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The standardized precipitation index (SPI) is the most commonly used index for detecting and characterizing meteorological droughts, and it is also extensively used as a proxy variable for soil moisture anomalies (SMA) for the purpose of monitoring agricultural drought in absence of long-term soil moisture observations. However, the potential capability of SPI to warn of the time-lagged soil water deficit—following the well-known "drought cascade" effect—is often overlooked in agricultural drought studies. In this research, a time-lagged correlation analysis is used to evaluate the relationship between the SMA dataset, generated as part of the Global Drought Observatory of the European Union's Copernicus Emergency Management Service, and a set of SPIs derived from the ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts. The possibility to achieve an optimal agreement between SPI and SMA that also preserves the early warning skills of SPI is evaluated. The results suggest that if only the correlation between SPI and SMA is considered, the maximum agreement is usually obtained with a zero lead time (almost 80% of the cases), with SPI-3 representing the best option in about 40% of the grid cells at global scale. By also accounting for the benefits of a positive lead time, short accumulation periods tend to be favored, with SPI-1 being the optimal choice in about one-half of the cases, and 10–20 days of lead time in more than 90% of the grid cells is achieved without any significant reduction in either correlation or skill in drought extreme detection. [ABSTRACT FROM AUTHOR]

Drought events evolve simultaneously in space and time; hence, a proper characterization of an event requires the tracking of its full spatiotemporal evolution. Here we present a generalized algorithm for the tracking of drought events based on a three-dimensional application of the DBSCAN (density-based spatial clustering of applications with noise) clustering approach. The need for a generalized and flexible algorithm is dictated by the absence of a unanimous consensus on the definition of a drought event, which often depends on the target of the study. The proposed methodology introduces a set of six parameters that control both the spatial and the temporal connectivity between cells under drought conditions, also accounting for the local intensity of the drought itself. The capability of the algorithm to adapt to different drought definitions is tested successfully over a study case in Australia in the period 2017–20 using a set of standardized precipitation index (SPI) data derived from the ERA5 precipitation reanalysis. Insights on the possible range of variability of the model parameters, as well as on their effects on the delineation of drought events, are provided for the case of meteorological droughts in order to incentivize further applications of the methodology. [ABSTRACT FROM AUTHOR]

• A 1-km actual ET monthly dataset for the period 1991–2020 is produce for Italy. • An expert-based multiple collocation procedure is used to combine 6 datasets. • The spread on the climatology seems to drive most of the ensemble uncertainty. Accurate estimations of actual evapotranspiration (ET) are key in a variety of water balance applications, but divergent results can be obtained due to the large range of available methodologies. The use of an ensemble approach is a suitable alternative, as it summarizes multiple sources in an optimized strategy. In this study, an expert-based multi-step collocation (MC) approach is tested to merge six ET datasets, with the aim of reconstructing a spatiotemporally-consistent monthly dataset for Italy in the climatological period 1991–2020. The merged products are: three water balance datasets (BIG BANG, LSA SAF, and LISFLOOD), two residual surface energy balance model datasets (SSEBop, and ALEXI), and the MODIS standard ET product. The merged product is analyzed for spatio-temporal consistency and evaluated using flux observations from 11 sites. On average, the merged product has higher accuracy (mean absolute difference = 0.47 ± 0.17 mm/d, relative difference = 27.9 ± 7.5 %) than any single base dataset, and it is characterized by limited bias (mean bias error = -0.17 ± 0.26 mm/d), high correlation (r = 0.83 ± 0.10), and more uniform performance across sites. The merged ET dataset is accompanied by an estimation of the ensemble spread, which highlights large differences in ET estimates in some areas and periods characterized by severe water stress, such as in southern Italy during the summer. This large spread seems to be mostly driven by systematic differences among datasets, which affect the estimation of the reference climatology, suggesting how inter-model spread can have a defining role in further improving the merging strategies. [ABSTRACT FROM AUTHOR]

Application of the two-source energy balance (TSEB) model to satellite data requires the definition of canopy (Tc) and soil (Ts) temperatures for the partitioning of the latent heat flux into transpiration (T) and evaporation (E) components. In this study, we evaluate the possibility of directly separating the satellite land-surface temperature (LST) into soil and canopy components, removing the need to adopt the iterative solution currently used in the TSEB approach. The method exploits contextual information at field scale, under the assumption that the field is homogeneous and characterized by spatially uniform Tc and Ts values. The approach was tested on a set of fields in California with typical woody perennial Mediterranean crops, and it was compared against the outcomes of two other standard versions of TSEB, as well as in-situ flux measurements. Overall, the proposed partitioning approach performs similarly to the standard TSEB models in reproducing instantaneous surface energy fluxes (mean absolute difference, MAD, on the order of 60 W m− 2 for turbulent fluxes), with only a slight tendency to overestimate transpiration. Differences in transpiration are mostly driven by divergences in modelled Tc (MAD between 2 and 3 °C), whereas differences in Ts are more limited (MAD between 1 and 2 °C). The main discrepancies were observed over low canopy coverage conditions (fractional cover lower than 35%), where small changes in Ts resulted in large differences in Tc. Despite this drawback, the results show that the method is a suitable alternative for a more straightforward operational field-scale application of the TSEB under suitable surface conditions. [ABSTRACT FROM AUTHOR]

Hydrological drought is currently underrepresented in global monitoring systems, mainly due the shortage of near real-time estimates of river discharge at the global scale. In this study, the outputs of the Lisflood model are used to define a low-flow drought index, which shows a good correspondence with long-term records of the Global Runoff Data Centre in the period 1980–2014, as well as with verified information from the literature on six major drought events (covering different regions and watershed sizes). In contrast, the near real-time simulation (from 2015 onward) provides temporally inconsistent estimates over about 20% of the modelled cells (mostly over South America and Central Africa), even if reasonable results are obtained over other regions, as confirmed by intercomparison with the operational outcomes of the European Drought Observatory for the 2018 drought. In spite of the highlighted limitations, valuable information for operational drought monitoring can be retrieved from these simulations. [ABSTRACT FROM AUTHOR]

• A harmonization procedure of GEOV2 and MODIS fAPAR data is introduced. • Systematic overestimations of GEOV2 anomalies compared to MODIS are removed. • Temporal consistent standardized anomalies can be used in drought studies. The temporal consistency of the fAPAR GEOV2 full time series (constituted by data derived from SPOT-VGT1/2 and PROBA-V) is analyzed against the single-sensor MODIS dataset, with a particular focus on the most recent fAPAR anomalies (z -scores) produced from PROBA-V in the period 2014–2017. The intercomparison highlights a systematic overestimation of GEOV2 fAPAR z -scores when compared to MODIS fAPAR, likely related to the observed positive bias (over 90% of the domain) in the PROBA-V vs. SPOT-VGT1/2 relationship. A simple two-step harmonization procedure has been proposed to remove this discrepancy, based on two separate linear corrections of SPOT-VGT1/2 (2001–2013) and PROBA-V (2014–2017) data with respect to MODIS, followed by a time lag correction. The harmonized GEOV2 time series preserves the overall dynamic of fAPAR, while removing the sensor bias and improving the consistency with MODIS data. The fAPAR anomalies from the harmonized GEOV2 time series provide unbiased estimates of z -scores that are overall well correlated (R = 0.55 ± 0.25) with the MODIS fAPAR anomalies. [ABSTRACT FROM AUTHOR]

ABSTRACT The Lisflood rainfall-runoff model was forced by the E- OBS () gridded meteorological dataset in order to produce 5-km resolution maps of root zone soil moisture for the period 1951-2013, which were used to evaluate the presence of significant trends in soil water deficit over Europe. The results of the trend analysis highlighted a clear subdivision of the European domain into two sub-regions: a southwest portion with mostly positive trends (drying of the soil) and a northeast part with decreasing soil water deficit. Overall, about 19% of the domain was affected by a significant linear trend according to the Mann-Kendall test and the false discovery rate ( FDR) procedure ( p = 0.05), with about 11.6% having a negative (wetting) and 7.6% a positive (drying) slope. A spatial cluster analysis identified 11 major areas (with extension > 10 000 km2) affected by significant trends, including the Ebro and Garonne basins (for positive slopes) and the Dniester watershed (for negative trends). A final analysis at national and sub-national levels highlights that most of the observed trends are also significant when aggregated at a regional ( NUTS-1) spatial scale, detecting the administrative areas where water management planes are most likely affected. As drying and wetting processes are occurring mainly in the already driest and wettest sub-areas of the modelling domain, respectively, the obtained results suggest a further polarization of the water deficit in Europe. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Summary In the context of evaluating the occurrence of drought events over Europe, soil moisture maps provide an invaluable resource to quantify the effects of rainfall deficits on vegetated lands. Spatially distributed models represent one of the main options, alongside satellite remote sensing, to successfully monitor this quantity over large areas in a cost effective way. This work has the double aim of: (i) intercomparing three soil moisture outputs obtained by different land-surface models (LISFOOD, CLM and TESSEL) through long (at least 6 years of data between 2001 and 2011) in-situ measured datastreams, and (ii) quantifying the added value of combining the estimates of these three models by means of a simple ensemble approach. Generally, the three models return similar soil moisture anomalies over most of Europe, with few notable exceptions during summer in Mediterranean regions. The comparison with in-situ data suggests no substantial differences among the models, with LISFLOOD slightly outperforming the other two in terms of correlation as also supported by a pairwise comparison. The combined soil moisture anomalies obtained via the ensemble-mean approach are characterized by an increase of both the correlation and the accuracy in retrieving extreme events compared to the single models; however, the number of observed extreme events actually captured by the ensemble model does not increase significantly if compared to the single models. Overall, the ensemble model results are skillful, with an all site average skill score of about 0.4. [ABSTRACT FROM AUTHOR]

Highlights: [•] A globally applicable ET MODIS/Lansat data fusion procedure was tested. [•] Differences in the performance on irrigated and rainfed fields were analyzed. [•] Accuracy of ET map is reduced when field size is smaller than MODIS pixel size. [ABSTRACT FROM AUTHOR]

Abstract: Application of FAO-56 methodology for the assessment of reference evapotranspiration, ET0, 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 ET0 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 ET0 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 0.4mmd−1, with a relative error of 12%. Similar to other applications of the same procedure, the MAK approach showed a slightly underestimation of ET0 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 0.05mmd−1. Analysis of monthly, seasonal and yearly ET0 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. [Copyright &y& Elsevier]

Abstract: 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. [Copyright &y& Elsevier]

Abstract: The two-source energy balance (TSEB) model uses remotely sensed maps of land–surface temperature (LST) along with local air temperature estimates at a nominal blending height to model heat and water fluxes across a landscape, partitioned between dual sources of canopy and soil. For operational implementation of TSEB, however, it is often difficult to obtain representative air temperature data that are compatible with the LST retrievals, which may themselves have residual errors due to atmospheric and emissivity corrections. To address this issue, two different strategies in applying the TSEB model without requiring local air temperature data were tested over a typical Mediterranean agricultural area using a set of high-resolution multispectral airborne remote sensing images. Alleviating the need for accurate local air temperature data as input, these two approaches estimate the surface-to-air temperature gradient that drives the sensible heat flux by directly exploiting the information available in the image. The two approaches include: 1) a scene-based internal calibration (TSEB-IC) procedure that estimates air temperature over a well-watered and fully vegetated pixel in the LST image, and 2) a disaggregation scheme (DisALEXI) that uses air temperature estimates from a time-differential coupled TSEB-atmospheric boundary layer model of atmosphere–land exchange (ALEXI). A comparison of the air temperatures modeled by TSEB-IC and DisALEXI with in situ weather station observations shows good agreement, with average differences on the order of 1K, comparable with the uncertainties in the remotely sensed surface temperature maps. Surface fluxes estimated by each method agree well with micro-meteorological measurements acquired over an olive orchard within the aircraft imaging domain. In comparison with fluxes generated with TSEB using local measurements of air temperature, instantaneous fluxes from these alternative methods show good spatial agreement, with differences of less than 10Wm−2 across the domain. Finally, a sensitivity analysis of the three models, performed by introducing artificial errors into the model inputs, demonstrates that the DisALEXI and TSEB-IC approaches are relatively insensitive to errors in absolute surface temperature calibration, while turbulent fluxes from TSEB applications using local air temperature measurements show sensitivity of approximately 30Wm−2 per degree temperature perturbation. This highlights the value of both internal calibration and time-differential estimation of the surface-to-air temperature gradient within a surface energy balance framework. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

Summary: The capability to accurately monitor and describe daily evapotranspiration (ET) in a cost effective manner is generally attributed to hydrological models. However, continuous solution of energy and water balance provides precise estimations only when a detailed knowledge of sub-surface characteristics is available. On the other hand, residual surface energy balance models, based on remote observation of land surface temperature, are characterised by sufficient accuracy, but their applicability is limited by the lack of high frequency and high resolution thermal data. A compromise between these two methodologies is represented by the use of data assimilation scheme to include sparse remote estimates of surface fluxes into continuous modelling. This paper aims to test the combined use of coupled energy/water budget model and data assimilation schemes to assess daily evapotranspiration at field scale in a typical Mediterranean environment characterised by sparse olive trees. The continuous model was applied at hourly scale using remote multispectral images in the short-wave and standard meteorological information. The model was validated by means of contextual micro-meteorological information adopting the best available parameterisation (including root zone depth). The validation suggests an accuracy of about 35Wm−2 for the hourly turbulent fluxes and of about 0.3–0.4mmd−1 for the daily ET. Successively, two data assimilation schemes based on the ensemble version of the Kalman filter were tested under the hypothesis of absence of information about the root zone depth. The application of a dual state-parameter filter (2EnKF) allows to obtain results very close to the ‘optimal’ ones independently from the value adopted as initial of root zone depth. Moreover, these results were obtained both by assimilating synthetic ‘perfect’ observations and ‘real’ remotely-derived estimations of latent heat flux. The methodology, which combines a coupled energy/water budget model and a dual state-parameter assimilation scheme, seems to be suitable to provide precise estimations of daily ET also when information on root zone depth are absent or not enough accurate. [ABSTRACT FROM AUTHOR]

We are proposing a new method for estimating soil surface water content from thermal inertia distributions retrieved from visible-near infrared (VIS-NIR) and thermal infrared (TIR) images. A drying experiment was conducted on three fine-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 modified 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. [ABSTRACT FROM AUTHOR]

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. [Copyright &y& Elsevier]

European forests are an important source for timber production, human welfare, income, protection and biodiversity. During the last two decades, Europe has experienced a number of droughts which have been exceptional within the last 500 years, both in terms of duration and intensity. These droughts seem to leave remarkable imprints on the mortality dynamics of European forests. However, systematic observations on tree decline, with emphasis on a single species, has been scarce so far so that our understanding of mortality dynamics and drought occurrence is still limited at a continental scale.Here, we make use of the ICP Forest crown defoliation dataset, permitting us to retrospectively monitor tree mortality for all major conifers, major broadleaves, as well as a pooled dataset of minor tree species in Europe. In total, we analysed more than three million observations gathered during the last 25 years and employed a high‐resolution drought index which can assess soil moisture anomaly based on a hydrological water‐balance and runoff model.We found overall and species‐specific increasing trends in mortality rates, accompanied by decreasing soil moisture. A generalized linear mixed model identified a previous‐year soil moisture anomaly as the most important driver of mortality patterns in conifers, but the response was not uniform across the numerous analysed plots.We conclude that mortality patterns in European forests are currently reaching a concerning upward trend which could be further accelerated by global change‐type droughts in the near future. [ABSTRACT FROM AUTHOR]

Highlights: [•] Hurwitz–Lerch Zeta discrete distributions were tested to model inter-arrival times. [•] 3-Parameter Lerch-series well reproduces inter-arrival times in Mediterranean sites. [•] 2-Parameter Polylog-series could be used to reconstruct dry spells frequency. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the statistical analysis of inter-arrival time series of rainfall events for Mediterranean and Italian Sub-Alpine areas. The study uses the discrete probability polylog-series distribution as well as applied a simple qualitative trend analysis to some quantiles of inter-arrival times and to the average extent of rain clusters. The study reveals that the duration of dry periods for both environments increased.