data acquired during a NERC (Natural Environment Research Council, UK) campaign in 2005 have been used. The results of this investigation seem to prove a slightly better agreement between SWAP and TSEB for some fields of the study area. Further investigations are programmed in order to confirm these indications.

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET) and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (e.g., air temperature, advection) are affecting plant functioning. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. The Atmosphere-Land Exchange Inverse (ALEXI) model is a multi-sensor TIR approach to ET mapping, coupling a two-source (soil + canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map daily fluxes at continental scales and 5 to 10-km resolution using thermal band imagery and insolation estimates from geostationary satellites. A related algorithm (DisALEXI) spatially disaggregates ALEXI fluxes down to finer spatial scales using moderate resolution TIR imagery from polar orbiting satellites. An overview of this modeling approach is presented, along with strategies for fusing information from multiple satellite platforms and wavebands to map daily ET down to resolutions on the order of 10 m. The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the US Geostationary Operational Environmental Satellites, the European Meteosat satellites, the Chinese Fen-yung 2B series, and the Japanese Geostationary Meteorological Satellites. Work is underway to further evaluate multi-scale ALEXI implementations over the US, Europe, Africa and other continents with geostationary satellite coverage.

For open orchard and vineyard canopies containing significant fractions of exposed soil (>50%), typical of Mediterranean agricultural regions, the energy balance of the vegetation elements is strongly influenced by heat exchange with the bare soil/substrate. For these agricultural systems a "two-source" approach, where radiation and turbulent exchange between the soil and canopy elements are explicitly modelled, appears to be the only suitable methodology for reliably assessing energy fluxes. In strongly clumped canopies, the effective wind speed profile inside and below the canopy layer can highly influence the partitioning of energy fluxes between the soil and vegetation components. To assess the impact of in-canopy wind profile on model flux estimates, an analysis of three different formulations is presented, including algorithms from Goudriaan (1977), Massman (1987) and Lalic et al. (2003). The in-canopy wind profile formulations are applied to the thermal-based Two-Source Energy Balance (TSEB) model developed by Norman et al. (1995) and modified by Kustas and Norman (1999). High resolution airborne remote sensing images, collected over an agricultural area located in the western part of Sicily (Italy) comprised primarily of vineyards, olive and citrus orchards, are used to derive all the input parameters need to apply the TSEB. The images were acquired from June to October 2008 and include a relatively wide range of meteorological and soil moisture conditions. A preliminary sensitivity analysis of the three wind profile algorithms highlight the dependence of wind speed just above the soil/substrate to leaf area index and canopy height over the typical canopy properties range of these agricultural area. It is found that differences in wind just above surface among the models is most significant under sparse and medium fractional cover conditions (20–60%). The TSEB model heat flux estimates are compared with micrometeorological measurements from a small aperture scintillometer and an eddy covariance tower collected over an olive orchard characterized by moderate fractional vegetation cover (≈35%) and relatively tall crop height (≈3.5 m). TSEB fluxes for the 7 image acquisition dates generated using both the Massman and Goudriaan in-canopy wind profile formulations give close agreement with measured fluxes, while the Lalic et al. equations yield poor results. The Massman wind profile scheme slightly outperforms that of Goudriaan, but it requires an additional parameter describing the roughness of the underlying vegetative surface. This parameter is not directly obtainable using remote sensing, hence this study suggests that the Goudriaan formulation for landscape applications is most suitable when detailed site-specific information regarding canopy architecture is unavailable.

For open orchard and vineyard canopies containing significant fractions of exposed soil (>50%), typical of Mediterranean agricultural regions, the energy balance of the vegetation elements is strongly influenced by heat exchange with the bare soil/substrate. For these agricultural systems a "two-source" approach, where radiation and turbulent exchange between the soil and canopy elements are explicitly modelled, appears to be the only suitable methodology for reliably assessing energy fluxes. In strongly clumped canopies, the effective wind speed profile inside and below the canopy layer can strongly influence the partitioning of energy fluxes between the soil and vegetation components. To assess the impact of in-canopy wind profile on model flux estimates, an analysis of three different formulations is presented, including algorithms from Goudriaan (1977), Massman (1987) and Lalic et al. (2003). The in-canopy wind profile formulations are applied to the thermal-based two-source energy balance (TSEB) model developed by Norman et al. (1995) and modified by Kustas and Norman (1999). High resolution airborne remote sensing images, collected over an agricultural area located in the western part of Sicily (Italy) comprised primarily of vineyards, olive and citrus orchards, are used to derive all the input parameters needed to apply the TSEB. The images were acquired from June to October 2008 and include a relatively wide range of meteorological and soil moisture conditions. A preliminary sensitivity analysis of the three wind profile algorithms highlights the dependence of wind speed just above the soil/substrate to leaf area index and canopy height over the typical range of canopy properties encountered in these agricultural areas. It is found that differences among the models in wind just above the soil surface are most significant under sparse and medium fractional cover conditions (15–50%). The TSEB model heat flux estimates are compared with micro-meteorological measurements from a small aperture scintillometer and an eddy covariance tower collected over an olive orchard characterized by moderate fractional vegetation cover (≈35%) and relatively tall crop (≈3.5 m). TSEB fluxes for the 7 image acquisition dates generated using both the Massman and Goudriaan in-canopy wind profile formulations give close agreement with measured fluxes, while the Lalic et al. equations yield poor results. The Massman wind profile scheme slightly outperforms that of Goudriaan, but it requires an additional parameter accounting for the roughness sub-layer of the underlying vegetative surface. The analysis also suggests that within-canopy wind profile model discrepancies become important, in terms of impact on modelled sensible heat flux, only for sparse canopies with moderate vegetation coverage.

The statistical inference of the alternation of wet and dry periods in daily rainfall records can be achieved through the modelling of inter-arrival time-series, IT, defined as the succession of times elapsed from a rainy day and the one immediately preceding it. In this paper, under the hypothesis that ITs are independent and identically distributed random variables, a modelling framework based on a generalisation of the commonly adopted Bernoulli process is introduced. Within this framework, the capability of three discrete distributions, belonging to the Hurwitz–Lerch-Zeta family, to reproduce the main statistical features of IT time-series was tested. These distributions namely Lerch-series (Lerch), polylogarithmic- series (Polylog) and logarithmic-series (Log) were selected thanks to their capability to describe some peculiar properties usually observed in IT series derived from daily rainfall records: very high standard deviation and skewness, relatively high frequency associated to the unitary IT, monotonically decreasing frequencies with a slow decay. Both Polylog and Log distributions are special cases of the 3-parameter Lerch distribution with a decreasing number of free parameters (2- and 1-parameter, respectively). The analysis, performed on 55 raingauges located in Sicily (Italy) under a typical Mediterranean climate, suggests that a reliable statistical representation of IT can be attained with the 3-parameter Lerch distribution. Despite the marked seasonality of rainfall in the study area, a simple subdivision of the year into two 6-month periods, roughly corresponding to the dry ‘‘semester’’ (D-sem) and the wet ‘‘semester’’ (W-sem), allows a satisfactory reproduction of IT, as well as of wet spells (WS) and dry spells (DS), separately. It was also noticed that the 2-parameter Polylog distribution could be successfully used to reconstruct the DS frequency distribution only. This result suggests that the additional parameter of the Lerch distribution is required by the inclusion of WS into the analysis. Finally, considering that Polylog outperforms the commonly adopted Log, a noteworthy step forward in DS modelling can be achieved by using Polylog distribution rather than Log one.

A remote sensing-based approach to estimate actual evapotranspiration (ET) was tested in an area covered by olive trees and characterized by Mediterranean climate. The methodology is a modified version of the standard FAO-56 dual crop coefficient procedure, in which the crop potential transpiration, T p, is obtained by directly applying the Penman-Monteith (PM) equation with actual canopy characteristics (i.e., leaf area index, albedo and canopy height) derived from optical remote sensing data. Due to the minimum requirement of in-situ ancillary inputs, the methodology is suitable also for applications on large areas where the use of tabled crop coefficient values become problematic, due to the need of corrections for specific crop parameters, i.e., percentage of ground cover, crop height, phenological cycles, etc. The methodology was applied using seven airborne remote sensing images acquired during spring-autumn 2008. The estimates based on PM approach always outperforms the ones obtained using simple crop coefficient constant values. Additionally, the comparison of simulated daily evapotranspiration and transpiration with the values observed by eddy correlation and sap flow techniques, respectively, shows a substantial agreement during both dry and wet days with an accuracy in the order of 0.5 and 0.3 mm d−1, respectively. The obtained results suggest the capability of the proposed approach to correctly partition evaporation and transpiration components during both the irrigation season and rainy period also under conditions of significant reduction of actual ET from the potential one.

Correct estimation of crop actual transpiration plays a key-role in precision irrigation scheduling, since crop growth and yield are associated to the water passing through the crop. Objective of the work was to assess how the combined use of micro-meteorological techniques (eddy covariance, EC) and physiological measurements (sap flow, SF) allows a better comprehension of the processes involving in the Soil–Plant–Atmosphere continuum. To this aim, an experimental dataset of actual evapotranspiration, plant transpiration, and soil water content measurements was collected in an olive orchard during the midseason phenological period of 2009 and 2010. It was demonstrated that the joint use of EC and SF techniques is effective to evaluate the components of actual evapotranspiration in an olive orchard characterized by sparse vegetation and a significant fraction of exposed bare soil. The availability of simultaneous soil water content measurements allowed to estimate the crop coefficients and to assess a simple crop water stress index, depending on actual transpiration that can be evaluated even in the absence of direct measurements of actual transpiration. The crop coefficients experimentally determined resulted very similar to those previously evaluated; in particular, in the absence of water stress, a seasonal average value of about 0.65 was obtained for the “single” crop coefficient, whereas values of a 0.34 and 0.41 were observed under limited water availability in the root zone. The comparison between the values of crop water stress index evaluated during the investigated periods evidenced systematically lower values (less crop water stress) in the first year compared to the second, according to the general trend of soil waters content in the root zone. Further researches are however necessary to extent the experimental dataset to periods characterized by values of soil evaporation higher than those observed, in order to verify the crop coefficients even under different conditions than those investigated.

Equations based on surface renewal (SR) analysis to estimate the sensible heat flux (H) require as input the mean ramp amplitude and period observed in the ramp‐like pattern of the air temperature measured at high frequency. A SR‐based method to estimate sensible heat flux (HSR‐LST) requiring only low‐frequency measurements of the air temperature, horizontal mean wind speed, and land‐surface temperature as input was derived and tested under unstable conditions over a heterogeneous canopy (olive grove). HSR‐LST assumes that the mean ramp amplitude can be inferred from the difference between land‐surface temperature and mean air temperature through a linear relationship and that the ramp frequency is related to a wind shear scale characteristic of the canopy flow. The land‐surface temperature was retrieved by integrating in situ sensing measures of thermal infrared energy emitted by the surface. The performance of HSR‐LST was analyzed against flux tower measurements collected at two heights (close to and well above the canopy top). Crucial parameters involved in HSR‐LST, which define the above mentioned linear relationship, were explained using the canopy height and the land surface temperature observed at sunrise and sunset. Although the olive grove can behave as either an isothermal or anisothermal surface, HSR‐LST performed close to H measured using the eddy covariance and the Bowen ratio energy balance methods. Root mean square differences between HSR‐LST and measured H were of about 55 W m−2. Thus, by using multitemporal thermal acquisitions, HSR‐LST appears to bypass inconsistency between land surface temperature and the mean aerodynamic temperature. The one‐source bulk transfer formulation for estimating H performed reliable after calibration against the eddy covariance method. After calibration, the latter performed similar to the proposed SR‐LST method. This research was funded by project CGL2012‐37416‐C04‐01 and CGL2015‐65627‐C3‐1‐R (Ministerio de Ciencia y Innovación of Spain), CEI Iberus, 2014 (Proyecto financiado por el Ministerio de Educación en el marco del Programa Campus de Excelencia Internacional of Spain), and Ayuda para estancias en centros extranjeros (Ministerio de Educación, Cultura y Deporte of Spain).

Reference evapotranspiration (ET 0 ) is widely used for irrigation scheduling, to promote an efficient use of water resources for a sustainable agro-ecosystem productivity, as well as to manage water quality and to face other environmental concerns. As suggested by ASCE-EWRI and FAO, standard Penman–Monteith methods are generally applied for an accurate estimation of ET 0 from hourly to daily scale. In absence of detailed meteorological information several simplified equations, using a limited number of variables, have been proposed as alternative. In this paper, the performance of different reference evapotranspiration methods, at hourly (Penman–Monteith, Pristley–Taylor, Makkink and Turc) and daily scale (Penman–Monteith, Blaney and Criddle, Hargreaves, Pristley–Taylor, Makkink and Turc), was evaluated against scintillometer measurements collected during six month in 2005 in an experimental plot maintained under “reference” conditions (alfalfa crop). The daily values of ET 0 obtained with the examined methodologies were then used as input in the FAO-56 agro-hydrological model, in order to evaluate, for an olive grove in a Mediterranean environment, the impact on simulated actual evapotranspiration. The experiment was carried out in South-West Sicily, in an area where olive groves are the major crop. The comparison between estimated and measured fluxes confirmed that FAO-56 Penman–Monteith (PM) standardized equation is characterized by the lowest mean bias error (−0.15 mm d −1 and 0.06 mm d −1 using daily or hourly data, respectively). Additionally, the analysis also highlighted that the Pristley–Taylor equation can be considered a valid alternative for an accurate estimation of ET 0 (mean bias error of 0.35 mm d −1 and 0.43 mm d −1 using daily or hourly data, respectively). The application of the FAO-56 water balance model on the investigated olive grove evidenced that the best estimations of actual evapotranspiration are obtained when the Pristley–Taylor ET 0 data are used as input, confirming that this approach can be considered a valid alternative to the standard Penman–Monteith.

In this work a set of time-series of inter-arrival times of rainfall events, at daily scale, was analysed, with the aim to verify the issue of increasing duration of dry periods. The set consists of 12 time-series recorded at rain gauges in 1926–2005, six of them belong to an Italian Sub-Alpine area (Piedmont) and six to a Mediterranean one (Sicily). In order to overcome the problem related to limited sample size for high values of inter-arrival times, the discrete probability polylog-series distribution was used to fit the empirical data from partial (20 yr) time-series. Moreover, a simple qualitative trend analysis was applied to some high quantiles of inter-arrival times as well as to the average extent of rain clusters. The preliminary analysis seems to confirm the issue of increasing duration of dry periods for both environments, which is limited to the ''cold'' season.

Summary An operational use of the actual evapotranspiration assessed by remote sensing approaches requires the integration of instantaneous fluxes to daily values. This is commonly achieved under the hypotheses of daytime self-preservation of evaporative fraction and negligible daily ground heat flux. The aim of this study is to evaluate the effect of these assumptions on estimate daily evapotranspiration over a full phenological cycle, including phases characterized by significant changes both in net radiation and vegetation cover. To assess the reliability of these hypotheses, the observations made by a flux tower, installed within a homogeneous field of cereal located in the valley part of the Imera Meridionale basin, were analyzed. Additionally, the widely-known SEBAL (Surface Energy Balance Algorithm for Land) model was applied on the same study area by means of four MODIS (MODerate-resolution Imaging Spectroradiometer) images selected across a three-rainfall events period in March–April 2007 with the aim to analyze the consistency of its estimates in an operational study case under different conditions of water availability. The analysis of in situ data highlights errors on 24-h evapotranspiration characterized by an average value of 20% due to daily soil heat flux neglecting; whereas, the hypothesis of evaporative fraction self-preservation causes an average error equal to −16%. Moreover, the analysis of the observations suggests that a compensation effect of the errors related to each hypothesis occurs in most cases (56%), and this makes suitable the approach for practical daily integration purposes. The application of the SEBAL model at basin scale shows a good capability to detect the increase of the actual 24-h evapotranspiration under the tested hypotheses, also in the case of instantaneous evaporative fraction and daily net radiation not derived form in situ observations.

Summary A coupled energy/hydrologic model was applied to simulate the exchange of energy and water in the soil–plant-atmosphere system (SPA). The model, which uses a “two-source” approach to estimate the energy fluxes, and the “force-restore” approach to represent the water balance, was validated by means of evapotranspiration measurements collected via scintillometry and soil moisture measurements collected via time domain reflectometry (TDR) in a Sicilian olive grove. The comparison between measured and estimated fluxes values at an hourly scale showed good agreement. Additional comparisons on a daily timescale confirmed the model’s applicability for quantifying crop water requirements. Also in terms of daily evapotranspiration and soil water content values, the obtained results confirmed the model’s applicability for those practical applications aiming to quantify the crop water requirement. Moreover, further studies should be conducted to test the feasibility of using this model for long term simulations over a broad range of conditions.

Dry spells duration and its extent in space, is a key factor in water resources problems. In order to modelling the empirical distribution of dry spells (DS) frequencies observed in Sicily (i.e. in a typical Mediterranean climate), Agnese et al. (2014) successfully applied the two-parameter polylogarithm-series distribution. Because of the strong seasonality characterising Sicily’s rainfall regime, statistical analysis was separately applied to two data sets, referred to as “dry” and “wet” seasons, respectively. In this work, a similar analysis was carried out for a set of 26 DS time-series recorded in a large area (about 30000 km2), including Piedmont and the Aosta Valley. Area altitude ranges between 100 to almost 5000 m a.s.l., and the Mediterranean sea is at about 20 km distance. Main climate character in the whole area is colder and more humid than that of Sicily, and it varies noticeably within the area itself, likely because of the complex role of geomorphology on rain and snow occurrence. Also, partition between rain and snow is evaluated. A subdivision in homogeneous subareas is found which is related to the main weather types occurring. In this work the focus is on the longer dry spells.

Daily precipitation records exist spanning several decades. A valuable amount of climatic information exists in the time-series of interarrival times (IT), defined as the succession of times (number of days) elapsed from a rainy (or snowy) day to the one immediately preceding it.In a previous work, Agnese et al. (2014) have been successfully tested some probabilistic modelling of rain occurrence on Sicily rainfall data; particularly, the better fitting of IT’s observed frequencies was obtained by 3-parameter Lerch-series distribution. In this work thisdistribution is tested on 70 years of 20 precipitation time-series taken in the North-West Italy, both in the plain and in the mountains, up to the 2000 meters altitude. In such Mediterranean climatetwo markedly different behaviours were observed in the dry semester (April to September) and in the wet one (October to March). A better fit was obtained with that simple subdivision of the year, in comparison with the whole year modelling. However, the NW Italy climate is both more similar to the Central Europe one, and it is deeply influenced by the higher peaks of the Alps. Therefore the seasonality of daily precipitation data is much more complicated. Usually spring and fall are the seasons characterized by the higher precipitations, but the convective vs. frontal events also play a role in the IT distributions. In this work, different subdivisions were compared with the whole year fitting. The whole year Lerch distributions successfully fitted the data in a part of the time series, opening the way to interesting climate applications.

Application of FAO-56 methodology for the assessment of reference evapotranspiration, ET 0 , is challenging in areas of the world with sparse meteorological network stations. For this reason alternative procedures using remotely observed data have been proposed in the literature. In this work, a simplified version of the Makkink approach [J. Inst. Wat. Eng. 11: 277–288, 1957] was tested in a typical Mediterranean environment (Sicily, Italy). The implemented Makkink approach (MAK) uses remotely estimated solar radiation derived from Meteosat Second Generation (MSG) satellite data and in situ observations of air temperature to assess ET 0 at daily time scale. Alternatively, taking advantage of well-defined relationships that exist between seasonality, elevation and air temperature, a deterministic procedure for estimating air temperature inputs used in the MAK approach (named RS) was also tested. This approach allows the assessment of daily ET 0 without the need of auxiliary air temperature ground observations. A comparison between the FAO-56 and MAK approaches was performed for 45 sites in Sicily over the period 2007–2010. Assuming FA0-56 as the benchmark, the average accuracy of the MAK methodology was 0.4 mm d −1 , with a relative error of 12%. Similar to other applications of the same procedure, the MAK approach showed a slightly underestimation of ET 0 high values; however, an average regression slope of 0.96 (and negligible intercept) suggests a satisfactory agreement with the FAO-56 modeled values. Air temperature observations acquired during 2002–2006 were used to calibrate the deterministic relation between air temperature, seasonality (as a function of the DOY) and orography (as a function of elevation). For the period 2007–2010, the RS approach performs similarly to MAK, with an average difference of less than 0.05 mm d −1 . Analysis of monthly, seasonal and yearly ET 0 maps shows a slight decrease in RS performance during June and July; nevertheless, the differences between MAK and RS approaches are negligible at all analyzed temporal scales.

Evapotranspiration estimation by micrometeorological techniques through the assessment of mass and energy exchanges in the soil-plant-atmosphere continuum (SPAC) is a very active research area, involving both well-known and novel measurement techniques. A crucial aspect in validating experimental results is the integration of independent measurements of mass and energy exchanges in the SPAC. To this aim, the development and validation of an integrated approach in major tree crop species, involving different independent techniques, are presented. Eddy covariance estimates of ET fluxes were compared to up-scaled sap flow measurements in olive, orange and grapevine, three important Mediterranean tree crop species with contrasting ecophysiological characteristics and responses to water deficits. These differences can affect directly the degree of coupling of the tree to the environment and, consequently, the degree of correspondence between instantaneous transpirational flux at tree level and the micrometeorological measurement of ET at orchard level. Data were analyzed to verify to what extent, in the three species, transpirational flow at orchard level is regulated by tree conductance, capacitance effects related to tree size or by environmental demand. Hourly observations were helpful in detecting physiological processes of the three species only when data were analyzed taking into consideration their diurnal changes.

Large area estimations of land surface fluxes can be a useful operational tool for up-scaling local measurements and can serve as an upper-boundary condition for higher spatial resolution applications. Given hourly measurements of radiometric surface temperature from a geostationary satellite, it is possible to derive the partitioning of energy fluxes based on the influence of the evapotranspiration process on morning surface temperature rise. In this work, the Atmosphere-Land Exchange Inverse (ALEXI) model and the Dual Temperature Difference (DTD) approach were applied in order to relate the sensible heat flux to time-differential remote observations of surface temperature obtained from Meteosat satellite data. Copyright © 2012 IAHS Press.

Estimation of evapotranspiration (ET) in Sicilian vineyard is an emerging issue since these agricultural systems are more and more converted from rainfed to irrigated conditions, with significant impacts on the management of the scarce water resources of the region. The choice of the most appropriate methodology for assessing water use in these systems is still an issue of debating, due to the complexity of canopy and root systems and for their high spatial fragmentation. In vineyards, quality and quantity of the final product are dependent on the controlled stress conditions to be set trough irrigation. This paper reports an application of the well-known Penman-Monteith approach, applied in a distributed way, using high resolution remote sensing data to map the potential evapotranspiration (ET p ). In 2008 a series of airborne multispectral images were acquired on "Tenute Rapitala", a wine farm located in the northwest of Sicily. Five airborne remote sensing scenes were collected using a SKY ARROW 351 650 TC/TCNS aircraft, at a height of about 1000 m a.g.l.. The acquisitions were performed encompassing a whole phenological period, period between June and September 2008 (approximately every three weeks). The platform had on board a multi-spectral camera with 3 spectral bands at green (G, 530-570 nm), red (R, 650-690 nm) and near infrared (NIR, 767-832 nm) wavelengths, and a thermal camera with a broad band in the range 7.5-13 µm. The nominal pixel resolution was approximately 0.7 m for VIS/NIR acquisitions, and 1.7 m for the thermal-IR data. Field data were acquired simultaneously to airborne acquisitions. These data include spectral reflectances in VIS-NIR-SWIR (shortwave infrared), leaf area index (LAI), soil moisture at different depths (both in row and below plants). Moreover, meteo variables were measured by a standard weather station whereas fluxes were measured by means of an Eddy correlation tower located within the field. The VIS-NIR bands were atmospherically corrected and calibrated in order to calculate albedo, NDVI and LAI, which represented the distributed inputs of the Penman-Monteith algorithm. Moreover a sensitivity analysis has been carried out on input parameters (such as albedo). A sensitivity analysis was carried out to highlight the variability of outputs (such as ET p ) on the accuracy in the parameters assessment obtainable using high spatial resolution airborne images. Scale effects have been also investigated by means of an artificial degradation of images spatial resolution. Finally the relationship between stress factor evaluated as the ratio between actual and reference ET and pre-dawn leaf water potential has been also investigated.

Remotely sensed observations in the visible to the shortwave infrared (VSWIR) and thermal infrared (TIR) regions of the electromagnetic spectrum can be used synergistically to provide valuable products of land surface properties for reliable assessments of carbon and water fluxes. The high spatial, spectral and temporal resolution VSWIR and TIR observations provided by the proposed Hyperspectral - InfraRed (HyspIRI) mission will enable a new era of global agricultural monitoring, critical for addressing growing issues of food insecurity. To enable predictions at fine spatial resolution (

We are proposing a new method for estimating soil surface water content from thermal inertia distributions retrieved from visible–near infrared (VISNIR)and thermal infrared (TIR) images. A drying experiment was conducted on three fi ne-textured soils while acquiring multispectral VIS-NIR and TIR images. Simultaneous measurements of soil water content and thermal inertia were conducted by the thermogravimetric method and the heat pulse technique, respectively. Direct measurements were used to test the thermal inertia approach proposed by Murray and Verhoef that requires only knowledge of soil porosity and can be easily inverted to derive soil water content from thermal inertia. For the three considered soils, the performance of the Murray and Verhoef model was practically equal to that of the traditional approach based on the direct estimation of thermal conductivity and heat capacity, which requires more detailed information about soil properties. With the aim of simplifying the estimation of thermal inertia from remotely sensed images,a modified Kersten function was proposed in which the normalized thermal inertia is substituted by the normalized apparent thermal inertia. Comparison between the two modifi ed Kersten functions was satisfactory. The proposed approach allowed predictions of the surface soil moisture from apparent thermal inertia distributions with an acceptable level of accuracy for practical purposes (0.028 ≤ RMSE ≤ 0.043 m3 m−3) and therefore it can be considered a simple and effective tool for estimating the spatial and temporal distribution of surface soil moisture from VIS-NIR and TIR remotely sensed data.

In the last years, modeling of surface processes - such as water, energy and carbon budgets, as well as vegetation growth- seems to be focused on integrated approaches that combine aspects of hydrology, biology and meteorology into unified analyses. In this context, remotely sensed data often have a core role due to the cross-cutting impact of this novel source of spatially distributed information on all these research areas. However, several applications - such as drought monitoring, yield forecasting and crop management - require spatially detailed products at sub-field scales, which can be obtained only with support of adequately fine resolution remote sensing data (< 100 m). In particular, observations in the visible to the near infrared (VIS/NIR) spectral region can be used to derive biophysical and biochemical properties of the vegetation (i.e., leaf area index and leaf chlorophyll). Complementarily, the thermal infrared (TIR) signal provides valuable information about land surface temperature, which in turn represents an accurate proxy indicator of the subsurface moisture status by means of surface energy budget analysis. Additionally, the strong link between crop water stress and stomatal closure allows inference of crop carbon assimilation using the same tools. In this work, an integrated approach is proposed to model both carbon and water budgets at field scale by means of a joint use of a thermal-based Two Source Energy Budget (TSEB) model and an analytical, Light-Use-Efficiency (LUE) based model of canopy resistance. This suite of models allows integration of information retrieved by both fine and coarse resolution satellites by means of a data fusion procedure. A set of Landsat and MODIS images are used to investigate the suitability of this approach, and the modeled fluxes are compared with observations made by several flux towers in terms of both water and carbon fluxes.

Agricultural water requirement in arid and semi-arid environments represents an important fraction of the total water consumption, suggesting the need of appropriate water management practices to sparingly use the resource. Furthermore the quality and quantity of some crops products, such as grape, is improved under a controlled amount of water stress. The latter is related, on a side to actual evapotranspiration (ET) through water demand, on the other side to plant water content through leaf water potential. Residual energy balance approaches based on remote sensing allow to estimate the spatial distribution of daily actual ET at plant scale, representing an useful tool to detect its spatial variability across different cultivars and even within each parcel. Moreover, the connection between actual ET and leaf water potential is still not well assessed, especially under water stress conditions, even if farmers use leaf water potential to plan irrigation. However residual energy balance methods are based on the hypothesis that storage terms are negligible, at least during the remote sensor overpass. Indeed, energy balance approaches estimate daily actual ET from the instantaneous value at the overpass time using a daily integration method. The paper first verifies this latter assumption using field data acquired by a flux tower on a whole phenological period. Then, the actual ET values measured by eddy covariance tower were analyzed together with water potential measured using a Scholander chamber; the analysis highlights that, under water stress conditions, daily actual ET is inversely linearly related with water potential. These results suggest the possibility to use remote sensing-based ET as support for irrigation management at plot scale.

Soil humidity plays a key-role in hydrological and agricultural processes. In the rainfall-runoff processes the knowledge of its spatial distribution is fundamental to accurately model these phenomena. Furthermore in agronomy and agricultural sciences, assessing the water content of the root zone is required in order to optimize the plant productivity and to improve the irrigation systems management. Despite the importance of this variable the in situ measurements techniques based on Time Domain Reflectometry (TDR) or on the standard thermo-gravimetric methods, are neither cost-effective nor representative of its spatial and temporal variability. Indirect estimations via Earth Observation (EO) images include the triangle method, which shows that Land Surface Temperature (LST) is prevalently controlled by surface and root zone humidity in bare and vegetated soils respectively. The effects of pre-processing techniques correcting for altimetry and seasonality are analyzed by means of shortwave and longwave airborne images acquired on a vineyard during a whole phenological period. The paper also discusses the advantages induced by replacing the absolute temperatures with relative values, that were obtained subtracting the temperatures measured by micrometeorological station or the surface temperature of high thermal inertia surfaces (as small irrigation reservoir) chosen as reference values. The validation with in situ data also highlights that a higher spatial resolution not necessarily imply a higher accuracy.

Soil moisture is difficult to quantify because of its high spatial variability. Consequently, great efforts have been undertaken by the research community to develop practical remote sensing approaches to estimate the spatial distribution of surface soil moisture over large areas and with high spatial detail. Many methodologies have been developed using remote sensing data acquiring information in different parts of the electromagnetic spectrum. Conventional field measurement techniques (including gravimetric and time-domain reflectometry) are point-based, involve on-site operators, are time expensive and, in any case, do not provide exhaustive information on the spatial distribution of soil moisture because it strongly depends on pedology, soil roughness and vegetation cover. The technological development of imaging sensors acquiring in the visible (VIS), near infrared (NIR) and thermal infrared (TIR), renewed the research interest in setting up remote sensed based techniques aimed to retrieve soil water content variability in the soil-plant-atmosphere system (SPA). In this context different approaches have been widely applied at regional scale throughout synthetic indexes based on VIS, NIR and TIR spectral bands. A laboratory experiment has been carried out to verify a physically based model based on the remote estimation of the soil thermal inertia, P, to indirectly retrieve the soil surface water content, θ. The paper shows laboratory retrievals using simultaneously a FLIR A320G thermal camera, a six bands customized TETRACAM MCA II (Multiple Camera Array) multispectral camera working in the VIS/NIR part of the spectrum. Using these two type of sensors a set of VIS/NIR and TIR images were acquired as the main input dataset to retrieve the spatial variability of the thermal inertia values. Moreover, given that the accuracy of the proposed approach strongly depends on the accurate estimation of the soil thermal conductivity, a Decagon Device KD2 PRO thermal analyzer was used to verify the remotely estimate of thermal conductivity. Remotely estimated water contents were validated using the gravimetric method. The considered thermal inertia approach allowed prediction of the spatial distribution of the soil water with a satisfactory level of accuracy.

Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET) and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (soil moisture, advection, air temperature) are affecting plant stress. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moisture conditions can be obtained with a surface energy balance model driven by TIR remote sensing. The Atmosphere-Land Exchange Inverse (ALEXI) model is a multi-sensor TIR approach to ET mapping, coupling a two-source (soil+canopy) land-surface model with an atmospheric boundary layer model in time-differencing mode to routinely and robustly map daily fluxes at continental scales and 5–10 km resolution using thermal band imagery and insolation estimates from geostationary satellites. A related algorithm (DisALEXI), spatially disaggregates ALEXI fluxes down to finer spatial scales using moderate resolution TIR imagery from polar orbiting satellites. An overview of this modeling approach is presented, along with strategies for fusing information from multiple satellite platforms and wavebands to map daily ET down to resolutions of 30 m. The ALEXI/DisALEXI model has potential for global applications by integrating data from multiple geostationary meteorological satellite systems, such as the US Geostationary Operational Environmental Satellites, the European Meteosat satellites, the Chinese Fen-yung 2B series, and the Japanese Geostationary Meteorological Satellites. Work is underway to further evaluate multi-scale ALEXI implementations over the US, Europe and, Africa and other continents with geostationary satellite coverage.

During last two decades the increasing availability of remotely sensed acquisitions in the thermal infrared part of the spectrum has encouraged hydrologist community to develop models and methodologies based on these kind of data. The aim of this paper is to compare three methods developed to assess the actual evapotranspiration spatial distribution by means of remote sensing data. The comparison was focused on the differences between the "single" (SEBAL) and "two" source (TSEB) surface energy balance approaches and the S-SEBI semi-empirical method. The first assumes a semiempirical internal calibration for the sensible heat flux assessment; the second uses a physically based approach in order to assess separately the soil and vegetation fluxes. Finally, the last one is based on the correlation between albedo and surface temperature for evaporative fraction estimations. The models were applied using 7 high resolution images, collected by an airborne platform between June and October 2008, approximately every 3 weeks. The acquired data include multi-spectral images (red, green and near infrared) and thermal infrared images for surface temperature estimation. The study area, located in the south-west cost of Sicily (Italy), is characterised by the presence of typical Mediterranean cultivations: olive, vineyard and citrus. Due to irrigation supplies and rainfall events, the water availability for the crops varies in time and this allowed to perform the comparison in a wide range of the modelled variables. Additionally, the availability of high spatial resolution images allowed the testing of the models performances at field scale despite the high vegetation fragmentation of the study area. The comparison of models performance highlights a good agreements of model estimations, analyzed by means of MAD (Mean Absolute Differences) and MAPD (Mean Absolute Percent Differences) indices, especially in terms of study area averaged fluxes. The analysis in correspondence of various crop fields highlights higher differences for low vegetation coverage and for scarce water availability.

Actual evapotranspiration from typical Mediterranean crops has been assessed in a Sicilian study area by using Surface Energy Balance and Agro-Hydrological models. Both modelling approaches require remotely sensed data to estimate evapotranspiration fluxes in a spatially distributed way. The first approach exploits visible (VIS), near-infrared (NIR) and thermal (TIR) observations to solve the surface energy balance equation. To this end two different schemes have been tested: the two-sources TSEB model, where soil and vegetation components of the surface energy balance are treated separately, and the widely used one-source SEBAL model, where soil and vegetation are considered as a sole source. Actual evapotranspiration estimates by means of the two surface energy balance models have been compared with the results of the Agro-Hydrological model SWAP, applied in a spatially distributed way to simulate one-dimensional water flow in the soil-plant-atmosphere continuum. In this latter model, remote sensing data in the VIS and NIR spectral ranges have been used to infer spatially distributed vegetation parameters needed to set up the upper boundary condition of SWAP. In the comparison presented here, actual evapotranspiration values obtained from the application of the soil water balance model SWAP have been considered as the reference. Considering that the study area is characterized by typical Mediterranean sparse vegetation, i.e. olive, citrus and vineyards, we focused the attention on the main conceptual differences between SEBAL and TSEB. Airborne hyperspectral data acquired during a NERC campaign in 2005 have been used. The results of the investigation evidenced that the remote sensing two-sources approach used in TSEB model describes turbulent and radiative surface fluxes in a more realistic way than the one-source approach.

Daily high spatial resolution assessment of actual evapotranspiration is essential for water management and crop water requirement estimation under stress conditions. The application of energy balance models usually requires satellite observations of radiometric surface temperat ure with high geometrical and temporal resolutions. By now, however, high spatial resolution (~ 100 m) is available with low time fre quency (approximately every two weeks); at the opposite daily acquisition are characterised by poor spatial resolution. The analysis of vegetation index (VI) and land surface temperature (LST) spatial relationship, shows in substance a scale invariant behaviour [1] ; this consideration allows the application of spatial sharpening algorithms of thermal data, by means of a combination of high spatial resolution data in VIS/NIR range with high temporal acquisition on TIR. In this paper, a sharpening algorithm was applied using the thermal bands of MODIS ( MOderate resolution Imaging Spectroradiometer ) and vegetation indices derived by ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer ) sensor; the choice of this sensors is justified by the simultaneous acquisition time. The results of this sharpening process was firstly compared against LST estimation (at the same spatial resolution) by means of the ASTER simultaneous data; then the derived high spatial resolution LST distribution was used in order to investigate the effect of the disaggregation on the outputs of surface energy balance models. The above described application was performed on a Sicilian study area. Keywords: land surface temperature, disaggregation, actual ev apotranspiration, surface energy balance models.